Update version number for poetry (#3637)

### What problem does this PR solve?



### Type of change

- [x] Refactoring

.github/ISSUE_TEMPLATE/bug_report.yml

@@ -15,16 +15,16 @@ body:
     value: "Please provide the following information to help us understand the issue."
 - type: input
   attributes:
-    label: Branch name
-    description: Enter the name of the branch where you encountered the issue.
-    placeholder: e.g., main
+    label: RAGFlow workspace code commit ID
+    description: Enter the commit ID associated with the issue.
+    placeholder: e.g., 26d3480e
   validations:
     required: true
 - type: input
   attributes:
-    label: Commit ID
-    description: Enter the commit ID associated with the issue.
-    placeholder: e.g., c3b2a1
+    label: RAGFlow image version
+    description: Enter the image version(shown in RAGFlow UI, `System` page) associated with the issue.
+    placeholder: e.g., 26d3480e(v0.13.0~174)
   validations:
     required: true
 - type: textarea

.github/workflows/tests.yml

@@ -0,0 +1,130 @@
+name: tests
+
+on:
+  push:
+    branches:
+      - 'main'
+      - '*.*.*'
+    paths-ignore:
+      - 'docs/**'
+      - '*.md'
+      - '*.mdx'
+  pull_request:
+    types: [ opened, synchronize, reopened, labeled ]
+    paths-ignore:
+      - 'docs/**'
+      - '*.md'
+      - '*.mdx'
+
+# https://docs.github.com/en/actions/using-jobs/using-concurrency
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  ragflow_tests:
+    name: ragflow_tests
+    # https://docs.github.com/en/actions/using-jobs/using-conditions-to-control-job-execution
+    # https://github.com/orgs/community/discussions/26261
+    if: ${{ github.event_name != 'pull_request' || contains(github.event.pull_request.labels.*.name, 'ci') }}
+    runs-on: [ "self-hosted", "debug" ]
+    steps:
+      # https://github.com/hmarr/debug-action
+      #- uses: hmarr/debug-action@v2
+
+      - name: Show PR labels
+        run: |
+          echo "Workflow triggered by ${{ github.event_name }}"
+          if [[ ${{ github.event_name }} == 'pull_request' ]]; then
+            echo "PR labels: ${{ join(github.event.pull_request.labels.*.name, ', ') }}"
+          fi
+
+      - name: Ensure workspace ownership
+        run: echo "chown -R $USER $GITHUB_WORKSPACE" && sudo chown -R $USER $GITHUB_WORKSPACE
+
+      # https://github.com/actions/checkout/issues/1781
+      - name: Check out code
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+          fetch-tags: true
+
+      - name: Build ragflow:dev-slim
+        run: |
+          RUNNER_WORKSPACE_PREFIX=${RUNNER_WORKSPACE_PREFIX:-$HOME}
+          cp -r ${RUNNER_WORKSPACE_PREFIX}/huggingface.co ${RUNNER_WORKSPACE_PREFIX}/nltk_data ${RUNNER_WORKSPACE_PREFIX}/libssl*.deb  ${RUNNER_WORKSPACE_PREFIX}/tika-server*.jar* ${RUNNER_WORKSPACE_PREFIX}/chrome* ${RUNNER_WORKSPACE_PREFIX}/cl100k_base.tiktoken .
+          sudo docker pull ubuntu:22.04
+          sudo docker build --progress=plain -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
+
+      - name: Build ragflow:dev
+        run: |
+          sudo docker build --progress=plain -f Dockerfile -t infiniflow/ragflow:dev .
+
+      - name: Start ragflow:dev-slim
+        run: |
+          sudo docker compose -f docker/docker-compose.yml up -d
+
+      - name: Stop ragflow:dev-slim
+        if: always()  # always run this step even if previous steps failed
+        run: |
+          sudo docker compose -f docker/docker-compose.yml down -v
+
+      - name: Start ragflow:dev
+        run: |
+          echo "RAGFLOW_IMAGE=infiniflow/ragflow:dev" >> docker/.env
+          sudo docker compose -f docker/docker-compose.yml up -d
+
+      - name: Run sdk tests against Elasticsearch
+        run: |
+          export http_proxy=""; export https_proxy=""; export no_proxy=""; export HTTP_PROXY=""; export HTTPS_PROXY=""; export NO_PROXY=""
+          export HOST_ADDRESS=http://host.docker.internal:9380
+          until sudo docker exec ragflow-server curl -s --connect-timeout 5 ${HOST_ADDRESS} > /dev/null; do
+            echo "Waiting for service to be available..."
+            sleep 5
+          done
+          cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_sdk_api && pytest -s --tb=short get_email.py t_dataset.py t_chat.py t_session.py t_document.py t_chunk.py
+
+      - name: Run frontend api tests against Elasticsearch
+        run: |
+          export http_proxy=""; export https_proxy=""; export no_proxy=""; export HTTP_PROXY=""; export HTTPS_PROXY=""; export NO_PROXY=""
+          export HOST_ADDRESS=http://host.docker.internal:9380
+          until sudo docker exec ragflow-server curl -s --connect-timeout 5 ${HOST_ADDRESS} > /dev/null; do
+            echo "Waiting for service to be available..."
+            sleep 5
+          done
+          cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_frontend_api && pytest -s --tb=short get_email.py test_dataset.py 
+          
+
+      - name: Stop ragflow:dev
+        if: always()  # always run this step even if previous steps failed
+        run: |
+          sudo docker compose -f docker/docker-compose.yml down -v
+
+      - name: Start ragflow:dev
+        run: |
+          sudo DOC_ENGINE=infinity docker compose -f docker/docker-compose.yml up -d
+
+      - name: Run sdk tests against Infinity
+        run: |
+          export http_proxy=""; export https_proxy=""; export no_proxy=""; export HTTP_PROXY=""; export HTTPS_PROXY=""; export NO_PROXY=""
+          export HOST_ADDRESS=http://host.docker.internal:9380
+          until sudo docker exec ragflow-server curl -s --connect-timeout 5 ${HOST_ADDRESS} > /dev/null; do
+            echo "Waiting for service to be available..."
+            sleep 5
+          done
+          cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_sdk_api && pytest -s --tb=short get_email.py t_dataset.py t_chat.py t_session.py t_document.py t_chunk.py
+
+      - name: Run frontend api tests against Infinity
+        run: |
+          export http_proxy=""; export https_proxy=""; export no_proxy=""; export HTTP_PROXY=""; export HTTPS_PROXY=""; export NO_PROXY=""
+          export HOST_ADDRESS=http://host.docker.internal:9380
+          until sudo docker exec ragflow-server curl -s --connect-timeout 5 ${HOST_ADDRESS} > /dev/null; do
+            echo "Waiting for service to be available..."
+            sleep 5
+          done
+          cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_frontend_api && pytest -s --tb=short get_email.py test_dataset.py
+
+      - name: Stop ragflow:dev
+        if: always()  # always run this step even if previous steps failed
+        run: |
+          sudo DOC_ENGINE=infinity docker compose -f docker/docker-compose.yml down -v

Dockerfile

@@ -1,6 +1,7 @@
 # base stage
-FROM ubuntu:24.04 AS base
+FROM ubuntu:22.04 AS base
 USER root
+SHELL ["/bin/bash", "-c"]
 
 ENV LIGHTEN=0
 
@@ -9,26 +10,48 @@ WORKDIR /ragflow
 RUN rm -f /etc/apt/apt.conf.d/docker-clean \
     && echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache
 
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+RUN --mount=type=cache,id=ragflow_base_apt,target=/var/cache/apt,sharing=locked \
     apt update && apt-get --no-install-recommends install -y ca-certificates
 
-# if you located in China, you can use tsinghua mirror to speed up apt
-RUN  sed -i 's|http://archive.ubuntu.com|https://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list.d/ubuntu.sources
+# Setup apt mirror site
+RUN sed -i 's|http://archive.ubuntu.com|https://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list
 
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
-    apt update && apt install -y curl libpython3-dev nginx libglib2.0-0 libglx-mesa0 pkg-config libicu-dev libgdiplus \
-    && rm -rf /var/lib/apt/lists/* \
-    && curl -sSL https://install.python-poetry.org | python3 -
+RUN --mount=type=cache,id=ragflow_base_apt,target=/var/cache/apt,sharing=locked \
+    apt update && DEBIAN_FRONTEND=noninteractive apt install -y curl libpython3-dev nginx libglib2.0-0 libglx-mesa0 pkg-config libicu-dev libgdiplus default-jdk python3-pip pipx \
+    libatk-bridge2.0-0 libgtk-4-1 libnss3 xdg-utils unzip libgbm-dev wget git \
+    && rm -rf /var/lib/apt/lists/*
 
-RUN curl -o libssl1.deb http://archive.ubuntu.com/ubuntu/pool/main/o/openssl1.0/libssl1.0.0_1.0.2n-1ubuntu5_amd64.deb && dpkg -i libssl1.deb && rm -f libssl1.deb
+RUN pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && pip3 config set global.trusted-host "pypi.tuna.tsinghua.edu.cn mirrors.pku.edu.cn" && pip3 config set global.extra-index-url "https://mirrors.pku.edu.cn/pypi/web/simple" \
+    && pipx install poetry \
+    && /root/.local/bin/poetry self add poetry-plugin-pypi-mirror
+
+# https://forum.aspose.com/t/aspose-slides-for-net-no-usable-version-of-libssl-found-with-linux-server/271344/13
+# aspose-slides on linux/arm64 is unavailable
+RUN --mount=type=bind,source=libssl1.1_1.1.1f-1ubuntu2_amd64.deb,target=/root/libssl1.1_1.1.1f-1ubuntu2_amd64.deb \
+    --mount=type=bind,source=libssl1.1_1.1.1f-1ubuntu2_arm64.deb,target=/root/libssl1.1_1.1.1f-1ubuntu2_arm64.deb \
+    if [ "$(uname -m)" = "x86_64" ]; then \
+        dpkg -i /root/libssl1.1_1.1.1f-1ubuntu2_amd64.deb; \
+    elif [ "$(uname -m)" = "aarch64" ]; then \
+        dpkg -i /root/libssl1.1_1.1.1f-1ubuntu2_arm64.deb; \
+    fi
 
 ENV PYTHONDONTWRITEBYTECODE=1 DOTNET_SYSTEM_GLOBALIZATION_INVARIANT=1
-
+ENV PATH=/root/.local/bin:$PATH
 # Configure Poetry
 ENV POETRY_NO_INTERACTION=1
 ENV POETRY_VIRTUALENVS_IN_PROJECT=true
 ENV POETRY_VIRTUALENVS_CREATE=true
 ENV POETRY_REQUESTS_TIMEOUT=15
+ENV POETRY_PYPI_MIRROR_URL=https://pypi.tuna.tsinghua.edu.cn/simple/
+
+# nodejs 12.22 on Ubuntu 22.04 is too old
+RUN --mount=type=cache,id=ragflow_base_apt,target=/var/cache/apt,sharing=locked \
+    curl -fsSL https://deb.nodesource.com/setup_20.x | bash - && \
+    apt purge -y nodejs npm && \
+    apt autoremove && \
+    apt update && \
+    apt install -y nodejs cargo && \
+    rm -rf /var/lib/apt/lists/*
 
 # builder stage
 FROM base AS builder
@@ -36,21 +59,38 @@ USER root
 
 WORKDIR /ragflow
 
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
-    apt update && apt install -y nodejs npm cargo && \
-    rm -rf /var/lib/apt/lists/*
+COPY .git /ragflow/.git
+
+RUN current_commit=$(git rev-parse --short HEAD); \
+    last_tag=$(git describe --tags --abbrev=0); \
+    commit_count=$(git rev-list --count "$last_tag..HEAD"); \
+    version_info=""; \
+    if [ "$commit_count" -eq 0 ]; then \
+        version_info=$last_tag; \
+    else \
+        version_info="$current_commit($last_tag~$commit_count)"; \
+    fi; \
+    if [ "$LIGHTEN" == "1" ]; then \
+        version_info="$version_info slim"; \
+    else \
+        version_info="$version_info full"; \
+    fi; \
+    echo "RAGFlow version: $version_info"; \
+    echo $version_info > /ragflow/VERSION
 
 COPY web web
-RUN cd web && npm i --force && npm run build
+COPY docs docs
+RUN --mount=type=cache,id=ragflow_builder_npm,target=/root/.npm,sharing=locked \
+    cd web && npm install --force && npm run build
 
 # install dependencies from poetry.lock file
 COPY pyproject.toml poetry.toml poetry.lock ./
 
-RUN --mount=type=cache,target=/root/.cache/pypoetry,sharing=locked \
-    if [ "$LIGHTEN" -eq 0 ]; then \
-        /root/.local/bin/poetry install --sync --no-cache --no-root --with=full; \
+RUN --mount=type=cache,id=ragflow_builder_poetry,target=/root/.cache/pypoetry,sharing=locked \
+    if [ "$LIGHTEN" == "1" ]; then \
+        poetry install --no-root; \
     else \
-        /root/.local/bin/poetry install --sync --no-cache --no-root; \
+        poetry install --no-root --with=full; \
     fi
 
 # production stage
@@ -59,9 +99,11 @@ USER root
 
 WORKDIR /ragflow
 
+COPY --from=builder /ragflow/VERSION /ragflow/VERSION
+
 # Install python packages' dependencies
 # cv2 requires libGL.so.1
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+RUN --mount=type=cache,id=ragflow_production_apt,target=/var/cache/apt,sharing=locked \
     apt update && apt install -y --no-install-recommends nginx libgl1 vim less && \
     rm -rf /var/lib/apt/lists/*
 
@@ -89,19 +131,39 @@ RUN --mount=type=bind,source=huggingface.co,target=/huggingface.co \
         /huggingface.co/maidalun1020/bce-reranker-base_v1 \
         | tar -xf - --strip-components=2 -C /root/.ragflow
 
+# Copy nltk data downloaded via download_deps.py
+COPY nltk_data /root/nltk_data
+
+# https://github.com/chrismattmann/tika-python
+# This is the only way to run python-tika without internet access. Without this set, the default is to check the tika version and pull latest every time from Apache.
+COPY tika-server-standard-3.0.0.jar /ragflow/tika-server-standard.jar
+COPY tika-server-standard-3.0.0.jar.md5 /ragflow/tika-server-standard.jar.md5
+ENV TIKA_SERVER_JAR="file:///ragflow/tika-server-standard.jar"
+
+# Copy cl100k_base
+COPY cl100k_base.tiktoken /ragflow/9b5ad71b2ce5302211f9c61530b329a4922fc6a4
+
+# Add dependencies of selenium
+RUN --mount=type=bind,source=chrome-linux64-121-0-6167-85,target=/chrome-linux64.zip \
+    unzip /chrome-linux64.zip && \
+    mv chrome-linux64 /opt/chrome && \
+    ln -s /opt/chrome/chrome /usr/local/bin/
+RUN --mount=type=bind,source=chromedriver-linux64-121-0-6167-85,target=/chromedriver-linux64.zip \
+    unzip -j /chromedriver-linux64.zip chromedriver-linux64/chromedriver && \
+    mv chromedriver /usr/local/bin/ && \
+    rm -f /usr/bin/google-chrome
+
 # Copy compiled web pages
 COPY --from=builder /ragflow/web/dist /ragflow/web/dist
 
 # Copy Python environment and packages
 ENV VIRTUAL_ENV=/ragflow/.venv
 COPY --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
-ENV PATH="${VIRTUAL_ENV}/bin:/root/.local/bin:${PATH}"
-
-# Download nltk data
-RUN python3 -m nltk.downloader wordnet punkt punkt_tab
+ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"
 
 ENV PYTHONPATH=/ragflow/
 
+COPY docker/service_conf.yaml.template ./conf/service_conf.yaml.template
 COPY docker/entrypoint.sh ./entrypoint.sh
 RUN chmod +x ./entrypoint.sh
 

Dockerfile.scratch.oc9

@@ -26,6 +26,7 @@ RUN dnf install -y nginx
 
 ADD ./web ./web
 ADD ./api ./api
+ADD ./docs ./docs
 ADD ./conf ./conf
 ADD ./deepdoc ./deepdoc
 ADD ./rag ./rag
@@ -37,7 +38,7 @@ RUN dnf install -y openmpi openmpi-devel python3-openmpi
 ENV C_INCLUDE_PATH /usr/include/openmpi-x86_64:$C_INCLUDE_PATH
 ENV LD_LIBRARY_PATH /usr/lib64/openmpi/lib:$LD_LIBRARY_PATH
 RUN rm /root/miniconda3/envs/py11/compiler_compat/ld
-RUN cd ./web && npm i --force && npm run build
+RUN cd ./web && npm i && npm run build
 RUN conda run -n py11 pip install $(grep -ivE "mpi4py" ./requirements.txt) # without mpi4py==3.1.5
 RUN conda run -n py11 pip install redis
 
@@ -52,6 +53,7 @@ RUN conda run -n py11 python -m nltk.downloader wordnet
 ENV PYTHONPATH=/ragflow/
 ENV HF_ENDPOINT=https://hf-mirror.com
 
+COPY docker/service_conf.yaml.template ./conf/service_conf.yaml.template
 ADD docker/entrypoint.sh ./entrypoint.sh
 RUN chmod +x ./entrypoint.sh
 

Dockerfile.slim

@@ -1,6 +1,7 @@
 # base stage
-FROM ubuntu:24.04 AS base
+FROM ubuntu:22.04 AS base
 USER root
+SHELL ["/bin/bash", "-c"]
 
 ENV LIGHTEN=1
 
@@ -9,26 +10,48 @@ WORKDIR /ragflow
 RUN rm -f /etc/apt/apt.conf.d/docker-clean \
     && echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache
 
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+RUN --mount=type=cache,id=ragflow_base_apt,target=/var/cache/apt,sharing=locked \
     apt update && apt-get --no-install-recommends install -y ca-certificates
 
-# if you located in China, you can use tsinghua mirror to speed up apt
-RUN  sed -i 's|http://archive.ubuntu.com|https://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list.d/ubuntu.sources
+# Setup apt mirror site
+RUN sed -i 's|http://archive.ubuntu.com|https://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list
 
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
-    apt update && apt install -y curl libpython3-dev nginx libglib2.0-0 libglx-mesa0 pkg-config libicu-dev libgdiplus \
-    && rm -rf /var/lib/apt/lists/* \
-    && curl -sSL https://install.python-poetry.org | python3 -
+RUN --mount=type=cache,id=ragflow_base_apt,target=/var/cache/apt,sharing=locked \
+    apt update && DEBIAN_FRONTEND=noninteractive apt install -y curl libpython3-dev nginx libglib2.0-0 libglx-mesa0 pkg-config libicu-dev libgdiplus default-jdk python3-pip pipx \
+    libatk-bridge2.0-0 libgtk-4-1 libnss3 xdg-utils unzip libgbm-dev wget git \
+    && rm -rf /var/lib/apt/lists/*
 
-RUN curl -o libssl1.deb http://archive.ubuntu.com/ubuntu/pool/main/o/openssl1.0/libssl1.0.0_1.0.2n-1ubuntu5_amd64.deb && dpkg -i libssl1.deb && rm -f libssl1.deb
+RUN pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && pip3 config set global.trusted-host "pypi.tuna.tsinghua.edu.cn mirrors.pku.edu.cn" && pip3 config set global.extra-index-url "https://mirrors.pku.edu.cn/pypi/web/simple" \
+    && pipx install poetry \
+    && /root/.local/bin/poetry self add poetry-plugin-pypi-mirror
+
+# https://forum.aspose.com/t/aspose-slides-for-net-no-usable-version-of-libssl-found-with-linux-server/271344/13
+# aspose-slides on linux/arm64 is unavailable
+RUN --mount=type=bind,source=libssl1.1_1.1.1f-1ubuntu2_amd64.deb,target=/root/libssl1.1_1.1.1f-1ubuntu2_amd64.deb \
+    --mount=type=bind,source=libssl1.1_1.1.1f-1ubuntu2_arm64.deb,target=/root/libssl1.1_1.1.1f-1ubuntu2_arm64.deb \
+    if [ "$(uname -m)" = "x86_64" ]; then \
+        dpkg -i /root/libssl1.1_1.1.1f-1ubuntu2_amd64.deb; \
+    elif [ "$(uname -m)" = "aarch64" ]; then \
+        dpkg -i /root/libssl1.1_1.1.1f-1ubuntu2_arm64.deb; \
+    fi
 
 ENV PYTHONDONTWRITEBYTECODE=1 DOTNET_SYSTEM_GLOBALIZATION_INVARIANT=1
-
+ENV PATH=/root/.local/bin:$PATH
 # Configure Poetry
 ENV POETRY_NO_INTERACTION=1
 ENV POETRY_VIRTUALENVS_IN_PROJECT=true
 ENV POETRY_VIRTUALENVS_CREATE=true
 ENV POETRY_REQUESTS_TIMEOUT=15
+ENV POETRY_PYPI_MIRROR_URL=https://pypi.tuna.tsinghua.edu.cn/simple/
+
+# nodejs 12.22 on Ubuntu 22.04 is too old
+RUN --mount=type=cache,id=ragflow_base_apt,target=/var/cache/apt,sharing=locked \
+    curl -fsSL https://deb.nodesource.com/setup_20.x | bash - && \
+    apt purge -y nodejs npm && \
+    apt autoremove && \
+    apt update && \
+    apt install -y nodejs cargo && \
+    rm -rf /var/lib/apt/lists/*
 
 # builder stage
 FROM base AS builder
@@ -36,21 +59,38 @@ USER root
 
 WORKDIR /ragflow
 
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
-    apt update && apt install -y nodejs npm cargo && \
-    rm -rf /var/lib/apt/lists/*
+COPY .git /ragflow/.git
+
+RUN current_commit=$(git rev-parse --short HEAD); \
+    last_tag=$(git describe --tags --abbrev=0); \
+    commit_count=$(git rev-list --count "$last_tag..HEAD"); \
+    version_info=""; \
+    if [ "$commit_count" -eq 0 ]; then \
+        version_info=$last_tag; \
+    else \
+        version_info="$current_commit($last_tag~$commit_count)"; \
+    fi; \
+    if [ "$LIGHTEN" == "1" ]; then \
+        version_info="$version_info slim"; \
+    else \
+        version_info="$version_info full"; \
+    fi; \
+    echo "RAGFlow version: $version_info"; \
+    echo $version_info > /ragflow/VERSION
 
 COPY web web
-RUN cd web && npm i --force && npm run build
+COPY docs docs
+RUN --mount=type=cache,id=ragflow_builder_npm,target=/root/.npm,sharing=locked \
+    cd web && npm install --force && npm run build
 
 # install dependencies from poetry.lock file
 COPY pyproject.toml poetry.toml poetry.lock ./
 
-RUN --mount=type=cache,target=/root/.cache/pypoetry,sharing=locked \
-    if [ "$LIGHTEN" -eq 0 ]; then \
-        /root/.local/bin/poetry install --sync --no-cache --no-root --with=full; \
+RUN --mount=type=cache,id=ragflow_builder_poetry,target=/root/.cache/pypoetry,sharing=locked \
+    if [ "$LIGHTEN" == "1" ]; then \
+        poetry install --no-root; \
     else \
-        /root/.local/bin/poetry install --sync --no-cache --no-root; \
+        poetry install --no-root --with=full; \
     fi
 
 # production stage
@@ -59,9 +99,11 @@ USER root
 
 WORKDIR /ragflow
 
+COPY --from=builder /ragflow/VERSION /ragflow/VERSION
+
 # Install python packages' dependencies
 # cv2 requires libGL.so.1
-RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
+RUN --mount=type=cache,id=ragflow_production_apt,target=/var/cache/apt,sharing=locked \
     apt update && apt install -y --no-install-recommends nginx libgl1 vim less && \
     rm -rf /var/lib/apt/lists/*
 
@@ -82,19 +124,39 @@ RUN --mount=type=bind,source=huggingface.co,target=/huggingface.co \
         /huggingface.co/InfiniFlow/deepdoc \
         | tar -xf - --strip-components=3 -C /ragflow/rag/res/deepdoc
 
+# Copy nltk data downloaded via download_deps.py
+COPY nltk_data /root/nltk_data
+
+# https://github.com/chrismattmann/tika-python
+# This is the only way to run python-tika without internet access. Without this set, the default is to check the tika version and pull latest every time from Apache.
+COPY tika-server-standard-3.0.0.jar /ragflow/tika-server-standard.jar
+COPY tika-server-standard-3.0.0.jar.md5 /ragflow/tika-server-standard.jar.md5
+ENV TIKA_SERVER_JAR="file:///ragflow/tika-server-standard.jar"
+
+# Copy cl100k_base
+COPY cl100k_base.tiktoken /ragflow/9b5ad71b2ce5302211f9c61530b329a4922fc6a4
+
+# Add dependencies of selenium
+RUN --mount=type=bind,source=chrome-linux64-121-0-6167-85,target=/chrome-linux64.zip \
+    unzip /chrome-linux64.zip && \
+    mv chrome-linux64 /opt/chrome && \
+    ln -s /opt/chrome/chrome /usr/local/bin/
+RUN --mount=type=bind,source=chromedriver-linux64-121-0-6167-85,target=/chromedriver-linux64.zip \
+    unzip -j /chromedriver-linux64.zip chromedriver-linux64/chromedriver && \
+    mv chromedriver /usr/local/bin/ && \
+    rm -f /usr/bin/google-chrome
+
 # Copy compiled web pages
 COPY --from=builder /ragflow/web/dist /ragflow/web/dist
 
 # Copy Python environment and packages
 ENV VIRTUAL_ENV=/ragflow/.venv
 COPY --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
-ENV PATH="${VIRTUAL_ENV}/bin:/root/.local/bin:${PATH}"
-
-# Download nltk data
-RUN python3 -m nltk.downloader wordnet punkt punkt_tab
+ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"
 
 ENV PYTHONPATH=/ragflow/
 
+COPY docker/service_conf.yaml.template ./conf/service_conf.yaml.template
 COPY docker/entrypoint.sh ./entrypoint.sh
 RUN chmod +x ./entrypoint.sh
 

README.md

@@ -8,20 +8,26 @@
   <a href="./README.md">English</a> |
   <a href="./README_zh.md">简体中文</a> |
   <a href="./README_ja.md">日本語</a> |
-  <a href="./README_ko.md">한국어</a>
+  <a href="./README_ko.md">한국어</a> |
+  <a href="./README_id.md">Bahasa Indonesia</a>
 </p>
 
 <p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://demo.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
+    </a>
     <a href="https://github.com/infiniflow/ragflow/releases/latest">
         <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
     </a>
-    <a href="https://demo.ragflow.io" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99"></a>
-    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
-        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.12.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.12.0"></a>
     <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
-    <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
-  </a>
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
 </p>
 
 <h4 align="center">
@@ -34,7 +40,7 @@
 
 <details open>
 <summary></b>📕 Table of Contents</b></summary>
-  
+
 - 💡 [What is RAGFlow?](#-what-is-ragflow)
 - 🎮 [Demo](#-demo)
 - 📌 [Latest Updates](#-latest-updates)
@@ -42,8 +48,8 @@
 - 🔎 [System Architecture](#-system-architecture)
 - 🎬 [Get Started](#-get-started)
 - 🔧 [Configurations](#-configurations)
-- 🪛 [Build the docker image without embedding models](#-build-the-docker-image-without-embedding-models)
-- 🪚 [Build the docker image including embedding models](#-build-the-docker-image-including-embedding-models)
+- 🔧 [Build a docker image without embedding models](#-build-a-docker-image-without-embedding-models)
+- 🔧 [Build a docker image including embedding models](#-build-a-docker-image-including-embedding-models)
 - 🔨 [Launch service from source for development](#-launch-service-from-source-for-development)
 - 📚 [Documentation](#-documentation)
 - 📜 [Roadmap](#-roadmap)
@@ -54,35 +60,41 @@
 
 ## 💡 What is RAGFlow?
 
-[RAGFlow](https://ragflow.io/) is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
+[RAGFlow](https://ragflow.io/) is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document
+understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models)
+to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted
+data.
 
 ## 🎮 Demo
 
 Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
 <div align="center" style="margin-top:20px;margin-bottom:20px;">
 <img src="https://github.com/infiniflow/ragflow/assets/7248/2f6baa3e-1092-4f11-866d-36f6a9d075e5" width="1200"/>
-<img src="https://github.com/infiniflow/ragflow/assets/12318111/b083d173-dadc-4ea9-bdeb-180d7df514eb" width="1200"/>
+<img src="https://github.com/user-attachments/assets/504bbbf1-c9f7-4d83-8cc5-e9cb63c26db6" width="1200"/>
 </div>
 
-
 ## 🔥 Latest Updates
 
-- 2024-09-29 Optimizes multi-round conversations.
+- 2024-11-22 Adds more variables to Agent.
+- 2024-11-01 Adds keyword extraction and related question generation to the parsed chunks to improve the accuracy of retrieval.
 - 2024-09-13 Adds search mode for knowledge base Q&A.
-- 2024-09-09 Adds a medical consultant agent template.
 - 2024-08-22 Support text to SQL statements through RAG.
 - 2024-08-02 Supports GraphRAG inspired by [graphrag](https://github.com/microsoft/graphrag) and mind map.
-- 2024-07-23 Supports audio file parsing.
-- 2024-07-08 Supports workflow based on [Graph](./agent/README.md).
-- 2024-06-27 Supports Markdown and Docx in the Q&A parsing method, extracting images from Docx files, extracting tables from Markdown files.
-- 2024-05-23 Supports [RAPTOR](https://arxiv.org/html/2401.18059v1) for better text retrieval.
 
+## 🎉 Stay Tuned
+
+⭐️ Star our repository to stay up-to-date with exciting new features and improvements! Get instant notifications for new
+releases! 🌟
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
 
 ## 🌟 Key Features
 
 ### 🍭 **"Quality in, quality out"**
 
-- [Deep document understanding](./deepdoc/README.md)-based knowledge extraction from unstructured data with complicated formats.
+- [Deep document understanding](./deepdoc/README.md)-based knowledge extraction from unstructured data with complicated
+  formats.
 - Finds "needle in a data haystack" of literally unlimited tokens.
 
 ### 🍱 **Template-based chunking**
@@ -120,7 +132,8 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
 - RAM >= 16 GB
 - Disk >= 50 GB
 - Docker >= 24.0.0 & Docker Compose >= v2.26.1
-  > If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).
+  > If you have not installed Docker on your local machine (Windows, Mac, or Linux),
+  see [Install Docker Engine](https://docs.docker.com/engine/install/).
 
 ### 🚀 Start up the server
 
@@ -139,7 +152,8 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
    > $ sudo sysctl -w vm.max_map_count=262144
    > ```
    >
-   > This change will be reset after a system reboot. To ensure your change remains permanent, add or update the `vm.max_map_count` value in **/etc/sysctl.conf** accordingly:
+   > This change will be reset after a system reboot. To ensure your change remains permanent, add or update the
+   `vm.max_map_count` value in **/etc/sysctl.conf** accordingly:
    >
    > ```bash
    > vm.max_map_count=262144
@@ -152,14 +166,28 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
    ```
 
 3. Build the pre-built Docker images and start up the server:
-   > Running the following commands automatically downloads the *dev* version RAGFlow Docker image. To download and run a specified Docker version, update `RAGFLOW_IMAGE` in **docker/.env** to the intended version, for example `RAGFLOW_IMAGE=infiniflow/ragflow:v0.12.0`, before running the following commands.
+
+   > The command below downloads the dev version Docker image for RAGFlow slim (`dev-slim`). Note that RAGFlow slim
+   Docker images do not include embedding models or Python libraries and hence are approximately 1GB in size.
 
    ```bash
    $ cd ragflow/docker
-   $ docker compose up -d
+   $ docker compose -f docker-compose.yml up -d
    ```
 
-   > The core image is about 9 GB in size and may take a while to load.
+   > - To download a RAGFlow slim Docker image of a specific version, update the `RAGFLOW_IMAGE` variable in *
+       *docker/.env** to your desired version. For example, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`. After
+       making this change, rerun the command above to initiate the download.
+   > - To download the dev version of RAGFlow Docker image *including* embedding models and Python libraries, update the
+       `RAGFLOW_IMAGE` variable in **docker/.env** to `RAGFLOW_IMAGE=infiniflow/ragflow:dev`. After making this change,
+       rerun the command above to initiate the download.
+   > - To download a specific version of RAGFlow Docker image *including* embedding models and Python libraries, update
+       the `RAGFLOW_IMAGE` variable in **docker/.env** to your desired version. For example,
+       `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`. After making this change, rerun the command above to initiate the
+       download.
+
+   > **NOTE:** A RAGFlow Docker image that includes embedding models and Python libraries is approximately 9GB in size
+   and may take significantly longer time to load.
 
 4. Check the server status after having the server up and running:
 
@@ -170,23 +198,26 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
    _The following output confirms a successful launch of the system:_
 
    ```bash
-        ____   ___    ______ ______ __               
-       / __ \ /   |  / ____// ____// /____  _      __
-      / /_/ // /| | / / __ / /_   / // __ \| | /| / /
-     / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ / 
-    /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/  
- 
+
+         ____   ___    ______ ______ __               
+        / __ \ /   |  / ____// ____// /____  _      __
+       / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+      / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ / 
+     /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/ 
 
     * Running on all addresses (0.0.0.0)
     * Running on http://127.0.0.1:9380
     * Running on http://x.x.x.x:9380
     INFO:werkzeug:Press CTRL+C to quit
    ```
-   > If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a `network abnormal` error because, at that moment, your RAGFlow may not be fully initialized.  
+   > If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a `network anormal`
+   error because, at that moment, your RAGFlow may not be fully initialized.
 
 5. In your web browser, enter the IP address of your server and log in to RAGFlow.
-   > With the default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default HTTP serving port `80` can be omitted when using the default configurations.
-6. In [service_conf.yaml](./docker/service_conf.yaml), select the desired LLM factory in `user_default_llm` and update the `API_KEY` field with the corresponding API key.
+   > With the default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default
+   HTTP serving port `80` can be omitted when using the default configurations.
+6. In [service_conf.yaml.template](./docker/service_conf.yaml.template), select the desired LLM factory in `user_default_llm` and update
+   the `API_KEY` field with the corresponding API key.
 
    > See [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) for more information.
 
@@ -196,104 +227,126 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
 
 When it comes to system configurations, you will need to manage the following files:
 
-- [.env](./docker/.env): Keeps the fundamental setups for the system, such as `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, and `MINIO_PASSWORD`.
-- [service_conf.yaml](./docker/service_conf.yaml): Configures the back-end services.
+- [.env](./docker/.env): Keeps the fundamental setups for the system, such as `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, and
+  `MINIO_PASSWORD`.
+- [service_conf.yaml.template](./docker/service_conf.yaml.template): Configures the back-end services. The environment variables in this file will be automatically populated when the Docker container starts. Any environment variables set within the Docker container will be available for use, allowing you to customize service behavior based on the deployment environment.
 - [docker-compose.yml](./docker/docker-compose.yml): The system relies on [docker-compose.yml](./docker/docker-compose.yml) to start up.
 
-You must ensure that changes to the [.env](./docker/.env) file are in line with what are in the [service_conf.yaml](./docker/service_conf.yaml) file.
+> The [./docker/README](./docker/README.md) file provides a detailed description of the environment settings and service
+> configurations which can be used as `${ENV_VARS}` in the [service_conf.yaml.template](./docker/service_conf.yaml.template) file.
 
-> The [./docker/README](./docker/README.md) file provides a detailed description of the environment settings and service configurations, and you are REQUIRED to ensure that all environment settings listed in the [./docker/README](./docker/README.md) file are aligned with the corresponding configurations in the [service_conf.yaml](./docker/service_conf.yaml) file.
-
-To update the default HTTP serving port (80), go to [docker-compose.yml](./docker/docker-compose.yml) and change `80:80` to `<YOUR_SERVING_PORT>:80`.
+To update the default HTTP serving port (80), go to [docker-compose.yml](./docker/docker-compose.yml) and change `80:80`
+to `<YOUR_SERVING_PORT>:80`.
 
 Updates to the above configurations require a reboot of all containers to take effect:
 
 > ```bash
-> $ docker-compose -f docker/docker-compose.yml up -d
+> $ docker compose -f docker/docker-compose.yml up -d
 > ```
 
-## 🪛 Build the Docker image without embedding models
+### Switch doc engine from Elasticsearch to Infinity
+
+RAGFlow uses Elasticsearch by default for storing full text and vectors. To switch to [Infinity](https://github.com/infiniflow/infinity/), follow these steps:
+
+1. Stop all running containers:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+2. Set `DOC_ENGINE` in **docker/.env** to `infinity`.
+
+3. Start the containers:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml up -d
+   ```
+
+> [!WARNING] 
+> Switching to Infinity on a Linux/arm64 machine is not yet officially supported.
+
+## 🔧 Build a Docker image without embedding models
 
 This image is approximately 1 GB in size and relies on external LLM and embedding services.
 
 ```bash
 git clone https://github.com/infiniflow/ragflow.git
 cd ragflow/
-pip3 install huggingface-hub
+pip3 install huggingface-hub nltk
 python3 download_deps.py
 docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
 ```
 
-## 🪚 Build the Docker image including embedding models
+## 🔧 Build a Docker image including embedding models
 
-This image is approximately 9 GB in size. As it includes embedding models, it relies on external LLM services only.  
+This image is approximately 9 GB in size. As it includes embedding models, it relies on external LLM services only.
 
 ```bash
 git clone https://github.com/infiniflow/ragflow.git
 cd ragflow/
-pip3 install huggingface-hub
+pip3 install huggingface-hub nltk
 python3 download_deps.py
 docker build -f Dockerfile -t infiniflow/ragflow:dev .
 ```
 
 ## 🔨 Launch service from source for development
 
-1. Install Poetry, or skip this step if it is already installed:  
+1. Install Poetry, or skip this step if it is already installed:
    ```bash
    curl -sSL https://install.python-poetry.org | python3 -
    ```
 
-2. Clone the source code and install Python dependencies:  
+2. Clone the source code and install Python dependencies:
    ```bash
    git clone https://github.com/infiniflow/ragflow.git
    cd ragflow/
    export POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true
-   ~/.local/bin/poetry install --sync --no-root # install RAGFlow dependent python modules
+   ~/.local/bin/poetry install --sync --no-root --with=full # install RAGFlow dependent python modules
    ```
 
-3. Launch the dependent services (MinIO, Elasticsearch, Redis, and MySQL) using Docker Compose:  
+3. Launch the dependent services (MinIO, Elasticsearch, Redis, and MySQL) using Docker Compose:
    ```bash
    docker compose -f docker/docker-compose-base.yml up -d
    ```
 
-   Add the following line to `/etc/hosts` to resolve all hosts specified in **docker/service_conf.yaml** to `127.0.0.1`:  
+   Add the following line to `/etc/hosts` to resolve all hosts specified in **docker/.env** to `127.0.0.1`:
    ```
-   127.0.0.1       es01 mysql minio redis
+   127.0.0.1       es01 infinity mysql minio redis
    ```  
-   In **docker/service_conf.yaml**, update mysql port to `5455` and es port to `1200`, as specified in **docker/.env**.
+   In **docker/service_conf.yaml.template**, update mysql port to `5455` and es port to `1200`, as specified in **docker/.env**.
+
+4. If you cannot access HuggingFace, set the `HF_ENDPOINT` environment variable to use a mirror site:
 
-4. If you cannot access HuggingFace, set the `HF_ENDPOINT` environment variable to use a mirror site:  
- 
    ```bash
    export HF_ENDPOINT=https://hf-mirror.com
    ```
 
-5. Launch backend service:  
+5. Launch backend service:
    ```bash
    source .venv/bin/activate
    export PYTHONPATH=$(pwd)
    bash docker/launch_backend_service.sh
    ```
 
-6. Install frontend dependencies:  
+6. Install frontend dependencies:
    ```bash
    cd web
    npm install --force
    ```  
 7. Configure frontend to update `proxy.target` in **.umirc.ts** to `http://127.0.0.1:9380`:
-8. Launch frontend service:  
+8. Launch frontend service:
    ```bash
    npm run dev 
    ```  
 
-   _The following output confirms a successful launch of the system:_  
+   _The following output confirms a successful launch of the system:_
 
    ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
 
 ## 📚 Documentation
 
 - [Quickstart](https://ragflow.io/docs/dev/)
-- [User guide](https://ragflow.io/docs/dev/category/user-guides)
+- [User guide](https://ragflow.io/docs/dev/category/guides)
 - [References](https://ragflow.io/docs/dev/category/references)
 - [FAQ](https://ragflow.io/docs/dev/faq)
 
@@ -309,4 +362,5 @@ See the [RAGFlow Roadmap 2024](https://github.com/infiniflow/ragflow/issues/162)
 
 ## 🙌 Contributing
 
-RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our [Contribution Guidelines](./CONTRIBUTING.md) first.
+RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community.
+If you would like to be a part, review our [Contribution Guidelines](./CONTRIBUTING.md) first.

README_id.md

@@ -0,0 +1,341 @@
+<div align="center">
+<a href="https://demo.ragflow.io/">
+<img src="web/src/assets/logo-with-text.png" width="520" alt="Logo ragflow">
+</a>
+</div>
+
+<p align="center">
+  <a href="./README.md">English</a> |
+  <a href="./README_zh.md">简体中文</a> |
+  <a href="./README_ja.md">日本語</a> |
+  <a href="./README_ko.md">한국어</a> |
+  <a href="./README_id.md">Bahasa Indonesia</a>
+</p>
+
+<p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="Ikuti di X (Twitter)">
+    </a>
+    <a href="https://demo.ragflow.io" target="_blank">
+        <img alt="Lencana Daring" src="https://img.shields.io/badge/Online-Demo-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/releases/latest">
+        <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Rilis%20Terbaru" alt="Rilis Terbaru">
+    </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/Lisensi-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="Lisensi">
+    </a>
+</p>
+
+<h4 align="center">
+  <a href="https://ragflow.io/docs/dev/">Dokumentasi</a> |
+  <a href="https://github.com/infiniflow/ragflow/issues/162">Peta Jalan</a> |
+  <a href="https://twitter.com/infiniflowai">Twitter</a> |
+  <a href="https://discord.gg/4XxujFgUN7">Discord</a> |
+  <a href="https://demo.ragflow.io">Demo</a>
+</h4>
+
+<details open>
+<summary></b>📕 Daftar Isi</b></summary>
+
+- 💡 [Apa Itu RAGFlow?](#-apa-itu-ragflow)
+- 🎮 [Demo](#-demo)
+- 📌 [Pembaruan Terbaru](#-pembaruan-terbaru)
+- 🌟 [Fitur Utama](#-fitur-utama)
+- 🔎 [Arsitektur Sistem](#-arsitektur-sistem)
+- 🎬 [Mulai](#-mulai)
+- 🔧 [Konfigurasi](#-konfigurasi)
+- 🔧 [Membangun Image Docker tanpa Model Embedding](#-membangun-image-docker-tanpa-model-embedding)
+- 🔧 [Membangun Image Docker dengan Model Embedding](#-membangun-image-docker-dengan-model-embedding)
+- 🔨 [Meluncurkan aplikasi dari Sumber untuk Pengembangan](#-meluncurkan-aplikasi-dari-sumber-untuk-pengembangan)
+- 📚 [Dokumentasi](#-dokumentasi)
+- 📜 [Peta Jalan](#-peta-jalan)
+- 🏄 [Komunitas](#-komunitas)
+- 🙌 [Kontribusi](#-kontribusi)
+
+</details>
+
+## 💡 Apa Itu RAGFlow?
+
+[RAGFlow](https://ragflow.io/) adalah mesin RAG (Retrieval-Augmented Generation) open-source berbasis pemahaman dokumen yang mendalam. Platform ini menyediakan alur kerja RAG yang efisien untuk bisnis dengan berbagai skala, menggabungkan LLM (Large Language Models) untuk menyediakan kemampuan tanya-jawab yang benar dan didukung oleh referensi dari data terstruktur kompleks.
+
+## 🎮 Demo
+
+Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/infiniflow/ragflow/assets/7248/2f6baa3e-1092-4f11-866d-36f6a9d075e5" width="1200"/>
+<img src="https://github.com/user-attachments/assets/504bbbf1-c9f7-4d83-8cc5-e9cb63c26db6" width="1200"/>
+</div>
+
+## 🔥 Pembaruan Terbaru
+
+- 22-11-2024 Peningkatan definisi dan penggunaan variabel di Agen.
+- 2024-11-01: Penambahan ekstraksi kata kunci dan pembuatan pertanyaan terkait untuk meningkatkan akurasi pengambilan.
+- 2024-09-13: Penambahan mode pencarian untuk Q&A basis pengetahuan.
+- 2024-08-22: Dukungan untuk teks ke pernyataan SQL melalui RAG.
+- 2024-08-02: Dukungan GraphRAG yang terinspirasi oleh [graphrag](https://github.com/microsoft/graphrag) dan mind map.
+
+## 🎉 Tetap Terkini
+
+⭐️ Star repositori kami untuk tetap mendapat informasi tentang fitur baru dan peningkatan menarik! 🌟
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
+## 🌟 Fitur Utama
+
+### 🍭 **"Kualitas Masuk, Kualitas Keluar"**
+
+- Ekstraksi pengetahuan berbasis pemahaman dokumen mendalam dari data tidak terstruktur dengan format yang rumit.
+- Menemukan "jarum di tumpukan data" dengan token yang hampir tidak terbatas.
+
+### 🍱 **Pemotongan Berbasis Template**
+
+- Cerdas dan dapat dijelaskan.
+- Banyak pilihan template yang tersedia.
+
+### 🌱 **Referensi yang Didasarkan pada Data untuk Mengurangi Hallusinasi**
+
+- Visualisasi pemotongan teks memungkinkan intervensi manusia.
+- Tampilan cepat referensi kunci dan referensi yang dapat dilacak untuk mendukung jawaban yang didasarkan pada fakta.
+
+### 🍔 **Kompatibilitas dengan Sumber Data Heterogen**
+
+- Mendukung Word, slide, excel, txt, gambar, salinan hasil scan, data terstruktur, halaman web, dan banyak lagi.
+
+### 🛀 **Alur Kerja RAG yang Otomatis dan Mudah**
+
+- Orkestrasi RAG yang ramping untuk bisnis kecil dan besar.
+- LLM yang dapat dikonfigurasi serta model embedding.
+- Peringkat ulang berpasangan dengan beberapa pengambilan ulang.
+- API intuitif untuk integrasi yang mudah dengan bisnis.
+
+## 🔎 Arsitektur Sistem
+
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/infiniflow/ragflow/assets/12318111/d6ac5664-c237-4200-a7c2-a4a00691b485" width="1000"/>
+</div>
+
+## 🎬 Mulai
+
+### 📝 Prasyarat
+
+- CPU >= 4 inti
+- RAM >= 16 GB
+- Disk >= 50 GB
+- Docker >= 24.0.0 & Docker Compose >= v2.26.1
+
+### 🚀 Menjalankan Server
+
+1. Pastikan `vm.max_map_count` >= 262144:
+
+   > Untuk memeriksa nilai `vm.max_map_count`:
+   >
+   > ```bash
+   > $ sysctl vm.max_map_count
+   > ```
+   >
+   > Jika nilainya kurang dari 262144, setel ulang `vm.max_map_count` ke setidaknya 262144:
+   >
+   > ```bash
+   > # Dalam contoh ini, kita atur menjadi 262144:
+   > $ sudo sysctl -w vm.max_map_count=262144
+   > ```
+   >
+   > Perubahan ini akan hilang setelah sistem direboot. Untuk membuat perubahan ini permanen, tambahkan atau perbarui nilai
+   `vm.max_map_count` di **/etc/sysctl.conf**:
+   >
+   > ```bash
+   > vm.max_map_count=262144
+   > ```
+
+2. Clone repositori:
+
+   ```bash
+   $ git clone https://github.com/infiniflow/ragflow.git
+   ```
+
+3. Bangun image Docker pre-built dan jalankan server:
+
+   > Perintah di bawah ini akan mengunduh versi dev dari Docker image RAGFlow slim (`dev-slim`). Image RAGFlow slim
+   tidak termasuk model embedding atau library Python dan berukuran sekitar 1GB.
+
+   ```bash
+   $ cd ragflow/docker
+   $ docker compose -f docker-compose.yml up -d
+   ```
+
+   > - Untuk mengunduh versi tertentu dari image Docker RAGFlow slim, perbarui variabel `RAGFlow_IMAGE` di *
+       *docker/.env** sesuai dengan versi yang diinginkan. Misalnya, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`.
+       Setelah mengubah ini, jalankan ulang perintah di atas untuk memulai unduhan.
+   > - Untuk mengunduh versi dev dari image Docker RAGFlow *termasuk* model embedding dan library Python, perbarui
+       variabel `RAGFlow_IMAGE` di **docker/.env** menjadi `RAGFLOW_IMAGE=infiniflow/ragflow:dev`. Setelah mengubah ini,
+       jalankan ulang perintah di atas untuk memulai unduhan.
+   > - Untuk mengunduh versi tertentu dari image Docker RAGFlow *termasuk* model embedding dan library Python, perbarui
+       variabel `RAGFlow_IMAGE` di **docker/.env** sesuai dengan versi yang diinginkan. Misalnya,
+       `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`. Setelah mengubah ini, jalankan ulang perintah di atas untuk memulai unduhan.
+
+   > **CATATAN:** Image Docker RAGFlow yang mencakup model embedding dan library Python berukuran sekitar 9GB
+   dan mungkin memerlukan waktu lebih lama untuk dimuat.
+
+4. Periksa status server setelah server aktif dan berjalan:
+
+   ```bash
+   $ docker logs -f ragflow-server
+   ```
+
+   _Output berikut menandakan bahwa sistem berhasil diluncurkan:_
+
+   ```bash
+
+         ____   ___    ______ ______ __               
+        / __ \ /   |  / ____// ____// /____  _      __
+       / /_/ // /| | / / __ / /_   / // __ \| | /| / /
+      / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ / 
+     /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/ 
+
+    * Running on all addresses (0.0.0.0)
+    * Running on http://127.0.0.1:9380
+    * Running on http://x.x.x.x:9380
+    INFO:werkzeug:Press CTRL+C to quit
+   ```
+   > Jika Anda melewatkan langkah ini dan langsung login ke RAGFlow, browser Anda mungkin menampilkan error `network anormal`
+   karena RAGFlow mungkin belum sepenuhnya siap.
+
+5. Buka browser web Anda, masukkan alamat IP server Anda, dan login ke RAGFlow.
+   > Dengan pengaturan default, Anda hanya perlu memasukkan `http://IP_DEVICE_ANDA` (**tanpa** nomor port) karena 
+   port HTTP default `80` bisa dihilangkan saat menggunakan konfigurasi default.
+6. Dalam [service_conf.yaml](./docker/service_conf.yaml), pilih LLM factory yang diinginkan di `user_default_llm` dan perbarui
+   bidang `API_KEY` dengan kunci API yang sesuai.
+
+   > Lihat [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) untuk informasi lebih lanjut.
+
+   _Sistem telah siap digunakan!_
+
+## 🔧 Konfigurasi
+
+Untuk konfigurasi sistem, Anda perlu mengelola file-file berikut:
+
+- [.env](./docker/.env): Menyimpan pengaturan dasar sistem, seperti `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, dan
+  `MINIO_PASSWORD`.
+- [service_conf.yaml](./docker/service_conf.yaml): Mengonfigurasi aplikasi backend.
+- [docker-compose.yml](./docker/docker-compose.yml): Sistem ini bergantung pada [docker-compose.yml](./docker/docker-compose.yml) untuk memulai.
+
+Anda harus memastikan bahwa perubahan pada file [.env](./docker/.env) sesuai dengan yang ada di file [service_conf.yaml](./docker/service_conf.yaml).
+
+> File [./docker/README](./docker/README.md) menyediakan penjelasan detail tentang pengaturan lingkungan dan konfigurasi aplikasi,
+> dan Anda DIWAJIBKAN memastikan bahwa semua pengaturan lingkungan yang tercantum di
+> [./docker/README](./docker/README.md) selaras dengan konfigurasi yang sesuai di
+> [service_conf.yaml](./docker/service_conf.yaml).
+
+Untuk memperbarui port HTTP default (80), buka [docker-compose.yml](./docker/docker-compose.yml) dan ubah `80:80`
+menjadi `<YOUR_SERVING_PORT>:80`.
+
+Pembaruan konfigurasi ini memerlukan reboot semua kontainer agar efektif:
+
+> ```bash
+> $ docker compose -f docker/docker-compose.yml up -d
+> ```
+
+## 🔧 Membangun Docker Image tanpa Model Embedding
+
+Image ini berukuran sekitar 1 GB dan bergantung pada aplikasi LLM eksternal dan embedding.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+pip3 install huggingface-hub nltk
+python3 download_deps.py
+docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
+```
+
+## 🔧 Membangun Docker Image Termasuk Model Embedding
+
+Image ini berukuran sekitar 9 GB. Karena sudah termasuk model embedding, ia hanya bergantung pada aplikasi LLM eksternal.
+
+```bash
+git clone https://github.com/infiniflow/ragflow.git
+cd ragflow/
+pip3 install huggingface-hub nltk
+python3 download_deps.py
+docker build -f Dockerfile -t infiniflow/ragflow:dev .
+```
+
+## 🔨 Menjalankan Aplikasi dari untuk Pengembangan
+
+1. Instal Poetry, atau lewati langkah ini jika sudah terinstal:
+   ```bash
+   curl -sSL https://install.python-poetry.org | python3 -
+   ```
+
+2. Clone kode sumber dan instal dependensi Python:
+   ```bash
+   git clone https://github.com/infiniflow/ragflow.git
+   cd ragflow/
+   export POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true
+   ~/.local/bin/poetry install --sync --no-root # install modul python RAGFlow
+   ```
+
+3. Jalankan aplikasi yang diperlukan (MinIO, Elasticsearch, Redis, dan MySQL) menggunakan Docker Compose:
+   ```bash
+   docker compose -f docker/docker-compose-base.yml up -d
+   ```
+
+   Tambahkan baris berikut ke `/etc/hosts` untuk memetakan semua host yang ditentukan di **docker/service_conf.yaml** ke `127.0.0.1`:
+   ```
+   127.0.0.1       es01 infinity mysql minio redis
+   ```  
+   Di **docker/service_conf.yaml**, perbarui port mysql ke `5455` dan es ke `1200`, sesuai dengan yang ditentukan di **docker/.env**.
+
+4. Jika Anda tidak dapat mengakses HuggingFace, atur variabel lingkungan `HF_ENDPOINT` untuk menggunakan situs mirror:
+
+   ```bash
+   export HF_ENDPOINT=https://hf-mirror.com
+   ```
+
+5. Jalankan aplikasi backend:
+   ```bash
+   source .venv/bin/activate
+   export PYTHONPATH=$(pwd)
+   bash docker/launch_backend_service.sh
+   ```
+
+6. Instal dependensi frontend:
+   ```bash
+   cd web
+   npm install --force
+   ```  
+7. Konfigurasikan frontend untuk memperbarui `proxy.target` di **.umirc.ts** menjadi `http://127.0.0.1:9380`:
+8. Jalankan aplikasi frontend:
+   ```bash
+   npm run dev 
+   ```  
+
+   _Output berikut menandakan bahwa sistem berhasil diluncurkan:_
+
+   ![](https://github.com/user-attachments/assets/0daf462c-a24d-4496-a66f-92533534e187)
+
+## 📚 Dokumentasi
+
+- [Quickstart](https://ragflow.io/docs/dev/)
+- [Panduan Pengguna](https://ragflow.io/docs/dev/category/guides)
+- [Referensi](https://ragflow.io/docs/dev/category/references)
+- [FAQ](https://ragflow.io/docs/dev/faq)
+
+## 📜 Roadmap
+
+Lihat [Roadmap RAGFlow 2024](https://github.com/infiniflow/ragflow/issues/162)
+
+## 🏄 Komunitas
+
+- [Discord](https://discord.gg/4XxujFgUN7)
+- [Twitter](https://twitter.com/infiniflowai)
+- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
+
+## 🙌 Kontribusi
+
+RAGFlow berkembang melalui kolaborasi open-source. Dalam semangat ini, kami menerima kontribusi dari komunitas.
+Jika Anda ingin berpartisipasi, tinjau terlebih dahulu [Panduan Kontribusi](./CONTRIBUTING.md).

README_ja.md

@@ -8,23 +8,29 @@
   <a href="./README.md">English</a> |
   <a href="./README_zh.md">简体中文</a> |
   <a href="./README_ja.md">日本語</a> |
-  <a href="./README_ko.md">한국어</a>
+  <a href="./README_ko.md">한국어</a> |
+  <a href="./README_id.md">Bahasa Indonesia</a>
 </p>
 
 <p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://demo.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
+    </a>
     <a href="https://github.com/infiniflow/ragflow/releases/latest">
         <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
     </a>
-    <a href="https://demo.ragflow.io" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99"></a>
-    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
-        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.12.0-brightgreen"
-            alt="docker pull infiniflow/ragflow:v0.12.0"></a>
-      <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
-    <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
-  </a>
+    <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
 </p>
 
+
 <h4 align="center">
   <a href="https://ragflow.io/docs/dev/">Document</a> |
   <a href="https://github.com/infiniflow/ragflow/issues/162">Roadmap</a> |
@@ -42,22 +48,23 @@
 デモをお試しください：[https://demo.ragflow.io](https://demo.ragflow.io)。
 <div align="center" style="margin-top:20px;margin-bottom:20px;">
 <img src="https://github.com/infiniflow/ragflow/assets/7248/2f6baa3e-1092-4f11-866d-36f6a9d075e5" width="1200"/>
-<img src="https://github.com/infiniflow/ragflow/assets/12318111/b083d173-dadc-4ea9-bdeb-180d7df514eb" width="1200"/>
+<img src="https://github.com/user-attachments/assets/504bbbf1-c9f7-4d83-8cc5-e9cb63c26db6" width="1200"/>
 </div>
 
 
 ## 🔥 最新情報
 
-- 2024-09-29 マルチラウンドダイアログを最適化。
+- 2024-11-22 エージェントでの変数の定義と使用法を改善しました。
+- 2024-11-01 再現の精度を向上させるために、解析されたチャンクにキーワード抽出と関連質問の生成を追加しました。
 - 2024-09-13 ナレッジベース Q&A の検索モードを追加しました。
-- 2024-09-09 エージェントに医療相談テンプレートを追加しました。
 - 2024-08-22 RAG を介して SQL ステートメントへのテキストをサポートします。
 - 2024-08-02 [graphrag](https://github.com/microsoft/graphrag) からインスピレーションを得た GraphRAG とマインド マップをサポートします。
-- 2024-07-23 音声ファイルの解析をサポートしました。
-- 2024-07-08 [Graph](./agent/README.md) ベースのワークフローをサポート
-- 2024-06-27 Q&A 解析メソッドで Markdown と Docx をサポートし、Docx ファイルから画像を抽出し、Markdown ファイルからテーブルを抽出します。
-- 2024-05-23 より良いテキスト検索のために [RAPTOR](https://arxiv.org/html/2401.18059v1) をサポート。
 
+## 🎉 続きを楽しみに
+⭐️ リポジトリをスター登録して、エキサイティングな新機能やアップデートを最新の状態に保ちましょう！すべての新しいリリースに関する即時通知を受け取れます！ 🌟
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
 
 ## 🌟 主な特徴
 
@@ -134,15 +141,18 @@
 
 3. ビルド済みの Docker イメージをビルドし、サーバーを起動する:
 
+   > 以下のコマンドは、RAGFlow slim（`dev-slim`）の開発版Dockerイメージをダウンロードします。RAGFlow slimのDockerイメージには、埋め込みモデルやPythonライブラリが含まれていないため、サイズは約1GBです。
+
    ```bash
    $ cd ragflow/docker
-   $ chmod +x ./entrypoint.sh
-   $ docker compose up -d
+   $ docker compose -f docker-compose.yml up -d
    ```
 
-   > 上記のコマンドを実行すると、RAGFlowの開発版dockerイメージが自動的にダウンロードされます。 特定のバージョンのDockerイメージをダウンロードして実行したい場合は、docker/.envファイルのRAGFLOW_IMAGE変数を見つけて、対応するバージョンに変更してください。 例えば、`RAGFLOW_IMAGE=infiniflow/ragflow:v0.12.0`として、上記のコマンドを実行してください。
-
-   > コアイメージのサイズは約 9 GB で、ロードに時間がかかる場合があります。
+   > - 特定のバージョンのRAGFlow slim Dockerイメージをダウンロードするには、**docker/.env**内の`RAGFlow_IMAGE`変数を希望のバージョンに更新します。例えば、`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`とします。この変更を行った後、上記のコマンドを再実行してダウンロードを開始してください。
+   > - RAGFlowの埋め込みモデルとPythonライブラリを含む開発版Dockerイメージをダウンロードするには、**docker/.env**内の`RAGFlow_IMAGE`変数を`RAGFLOW_IMAGE=infiniflow/ragflow:dev`に更新します。この変更を行った後、上記のコマンドを再実行してダウンロードを開始してください。
+   > - 特定のバージョンのRAGFlow Dockerイメージ（埋め込みモデルとPythonライブラリを含む）をダウンロードするには、**docker/.env**内の`RAGFlow_IMAGE`変数を希望のバージョンに更新します。例えば、`RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`とします。この変更を行った後、上記のコマンドを再実行してダウンロードを開始してください。  
+   
+   > **NOTE:** 埋め込みモデルとPythonライブラリを含むRAGFlow Dockerイメージのサイズは約9GBであり、読み込みにかなりの時間がかかる場合があります。
 
 4. サーバーを立ち上げた後、サーバーの状態を確認する:
 
@@ -191,29 +201,46 @@
 > すべてのシステム設定のアップデートを有効にするには、システムの再起動が必要です:
 >
 > ```bash
-> $ docker-compose up -d
+> $ docker compose -f docker/docker-compose.yml up -d
 > ```
 
-## 🪛 ソースコードでDockerイメージを作成（埋め込みモデルなし）
+### Elasticsearch から Infinity にドキュメントエンジンを切り替えます
+
+RAGFlow はデフォルトで Elasticsearch を使用して全文とベクトルを保存します。［Infinity］に切り替え（https://github.com/infiniflow/infinity/)、次の手順に従います。
+
+1. 実行中のすべてのコンテナを停止するには：
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+2. **docker/.env** の「DOC _ ENGINE」を「infinity」に設定します。
+
+3. 起動コンテナ：
+   ```bash
+   $ docker compose -f docker/docker-compose.yml up -d
+   ```
+> [!WARNING]  
+> Linux/arm64 マシンでの Infinity への切り替えは正式にサポートされていません。
+
+## 🔧 ソースコードでDockerイメージを作成（埋め込みモデルなし）
 
 この Docker イメージのサイズは約 1GB で、外部の大モデルと埋め込みサービスに依存しています。
 
 ```bash
 git clone https://github.com/infiniflow/ragflow.git
 cd ragflow/
-pip3 install huggingface-hub
+pip3 install huggingface-hub nltk
 python3 download_deps.py
 docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
 ```
 
-## 🪚 ソースコードをコンパイルしたDockerイメージ（埋め込みモデルを含む）
+## 🔧 ソースコードをコンパイルしたDockerイメージ（埋め込みモデルを含む）
 
 この Docker のサイズは約 9GB で、埋め込みモデルを含むため、外部の大モデルサービスのみが必要です。
 
 ```bash
 git clone https://github.com/infiniflow/ragflow.git
 cd ragflow/
-pip3 install huggingface-hub
+pip3 install huggingface-hub nltk
 python3 download_deps.py
 docker build -f Dockerfile -t infiniflow/ragflow:dev .
 ```
@@ -240,7 +267,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
 
    `/etc/hosts` に以下の行を追加して、**docker/service_conf.yaml** に指定されたすべてのホストを `127.0.0.1` に解決します:  
    ```
-   127.0.0.1       es01 mysql minio redis
+   127.0.0.1       es01 infinity mysql minio redis
    ```  
    **docker/service_conf.yaml** で mysql のポートを `5455` に、es のポートを `1200` に更新します（**docker/.env** に指定された通り）.
 
@@ -275,7 +302,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
 ## 📚 ドキュメンテーション
 
 - [Quickstart](https://ragflow.io/docs/dev/)
-- [User guide](https://ragflow.io/docs/dev/category/user-guides)
+- [User guide](https://ragflow.io/docs/dev/category/guides)
 - [References](https://ragflow.io/docs/dev/category/references)
 - [FAQ](https://ragflow.io/docs/dev/faq)
 

README_ko.md

@@ -9,21 +9,28 @@
   <a href="./README_zh.md">简体中文</a> |
   <a href="./README_ja.md">日本語</a> |
   <a href="./README_ko.md">한국어</a> |
+  <a href="./README_id.md">Bahasa Indonesia</a>
 </p>
 
 <p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://demo.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
+    </a>
     <a href="https://github.com/infiniflow/ragflow/releases/latest">
         <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
     </a>
-    <a href="https://demo.ragflow.io" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99"></a>
-    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
-        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.12.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.12.0"></a>
     <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
-    <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
-  </a>
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
 </p>
 
+
 <h4 align="center">
   <a href="https://ragflow.io/docs/dev/">Document</a> |
   <a href="https://github.com/infiniflow/ragflow/issues/162">Roadmap</a> |
@@ -43,30 +50,28 @@
 데모를 [https://demo.ragflow.io](https://demo.ragflow.io)에서 실행해 보세요.
 <div align="center" style="margin-top:20px;margin-bottom:20px;">
 <img src="https://github.com/infiniflow/ragflow/assets/7248/2f6baa3e-1092-4f11-866d-36f6a9d075e5" width="1200"/>
-<img src="https://github.com/infiniflow/ragflow/assets/12318111/b083d173-dadc-4ea9-bdeb-180d7df514eb" width="1200"/>
+<img src="https://github.com/user-attachments/assets/504bbbf1-c9f7-4d83-8cc5-e9cb63c26db6" width="1200"/>
 </div>
 
 
 ## 🔥 업데이트
 
-- 2024-09-29 다단계 대화를 최적화합니다.
+- 2024-11-22 에이전트의 변수 정의 및 사용을 개선했습니다.
+  
+- 2024-11-01 파싱된 청크에 키워드 추출 및 관련 질문 생성을 추가하여 재현율을 향상시킵니다.
   
 - 2024-09-13 지식베이스 Q&A 검색 모드를 추가합니다.
   
-- 2024-09-09 Agent에 의료상담 템플릿을 추가하였습니다.
-  
 - 2024-08-22 RAG를 통해 SQL 문에 텍스트를 지원합니다.
   
 - 2024-08-02: [graphrag](https://github.com/microsoft/graphrag)와 마인드맵에서 영감을 받은 GraphRAG를 지원합니다.
 
-- 2024-07-23: 오디오 파일 분석을 지원합니다.
-
-- 2024-07-08: [Graph](./agent/README.md)를 기반으로 한 워크플로우를 지원합니다.
-
-- 2024-06-27 Q&A 구문 분석 방식에서 Markdown 및 Docx를 지원하고, Docx 파일에서 이미지 추출, Markdown 파일에서 테이블 추출을 지원합니다.
-
-- 2024-05-23: 더 나은 텍스트 검색을 위해 [RAPTOR](https://arxiv.org/html/2401.18059v1)를 지원합니다.
 
+## 🎉 계속 지켜봐 주세요
+⭐️우리의 저장소를 즐겨찾기에 등록하여 흥미로운 새로운 기능과 업데이트를 최신 상태로 유지하세요! 모든 새로운 릴리스에 대한 즉시 알림을 받으세요! 🌟
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
 
 
 ## 🌟 주요 기능
@@ -140,14 +145,18 @@
 
 3. 미리 빌드된 Docker 이미지를 생성하고 서버를 시작하세요:
 
-   > 다음 명령어를 실행하면 *dev* 버전의 RAGFlow Docker 이미지가 자동으로 다운로드됩니다. 특정 Docker 버전을 다운로드하고 실행하려면, **docker/.env** 파일에서 `RAGFLOW_IMAGE`을 원하는 버전으로 업데이트한 후, 예를 들어 `RAGFLOW_IMAGE=infiniflow/ragflow:v0.12.0`로 업데이트 한 뒤, 다음 명령어를 실행하세요.
+   > 아래의 명령은 RAGFlow slim(dev-slim)의 개발 버전 Docker 이미지를 다운로드합니다. RAGFlow slim Docker 이미지에는 임베딩 모델이나 Python 라이브러리가 포함되어 있지 않으므로 크기는 약 1GB입니다.
+
    ```bash
    $ cd ragflow/docker
-   $ chmod +x ./entrypoint.sh
-   $ docker compose up -d
+   $ docker compose -f docker-compose.yml up -d
    ```
    
-   > 기본 이미지는 약 9GB 크기이며 로드하는 데 시간이 걸릴 수 있습니다.
+   > - 특정 버전의 RAGFlow slim Docker 이미지를 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 원하는 버전으로 업데이트하세요. 예를 들어, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`으로 설정합니다. 이 변경을 완료한 후, 위의 명령을 다시 실행하여 다운로드를 시작하세요.
+   > - RAGFlow의 임베딩 모델과 Python 라이브러리를 포함한 개발 버전 Docker 이미지를 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 `RAGFLOW_IMAGE=infiniflow/ragflow:dev`로 업데이트하세요. 이 변경을 완료한 후, 위의 명령을 다시 실행하여 다운로드를 시작하세요.
+   > - 특정 버전의 RAGFlow Docker 이미지를 임베딩 모델과 Python 라이브러리를 포함하여 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 원하는 버전으로 업데이트하세요. 예를 들어, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0` 로 설정합니다. 이 변경을 완료한 후, 위의 명령을 다시 실행하여 다운로드를 시작하세요.  
+   
+   > **NOTE:** 임베딩 모델과 Python 라이브러리를 포함한 RAGFlow Docker 이미지의 크기는 약 9GB이며, 로드하는 데 상당히 오랜 시간이 걸릴 수 있습니다.
 
 
 4. 서버가 시작된 후 서버 상태를 확인하세요:
@@ -170,7 +179,7 @@
     * Running on http://x.x.x.x:9380
     INFO:werkzeug:Press CTRL+C to quit
    ```
-   > 만약 확인 단계를 건너뛰고 바로 RAGFlow에 로그인하면, RAGFlow가 완전히 초기화되지 않았기 때문에 브라우저에서 `network abnormal` 오류가 발생할 수 있습니다.
+   > 만약 확인 단계를 건너뛰고 바로 RAGFlow에 로그인하면, RAGFlow가 완전히 초기화되지 않았기 때문에 브라우저에서 `network anormal` 오류가 발생할 수 있습니다.
 
 5. 웹 브라우저에 서버의 IP 주소를 입력하고 RAGFlow에 로그인하세요.
    > 기본 설정을 사용할 경우, `http://IP_OF_YOUR_MACHINE`만 입력하면 됩니다 (포트 번호는 제외). 기본 HTTP 서비스 포트 `80`은 기본 구성으로 사용할 때 생략할 수 있습니다.
@@ -196,29 +205,44 @@
 > 모든 시스템 구성 업데이트는 적용되기 위해 시스템 재부팅이 필요합니다.
 >
 > ```bash
-> $ docker-compose up -d
+> $ docker compose -f docker/docker-compose.yml up -d
 > ```
 
-## 🪛 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함하지 않음)
+### Elasticsearch 에서 Infinity 로 문서 엔진 전환
+
+RAGFlow 는 기본적으로 Elasticsearch 를 사용하여 전체 텍스트 및 벡터를 저장합니다. [Infinity]로 전환(https://github.com/infiniflow/infinity/), 다음 절차를 따르십시오.
+1. 실행 중인 모든 컨테이너를 중지합니다.
+   ```bash
+   $docker compose-f docker/docker-compose.yml down-v
+   ```
+2. **docker/.env**의 "DOC_ENGINE" 을 "infinity" 로 설정합니다.
+3. 컨테이너 부팅:
+   ```bash
+   $docker compose-f docker/docker-compose.yml up-d
+   ``` 
+> [!WARNING]
+> Linux/arm64 시스템에서 Infinity로 전환하는 것은 공식적으로 지원되지 않습니다.
+ 
+## 🔧 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함하지 않음)
 
 이 Docker 이미지의 크기는 약 1GB이며, 외부 대형 모델과 임베딩 서비스에 의존합니다.
 
 ```bash
 git clone https://github.com/infiniflow/ragflow.git
 cd ragflow/
-pip3 install huggingface-hub
+pip3 install huggingface-hub nltk
 python3 download_deps.py
 docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
 ```
 
-## 🪚 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함)
+## 🔧 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함)
 
 이 Docker의 크기는 약 9GB이며, 이미 임베딩 모델을 포함하고 있으므로 외부 대형 모델 서비스에만 의존하면 됩니다.
 
 ```bash
 git clone https://github.com/infiniflow/ragflow.git
 cd ragflow/
-pip3 install huggingface-hub
+pip3 install huggingface-hub nltk
 python3 download_deps.py
 docker build -f Dockerfile -t infiniflow/ragflow:dev .
 ```
@@ -245,7 +269,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
 
    `/etc/hosts` 에 다음 줄을 추가하여 **docker/service_conf.yaml** 에 지정된 모든 호스트를 `127.0.0.1` 로 해결합니다:  
    ```
-   127.0.0.1       es01 mysql minio redis
+   127.0.0.1       es01 infinity mysql minio redis
    ```  
    **docker/service_conf.yaml** 에서 mysql 포트를 `5455` 로, es 포트를 `1200` 으로 업데이트합니다( **docker/.env** 에 지정된 대로).
 
@@ -280,7 +304,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
 ## 📚 문서
 
 - [Quickstart](https://ragflow.io/docs/dev/)
-- [User guide](https://ragflow.io/docs/dev/category/user-guides)
+- [User guide](https://ragflow.io/docs/dev/category/guides)
 - [References](https://ragflow.io/docs/dev/category/references)
 - [FAQ](https://ragflow.io/docs/dev/faq)
 

README_zh.md

@@ -8,22 +8,29 @@
   <a href="./README.md">English</a> |
   <a href="./README_zh.md">简体中文</a> |
   <a href="./README_ja.md">日本語</a> |
-  <a href="./README_ko.md">한국어</a>
+  <a href="./README_ko.md">한국어</a> |
+  <a href="./README_id.md">Bahasa Indonesia</a>
 </p>
 
 <p align="center">
+    <a href="https://x.com/intent/follow?screen_name=infiniflowai" target="_blank">
+        <img src="https://img.shields.io/twitter/follow/infiniflow?logo=X&color=%20%23f5f5f5" alt="follow on X(Twitter)">
+    </a>
+    <a href="https://demo.ragflow.io" target="_blank">
+        <img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99">
+    </a>
+    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
+        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.14.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.14.0">
+    </a>
     <a href="https://github.com/infiniflow/ragflow/releases/latest">
         <img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
     </a>
-    <a href="https://demo.ragflow.io" target="_blank">
-        <img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99"></a>
-    <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
-        <img src="https://img.shields.io/badge/docker_pull-ragflow:v0.12.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.12.0"></a>
     <a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
-    <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
-  </a>
+        <img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
+    </a>
 </p>
 
+
 <h4 align="center">
   <a href="https://ragflow.io/docs/dev/">Document</a> |
   <a href="https://github.com/infiniflow/ragflow/issues/162">Roadmap</a> |
@@ -41,21 +48,24 @@
 请登录网址 [https://demo.ragflow.io](https://demo.ragflow.io) 试用 demo。
 <div align="center" style="margin-top:20px;margin-bottom:20px;">
 <img src="https://github.com/infiniflow/ragflow/assets/7248/2f6baa3e-1092-4f11-866d-36f6a9d075e5" width="1200"/>
-<img src="https://github.com/infiniflow/ragflow/assets/12318111/b083d173-dadc-4ea9-bdeb-180d7df514eb" width="1200"/>
+<img src="https://github.com/user-attachments/assets/504bbbf1-c9f7-4d83-8cc5-e9cb63c26db6" width="1200"/>
 </div>
 
 
 ## 🔥 近期更新
 
-- 2024-09-29 优化多轮对话.
+- 2024-11-22 完善了 Agent 中的变量定义和使用。
+- 2024-11-01 对解析后的 chunk 加入关键词抽取和相关问题生成以提高召回的准确度。
 - 2024-09-13 增加知识库问答搜索模式。
-- 2024-09-09 在 Agent 中加入医疗问诊模板。
 - 2024-08-22 支持用 RAG 技术实现从自然语言到 SQL 语句的转换。
 - 2024-08-02 支持 GraphRAG 启发于 [graphrag](https://github.com/microsoft/graphrag) 和思维导图。
-- 2024-07-23 支持解析音频文件。
-- 2024-07-08 支持 Agentic RAG: 基于 [Graph](./agent/README.md) 的工作流。
-- 2024-06-27 Q&A 解析方式支持 Markdown 文件和 Docx 文件，支持提取出 Docx 文件中的图片和 Markdown 文件中的表格。
-- 2024-05-23 实现 [RAPTOR](https://arxiv.org/html/2401.18059v1) 提供更好的文本检索。
+
+## 🎉 关注项目
+⭐️点击右上角的 Star 关注RAGFlow，可以获取最新发布的实时通知 !🌟
+<div align="center" style="margin-top:20px;margin-bottom:20px;">
+<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
+</div>
+
 
 ## 🌟 主要功能
 
@@ -132,16 +142,18 @@
 
 3. 进入 **docker** 文件夹，利用提前编译好的 Docker 镜像启动服务器：
 
+   > 运行以下命令会自动下载 dev 版的 RAGFlow slim Docker 镜像（`dev-slim`），该镜像并不包含 embedding 模型以及一些 Python 库，因此镜像大小约 1GB。
+
    ```bash
    $ cd ragflow/docker
-   $ chmod +x ./entrypoint.sh
    $ docker compose -f docker-compose.yml up -d
    ```
 
-   > 请注意，运行上述命令会自动下载 RAGFlow 的开发版本 docker 镜像。如果你想下载并运行特定版本的 docker 镜像，请在 docker/.env 文件中找到 RAGFLOW_IMAGE 变量，将其改为对应版本。例如 `RAGFLOW_IMAGE=infiniflow/ragflow:v0.12.0`，然后运行上述命令。
-
-   > 核心镜像下载大小为 9 GB，可能需要一定时间拉取。请耐心等待。
-
+   > - 如果你想下载并运行特定版本的 RAGFlow slim Docker 镜像，请在 **docker/.env** 文件中找到 `RAGFLOW_IMAGE` 变量，将其改为对应版本。例如 `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0-slim`，然后再运行上述命令。
+   > - 如果您想安装内置 embedding 模型和 Python 库的 dev 版本的 Docker 镜像，需要将 **docker/.env** 文件中的 `RAGFLOW_IMAGE` 变量修改为： `RAGFLOW_IMAGE=infiniflow/ragflow:dev`。
+   > - 如果您想安装内置 embedding 模型和 Python 库的指定版本的 RAGFlow Docker 镜像，需要将 **docker/.env** 文件中的 `RAGFLOW_IMAGE` 变量修改为： `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.0`。修改后，再运行上面的命令。
+   > **注意：** 安装内置 embedding 模型和 Python 库的指定版本的 RAGFlow Docker 镜像大小约 9 GB，可能需要更长时间下载，请耐心等待。
+   
 4. 服务器启动成功后再次确认服务器状态：
 
    ```bash
@@ -162,7 +174,7 @@
     * Running on http://x.x.x.x:9380
     INFO:werkzeug:Press CTRL+C to quit
    ```
-   > 如果您跳过这一步系统确认步骤就登录 RAGFlow，你的浏览器有可能会提示 `network abnormal` 或 `网络异常`，因为 RAGFlow 可能并未完全启动成功。
+   > 如果您跳过这一步系统确认步骤就登录 RAGFlow，你的浏览器有可能会提示 `network anormal` 或 `网络异常`，因为 RAGFlow 可能并未完全启动成功。
 
 5. 在你的浏览器中输入你的服务器对应的 IP 地址并登录 RAGFlow。
    > 上面这个例子中，您只需输入 http://IP_OF_YOUR_MACHINE 即可：未改动过配置则无需输入端口（默认的 HTTP 服务端口 80）。
@@ -194,26 +206,48 @@
 > $ docker compose -f docker-compose.yml up -d
 > ```
 
-## 🪛 源码编译 Docker 镜像（不含 embedding 模型）
+### 把文档引擎从 Elasticsearch 切换成为 Infinity
+
+RAGFlow 默认使用 Elasticsearch 存储文本和向量数据. 如果要切换为 [Infinity](https://github.com/infiniflow/infinity/), 可以按照下面步骤进行:
+
+1. 停止所有容器运行:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml down -v
+   ```
+
+2. 设置 **docker/.env** 目录中的 `DOC_ENGINE` 为 `infinity`.
+
+3. 启动容器:
+
+   ```bash
+   $ docker compose -f docker/docker-compose.yml up -d
+   ```
+
+> [!WARNING] 
+> Infinity 目前官方并未正式支持在 Linux/arm64 架构下的机器上运行.
+
+
+## 🔧 源码编译 Docker 镜像（不含 embedding 模型）
 
 本 Docker 镜像大小约 1 GB 左右并且依赖外部的大模型和 embedding 服务。
 
 ```bash
 git clone https://github.com/infiniflow/ragflow.git
 cd ragflow/
-pip3 install huggingface-hub
+pip3 install huggingface-hub nltk
 python3 download_deps.py
 docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
 ```
 
-## 🪚 源码编译 Docker 镜像（包含 embedding 模型）
+## 🔧 源码编译 Docker 镜像（包含 embedding 模型）
 
 本 Docker 大小约 9 GB 左右。由于已包含 embedding 模型，所以只需依赖外部的大模型服务即可。
 
 ```bash
 git clone https://github.com/infiniflow/ragflow.git
 cd ragflow/
-pip3 install huggingface-hub
+pip3 install huggingface-hub nltk
 python3 download_deps.py
 docker build -f Dockerfile -t infiniflow/ragflow:dev .
 ```
@@ -240,7 +274,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
 
    在 `/etc/hosts` 中添加以下代码，将 **docker/service_conf.yaml** 文件中的所有 host 地址都解析为 `127.0.0.1`：  
    ```
-   127.0.0.1       es01 mysql minio redis
+   127.0.0.1       es01 infinity mysql minio redis
    ```  
    在文件 **docker/service_conf.yaml** 中，对照 **docker/.env** 的配置将 mysql 端口更新为 `5455`，es 端口更新为 `1200`。
 
@@ -275,7 +309,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
 ## 📚 技术文档
 
 - [Quickstart](https://ragflow.io/docs/dev/)
-- [User guide](https://ragflow.io/docs/dev/category/user-guides)
+- [User guide](https://ragflow.io/docs/dev/category/guides)
 - [References](https://ragflow.io/docs/dev/category/references)
 - [FAQ](https://ragflow.io/docs/dev/faq)
 

agent/canvas.py

@@ -13,19 +13,13 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-import importlib
+import logging
 import json
-import traceback
 from abc import ABC
 from copy import deepcopy
 from functools import partial
-
-import pandas as pd
-
 from agent.component import component_class
 from agent.component.base import ComponentBase
-from agent.settings import flow_logger, DEBUG
-
 
 class Canvas(ABC):
     """
@@ -162,8 +156,12 @@ class Canvas(ABC):
             self.components[k]["obj"].reset()
         self._embed_id = ""
 
+    def get_compnent_name(self, cid):
+        for n in self.dsl["graph"]["nodes"]:
+            if cid == n["id"]: return n["data"]["name"]
+        return ""
+
     def run(self, **kwargs):
-        ans = ""
         if self.answer:
             cpn_id = self.answer[0]
             self.answer.pop(0)
@@ -173,10 +171,10 @@ class Canvas(ABC):
                 ans = ComponentBase.be_output(str(e))
             self.path[-1].append(cpn_id)
             if kwargs.get("stream"):
-                assert isinstance(ans, partial)
-                return ans
-            self.history.append(("assistant", ans.to_dict("records")))
-            return ans
+                for an in ans():
+                    yield an
+            else: yield ans
+            return
 
         if not self.path:
             self.components["begin"]["obj"].run(self.history, **kwargs)
@@ -184,6 +182,8 @@ class Canvas(ABC):
 
         self.path.append([])
         ran = -1
+        waiting = []
+        without_dependent_checking = []
 
         def prepare2run(cpns):
             nonlocal ran, ans
@@ -193,18 +193,22 @@ class Canvas(ABC):
                 if cpn.component_name == "Answer":
                     self.answer.append(c)
                 else:
-                    if DEBUG: print("RUN: ", c)
-                    if cpn.component_name == "Generate":
+                    logging.debug(f"Canvas.prepare2run: {c}")
+                    if c not in without_dependent_checking:
                         cpids = cpn.get_dependent_components()
-                        if any([c not in self.path[-1] for c in cpids]):
+                        if any([cc not in self.path[-1] for cc in cpids]):
+                            if c not in waiting: waiting.append(c)
                             continue
+                    yield "*'{}'* is running...🕞".format(self.get_compnent_name(c))
                     ans = cpn.run(self.history, **kwargs)
                     self.path[-1].append(c)
             ran += 1
 
-        prepare2run(self.components[self.path[-2][-1]]["downstream"])
+        for m in prepare2run(self.components[self.path[-2][-1]]["downstream"]):
+            yield {"content": m, "running_status": True}
+
         while 0 <= ran < len(self.path[-1]):
-            if DEBUG: print(ran, self.path)
+            logging.debug(f"Canvas.run: {ran} {self.path}")
             cpn_id = self.path[-1][ran]
             cpn = self.get_component(cpn_id)
             if not cpn["downstream"]: break
@@ -217,27 +221,26 @@ class Canvas(ABC):
                 assert switch_out in self.components, \
                     "{}'s output: {} not valid.".format(cpn_id, switch_out)
                 try:
-                    prepare2run([switch_out])
+                    for m in prepare2run([switch_out]):
+                        yield {"content": m, "running_status": True}
                 except Exception as e:
-                    for p in [c for p in self.path for c in p][::-1]:
-                        if p.lower().find("answer") >= 0:
-                            self.get_component(p)["obj"].set_exception(e)
-                            prepare2run([p])
-                            break
-                    traceback.print_exc()
-                    break
+                    yield {"content": "*Exception*: {}".format(e), "running_status": True}
+                    logging.exception("Canvas.run got exception")
                 continue
 
             try:
-                prepare2run(cpn["downstream"])
+                for m in prepare2run(cpn["downstream"]):
+                    yield {"content": m, "running_status": True}
             except Exception as e:
-                for p in [c for p in self.path for c in p][::-1]:
-                    if p.lower().find("answer") >= 0:
-                        self.get_component(p)["obj"].set_exception(e)
-                        prepare2run([p])
-                        break
-                traceback.print_exc()
-                break
+                yield {"content": "*Exception*: {}".format(e), "running_status": True}
+                logging.exception("Canvas.run got exception")
+
+            if ran >= len(self.path[-1]) and waiting:
+                without_dependent_checking = waiting
+                waiting = []
+                for m in prepare2run(without_dependent_checking):
+                    yield {"content": m, "running_status": True}
+                ran -= 1
 
         if self.answer:
             cpn_id = self.answer[0]
@@ -246,11 +249,13 @@ class Canvas(ABC):
             self.path[-1].append(cpn_id)
             if kwargs.get("stream"):
                 assert isinstance(ans, partial)
-                return ans
+                for an in ans():
+                    yield an
+            else:
+                yield ans
 
-            self.history.append(("assistant", ans.to_dict("records")))
-
-        return ans
+        else:
+            raise Exception("The dialog flow has no way to interact with you. Please add an 'Interact' component to the end of the flow.")
 
     def get_component(self, cpn_id):
         return self.components[cpn_id]
@@ -260,9 +265,11 @@ class Canvas(ABC):
 
     def get_history(self, window_size):
         convs = []
-        for role, obj in self.history[(window_size + 1) * -1:]:
-            convs.append({"role": role, "content": (obj if role == "user" else
-                                                    '\n'.join(pd.DataFrame(obj)['content']))})
+        for role, obj in self.history[window_size * -1:]:
+            if isinstance(obj, list) and obj and all([isinstance(o, dict) for o in obj]):
+                convs.append({"role": role, "content": '\n'.join([str(s.get("content", "")) for s in obj])})
+            else:
+                convs.append({"role": role, "content": str(obj)})
         return convs
 
     def add_user_input(self, question):

agent/component/__init__.py

@@ -28,6 +28,9 @@ from .wencai import WenCai, WenCaiParam
 from .jin10 import Jin10, Jin10Param
 from .tushare import TuShare, TuShareParam
 from .akshare import AkShare, AkShareParam
+from .crawler import Crawler, CrawlerParam
+from .invoke import Invoke, InvokeParam
+from .template import Template, TemplateParam
 
 
 def component_class(class_name):

agent/component/arxiv.py

@@ -13,13 +13,12 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 import arxiv
 import pandas as pd
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 
-
 class ArXivParam(ComponentParamBase):
     """
     Define the ArXiv component parameters.
@@ -65,5 +64,5 @@ class ArXiv(ComponentBase, ABC):
             return ArXiv.be_output("")
 
         df = pd.DataFrame(arxiv_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"df: {str(df)}")
         return df

agent/component/baidu.py

@@ -13,13 +13,11 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-import random
+import logging
 from abc import ABC
-from functools import partial
 import pandas as pd
 import requests
 import re
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -64,6 +62,6 @@ class Baidu(ComponentBase, ABC):
             return Baidu.be_output("")
 
         df = pd.DataFrame(baidu_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"df: {str(df)}")
         return df
 

agent/component/baidufanyi.py

@@ -36,7 +36,6 @@ class BaiduFanyiParam(ComponentParamBase):
         self.domain = 'finance'
 
     def check(self):
-        self.check_positive_integer(self.top_n, "Top N")
         self.check_empty(self.appid, "BaiduFanyi APPID")
         self.check_empty(self.secret_key, "BaiduFanyi Secret Key")
         self.check_valid_value(self.trans_type, "Translate type", ['translate', 'fieldtranslate'])

agent/component/base.py

@@ -17,14 +17,13 @@ from abc import ABC
 import builtins
 import json
 import os
-from copy import deepcopy
+import logging
 from functools import partial
-from typing import List, Dict, Tuple, Union
+from typing import Tuple, Union
 
 import pandas as pd
 
 from agent import settings
-from agent.settings import flow_logger, DEBUG
 
 _FEEDED_DEPRECATED_PARAMS = "_feeded_deprecated_params"
 _DEPRECATED_PARAMS = "_deprecated_params"
@@ -36,6 +35,8 @@ class ComponentParamBase(ABC):
     def __init__(self):
         self.output_var_name = "output"
         self.message_history_window_size = 22
+        self.query = []
+        self.inputs = []
 
     def set_name(self, name: str):
         self._name = name
@@ -81,7 +82,6 @@ class ComponentParamBase(ABC):
         return {name: True for name in self.get_feeded_deprecated_params()}
 
     def __str__(self):
-
         return json.dumps(self.as_dict(), ensure_ascii=False)
 
     def as_dict(self):
@@ -359,13 +359,13 @@ class ComponentParamBase(ABC):
 
     def _warn_deprecated_param(self, param_name, descr):
         if self._deprecated_params_set.get(param_name):
-            flow_logger.warning(
+            logging.warning(
                 f"{descr} {param_name} is deprecated and ignored in this version."
             )
 
     def _warn_to_deprecate_param(self, param_name, descr, new_param):
         if self._deprecated_params_set.get(param_name):
-            flow_logger.warning(
+            logging.warning(
                 f"{descr} {param_name} will be deprecated in future release; "
                 f"please use {new_param} instead."
             )
@@ -385,10 +385,14 @@ class ComponentBase(ABC):
         """
         return """{{
             "component_name": "{}",
-            "params": {}
+            "params": {},
+            "output": {},
+            "inputs": {}
         }}""".format(self.component_name,
-                     self._param
-                     )
+                     self._param,
+                     json.dumps(json.loads(str(self._param)).get("output", {}), ensure_ascii=False),
+                     json.dumps(json.loads(str(self._param)).get("inputs", []), ensure_ascii=False)
+        )
 
     def __init__(self, canvas, id, param: ComponentParamBase):
         self._canvas = canvas
@@ -396,8 +400,15 @@ class ComponentBase(ABC):
         self._param = param
         self._param.check()
 
+    def get_dependent_components(self):
+        cpnts = set([para["component_id"].split("@")[0] for para in self._param.query \
+                     if para.get("component_id") \
+                     and para["component_id"].lower().find("answer") < 0 \
+                     and para["component_id"].lower().find("begin") < 0])
+        return list(cpnts)
+
     def run(self, history, **kwargs):
-        flow_logger.info("{}, history: {}, kwargs: {}".format(self, json.dumps(history, ensure_ascii=False),
+        logging.debug("{}, history: {}, kwargs: {}".format(self, json.dumps(history, ensure_ascii=False),
                                                               json.dumps(kwargs, ensure_ascii=False)))
         try:
             res = self._run(history, **kwargs)
@@ -431,48 +442,85 @@ class ComponentBase(ABC):
 
     def reset(self):
         setattr(self._param, self._param.output_var_name, None)
+        self._param.inputs = []
 
-    def set_output(self, v: pd.DataFrame):
+    def set_output(self, v: partial | pd.DataFrame):
         setattr(self._param, self._param.output_var_name, v)
 
     def get_input(self):
-        upstream_outs = []
         reversed_cpnts = []
         if len(self._canvas.path) > 1:
             reversed_cpnts.extend(self._canvas.path[-2])
         reversed_cpnts.extend(self._canvas.path[-1])
 
-        if DEBUG: print(self.component_name, reversed_cpnts[::-1])
+        if self._param.query:
+            self._param.inputs = []
+            outs = []
+            for q in self._param.query:
+                if q["component_id"]:
+                    if q["component_id"].split("@")[0].lower().find("begin") >= 0:
+                        cpn_id, key = q["component_id"].split("@")
+                        for p in self._canvas.get_component(cpn_id)["obj"]._param.query:
+                            if p["key"] == key:
+                                outs.append(pd.DataFrame([{"content": p.get("value", "")}]))
+                                self._param.inputs.append({"component_id": q["component_id"],
+                                                           "content": p.get("value", "")})
+                                break
+                        else:
+                            assert False, f"Can't find parameter '{key}' for {cpn_id}"
+                        continue
+
+                    outs.append(self._canvas.get_component(q["component_id"])["obj"].output(allow_partial=False)[1])
+                    self._param.inputs.append({"component_id": q["component_id"],
+                                               "content": "\n".join(
+                                                   [str(d["content"]) for d in outs[-1].to_dict('records')])})
+                elif q["value"]:
+                    self._param.inputs.append({"component_id": None, "content": q["value"]})
+                    outs.append(pd.DataFrame([{"content": q["value"]}]))
+            if outs:
+                df = pd.concat(outs, ignore_index=True)
+                if "content" in df: df = df.drop_duplicates(subset=['content']).reset_index(drop=True)
+                return df
+
+        upstream_outs = []
+
         for u in reversed_cpnts[::-1]:
             if self.get_component_name(u) in ["switch", "concentrator"]: continue
             if self.component_name.lower() == "generate" and self.get_component_name(u) == "retrieval":
                 o = self._canvas.get_component(u)["obj"].output(allow_partial=False)[1]
                 if o is not None:
+                    o["component_id"] = u
                     upstream_outs.append(o)
                     continue
-            if u not in self._canvas.get_component(self._id)["upstream"]: continue
+            #if self.component_name.lower()!="answer" and u not in self._canvas.get_component(self._id)["upstream"]: continue
             if self.component_name.lower().find("switch") < 0 \
                     and self.get_component_name(u) in ["relevant", "categorize"]:
                 continue
             if u.lower().find("answer") >= 0:
                 for r, c in self._canvas.history[::-1]:
                     if r == "user":
-                        upstream_outs.append(pd.DataFrame([{"content": c}]))
+                        upstream_outs.append(pd.DataFrame([{"content": c, "component_id": u}]))
                         break
                 break
             if self.component_name.lower().find("answer") >= 0 and self.get_component_name(u) in ["relevant"]:
                 continue
             o = self._canvas.get_component(u)["obj"].output(allow_partial=False)[1]
             if o is not None:
+                o["component_id"] = u
                 upstream_outs.append(o)
             break
 
-        if upstream_outs:
-            df = pd.concat(upstream_outs, ignore_index=True)
-            if "content" in df:
-                df = df.drop_duplicates(subset=['content']).reset_index(drop=True)
-            return df
-        return pd.DataFrame(self._canvas.get_history(3)[-1:])
+        assert upstream_outs, "Can't inference the where the component input is. Please identify whose output is this component's input."
+
+        df = pd.concat(upstream_outs, ignore_index=True)
+        if "content" in df:
+            df = df.drop_duplicates(subset=['content']).reset_index(drop=True)
+
+        self._param.inputs = []
+        for _, r in df.iterrows():
+            self._param.inputs.append({"component_id": r["component_id"], "content": r["content"]})
+
+        return df
 
     def get_stream_input(self):
         reversed_cpnts = []

agent/component/bing.py

@@ -13,13 +13,12 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 import requests
 import pandas as pd
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 
-
 class BingParam(ComponentParamBase):
     """
     Define the Bing component parameters.
@@ -81,5 +80,5 @@ class Bing(ComponentBase, ABC):
             return Bing.be_output("")
 
         df = pd.DataFrame(bing_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"df: {str(df)}")
         return df

agent/component/categorize.py

@@ -13,11 +13,11 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 from api.db import LLMType
 from api.db.services.llm_service import LLMBundle
 from agent.component import GenerateParam, Generate
-from agent.settings import DEBUG
 
 
 class CategorizeParam(GenerateParam):
@@ -34,7 +34,7 @@ class CategorizeParam(GenerateParam):
         super().check()
         self.check_empty(self.category_description, "[Categorize] Category examples")
         for k, v in self.category_description.items():
-            if not k: raise ValueError(f"[Categorize] Category name can not be empty!")
+            if not k: raise ValueError("[Categorize] Category name can not be empty!")
             if not v.get("to"): raise ValueError(f"[Categorize] 'To' of category {k} can not be empty!")
 
     def get_prompt(self):
@@ -73,11 +73,11 @@ class Categorize(Generate, ABC):
 
     def _run(self, history, **kwargs):
         input = self.get_input()
-        input = "Question: " + ("; ".join(input["content"]) if "content" in input else "") + "Category: "
+        input = "Question: " + (list(input["content"])[-1] if "content" in input else "") + "\tCategory: "
         chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
         ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": input}],
                             self._param.gen_conf())
-        if DEBUG: print(ans, ":::::::::::::::::::::::::::::::::", input)
+        logging.debug(f"input: {input}, answer: {str(ans)}")
         for c in self._param.category_description.keys():
             if ans.lower().find(c.lower()) >= 0:
                 return Categorize.be_output(self._param.category_description[c]["to"])

agent/component/cite.py

@@ -1,75 +0,0 @@
-#
-#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
-#
-#  Licensed under the Apache License, Version 2.0 (the "License");
-#  you may not use this file except in compliance with the License.
-#  You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-#  Unless required by applicable law or agreed to in writing, software
-#  distributed under the License is distributed on an "AS IS" BASIS,
-#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#  See the License for the specific language governing permissions and
-#  limitations under the License.
-#
-from abc import ABC
-
-import pandas as pd
-
-from api.db import LLMType
-from api.db.services.knowledgebase_service import KnowledgebaseService
-from api.db.services.llm_service import LLMBundle
-from api.settings import retrievaler
-from agent.component.base import ComponentBase, ComponentParamBase
-
-
-class CiteParam(ComponentParamBase):
-
-    """
-    Define the Retrieval component parameters.
-    """
-    def __init__(self):
-        super().__init__()
-        self.cite_sources = []
-
-    def check(self):
-        self.check_empty(self.cite_source, "Please specify where you want to cite from.")
-
-
-class Cite(ComponentBase, ABC):
-    component_name = "Cite"
-
-    def _run(self, history, **kwargs):
-        input = "\n- ".join(self.get_input()["content"])
-        sources = [self._canvas.get_component(cpn_id).output()[1] for cpn_id in self._param.cite_source]
-        query = []
-        for role, cnt in history[::-1][:self._param.message_history_window_size]:
-            if role != "user":continue
-            query.append(cnt)
-        query = "\n".join(query)
-
-        kbs = KnowledgebaseService.get_by_ids(self._param.kb_ids)
-        if not kbs:
-            raise ValueError("Can't find knowledgebases by {}".format(self._param.kb_ids))
-        embd_nms = list(set([kb.embd_id for kb in kbs]))
-        assert len(embd_nms) == 1, "Knowledge bases use different embedding models."
-
-        embd_mdl = LLMBundle(kbs[0].tenant_id, LLMType.EMBEDDING, embd_nms[0])
-
-        rerank_mdl = None
-        if self._param.rerank_id:
-            rerank_mdl = LLMBundle(kbs[0].tenant_id, LLMType.RERANK, self._param.rerank_id)
-
-        kbinfos = retrievaler.retrieval(query, embd_mdl, kbs[0].tenant_id, self._param.kb_ids,
-                                        1, self._param.top_n,
-                                        self._param.similarity_threshold, 1 - self._param.keywords_similarity_weight,
-                                        aggs=False, rerank_mdl=rerank_mdl)
-
-        if not kbinfos["chunks"]: return pd.DataFrame()
-        df = pd.DataFrame(kbinfos["chunks"])
-        df["content"] = df["content_with_weight"]
-        del df["content_with_weight"]
-        return df
-
-

agent/component/crawler.py

@@ -0,0 +1,70 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from abc import ABC
+import asyncio
+from crawl4ai import AsyncWebCrawler
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class CrawlerParam(ComponentParamBase):
+    """
+    Define the Crawler component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.proxy = None
+        self.extract_type = "markdown"
+    
+    def check(self):
+        self.check_valid_value(self.extract_type, "Type of content from the crawler", ['html', 'markdown', 'content'])
+
+
+class Crawler(ComponentBase, ABC):
+    component_name = "Crawler"
+
+    def _run(self, history, **kwargs):
+        ans = self.get_input()
+        ans = " - ".join(ans["content"]) if "content" in ans else ""
+        if not ans:
+            return Crawler.be_output("")
+        try:
+            result = asyncio.run(self.get_web(ans))
+
+            return Crawler.be_output(result)
+            
+        except Exception as e:
+            return Crawler.be_output(f"An unexpected error occurred: {str(e)}")
+
+    async def get_web(self, url):
+        proxy = self._param.proxy if self._param.proxy else None
+        async with AsyncWebCrawler(verbose=True, proxy=proxy) as crawler:
+            result = await crawler.arun(
+                url=url,
+                bypass_cache=True
+            )
+            
+            if self._param.extract_type == 'html':
+                return result.cleaned_html
+            elif self._param.extract_type == 'markdown':
+                return result.markdown
+            elif self._param.extract_type == 'content':
+                result.extracted_content
+            return result.markdown
+            
+
+
+    

agent/component/duckduckgo.py

@@ -13,10 +13,10 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 from duckduckgo_search import DDGS
 import pandas as pd
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -62,5 +62,5 @@ class DuckDuckGo(ComponentBase, ABC):
             return DuckDuckGo.be_output("")
 
         df = pd.DataFrame(duck_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug("df: {df}")
         return df

agent/component/exesql.py

@@ -16,7 +16,8 @@
 from abc import ABC
 import re
 import pandas as pd
-from peewee import MySQLDatabase, PostgresqlDatabase
+import pymysql
+import psycopg2
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -44,6 +45,9 @@ class ExeSQLParam(ComponentParamBase):
         self.check_positive_integer(self.port, "IP Port")
         self.check_empty(self.password, "Database password")
         self.check_positive_integer(self.top_n, "Number of records")
+        if self.database == "rag_flow":
+            if self.host == "ragflow-mysql": raise ValueError("The host is not accessible.")
+            if self.password == "infini_rag_flow": raise ValueError("The host is not accessible.")
 
 
 class ExeSQL(ComponentBase, ABC):
@@ -66,14 +70,14 @@ class ExeSQL(ComponentBase, ABC):
             raise Exception("SQL statement not found!")
 
         if self._param.db_type in ["mysql", "mariadb"]:
-            db = MySQLDatabase(self._param.database, user=self._param.username, host=self._param.host,
-                               port=self._param.port, password=self._param.password)
+            db = pymysql.connect(db=self._param.database, user=self._param.username, host=self._param.host,
+                                 port=self._param.port, password=self._param.password)
         elif self._param.db_type == 'postgresql':
-            db = PostgresqlDatabase(self._param.database, user=self._param.username, host=self._param.host,
-                                    port=self._param.port, password=self._param.password)
+            db = psycopg2.connect(dbname=self._param.database, user=self._param.username, host=self._param.host,
+                                  port=self._param.port, password=self._param.password)
 
         try:
-            db.connect()
+            cursor = db.cursor()
         except Exception as e:
             raise Exception("Database Connection Failed! \n" + str(e))
         sql_res = []
@@ -81,13 +85,13 @@ class ExeSQL(ComponentBase, ABC):
             if not single_sql:
                 continue
             try:
-                query = db.execute_sql(single_sql)
-                if query.rowcount == 0:
-                    sql_res.append({"content": "\nTotal: " + str(query.rowcount) + "\n No record in the database!"})
+                cursor.execute(single_sql)
+                if cursor.rowcount == 0:
+                    sql_res.append({"content": "\nTotal: 0\n No record in the database!"})
                     continue
-                single_res = pd.DataFrame([i for i in query.fetchmany(size=self._param.top_n)])
-                single_res.columns = [i[0] for i in query.description]
-                sql_res.append({"content": "\nTotal: " + str(query.rowcount) + "\n" + single_res.to_markdown()})
+                single_res = pd.DataFrame([i for i in cursor.fetchmany(size=self._param.top_n)])
+                single_res.columns = [i[0] for i in cursor.description]
+                sql_res.append({"content": "\nTotal: " + str(cursor.rowcount) + "\n" + single_res.to_markdown()})
             except Exception as e:
                 sql_res.append({"content": "**Error**:" + str(e) + "\nError SQL Statement:" + single_sql})
                 pass

agent/component/generate.py

@@ -17,8 +17,9 @@ import re
 from functools import partial
 import pandas as pd
 from api.db import LLMType
+from api.db.services.dialog_service import message_fit_in
 from api.db.services.llm_service import LLMBundle
-from api.settings import retrievaler
+from api import settings
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -62,18 +63,22 @@ class Generate(ComponentBase):
     component_name = "Generate"
 
     def get_dependent_components(self):
-        cpnts = [para["component_id"] for para in self._param.parameters]
-        return cpnts
+        cpnts = set([para["component_id"].split("@")[0] for para in self._param.parameters \
+                     if para.get("component_id") \
+                     and para["component_id"].lower().find("answer") < 0 \
+                     and para["component_id"].lower().find("begin") < 0])
+        return list(cpnts)
 
     def set_cite(self, retrieval_res, answer):
         retrieval_res = retrieval_res.dropna(subset=["vector", "content_ltks"]).reset_index(drop=True)
         if "empty_response" in retrieval_res.columns:
             retrieval_res["empty_response"].fillna("", inplace=True)
-        answer, idx = retrievaler.insert_citations(answer, [ck["content_ltks"] for _, ck in retrieval_res.iterrows()],
-                                                   [ck["vector"] for _, ck in retrieval_res.iterrows()],
-                                                   LLMBundle(self._canvas.get_tenant_id(), LLMType.EMBEDDING,
-                                                             self._canvas.get_embedding_model()), tkweight=0.7,
-                                                   vtweight=0.3)
+        answer, idx = settings.retrievaler.insert_citations(answer,
+                                                            [ck["content_ltks"] for _, ck in retrieval_res.iterrows()],
+                                                            [ck["vector"] for _, ck in retrieval_res.iterrows()],
+                                                            LLMBundle(self._canvas.get_tenant_id(), LLMType.EMBEDDING,
+                                                                      self._canvas.get_embedding_model()), tkweight=0.7,
+                                                            vtweight=0.3)
         doc_ids = set([])
         recall_docs = []
         for i in idx:
@@ -100,19 +105,53 @@ class Generate(ComponentBase):
         chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
         prompt = self._param.prompt
 
-        retrieval_res = self.get_input()
-        input = ("  - " + "\n  - ".join(retrieval_res["content"])) if "content" in retrieval_res else ""
+        retrieval_res = []
+        self._param.inputs = []
         for para in self._param.parameters:
-            cpn = self._canvas.get_component(para["component_id"])["obj"]
+            if not para.get("component_id"): continue
+            component_id = para["component_id"].split("@")[0]
+            if para["component_id"].lower().find("@") >= 0:
+                cpn_id, key = para["component_id"].split("@")
+                for p in self._canvas.get_component(cpn_id)["obj"]._param.query:
+                    if p["key"] == key:
+                        kwargs[para["key"]] = p.get("value", "")
+                        self._param.inputs.append(
+                            {"component_id": para["component_id"], "content": kwargs[para["key"]]})
+                        break
+                else:
+                    assert False, f"Can't find parameter '{key}' for {cpn_id}"
+                continue
+
+            cpn = self._canvas.get_component(component_id)["obj"]
+            if cpn.component_name.lower() == "answer":
+                hist = self._canvas.get_history(1)
+                if hist:
+                    hist = hist[0]["content"]
+                else:
+                    hist = ""
+                kwargs[para["key"]] = hist
+                continue
             _, out = cpn.output(allow_partial=False)
             if "content" not in out.columns:
-                kwargs[para["key"]] = "Nothing"
+                kwargs[para["key"]] = ""
             else:
-                kwargs[para["key"]] = "  - " + "\n  - ".join(out["content"])
+                if cpn.component_name.lower() == "retrieval":
+                    retrieval_res.append(out)
+                kwargs[para["key"]] = "  - "+"\n - ".join([o if isinstance(o, str) else str(o) for o in out["content"]])
+            self._param.inputs.append({"component_id": para["component_id"], "content": kwargs[para["key"]]})
+
+        if retrieval_res:
+            retrieval_res = pd.concat(retrieval_res, ignore_index=True)
+        else: retrieval_res = pd.DataFrame([])
 
-        kwargs["input"] = input
         for n, v in kwargs.items():
-            prompt = re.sub(r"\{%s\}" % n, re.escape(str(v)), prompt)
+            prompt = re.sub(r"\{%s\}" % re.escape(n), str(v).replace("\\", " "), prompt)
+
+        if not self._param.inputs and prompt.find("{input}") >= 0:
+            retrieval_res = self.get_input()
+            input = ("  - " + "\n  - ".join(
+                [c for c in retrieval_res["content"] if isinstance(c, str)])) if "content" in retrieval_res else ""
+            prompt = re.sub(r"\{input\}", re.escape(input), prompt)
 
         downstreams = self._canvas.get_component(self._id)["downstream"]
         if kwargs.get("stream") and len(downstreams) == 1 and self._canvas.get_component(downstreams[0])[
@@ -124,8 +163,12 @@ class Generate(ComponentBase):
                 retrieval_res["empty_response"]) else "Nothing found in knowledgebase!", "reference": []}
             return pd.DataFrame([res])
 
-        ans = chat_mdl.chat(prompt, self._canvas.get_history(self._param.message_history_window_size),
-                            self._param.gen_conf())
+        msg = self._canvas.get_history(self._param.message_history_window_size)
+        if len(msg) < 1: msg.append({"role": "user", "content": ""})
+        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(chat_mdl.max_length * 0.97))
+        if len(msg) < 2: msg.append({"role": "user", "content": ""})
+        ans = chat_mdl.chat(msg[0]["content"], msg[1:], self._param.gen_conf())
+
         if self._param.cite and "content_ltks" in retrieval_res.columns and "vector" in retrieval_res.columns:
             res = self.set_cite(retrieval_res, ans)
             return pd.DataFrame([res])
@@ -141,9 +184,12 @@ class Generate(ComponentBase):
             self.set_output(res)
             return
 
+        msg = self._canvas.get_history(self._param.message_history_window_size)
+        if len(msg) < 1: msg.append({"role": "user", "content": ""})
+        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(chat_mdl.max_length * 0.97))
+        if len(msg) < 2: msg.append({"role": "user", "content": ""})
         answer = ""
-        for ans in chat_mdl.chat_streamly(prompt, self._canvas.get_history(self._param.message_history_window_size),
-                                          self._param.gen_conf()):
+        for ans in chat_mdl.chat_streamly(msg[0]["content"], msg[1:], self._param.gen_conf()):
             res = {"content": ans, "reference": []}
             answer = ans
             yield res

agent/component/github.py

@@ -13,10 +13,10 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 import pandas as pd
 import requests
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -57,5 +57,5 @@ class GitHub(ComponentBase, ABC):
             return GitHub.be_output("")
 
         df = pd.DataFrame(github_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"df: {df}")
         return df

agent/component/google.py

@@ -13,10 +13,10 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 from serpapi import GoogleSearch
 import pandas as pd
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -85,12 +85,12 @@ class Google(ComponentBase, ABC):
                  "hl": self._param.language, "num": self._param.top_n})
             google_res = [{"content": '<a href="' + i["link"] + '">' + i["title"] + '</a>    ' + i["snippet"]} for i in
                           client.get_dict()["organic_results"]]
-        except Exception as e:
+        except Exception:
             return Google.be_output("**ERROR**: Existing Unavailable Parameters!")
 
         if not google_res:
             return Google.be_output("")
 
         df = pd.DataFrame(google_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"df: {df}")
         return df

agent/component/googlescholar.py

@@ -13,9 +13,9 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 import pandas as pd
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 from scholarly import scholarly
 
@@ -58,13 +58,13 @@ class GoogleScholar(ComponentBase, ABC):
                     'pub_url'] + '"></a> ' + "\n author: " + ",".join(pub['bib']['author']) + '\n Abstract: ' + pub[
                                                    'bib'].get('abstract', 'no abstract')})
 
-            except StopIteration or Exception as e:
-                print("**ERROR** " + str(e))
+            except StopIteration or Exception:
+                logging.exception("GoogleScholar")
                 break
 
         if not scholar_res:
             return GoogleScholar.be_output("")
 
         df = pd.DataFrame(scholar_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"df: {df}")
         return df

agent/component/invoke.py

@@ -0,0 +1,106 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import json
+import re
+from abc import ABC
+import requests
+from deepdoc.parser import HtmlParser
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class InvokeParam(ComponentParamBase):
+    """
+    Define the Crawler component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.proxy = None
+        self.headers = ""
+        self.method = "get"
+        self.variables = []
+        self.url = ""
+        self.timeout = 60
+        self.clean_html = False
+
+    def check(self):
+        self.check_valid_value(self.method.lower(), "Type of content from the crawler", ['get', 'post', 'put'])
+        self.check_empty(self.url, "End point URL")
+        self.check_positive_integer(self.timeout, "Timeout time in second")
+        self.check_boolean(self.clean_html, "Clean HTML")
+
+
+class Invoke(ComponentBase, ABC):
+    component_name = "Invoke"
+
+    def _run(self, history, **kwargs):
+        args = {}
+        for para in self._param.variables:
+            if para.get("component_id"):
+                cpn = self._canvas.get_component(para["component_id"])["obj"]
+                if cpn.component_name.lower() == "answer":
+                    args[para["key"]] = self._canvas.get_history(1)[0]["content"]
+                    continue
+                _, out = cpn.output(allow_partial=False)
+                args[para["key"]] = "\n".join(out["content"])
+            else:
+                args[para["key"]] = "\n".join(para["value"])
+
+        url = self._param.url.strip()
+        if url.find("http") != 0:
+            url = "http://" + url
+
+        method = self._param.method.lower()
+        headers = {}
+        if self._param.headers:
+            headers = json.loads(self._param.headers)
+        proxies = None
+        if re.sub(r"https?:?/?/?", "", self._param.proxy):
+            proxies = {"http": self._param.proxy, "https": self._param.proxy}
+
+        if method == 'get':
+            response = requests.get(url=url,
+                                    params=args,
+                                    headers=headers,
+                                    proxies=proxies,
+                                    timeout=self._param.timeout)
+            if self._param.clean_html:
+                sections = HtmlParser()(None, response.content)
+                return Invoke.be_output("\n".join(sections))
+
+            return Invoke.be_output(response.text)
+
+        if method == 'put':
+            response = requests.put(url=url,
+                                    data=args,
+                                    headers=headers,
+                                    proxies=proxies,
+                                    timeout=self._param.timeout)
+            if self._param.clean_html:
+                sections = HtmlParser()(None, response.content)
+                return Invoke.be_output("\n".join(sections))
+            return Invoke.be_output(response.text)
+
+        if method == 'post':
+            response = requests.post(url=url,
+                                    json=args,
+                                    headers=headers,
+                                    proxies=proxies,
+                                    timeout=self._param.timeout)
+            if self._param.clean_html:
+                sections = HtmlParser()(None, response.content)
+                return Invoke.be_output("\n".join(sections))
+            return Invoke.be_output(response.text)

agent/component/keyword.py

@@ -13,12 +13,12 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import re
 from abc import ABC
 from api.db import LLMType
 from api.db.services.llm_service import LLMBundle
 from agent.component import GenerateParam, Generate
-from agent.settings import DEBUG
 
 
 class KeywordExtractParam(GenerateParam):
@@ -50,16 +50,13 @@ class KeywordExtract(Generate, ABC):
     component_name = "KeywordExtract"
 
     def _run(self, history, **kwargs):
-        q = ""
-        for r, c in self._canvas.history[::-1]:
-            if r == "user":
-                q += c
-                break
+        query = self.get_input()
+        query = str(query["content"][0]) if "content" in query else ""
 
         chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
-        ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": q}],
+        ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": query}],
                             self._param.gen_conf())
 
         ans = re.sub(r".*keyword:", "", ans).strip()
-        if DEBUG: print(ans, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"ans: {ans}")
         return KeywordExtract.be_output(ans)

agent/component/pubmed.py

@@ -13,12 +13,12 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 from Bio import Entrez
 import re
 import pandas as pd
 import xml.etree.ElementTree as ET
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -65,5 +65,5 @@ class PubMed(ComponentBase, ABC):
             return PubMed.be_output("")
 
         df = pd.DataFrame(pubmed_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"df: {df}")
         return df

agent/component/relevant.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 from api.db import LLMType
 from api.db.services.llm_service import LLMBundle
@@ -70,7 +71,7 @@ class Relevant(Generate, ABC):
         ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": ans}],
                             self._param.gen_conf())
 
-        print(ans, ":::::::::::::::::::::::::::::::::")
+        logging.debug(ans)
         if ans.lower().find("yes") >= 0:
             return Relevant.be_output(self._param.yes)
         if ans.lower().find("no") >= 0:

agent/component/retrieval.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 
 import pandas as pd
@@ -20,7 +21,7 @@ import pandas as pd
 from api.db import LLMType
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMBundle
-from api.settings import retrievaler
+from api import settings
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -43,22 +44,19 @@ class RetrievalParam(ComponentParamBase):
         self.check_decimal_float(self.similarity_threshold, "[Retrieval] Similarity threshold")
         self.check_decimal_float(self.keywords_similarity_weight, "[Retrieval] Keywords similarity weight")
         self.check_positive_number(self.top_n, "[Retrieval] Top N")
-        self.check_empty(self.kb_ids, "[Retrieval] Knowledge bases")
 
 
 class Retrieval(ComponentBase, ABC):
     component_name = "Retrieval"
 
     def _run(self, history, **kwargs):
-        query = []
-        for role, cnt in history[::-1][:self._param.message_history_window_size]:
-            if role != "user":continue
-            query.append(cnt)
-        # query = "\n".join(query)
-        query = query[0]
+        query = self.get_input()
+        query = str(query["content"][0]) if "content" in query else ""
+
         kbs = KnowledgebaseService.get_by_ids(self._param.kb_ids)
         if not kbs:
-            raise ValueError("Can't find knowledgebases by {}".format(self._param.kb_ids))
+            return Retrieval.be_output("")
+
         embd_nms = list(set([kb.embd_id for kb in kbs]))
         assert len(embd_nms) == 1, "Knowledge bases use different embedding models."
 
@@ -69,7 +67,7 @@ class Retrieval(ComponentBase, ABC):
         if self._param.rerank_id:
             rerank_mdl = LLMBundle(kbs[0].tenant_id, LLMType.RERANK, self._param.rerank_id)
 
-        kbinfos = retrievaler.retrieval(query, embd_mdl, kbs[0].tenant_id, self._param.kb_ids,
+        kbinfos = settings.retrievaler.retrieval(query, embd_mdl, kbs[0].tenant_id, self._param.kb_ids,
                                         1, self._param.top_n,
                                         self._param.similarity_threshold, 1 - self._param.keywords_similarity_weight,
                                         aggs=False, rerank_mdl=rerank_mdl)
@@ -83,7 +81,7 @@ class Retrieval(ComponentBase, ABC):
         df = pd.DataFrame(kbinfos["chunks"])
         df["content"] = df["content_with_weight"]
         del df["content_with_weight"]
-        print(">>>>>>>>>>>>>>>>>>>>>>>>>>\n", query, df)
+        logging.debug("{} {}".format(query, df))
         return df
 
 

agent/component/rewrite.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 from api.db import LLMType
 from api.db.services.llm_service import LLMBundle
@@ -33,7 +34,7 @@ class RewriteQuestionParam(GenerateParam):
     def check(self):
         super().check()
 
-    def get_prompt(self):
+    def get_prompt(self, conv):
         self.prompt = """
         You are an expert at query expansion to generate a paraphrasing of a question.
         I can't retrieval relevant information from the knowledge base by using user's question directly.     
@@ -43,6 +44,40 @@ class RewriteQuestionParam(GenerateParam):
         And return 5 versions of question and one is from translation.
         Just list the question. No other words are needed.
         """
+        return f"""
+Role: A helpful assistant
+Task: Generate a full user question that would follow the conversation.
+Requirements & Restrictions:
+  - Text generated MUST be in the same language of the original user's question.
+  - If the user's latest question is completely, don't do anything, just return the original question.
+  - DON'T generate anything except a refined question.
+
+######################
+-Examples-
+######################
+# Example 1
+## Conversation
+USER: What is the name of Donald Trump's father?
+ASSISTANT:  Fred Trump.
+USER: And his mother?
+###############
+Output: What's the name of Donald Trump's mother?
+------------
+# Example 2
+## Conversation
+USER: What is the name of Donald Trump's father?
+ASSISTANT:  Fred Trump.
+USER: And his mother?
+ASSISTANT:  Mary Trump.
+User: What's her full name?
+###############
+Output: What's the full name of Donald Trump's mother Mary Trump?
+######################
+# Real Data
+## Conversation
+{conv}
+###############
+    """
         return self.prompt
 
 
@@ -56,19 +91,21 @@ class RewriteQuestion(Generate, ABC):
             self._loop = 0
             raise Exception("Sorry! Nothing relevant found.")
         self._loop += 1
-        q = "Question: "
-        for r, c in self._canvas.history[::-1]:
-            if r == "user":
-                q += c
-                break
+
+        hist = self._canvas.get_history(4)
+        conv = []
+        for m in hist:
+            if m["role"] not in ["user", "assistant"]: continue
+            conv.append("{}: {}".format(m["role"].upper(), m["content"]))
+        conv = "\n".join(conv)
 
         chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
-        ans = chat_mdl.chat(self._param.get_prompt(), [{"role": "user", "content": q}],
+        ans = chat_mdl.chat(self._param.get_prompt(conv), [{"role": "user", "content": "Output: "}],
                             self._param.gen_conf())
         self._canvas.history.pop()
         self._canvas.history.append(("user", ans))
 
-        print(ans, ":::::::::::::::::::::::::::::::::")
+        logging.debug(ans)
         return RewriteQuestion.be_output(ans)
 
 

agent/component/switch.py

@@ -47,13 +47,35 @@ class SwitchParam(ComponentParamBase):
 class Switch(ComponentBase, ABC):
     component_name = "Switch"
 
+    def get_dependent_components(self):
+        res = []
+        for cond in self._param.conditions:
+            for item in cond["items"]:
+                if not item["cpn_id"]: continue
+                if item["cpn_id"].find("begin") >= 0:
+                    continue
+                cid = item["cpn_id"].split("@")[0]
+                res.append(cid)
+
+        return list(set(res))
+
     def _run(self, history, **kwargs):
         for cond in self._param.conditions:
             res = []
             for item in cond["items"]:
-                out = self._canvas.get_component(item["cpn_id"])["obj"].output()[1]
-                cpn_input = "" if "content" not in out.columns else " ".join(out["content"])
-                res.append(self.process_operator(cpn_input, item["operator"], item["value"]))
+                if not item["cpn_id"]:continue
+                cid = item["cpn_id"].split("@")[0]
+                if item["cpn_id"].find("@") > 0:
+                    cpn_id, key = item["cpn_id"].split("@")
+                    for p in self._canvas.get_component(cid)["obj"]._param.query:
+                        if p["key"] == key:
+                            res.append(self.process_operator(p.get("value",""), item["operator"], item.get("value", "")))
+                            break
+                else:
+                    out = self._canvas.get_component(cid)["obj"].output()[1]
+                    cpn_input = "" if "content" not in out.columns else " ".join([str(s) for s in out["content"]])
+                    res.append(self.process_operator(cpn_input, item["operator"], item.get("value", "")))
+
                 if cond["logical_operator"] != "and" and any(res):
                     return Switch.be_output(cond["to"])
 

agent/component/template.py

@@ -0,0 +1,85 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import re
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class TemplateParam(ComponentParamBase):
+    """
+    Define the Generate component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.content = ""
+        self.parameters = []
+
+    def check(self):
+        self.check_empty(self.content, "[Template] Content")
+        return True
+
+
+class Template(ComponentBase):
+    component_name = "Template"
+
+    def get_dependent_components(self):
+        cpnts = set([para["component_id"].split("@")[0] for para in self._param.parameters \
+                     if para.get("component_id") \
+                     and para["component_id"].lower().find("answer") < 0 \
+                     and para["component_id"].lower().find("begin") < 0])
+        return list(cpnts)
+
+    def _run(self, history, **kwargs):
+        content = self._param.content
+
+        self._param.inputs = []
+        for para in self._param.parameters:
+            if not para.get("component_id"): continue
+            component_id = para["component_id"].split("@")[0]
+            if para["component_id"].lower().find("@") >= 0:
+                cpn_id, key = para["component_id"].split("@")
+                for p in self._canvas.get_component(cpn_id)["obj"]._param.query:
+                    if p["key"] == key:
+                        kwargs[para["key"]] = p.get("value", "")
+                        self._param.inputs.append(
+                            {"component_id": para["component_id"], "content": kwargs[para["key"]]})
+                        break
+                else:
+                    assert False, f"Can't find parameter '{key}' for {cpn_id}"
+                continue
+
+            cpn = self._canvas.get_component(component_id)["obj"]
+            if cpn.component_name.lower() == "answer":
+                hist = self._canvas.get_history(1)
+                if hist:
+                    hist = hist[0]["content"]
+                else:
+                    hist = ""
+                kwargs[para["key"]] = hist
+                continue
+
+            _, out = cpn.output(allow_partial=False)
+            if "content" not in out.columns:
+                kwargs[para["key"]] = ""
+            else:
+                kwargs[para["key"]] = "  - "+"\n - ".join([o if isinstance(o, str) else str(o) for o in out["content"]])
+            self._param.inputs.append({"component_id": para["component_id"], "content": kwargs[para["key"]]})
+
+        for n, v in kwargs.items():
+            content = re.sub(r"\{%s\}" % re.escape(n), str(v).replace("\\", " "), content)
+
+        return Template.be_output(content)
+

agent/component/wikipedia.py

@@ -13,12 +13,10 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-import random
+import logging
 from abc import ABC
-from functools import partial
 import wikipedia
 import pandas as pd
-from agent.settings import DEBUG
 from agent.component.base import ComponentBase, ComponentParamBase
 
 
@@ -65,5 +63,5 @@ class Wikipedia(ComponentBase, ABC):
             return Wikipedia.be_output("")
 
         df = pd.DataFrame(wiki_res)
-        if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
+        logging.debug(f"df: {df}")
         return df

agent/component/yahoofinance.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from abc import ABC
 import pandas as pd
 from agent.component.base import ComponentBase, ComponentParamBase
@@ -74,8 +75,8 @@ class YahooFinance(ComponentBase, ABC):
                     {"content": "quarterly cash flow statement:\n" + msft.quarterly_cashflow.to_markdown() + "\n"})
             if self._param.news:
                 yohoo_res.append({"content": "news:\n" + pd.DataFrame(msft.news).to_markdown() + "\n"})
-        except Exception as e:
-            print("**ERROR** " + str(e))
+        except Exception:
+            logging.exception("YahooFinance got exception")
 
         if not yohoo_res:
             return YahooFinance.be_output("")

agent/settings.py

@@ -13,22 +13,6 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-# Logger
-import os
 
-from api.utils.file_utils import get_project_base_directory
-from api.utils.log_utils import LoggerFactory, getLogger
-
-DEBUG = 0
-LoggerFactory.set_directory(
-    os.path.join(
-        get_project_base_directory(),
-        "logs",
-        "flow"))
-# {CRITICAL: 50, FATAL:50, ERROR:40, WARNING:30, WARN:30, INFO:20, DEBUG:10, NOTSET:0}
-LoggerFactory.LEVEL = 30
-
-flow_logger = getLogger("flow")
-database_logger = getLogger("database")
 FLOAT_ZERO = 1e-8
 PARAM_MAXDEPTH = 5

api/apps/__init__.py

@@ -13,14 +13,16 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-import logging
 import os
 import sys
+import logging
 from importlib.util import module_from_spec, spec_from_file_location
 from pathlib import Path
 from flask import Blueprint, Flask
 from werkzeug.wrappers.request import Request
 from flask_cors import CORS
+from flasgger import Swagger
+from itsdangerous.url_safe import URLSafeTimedSerializer as Serializer
 
 from api.db import StatusEnum
 from api.db.db_models import close_connection
@@ -29,32 +31,60 @@ from api.utils import CustomJSONEncoder, commands
 
 from flask_session import Session
 from flask_login import LoginManager
-from api.settings import SECRET_KEY, stat_logger
-from api.settings import API_VERSION, access_logger
+from api import settings
 from api.utils.api_utils import server_error_response
-from itsdangerous.url_safe import URLSafeTimedSerializer as Serializer
+from api.constants import API_VERSION
 
-__all__ = ['app']
-
-
-logger = logging.getLogger('flask.app')
-for h in access_logger.handlers:
-    logger.addHandler(h)
+__all__ = ["app"]
 
 Request.json = property(lambda self: self.get_json(force=True, silent=True))
 
 app = Flask(__name__)
-CORS(app, supports_credentials=True,max_age=2592000)
+
+# Add this at the beginning of your file to configure Swagger UI
+swagger_config = {
+    "headers": [],
+    "specs": [
+        {
+            "endpoint": "apispec",
+            "route": "/apispec.json",
+            "rule_filter": lambda rule: True,  # Include all endpoints
+            "model_filter": lambda tag: True,  # Include all models
+        }
+    ],
+    "static_url_path": "/flasgger_static",
+    "swagger_ui": True,
+    "specs_route": "/apidocs/",
+}
+
+swagger = Swagger(
+    app,
+    config=swagger_config,
+    template={
+        "swagger": "2.0",
+        "info": {
+            "title": "RAGFlow API",
+            "description": "",
+            "version": "1.0.0",
+        },
+        "securityDefinitions": {
+            "ApiKeyAuth": {"type": "apiKey", "name": "Authorization", "in": "header"}
+        },
+    },
+)
+
+CORS(app, supports_credentials=True, max_age=2592000)
 app.url_map.strict_slashes = False
 app.json_encoder = CustomJSONEncoder
 app.errorhandler(Exception)(server_error_response)
 
-
 ## convince for dev and debug
-#app.config["LOGIN_DISABLED"] = True
+# app.config["LOGIN_DISABLED"] = True
 app.config["SESSION_PERMANENT"] = False
 app.config["SESSION_TYPE"] = "filesystem"
-app.config['MAX_CONTENT_LENGTH'] = int(os.environ.get("MAX_CONTENT_LENGTH", 128 * 1024 * 1024))
+app.config["MAX_CONTENT_LENGTH"] = int(
+    os.environ.get("MAX_CONTENT_LENGTH", 128 * 1024 * 1024)
+)
 
 Session(app)
 login_manager = LoginManager()
@@ -64,17 +94,23 @@ commands.register_commands(app)
 
 
 def search_pages_path(pages_dir):
-    app_path_list = [path for path in pages_dir.glob('*_app.py') if not path.name.startswith('.')]
-    api_path_list = [path for path in pages_dir.glob('*sdk/*.py') if not path.name.startswith('.')]
+    app_path_list = [
+        path for path in pages_dir.glob("*_app.py") if not path.name.startswith(".")
+    ]
+    api_path_list = [
+        path for path in pages_dir.glob("*sdk/*.py") if not path.name.startswith(".")
+    ]
     app_path_list.extend(api_path_list)
     return app_path_list
 
 
 def register_page(page_path):
-    path = f'{page_path}'
+    path = f"{page_path}"
 
-    page_name = page_path.stem.rstrip('_app')
-    module_name = '.'.join(page_path.parts[page_path.parts.index('api'):-1] + (page_name,))
+    page_name = page_path.stem.rstrip("_app")
+    module_name = ".".join(
+        page_path.parts[page_path.parts.index("api"): -1] + (page_name,)
+    )
 
     spec = spec_from_file_location(module_name, page_path)
     page = module_from_spec(spec)
@@ -82,8 +118,10 @@ def register_page(page_path):
     page.manager = Blueprint(page_name, module_name)
     sys.modules[module_name] = page
     spec.loader.exec_module(page)
-    page_name = getattr(page, 'page_name', page_name)
-    url_prefix = f'/api/{API_VERSION}/{page_name}' if "/sdk/" in path else f'/{API_VERSION}/{page_name}'
+    page_name = getattr(page, "page_name", page_name)
+    url_prefix = (
+        f"/api/{API_VERSION}" if "/sdk/" in path else f"/{API_VERSION}/{page_name}"
+    )
 
     app.register_blueprint(page.manager, url_prefix=url_prefix)
     return url_prefix
@@ -91,31 +129,31 @@ def register_page(page_path):
 
 pages_dir = [
     Path(__file__).parent,
-    Path(__file__).parent.parent / 'api' / 'apps',
-    Path(__file__).parent.parent / 'api' / 'apps' / 'sdk',
+    Path(__file__).parent.parent / "api" / "apps",
+    Path(__file__).parent.parent / "api" / "apps" / "sdk",
 ]
 
 client_urls_prefix = [
-    register_page(path)
-    for dir in pages_dir
-    for path in search_pages_path(dir)
+    register_page(path) for dir in pages_dir for path in search_pages_path(dir)
 ]
 
 
 @login_manager.request_loader
 def load_user(web_request):
-    jwt = Serializer(secret_key=SECRET_KEY)
+    jwt = Serializer(secret_key=settings.SECRET_KEY)
     authorization = web_request.headers.get("Authorization")
     if authorization:
         try:
             access_token = str(jwt.loads(authorization))
-            user = UserService.query(access_token=access_token, status=StatusEnum.VALID.value)
+            user = UserService.query(
+                access_token=access_token, status=StatusEnum.VALID.value
+            )
             if user:
                 return user[0]
             else:
                 return None
-        except Exception as e:
-            stat_logger.exception(e)
+        except Exception:
+            logging.exception("load_user got exception")
             return None
     else:
         return None
@@ -123,4 +161,4 @@ def load_user(web_request):
 
 @app.teardown_request
 def _db_close(exc):
-    close_connection()
+    close_connection()

api/apps/api_app.py

@@ -22,35 +22,29 @@ from api.db.services.llm_service import TenantLLMService
 from flask_login import login_required, current_user
 
 from api.db import FileType, LLMType, ParserType, FileSource
-from api.db.db_models import APIToken, API4Conversation, Task, File
+from api.db.db_models import APIToken, Task, File
 from api.db.services import duplicate_name
 from api.db.services.api_service import APITokenService, API4ConversationService
-from api.db.services.dialog_service import DialogService, chat
+from api.db.services.dialog_service import DialogService, chat, keyword_extraction
 from api.db.services.document_service import DocumentService, doc_upload_and_parse
 from api.db.services.file2document_service import File2DocumentService
 from api.db.services.file_service import FileService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.task_service import queue_tasks, TaskService
 from api.db.services.user_service import UserTenantService
-from api.settings import RetCode, retrievaler
+from api import settings
 from api.utils import get_uuid, current_timestamp, datetime_format
-from api.utils.api_utils import server_error_response, get_data_error_result, get_json_result, validate_request
-from itsdangerous import URLSafeTimedSerializer
+from api.utils.api_utils import server_error_response, get_data_error_result, get_json_result, validate_request, \
+    generate_confirmation_token
 
 from api.utils.file_utils import filename_type, thumbnail
-from rag.nlp import keyword_extraction
 from rag.utils.storage_factory import STORAGE_IMPL
 
-from api.db.services.canvas_service import CanvasTemplateService, UserCanvasService
+from api.db.services.canvas_service import UserCanvasService
 from agent.canvas import Canvas
 from functools import partial
 
 
-def generate_confirmation_token(tenent_id):
-    serializer = URLSafeTimedSerializer(tenent_id)
-    return "ragflow-" + serializer.dumps(get_uuid(), salt=tenent_id)[2:34]
-
-
 @manager.route('/new_token', methods=['POST'])
 @login_required
 def new_token():
@@ -58,7 +52,7 @@ def new_token():
     try:
         tenants = UserTenantService.query(user_id=current_user.id)
         if not tenants:
-            return get_data_error_result(retmsg="Tenant not found!")
+            return get_data_error_result(message="Tenant not found!")
 
         tenant_id = tenants[0].tenant_id
         obj = {"tenant_id": tenant_id, "token": generate_confirmation_token(tenant_id),
@@ -74,7 +68,7 @@ def new_token():
             obj["dialog_id"] = req["dialog_id"]
 
         if not APITokenService.save(**obj):
-            return get_data_error_result(retmsg="Fail to new a dialog!")
+            return get_data_error_result(message="Fail to new a dialog!")
 
         return get_json_result(data=obj)
     except Exception as e:
@@ -87,7 +81,7 @@ def token_list():
     try:
         tenants = UserTenantService.query(user_id=current_user.id)
         if not tenants:
-            return get_data_error_result(retmsg="Tenant not found!")
+            return get_data_error_result(message="Tenant not found!")
 
         id = request.args["dialog_id"] if "dialog_id" in request.args else request.args["canvas_id"]
         objs = APITokenService.query(tenant_id=tenants[0].tenant_id, dialog_id=id)
@@ -116,7 +110,7 @@ def stats():
     try:
         tenants = UserTenantService.query(user_id=current_user.id)
         if not tenants:
-            return get_data_error_result(retmsg="Tenant not found!")
+            return get_data_error_result(message="Tenant not found!")
         objs = API4ConversationService.stats(
             tenants[0].tenant_id,
             request.args.get(
@@ -147,7 +141,7 @@ def set_conversation():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
     req = request.json
     try:
         if objs[0].source == "agent":
@@ -169,7 +163,7 @@ def set_conversation():
         else:
             e, dia = DialogService.get_by_id(objs[0].dialog_id)
             if not e:
-                return get_data_error_result(retmsg="Dialog not found")
+                return get_data_error_result(message="Dialog not found")
             conv = {
                 "id": get_uuid(),
                 "dialog_id": dia.id,
@@ -189,11 +183,11 @@ def completion():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
     req = request.json
     e, conv = API4ConversationService.get_by_id(req["conversation_id"])
     if not e:
-        return get_data_error_result(retmsg="Conversation not found!")
+        return get_data_error_result(message="Conversation not found!")
     if "quote" not in req: req["quote"] = False
 
     msg = []
@@ -263,19 +257,20 @@ def completion():
                             ans = {"answer": ans["content"], "reference": ans.get("reference", [])}
                             fillin_conv(ans)
                             rename_field(ans)
-                            yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": ans},
+                            yield "data:" + json.dumps({"code": 0, "message": "", "data": ans},
                                                        ensure_ascii=False) + "\n\n"
 
                         canvas.messages.append({"role": "assistant", "content": final_ans["content"], "id": message_id})
+                        canvas.history.append(("assistant", final_ans["content"]))
                         if final_ans.get("reference"):
                             canvas.reference.append(final_ans["reference"])
                         cvs.dsl = json.loads(str(canvas))
                         API4ConversationService.append_message(conv.id, conv.to_dict())
                     except Exception as e:
-                        yield "data:" + json.dumps({"retcode": 500, "retmsg": str(e),
+                        yield "data:" + json.dumps({"code": 500, "message": str(e),
                                                     "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
                                                    ensure_ascii=False) + "\n\n"
-                    yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": True}, ensure_ascii=False) + "\n\n"
+                    yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
 
                 resp = Response(sse(), mimetype="text/event-stream")
                 resp.headers.add_header("Cache-control", "no-cache")
@@ -295,12 +290,12 @@ def completion():
             API4ConversationService.append_message(conv.id, conv.to_dict())
             rename_field(result)
             return get_json_result(data=result)
-        
-        #******************For dialog******************
+
+        # ******************For dialog******************
         conv.message.append(msg[-1])
         e, dia = DialogService.get_by_id(conv.dialog_id)
         if not e:
-            return get_data_error_result(retmsg="Dialog not found!")
+            return get_data_error_result(message="Dialog not found!")
         del req["conversation_id"]
         del req["messages"]
 
@@ -315,14 +310,14 @@ def completion():
                 for ans in chat(dia, msg, True, **req):
                     fillin_conv(ans)
                     rename_field(ans)
-                    yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": ans},
+                    yield "data:" + json.dumps({"code": 0, "message": "", "data": ans},
                                                ensure_ascii=False) + "\n\n"
                 API4ConversationService.append_message(conv.id, conv.to_dict())
             except Exception as e:
-                yield "data:" + json.dumps({"retcode": 500, "retmsg": str(e),
+                yield "data:" + json.dumps({"code": 500, "message": str(e),
                                             "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
                                            ensure_ascii=False) + "\n\n"
-            yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": True}, ensure_ascii=False) + "\n\n"
+            yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
 
         if req.get("stream", True):
             resp = Response(stream(), mimetype="text/event-stream")
@@ -331,7 +326,7 @@ def completion():
             resp.headers.add_header("X-Accel-Buffering", "no")
             resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
             return resp
-            
+
         answer = None
         for ans in chat(dia, msg, **req):
             answer = ans
@@ -352,18 +347,18 @@ def get(conversation_id):
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
-    
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
+
     try:
         e, conv = API4ConversationService.get_by_id(conversation_id)
         if not e:
-            return get_data_error_result(retmsg="Conversation not found!")
+            return get_data_error_result(message="Conversation not found!")
 
         conv = conv.to_dict()
         if token != APIToken.query(dialog_id=conv['dialog_id'])[0].token:
-            return get_json_result(data=False, retmsg='Token is not valid for this conversation_id!"',
-                                   retcode=RetCode.AUTHENTICATION_ERROR)
-            
+            return get_json_result(data=False, message='Token is not valid for this conversation_id!"',
+                                   code=settings.RetCode.AUTHENTICATION_ERROR)
+
         for referenct_i in conv['reference']:
             if referenct_i is None or len(referenct_i) == 0:
                 continue
@@ -383,7 +378,7 @@ def upload():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
 
     kb_name = request.form.get("kb_name").strip()
     tenant_id = objs[0].tenant_id
@@ -392,19 +387,19 @@ def upload():
         e, kb = KnowledgebaseService.get_by_name(kb_name, tenant_id)
         if not e:
             return get_data_error_result(
-                retmsg="Can't find this knowledgebase!")
+                message="Can't find this knowledgebase!")
         kb_id = kb.id
     except Exception as e:
         return server_error_response(e)
 
     if 'file' not in request.files:
         return get_json_result(
-            data=False, retmsg='No file part!', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='No file part!', code=settings.RetCode.ARGUMENT_ERROR)
 
     file = request.files['file']
     if file.filename == '':
         return get_json_result(
-            data=False, retmsg='No file selected!', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='No file selected!', code=settings.RetCode.ARGUMENT_ERROR)
 
     root_folder = FileService.get_root_folder(tenant_id)
     pf_id = root_folder["id"]
@@ -415,7 +410,7 @@ def upload():
     try:
         if DocumentService.get_doc_count(kb.tenant_id) >= int(os.environ.get('MAX_FILE_NUM_PER_USER', 8192)):
             return get_data_error_result(
-                retmsg="Exceed the maximum file number of a free user!")
+                message="Exceed the maximum file number of a free user!")
 
         filename = duplicate_name(
             DocumentService.query,
@@ -424,7 +419,7 @@ def upload():
         filetype = filename_type(filename)
         if not filetype:
             return get_data_error_result(
-                retmsg="This type of file has not been supported yet!")
+                message="This type of file has not been supported yet!")
 
         location = filename
         while STORAGE_IMPL.obj_exist(kb_id, location):
@@ -473,7 +468,7 @@ def upload():
                 # if str(req["run"]) == TaskStatus.CANCEL.value:
                 tenant_id = DocumentService.get_tenant_id(doc["id"])
                 if not tenant_id:
-                    return get_data_error_result(retmsg="Tenant not found!")
+                    return get_data_error_result(message="Tenant not found!")
 
                 # e, doc = DocumentService.get_by_id(doc["id"])
                 TaskService.filter_delete([Task.doc_id == doc["id"]])
@@ -495,17 +490,17 @@ def upload_parse():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
 
     if 'file' not in request.files:
         return get_json_result(
-            data=False, retmsg='No file part!', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='No file part!', code=settings.RetCode.ARGUMENT_ERROR)
 
     file_objs = request.files.getlist('file')
     for file_obj in file_objs:
         if file_obj.filename == '':
             return get_json_result(
-                data=False, retmsg='No file selected!', retcode=RetCode.ARGUMENT_ERROR)
+                data=False, message='No file selected!', code=settings.RetCode.ARGUMENT_ERROR)
 
     doc_ids = doc_upload_and_parse(request.form.get("conversation_id"), file_objs, objs[0].tenant_id)
     return get_json_result(data=doc_ids)
@@ -518,7 +513,7 @@ def list_chunks():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
 
     req = request.json
 
@@ -532,15 +527,16 @@ def list_chunks():
             doc_id = req['doc_id']
         else:
             return get_json_result(
-                data=False, retmsg="Can't find doc_name or doc_id"
+                data=False, message="Can't find doc_name or doc_id"
             )
+        kb_ids = KnowledgebaseService.get_kb_ids(tenant_id)
 
-        res = retrievaler.chunk_list(doc_id=doc_id, tenant_id=tenant_id)
+        res = settings.retrievaler.chunk_list(doc_id, tenant_id, kb_ids)
         res = [
             {
                 "content": res_item["content_with_weight"],
                 "doc_name": res_item["docnm_kwd"],
-                "img_id": res_item["img_id"]
+                "image_id": res_item["img_id"]
             } for res_item in res
         ]
 
@@ -557,7 +553,7 @@ def list_kb_docs():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
 
     req = request.json
     tenant_id = objs[0].tenant_id
@@ -567,7 +563,7 @@ def list_kb_docs():
         e, kb = KnowledgebaseService.get_by_name(kb_name, tenant_id)
         if not e:
             return get_data_error_result(
-                retmsg="Can't find this knowledgebase!")
+                message="Can't find this knowledgebase!")
         kb_id = kb.id
 
     except Exception as e:
@@ -589,6 +585,7 @@ def list_kb_docs():
     except Exception as e:
         return server_error_response(e)
 
+
 @manager.route('/document/infos', methods=['POST'])
 @validate_request("doc_ids")
 def docinfos():
@@ -596,7 +593,7 @@ def docinfos():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
     req = request.json
     doc_ids = req["doc_ids"]
     docs = DocumentService.get_by_ids(doc_ids)
@@ -610,7 +607,7 @@ def document_rm():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
 
     tenant_id = objs[0].tenant_id
     req = request.json
@@ -622,7 +619,7 @@ def document_rm():
 
         if not doc_ids:
             return get_json_result(
-                data=False, retmsg="Can't find doc_names or doc_ids"
+                data=False, message="Can't find doc_names or doc_ids"
             )
 
     except Exception as e:
@@ -637,16 +634,16 @@ def document_rm():
         try:
             e, doc = DocumentService.get_by_id(doc_id)
             if not e:
-                return get_data_error_result(retmsg="Document not found!")
+                return get_data_error_result(message="Document not found!")
             tenant_id = DocumentService.get_tenant_id(doc_id)
             if not tenant_id:
-                return get_data_error_result(retmsg="Tenant not found!")
+                return get_data_error_result(message="Tenant not found!")
 
             b, n = File2DocumentService.get_storage_address(doc_id=doc_id)
 
             if not DocumentService.remove_document(doc, tenant_id):
                 return get_data_error_result(
-                    retmsg="Database error (Document removal)!")
+                    message="Database error (Document removal)!")
 
             f2d = File2DocumentService.get_by_document_id(doc_id)
             FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.id == f2d[0].file_id])
@@ -657,7 +654,7 @@ def document_rm():
             errors += str(e)
 
     if errors:
-        return get_json_result(data=False, retmsg=errors, retcode=RetCode.SERVER_ERROR)
+        return get_json_result(data=False, message=errors, code=settings.RetCode.SERVER_ERROR)
 
     return get_json_result(data=True)
 
@@ -672,11 +669,11 @@ def completion_faq():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
 
     e, conv = API4ConversationService.get_by_id(req["conversation_id"])
     if not e:
-        return get_data_error_result(retmsg="Conversation not found!")
+        return get_data_error_result(message="Conversation not found!")
     if "quote" not in req: req["quote"] = True
 
     msg = []
@@ -757,7 +754,7 @@ def completion_faq():
         conv.message.append(msg[-1])
         e, dia = DialogService.get_by_id(conv.dialog_id)
         if not e:
-            return get_data_error_result(retmsg="Dialog not found!")
+            return get_data_error_result(message="Dialog not found!")
         del req["conversation_id"]
 
         if not conv.reference:
@@ -809,10 +806,10 @@ def retrieval():
     objs = APIToken.query(token=token)
     if not objs:
         return get_json_result(
-            data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
+            data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
 
     req = request.json
-    kb_ids = req.get("kb_id",[])
+    kb_ids = req.get("kb_id", [])
     doc_ids = req.get("doc_ids", [])
     question = req.get("question")
     page = int(req.get("page", 1))
@@ -826,26 +823,26 @@ def retrieval():
         embd_nms = list(set([kb.embd_id for kb in kbs]))
         if len(embd_nms) != 1:
             return get_json_result(
-                data=False, retmsg='Knowledge bases use different embedding models or does not exist."', retcode=RetCode.AUTHENTICATION_ERROR)
+                data=False, message='Knowledge bases use different embedding models or does not exist."',
+                code=settings.RetCode.AUTHENTICATION_ERROR)
 
         embd_mdl = TenantLLMService.model_instance(
             kbs[0].tenant_id, LLMType.EMBEDDING.value, llm_name=kbs[0].embd_id)
         rerank_mdl = None
         if req.get("rerank_id"):
             rerank_mdl = TenantLLMService.model_instance(
-            kbs[0].tenant_id, LLMType.RERANK.value, llm_name=req["rerank_id"])
+                kbs[0].tenant_id, LLMType.RERANK.value, llm_name=req["rerank_id"])
         if req.get("keyword", False):
             chat_mdl = TenantLLMService.model_instance(kbs[0].tenant_id, LLMType.CHAT)
             question += keyword_extraction(chat_mdl, question)
-        ranks = retrievaler.retrieval(question, embd_mdl, kbs[0].tenant_id, kb_ids, page, size,
-            similarity_threshold, vector_similarity_weight, top,
-            doc_ids, rerank_mdl=rerank_mdl)
+        ranks = settings.retrievaler.retrieval(question, embd_mdl, kbs[0].tenant_id, kb_ids, page, size,
+                                               similarity_threshold, vector_similarity_weight, top,
+                                               doc_ids, rerank_mdl=rerank_mdl)
         for c in ranks["chunks"]:
-            if "vector" in c:
-                del c["vector"]
+            c.pop("vector", None)
         return get_json_result(data=ranks)
     except Exception as e:
         if str(e).find("not_found") > 0:
-            return get_json_result(data=False, retmsg=f'No chunk found! Check the chunk status please!',
-                                   retcode=RetCode.DATA_ERROR)
+            return get_json_result(data=False, message='No chunk found! Check the chunk status please!',
+                                   code=settings.RetCode.DATA_ERROR)
         return server_error_response(e)

api/apps/canvas_app.py

@@ -13,13 +13,13 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import json
+import traceback
 from functools import partial
 from flask import request, Response
 from flask_login import login_required, current_user
 from api.db.services.canvas_service import CanvasTemplateService, UserCanvasService
-from api.db.services.dialog_service import full_question
-from api.db.services.user_service import TenantService
 from api.settings import RetCode
 from api.utils import get_uuid
 from api.utils.api_utils import get_json_result, server_error_response, validate_request, get_data_error_result
@@ -48,8 +48,8 @@ def rm():
     for i in request.json["canvas_ids"]:
         if not UserCanvasService.query(user_id=current_user.id,id=i):
             return get_json_result(
-                data=False, retmsg=f'Only owner of canvas authorized for this operation.',
-                retcode=RetCode.OPERATING_ERROR)
+                data=False, message='Only owner of canvas authorized for this operation.',
+                code=RetCode.OPERATING_ERROR)
         UserCanvasService.delete_by_id(i)
     return get_json_result(data=True)
 
@@ -68,12 +68,12 @@ def save():
             return server_error_response(ValueError("Duplicated title."))
         req["id"] = get_uuid()
         if not UserCanvasService.save(**req):
-            return get_data_error_result(retmsg="Fail to save canvas.")
+            return get_data_error_result(message="Fail to save canvas.")
     else:
         if not UserCanvasService.query(user_id=current_user.id, id=req["id"]):
             return get_json_result(
-                data=False, retmsg=f'Only owner of canvas authorized for this operation.',
-                retcode=RetCode.OPERATING_ERROR)
+                data=False, message='Only owner of canvas authorized for this operation.',
+                code=RetCode.OPERATING_ERROR)
         UserCanvasService.update_by_id(req["id"], req)
     return get_json_result(data=req)
 
@@ -83,7 +83,7 @@ def save():
 def get(canvas_id):
     e, c = UserCanvasService.get_by_id(canvas_id)
     if not e:
-        return get_data_error_result(retmsg="canvas not found.")
+        return get_data_error_result(message="canvas not found.")
     return get_json_result(data=c.to_dict())
 
 
@@ -95,11 +95,11 @@ def run():
     stream = req.get("stream", True)
     e, cvs = UserCanvasService.get_by_id(req["id"])
     if not e:
-        return get_data_error_result(retmsg="canvas not found.")
+        return get_data_error_result(message="canvas not found.")
     if not UserCanvasService.query(user_id=current_user.id, id=req["id"]):
         return get_json_result(
-            data=False, retmsg=f'Only owner of canvas authorized for this operation.',
-            retcode=RetCode.OPERATING_ERROR)
+            data=False, message='Only owner of canvas authorized for this operation.',
+            code=RetCode.OPERATING_ERROR)
 
     if not isinstance(cvs.dsl, str):
         cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False)
@@ -110,39 +110,40 @@ def run():
         canvas = Canvas(cvs.dsl, current_user.id)
         if "message" in req:
             canvas.messages.append({"role": "user", "content": req["message"], "id": message_id})
-            if len([m for m in canvas.messages if m["role"] == "user"]) > 1:
-                ten = TenantService.get_by_user_id(current_user.id)[0]
-                req["message"] = full_question(ten["tenant_id"], ten["llm_id"], canvas.messages)
             canvas.add_user_input(req["message"])
-        answer = canvas.run(stream=stream)
-        print(canvas)
     except Exception as e:
         return server_error_response(e)
 
-    assert answer is not None, "Nothing. Is it over?"
-
     if stream:
-        assert isinstance(answer, partial), "Nothing. Is it over?"
-
         def sse():
             nonlocal answer, cvs
             try:
-                for ans in answer():
+                for ans in canvas.run(stream=True):
+                    if ans.get("running_status"):
+                        yield "data:" + json.dumps({"code": 0, "message": "",
+                                                    "data": {"answer": ans["content"],
+                                                             "running_status": True}},
+                                                   ensure_ascii=False) + "\n\n"
+                        continue
                     for k in ans.keys():
                         final_ans[k] = ans[k]
                     ans = {"answer": ans["content"], "reference": ans.get("reference", [])}
-                    yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": ans}, ensure_ascii=False) + "\n\n"
+                    yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
 
                 canvas.messages.append({"role": "assistant", "content": final_ans["content"], "id": message_id})
+                canvas.history.append(("assistant", final_ans["content"]))
                 if final_ans.get("reference"):
                     canvas.reference.append(final_ans["reference"])
                 cvs.dsl = json.loads(str(canvas))
                 UserCanvasService.update_by_id(req["id"], cvs.to_dict())
             except Exception as e:
-                yield "data:" + json.dumps({"retcode": 500, "retmsg": str(e),
+                cvs.dsl = json.loads(str(canvas))
+                UserCanvasService.update_by_id(req["id"], cvs.to_dict())
+                traceback.print_exc()
+                yield "data:" + json.dumps({"code": 500, "message": str(e),
                                             "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
                                            ensure_ascii=False) + "\n\n"
-            yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": True}, ensure_ascii=False) + "\n\n"
+            yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
 
         resp = Response(sse(), mimetype="text/event-stream")
         resp.headers.add_header("Cache-control", "no-cache")
@@ -151,13 +152,15 @@ def run():
         resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
         return resp
 
-    final_ans["content"] = "\n".join(answer["content"]) if "content" in answer else ""
-    canvas.messages.append({"role": "assistant", "content": final_ans["content"], "id": message_id})
-    if final_ans.get("reference"):
-        canvas.reference.append(final_ans["reference"])
-    cvs.dsl = json.loads(str(canvas))
-    UserCanvasService.update_by_id(req["id"], cvs.to_dict())
-    return get_json_result(data={"answer": final_ans["content"], "reference": final_ans.get("reference", [])})
+    for answer in canvas.run(stream=False):
+        if answer.get("running_status"): continue
+        final_ans["content"] = "\n".join(answer["content"]) if "content" in answer else ""
+        canvas.messages.append({"role": "assistant", "content": final_ans["content"], "id": message_id})
+        if final_ans.get("reference"):
+            canvas.reference.append(final_ans["reference"])
+        cvs.dsl = json.loads(str(canvas))
+        UserCanvasService.update_by_id(req["id"], cvs.to_dict())
+        return get_json_result(data={"answer": final_ans["content"], "reference": final_ans.get("reference", [])})
 
 
 @manager.route('/reset', methods=['POST'])
@@ -168,11 +171,11 @@ def reset():
     try:
         e, user_canvas = UserCanvasService.get_by_id(req["id"])
         if not e:
-            return get_data_error_result(retmsg="canvas not found.")
+            return get_data_error_result(message="canvas not found.")
         if not UserCanvasService.query(user_id=current_user.id, id=req["id"]):
             return get_json_result(
-                data=False, retmsg=f'Only owner of canvas authorized for this operation.',
-                retcode=RetCode.OPERATING_ERROR)
+                data=False, message='Only owner of canvas authorized for this operation.',
+                code=RetCode.OPERATING_ERROR)
 
         canvas = Canvas(json.dumps(user_canvas.dsl), current_user.id)
         canvas.reset()

api/apps/chunk_app.py

@@ -15,15 +15,13 @@
 #
 import datetime
 import json
-import traceback
 
 from flask import request
 from flask_login import login_required, current_user
-from elasticsearch_dsl import Q
 
+from api.db.services.dialog_service import keyword_extraction
 from rag.app.qa import rmPrefix, beAdoc
-from rag.nlp import search, rag_tokenizer, keyword_extraction
-from rag.utils.es_conn import ELASTICSEARCH
+from rag.nlp import search, rag_tokenizer
 from rag.utils import rmSpace
 from api.db import LLMType, ParserType
 from api.db.services.knowledgebase_service import KnowledgebaseService
@@ -31,7 +29,7 @@ from api.db.services.llm_service import LLMBundle
 from api.db.services.user_service import UserTenantService
 from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
 from api.db.services.document_service import DocumentService
-from api.settings import RetCode, retrievaler, kg_retrievaler
+from api import settings
 from api.utils.api_utils import get_json_result
 import hashlib
 import re
@@ -49,16 +47,17 @@ def list_chunk():
     try:
         tenant_id = DocumentService.get_tenant_id(req["doc_id"])
         if not tenant_id:
-            return get_data_error_result(retmsg="Tenant not found!")
+            return get_data_error_result(message="Tenant not found!")
         e, doc = DocumentService.get_by_id(doc_id)
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
+        kb_ids = KnowledgebaseService.get_kb_ids(tenant_id)
         query = {
             "doc_ids": [doc_id], "page": page, "size": size, "question": question, "sort": True
         }
         if "available_int" in req:
             query["available_int"] = int(req["available_int"])
-        sres = retrievaler.search(query, search.index_name(tenant_id), highlight=True)
+        sres = settings.retrievaler.search(query, search.index_name(tenant_id), kb_ids, highlight=True)
         res = {"total": sres.total, "chunks": [], "doc": doc.to_dict()}
         for id in sres.ids:
             d = {
@@ -69,22 +68,18 @@ def list_chunk():
                 "doc_id": sres.field[id]["doc_id"],
                 "docnm_kwd": sres.field[id]["docnm_kwd"],
                 "important_kwd": sres.field[id].get("important_kwd", []),
-                "img_id": sres.field[id].get("img_id", ""),
+                "image_id": sres.field[id].get("img_id", ""),
                 "available_int": sres.field[id].get("available_int", 1),
-                "positions": sres.field[id].get("position_int", "").split("\t")
+                "positions": json.loads(sres.field[id].get("position_list", "[]")),
             }
-            if len(d["positions"]) % 5 == 0:
-                poss = []
-                for i in range(0, len(d["positions"]), 5):
-                    poss.append([float(d["positions"][i]), float(d["positions"][i + 1]), float(d["positions"][i + 2]),
-                                 float(d["positions"][i + 3]), float(d["positions"][i + 4])])
-                d["positions"] = poss
+            assert isinstance(d["positions"], list)
+            assert len(d["positions"]) == 0 or (isinstance(d["positions"][0], list) and len(d["positions"][0]) == 5)
             res["chunks"].append(d)
         return get_json_result(data=res)
     except Exception as e:
         if str(e).find("not_found") > 0:
-            return get_json_result(data=False, retmsg=f'No chunk found!',
-                                   retcode=RetCode.DATA_ERROR)
+            return get_json_result(data=False, message='No chunk found!',
+                                   code=settings.RetCode.DATA_ERROR)
         return server_error_response(e)
 
 
@@ -95,27 +90,25 @@ def get():
     try:
         tenants = UserTenantService.query(user_id=current_user.id)
         if not tenants:
-            return get_data_error_result(retmsg="Tenant not found!")
-        res = ELASTICSEARCH.get(
-            chunk_id, search.index_name(
-                tenants[0].tenant_id))
-        if not res.get("found"):
+            return get_data_error_result(message="Tenant not found!")
+        tenant_id = tenants[0].tenant_id
+
+        kb_ids = KnowledgebaseService.get_kb_ids(tenant_id)
+        chunk = settings.docStoreConn.get(chunk_id, search.index_name(tenant_id), kb_ids)
+        if chunk is None:
             return server_error_response("Chunk not found")
-        id = res["_id"]
-        res = res["_source"]
-        res["chunk_id"] = id
         k = []
-        for n in res.keys():
+        for n in chunk.keys():
             if re.search(r"(_vec$|_sm_|_tks|_ltks)", n):
                 k.append(n)
         for n in k:
-            del res[n]
+            del chunk[n]
 
-        return get_json_result(data=res)
+        return get_json_result(data=chunk)
     except Exception as e:
         if str(e).find("NotFoundError") >= 0:
-            return get_json_result(data=False, retmsg=f'Chunk not found!',
-                                   retcode=RetCode.DATA_ERROR)
+            return get_json_result(data=False, message='Chunk not found!',
+                                   code=settings.RetCode.DATA_ERROR)
         return server_error_response(e)
 
 
@@ -138,14 +131,14 @@ def set():
     try:
         tenant_id = DocumentService.get_tenant_id(req["doc_id"])
         if not tenant_id:
-            return get_data_error_result(retmsg="Tenant not found!")
+            return get_data_error_result(message="Tenant not found!")
 
         embd_id = DocumentService.get_embd_id(req["doc_id"])
         embd_mdl = LLMBundle(tenant_id, LLMType.EMBEDDING, embd_id)
 
         e, doc = DocumentService.get_by_id(req["doc_id"])
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
 
         if doc.parser_id == ParserType.QA:
             arr = [
@@ -154,7 +147,7 @@ def set():
                     req["content_with_weight"]) if len(t) > 1]
             if len(arr) != 2:
                 return get_data_error_result(
-                    retmsg="Q&A must be separated by TAB/ENTER key.")
+                    message="Q&A must be separated by TAB/ENTER key.")
             q, a = rmPrefix(arr[0]), rmPrefix(arr[1])
             d = beAdoc(d, arr[0], arr[1], not any(
                 [rag_tokenizer.is_chinese(t) for t in q + a]))
@@ -162,7 +155,7 @@ def set():
         v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
         v = 0.1 * v[0] + 0.9 * v[1] if doc.parser_id != ParserType.QA else v[1]
         d["q_%d_vec" % len(v)] = v.tolist()
-        ELASTICSEARCH.upsert([d], search.index_name(tenant_id))
+        settings.docStoreConn.insert([d], search.index_name(tenant_id), doc.kb_id)
         return get_json_result(data=True)
     except Exception as e:
         return server_error_response(e)
@@ -174,12 +167,15 @@ def set():
 def switch():
     req = request.json
     try:
-        tenant_id = DocumentService.get_tenant_id(req["doc_id"])
-        if not tenant_id:
-            return get_data_error_result(retmsg="Tenant not found!")
-        if not ELASTICSEARCH.upsert([{"id": i, "available_int": int(req["available_int"])} for i in req["chunk_ids"]],
-                                    search.index_name(tenant_id)):
-            return get_data_error_result(retmsg="Index updating failure")
+        e, doc = DocumentService.get_by_id(req["doc_id"])
+        if not e:
+            return get_data_error_result(message="Document not found!")
+        for cid in req["chunk_ids"]:
+            if not settings.docStoreConn.update({"id": cid},
+                                                {"available_int": int(req["available_int"])},
+                                                search.index_name(DocumentService.get_tenant_id(req["doc_id"])),
+                                                doc.kb_id):
+                return get_data_error_result(message="Index updating failure")
         return get_json_result(data=True)
     except Exception as e:
         return server_error_response(e)
@@ -191,12 +187,11 @@ def switch():
 def rm():
     req = request.json
     try:
-        if not ELASTICSEARCH.deleteByQuery(
-                Q("ids", values=req["chunk_ids"]), search.index_name(current_user.id)):
-            return get_data_error_result(retmsg="Index updating failure")
         e, doc = DocumentService.get_by_id(req["doc_id"])
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
+        if not settings.docStoreConn.delete({"id": req["chunk_ids"]}, search.index_name(current_user.id), doc.kb_id):
+            return get_data_error_result(message="Index updating failure")
         deleted_chunk_ids = req["chunk_ids"]
         chunk_number = len(deleted_chunk_ids)
         DocumentService.decrement_chunk_num(doc.id, doc.kb_id, 1, chunk_number, 0)
@@ -224,14 +219,14 @@ def create():
     try:
         e, doc = DocumentService.get_by_id(req["doc_id"])
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
         d["kb_id"] = [doc.kb_id]
         d["docnm_kwd"] = doc.name
         d["doc_id"] = doc.id
 
         tenant_id = DocumentService.get_tenant_id(req["doc_id"])
         if not tenant_id:
-            return get_data_error_result(retmsg="Tenant not found!")
+            return get_data_error_result(message="Tenant not found!")
 
         embd_id = DocumentService.get_embd_id(req["doc_id"])
         embd_mdl = LLMBundle(tenant_id, LLMType.EMBEDDING.value, embd_id)
@@ -239,7 +234,7 @@ def create():
         v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
         v = 0.1 * v[0] + 0.9 * v[1]
         d["q_%d_vec" % len(v)] = v.tolist()
-        ELASTICSEARCH.upsert([d], search.index_name(tenant_id))
+        settings.docStoreConn.insert([d], search.index_name(tenant_id), doc.kb_id)
 
         DocumentService.increment_chunk_num(
             doc.id, doc.kb_id, c, 1, 0)
@@ -256,28 +251,31 @@ def retrieval_test():
     page = int(req.get("page", 1))
     size = int(req.get("size", 30))
     question = req["question"]
-    kb_id = req["kb_id"]
-    if isinstance(kb_id, str): kb_id = [kb_id]
+    kb_ids = req["kb_id"]
+    if isinstance(kb_ids, str):
+        kb_ids = [kb_ids]
     doc_ids = req.get("doc_ids", [])
     similarity_threshold = float(req.get("similarity_threshold", 0.0))
     vector_similarity_weight = float(req.get("vector_similarity_weight", 0.3))
     top = int(req.get("top_k", 1024))
+    tenant_ids = []
 
     try:
         tenants = UserTenantService.query(user_id=current_user.id)
-        for kid in kb_id:
+        for kb_id in kb_ids:
             for tenant in tenants:
                 if KnowledgebaseService.query(
-                        tenant_id=tenant.tenant_id, id=kid):
+                        tenant_id=tenant.tenant_id, id=kb_id):
+                    tenant_ids.append(tenant.tenant_id)
                     break
             else:
                 return get_json_result(
-                    data=False, retmsg=f'Only owner of knowledgebase authorized for this operation.',
-                    retcode=RetCode.OPERATING_ERROR)
+                    data=False, message='Only owner of knowledgebase authorized for this operation.',
+                    code=settings.RetCode.OPERATING_ERROR)
 
-        e, kb = KnowledgebaseService.get_by_id(kb_id[0])
+        e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
         if not e:
-            return get_data_error_result(retmsg="Knowledgebase not found!")
+            return get_data_error_result(message="Knowledgebase not found!")
 
         embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
 
@@ -289,19 +287,18 @@ def retrieval_test():
             chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
             question += keyword_extraction(chat_mdl, question)
 
-        retr = retrievaler if kb.parser_id != ParserType.KG else kg_retrievaler
-        ranks = retr.retrieval(question, embd_mdl, kb.tenant_id, kb_id, page, size,
+        retr = settings.retrievaler if kb.parser_id != ParserType.KG else settings.kg_retrievaler
+        ranks = retr.retrieval(question, embd_mdl, tenant_ids, kb_ids, page, size,
                                similarity_threshold, vector_similarity_weight, top,
                                doc_ids, rerank_mdl=rerank_mdl, highlight=req.get("highlight"))
         for c in ranks["chunks"]:
-            if "vector" in c:
-                del c["vector"]
+            c.pop("vector", None)
 
         return get_json_result(data=ranks)
     except Exception as e:
         if str(e).find("not_found") > 0:
-            return get_json_result(data=False, retmsg=f'No chunk found! Check the chunk status please!',
-                                   retcode=RetCode.DATA_ERROR)
+            return get_json_result(data=False, message='No chunk found! Check the chunk status please!',
+                                   code=settings.RetCode.DATA_ERROR)
         return server_error_response(e)
 
 
@@ -309,19 +306,38 @@ def retrieval_test():
 @login_required
 def knowledge_graph():
     doc_id = request.args["doc_id"]
+    tenant_id = DocumentService.get_tenant_id(doc_id)
+    kb_ids = KnowledgebaseService.get_kb_ids(tenant_id)
     req = {
-        "doc_ids":[doc_id],
+        "doc_ids": [doc_id],
         "knowledge_graph_kwd": ["graph", "mind_map"]
     }
-    tenant_id = DocumentService.get_tenant_id(doc_id)
-    sres = retrievaler.search(req, search.index_name(tenant_id))
+    sres = settings.retrievaler.search(req, search.index_name(tenant_id), kb_ids)
     obj = {"graph": {}, "mind_map": {}}
     for id in sres.ids[:2]:
         ty = sres.field[id]["knowledge_graph_kwd"]
         try:
-            obj[ty] = json.loads(sres.field[id]["content_with_weight"])
-        except Exception as e:
-            print(traceback.format_exc(), flush=True)
+            content_json = json.loads(sres.field[id]["content_with_weight"])
+        except Exception:
+            continue
+
+        if ty == 'mind_map':
+            node_dict = {}
+
+            def repeat_deal(content_json, node_dict):
+                if 'id' in content_json:
+                    if content_json['id'] in node_dict:
+                        node_name = content_json['id']
+                        content_json['id'] += f"({node_dict[content_json['id']]})"
+                        node_dict[node_name] += 1
+                    else:
+                        node_dict[content_json['id']] = 1
+                if 'children' in content_json and content_json['children']:
+                    for item in content_json['children']:
+                        repeat_deal(item, node_dict)
+
+            repeat_deal(content_json, node_dict)
+
+        obj[ty] = content_json
 
     return get_json_result(data=obj)
-

api/apps/conversation_app.py

@@ -25,8 +25,7 @@ from api.db import LLMType
 from api.db.services.dialog_service import DialogService, ConversationService, chat, ask
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMBundle, TenantService, TenantLLMService
-from api.settings import RetCode, retrievaler
-from api.utils import get_uuid
+from api import settings
 from api.utils.api_utils import get_json_result
 from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
 from graphrag.mind_map_extractor import MindMapExtractor
@@ -43,11 +42,11 @@ def set_conversation():
         del req["conversation_id"]
         try:
             if not ConversationService.update_by_id(conv_id, req):
-                return get_data_error_result(retmsg="Conversation not found!")
+                return get_data_error_result(message="Conversation not found!")
             e, conv = ConversationService.get_by_id(conv_id)
             if not e:
                 return get_data_error_result(
-                    retmsg="Fail to update a conversation!")
+                    message="Fail to update a conversation!")
             conv = conv.to_dict()
             return get_json_result(data=conv)
         except Exception as e:
@@ -56,7 +55,7 @@ def set_conversation():
     try:
         e, dia = DialogService.get_by_id(req["dialog_id"])
         if not e:
-            return get_data_error_result(retmsg="Dialog not found")
+            return get_data_error_result(message="Dialog not found")
         conv = {
             "id": conv_id,
             "dialog_id": req["dialog_id"],
@@ -66,7 +65,7 @@ def set_conversation():
         ConversationService.save(**conv)
         e, conv = ConversationService.get_by_id(conv["id"])
         if not e:
-            return get_data_error_result(retmsg="Fail to new a conversation!")
+            return get_data_error_result(message="Fail to new a conversation!")
         conv = conv.to_dict()
         return get_json_result(data=conv)
     except Exception as e:
@@ -80,15 +79,15 @@ def get():
     try:
         e, conv = ConversationService.get_by_id(conv_id)
         if not e:
-            return get_data_error_result(retmsg="Conversation not found!")
+            return get_data_error_result(message="Conversation not found!")
         tenants = UserTenantService.query(user_id=current_user.id)
         for tenant in tenants:
             if DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id):
                 break
         else:
             return get_json_result(
-                data=False, retmsg=f'Only owner of conversation authorized for this operation.',
-                retcode=RetCode.OPERATING_ERROR)
+                data=False, message='Only owner of conversation authorized for this operation.',
+                code=settings.RetCode.OPERATING_ERROR)
         conv = conv.to_dict()
         return get_json_result(data=conv)
     except Exception as e:
@@ -103,15 +102,15 @@ def rm():
         for cid in conv_ids:
             exist, conv = ConversationService.get_by_id(cid)
             if not exist:
-                return get_data_error_result(retmsg="Conversation not found!")
+                return get_data_error_result(message="Conversation not found!")
             tenants = UserTenantService.query(user_id=current_user.id)
             for tenant in tenants:
                 if DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id):
                     break
             else:
                 return get_json_result(
-                    data=False, retmsg=f'Only owner of conversation authorized for this operation.',
-                    retcode=RetCode.OPERATING_ERROR)
+                    data=False, message='Only owner of conversation authorized for this operation.',
+                    code=settings.RetCode.OPERATING_ERROR)
             ConversationService.delete_by_id(cid)
         return get_json_result(data=True)
     except Exception as e:
@@ -125,8 +124,8 @@ def list_convsersation():
     try:
         if not DialogService.query(tenant_id=current_user.id, id=dialog_id):
             return get_json_result(
-                data=False, retmsg=f'Only owner of dialog authorized for this operation.',
-                retcode=RetCode.OPERATING_ERROR)
+                data=False, message='Only owner of dialog authorized for this operation.',
+                code=settings.RetCode.OPERATING_ERROR)
         convs = ConversationService.query(
             dialog_id=dialog_id,
             order_by=ConversationService.model.create_time,
@@ -142,9 +141,6 @@ def list_convsersation():
 @validate_request("conversation_id", "messages")
 def completion():
     req = request.json
-    # req = {"conversation_id": "9aaaca4c11d311efa461fa163e197198", "messages": [
-    #    {"role": "user", "content": "上海有吗？"}
-    # ]}
     msg = []
     for m in req["messages"]:
         if m["role"] == "system":
@@ -156,11 +152,11 @@ def completion():
     try:
         e, conv = ConversationService.get_by_id(req["conversation_id"])
         if not e:
-            return get_data_error_result(retmsg="Conversation not found!")
+            return get_data_error_result(message="Conversation not found!")
         conv.message = deepcopy(req["messages"])
         e, dia = DialogService.get_by_id(conv.dialog_id)
         if not e:
-            return get_data_error_result(retmsg="Dialog not found!")
+            return get_data_error_result(message="Dialog not found!")
         del req["conversation_id"]
         del req["messages"]
 
@@ -184,13 +180,14 @@ def completion():
             try:
                 for ans in chat(dia, msg, True, **req):
                     fillin_conv(ans)
-                    yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": ans}, ensure_ascii=False) + "\n\n"
+                    yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
                 ConversationService.update_by_id(conv.id, conv.to_dict())
             except Exception as e:
-                yield "data:" + json.dumps({"retcode": 500, "retmsg": str(e),
+                traceback.print_exc()
+                yield "data:" + json.dumps({"code": 500, "message": str(e),
                                             "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
                                            ensure_ascii=False) + "\n\n"
-            yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": True}, ensure_ascii=False) + "\n\n"
+            yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
 
         if req.get("stream", True):
             resp = Response(stream(), mimetype="text/event-stream")
@@ -218,13 +215,13 @@ def tts():
     req = request.json
     text = req["text"]
 
-    tenants = TenantService.get_by_user_id(current_user.id)
+    tenants = TenantService.get_info_by(current_user.id)
     if not tenants:
-        return get_data_error_result(retmsg="Tenant not found!")
+        return get_data_error_result(message="Tenant not found!")
 
     tts_id = tenants[0]["tts_id"]
     if not tts_id:
-        return get_data_error_result(retmsg="No default TTS model is set")
+        return get_data_error_result(message="No default TTS model is set")
 
     tts_mdl = LLMBundle(tenants[0]["tenant_id"], LLMType.TTS, tts_id)
 
@@ -234,7 +231,7 @@ def tts():
                 for chunk in tts_mdl.tts(txt):
                     yield chunk
         except Exception as e:
-            yield ("data:" + json.dumps({"retcode": 500, "retmsg": str(e),
+            yield ("data:" + json.dumps({"code": 500, "message": str(e),
                                          "data": {"answer": "**ERROR**: " + str(e)}},
                                         ensure_ascii=False)).encode('utf-8')
 
@@ -253,7 +250,7 @@ def delete_msg():
     req = request.json
     e, conv = ConversationService.get_by_id(req["conversation_id"])
     if not e:
-        return get_data_error_result(retmsg="Conversation not found!")
+        return get_data_error_result(message="Conversation not found!")
 
     conv = conv.to_dict()
     for i, msg in enumerate(conv["message"]):
@@ -276,7 +273,7 @@ def thumbup():
     req = request.json
     e, conv = ConversationService.get_by_id(req["conversation_id"])
     if not e:
-        return get_data_error_result(retmsg="Conversation not found!")
+        return get_data_error_result(message="Conversation not found!")
     up_down = req.get("set")
     feedback = req.get("feedback", "")
     conv = conv.to_dict()
@@ -300,16 +297,17 @@ def thumbup():
 def ask_about():
     req = request.json
     uid = current_user.id
+
     def stream():
         nonlocal req, uid
         try:
             for ans in ask(req["question"], req["kb_ids"], uid):
-                yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": ans}, ensure_ascii=False) + "\n\n"
+                yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
         except Exception as e:
-            yield "data:" + json.dumps({"retcode": 500, "retmsg": str(e),
+            yield "data:" + json.dumps({"code": 500, "message": str(e),
                                         "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
                                        ensure_ascii=False) + "\n\n"
-        yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": True}, ensure_ascii=False) + "\n\n"
+        yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
 
     resp = Response(stream(), mimetype="text/event-stream")
     resp.headers.add_header("Cache-control", "no-cache")
@@ -327,13 +325,13 @@ def mindmap():
     kb_ids = req["kb_ids"]
     e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
     if not e:
-        return get_data_error_result(retmsg="Knowledgebase not found!")
+        return get_data_error_result(message="Knowledgebase not found!")
 
     embd_mdl = TenantLLMService.model_instance(
         kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
     chat_mdl = LLMBundle(current_user.id, LLMType.CHAT)
-    ranks = retrievaler.retrieval(req["question"], embd_mdl, kb.tenant_id, kb_ids, 1, 12,
-                           0.3, 0.3, aggs=False)
+    ranks = settings.retrievaler.retrieval(req["question"], embd_mdl, kb.tenant_id, kb_ids, 1, 12,
+                                           0.3, 0.3, aggs=False)
     mindmap = MindMapExtractor(chat_mdl)
     mind_map = mindmap([c["content_with_weight"] for c in ranks["chunks"]]).output
     if "error" in mind_map:

api/apps/dataset_api.py

@@ -1,880 +0,0 @@
-#
-#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
-#
-#  Licensed under the Apache License, Version 2.0 (the "License");
-#  you may not use this file except in compliance with the License.
-#  You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-#  Unless required by applicable law or agreed to in writing, software
-#  distributed under the License is distributed on an "AS IS" BASIS,
-#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#  See the License for the specific language governing permissions and
-#  limitations under the License.
-import os
-import pathlib
-import re
-import warnings
-from functools import partial
-from io import BytesIO
-
-from elasticsearch_dsl import Q
-from flask import request, send_file
-from flask_login import login_required, current_user
-from httpx import HTTPError
-
-from api.contants import NAME_LENGTH_LIMIT
-from api.db import FileType, ParserType, FileSource, TaskStatus
-from api.db import StatusEnum
-from api.db.db_models import File
-from api.db.services import duplicate_name
-from api.db.services.document_service import DocumentService
-from api.db.services.file2document_service import File2DocumentService
-from api.db.services.file_service import FileService
-from api.db.services.knowledgebase_service import KnowledgebaseService
-from api.db.services.user_service import TenantService
-from api.settings import RetCode
-from api.utils import get_uuid
-from api.utils.api_utils import construct_json_result, construct_error_response
-from api.utils.api_utils import construct_result, validate_request
-from api.utils.file_utils import filename_type, thumbnail
-from rag.app import book, laws, manual, naive, one, paper, presentation, qa, resume, table, picture, audio, email
-from rag.nlp import search
-from rag.utils.es_conn import ELASTICSEARCH
-from rag.utils.storage_factory import STORAGE_IMPL
-
-MAXIMUM_OF_UPLOADING_FILES = 256
-
-
-# ------------------------------ create a dataset ---------------------------------------
-
-@manager.route("/", methods=["POST"])
-@login_required  # use login
-@validate_request("name")  # check name key
-def create_dataset():
-    # Check if Authorization header is present
-    authorization_token = request.headers.get("Authorization")
-    if not authorization_token:
-        return construct_json_result(code=RetCode.AUTHENTICATION_ERROR, message="Authorization header is missing.")
-
-    # TODO: Login or API key
-    # objs = APIToken.query(token=authorization_token)
-    #
-    # # Authorization error
-    # if not objs:
-    #     return construct_json_result(code=RetCode.AUTHENTICATION_ERROR, message="Token is invalid.")
-    #
-    # tenant_id = objs[0].tenant_id
-
-    tenant_id = current_user.id
-    request_body = request.json
-
-    # In case that there's no name
-    if "name" not in request_body:
-        return construct_json_result(code=RetCode.DATA_ERROR, message="Expected 'name' field in request body")
-
-    dataset_name = request_body["name"]
-
-    # empty dataset_name
-    if not dataset_name:
-        return construct_json_result(code=RetCode.DATA_ERROR, message="Empty dataset name")
-
-    # In case that there's space in the head or the tail
-    dataset_name = dataset_name.strip()
-
-    # In case that the length of the name exceeds the limit
-    dataset_name_length = len(dataset_name)
-    if dataset_name_length > NAME_LENGTH_LIMIT:
-        return construct_json_result(
-            code=RetCode.DATA_ERROR,
-            message=f"Dataset name: {dataset_name} with length {dataset_name_length} exceeds {NAME_LENGTH_LIMIT}!")
-
-    # In case that there are other fields in the data-binary
-    if len(request_body.keys()) > 1:
-        name_list = []
-        for key_name in request_body.keys():
-            if key_name != "name":
-                name_list.append(key_name)
-        return construct_json_result(code=RetCode.DATA_ERROR,
-                                     message=f"fields: {name_list}, are not allowed in request body.")
-
-    # If there is a duplicate name, it will modify it to make it unique
-    request_body["name"] = duplicate_name(
-        KnowledgebaseService.query,
-        name=dataset_name,
-        tenant_id=tenant_id,
-        status=StatusEnum.VALID.value)
-    try:
-        request_body["id"] = get_uuid()
-        request_body["tenant_id"] = tenant_id
-        request_body["created_by"] = tenant_id
-        exist, t = TenantService.get_by_id(tenant_id)
-        if not exist:
-            return construct_result(code=RetCode.AUTHENTICATION_ERROR, message="Tenant not found.")
-        request_body["embd_id"] = t.embd_id
-        if not KnowledgebaseService.save(**request_body):
-            # failed to create new dataset
-            return construct_result()
-        return construct_json_result(code=RetCode.SUCCESS,
-                                     data={"dataset_name": request_body["name"], "dataset_id": request_body["id"]})
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# -----------------------------list datasets-------------------------------------------------------
-
-@manager.route("/", methods=["GET"])
-@login_required
-def list_datasets():
-    offset = request.args.get("offset", 0)
-    count = request.args.get("count", -1)
-    orderby = request.args.get("orderby", "create_time")
-    desc = request.args.get("desc", True)
-    try:
-        tenants = TenantService.get_joined_tenants_by_user_id(current_user.id)
-        datasets = KnowledgebaseService.get_by_tenant_ids_by_offset(
-            [m["tenant_id"] for m in tenants], current_user.id, int(offset), int(count), orderby, desc)
-        return construct_json_result(data=datasets, code=RetCode.SUCCESS, message=f"List datasets successfully!")
-    except Exception as e:
-        return construct_error_response(e)
-    except HTTPError as http_err:
-        return construct_json_result(http_err)
-
-
-# ---------------------------------delete a dataset ----------------------------
-
-@manager.route("/<dataset_id>", methods=["DELETE"])
-@login_required
-def remove_dataset(dataset_id):
-    try:
-        datasets = KnowledgebaseService.query(created_by=current_user.id, id=dataset_id)
-
-        # according to the id, searching for the dataset
-        if not datasets:
-            return construct_json_result(message=f"The dataset cannot be found for your current account.",
-                                         code=RetCode.OPERATING_ERROR)
-
-        # Iterating the documents inside the dataset
-        for doc in DocumentService.query(kb_id=dataset_id):
-            if not DocumentService.remove_document(doc, datasets[0].tenant_id):
-                # the process of deleting failed
-                return construct_json_result(code=RetCode.DATA_ERROR,
-                                             message="There was an error during the document removal process. "
-                                                     "Please check the status of the RAGFlow server and try the removal again.")
-            # delete the other files
-            f2d = File2DocumentService.get_by_document_id(doc.id)
-            FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.id == f2d[0].file_id])
-            File2DocumentService.delete_by_document_id(doc.id)
-
-        # delete the dataset
-        if not KnowledgebaseService.delete_by_id(dataset_id):
-            return construct_json_result(code=RetCode.DATA_ERROR,
-                                         message="There was an error during the dataset removal process. "
-                                                 "Please check the status of the RAGFlow server and try the removal again.")
-        # success
-        return construct_json_result(code=RetCode.SUCCESS, message=f"Remove dataset: {dataset_id} successfully")
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# ------------------------------ get details of a dataset ----------------------------------------
-
-@manager.route("/<dataset_id>", methods=["GET"])
-@login_required
-def get_dataset(dataset_id):
-    try:
-        dataset = KnowledgebaseService.get_detail(dataset_id)
-        if not dataset:
-            return construct_json_result(code=RetCode.DATA_ERROR, message="Can't find this dataset!")
-        return construct_json_result(data=dataset, code=RetCode.SUCCESS)
-    except Exception as e:
-        return construct_json_result(e)
-
-
-# ------------------------------ update a dataset --------------------------------------------
-
-@manager.route("/<dataset_id>", methods=["PUT"])
-@login_required
-def update_dataset(dataset_id):
-    req = request.json
-    try:
-        # the request cannot be empty
-        if not req:
-            return construct_json_result(code=RetCode.DATA_ERROR, message="Please input at least one parameter that "
-                                                                          "you want to update!")
-        # check whether the dataset can be found
-        if not KnowledgebaseService.query(created_by=current_user.id, id=dataset_id):
-            return construct_json_result(message=f"Only the owner of knowledgebase is authorized for this operation!",
-                                         code=RetCode.OPERATING_ERROR)
-
-        exist, dataset = KnowledgebaseService.get_by_id(dataset_id)
-        # check whether there is this dataset
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR, message="This dataset cannot be found!")
-
-        if "name" in req:
-            name = req["name"].strip()
-            # check whether there is duplicate name
-            if name.lower() != dataset.name.lower() \
-                    and len(KnowledgebaseService.query(name=name, tenant_id=current_user.id,
-                                                       status=StatusEnum.VALID.value)) > 1:
-                return construct_json_result(code=RetCode.DATA_ERROR,
-                                             message=f"The name: {name.lower()} is already used by other "
-                                                     f"datasets. Please choose a different name.")
-
-        dataset_updating_data = {}
-        chunk_num = req.get("chunk_num")
-        # modify the value of 11 parameters
-
-        # 2 parameters: embedding id and chunk method
-        # only if chunk_num is 0, the user can update the embedding id
-        if req.get("embedding_model_id"):
-            if chunk_num == 0:
-                dataset_updating_data["embd_id"] = req["embedding_model_id"]
-            else:
-                return construct_json_result(code=RetCode.DATA_ERROR,
-                                             message="You have already parsed the document in this "
-                                                     "dataset, so you cannot change the embedding "
-                                                     "model.")
-        # only if chunk_num is 0, the user can update the chunk_method
-        if "chunk_method" in req:
-            type_value = req["chunk_method"]
-            if is_illegal_value_for_enum(type_value, ParserType):
-                return construct_json_result(message=f"Illegal value {type_value} for 'chunk_method' field.",
-                                             code=RetCode.DATA_ERROR)
-            if chunk_num != 0:
-                construct_json_result(code=RetCode.DATA_ERROR, message="You have already parsed the document "
-                                                                       "in this dataset, so you cannot "
-                                                                       "change the chunk method.")
-            dataset_updating_data["parser_id"] = req["template_type"]
-
-        # convert the photo parameter to avatar
-        if req.get("photo"):
-            dataset_updating_data["avatar"] = req["photo"]
-
-        # layout_recognize
-        if "layout_recognize" in req:
-            if "parser_config" not in dataset_updating_data:
-                dataset_updating_data['parser_config'] = {}
-            dataset_updating_data['parser_config']['layout_recognize'] = req['layout_recognize']
-
-        # TODO: updating use_raptor needs to construct a class
-
-        # 6 parameters
-        for key in ["name", "language", "description", "permission", "id", "token_num"]:
-            if key in req:
-                dataset_updating_data[key] = req.get(key)
-
-        # update
-        if not KnowledgebaseService.update_by_id(dataset.id, dataset_updating_data):
-            return construct_json_result(code=RetCode.OPERATING_ERROR, message="Failed to update! "
-                                                                               "Please check the status of RAGFlow "
-                                                                               "server and try again!")
-
-        exist, dataset = KnowledgebaseService.get_by_id(dataset.id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR, message="Failed to get the dataset "
-                                                                          "using the dataset ID.")
-
-        return construct_json_result(data=dataset.to_json(), code=RetCode.SUCCESS)
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# --------------------------------content management ----------------------------------------------
-
-# ----------------------------upload files-----------------------------------------------------
-@manager.route("/<dataset_id>/documents/", methods=["POST"])
-@login_required
-def upload_documents(dataset_id):
-    # no files
-    if not request.files:
-        return construct_json_result(
-            message="There is no file!", code=RetCode.ARGUMENT_ERROR)
-
-    # the number of uploading files exceeds the limit
-    file_objs = request.files.getlist("file")
-    num_file_objs = len(file_objs)
-
-    if num_file_objs > MAXIMUM_OF_UPLOADING_FILES:
-        return construct_json_result(code=RetCode.DATA_ERROR, message=f"You try to upload {num_file_objs} files, "
-                                                                      f"which exceeds the maximum number of uploading files: {MAXIMUM_OF_UPLOADING_FILES}")
-
-    # no dataset
-    exist, dataset = KnowledgebaseService.get_by_id(dataset_id)
-    if not exist:
-        return construct_json_result(message="Can't find this dataset", code=RetCode.DATA_ERROR)
-
-    for file_obj in file_objs:
-        file_name = file_obj.filename
-        # no name
-        if not file_name:
-            return construct_json_result(
-                message="There is a file without name!", code=RetCode.ARGUMENT_ERROR)
-
-        # TODO: support the remote files
-        if 'http' in file_name:
-            return construct_json_result(code=RetCode.ARGUMENT_ERROR, message="Remote files have not unsupported.")
-
-    # get the root_folder
-    root_folder = FileService.get_root_folder(current_user.id)
-    # get the id of the root_folder
-    parent_file_id = root_folder["id"]  # document id
-    # this is for the new user, create '.knowledgebase' file
-    FileService.init_knowledgebase_docs(parent_file_id, current_user.id)
-    # go inside this folder, get the kb_root_folder
-    kb_root_folder = FileService.get_kb_folder(current_user.id)
-    # link the file management to the kb_folder
-    kb_folder = FileService.new_a_file_from_kb(dataset.tenant_id, dataset.name, kb_root_folder["id"])
-
-    # grab all the errs
-    err = []
-    MAX_FILE_NUM_PER_USER = int(os.environ.get("MAX_FILE_NUM_PER_USER", 0))
-    uploaded_docs_json = []
-    for file in file_objs:
-        try:
-            # TODO: get this value from the database as some tenants have this limit while others don't
-            if MAX_FILE_NUM_PER_USER > 0 and DocumentService.get_doc_count(dataset.tenant_id) >= MAX_FILE_NUM_PER_USER:
-                return construct_json_result(code=RetCode.DATA_ERROR,
-                                             message="Exceed the maximum file number of a free user!")
-            # deal with the duplicate name
-            filename = duplicate_name(
-                DocumentService.query,
-                name=file.filename,
-                kb_id=dataset.id)
-
-            # deal with the unsupported type
-            filetype = filename_type(filename)
-            if filetype == FileType.OTHER.value:
-                return construct_json_result(code=RetCode.DATA_ERROR,
-                                             message="This type of file has not been supported yet!")
-
-            # upload to the minio
-            location = filename
-            while STORAGE_IMPL.obj_exist(dataset_id, location):
-                location += "_"
-
-            blob = file.read()
-
-            # the content is empty, raising a warning
-            if blob == b'':
-                warnings.warn(f"[WARNING]: The content of the file {filename} is empty.")
-
-            STORAGE_IMPL.put(dataset_id, location, blob)
-
-            doc = {
-                "id": get_uuid(),
-                "kb_id": dataset.id,
-                "parser_id": dataset.parser_id,
-                "parser_config": dataset.parser_config,
-                "created_by": current_user.id,
-                "type": filetype,
-                "name": filename,
-                "location": location,
-                "size": len(blob),
-                "thumbnail": thumbnail(filename, blob)
-            }
-            if doc["type"] == FileType.VISUAL:
-                doc["parser_id"] = ParserType.PICTURE.value
-            if doc["type"] == FileType.AURAL:
-                doc["parser_id"] = ParserType.AUDIO.value
-            if re.search(r"\.(ppt|pptx|pages)$", filename):
-                doc["parser_id"] = ParserType.PRESENTATION.value
-            if re.search(r"\.(eml)$", filename):
-                doc["parser_id"] = ParserType.EMAIL.value
-            DocumentService.insert(doc)
-
-            FileService.add_file_from_kb(doc, kb_folder["id"], dataset.tenant_id)
-            uploaded_docs_json.append(doc)
-        except Exception as e:
-            err.append(file.filename + ": " + str(e))
-
-    if err:
-        # return all the errors
-        return construct_json_result(message="\n".join(err), code=RetCode.SERVER_ERROR)
-    # success
-    return construct_json_result(data=uploaded_docs_json, code=RetCode.SUCCESS)
-
-
-# ----------------------------delete a file-----------------------------------------------------
-@manager.route("/<dataset_id>/documents/<document_id>", methods=["DELETE"])
-@login_required
-def delete_document(document_id, dataset_id):  # string
-    # get the root folder
-    root_folder = FileService.get_root_folder(current_user.id)
-    # parent file's id
-    parent_file_id = root_folder["id"]
-    # consider the new user
-    FileService.init_knowledgebase_docs(parent_file_id, current_user.id)
-    # store all the errors that may have
-    errors = ""
-    try:
-        # whether there is this document
-        exist, doc = DocumentService.get_by_id(document_id)
-        if not exist:
-            return construct_json_result(message=f"Document {document_id} not found!", code=RetCode.DATA_ERROR)
-        # whether this doc is authorized by this tenant
-        tenant_id = DocumentService.get_tenant_id(document_id)
-        if not tenant_id:
-            return construct_json_result(
-                message=f"You cannot delete this document {document_id} due to the authorization"
-                        f" reason!", code=RetCode.AUTHENTICATION_ERROR)
-
-        # get the doc's id and location
-        real_dataset_id, location = File2DocumentService.get_storage_address(doc_id=document_id)
-
-        if real_dataset_id != dataset_id:
-            return construct_json_result(message=f"The document {document_id} is not in the dataset: {dataset_id}, "
-                                                 f"but in the dataset: {real_dataset_id}.", code=RetCode.ARGUMENT_ERROR)
-
-        # there is an issue when removing
-        if not DocumentService.remove_document(doc, tenant_id):
-            return construct_json_result(
-                message="There was an error during the document removal process. Please check the status of the "
-                        "RAGFlow server and try the removal again.", code=RetCode.OPERATING_ERROR)
-
-        # fetch the File2Document record associated with the provided document ID.
-        file_to_doc = File2DocumentService.get_by_document_id(document_id)
-        # delete the associated File record.
-        FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.id == file_to_doc[0].file_id])
-        # delete the File2Document record itself using the document ID. This removes the
-        # association between the document and the file after the File record has been deleted.
-        File2DocumentService.delete_by_document_id(document_id)
-
-        # delete it from minio
-        STORAGE_IMPL.rm(dataset_id, location)
-    except Exception as e:
-        errors += str(e)
-    if errors:
-        return construct_json_result(data=False, message=errors, code=RetCode.SERVER_ERROR)
-
-    return construct_json_result(data=True, code=RetCode.SUCCESS)
-
-
-# ----------------------------list files-----------------------------------------------------
-@manager.route('/<dataset_id>/documents/', methods=['GET'])
-@login_required
-def list_documents(dataset_id):
-    if not dataset_id:
-        return construct_json_result(
-            data=False, message="Lack of 'dataset_id'", code=RetCode.ARGUMENT_ERROR)
-
-    # searching keywords
-    keywords = request.args.get("keywords", "")
-
-    offset = request.args.get("offset", 0)
-    count = request.args.get("count", -1)
-    order_by = request.args.get("order_by", "create_time")
-    descend = request.args.get("descend", True)
-    try:
-        docs, total = DocumentService.list_documents_in_dataset(dataset_id, int(offset), int(count), order_by,
-                                                                descend, keywords)
-
-        return construct_json_result(data={"total": total, "docs": docs}, message=RetCode.SUCCESS)
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# ----------------------------update: enable rename-----------------------------------------------------
-@manager.route("/<dataset_id>/documents/<document_id>", methods=["PUT"])
-@login_required
-def update_document(dataset_id, document_id):
-    req = request.json
-    try:
-        legal_parameters = set()
-        legal_parameters.add("name")
-        legal_parameters.add("enable")
-        legal_parameters.add("template_type")
-
-        for key in req.keys():
-            if key not in legal_parameters:
-                return construct_json_result(code=RetCode.ARGUMENT_ERROR, message=f"{key} is an illegal parameter.")
-
-        # The request body cannot be empty
-        if not req:
-            return construct_json_result(
-                code=RetCode.DATA_ERROR,
-                message="Please input at least one parameter that you want to update!")
-
-        # Check whether there is this dataset
-        exist, dataset = KnowledgebaseService.get_by_id(dataset_id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR, message=f"This dataset {dataset_id} cannot be found!")
-
-        # The document does not exist
-        exist, document = DocumentService.get_by_id(document_id)
-        if not exist:
-            return construct_json_result(message=f"This document {document_id} cannot be found!",
-                                         code=RetCode.ARGUMENT_ERROR)
-
-        # Deal with the different keys
-        updating_data = {}
-        if "name" in req:
-            new_name = req["name"]
-            updating_data["name"] = new_name
-            # Check whether the new_name is suitable
-            # 1. no name value
-            if not new_name:
-                return construct_json_result(code=RetCode.DATA_ERROR, message="There is no new name.")
-
-            # 2. In case that there's space in the head or the tail
-            new_name = new_name.strip()
-
-            # 3. Check whether the new_name has the same extension of file as before
-            if pathlib.Path(new_name.lower()).suffix != pathlib.Path(
-                    document.name.lower()).suffix:
-                return construct_json_result(
-                    data=False,
-                    message="The extension of file cannot be changed",
-                    code=RetCode.ARGUMENT_ERROR)
-
-            # 4. Check whether the new name has already been occupied by other file
-            for d in DocumentService.query(name=new_name, kb_id=document.kb_id):
-                if d.name == new_name:
-                    return construct_json_result(
-                        message="Duplicated document name in the same dataset.",
-                        code=RetCode.ARGUMENT_ERROR)
-
-        if "enable" in req:
-            enable_value = req["enable"]
-            if is_illegal_value_for_enum(enable_value, StatusEnum):
-                return construct_json_result(message=f"Illegal value {enable_value} for 'enable' field.",
-                                             code=RetCode.DATA_ERROR)
-            updating_data["status"] = enable_value
-
-        # TODO: Chunk-method - update parameters inside the json object parser_config
-        if "template_type" in req:
-            type_value = req["template_type"]
-            if is_illegal_value_for_enum(type_value, ParserType):
-                return construct_json_result(message=f"Illegal value {type_value} for 'template_type' field.",
-                                             code=RetCode.DATA_ERROR)
-            updating_data["parser_id"] = req["template_type"]
-
-        # The process of updating
-        if not DocumentService.update_by_id(document_id, updating_data):
-            return construct_json_result(
-                code=RetCode.OPERATING_ERROR,
-                message="Failed to update document in the database! "
-                        "Please check the status of RAGFlow server and try again!")
-
-        # name part: file service
-        if "name" in req:
-            # Get file by document id
-            file_information = File2DocumentService.get_by_document_id(document_id)
-            if file_information:
-                exist, file = FileService.get_by_id(file_information[0].file_id)
-                FileService.update_by_id(file.id, {"name": req["name"]})
-
-        exist, document = DocumentService.get_by_id(document_id)
-
-        # Success
-        return construct_json_result(data=document.to_json(), message="Success", code=RetCode.SUCCESS)
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# Helper method to judge whether it's an illegal value
-def is_illegal_value_for_enum(value, enum_class):
-    return value not in enum_class.__members__.values()
-
-
-# ----------------------------download a file-----------------------------------------------------
-@manager.route("/<dataset_id>/documents/<document_id>", methods=["GET"])
-@login_required
-def download_document(dataset_id, document_id):
-    try:
-        # Check whether there is this dataset
-        exist, _ = KnowledgebaseService.get_by_id(dataset_id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR,
-                                         message=f"This dataset '{dataset_id}' cannot be found!")
-
-        # Check whether there is this document
-        exist, document = DocumentService.get_by_id(document_id)
-        if not exist:
-            return construct_json_result(message=f"This document '{document_id}' cannot be found!",
-                                         code=RetCode.ARGUMENT_ERROR)
-
-        # The process of downloading
-        doc_id, doc_location = File2DocumentService.get_storage_address(doc_id=document_id)  # minio address
-        file_stream = STORAGE_IMPL.get(doc_id, doc_location)
-        if not file_stream:
-            return construct_json_result(message="This file is empty.", code=RetCode.DATA_ERROR)
-
-        file = BytesIO(file_stream)
-
-        # Use send_file with a proper filename and MIME type
-        return send_file(
-            file,
-            as_attachment=True,
-            download_name=document.name,
-            mimetype='application/octet-stream'  # Set a default MIME type
-        )
-
-    # Error
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# ----------------------------start parsing a document-----------------------------------------------------
-# helper method for parsing
-# callback method
-def doc_parse_callback(doc_id, prog=None, msg=""):
-    cancel = DocumentService.do_cancel(doc_id)
-    if cancel:
-        raise Exception("The parsing process has been cancelled!")
-
-"""
-def doc_parse(binary, doc_name, parser_name, tenant_id, doc_id):
-    match parser_name:
-        case "book":
-            book.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "laws":
-            laws.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "manual":
-            manual.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "naive":
-            # It's the mode by default, which is general in the front-end
-            naive.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "one":
-            one.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "paper":
-            paper.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "picture":
-            picture.chunk(doc_name, binary=binary, tenant_id=tenant_id, lang="Chinese",
-                          callback=partial(doc_parse_callback, doc_id))
-        case "presentation":
-            presentation.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "qa":
-            qa.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "resume":
-            resume.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "table":
-            table.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "audio":
-            audio.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case "email":
-            email.chunk(doc_name, binary=binary, callback=partial(doc_parse_callback, doc_id))
-        case _:
-            return False
-
-    return True
-    """
-
-
-@manager.route("/<dataset_id>/documents/<document_id>/status", methods=["POST"])
-@login_required
-def parse_document(dataset_id, document_id):
-    try:
-        # valid dataset
-        exist, _ = KnowledgebaseService.get_by_id(dataset_id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR,
-                                         message=f"This dataset '{dataset_id}' cannot be found!")
-
-        return parsing_document_internal(document_id)
-
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# ----------------------------start parsing documents-----------------------------------------------------
-@manager.route("/<dataset_id>/documents/status", methods=["POST"])
-@login_required
-def parse_documents(dataset_id):
-    doc_ids = request.json["doc_ids"]
-    try:
-        exist, _ = KnowledgebaseService.get_by_id(dataset_id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR,
-                                         message=f"This dataset '{dataset_id}' cannot be found!")
-        # two conditions
-        if not doc_ids:
-            # documents inside the dataset
-            docs, total = DocumentService.list_documents_in_dataset(dataset_id, 0, -1, "create_time",
-                                                                    True, "")
-            doc_ids = [doc["id"] for doc in docs]
-
-        message = ""
-        # for loop
-        for id in doc_ids:
-            res = parsing_document_internal(id)
-            res_body = res.json
-            if res_body["code"] == RetCode.SUCCESS:
-                message += res_body["message"]
-            else:
-                return res
-        return construct_json_result(data=True, code=RetCode.SUCCESS, message=message)
-
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# helper method for parsing the document
-def parsing_document_internal(id):
-    message = ""
-    try:
-        # Check whether there is this document
-        exist, document = DocumentService.get_by_id(id)
-        if not exist:
-            return construct_json_result(message=f"This document '{id}' cannot be found!",
-                                         code=RetCode.ARGUMENT_ERROR)
-
-        tenant_id = DocumentService.get_tenant_id(id)
-        if not tenant_id:
-            return construct_json_result(message="Tenant not found!", code=RetCode.AUTHENTICATION_ERROR)
-
-        info = {"run": "1", "progress": 0}
-        info["progress_msg"] = ""
-        info["chunk_num"] = 0
-        info["token_num"] = 0
-
-        DocumentService.update_by_id(id, info)
-
-        ELASTICSEARCH.deleteByQuery(Q("match", doc_id=id), idxnm=search.index_name(tenant_id))
-
-        _, doc_attributes = DocumentService.get_by_id(id)
-        doc_attributes = doc_attributes.to_dict()
-        doc_id = doc_attributes["id"]
-
-        bucket, doc_name = File2DocumentService.get_storage_address(doc_id=doc_id)
-        binary = STORAGE_IMPL.get(bucket, doc_name)
-        parser_name = doc_attributes["parser_id"]
-        if binary:
-            res = doc_parse(binary, doc_name, parser_name, tenant_id, doc_id)
-            if res is False:
-                message += f"The parser id: {parser_name} of the document {doc_id} is not supported; "
-        else:
-            message += f"Empty data in the document: {doc_name}; "
-        # failed in parsing
-        if doc_attributes["status"] == TaskStatus.FAIL.value:
-            message += f"Failed in parsing the document: {doc_id}; "
-        return construct_json_result(code=RetCode.SUCCESS, message=message)
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# ----------------------------stop parsing a doc-----------------------------------------------------
-@manager.route("<dataset_id>/documents/<document_id>/status", methods=["DELETE"])
-@login_required
-def stop_parsing_document(dataset_id, document_id):
-    try:
-        # valid dataset
-        exist, _ = KnowledgebaseService.get_by_id(dataset_id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR,
-                                         message=f"This dataset '{dataset_id}' cannot be found!")
-
-        return stop_parsing_document_internal(document_id)
-
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# ----------------------------stop parsing docs-----------------------------------------------------
-@manager.route("<dataset_id>/documents/status", methods=["DELETE"])
-@login_required
-def stop_parsing_documents(dataset_id):
-    doc_ids = request.json["doc_ids"]
-    try:
-        # valid dataset?
-        exist, _ = KnowledgebaseService.get_by_id(dataset_id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR,
-                                         message=f"This dataset '{dataset_id}' cannot be found!")
-        if not doc_ids:
-            # documents inside the dataset
-            docs, total = DocumentService.list_documents_in_dataset(dataset_id, 0, -1, "create_time",
-                                                                        True, "")
-            doc_ids = [doc["id"] for doc in docs]
-
-        message = ""
-        # for loop
-        for id in doc_ids:
-            res = stop_parsing_document_internal(id)
-            res_body = res.json
-            if res_body["code"] == RetCode.SUCCESS:
-                message += res_body["message"]
-            else:
-                return res
-        return construct_json_result(data=True, code=RetCode.SUCCESS, message=message)
-
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# Helper method
-def stop_parsing_document_internal(document_id):
-    try:
-        # valid doc?
-        exist, doc = DocumentService.get_by_id(document_id)
-        if not exist:
-            return construct_json_result(message=f"This document '{document_id}' cannot be found!",
-                                         code=RetCode.ARGUMENT_ERROR)
-        doc_attributes = doc.to_dict()
-
-        # only when the status is parsing, we need to stop it
-        if doc_attributes["status"] == TaskStatus.RUNNING.value:
-            tenant_id = DocumentService.get_tenant_id(document_id)
-            if not tenant_id:
-                return construct_json_result(message="Tenant not found!", code=RetCode.AUTHENTICATION_ERROR)
-
-            # update successfully?
-            if not DocumentService.update_by_id(document_id, {"status": "2"}):  # cancel
-                return construct_json_result(
-                    code=RetCode.OPERATING_ERROR,
-                    message="There was an error during the stopping parsing the document process. "
-                            "Please check the status of the RAGFlow server and try the update again."
-                )
-
-            _, doc_attributes = DocumentService.get_by_id(document_id)
-            doc_attributes = doc_attributes.to_dict()
-
-            # failed in stop parsing
-            if doc_attributes["status"] == TaskStatus.RUNNING.value:
-                return construct_json_result(message=f"Failed in parsing the document: {document_id}; ", code=RetCode.SUCCESS)
-        return construct_json_result(code=RetCode.SUCCESS, message="")
-    except Exception as e:
-        return construct_error_response(e)
-
-
-# ----------------------------show the status of the file-----------------------------------------------------
-@manager.route("/<dataset_id>/documents/<document_id>/status", methods=["GET"])
-@login_required
-def show_parsing_status(dataset_id, document_id):
-    try:
-        # valid dataset
-        exist, _ = KnowledgebaseService.get_by_id(dataset_id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR,
-                                         message=f"This dataset: '{dataset_id}' cannot be found!")
-        # valid document
-        exist, _ = DocumentService.get_by_id(document_id)
-        if not exist:
-            return construct_json_result(code=RetCode.DATA_ERROR,
-                                         message=f"This document: '{document_id}' is not a valid document.")
-
-        _, doc = DocumentService.get_by_id(document_id)  # get doc object
-        doc_attributes = doc.to_dict()
-
-        return construct_json_result(
-            data={"progress": doc_attributes["progress"], "status": TaskStatus(doc_attributes["status"]).name},
-            code=RetCode.SUCCESS
-        )
-    except Exception as e:
-        return construct_error_response(e)
-
-# ----------------------------list the chunks of the file-----------------------------------------------------
-
-# -- --------------------------delete the chunk-----------------------------------------------------
-
-# ----------------------------edit the status of the chunk-----------------------------------------------------
-
-# ----------------------------insert a new chunk-----------------------------------------------------
-
-# ----------------------------upload a file-----------------------------------------------------
-
-# ----------------------------get a specific chunk-----------------------------------------------------
-
-# ----------------------------retrieval test-----------------------------------------------------

api/apps/dialog_app.py

@@ -20,7 +20,7 @@ from api.db.services.dialog_service import DialogService
 from api.db import StatusEnum
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.user_service import TenantService, UserTenantService
-from api.settings import RetCode
+from api import settings
 from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
 from api.utils import get_uuid
 from api.utils.api_utils import get_json_result
@@ -68,17 +68,17 @@ def set_dialog():
             continue
         if prompt_config["system"].find("{%s}" % p["key"]) < 0:
             return get_data_error_result(
-                retmsg="Parameter '{}' is not used".format(p["key"]))
+                message="Parameter '{}' is not used".format(p["key"]))
 
     try:
         e, tenant = TenantService.get_by_id(current_user.id)
         if not e:
-            return get_data_error_result(retmsg="Tenant not found!")
+            return get_data_error_result(message="Tenant not found!")
         llm_id = req.get("llm_id", tenant.llm_id)
         if not dialog_id:
             if not req.get("kb_ids"):
                 return get_data_error_result(
-                    retmsg="Fail! Please select knowledgebase!")
+                    message="Fail! Please select knowledgebase!")
             dia = {
                 "id": get_uuid(),
                 "tenant_id": current_user.id,
@@ -96,20 +96,20 @@ def set_dialog():
                 "icon": icon
             }
             if not DialogService.save(**dia):
-                return get_data_error_result(retmsg="Fail to new a dialog!")
+                return get_data_error_result(message="Fail to new a dialog!")
             e, dia = DialogService.get_by_id(dia["id"])
             if not e:
-                return get_data_error_result(retmsg="Fail to new a dialog!")
+                return get_data_error_result(message="Fail to new a dialog!")
             return get_json_result(data=dia.to_json())
         else:
             del req["dialog_id"]
             if "kb_names" in req:
                 del req["kb_names"]
             if not DialogService.update_by_id(dialog_id, req):
-                return get_data_error_result(retmsg="Dialog not found!")
+                return get_data_error_result(message="Dialog not found!")
             e, dia = DialogService.get_by_id(dialog_id)
             if not e:
-                return get_data_error_result(retmsg="Fail to update a dialog!")
+                return get_data_error_result(message="Fail to update a dialog!")
             dia = dia.to_dict()
             dia["kb_ids"], dia["kb_names"] = get_kb_names(dia["kb_ids"])
             return get_json_result(data=dia)
@@ -124,7 +124,7 @@ def get():
     try:
         e, dia = DialogService.get_by_id(dialog_id)
         if not e:
-            return get_data_error_result(retmsg="Dialog not found!")
+            return get_data_error_result(message="Dialog not found!")
         dia = dia.to_dict()
         dia["kb_ids"], dia["kb_names"] = get_kb_names(dia["kb_ids"])
         return get_json_result(data=dia)
@@ -174,8 +174,8 @@ def rm():
                     break
             else:
                 return get_json_result(
-                    data=False, retmsg=f'Only owner of dialog authorized for this operation.',
-                    retcode=RetCode.OPERATING_ERROR)
+                    data=False, message='Only owner of dialog authorized for this operation.',
+                    code=settings.RetCode.OPERATING_ERROR)
             dialog_list.append({"id": id,"status":StatusEnum.INVALID.value})
         DialogService.update_many_by_id(dialog_list)
         return get_json_result(data=True)

api/apps/document_app.py

@@ -13,44 +13,34 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License
 #
-import datetime
-import hashlib
 import json
-import os
+import os.path
 import pathlib
 import re
-import traceback
-from concurrent.futures import ThreadPoolExecutor
-from copy import deepcopy
-from io import BytesIO
 
 import flask
-from elasticsearch_dsl import Q
 from flask import request
 from flask_login import login_required, current_user
 
 from api.db.db_models import Task, File
-from api.db.services.dialog_service import DialogService, ConversationService
 from api.db.services.file2document_service import File2DocumentService
 from api.db.services.file_service import FileService
-from api.db.services.llm_service import LLMBundle
 from api.db.services.task_service import TaskService, queue_tasks
-from api.db.services.user_service import TenantService, UserTenantService
-from graphrag.mind_map_extractor import MindMapExtractor
-from rag.app import naive
+from api.db.services.user_service import UserTenantService
+from deepdoc.parser.html_parser import RAGFlowHtmlParser
 from rag.nlp import search
-from rag.utils.es_conn import ELASTICSEARCH
 from api.db.services import duplicate_name
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
 from api.utils import get_uuid
-from api.db import FileType, TaskStatus, ParserType, FileSource, LLMType
+from api.db import FileType, TaskStatus, ParserType, FileSource
 from api.db.services.document_service import DocumentService, doc_upload_and_parse
-from api.settings import RetCode, stat_logger
+from api import settings
 from api.utils.api_utils import get_json_result
 from rag.utils.storage_factory import STORAGE_IMPL
 from api.utils.file_utils import filename_type, thumbnail, get_project_base_directory
 from api.utils.web_utils import html2pdf, is_valid_url
+from api.constants import IMG_BASE64_PREFIX
 
 
 @manager.route('/upload', methods=['POST'])
@@ -60,16 +50,16 @@ def upload():
     kb_id = request.form.get("kb_id")
     if not kb_id:
         return get_json_result(
-            data=False, retmsg='Lack of "KB ID"', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='Lack of "KB ID"', code=settings.RetCode.ARGUMENT_ERROR)
     if 'file' not in request.files:
         return get_json_result(
-            data=False, retmsg='No file part!', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='No file part!', code=settings.RetCode.ARGUMENT_ERROR)
 
     file_objs = request.files.getlist('file')
     for file_obj in file_objs:
         if file_obj.filename == '':
             return get_json_result(
-                data=False, retmsg='No file selected!', retcode=RetCode.ARGUMENT_ERROR)
+                data=False, message='No file selected!', code=settings.RetCode.ARGUMENT_ERROR)
 
     e, kb = KnowledgebaseService.get_by_id(kb_id)
     if not e:
@@ -78,7 +68,7 @@ def upload():
     err, _ = FileService.upload_document(kb, file_objs, current_user.id)
     if err:
         return get_json_result(
-            data=False, retmsg="\n".join(err), retcode=RetCode.SERVER_ERROR)
+            data=False, message="\n".join(err), code=settings.RetCode.SERVER_ERROR)
     return get_json_result(data=True)
 
 
@@ -89,12 +79,12 @@ def web_crawl():
     kb_id = request.form.get("kb_id")
     if not kb_id:
         return get_json_result(
-            data=False, retmsg='Lack of "KB ID"', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='Lack of "KB ID"', code=settings.RetCode.ARGUMENT_ERROR)
     name = request.form.get("name")
     url = request.form.get("url")
     if not is_valid_url(url):
         return get_json_result(
-            data=False, retmsg='The URL format is invalid', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='The URL format is invalid', code=settings.RetCode.ARGUMENT_ERROR)
     e, kb = KnowledgebaseService.get_by_id(kb_id)
     if not e:
         raise LookupError("Can't find this knowledgebase!")
@@ -156,17 +146,17 @@ def create():
     kb_id = req["kb_id"]
     if not kb_id:
         return get_json_result(
-            data=False, retmsg='Lack of "KB ID"', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='Lack of "KB ID"', code=settings.RetCode.ARGUMENT_ERROR)
 
     try:
         e, kb = KnowledgebaseService.get_by_id(kb_id)
         if not e:
             return get_data_error_result(
-                retmsg="Can't find this knowledgebase!")
+                message="Can't find this knowledgebase!")
 
         if DocumentService.query(name=req["name"], kb_id=kb_id):
             return get_data_error_result(
-                retmsg="Duplicated document name in the same knowledgebase.")
+                message="Duplicated document name in the same knowledgebase.")
 
         doc = DocumentService.insert({
             "id": get_uuid(),
@@ -190,7 +180,7 @@ def list_docs():
     kb_id = request.args.get("kb_id")
     if not kb_id:
         return get_json_result(
-            data=False, retmsg='Lack of "KB ID"', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='Lack of "KB ID"', code=settings.RetCode.ARGUMENT_ERROR)
     tenants = UserTenantService.query(user_id=current_user.id)
     for tenant in tenants:
         if KnowledgebaseService.query(
@@ -198,8 +188,8 @@ def list_docs():
             break
     else:
         return get_json_result(
-            data=False, retmsg=f'Only owner of knowledgebase authorized for this operation.',
-            retcode=RetCode.OPERATING_ERROR)
+            data=False, message='Only owner of knowledgebase authorized for this operation.',
+            code=settings.RetCode.OPERATING_ERROR)
     keywords = request.args.get("keywords", "")
 
     page_number = int(request.args.get("page", 1))
@@ -209,29 +199,47 @@ def list_docs():
     try:
         docs, tol = DocumentService.get_by_kb_id(
             kb_id, page_number, items_per_page, orderby, desc, keywords)
+
+        for doc_item in docs:
+            if doc_item['thumbnail'] and not doc_item['thumbnail'].startswith(IMG_BASE64_PREFIX):
+                doc_item['thumbnail'] = f"/v1/document/image/{kb_id}-{doc_item['thumbnail']}"
+
         return get_json_result(data={"total": tol, "docs": docs})
     except Exception as e:
         return server_error_response(e)
 
 
 @manager.route('/infos', methods=['POST'])
+@login_required
 def docinfos():
     req = request.json
     doc_ids = req["doc_ids"]
+    for doc_id in doc_ids:
+        if not DocumentService.accessible(doc_id, current_user.id):
+            return get_json_result(
+                data=False,
+                message='No authorization.',
+                code=settings.RetCode.AUTHENTICATION_ERROR
+            )
     docs = DocumentService.get_by_ids(doc_ids)
     return get_json_result(data=list(docs.dicts()))
 
 
 @manager.route('/thumbnails', methods=['GET'])
-#@login_required
+# @login_required
 def thumbnails():
     doc_ids = request.args.get("doc_ids").split(",")
     if not doc_ids:
         return get_json_result(
-            data=False, retmsg='Lack of "Document ID"', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='Lack of "Document ID"', code=settings.RetCode.ARGUMENT_ERROR)
 
     try:
         docs = DocumentService.get_thumbnails(doc_ids)
+
+        for doc_item in docs:
+            if doc_item['thumbnail'] and not doc_item['thumbnail'].startswith(IMG_BASE64_PREFIX):
+                doc_item['thumbnail'] = f"/v1/document/image/{doc_item['kb_id']}-{doc_item['thumbnail']}"
+
         return get_json_result(data={d["id"]: d["thumbnail"] for d in docs})
     except Exception as e:
         return server_error_response(e)
@@ -243,37 +251,34 @@ def thumbnails():
 def change_status():
     req = request.json
     if str(req["status"]) not in ["0", "1"]:
-        get_json_result(
+        return get_json_result(
             data=False,
-            retmsg='"Status" must be either 0 or 1!',
-            retcode=RetCode.ARGUMENT_ERROR)
+            message='"Status" must be either 0 or 1!',
+            code=settings.RetCode.ARGUMENT_ERROR)
+
+    if not DocumentService.accessible(req["doc_id"], current_user.id):
+        return get_json_result(
+            data=False,
+            message='No authorization.',
+            code=settings.RetCode.AUTHENTICATION_ERROR)
 
     try:
         e, doc = DocumentService.get_by_id(req["doc_id"])
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
         e, kb = KnowledgebaseService.get_by_id(doc.kb_id)
         if not e:
             return get_data_error_result(
-                retmsg="Can't find this knowledgebase!")
+                message="Can't find this knowledgebase!")
 
         if not DocumentService.update_by_id(
                 req["doc_id"], {"status": str(req["status"])}):
             return get_data_error_result(
-                retmsg="Database error (Document update)!")
+                message="Database error (Document update)!")
 
-        if str(req["status"]) == "0":
-            ELASTICSEARCH.updateScriptByQuery(Q("term", doc_id=req["doc_id"]),
-                                              scripts="ctx._source.available_int=0;",
-                                              idxnm=search.index_name(
-                                                  kb.tenant_id)
-                                              )
-        else:
-            ELASTICSEARCH.updateScriptByQuery(Q("term", doc_id=req["doc_id"]),
-                                              scripts="ctx._source.available_int=1;",
-                                              idxnm=search.index_name(
-                                                  kb.tenant_id)
-                                              )
+        status = int(req["status"])
+        settings.docStoreConn.update({"doc_id": req["doc_id"]}, {"available_int": status},
+                                     search.index_name(kb.tenant_id), doc.kb_id)
         return get_json_result(data=True)
     except Exception as e:
         return server_error_response(e)
@@ -286,6 +291,15 @@ def rm():
     req = request.json
     doc_ids = req["doc_id"]
     if isinstance(doc_ids, str): doc_ids = [doc_ids]
+
+    for doc_id in doc_ids:
+        if not DocumentService.accessible4deletion(doc_id, current_user.id):
+            return get_json_result(
+                data=False,
+                message='No authorization.',
+                code=settings.RetCode.AUTHENTICATION_ERROR
+            )
+
     root_folder = FileService.get_root_folder(current_user.id)
     pf_id = root_folder["id"]
     FileService.init_knowledgebase_docs(pf_id, current_user.id)
@@ -294,16 +308,16 @@ def rm():
         try:
             e, doc = DocumentService.get_by_id(doc_id)
             if not e:
-                return get_data_error_result(retmsg="Document not found!")
+                return get_data_error_result(message="Document not found!")
             tenant_id = DocumentService.get_tenant_id(doc_id)
             if not tenant_id:
-                return get_data_error_result(retmsg="Tenant not found!")
+                return get_data_error_result(message="Tenant not found!")
 
             b, n = File2DocumentService.get_storage_address(doc_id=doc_id)
 
             if not DocumentService.remove_document(doc, tenant_id):
                 return get_data_error_result(
-                    retmsg="Database error (Document removal)!")
+                    message="Database error (Document removal)!")
 
             f2d = File2DocumentService.get_by_document_id(doc_id)
             FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.id == f2d[0].file_id])
@@ -314,7 +328,7 @@ def rm():
             errors += str(e)
 
     if errors:
-        return get_json_result(data=False, retmsg=errors, retcode=RetCode.SERVER_ERROR)
+        return get_json_result(data=False, message=errors, code=settings.RetCode.SERVER_ERROR)
 
     return get_json_result(data=True)
 
@@ -324,6 +338,13 @@ def rm():
 @validate_request("doc_ids", "run")
 def run():
     req = request.json
+    for doc_id in req["doc_ids"]:
+        if not DocumentService.accessible(doc_id, current_user.id):
+            return get_json_result(
+                data=False,
+                message='No authorization.',
+                code=settings.RetCode.AUTHENTICATION_ERROR
+            )
     try:
         for id in req["doc_ids"]:
             info = {"run": str(req["run"]), "progress": 0}
@@ -335,9 +356,12 @@ def run():
             # if str(req["run"]) == TaskStatus.CANCEL.value:
             tenant_id = DocumentService.get_tenant_id(id)
             if not tenant_id:
-                return get_data_error_result(retmsg="Tenant not found!")
-            ELASTICSEARCH.deleteByQuery(
-                Q("match", doc_id=id), idxnm=search.index_name(tenant_id))
+                return get_data_error_result(message="Tenant not found!")
+            e, doc = DocumentService.get_by_id(id)
+            if not e:
+                return get_data_error_result(message="Document not found!")
+            if settings.docStoreConn.indexExist(search.index_name(tenant_id), doc.kb_id):
+                settings.docStoreConn.delete({"doc_id": id}, search.index_name(tenant_id), doc.kb_id)
 
             if str(req["run"]) == TaskStatus.RUNNING.value:
                 TaskService.filter_delete([Task.doc_id == id])
@@ -357,25 +381,31 @@ def run():
 @validate_request("doc_id", "name")
 def rename():
     req = request.json
+    if not DocumentService.accessible(req["doc_id"], current_user.id):
+        return get_json_result(
+            data=False,
+            message='No authorization.',
+            code=settings.RetCode.AUTHENTICATION_ERROR
+        )
     try:
         e, doc = DocumentService.get_by_id(req["doc_id"])
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
         if pathlib.Path(req["name"].lower()).suffix != pathlib.Path(
                 doc.name.lower()).suffix:
             return get_json_result(
                 data=False,
-                retmsg="The extension of file can't be changed",
-                retcode=RetCode.ARGUMENT_ERROR)
+                message="The extension of file can't be changed",
+                code=settings.RetCode.ARGUMENT_ERROR)
         for d in DocumentService.query(name=req["name"], kb_id=doc.kb_id):
             if d.name == req["name"]:
                 return get_data_error_result(
-                    retmsg="Duplicated document name in the same knowledgebase.")
+                    message="Duplicated document name in the same knowledgebase.")
 
         if not DocumentService.update_by_id(
                 req["doc_id"], {"name": req["name"]}):
             return get_data_error_result(
-                retmsg="Database error (Document rename)!")
+                message="Database error (Document rename)!")
 
         informs = File2DocumentService.get_by_document_id(req["doc_id"])
         if informs:
@@ -393,7 +423,7 @@ def get(doc_id):
     try:
         e, doc = DocumentService.get_by_id(doc_id)
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
 
         b, n = File2DocumentService.get_storage_address(doc_id=doc_id)
         response = flask.make_response(STORAGE_IMPL.get(b, n))
@@ -417,10 +447,17 @@ def get(doc_id):
 @validate_request("doc_id", "parser_id")
 def change_parser():
     req = request.json
+
+    if not DocumentService.accessible(req["doc_id"], current_user.id):
+        return get_json_result(
+            data=False,
+            message='No authorization.',
+            code=settings.RetCode.AUTHENTICATION_ERROR
+        )
     try:
         e, doc = DocumentService.get_by_id(req["doc_id"])
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
         if doc.parser_id.lower() == req["parser_id"].lower():
             if "parser_config" in req:
                 if req["parser_config"] == doc.parser_config:
@@ -428,27 +465,28 @@ def change_parser():
             else:
                 return get_json_result(data=True)
 
-        if doc.type == FileType.VISUAL or re.search(
-                r"\.(ppt|pptx|pages)$", doc.name):
-            return get_data_error_result(retmsg="Not supported yet!")
+        if ((doc.type == FileType.VISUAL and req["parser_id"] != "picture")
+                or (re.search(
+                    r"\.(ppt|pptx|pages)$", doc.name) and req["parser_id"] != "presentation")):
+            return get_data_error_result(message="Not supported yet!")
 
         e = DocumentService.update_by_id(doc.id,
                                          {"parser_id": req["parser_id"], "progress": 0, "progress_msg": "",
                                           "run": TaskStatus.UNSTART.value})
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
         if "parser_config" in req:
             DocumentService.update_parser_config(doc.id, req["parser_config"])
         if doc.token_num > 0:
             e = DocumentService.increment_chunk_num(doc.id, doc.kb_id, doc.token_num * -1, doc.chunk_num * -1,
                                                     doc.process_duation * -1)
             if not e:
-                return get_data_error_result(retmsg="Document not found!")
+                return get_data_error_result(message="Document not found!")
             tenant_id = DocumentService.get_tenant_id(req["doc_id"])
             if not tenant_id:
-                return get_data_error_result(retmsg="Tenant not found!")
-            ELASTICSEARCH.deleteByQuery(
-                Q("match", doc_id=doc.id), idxnm=search.index_name(tenant_id))
+                return get_data_error_result(message="Tenant not found!")
+            if settings.docStoreConn.indexExist(search.index_name(tenant_id), doc.kb_id):
+                settings.docStoreConn.delete({"doc_id": doc.id}, search.index_name(tenant_id), doc.kb_id)
 
         return get_json_result(data=True)
     except Exception as e:
@@ -473,14 +511,74 @@ def get_image(image_id):
 def upload_and_parse():
     if 'file' not in request.files:
         return get_json_result(
-            data=False, retmsg='No file part!', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='No file part!', code=settings.RetCode.ARGUMENT_ERROR)
 
     file_objs = request.files.getlist('file')
     for file_obj in file_objs:
         if file_obj.filename == '':
             return get_json_result(
-                data=False, retmsg='No file selected!', retcode=RetCode.ARGUMENT_ERROR)
+                data=False, message='No file selected!', code=settings.RetCode.ARGUMENT_ERROR)
 
     doc_ids = doc_upload_and_parse(request.form.get("conversation_id"), file_objs, current_user.id)
 
     return get_json_result(data=doc_ids)
+
+
+@manager.route('/parse', methods=['POST'])
+@login_required
+def parse():
+    url = request.json.get("url") if request.json else ""
+    if url:
+        if not is_valid_url(url):
+            return get_json_result(
+                data=False, message='The URL format is invalid', code=settings.RetCode.ARGUMENT_ERROR)
+        download_path = os.path.join(get_project_base_directory(), "logs/downloads")
+        os.makedirs(download_path, exist_ok=True)
+        from seleniumwire.webdriver import Chrome, ChromeOptions
+        options = ChromeOptions()
+        options.add_argument('--headless')
+        options.add_argument('--disable-gpu')
+        options.add_argument('--no-sandbox')
+        options.add_argument('--disable-dev-shm-usage')
+        options.add_experimental_option('prefs', {
+            'download.default_directory': download_path,
+            'download.prompt_for_download': False,
+            'download.directory_upgrade': True,
+            'safebrowsing.enabled': True
+        })
+        driver = Chrome(options=options)
+        driver.get(url)
+        res_headers = [r.response.headers for r in driver.requests]
+        if len(res_headers) > 1:
+            sections = RAGFlowHtmlParser().parser_txt(driver.page_source)
+            driver.quit()
+            return get_json_result(data="\n".join(sections))
+
+        class File:
+            filename: str
+            filepath: str
+
+            def __init__(self, filename, filepath):
+                self.filename = filename
+                self.filepath = filepath
+
+            def read(self):
+                with open(self.filepath, "rb") as f:
+                    return f.read()
+
+        r = re.search(r"filename=\"([^\"]+)\"", str(res_headers))
+        if not r or not r.group(1):
+            return get_json_result(
+                data=False, message="Can't not identify downloaded file", code=settings.RetCode.ARGUMENT_ERROR)
+        f = File(r.group(1), os.path.join(download_path, r.group(1)))
+        txt = FileService.parse_docs([f], current_user.id)
+        return get_json_result(data=txt)
+
+    if 'file' not in request.files:
+        return get_json_result(
+            data=False, message='No file part!', code=settings.RetCode.ARGUMENT_ERROR)
+
+    file_objs = request.files.getlist('file')
+    txt = FileService.parse_docs(file_objs, current_user.id)
+
+    return get_json_result(data=txt)

api/apps/file2document_app.py

@@ -13,9 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License
 #
-from elasticsearch_dsl import Q
 
-from api.db.db_models import File2Document
 from api.db.services.file2document_service import File2DocumentService
 from api.db.services.file_service import FileService
 
@@ -26,10 +24,8 @@ from api.utils.api_utils import server_error_response, get_data_error_result, va
 from api.utils import get_uuid
 from api.db import FileType
 from api.db.services.document_service import DocumentService
-from api.settings import RetCode
+from api import settings
 from api.utils.api_utils import get_json_result
-from rag.nlp import search
-from rag.utils.es_conn import ELASTICSEARCH
 
 
 @manager.route('/convert', methods=['POST'])
@@ -54,13 +50,13 @@ def convert():
                     doc_id = inform.document_id
                     e, doc = DocumentService.get_by_id(doc_id)
                     if not e:
-                        return get_data_error_result(retmsg="Document not found!")
+                        return get_data_error_result(message="Document not found!")
                     tenant_id = DocumentService.get_tenant_id(doc_id)
                     if not tenant_id:
-                        return get_data_error_result(retmsg="Tenant not found!")
+                        return get_data_error_result(message="Tenant not found!")
                     if not DocumentService.remove_document(doc, tenant_id):
                         return get_data_error_result(
-                            retmsg="Database error (Document removal)!")
+                            message="Database error (Document removal)!")
                 File2DocumentService.delete_by_file_id(id)
 
                 # insert
@@ -68,11 +64,11 @@ def convert():
                     e, kb = KnowledgebaseService.get_by_id(kb_id)
                     if not e:
                         return get_data_error_result(
-                            retmsg="Can't find this knowledgebase!")
+                            message="Can't find this knowledgebase!")
                     e, file = FileService.get_by_id(id)
                     if not e:
                         return get_data_error_result(
-                            retmsg="Can't find this file!")
+                            message="Can't find this file!")
 
                     doc = DocumentService.insert({
                         "id": get_uuid(),
@@ -104,26 +100,26 @@ def rm():
     file_ids = req["file_ids"]
     if not file_ids:
         return get_json_result(
-            data=False, retmsg='Lack of "Files ID"', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='Lack of "Files ID"', code=settings.RetCode.ARGUMENT_ERROR)
     try:
         for file_id in file_ids:
             informs = File2DocumentService.get_by_file_id(file_id)
             if not informs:
-                return get_data_error_result(retmsg="Inform not found!")
+                return get_data_error_result(message="Inform not found!")
             for inform in informs:
                 if not inform:
-                    return get_data_error_result(retmsg="Inform not found!")
+                    return get_data_error_result(message="Inform not found!")
                 File2DocumentService.delete_by_file_id(file_id)
                 doc_id = inform.document_id
                 e, doc = DocumentService.get_by_id(doc_id)
                 if not e:
-                    return get_data_error_result(retmsg="Document not found!")
+                    return get_data_error_result(message="Document not found!")
                 tenant_id = DocumentService.get_tenant_id(doc_id)
                 if not tenant_id:
-                    return get_data_error_result(retmsg="Tenant not found!")
+                    return get_data_error_result(message="Tenant not found!")
                 if not DocumentService.remove_document(doc, tenant_id):
                     return get_data_error_result(
-                        retmsg="Database error (Document removal)!")
+                        message="Database error (Document removal)!")
         return get_json_result(data=True)
     except Exception as e:
         return server_error_response(e)

api/apps/file_app.py

@@ -18,7 +18,6 @@ import pathlib
 import re
 
 import flask
-from elasticsearch_dsl import Q
 from flask import request
 from flask_login import login_required, current_user
 
@@ -29,11 +28,9 @@ from api.utils import get_uuid
 from api.db import FileType, FileSource
 from api.db.services import duplicate_name
 from api.db.services.file_service import FileService
-from api.settings import RetCode
+from api import settings
 from api.utils.api_utils import get_json_result
 from api.utils.file_utils import filename_type
-from rag.nlp import search
-from rag.utils.es_conn import ELASTICSEARCH
 from rag.utils.storage_factory import STORAGE_IMPL
 
 
@@ -49,24 +46,24 @@ def upload():
 
     if 'file' not in request.files:
         return get_json_result(
-            data=False, retmsg='No file part!', retcode=RetCode.ARGUMENT_ERROR)
+            data=False, message='No file part!', code=settings.RetCode.ARGUMENT_ERROR)
     file_objs = request.files.getlist('file')
 
     for file_obj in file_objs:
         if file_obj.filename == '':
             return get_json_result(
-                data=False, retmsg='No file selected!', retcode=RetCode.ARGUMENT_ERROR)
+                data=False, message='No file selected!', code=settings.RetCode.ARGUMENT_ERROR)
     file_res = []
     try:
         for file_obj in file_objs:
             e, file = FileService.get_by_id(pf_id)
             if not e:
                 return get_data_error_result(
-                    retmsg="Can't find this folder!")
+                    message="Can't find this folder!")
             MAX_FILE_NUM_PER_USER = int(os.environ.get('MAX_FILE_NUM_PER_USER', 0))
             if MAX_FILE_NUM_PER_USER > 0 and DocumentService.get_doc_count(current_user.id) >= MAX_FILE_NUM_PER_USER:
                 return get_data_error_result(
-                    retmsg="Exceed the maximum file number of a free user!")
+                    message="Exceed the maximum file number of a free user!")
 
             # split file name path
             if not file_obj.filename:
@@ -85,13 +82,13 @@ def upload():
             if file_len != len_id_list:
                 e, file = FileService.get_by_id(file_id_list[len_id_list - 1])
                 if not e:
-                    return get_data_error_result(retmsg="Folder not found!")
+                    return get_data_error_result(message="Folder not found!")
                 last_folder = FileService.create_folder(file, file_id_list[len_id_list - 1], file_obj_names,
                                                         len_id_list)
             else:
                 e, file = FileService.get_by_id(file_id_list[len_id_list - 2])
                 if not e:
-                    return get_data_error_result(retmsg="Folder not found!")
+                    return get_data_error_result(message="Folder not found!")
                 last_folder = FileService.create_folder(file, file_id_list[len_id_list - 2], file_obj_names,
                                                         len_id_list)
 
@@ -137,10 +134,10 @@ def create():
     try:
         if not FileService.is_parent_folder_exist(pf_id):
             return get_json_result(
-                data=False, retmsg="Parent Folder Doesn't Exist!", retcode=RetCode.OPERATING_ERROR)
+                data=False, message="Parent Folder Doesn't Exist!", code=settings.RetCode.OPERATING_ERROR)
         if FileService.query(name=req["name"], parent_id=pf_id):
             return get_data_error_result(
-                retmsg="Duplicated folder name in the same folder.")
+                message="Duplicated folder name in the same folder.")
 
         if input_file_type == FileType.FOLDER.value:
             file_type = FileType.FOLDER.value
@@ -181,14 +178,14 @@ def list_files():
     try:
         e, file = FileService.get_by_id(pf_id)
         if not e:
-            return get_data_error_result(retmsg="Folder not found!")
+            return get_data_error_result(message="Folder not found!")
 
         files, total = FileService.get_by_pf_id(
             current_user.id, pf_id, page_number, items_per_page, orderby, desc, keywords)
 
         parent_folder = FileService.get_parent_folder(pf_id)
         if not FileService.get_parent_folder(pf_id):
-            return get_json_result(retmsg="File not found!")
+            return get_json_result(message="File not found!")
 
         return get_json_result(data={"total": total, "files": files, "parent_folder": parent_folder.to_json()})
     except Exception as e:
@@ -212,7 +209,7 @@ def get_parent_folder():
     try:
         e, file = FileService.get_by_id(file_id)
         if not e:
-            return get_data_error_result(retmsg="Folder not found!")
+            return get_data_error_result(message="Folder not found!")
 
         parent_folder = FileService.get_parent_folder(file_id)
         return get_json_result(data={"parent_folder": parent_folder.to_json()})
@@ -227,7 +224,7 @@ def get_all_parent_folders():
     try:
         e, file = FileService.get_by_id(file_id)
         if not e:
-            return get_data_error_result(retmsg="Folder not found!")
+            return get_data_error_result(message="Folder not found!")
 
         parent_folders = FileService.get_all_parent_folders(file_id)
         parent_folders_res = []
@@ -248,9 +245,9 @@ def rm():
         for file_id in file_ids:
             e, file = FileService.get_by_id(file_id)
             if not e:
-                return get_data_error_result(retmsg="File or Folder not found!")
+                return get_data_error_result(message="File or Folder not found!")
             if not file.tenant_id:
-                return get_data_error_result(retmsg="Tenant not found!")
+                return get_data_error_result(message="Tenant not found!")
             if file.source_type == FileSource.KNOWLEDGEBASE:
                 continue
 
@@ -259,13 +256,13 @@ def rm():
                 for inner_file_id in file_id_list:
                     e, file = FileService.get_by_id(inner_file_id)
                     if not e:
-                        return get_data_error_result(retmsg="File not found!")
+                        return get_data_error_result(message="File not found!")
                     STORAGE_IMPL.rm(file.parent_id, file.location)
                 FileService.delete_folder_by_pf_id(current_user.id, file_id)
             else:
                 if not FileService.delete(file):
                     return get_data_error_result(
-                        retmsg="Database error (File removal)!")
+                        message="Database error (File removal)!")
 
             # delete file2document
             informs = File2DocumentService.get_by_file_id(file_id)
@@ -273,13 +270,13 @@ def rm():
                 doc_id = inform.document_id
                 e, doc = DocumentService.get_by_id(doc_id)
                 if not e:
-                    return get_data_error_result(retmsg="Document not found!")
+                    return get_data_error_result(message="Document not found!")
                 tenant_id = DocumentService.get_tenant_id(doc_id)
                 if not tenant_id:
-                    return get_data_error_result(retmsg="Tenant not found!")
+                    return get_data_error_result(message="Tenant not found!")
                 if not DocumentService.remove_document(doc, tenant_id):
                     return get_data_error_result(
-                        retmsg="Database error (Document removal)!")
+                        message="Database error (Document removal)!")
             File2DocumentService.delete_by_file_id(file_id)
 
         return get_json_result(data=True)
@@ -295,30 +292,30 @@ def rename():
     try:
         e, file = FileService.get_by_id(req["file_id"])
         if not e:
-            return get_data_error_result(retmsg="File not found!")
+            return get_data_error_result(message="File not found!")
         if file.type != FileType.FOLDER.value \
             and pathlib.Path(req["name"].lower()).suffix != pathlib.Path(
                 file.name.lower()).suffix:
             return get_json_result(
                 data=False,
-                retmsg="The extension of file can't be changed",
-                retcode=RetCode.ARGUMENT_ERROR)
+                message="The extension of file can't be changed",
+                code=settings.RetCode.ARGUMENT_ERROR)
         for file in FileService.query(name=req["name"], pf_id=file.parent_id):
             if file.name == req["name"]:
                 return get_data_error_result(
-                    retmsg="Duplicated file name in the same folder.")
+                    message="Duplicated file name in the same folder.")
 
         if not FileService.update_by_id(
                 req["file_id"], {"name": req["name"]}):
             return get_data_error_result(
-                retmsg="Database error (File rename)!")
+                message="Database error (File rename)!")
 
         informs = File2DocumentService.get_by_file_id(req["file_id"])
         if informs:
             if not DocumentService.update_by_id(
                     informs[0].document_id, {"name": req["name"]}):
                 return get_data_error_result(
-                    retmsg="Database error (Document rename)!")
+                    message="Database error (Document rename)!")
 
         return get_json_result(data=True)
     except Exception as e:
@@ -331,7 +328,7 @@ def get(file_id):
     try:
         e, file = FileService.get_by_id(file_id)
         if not e:
-            return get_data_error_result(retmsg="Document not found!")
+            return get_data_error_result(message="Document not found!")
         b, n = File2DocumentService.get_storage_address(file_id=file_id)
         response = flask.make_response(STORAGE_IMPL.get(b, n))
         ext = re.search(r"\.([^.]+)$", file.name)
@@ -359,12 +356,12 @@ def move():
         for file_id in file_ids:
             e, file = FileService.get_by_id(file_id)
             if not e:
-                return get_data_error_result(retmsg="File or Folder not found!")
+                return get_data_error_result(message="File or Folder not found!")
             if not file.tenant_id:
-                return get_data_error_result(retmsg="Tenant not found!")
+                return get_data_error_result(message="Tenant not found!")
         fe, _ = FileService.get_by_id(parent_id)
         if not fe:
-            return get_data_error_result(retmsg="Parent Folder not found!")
+            return get_data_error_result(message="Parent Folder not found!")
         FileService.move_file(file_ids, parent_id)
         return get_json_result(data=True)
     except Exception as e:

api/apps/kb_app.py

@@ -13,7 +13,6 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-from elasticsearch_dsl import Q
 from flask import request
 from flask_login import login_required, current_user
 
@@ -23,14 +22,13 @@ from api.db.services.file2document_service import File2DocumentService
 from api.db.services.file_service import FileService
 from api.db.services.user_service import TenantService, UserTenantService
 from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
-from api.utils import get_uuid, get_format_time
-from api.db import StatusEnum, UserTenantRole, FileSource
+from api.utils import get_uuid
+from api.db import StatusEnum, FileSource
 from api.db.services.knowledgebase_service import KnowledgebaseService
-from api.db.db_models import Knowledgebase, File
-from api.settings import stat_logger, RetCode
+from api.db.db_models import File
 from api.utils.api_utils import get_json_result
+from api import settings
 from rag.nlp import search
-from rag.utils.es_conn import ELASTICSEARCH
 
 
 @manager.route('/create', methods=['post'])
@@ -50,7 +48,7 @@ def create():
         req["created_by"] = current_user.id
         e, t = TenantService.get_by_id(current_user.id)
         if not e:
-            return get_data_error_result(retmsg="Tenant not found.")
+            return get_data_error_result(message="Tenant not found.")
         req["embd_id"] = t.embd_id
         if not KnowledgebaseService.save(**req):
             return get_data_error_result()
@@ -65,21 +63,27 @@ def create():
 def update():
     req = request.json
     req["name"] = req["name"].strip()
+    if not KnowledgebaseService.accessible4deletion(req["kb_id"], current_user.id):
+        return get_json_result(
+            data=False,
+            message='No authorization.',
+            code=settings.RetCode.AUTHENTICATION_ERROR
+        )
     try:
         if not KnowledgebaseService.query(
                 created_by=current_user.id, id=req["kb_id"]):
             return get_json_result(
-                data=False, retmsg=f'Only owner of knowledgebase authorized for this operation.', retcode=RetCode.OPERATING_ERROR)
+                data=False, message='Only owner of knowledgebase authorized for this operation.', code=settings.RetCode.OPERATING_ERROR)
 
         e, kb = KnowledgebaseService.get_by_id(req["kb_id"])
         if not e:
             return get_data_error_result(
-                retmsg="Can't find this knowledgebase!")
+                message="Can't find this knowledgebase!")
 
         if req["name"].lower() != kb.name.lower() \
                 and len(KnowledgebaseService.query(name=req["name"], tenant_id=current_user.id, status=StatusEnum.VALID.value)) > 1:
             return get_data_error_result(
-                retmsg="Duplicated knowledgebase name.")
+                message="Duplicated knowledgebase name.")
 
         del req["kb_id"]
         if not KnowledgebaseService.update_by_id(kb.id, req):
@@ -88,7 +92,7 @@ def update():
         e, kb = KnowledgebaseService.get_by_id(kb.id)
         if not e:
             return get_data_error_result(
-                retmsg="Database error (Knowledgebase rename)!")
+                message="Database error (Knowledgebase rename)!")
 
         return get_json_result(data=kb.to_json())
     except Exception as e:
@@ -107,12 +111,12 @@ def detail():
                 break
         else:
             return get_json_result(
-                data=False, retmsg=f'Only owner of knowledgebase authorized for this operation.',
-                retcode=RetCode.OPERATING_ERROR)
+                data=False, message='Only owner of knowledgebase authorized for this operation.',
+                code=settings.RetCode.OPERATING_ERROR)
         kb = KnowledgebaseService.get_detail(kb_id)
         if not kb:
             return get_data_error_result(
-                retmsg="Can't find this knowledgebase!")
+                message="Can't find this knowledgebase!")
         return get_json_result(data=kb)
     except Exception as e:
         return server_error_response(e)
@@ -139,24 +143,32 @@ def list_kbs():
 @validate_request("kb_id")
 def rm():
     req = request.json
+    if not KnowledgebaseService.accessible4deletion(req["kb_id"], current_user.id):
+        return get_json_result(
+            data=False,
+            message='No authorization.',
+            code=settings.RetCode.AUTHENTICATION_ERROR
+        )
     try:
         kbs = KnowledgebaseService.query(
                 created_by=current_user.id, id=req["kb_id"])
         if not kbs:
             return get_json_result(
-                data=False, retmsg=f'Only owner of knowledgebase authorized for this operation.', retcode=RetCode.OPERATING_ERROR)
+                data=False, message='Only owner of knowledgebase authorized for this operation.', code=settings.RetCode.OPERATING_ERROR)
 
         for doc in DocumentService.query(kb_id=req["kb_id"]):
             if not DocumentService.remove_document(doc, kbs[0].tenant_id):
                 return get_data_error_result(
-                    retmsg="Database error (Document removal)!")
+                    message="Database error (Document removal)!")
             f2d = File2DocumentService.get_by_document_id(doc.id)
             FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.id == f2d[0].file_id])
+            FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.type == "folder", File.name == kbs[0].name])
             File2DocumentService.delete_by_document_id(doc.id)
 
         if not KnowledgebaseService.delete_by_id(req["kb_id"]):
             return get_data_error_result(
-                retmsg="Database error (Knowledgebase removal)!")
+                message="Database error (Knowledgebase removal)!")
+        settings.docStoreConn.delete({"kb_id": req["kb_id"]}, search.index_name(kbs[0].tenant_id), req["kb_id"])
         return get_json_result(data=True)
     except Exception as e:
         return server_error_response(e)

api/apps/llm_app.py

@@ -13,12 +13,13 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import json
 
 from flask import request
 from flask_login import login_required, current_user
 from api.db.services.llm_service import LLMFactoriesService, TenantLLMService, LLMService
-from api.settings import LIGHTEN
+from api import settings
 from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
 from api.db import StatusEnum, LLMType
 from api.db.db_models import TenantLLM
@@ -58,7 +59,7 @@ def set_api_key():
     chat_passed, embd_passed, rerank_passed = False, False, False
     factory = req["llm_factory"]
     msg = ""
-    for llm in LLMService.query(fid=factory)[:3]:
+    for llm in LLMService.query(fid=factory):
         if not embd_passed and llm.model_type == LLMType.EMBEDDING.value:
             mdl = EmbeddingModel[factory](
                 req["api_key"], llm.llm_name, base_url=req.get("base_url"))
@@ -73,14 +74,14 @@ def set_api_key():
             mdl = ChatModel[factory](
                 req["api_key"], llm.llm_name, base_url=req.get("base_url"))
             try:
-                m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], 
-                                 {"temperature": 0.9,'max_tokens':50})
-                if m.find("**ERROR**") >=0:
+                m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}],
+                                 {"temperature": 0.9, 'max_tokens': 50})
+                if m.find("**ERROR**") >= 0:
                     raise Exception(m)
+                chat_passed = True
             except Exception as e:
                 msg += f"\nFail to access model({llm.llm_name}) using this api key." + str(
                     e)
-            chat_passed = True
         elif not rerank_passed and llm.model_type == LLMType.RERANK:
             mdl = RerankModel[factory](
                 req["api_key"], llm.llm_name, base_url=req.get("base_url"))
@@ -88,13 +89,17 @@ def set_api_key():
                 arr, tc = mdl.similarity("What's the weather?", ["Is it sunny today?"])
                 if len(arr) == 0 or tc == 0:
                     raise Exception("Fail")
+                rerank_passed = True
+                logging.debug(f'passed model rerank {llm.llm_name}')
             except Exception as e:
                 msg += f"\nFail to access model({llm.llm_name}) using this api key." + str(
                     e)
-            rerank_passed = True
+        if any([embd_passed, chat_passed, rerank_passed]):
+            msg = ''
+            break
 
     if msg:
-        return get_data_error_result(retmsg=msg)
+        return get_data_error_result(message=msg)
 
     llm_config = {
         "api_key": req["api_key"],
@@ -105,6 +110,7 @@ def set_api_key():
             llm_config[n] = req[n]
 
     for llm in LLMService.query(fid=factory):
+        llm_config["max_tokens"]=llm.max_tokens
         if not TenantLLMService.filter_update(
                 [TenantLLM.tenant_id == current_user.id,
                  TenantLLM.llm_factory == factory,
@@ -116,7 +122,8 @@ def set_api_key():
                 llm_name=llm.llm_name,
                 model_type=llm.model_type,
                 api_key=llm_config["api_key"],
-                api_base=llm_config["api_base"]
+                api_base=llm_config["api_base"],
+                max_tokens=llm_config["max_tokens"]
             )
 
     return get_json_result(data=True)
@@ -153,23 +160,23 @@ def add_llm():
         api_key = apikey_json(["bedrock_ak", "bedrock_sk", "bedrock_region"])
 
     elif factory == "LocalAI":
-        llm_name = req["llm_name"]+"___LocalAI"
+        llm_name = req["llm_name"] + "___LocalAI"
         api_key = "xxxxxxxxxxxxxxx"
-        
+
     elif factory == "HuggingFace":
-        llm_name = req["llm_name"]+"___HuggingFace"
+        llm_name = req["llm_name"] + "___HuggingFace"
         api_key = "xxxxxxxxxxxxxxx"
 
     elif factory == "OpenAI-API-Compatible":
-        llm_name = req["llm_name"]+"___OpenAI-API"
-        api_key = req.get("api_key","xxxxxxxxxxxxxxx")
+        llm_name = req["llm_name"] + "___OpenAI-API"
+        api_key = req.get("api_key", "xxxxxxxxxxxxxxx")
 
-    elif factory =="XunFei Spark":
+    elif factory == "XunFei Spark":
         llm_name = req["llm_name"]
         if req["model_type"] == "chat":
             api_key = req.get("spark_api_password", "xxxxxxxxxxxxxxx")
         elif req["model_type"] == "tts":
-            api_key = apikey_json(["spark_app_id", "spark_api_secret","spark_api_key"])
+            api_key = apikey_json(["spark_app_id", "spark_api_secret", "spark_api_key"])
 
     elif factory == "BaiduYiyan":
         llm_name = req["llm_name"]
@@ -183,6 +190,10 @@ def add_llm():
         llm_name = req["llm_name"]
         api_key = apikey_json(["google_project_id", "google_region", "google_service_account_key"])
 
+    elif factory == "Azure-OpenAI":
+        llm_name = req["llm_name"]
+        api_key = apikey_json(["api_key", "api_version"])
+
     else:
         llm_name = req["llm_name"]
         api_key = req.get("api_key", "xxxxxxxxxxxxxxx")
@@ -193,14 +204,15 @@ def add_llm():
         "model_type": req["model_type"],
         "llm_name": llm_name,
         "api_base": req.get("api_base", ""),
-        "api_key": api_key
+        "api_key": api_key,
+        "max_tokens": req.get("max_tokens")
     }
 
     msg = ""
     if llm["model_type"] == LLMType.EMBEDDING.value:
         mdl = EmbeddingModel[factory](
             key=llm['api_key'],
-            model_name=llm["llm_name"], 
+            model_name=llm["llm_name"],
             base_url=llm["api_base"])
         try:
             arr, tc = mdl.encode(["Test if the api key is available"])
@@ -216,7 +228,7 @@ def add_llm():
         )
         try:
             m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], {
-                             "temperature": 0.9})
+                "temperature": 0.9})
             if not tc:
                 raise Exception(m)
         except Exception as e:
@@ -224,12 +236,12 @@ def add_llm():
                 e)
     elif llm["model_type"] == LLMType.RERANK:
         mdl = RerankModel[factory](
-            key=llm["api_key"], 
-            model_name=llm["llm_name"], 
+            key=llm["api_key"],
+            model_name=llm["llm_name"],
             base_url=llm["api_base"]
         )
         try:
-            arr, tc = mdl.similarity("Hello~ Ragflower!", ["Hi, there!"])
+            arr, tc = mdl.similarity("Hello~ Ragflower!", ["Hi, there!", "Ohh, my friend!"])
             if len(arr) == 0 or tc == 0:
                 raise Exception("Not known.")
         except Exception as e:
@@ -237,8 +249,8 @@ def add_llm():
                 e)
     elif llm["model_type"] == LLMType.IMAGE2TEXT.value:
         mdl = CvModel[factory](
-            key=llm["api_key"], 
-            model_name=llm["llm_name"], 
+            key=llm["api_key"],
+            model_name=llm["llm_name"],
             base_url=llm["api_base"]
         )
         try:
@@ -270,10 +282,11 @@ def add_llm():
         pass
 
     if msg:
-        return get_data_error_result(retmsg=msg)
+        return get_data_error_result(message=msg)
 
     if not TenantLLMService.filter_update(
-            [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == factory, TenantLLM.llm_name == llm["llm_name"]], llm):
+            [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == factory,
+             TenantLLM.llm_name == llm["llm_name"]], llm):
         TenantLLMService.save(**llm)
 
     return get_json_result(data=True)
@@ -285,7 +298,8 @@ def add_llm():
 def delete_llm():
     req = request.json
     TenantLLMService.filter_delete(
-            [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"], TenantLLM.llm_name == req["llm_name"]])
+        [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"],
+         TenantLLM.llm_name == req["llm_name"]])
     return get_json_result(data=True)
 
 
@@ -295,7 +309,7 @@ def delete_llm():
 def delete_factory():
     req = request.json
     TenantLLMService.filter_delete(
-            [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"]])
+        [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"]])
     return get_json_result(data=True)
 
 
@@ -323,8 +337,8 @@ def my_llms():
 @manager.route('/list', methods=['GET'])
 @login_required
 def list_app():
-    self_deploied = ["Youdao","FastEmbed", "BAAI", "Ollama", "Xinference", "LocalAI", "LM-Studio"]
-    weighted = ["Youdao","FastEmbed", "BAAI"] if LIGHTEN else []
+    self_deploied = ["Youdao", "FastEmbed", "BAAI", "Ollama", "Xinference", "LocalAI", "LM-Studio"]
+    weighted = ["Youdao", "FastEmbed", "BAAI"] if settings.LIGHTEN != 0 else []
     model_type = request.args.get("model_type")
     try:
         objs = TenantLLMService.query(tenant_id=current_user.id)
@@ -335,15 +349,15 @@ def list_app():
         for m in llms:
             m["available"] = m["fid"] in facts or m["llm_name"].lower() == "flag-embedding" or m["fid"] in self_deploied
 
-        llm_set = set([m["llm_name"] for m in llms])
+        llm_set = set([m["llm_name"] + "@" + m["fid"] for m in llms])
         for o in objs:
-            if not o.api_key:continue
-            if o.llm_name in llm_set:continue
+            if not o.api_key: continue
+            if o.llm_name + "@" + o.llm_factory in llm_set: continue
             llms.append({"llm_name": o.llm_name, "model_type": o.model_type, "fid": o.llm_factory, "available": True})
 
         res = {}
         for m in llms:
-            if model_type and m["model_type"].find(model_type)<0:
+            if model_type and m["model_type"].find(model_type) < 0:
                 continue
             if m["fid"] not in res:
                 res[m["fid"]] = []
@@ -351,4 +365,4 @@ def list_app():
 
         return get_json_result(data=res)
     except Exception as e:
-        return server_error_response(e)
+        return server_error_response(e)

api/apps/sdk/assistant.py

@@ -1,304 +0,0 @@
-#
-#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
-#
-#  Licensed under the Apache License, Version 2.0 (the "License");
-#  you may not use this file except in compliance with the License.
-#  You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-#  Unless required by applicable law or agreed to in writing, software
-#  distributed under the License is distributed on an "AS IS" BASIS,
-#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#  See the License for the specific language governing permissions and
-#  limitations under the License.
-#
-from flask import request
-
-from api.db import StatusEnum
-from api.db.db_models import TenantLLM
-from api.db.services.dialog_service import DialogService
-from api.db.services.knowledgebase_service import KnowledgebaseService
-from api.db.services.llm_service import LLMService, TenantLLMService
-from api.db.services.user_service import TenantService
-from api.settings import RetCode
-from api.utils import get_uuid
-from api.utils.api_utils import get_data_error_result, token_required
-from api.utils.api_utils import get_json_result
-
-
-@manager.route('/save', methods=['POST'])
-@token_required
-def save(tenant_id):
-    req = request.json
-    # dataset
-    if req.get("knowledgebases") == []:
-        return get_data_error_result(retmsg="knowledgebases can not be empty list")
-    kb_list = []
-    if req.get("knowledgebases"):
-        for kb in req.get("knowledgebases"):
-            if not kb["id"]:
-                return get_data_error_result(retmsg="knowledgebase needs id")
-            if not KnowledgebaseService.query(id=kb["id"], tenant_id=tenant_id):
-                return get_data_error_result(retmsg="you do not own the knowledgebase")
-            # if not DocumentService.query(kb_id=kb["id"]):
-            #  return get_data_error_result(retmsg="There is a invalid knowledgebase")
-            kb_list.append(kb["id"])
-    req["kb_ids"] = kb_list
-    # llm
-    llm = req.get("llm")
-    if llm:
-        if "model_name" in llm:
-            req["llm_id"] = llm.pop("model_name")
-        req["llm_setting"] = req.pop("llm")
-    e, tenant = TenantService.get_by_id(tenant_id)
-    if not e:
-        return get_data_error_result(retmsg="Tenant not found!")
-    # prompt
-    prompt = req.get("prompt")
-    key_mapping = {"parameters": "variables",
-                   "prologue": "opener",
-                   "quote": "show_quote",
-                   "system": "prompt",
-                   "rerank_id": "rerank_model",
-                   "vector_similarity_weight": "keywords_similarity_weight"}
-    key_list = ["similarity_threshold", "vector_similarity_weight", "top_n", "rerank_id"]
-    if prompt:
-        for new_key, old_key in key_mapping.items():
-            if old_key in prompt:
-                prompt[new_key] = prompt.pop(old_key)
-        for key in key_list:
-            if key in prompt:
-                req[key] = prompt.pop(key)
-        req["prompt_config"] = req.pop("prompt")
-    # create
-    if "id" not in req:
-        # dataset
-        if not kb_list:
-            return get_data_error_result(retmsg="knowledgebases are required!")
-        # init
-        req["id"] = get_uuid()
-        req["description"] = req.get("description", "A helpful Assistant")
-        req["icon"] = req.get("avatar", "")
-        req["top_n"] = req.get("top_n", 6)
-        req["top_k"] = req.get("top_k", 1024)
-        req["rerank_id"] = req.get("rerank_id", "")
-        if req.get("llm_id"):
-            if not TenantLLMService.query(llm_name=req["llm_id"]):
-                return get_data_error_result(retmsg="the model_name does not exist.")
-        else:
-            req["llm_id"] = tenant.llm_id
-        if not req.get("name"):
-            return get_data_error_result(retmsg="name is required.")
-        if DialogService.query(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value):
-            return get_data_error_result(retmsg="Duplicated assistant name in creating dataset.")
-        # tenant_id
-        if req.get("tenant_id"):
-            return get_data_error_result(retmsg="tenant_id must not be provided.")
-        req["tenant_id"] = tenant_id
-        # prompt more parameter
-        default_prompt = {
-            "system": """你是一个智能助手，请总结知识库的内容来回答问题，请列举知识库中的数据详细回答。当所有知识库内容都与问题无关时，你的回答必须包括“知识库中未找到您要的答案！”这句话。回答需要考虑聊天历史。
-                以下是知识库：
-                {knowledge}
-                以上是知识库。""",
-            "prologue": "您好，我是您的助手小樱，长得可爱又善良，can I help you?",
-            "parameters": [
-                {"key": "knowledge", "optional": False}
-            ],
-            "empty_response": "Sorry! 知识库中未找到相关内容！"
-        }
-        key_list_2 = ["system", "prologue", "parameters", "empty_response"]
-        if "prompt_config" not in req:
-            req['prompt_config'] = {}
-        for key in key_list_2:
-            temp = req['prompt_config'].get(key)
-            if not temp:
-                req['prompt_config'][key] = default_prompt[key]
-        for p in req['prompt_config']["parameters"]:
-            if p["optional"]:
-                continue
-            if req['prompt_config']["system"].find("{%s}" % p["key"]) < 0:
-                return get_data_error_result(
-                    retmsg="Parameter '{}' is not used".format(p["key"]))
-        # save
-        if not DialogService.save(**req):
-            return get_data_error_result(retmsg="Fail to new an assistant!")
-        # response
-        e, res = DialogService.get_by_id(req["id"])
-        if not e:
-            return get_data_error_result(retmsg="Fail to new an assistant!")
-        res = res.to_json()
-        renamed_dict = {}
-        for key, value in res["prompt_config"].items():
-            new_key = key_mapping.get(key, key)
-            renamed_dict[new_key] = value
-        res["prompt"] = renamed_dict
-        del res["prompt_config"]
-        new_dict = {"similarity_threshold": res["similarity_threshold"],
-                    "keywords_similarity_weight": res["vector_similarity_weight"],
-                    "top_n": res["top_n"],
-                    "rerank_model": res['rerank_id']}
-        res["prompt"].update(new_dict)
-        for key in key_list:
-            del res[key]
-        res["llm"] = res.pop("llm_setting")
-        res["llm"]["model_name"] = res.pop("llm_id")
-        del res["kb_ids"]
-        res["knowledgebases"] = req["knowledgebases"]
-        res["avatar"] = res.pop("icon")
-        return get_json_result(data=res)
-    else:
-        # authorization
-        if not DialogService.query(tenant_id=tenant_id, id=req["id"], status=StatusEnum.VALID.value):
-            return get_json_result(data=False, retmsg='You do not own the assistant', retcode=RetCode.OPERATING_ERROR)
-        # prompt
-        if not req["id"]:
-            return get_data_error_result(retmsg="id can not be empty")
-        e, res = DialogService.get_by_id(req["id"])
-        res = res.to_json()
-        if "llm_id" in req:
-            if not TenantLLMService.query(llm_name=req["llm_id"]):
-                return get_data_error_result(retmsg="the model_name does not exist.")
-        if "name" in req:
-            if not req.get("name"):
-                return get_data_error_result(retmsg="name is not empty.")
-            if req["name"].lower() != res["name"].lower() \
-                    and len(
-                DialogService.query(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value)) > 0:
-                return get_data_error_result(retmsg="Duplicated assistant name in updating dataset.")
-        if "prompt_config" in req:
-            res["prompt_config"].update(req["prompt_config"])
-            for p in res["prompt_config"]["parameters"]:
-                if p["optional"]:
-                    continue
-                if res["prompt_config"]["system"].find("{%s}" % p["key"]) < 0:
-                    return get_data_error_result(retmsg="Parameter '{}' is not used".format(p["key"]))
-        if "llm_setting" in req:
-            res["llm_setting"].update(req["llm_setting"])
-        req["prompt_config"] = res["prompt_config"]
-        req["llm_setting"] = res["llm_setting"]
-        # avatar
-        if "avatar" in req:
-            req["icon"] = req.pop("avatar")
-        assistant_id = req.pop("id")
-        if "knowledgebases" in req:
-            req.pop("knowledgebases")
-        if not DialogService.update_by_id(assistant_id, req):
-            return get_data_error_result(retmsg="Assistant not found!")
-        return get_json_result(data=True)
-
-
-@manager.route('/delete', methods=['DELETE'])
-@token_required
-def delete(tenant_id):
-    req = request.args
-    if "id" not in req:
-        return get_data_error_result(retmsg="id is required")
-    id = req['id']
-    if not DialogService.query(tenant_id=tenant_id, id=id, status=StatusEnum.VALID.value):
-        return get_json_result(data=False, retmsg='you do not own the assistant.', retcode=RetCode.OPERATING_ERROR)
-
-    temp_dict = {"status": StatusEnum.INVALID.value}
-    DialogService.update_by_id(req["id"], temp_dict)
-    return get_json_result(data=True)
-
-
-@manager.route('/get', methods=['GET'])
-@token_required
-def get(tenant_id):
-    req = request.args
-    if "id" in req:
-        id = req["id"]
-        ass = DialogService.query(tenant_id=tenant_id, id=id, status=StatusEnum.VALID.value)
-        if not ass:
-            return get_json_result(data=False, retmsg='You do not own the assistant.', retcode=RetCode.OPERATING_ERROR)
-        if "name" in req:
-            name = req["name"]
-            if ass[0].name != name:
-                return get_json_result(data=False, retmsg='name does not match id.', retcode=RetCode.OPERATING_ERROR)
-        res = ass[0].to_json()
-    else:
-        if "name" in req:
-            name = req["name"]
-            ass = DialogService.query(name=name, tenant_id=tenant_id, status=StatusEnum.VALID.value)
-            if not ass:
-                return get_json_result(data=False, retmsg='You do not own the assistant.',
-                                       retcode=RetCode.OPERATING_ERROR)
-            res = ass[0].to_json()
-        else:
-            return get_data_error_result(retmsg="At least one of `id` or `name` must be provided.")
-    renamed_dict = {}
-    key_mapping = {"parameters": "variables",
-                   "prologue": "opener",
-                   "quote": "show_quote",
-                   "system": "prompt",
-                   "rerank_id": "rerank_model",
-                   "vector_similarity_weight": "keywords_similarity_weight"}
-    key_list = ["similarity_threshold", "vector_similarity_weight", "top_n", "rerank_id"]
-    for key, value in res["prompt_config"].items():
-        new_key = key_mapping.get(key, key)
-        renamed_dict[new_key] = value
-    res["prompt"] = renamed_dict
-    del res["prompt_config"]
-    new_dict = {"similarity_threshold": res["similarity_threshold"],
-                "keywords_similarity_weight": res["vector_similarity_weight"],
-                "top_n": res["top_n"],
-                "rerank_model": res['rerank_id']}
-    res["prompt"].update(new_dict)
-    for key in key_list:
-        del res[key]
-    res["llm"] = res.pop("llm_setting")
-    res["llm"]["model_name"] = res.pop("llm_id")
-    kb_list = []
-    for kb_id in res["kb_ids"]:
-        kb = KnowledgebaseService.query(id=kb_id)
-        kb_list.append(kb[0].to_json())
-    del res["kb_ids"]
-    res["knowledgebases"] = kb_list
-    res["avatar"] = res.pop("icon")
-    return get_json_result(data=res)
-
-
-@manager.route('/list', methods=['GET'])
-@token_required
-def list_assistants(tenant_id):
-    assts = DialogService.query(
-        tenant_id=tenant_id,
-        status=StatusEnum.VALID.value,
-        reverse=True,
-        order_by=DialogService.model.create_time)
-    assts = [d.to_dict() for d in assts]
-    list_assts = []
-    renamed_dict = {}
-    key_mapping = {"parameters": "variables",
-                   "prologue": "opener",
-                   "quote": "show_quote",
-                   "system": "prompt",
-                   "rerank_id": "rerank_model",
-                   "vector_similarity_weight": "keywords_similarity_weight"}
-    key_list = ["similarity_threshold", "vector_similarity_weight", "top_n", "rerank_id"]
-    for res in assts:
-        for key, value in res["prompt_config"].items():
-            new_key = key_mapping.get(key, key)
-            renamed_dict[new_key] = value
-        res["prompt"] = renamed_dict
-        del res["prompt_config"]
-        new_dict = {"similarity_threshold": res["similarity_threshold"],
-                    "keywords_similarity_weight": res["vector_similarity_weight"],
-                    "top_n": res["top_n"],
-                    "rerank_model": res['rerank_id']}
-        res["prompt"].update(new_dict)
-        for key in key_list:
-            del res[key]
-        res["llm"] = res.pop("llm_setting")
-        res["llm"]["model_name"] = res.pop("llm_id")
-        kb_list = []
-        for kb_id in res["kb_ids"]:
-            kb = KnowledgebaseService.query(id=kb_id)
-            kb_list.append(kb[0].to_json())
-        del res["kb_ids"]
-        res["knowledgebases"] = kb_list
-        res["avatar"] = res.pop("icon")
-        list_assts.append(res)
-    return get_json_result(data=list_assts)

api/apps/sdk/chat.py

@@ -0,0 +1,313 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from flask import request
+from api import settings
+from api.db import StatusEnum
+from api.db.services.dialog_service import DialogService
+from api.db.services.knowledgebase_service import KnowledgebaseService
+from api.db.services.llm_service import  TenantLLMService
+from api.db.services.user_service import TenantService
+from api.utils import get_uuid
+from api.utils.api_utils import get_error_data_result, token_required
+from api.utils.api_utils import get_result
+
+
+
+@manager.route('/chats', methods=['POST'])
+@token_required
+def create(tenant_id):
+    req=request.json
+    ids= req.get("dataset_ids")
+    if not ids:
+        return get_error_data_result(message="`dataset_ids` is required")
+    for kb_id in ids:
+        kbs = KnowledgebaseService.accessible(kb_id=kb_id,user_id=tenant_id)
+        if not kbs:
+            return get_error_data_result(f"You don't own the dataset {kb_id}")
+        kbs = KnowledgebaseService.query(id=kb_id)
+        kb = kbs[0]
+        if kb.chunk_num == 0:
+            return get_error_data_result(f"The dataset {kb_id} doesn't own parsed file")
+    kbs = KnowledgebaseService.get_by_ids(ids)
+    embd_count = list(set([kb.embd_id for kb in kbs]))
+    if len(embd_count) != 1:
+        return get_result(message='Datasets use different embedding models."',code=settings.RetCode.AUTHENTICATION_ERROR)
+    req["kb_ids"] = ids
+    # llm
+    llm = req.get("llm")
+    if llm:
+        if "model_name" in llm:
+            req["llm_id"] = llm.pop("model_name")
+            if not TenantLLMService.query(tenant_id=tenant_id,llm_name=req["llm_id"],model_type="chat"):
+                return get_error_data_result(f"`model_name` {req.get('llm_id')} doesn't exist")
+        req["llm_setting"] = req.pop("llm")
+    e, tenant = TenantService.get_by_id(tenant_id)
+    if not e:
+        return get_error_data_result(message="Tenant not found!")
+    # prompt
+    prompt = req.get("prompt")
+    key_mapping = {"parameters": "variables",
+                   "prologue": "opener",
+                   "quote": "show_quote",
+                   "system": "prompt",
+                   "rerank_id": "rerank_model",
+                   "vector_similarity_weight": "keywords_similarity_weight"}
+    key_list = ["similarity_threshold", "vector_similarity_weight", "top_n", "rerank_id"]
+    if prompt:
+        for new_key, old_key in key_mapping.items():
+            if old_key in prompt:
+                prompt[new_key] = prompt.pop(old_key)
+        for key in key_list:
+            if key in prompt:
+                req[key] = prompt.pop(key)
+        req["prompt_config"] = req.pop("prompt")
+    # init
+    req["id"] = get_uuid()
+    req["description"] = req.get("description", "A helpful Assistant")
+    req["icon"] = req.get("avatar", "")
+    req["top_n"] = req.get("top_n", 6)
+    req["top_k"] = req.get("top_k", 1024)
+    req["rerank_id"] = req.get("rerank_id", "")
+    if req.get("rerank_id"):
+        if not TenantLLMService.query(tenant_id=tenant_id,llm_name=req.get("rerank_id"),model_type="rerank"):
+            return get_error_data_result(f"`rerank_model` {req.get('rerank_id')} doesn't exist")
+    if not req.get("llm_id"):
+        req["llm_id"] = tenant.llm_id
+    if not req.get("name"):
+        return get_error_data_result(message="`name` is required.")
+    if DialogService.query(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value):
+        return get_error_data_result(message="Duplicated chat name in creating chat.")
+    # tenant_id
+    if req.get("tenant_id"):
+        return get_error_data_result(message="`tenant_id` must not be provided.")
+    req["tenant_id"] = tenant_id
+    # prompt more parameter
+    default_prompt = {
+        "system": """You are an intelligent assistant. Please summarize the content of the knowledge base to answer the question. Please list the data in the knowledge base and answer in detail. When all knowledge base content is irrelevant to the question, your answer must include the sentence "The answer you are looking for is not found in the knowledge base!" Answers need to consider chat history.
+      Here is the knowledge base:
+      {knowledge}
+      The above is the knowledge base.""",
+        "prologue": "Hi! I'm your assistant, what can I do for you?",
+        "parameters": [
+            {"key": "knowledge", "optional": False}
+        ],
+        "empty_response": "Sorry! No relevant content was found in the knowledge base!"
+    }
+    key_list_2 = ["system", "prologue", "parameters", "empty_response"]
+    if "prompt_config" not in req:
+        req['prompt_config'] = {}
+    for key in key_list_2:
+        temp = req['prompt_config'].get(key)
+        if (not temp and key == 'system') or (key not in req["prompt_config"]):
+            req['prompt_config'][key] = default_prompt[key]
+    for p in req['prompt_config']["parameters"]:
+        if p["optional"]:
+            continue
+        if req['prompt_config']["system"].find("{%s}" % p["key"]) < 0:
+            return get_error_data_result(
+                message="Parameter '{}' is not used".format(p["key"]))
+    # save
+    if not DialogService.save(**req):
+        return get_error_data_result(message="Fail to new a chat!")
+    # response
+    e, res = DialogService.get_by_id(req["id"])
+    if not e:
+        return get_error_data_result(message="Fail to new a chat!")
+    res = res.to_json()
+    renamed_dict = {}
+    for key, value in res["prompt_config"].items():
+        new_key = key_mapping.get(key, key)
+        renamed_dict[new_key] = value
+    res["prompt"] = renamed_dict
+    del res["prompt_config"]
+    new_dict = {"similarity_threshold": res["similarity_threshold"],
+                "keywords_similarity_weight": res["vector_similarity_weight"],
+                "top_n": res["top_n"],
+                "rerank_model": res['rerank_id']}
+    res["prompt"].update(new_dict)
+    for key in key_list:
+        del res[key]
+    res["llm"] = res.pop("llm_setting")
+    res["llm"]["model_name"] = res.pop("llm_id")
+    del res["kb_ids"]
+    res["dataset_ids"] = req["dataset_ids"]
+    res["avatar"] = res.pop("icon")
+    return get_result(data=res)
+
+@manager.route('/chats/<chat_id>', methods=['PUT'])
+@token_required
+def update(tenant_id,chat_id):
+    if not DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value):
+        return get_error_data_result(message='You do not own the chat')
+    req =request.json
+    ids = req.get("dataset_ids")
+    if "show_quotation" in req:
+        req["do_refer"]=req.pop("show_quotation")
+    if "dataset_ids" in req:
+        if not ids:
+            return get_error_data_result("`datasets` can't be empty")
+        if ids:
+            for kb_id in ids:
+                kbs = KnowledgebaseService.accessible(kb_id=chat_id, user_id=tenant_id)
+                if not kbs:
+                    return get_error_data_result(f"You don't own the dataset {kb_id}")
+                kbs = KnowledgebaseService.query(id=kb_id)
+                kb = kbs[0]
+                if kb.chunk_num == 0:
+                    return get_error_data_result(f"The dataset {kb_id} doesn't own parsed file")
+            kbs = KnowledgebaseService.get_by_ids(ids)
+            embd_count=list(set([kb.embd_id for kb in kbs]))
+            if len(embd_count) != 1 :
+                return get_result(
+                    message='Datasets use different embedding models."',
+                    code=settings.RetCode.AUTHENTICATION_ERROR)
+            req["kb_ids"] = ids
+    llm = req.get("llm")
+    if llm:
+        if "model_name" in llm:
+            req["llm_id"] = llm.pop("model_name")
+            if not TenantLLMService.query(tenant_id=tenant_id,llm_name=req["llm_id"],model_type="chat"):
+                return get_error_data_result(f"`model_name` {req.get('llm_id')} doesn't exist")
+        req["llm_setting"] = req.pop("llm")
+    e, tenant = TenantService.get_by_id(tenant_id)
+    if not e:
+        return get_error_data_result(message="Tenant not found!")
+    if req.get("rerank_model"):
+        if not TenantLLMService.query(tenant_id=tenant_id,llm_name=req.get("rerank_model"),model_type="rerank"):
+            return get_error_data_result(f"`rerank_model` {req.get('rerank_model')} doesn't exist")
+    # prompt
+    prompt = req.get("prompt")
+    key_mapping = {"parameters": "variables",
+                   "prologue": "opener",
+                   "quote": "show_quote",
+                   "system": "prompt",
+                   "rerank_id": "rerank_model",
+                   "vector_similarity_weight": "keywords_similarity_weight"}
+    key_list = ["similarity_threshold", "vector_similarity_weight", "top_n", "rerank_id"]
+    if prompt:
+        for new_key, old_key in key_mapping.items():
+            if old_key in prompt:
+                prompt[new_key] = prompt.pop(old_key)
+        for key in key_list:
+            if key in prompt:
+                req[key] = prompt.pop(key)
+        req["prompt_config"] = req.pop("prompt")
+    e, res = DialogService.get_by_id(chat_id)
+    res = res.to_json()
+    if "name" in req:
+        if not req.get("name"):
+            return get_error_data_result(message="`name` is not empty.")
+        if req["name"].lower() != res["name"].lower() \
+                and len(
+            DialogService.query(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value)) > 0:
+            return get_error_data_result(message="Duplicated chat name in updating dataset.")
+    if "prompt_config" in req:
+        res["prompt_config"].update(req["prompt_config"])
+        for p in res["prompt_config"]["parameters"]:
+            if p["optional"]:
+                continue
+            if res["prompt_config"]["system"].find("{%s}" % p["key"]) < 0:
+                return get_error_data_result(message="Parameter '{}' is not used".format(p["key"]))
+    if "llm_setting" in req:
+        res["llm_setting"].update(req["llm_setting"])
+    req["prompt_config"] = res["prompt_config"]
+    req["llm_setting"] = res["llm_setting"]
+    # avatar
+    if "avatar" in req:
+        req["icon"] = req.pop("avatar")
+    if "dataset_ids" in req:
+        req.pop("dataset_ids")
+    if not DialogService.update_by_id(chat_id, req):
+        return get_error_data_result(message="Chat not found!")
+    return get_result()
+
+
+@manager.route('/chats', methods=['DELETE'])
+@token_required
+def delete(tenant_id):
+    req = request.json
+    if not req:
+        ids=None
+    else:
+        ids=req.get("ids")
+    if not ids:
+        id_list = []
+        dias=DialogService.query(tenant_id=tenant_id,status=StatusEnum.VALID.value)
+        for dia in dias:
+            id_list.append(dia.id)
+    else:
+        id_list=ids
+    for id in id_list:
+        if not DialogService.query(tenant_id=tenant_id, id=id, status=StatusEnum.VALID.value):
+            return get_error_data_result(message=f"You don't own the chat {id}")
+        temp_dict = {"status": StatusEnum.INVALID.value}
+        DialogService.update_by_id(id, temp_dict)
+    return get_result()
+
+@manager.route('/chats', methods=['GET'])
+@token_required
+def list_chat(tenant_id):
+    id = request.args.get("id")
+    name = request.args.get("name")
+    chat = DialogService.query(id=id,name=name,status=StatusEnum.VALID.value,tenant_id=tenant_id)
+    if not chat:
+        return get_error_data_result(message="The chat doesn't exist")
+    page_number = int(request.args.get("page", 1))
+    items_per_page = int(request.args.get("page_size", 30))
+    orderby = request.args.get("orderby", "create_time")
+    if request.args.get("desc") == "False" or request.args.get("desc") == "false":
+        desc = False
+    else:
+        desc = True
+    chats = DialogService.get_list(tenant_id,page_number,items_per_page,orderby,desc,id,name)
+    if not chats:
+        return get_result(data=[])
+    list_assts = []
+    renamed_dict = {}
+    key_mapping = {"parameters": "variables",
+                   "prologue": "opener",
+                   "quote": "show_quote",
+                   "system": "prompt",
+                   "rerank_id": "rerank_model",
+                   "vector_similarity_weight": "keywords_similarity_weight",
+                   "do_refer":"show_quotation"}
+    key_list = ["similarity_threshold", "vector_similarity_weight", "top_n", "rerank_id"]
+    for res in chats:
+        for key, value in res["prompt_config"].items():
+            new_key = key_mapping.get(key, key)
+            renamed_dict[new_key] = value
+        res["prompt"] = renamed_dict
+        del res["prompt_config"]
+        new_dict = {"similarity_threshold": res["similarity_threshold"],
+                    "keywords_similarity_weight": res["vector_similarity_weight"],
+                    "top_n": res["top_n"],
+                    "rerank_model": res['rerank_id']}
+        res["prompt"].update(new_dict)
+        for key in key_list:
+            del res[key]
+        res["llm"] = res.pop("llm_setting")
+        res["llm"]["model_name"] = res.pop("llm_id")
+        kb_list = []
+        for kb_id in res["kb_ids"]:
+            kb = KnowledgebaseService.query(id=kb_id)
+            if not kb :
+                return get_error_data_result(message=f"Don't exist the kb {kb_id}")
+            kb_list.append(kb[0].to_json())
+        del res["kb_ids"]
+        res["datasets"] = kb_list
+        res["avatar"] = res.pop("icon")
+        list_assts.append(res)
+    return get_result(data=list_assts)

api/apps/sdk/dataset.py

@@ -1,224 +1,531 @@
-#
-#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
-#
-#  Licensed under the Apache License, Version 2.0 (the "License");
-#  you may not use this file except in compliance with the License.
-#  You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-#  Unless required by applicable law or agreed to in writing, software
-#  distributed under the License is distributed on an "AS IS" BASIS,
-#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#  See the License for the specific language governing permissions and
-#  limitations under the License.
-#
-
-from flask import request
-
-from api.db import StatusEnum, FileSource
-from api.db.db_models import File
-from api.db.services.document_service import DocumentService
-from api.db.services.file2document_service import File2DocumentService
-from api.db.services.file_service import FileService
-from api.db.services.knowledgebase_service import KnowledgebaseService
-from api.db.services.user_service import TenantService
-from api.settings import RetCode
-from api.utils import get_uuid
-from api.utils.api_utils import get_json_result, token_required, get_data_error_result
-
-
-@manager.route('/save', methods=['POST'])
-@token_required
-def save(tenant_id):
-    req = request.json
-    e, t = TenantService.get_by_id(tenant_id)
-    if "id" not in req:
-        if "tenant_id" in req or "embedding_model" in req:
-            return get_data_error_result(
-                retmsg="Tenant_id or embedding_model must not be provided")
-        if "name" not in req:
-            return get_data_error_result(
-                retmsg="Name is not empty!")
-        req['id'] = get_uuid()
-        req["name"] = req["name"].strip()
-        if req["name"] == "":
-            return get_data_error_result(
-                retmsg="Name is not empty string!")
-        if KnowledgebaseService.query(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value):
-            return get_data_error_result(
-                retmsg="Duplicated knowledgebase name in creating dataset.")
-        req["tenant_id"] = req['created_by'] = tenant_id
-        req['embedding_model'] = t.embd_id
-        key_mapping = {
-            "chunk_num": "chunk_count",
-            "doc_num": "document_count",
-            "parser_id": "parse_method",
-            "embd_id": "embedding_model"
-        }
-        mapped_keys = {new_key: req[old_key] for new_key, old_key in key_mapping.items() if old_key in req}
-        req.update(mapped_keys)
-        if not KnowledgebaseService.save(**req):
-            return get_data_error_result(retmsg="Create dataset error.(Database error)")
-        renamed_data = {}
-        e, k = KnowledgebaseService.get_by_id(req["id"])
-        for key, value in k.to_dict().items():
-            new_key = key_mapping.get(key, key)
-            renamed_data[new_key] = value
-        return get_json_result(data=renamed_data)
-    else:
-        invalid_keys = {"embd_id", "chunk_num", "doc_num", "parser_id"}
-        if any(key in req for key in invalid_keys):
-            return get_data_error_result(retmsg="The input parameters are invalid.")
-
-        if "tenant_id" in req:
-            if req["tenant_id"] != tenant_id:
-                return get_data_error_result(
-                    retmsg="Can't change tenant_id.")
-
-        if "embedding_model" in req:
-            if req["embedding_model"] != t.embd_id:
-                return get_data_error_result(
-                    retmsg="Can't change embedding_model.")
-            req.pop("embedding_model")
-
-        if not KnowledgebaseService.query(
-                created_by=tenant_id, id=req["id"]):
-            return get_json_result(
-                data=False, retmsg='You do not own the dataset.',
-                retcode=RetCode.OPERATING_ERROR)
-
-        if not req["id"]:
-            return get_data_error_result(
-                retmsg="id can not be empty.")
-        e, kb = KnowledgebaseService.get_by_id(req["id"])
-
-        if "chunk_count" in req:
-            if req["chunk_count"] != kb.chunk_num:
-                return get_data_error_result(
-                    retmsg="Can't change chunk_count.")
-            req.pop("chunk_count")
-
-        if "document_count" in req:
-            if req['document_count'] != kb.doc_num:
-                return get_data_error_result(
-                    retmsg="Can't change document_count.")
-            req.pop("document_count")
-
-        if "parse_method" in req:
-            if kb.chunk_num != 0 and req['parse_method'] != kb.parser_id:
-                return get_data_error_result(
-                    retmsg="If chunk count is not 0, parse method is not changable.")
-            req['parser_id'] = req.pop('parse_method')
-        if "name" in req:
-            req["name"] = req["name"].strip()
-            if req["name"].lower() != kb.name.lower() \
-                    and len(KnowledgebaseService.query(name=req["name"], tenant_id=tenant_id,
-                                                       status=StatusEnum.VALID.value)) > 0:
-                return get_data_error_result(
-                    retmsg="Duplicated knowledgebase name in updating dataset.")
-
-        del req["id"]
-        if not KnowledgebaseService.update_by_id(kb.id, req):
-            return get_data_error_result(retmsg="Update dataset error.(Database error)")
-        return get_json_result(data=True)
-
-
-@manager.route('/delete', methods=['DELETE'])
-@token_required
-def delete(tenant_id):
-    req = request.args
-    if "id" not in req:
-        return get_data_error_result(
-            retmsg="id is required")
-    kbs = KnowledgebaseService.query(
-        created_by=tenant_id, id=req["id"])
-    if not kbs:
-        return get_json_result(
-            data=False, retmsg='You do not own the dataset',
-            retcode=RetCode.OPERATING_ERROR)
-
-    for doc in DocumentService.query(kb_id=req["id"]):
-        if not DocumentService.remove_document(doc, kbs[0].tenant_id):
-            return get_data_error_result(
-                retmsg="Remove document error.(Database error)")
-        f2d = File2DocumentService.get_by_document_id(doc.id)
-        FileService.filter_delete([File.source_type == FileSource.KNOWLEDGEBASE, File.id == f2d[0].file_id])
-        File2DocumentService.delete_by_document_id(doc.id)
-
-    if not KnowledgebaseService.delete_by_id(req["id"]):
-        return get_data_error_result(
-            retmsg="Delete dataset error.(Database serror)")
-    return get_json_result(data=True)
-
-
-@manager.route('/list', methods=['GET'])
-@token_required
-def list_datasets(tenant_id):
-    page_number = int(request.args.get("page", 1))
-    items_per_page = int(request.args.get("page_size", 1024))
-    orderby = request.args.get("orderby", "create_time")
-    desc = bool(request.args.get("desc", True))
-    tenants = TenantService.get_joined_tenants_by_user_id(tenant_id)
-    kbs = KnowledgebaseService.get_by_tenant_ids(
-        [m["tenant_id"] for m in tenants], tenant_id, page_number, items_per_page, orderby, desc)
-    renamed_list = []
-    for kb in kbs:
-        key_mapping = {
-            "chunk_num": "chunk_count",
-            "doc_num": "document_count",
-            "parser_id": "parse_method",
-            "embd_id": "embedding_model"
-        }
-        renamed_data = {}
-        for key, value in kb.items():
-            new_key = key_mapping.get(key, key)
-            renamed_data[new_key] = value
-        renamed_list.append(renamed_data)
-    return get_json_result(data=renamed_list)
-
-
-@manager.route('/detail', methods=['GET'])
-@token_required
-def detail(tenant_id):
-    req = request.args
-    key_mapping = {
-        "chunk_num": "chunk_count",
-        "doc_num": "document_count",
-        "parser_id": "parse_method",
-        "embd_id": "embedding_model"
-    }
-    renamed_data = {}
-    if "id" in req:
-        id = req["id"]
-        kb = KnowledgebaseService.query(created_by=tenant_id, id=req["id"])
-        if not kb:
-            return get_json_result(
-                data=False, retmsg='You do not own the dataset.',
-                retcode=RetCode.OPERATING_ERROR)
-        if "name" in req:
-            name = req["name"]
-            if kb[0].name != name:
-                return get_json_result(
-                    data=False, retmsg='You do not own the dataset.',
-                    retcode=RetCode.OPERATING_ERROR)
-        e, k = KnowledgebaseService.get_by_id(id)
-        for key, value in k.to_dict().items():
-            new_key = key_mapping.get(key, key)
-            renamed_data[new_key] = value
-        return get_json_result(data=renamed_data)
-    else:
-        if "name" in req:
-            name = req["name"]
-            e, k = KnowledgebaseService.get_by_name(kb_name=name, tenant_id=tenant_id)
-            if not e:
-                return get_json_result(
-                    data=False, retmsg='You do not own the dataset.',
-                    retcode=RetCode.OPERATING_ERROR)
-            for key, value in k.to_dict().items():
-                new_key = key_mapping.get(key, key)
-                renamed_data[new_key] = value
-            return get_json_result(data=renamed_data)
-        else:
-            return get_data_error_result(
-                retmsg="At least one of `id` or `name` must be provided.")
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+from flask import request
+from api.db import StatusEnum, FileSource
+from api.db.db_models import File
+from api.db.services.document_service import DocumentService
+from api.db.services.file2document_service import File2DocumentService
+from api.db.services.file_service import FileService
+from api.db.services.knowledgebase_service import KnowledgebaseService
+from api.db.services.llm_service import TenantLLMService, LLMService
+from api.db.services.user_service import TenantService
+from api import settings
+from api.utils import get_uuid
+from api.utils.api_utils import (
+    get_result,
+    token_required,
+    get_error_data_result,
+    valid,
+    get_parser_config,
+)
+
+
+@manager.route("/datasets", methods=["POST"])
+@token_required
+def create(tenant_id):
+    """
+    Create a new dataset.
+    ---
+    tags:
+      - Datasets
+    security:
+      - ApiKeyAuth: []
+    parameters:
+      - in: header
+        name: Authorization
+        type: string
+        required: true
+        description: Bearer token for authentication.
+      - in: body
+        name: body
+        description: Dataset creation parameters.
+        required: true
+        schema:
+          type: object
+          required:
+            - name
+          properties:
+            name:
+              type: string
+              description: Name of the dataset.
+            permission:
+              type: string
+              enum: ['me', 'team']
+              description: Dataset permission.
+            language:
+              type: string
+              enum: ['Chinese', 'English']
+              description: Language of the dataset.
+            chunk_method:
+              type: string
+              enum: ["naive", "manual", "qa", "table", "paper", "book", "laws",
+                     "presentation", "picture", "one", "knowledge_graph", "email"]
+              description: Chunking method.
+            parser_config:
+              type: object
+              description: Parser configuration.
+    responses:
+      200:
+        description: Successful operation.
+        schema:
+          type: object
+          properties:
+            data:
+              type: object
+    """
+    req = request.json
+    e, t = TenantService.get_by_id(tenant_id)
+    permission = req.get("permission")
+    language = req.get("language")
+    chunk_method = req.get("chunk_method")
+    parser_config = req.get("parser_config")
+    valid_permission = ["me", "team"]
+    valid_language = ["Chinese", "English"]
+    valid_chunk_method = [
+        "naive",
+        "manual",
+        "qa",
+        "table",
+        "paper",
+        "book",
+        "laws",
+        "presentation",
+        "picture",
+        "one",
+        "knowledge_graph",
+        "email",
+    ]
+    check_validation = valid(
+        permission,
+        valid_permission,
+        language,
+        valid_language,
+        chunk_method,
+        valid_chunk_method,
+    )
+    if check_validation:
+        return check_validation
+    req["parser_config"] = get_parser_config(chunk_method, parser_config)
+    if "tenant_id" in req:
+        return get_error_data_result(message="`tenant_id` must not be provided")
+    if "chunk_count" in req or "document_count" in req:
+        return get_error_data_result(
+            message="`chunk_count` or `document_count` must not be provided"
+        )
+    if "name" not in req:
+        return get_error_data_result(message="`name` is not empty!")
+    req["id"] = get_uuid()
+    req["name"] = req["name"].strip()
+    if req["name"] == "":
+        return get_error_data_result(message="`name` is not empty string!")
+    if KnowledgebaseService.query(
+        name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value
+    ):
+        return get_error_data_result(
+            message="Duplicated dataset name in creating dataset."
+        )
+    req["tenant_id"] = req["created_by"] = tenant_id
+    if not req.get("embedding_model"):
+        req["embedding_model"] = t.embd_id
+    else:
+        valid_embedding_models = [
+            "BAAI/bge-large-zh-v1.5",
+            "BAAI/bge-base-en-v1.5",
+            "BAAI/bge-large-en-v1.5",
+            "BAAI/bge-small-en-v1.5",
+            "BAAI/bge-small-zh-v1.5",
+            "jinaai/jina-embeddings-v2-base-en",
+            "jinaai/jina-embeddings-v2-small-en",
+            "nomic-ai/nomic-embed-text-v1.5",
+            "sentence-transformers/all-MiniLM-L6-v2",
+            "text-embedding-v2",
+            "text-embedding-v3",
+            "maidalun1020/bce-embedding-base_v1",
+        ]
+        embd_model = LLMService.query(
+            llm_name=req["embedding_model"], model_type="embedding"
+        )
+        if embd_model:
+            if req["embedding_model"] not in valid_embedding_models and not TenantLLMService.query(tenant_id=tenant_id,model_type="embedding",llm_name=req.get("embedding_model"),):
+                return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
+        if not embd_model:
+            embd_model=TenantLLMService.query(tenant_id=tenant_id,model_type="embedding", llm_name=req.get("embedding_model"))
+        if not embd_model:
+            return get_error_data_result(
+                f"`embedding_model` {req.get('embedding_model')} doesn't exist"
+            )
+    key_mapping = {
+        "chunk_num": "chunk_count",
+        "doc_num": "document_count",
+        "parser_id": "chunk_method",
+        "embd_id": "embedding_model",
+    }
+    mapped_keys = {
+        new_key: req[old_key]
+        for new_key, old_key in key_mapping.items()
+        if old_key in req
+    }
+    req.update(mapped_keys)
+    if not KnowledgebaseService.save(**req):
+        return get_error_data_result(message="Create dataset error.(Database error)")
+    renamed_data = {}
+    e, k = KnowledgebaseService.get_by_id(req["id"])
+    for key, value in k.to_dict().items():
+        new_key = key_mapping.get(key, key)
+        renamed_data[new_key] = value
+    return get_result(data=renamed_data)
+
+
+@manager.route("/datasets", methods=["DELETE"])
+@token_required
+def delete(tenant_id):
+    """
+    Delete datasets.
+    ---
+    tags:
+      - Datasets
+    security:
+      - ApiKeyAuth: []
+    parameters:
+      - in: header
+        name: Authorization
+        type: string
+        required: true
+        description: Bearer token for authentication.
+      - in: body
+        name: body
+        description: Dataset deletion parameters.
+        required: true
+        schema:
+          type: object
+          properties:
+            ids:
+              type: array
+              items:
+                type: string
+              description: List of dataset IDs to delete.
+    responses:
+      200:
+        description: Successful operation.
+        schema:
+          type: object
+    """
+    req = request.json
+    if not req:
+        ids = None
+    else:
+        ids = req.get("ids")
+    if not ids:
+        id_list = []
+        kbs = KnowledgebaseService.query(tenant_id=tenant_id)
+        for kb in kbs:
+            id_list.append(kb.id)
+    else:
+        id_list = ids
+    for id in id_list:
+        kbs = KnowledgebaseService.query(id=id, tenant_id=tenant_id)
+        if not kbs:
+            return get_error_data_result(message=f"You don't own the dataset {id}")
+        for doc in DocumentService.query(kb_id=id):
+            if not DocumentService.remove_document(doc, tenant_id):
+                return get_error_data_result(
+                    message="Remove document error.(Database error)"
+                )
+            f2d = File2DocumentService.get_by_document_id(doc.id)
+            FileService.filter_delete(
+                [
+                    File.source_type == FileSource.KNOWLEDGEBASE,
+                    File.id == f2d[0].file_id,
+                ]
+            )
+            FileService.filter_delete(
+                [File.source_type == FileSource.KNOWLEDGEBASE, File.type == "folder", File.name == kbs[0].name])
+            File2DocumentService.delete_by_document_id(doc.id)
+        if not KnowledgebaseService.delete_by_id(id):
+            return get_error_data_result(message="Delete dataset error.(Database error)")
+    return get_result(code=settings.RetCode.SUCCESS)
+
+
+@manager.route("/datasets/<dataset_id>", methods=["PUT"])
+@token_required
+def update(tenant_id, dataset_id):
+    """
+    Update a dataset.
+    ---
+    tags:
+      - Datasets
+    security:
+      - ApiKeyAuth: []
+    parameters:
+      - in: path
+        name: dataset_id
+        type: string
+        required: true
+        description: ID of the dataset to update.
+      - in: header
+        name: Authorization
+        type: string
+        required: true
+        description: Bearer token for authentication.
+      - in: body
+        name: body
+        description: Dataset update parameters.
+        required: true
+        schema:
+          type: object
+          properties:
+            name:
+              type: string
+              description: New name of the dataset.
+            permission:
+              type: string
+              enum: ['me', 'team']
+              description: Updated permission.
+            language:
+              type: string
+              enum: ['Chinese', 'English']
+              description: Updated language.
+            chunk_method:
+              type: string
+              enum: ["naive", "manual", "qa", "table", "paper", "book", "laws",
+                     "presentation", "picture", "one", "knowledge_graph", "email"]
+              description: Updated chunking method.
+            parser_config:
+              type: object
+              description: Updated parser configuration.
+    responses:
+      200:
+        description: Successful operation.
+        schema:
+          type: object
+    """
+    if not KnowledgebaseService.query(id=dataset_id, tenant_id=tenant_id):
+        return get_error_data_result(message="You don't own the dataset")
+    req = request.json
+    e, t = TenantService.get_by_id(tenant_id)
+    invalid_keys = {"id", "embd_id", "chunk_num", "doc_num", "parser_id"}
+    if any(key in req for key in invalid_keys):
+        return get_error_data_result(message="The input parameters are invalid.")
+    permission = req.get("permission")
+    language = req.get("language")
+    chunk_method = req.get("chunk_method")
+    parser_config = req.get("parser_config")
+    valid_permission = ["me", "team"]
+    valid_language = ["Chinese", "English"]
+    valid_chunk_method = [
+        "naive",
+        "manual",
+        "qa",
+        "table",
+        "paper",
+        "book",
+        "laws",
+        "presentation",
+        "picture",
+        "one",
+        "knowledge_graph",
+        "email",
+    ]
+    check_validation = valid(
+        permission,
+        valid_permission,
+        language,
+        valid_language,
+        chunk_method,
+        valid_chunk_method,
+    )
+    if check_validation:
+        return check_validation
+    if "tenant_id" in req:
+        if req["tenant_id"] != tenant_id:
+            return get_error_data_result(message="Can't change `tenant_id`.")
+    e, kb = KnowledgebaseService.get_by_id(dataset_id)
+    if "parser_config" in req:
+        temp_dict = kb.parser_config
+        temp_dict.update(req["parser_config"])
+        req["parser_config"] = temp_dict
+    if "chunk_count" in req:
+        if req["chunk_count"] != kb.chunk_num:
+            return get_error_data_result(message="Can't change `chunk_count`.")
+        req.pop("chunk_count")
+    if "document_count" in req:
+        if req["document_count"] != kb.doc_num:
+            return get_error_data_result(message="Can't change `document_count`.")
+        req.pop("document_count")
+    if "chunk_method" in req:
+        if kb.chunk_num != 0 and req["chunk_method"] != kb.parser_id:
+            return get_error_data_result(
+                message="If `chunk_count` is not 0, `chunk_method` is not changeable."
+            )
+        req["parser_id"] = req.pop("chunk_method")
+        if req["parser_id"] != kb.parser_id:
+            if not req.get("parser_config"):
+                req["parser_config"] = get_parser_config(chunk_method, parser_config)
+    if "embedding_model" in req:
+        if kb.chunk_num != 0 and req["embedding_model"] != kb.embd_id:
+            return get_error_data_result(
+                message="If `chunk_count` is not 0, `embedding_model` is not changeable."
+            )
+        if not req.get("embedding_model"):
+            return get_error_data_result("`embedding_model` can't be empty")
+        valid_embedding_models = [
+            "BAAI/bge-large-zh-v1.5",
+            "BAAI/bge-base-en-v1.5",
+            "BAAI/bge-large-en-v1.5",
+            "BAAI/bge-small-en-v1.5",
+            "BAAI/bge-small-zh-v1.5",
+            "jinaai/jina-embeddings-v2-base-en",
+            "jinaai/jina-embeddings-v2-small-en",
+            "nomic-ai/nomic-embed-text-v1.5",
+            "sentence-transformers/all-MiniLM-L6-v2",
+            "text-embedding-v2",
+            "text-embedding-v3",
+            "maidalun1020/bce-embedding-base_v1",
+        ]
+        embd_model = LLMService.query(
+            llm_name=req["embedding_model"], model_type="embedding"
+        )
+        if embd_model:
+            if req["embedding_model"] not in valid_embedding_models and not TenantLLMService.query(tenant_id=tenant_id,model_type="embedding",llm_name=req.get("embedding_model"),):
+                return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
+        if not embd_model:
+            embd_model=TenantLLMService.query(tenant_id=tenant_id,model_type="embedding", llm_name=req.get("embedding_model"))
+
+        if not embd_model:
+            return get_error_data_result(
+                f"`embedding_model` {req.get('embedding_model')} doesn't exist"
+            )
+        req["embd_id"] = req.pop("embedding_model")
+    if "name" in req:
+        req["name"] = req["name"].strip()
+        if (
+            req["name"].lower() != kb.name.lower()
+            and len(
+                KnowledgebaseService.query(
+                    name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value
+                )
+            )
+            > 0
+        ):
+            return get_error_data_result(
+                message="Duplicated dataset name in updating dataset."
+            )
+    if not KnowledgebaseService.update_by_id(kb.id, req):
+        return get_error_data_result(message="Update dataset error.(Database error)")
+    return get_result(code=settings.RetCode.SUCCESS)
+
+
+@manager.route("/datasets", methods=["GET"])
+@token_required
+def list(tenant_id):
+    """
+    List datasets.
+    ---
+    tags:
+      - Datasets
+    security:
+      - ApiKeyAuth: []
+    parameters:
+      - in: query
+        name: id
+        type: string
+        required: false
+        description: Dataset ID to filter.
+      - in: query
+        name: name
+        type: string
+        required: false
+        description: Dataset name to filter.
+      - in: query
+        name: page
+        type: integer
+        required: false
+        default: 1
+        description: Page number.
+      - in: query
+        name: page_size
+        type: integer
+        required: false
+        default: 1024
+        description: Number of items per page.
+      - in: query
+        name: orderby
+        type: string
+        required: false
+        default: "create_time"
+        description: Field to order by.
+      - in: query
+        name: desc
+        type: boolean
+        required: false
+        default: true
+        description: Order in descending.
+      - in: header
+        name: Authorization
+        type: string
+        required: true
+        description: Bearer token for authentication.
+    responses:
+      200:
+        description: Successful operation.
+        schema:
+          type: array
+          items:
+            type: object
+    """
+    id = request.args.get("id")
+    name = request.args.get("name")
+    if id:
+        kbs = KnowledgebaseService.get_kb_by_id(id,tenant_id)
+        if not kbs:
+            return get_error_data_result(f"You don't own the dataset {id}")
+    if name:
+        kbs = KnowledgebaseService.get_kb_by_name(name,tenant_id)
+        if not kbs:
+            return get_error_data_result(f"You don't own the dataset {name}")
+    page_number = int(request.args.get("page", 1))
+    items_per_page = int(request.args.get("page_size", 30))
+    orderby = request.args.get("orderby", "create_time")
+    if request.args.get("desc") == "False" or request.args.get("desc") == "false":
+        desc = False
+    else:
+        desc = True
+    tenants = TenantService.get_joined_tenants_by_user_id(tenant_id)
+    kbs = KnowledgebaseService.get_list(
+        [m["tenant_id"] for m in tenants],
+        tenant_id,
+        page_number,
+        items_per_page,
+        orderby,
+        desc,
+        id,
+        name,
+    )
+    renamed_list = []
+    for kb in kbs:
+        key_mapping = {
+            "chunk_num": "chunk_count",
+            "doc_num": "document_count",
+            "parser_id": "chunk_method",
+            "embd_id": "embedding_model",
+        }
+        renamed_data = {}
+        for key, value in kb.items():
+            new_key = key_mapping.get(key, key)
+            renamed_data[new_key] = value
+        renamed_list.append(renamed_data)
+    return get_result(data=renamed_list)

api/apps/sdk/dify_retrieval.py

@@ -0,0 +1,76 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+from flask import request, jsonify
+
+from api.db import LLMType, ParserType
+from api.db.services.knowledgebase_service import KnowledgebaseService
+from api.db.services.llm_service import LLMBundle
+from api import settings
+from api.utils.api_utils import validate_request, build_error_result, apikey_required
+
+
+@manager.route('/dify/retrieval', methods=['POST'])
+@apikey_required
+@validate_request("knowledge_id", "query")
+def retrieval(tenant_id):
+    req = request.json
+    question = req["query"]
+    kb_id = req["knowledge_id"]
+    retrieval_setting = req.get("retrieval_setting", {})
+    similarity_threshold = float(retrieval_setting.get("score_threshold", 0.0))
+    top = int(retrieval_setting.get("top_k", 1024))
+
+    try:
+
+        e, kb = KnowledgebaseService.get_by_id(kb_id)
+        if not e:
+            return build_error_result(message="Knowledgebase not found!", code=settings.RetCode.NOT_FOUND)
+
+        if kb.tenant_id != tenant_id:
+            return build_error_result(message="Knowledgebase not found!", code=settings.RetCode.NOT_FOUND)
+
+        embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
+
+        retr = settings.retrievaler if kb.parser_id != ParserType.KG else settings.kg_retrievaler
+        ranks = retr.retrieval(
+            question,
+            embd_mdl,
+            kb.tenant_id,
+            [kb_id],
+            page=1,
+            page_size=top,
+            similarity_threshold=similarity_threshold,
+            vector_similarity_weight=0.3,
+            top=top
+        )
+        records = []
+        for c in ranks["chunks"]:
+            c.pop("vector", None)
+            records.append({
+                "content": c["content_ltks"],
+                "score": c["similarity"],
+                "title": c["docnm_kwd"],
+                "metadata": {}
+            })
+
+        return jsonify({"records": records})
+    except Exception as e:
+        if str(e).find("not_found") > 0:
+            return build_error_result(
+                message='No chunk found! Check the chunk status please!',
+                code=settings.RetCode.NOT_FOUND
+            )
+        return build_error_result(message=str(e), code=settings.RetCode.SERVER_ERROR)

api/apps/sdk/session.py

@@ -1,266 +1,531 @@
-#
-#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
-#
-#  Licensed under the Apache License, Version 2.0 (the "License");
-#  you may not use this file except in compliance with the License.
-#  You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-#  Unless required by applicable law or agreed to in writing, software
-#  distributed under the License is distributed on an "AS IS" BASIS,
-#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#  See the License for the specific language governing permissions and
-#  limitations under the License.
-#
-import json
-from uuid import uuid4
-
-from flask import request, Response
-
-from api.db import StatusEnum
-from api.db.services.dialog_service import DialogService, ConversationService, chat
-from api.settings import RetCode
-from api.utils import get_uuid
-from api.utils.api_utils import get_data_error_result
-from api.utils.api_utils import get_json_result, token_required
-
-
-@manager.route('/save', methods=['POST'])
-@token_required
-def set_conversation(tenant_id):
-    req = request.json
-    conv_id = req.get("id")
-    if "assistant_id" in req:
-        req["dialog_id"] = req.pop("assistant_id")
-    if "id" in req:
-        del req["id"]
-        conv = ConversationService.query(id=conv_id)
-        if not conv:
-            return get_data_error_result(retmsg="Session does not exist")
-        if not DialogService.query(id=conv[0].dialog_id, tenant_id=tenant_id, status=StatusEnum.VALID.value):
-            return get_data_error_result(retmsg="You do not own the session")
-        if req.get("dialog_id"):
-            dia = DialogService.query(tenant_id=tenant_id, id=req["dialog_id"], status=StatusEnum.VALID.value)
-            if not dia:
-                return get_data_error_result(retmsg="You do not own the assistant")
-        if "dialog_id" in req and not req.get("dialog_id"):
-            return get_data_error_result(retmsg="assistant_id can not be empty.")
-        if "message" in req:
-            return get_data_error_result(retmsg="message can not be change")
-        if "reference" in req:
-            return get_data_error_result(retmsg="reference can not be change")
-        if "name" in req and not req.get("name"):
-            return get_data_error_result(retmsg="name can not be empty.")
-        if not ConversationService.update_by_id(conv_id, req):
-            return get_data_error_result(retmsg="Session updates error")
-        return get_json_result(data=True)
-
-    if not req.get("dialog_id"):
-        return get_data_error_result(retmsg="assistant_id is required.")
-    dia = DialogService.query(tenant_id=tenant_id, id=req["dialog_id"], status=StatusEnum.VALID.value)
-    if not dia:
-        return get_data_error_result(retmsg="You do not own the assistant")
-    conv = {
-        "id": get_uuid(),
-        "dialog_id": req["dialog_id"],
-        "name": req.get("name", "New session"),
-        "message": [{"role": "assistant", "content": "Hi! I am your assistant，can I help you?"}]
-    }
-    if not conv.get("name"):
-        return get_data_error_result(retmsg="name can not be empty.")
-    ConversationService.save(**conv)
-    e, conv = ConversationService.get_by_id(conv["id"])
-    if not e:
-        return get_data_error_result(retmsg="Fail to new session!")
-    conv = conv.to_dict()
-    conv['messages'] = conv.pop("message")
-    conv["assistant_id"] = conv.pop("dialog_id")
-    del conv["reference"]
-    return get_json_result(data=conv)
-
-
-@manager.route('/completion', methods=['POST'])
-@token_required
-def completion(tenant_id):
-    req = request.json
-    # req = {"conversation_id": "9aaaca4c11d311efa461fa163e197198", "messages": [
-    #    {"role": "user", "content": "上海有吗？"}
-    # ]}
-    if "session_id" not in req:
-        return get_data_error_result(retmsg="session_id is required")
-    conv = ConversationService.query(id=req["session_id"])
-    if not conv:
-        return get_data_error_result(retmsg="Session does not exist")
-    conv = conv[0]
-    if not DialogService.query(id=conv.dialog_id, tenant_id=tenant_id, status=StatusEnum.VALID.value):
-        return get_data_error_result(retmsg="You do not own the session")
-    msg = []
-    question = {
-        "content": req.get("question"),
-        "role": "user",
-        "id": str(uuid4())
-    }
-    conv.message.append(question)
-    for m in conv.message:
-        if m["role"] == "system": continue
-        if m["role"] == "assistant" and not msg: continue
-        msg.append(m)
-    message_id = msg[-1].get("id")
-    e, dia = DialogService.get_by_id(conv.dialog_id)
-    del req["session_id"]
-
-    if not conv.reference:
-        conv.reference = []
-    conv.message.append({"role": "assistant", "content": "", "id": message_id})
-    conv.reference.append({"chunks": [], "doc_aggs": []})
-
-    def fillin_conv(ans):
-        nonlocal conv, message_id
-        if not conv.reference:
-            conv.reference.append(ans["reference"])
-        else:
-            conv.reference[-1] = ans["reference"]
-        conv.message[-1] = {"role": "assistant", "content": ans["answer"],
-                            "id": message_id, "prompt": ans.get("prompt", "")}
-        ans["id"] = message_id
-
-    def stream():
-        nonlocal dia, msg, req, conv
-        try:
-            for ans in chat(dia, msg, **req):
-                fillin_conv(ans)
-                yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": ans}, ensure_ascii=False) + "\n\n"
-            ConversationService.update_by_id(conv.id, conv.to_dict())
-        except Exception as e:
-            yield "data:" + json.dumps({"retcode": 500, "retmsg": str(e),
-                                        "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
-                                       ensure_ascii=False) + "\n\n"
-        yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": True}, ensure_ascii=False) + "\n\n"
-
-    if req.get("stream", True):
-        resp = Response(stream(), mimetype="text/event-stream")
-        resp.headers.add_header("Cache-control", "no-cache")
-        resp.headers.add_header("Connection", "keep-alive")
-        resp.headers.add_header("X-Accel-Buffering", "no")
-        resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
-        return resp
-
-    else:
-        answer = None
-        for ans in chat(dia, msg, **req):
-            answer = ans
-            fillin_conv(ans)
-            ConversationService.update_by_id(conv.id, conv.to_dict())
-            break
-        return get_json_result(data=answer)
-
-
-@manager.route('/get', methods=['GET'])
-@token_required
-def get(tenant_id):
-    req = request.args
-    if "id" not in req:
-        return get_data_error_result(retmsg="id is required")
-    conv_id = req["id"]
-    conv = ConversationService.query(id=conv_id)
-    if not conv:
-        return get_data_error_result(retmsg="Session does not exist")
-    if not DialogService.query(id=conv[0].dialog_id, tenant_id=tenant_id, status=StatusEnum.VALID.value):
-        return get_data_error_result(retmsg="You do not own the session")
-    if "assistant_id" in req:
-        if req["assistant_id"] != conv[0].dialog_id:
-            return get_data_error_result(retmsg="The session doesn't belong to the assistant")
-    conv = conv[0].to_dict()
-    conv['messages'] = conv.pop("message")
-    conv["assistant_id"] = conv.pop("dialog_id")
-    if conv["reference"]:
-        messages = conv["messages"]
-        message_num = 0
-        chunk_num = 0
-        while message_num < len(messages):
-            if message_num != 0 and messages[message_num]["role"] != "user":
-                chunk_list = []
-                if "chunks" in conv["reference"][chunk_num]:
-                    chunks = conv["reference"][chunk_num]["chunks"]
-                    for chunk in chunks:
-                        new_chunk = {
-                            "id": chunk["chunk_id"],
-                            "content": chunk["content_with_weight"],
-                            "document_id": chunk["doc_id"],
-                            "document_name": chunk["docnm_kwd"],
-                            "knowledgebase_id": chunk["kb_id"],
-                            "image_id": chunk["img_id"],
-                            "similarity": chunk["similarity"],
-                            "vector_similarity": chunk["vector_similarity"],
-                            "term_similarity": chunk["term_similarity"],
-                            "positions": chunk["positions"],
-                        }
-                        chunk_list.append(new_chunk)
-                chunk_num += 1
-                messages[message_num]["reference"] = chunk_list
-            message_num += 1
-    del conv["reference"]
-    return get_json_result(data=conv)
-
-
-@manager.route('/list', methods=["GET"])
-@token_required
-def list(tenant_id):
-    assistant_id = request.args["assistant_id"]
-    if not DialogService.query(tenant_id=tenant_id, id=assistant_id, status=StatusEnum.VALID.value):
-        return get_json_result(
-            data=False, retmsg=f"You don't own the assistant.",
-            retcode=RetCode.OPERATING_ERROR)
-    convs = ConversationService.query(
-        dialog_id=assistant_id,
-        order_by=ConversationService.model.create_time,
-        reverse=True)
-    convs = [d.to_dict() for d in convs]
-    for conv in convs:
-        conv['messages'] = conv.pop("message")
-        conv["assistant_id"] = conv.pop("dialog_id")
-        if conv["reference"]:
-            messages = conv["messages"]
-            message_num = 0
-            chunk_num = 0
-            while message_num < len(messages):
-                if message_num != 0 and messages[message_num]["role"] != "user":
-                    chunk_list = []
-                    if "chunks" in conv["reference"][chunk_num]:
-                        chunks = conv["reference"][chunk_num]["chunks"]
-                        for chunk in chunks:
-                            new_chunk = {
-                                "id": chunk["chunk_id"],
-                                "content": chunk["content_with_weight"],
-                                "document_id": chunk["doc_id"],
-                                "document_name": chunk["docnm_kwd"],
-                                "knowledgebase_id": chunk["kb_id"],
-                                "image_id": chunk["img_id"],
-                                "similarity": chunk["similarity"],
-                                "vector_similarity": chunk["vector_similarity"],
-                                "term_similarity": chunk["term_similarity"],
-                                "positions": chunk["positions"],
-                            }
-                            chunk_list.append(new_chunk)
-                    chunk_num += 1
-                    messages[message_num]["reference"] = chunk_list
-                message_num += 1
-        del conv["reference"]
-    return get_json_result(data=convs)
-
-
-@manager.route('/delete', methods=["DELETE"])
-@token_required
-def delete(tenant_id):
-    id = request.args.get("id")
-    if not id:
-        return get_data_error_result(retmsg="`id` is required in deleting operation")
-    conv = ConversationService.query(id=id)
-    if not conv:
-        return get_data_error_result(retmsg="Session doesn't exist")
-    conv = conv[0]
-    if not DialogService.query(id=conv.dialog_id, tenant_id=tenant_id, status=StatusEnum.VALID.value):
-        return get_data_error_result(retmsg="You don't own the session")
-    ConversationService.delete_by_id(id)
-    return get_json_result(data=True)
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import re
+import json
+from copy import deepcopy
+from uuid import uuid4
+from api.db import LLMType
+from flask import request, Response
+from api.db.services.dialog_service import ask
+from agent.canvas import Canvas
+from api.db import StatusEnum
+from api.db.db_models import API4Conversation
+from api.db.services.api_service import API4ConversationService
+from api.db.services.canvas_service import UserCanvasService
+from api.db.services.dialog_service import DialogService, ConversationService, chat
+from api.db.services.knowledgebase_service import KnowledgebaseService
+from api.utils import get_uuid
+from api.utils.api_utils import get_error_data_result
+from api.utils.api_utils import get_result, token_required
+from api.db.services.llm_service import LLMBundle
+
+
+@manager.route('/chats/<chat_id>/sessions', methods=['POST'])
+@token_required
+def create(tenant_id,chat_id):
+    req = request.json
+    req["dialog_id"] = chat_id
+    dia = DialogService.query(tenant_id=tenant_id, id=req["dialog_id"], status=StatusEnum.VALID.value)
+    if not dia:
+        return get_error_data_result(message="You do not own the assistant.")
+    conv = {
+        "id": get_uuid(),
+        "dialog_id": req["dialog_id"],
+        "name": req.get("name", "New session"),
+        "message": [{"role": "assistant", "content": "Hi! I am your assistant，can I help you?"}]
+    }
+    if not conv.get("name"):
+        return get_error_data_result(message="`name` can not be empty.")
+    ConversationService.save(**conv)
+    e, conv = ConversationService.get_by_id(conv["id"])
+    if not e:
+        return get_error_data_result(message="Fail to create a session!")
+    conv = conv.to_dict()
+    conv['messages'] = conv.pop("message")
+    conv["chat_id"] = conv.pop("dialog_id")
+    del conv["reference"]
+    return get_result(data=conv)
+
+
+@manager.route('/agents/<agent_id>/sessions', methods=['POST'])
+@token_required
+def create_agent_session(tenant_id, agent_id):
+    req = request.json
+    e, cvs = UserCanvasService.get_by_id(agent_id)
+    if not e:
+        return get_error_data_result("Agent not found.")
+    if cvs.user_id != tenant_id:
+        return get_error_data_result(message="You do not own the agent.")
+
+    if not isinstance(cvs.dsl, str):
+        cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False)
+
+    canvas = Canvas(cvs.dsl, tenant_id)
+    conv = {
+        "id": get_uuid(),
+        "dialog_id": cvs.id,
+        "user_id": req.get("usr_id","") if isinstance(req, dict) else "",
+        "message": [{"role": "assistant", "content": canvas.get_prologue()}],
+        "source": "agent"
+    }
+    API4ConversationService.save(**conv)
+    conv["agent_id"] = conv.pop("dialog_id")
+    return get_result(data=conv)
+
+
+@manager.route('/chats/<chat_id>/sessions/<session_id>', methods=['PUT'])
+@token_required
+def update(tenant_id,chat_id,session_id):
+    req = request.json
+    req["dialog_id"] = chat_id
+    conv_id = session_id
+    conv = ConversationService.query(id=conv_id,dialog_id=chat_id)
+    if not conv:
+        return get_error_data_result(message="Session does not exist")
+    if not DialogService.query(id=chat_id, tenant_id=tenant_id, status=StatusEnum.VALID.value):
+        return get_error_data_result(message="You do not own the session")
+    if "message" in req or "messages" in req:
+        return get_error_data_result(message="`message` can not be change")
+    if "reference" in req:
+        return get_error_data_result(message="`reference` can not be change")
+    if "name" in req and not req.get("name"):
+        return get_error_data_result(message="`name` can not be empty.")
+    if not ConversationService.update_by_id(conv_id, req):
+        return get_error_data_result(message="Session updates error")
+    return get_result()
+
+
+@manager.route('/chats/<chat_id>/completions', methods=['POST'])
+@token_required
+def completion(tenant_id, chat_id):
+    req = request.json
+    if not req.get("session_id"):
+        conv = {
+            "id": get_uuid(),
+            "dialog_id": chat_id,
+            "name": req.get("name", "New session"),
+            "message": [{"role": "assistant", "content": "Hi! I am your assistant，can I help you?"}]
+        }
+        if not conv.get("name"):
+            return get_error_data_result(message="`name` can not be empty.")
+        ConversationService.save(**conv)
+        e, conv = ConversationService.get_by_id(conv["id"])
+        session_id=conv.id
+    else:
+        session_id = req.get("session_id")
+    if not req.get("question"):
+        return get_error_data_result(message="Please input your question.")
+    conv = ConversationService.query(id=session_id,dialog_id=chat_id)
+    if not conv:
+        return get_error_data_result(message="Session does not exist")
+    conv = conv[0]
+    if not DialogService.query(id=chat_id, tenant_id=tenant_id, status=StatusEnum.VALID.value):
+        return get_error_data_result(message="You do not own the chat")
+    msg = []
+    question = {
+        "content": req.get("question"),
+        "role": "user",
+        "id": str(uuid4())
+    }
+    conv.message.append(question)
+    for m in conv.message:
+        if m["role"] == "system": continue
+        if m["role"] == "assistant" and not msg: continue
+        msg.append(m)
+    message_id = msg[-1].get("id")
+    e, dia = DialogService.get_by_id(conv.dialog_id)
+
+    if not conv.reference:
+        conv.reference = []
+    conv.message.append({"role": "assistant", "content": "", "id": message_id})
+    conv.reference.append({"chunks": [], "doc_aggs": []})
+
+    def fillin_conv(ans):
+        reference = ans["reference"]
+        temp_reference = deepcopy(ans["reference"])
+        nonlocal conv, message_id
+        if not conv.reference:
+            conv.reference.append(temp_reference)
+        else:
+            conv.reference[-1] = temp_reference
+        conv.message[-1] = {"role": "assistant", "content": ans["answer"],
+                            "id": message_id, "prompt": ans.get("prompt", "")}
+        if "chunks" in reference:
+            chunks = reference.get("chunks")
+            chunk_list = []
+            for chunk in chunks:
+                new_chunk = {
+                    "id": chunk["chunk_id"],
+                    "content": chunk["content_with_weight"],
+                    "document_id": chunk["doc_id"],
+                    "document_name": chunk["docnm_kwd"],
+                    "dataset_id": chunk["kb_id"],
+                    "image_id": chunk.get("image_id", ""),
+                    "similarity": chunk["similarity"],
+                    "vector_similarity": chunk["vector_similarity"],
+                    "term_similarity": chunk["term_similarity"],
+                    "positions": chunk.get("positions", []),
+                }
+                chunk_list.append(new_chunk)
+            reference["chunks"] = chunk_list
+        ans["id"] = message_id
+        ans["session_id"]=session_id
+
+    def stream():
+        nonlocal dia, msg, req, conv
+        try:
+            for ans in chat(dia, msg, **req):
+                fillin_conv(ans)
+                yield "data:" + json.dumps({"code": 0,  "data": ans}, ensure_ascii=False) + "\n\n"
+            ConversationService.update_by_id(conv.id, conv.to_dict())
+        except Exception as e:
+            yield "data:" + json.dumps({"code": 500, "message": str(e),
+                                        "data": {"answer": "**ERROR**: " + str(e),"reference": []}},
+                                       ensure_ascii=False) + "\n\n"
+        yield "data:" + json.dumps({"code": 0, "data": True}, ensure_ascii=False) + "\n\n"
+
+    if req.get("stream", True):
+        resp = Response(stream(), mimetype="text/event-stream")
+        resp.headers.add_header("Cache-control", "no-cache")
+        resp.headers.add_header("Connection", "keep-alive")
+        resp.headers.add_header("X-Accel-Buffering", "no")
+        resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
+
+        return resp
+
+    else:
+        answer = None
+        for ans in chat(dia, msg, **req):
+            answer = ans
+            fillin_conv(ans)
+            ConversationService.update_by_id(conv.id, conv.to_dict())
+            break
+        return get_result(data=answer)
+
+
+@manager.route('/agents/<agent_id>/completions', methods=['POST'])
+@token_required
+def agent_completion(tenant_id, agent_id):
+    req = request.json
+
+    e, cvs = UserCanvasService.get_by_id(agent_id)
+    if not e:
+        return get_error_data_result("Agent not found.")
+    if cvs.user_id != tenant_id:
+        return get_error_data_result(message="You do not own the agent.")
+    if not isinstance(cvs.dsl, str):
+        cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False)
+    canvas = Canvas(cvs.dsl, tenant_id)
+
+    if not req.get("session_id"):
+        session_id = get_uuid()
+        conv = {
+            "id": session_id,
+            "dialog_id": cvs.id,
+            "user_id": req.get("user_id",""),
+            "message": [{"role": "assistant", "content": canvas.get_prologue()}],
+            "source": "agent"
+        }
+        API4ConversationService.save(**conv)
+        conv = API4Conversation(**conv)
+    else:
+        session_id = req.get("session_id")
+        e, conv = API4ConversationService.get_by_id(req["session_id"])
+        if not e:
+            return get_error_data_result(message="Session not found!")
+
+    messages = conv.message
+    question = req.get("question")
+    if not question:
+        return get_error_data_result("`question` is required.")
+    question={
+        "role":"user",
+        "content":question,
+        "id": str(uuid4())
+    }
+    messages.append(question)
+    msg = []
+    for m in messages:
+        if m["role"] == "system":
+            continue
+        if m["role"] == "assistant" and not msg:
+            continue
+        msg.append(m)
+    if not msg[-1].get("id"): msg[-1]["id"] = get_uuid()
+    message_id = msg[-1]["id"]
+
+    if "quote" not in req: req["quote"] = False
+    stream = req.get("stream", True)
+
+    def fillin_conv(ans):
+        reference = ans["reference"]
+        temp_reference = deepcopy(ans["reference"])
+        nonlocal conv, message_id
+        if not conv.reference:
+            conv.reference.append(temp_reference)
+        else:
+            conv.reference[-1] = temp_reference
+        conv.message[-1] = {"role": "assistant", "content": ans["answer"], "id": message_id}
+        if "chunks" in reference:
+            chunks = reference.get("chunks")
+            chunk_list = []
+            for chunk in chunks:
+                new_chunk = {
+                    "id": chunk["chunk_id"],
+                    "content": chunk["content_with_weight"],
+                    "document_id": chunk["doc_id"],
+                    "document_name": chunk["docnm_kwd"],
+                    "dataset_id": chunk["kb_id"],
+                    "image_id": chunk["image_id"],
+                    "similarity": chunk["similarity"],
+                    "vector_similarity": chunk["vector_similarity"],
+                    "term_similarity": chunk["term_similarity"],
+                    "positions": chunk["positions"],
+                }
+                chunk_list.append(new_chunk)
+            reference["chunks"] = chunk_list
+        ans["id"] = message_id
+        ans["session_id"] = session_id
+
+    def rename_field(ans):
+        reference = ans['reference']
+        if not isinstance(reference, dict):
+            return
+        for chunk_i in reference.get('chunks', []):
+            if 'docnm_kwd' in chunk_i:
+                chunk_i['doc_name'] = chunk_i['docnm_kwd']
+                chunk_i.pop('docnm_kwd')
+    conv.message.append(msg[-1])
+
+    if not conv.reference:
+        conv.reference = []
+    conv.message.append({"role": "assistant", "content": "", "id": message_id})
+    conv.reference.append({"chunks": [], "doc_aggs": []})
+
+    final_ans = {"reference": [], "content": ""}
+
+    canvas.messages.append(msg[-1])
+    canvas.add_user_input(msg[-1]["content"])
+
+    if stream:
+        def sse():
+            nonlocal answer, cvs
+            try:
+                for ans in canvas.run(stream=True):
+                    if ans.get("running_status"):
+                        yield "data:" + json.dumps({"code": 0, "message": "",
+                                                    "data": {"answer": ans["content"],
+                                                             "running_status": True}},
+                                                   ensure_ascii=False) + "\n\n"
+                        continue
+                    for k in ans.keys():
+                        final_ans[k] = ans[k]
+                    ans = {"answer": ans["content"], "reference": ans.get("reference", [])}
+                    fillin_conv(ans)
+                    rename_field(ans)
+                    yield "data:" + json.dumps({"code": 0, "message": "", "data": ans},
+                                               ensure_ascii=False) + "\n\n"
+
+                canvas.messages.append({"role": "assistant", "content": final_ans["content"], "id": message_id})
+                canvas.history.append(("assistant", final_ans["content"]))
+                if final_ans.get("reference"):
+                    canvas.reference.append(final_ans["reference"])
+                cvs.dsl = json.loads(str(canvas))
+                API4ConversationService.append_message(conv.id, conv.to_dict())
+            except Exception as e:
+                cvs.dsl = json.loads(str(canvas))
+                API4ConversationService.append_message(conv.id, conv.to_dict())
+                yield "data:" + json.dumps({"code": 500, "message": str(e),
+                                            "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
+                                           ensure_ascii=False) + "\n\n"
+            yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
+
+        resp = Response(sse(), mimetype="text/event-stream")
+        resp.headers.add_header("Cache-control", "no-cache")
+        resp.headers.add_header("Connection", "keep-alive")
+        resp.headers.add_header("X-Accel-Buffering", "no")
+        resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
+        return resp
+
+    for answer in canvas.run(stream=False):
+        if answer.get("running_status"): continue
+        final_ans["content"] = "\n".join(answer["content"]) if "content" in answer else ""
+        canvas.messages.append({"role": "assistant", "content": final_ans["content"], "id": message_id})
+        if final_ans.get("reference"):
+            canvas.reference.append(final_ans["reference"])
+        cvs.dsl = json.loads(str(canvas))
+
+        result = {"answer": final_ans["content"], "reference": final_ans.get("reference", [])}
+        fillin_conv(result)
+        API4ConversationService.append_message(conv.id, conv.to_dict())
+        rename_field(result)
+        return get_result(data=result)
+
+
+@manager.route('/chats/<chat_id>/sessions', methods=['GET'])
+@token_required
+def list_session(chat_id,tenant_id):
+    if not DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value):
+        return get_error_data_result(message=f"You don't own the assistant {chat_id}.")
+    id = request.args.get("id")
+    name = request.args.get("name")
+    page_number = int(request.args.get("page", 1))
+    items_per_page = int(request.args.get("page_size", 30))
+    orderby = request.args.get("orderby", "create_time")
+    if request.args.get("desc") == "False" or request.args.get("desc") == "false":
+        desc = False
+    else:
+        desc = True
+    convs = ConversationService.get_list(chat_id,page_number,items_per_page,orderby,desc,id,name)
+    if not convs:
+        return get_result(data=[])
+    for conv in convs:
+        conv['messages'] = conv.pop("message")
+        infos = conv["messages"]
+        for info in infos:
+            if "prompt" in info:
+                info.pop("prompt")
+        conv["chat_id"] = conv.pop("dialog_id")
+        if conv["reference"]:
+            messages = conv["messages"]
+            message_num = 0
+            chunk_num = 0
+            while message_num < len(messages):
+                if message_num != 0 and messages[message_num]["role"] != "user":
+                    chunk_list = []
+                    if "chunks" in conv["reference"][chunk_num]:
+                        chunks = conv["reference"][chunk_num]["chunks"]
+                        for chunk in chunks:
+                            new_chunk = {
+                                "id": chunk["chunk_id"],
+                                "content": chunk["content_with_weight"],
+                                "document_id": chunk["doc_id"],
+                                "document_name": chunk["docnm_kwd"],
+                                "dataset_id": chunk["kb_id"],
+                                "image_id": chunk["image_id"],
+                                "similarity": chunk["similarity"],
+                                "vector_similarity": chunk["vector_similarity"],
+                                "term_similarity": chunk["term_similarity"],
+                                "positions": chunk["positions"],
+                            }
+                            chunk_list.append(new_chunk)
+                    chunk_num += 1
+                    messages[message_num]["reference"] = chunk_list
+                message_num += 1
+        del conv["reference"]
+    return get_result(data=convs)
+
+
+@manager.route('/chats/<chat_id>/sessions', methods=["DELETE"])
+@token_required
+def delete(tenant_id,chat_id):
+    if not DialogService.query(id=chat_id, tenant_id=tenant_id, status=StatusEnum.VALID.value):
+        return get_error_data_result(message="You don't own the chat")
+    req = request.json
+    convs = ConversationService.query(dialog_id=chat_id)
+    if not req:
+        ids = None
+    else:
+        ids=req.get("ids")
+
+    if not ids:
+        conv_list = []
+        for conv in convs:
+            conv_list.append(conv.id)
+    else:
+        conv_list=ids
+    for id in conv_list:
+        conv = ConversationService.query(id=id,dialog_id=chat_id)
+        if not conv:
+            return get_error_data_result(message="The chat doesn't own the session")
+        ConversationService.delete_by_id(id)
+    return get_result()
+
+@manager.route('/sessions/ask', methods=['POST'])
+@token_required
+def ask_about(tenant_id):
+    req = request.json
+    if not req.get("question"):
+        return get_error_data_result("`question` is required.")
+    if not req.get("dataset_ids"):
+        return get_error_data_result("`dataset_ids` is required.")
+    if not isinstance(req.get("dataset_ids"),list):
+        return get_error_data_result("`dataset_ids` should be a list.")
+    req["kb_ids"]=req.pop("dataset_ids")
+    for kb_id in req["kb_ids"]:
+        if not KnowledgebaseService.accessible(kb_id,tenant_id):
+            return get_error_data_result(f"You don't own the dataset {kb_id}.")
+        kbs = KnowledgebaseService.query(id=kb_id)
+        kb = kbs[0]
+        if kb.chunk_num == 0:
+            return get_error_data_result(f"The dataset {kb_id} doesn't own parsed file")
+    uid = tenant_id
+    def stream():
+        nonlocal req, uid
+        try:
+            for ans in ask(req["question"], req["kb_ids"], uid):
+                yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
+        except Exception as e:
+            yield "data:" + json.dumps({"code": 500, "message": str(e),
+                                        "data": {"answer": "**ERROR**: " + str(e), "reference": []}},
+                                       ensure_ascii=False) + "\n\n"
+        yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
+
+    resp = Response(stream(), mimetype="text/event-stream")
+    resp.headers.add_header("Cache-control", "no-cache")
+    resp.headers.add_header("Connection", "keep-alive")
+    resp.headers.add_header("X-Accel-Buffering", "no")
+    resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
+    return resp
+
+
+@manager.route('/sessions/related_questions', methods=['POST'])
+@token_required
+def related_questions(tenant_id):
+    req = request.json
+    if not req.get("question"):
+        return get_error_data_result("`question` is required.")
+    question = req["question"]
+    chat_mdl = LLMBundle(tenant_id, LLMType.CHAT)
+    prompt = """
+Objective: To generate search terms related to the user's search keywords, helping users find more valuable information.
+Instructions:
+ - Based on the keywords provided by the user, generate 5-10 related search terms.
+ - Each search term should be directly or indirectly related to the keyword, guiding the user to find more valuable information.
+ - Use common, general terms as much as possible, avoiding obscure words or technical jargon.
+ - Keep the term length between 2-4 words, concise and clear.
+ - DO NOT translate, use the language of the original keywords.
+
+### Example:
+Keywords: Chinese football
+Related search terms:
+1. Current status of Chinese football
+2. Reform of Chinese football
+3. Youth training of Chinese football
+4. Chinese football in the Asian Cup
+5. Chinese football in the World Cup
+
+Reason:
+ - When searching, users often only use one or two keywords, making it difficult to fully express their information needs.
+ - Generating related search terms can help users dig deeper into relevant information and improve search efficiency. 
+ - At the same time, related terms can also help search engines better understand user needs and return more accurate search results.
+
+"""
+    ans = chat_mdl.chat(prompt, [{"role": "user", "content": f"""
+Keywords: {question}
+Related search terms:
+    """}], {"temperature": 0.9})
+    return get_result(data=[re.sub(r"^[0-9]\. ", "", a) for a in ans.split("\n") if re.match(r"^[0-9]\. ", a)])

api/apps/system_app.py

@@ -13,78 +13,281 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License
 #
+import logging
+from datetime import datetime
 import json
 
-from flask_login import login_required
+from flask_login import login_required, current_user
 
+from api.db.db_models import APIToken
+from api.db.services.api_service import APITokenService
 from api.db.services.knowledgebase_service import KnowledgebaseService
-from api.settings import DATABASE_TYPE
-from api.utils.api_utils import get_json_result
-from api.versions import get_rag_version
-from rag.settings import SVR_QUEUE_NAME
-from rag.utils.es_conn import ELASTICSEARCH
+from api.db.services.user_service import UserTenantService
+from api import settings
+from api.utils import current_timestamp, datetime_format
+from api.utils.api_utils import (
+    get_json_result,
+    get_data_error_result,
+    server_error_response,
+    generate_confirmation_token,
+)
+from api.versions import get_ragflow_version
 from rag.utils.storage_factory import STORAGE_IMPL, STORAGE_IMPL_TYPE
 from timeit import default_timer as timer
 
 from rag.utils.redis_conn import REDIS_CONN
 
 
-@manager.route('/version', methods=['GET'])
+@manager.route("/version", methods=["GET"])
 @login_required
 def version():
-    return get_json_result(data=get_rag_version())
+    """
+    Get the current version of the application.
+    ---
+    tags:
+      - System
+    security:
+      - ApiKeyAuth: []
+    responses:
+      200:
+        description: Version retrieved successfully.
+        schema:
+          type: object
+          properties:
+            version:
+              type: string
+              description: Version number.
+    """
+    return get_json_result(data=get_ragflow_version())
 
 
-@manager.route('/status', methods=['GET'])
+@manager.route("/status", methods=["GET"])
 @login_required
 def status():
+    """
+    Get the system status.
+    ---
+    tags:
+      - System
+    security:
+      - ApiKeyAuth: []
+    responses:
+      200:
+        description: System is operational.
+        schema:
+          type: object
+          properties:
+            es:
+              type: object
+              description: Elasticsearch status.
+            storage:
+              type: object
+              description: Storage status.
+            database:
+              type: object
+              description: Database status.
+      503:
+        description: Service unavailable.
+        schema:
+          type: object
+          properties:
+            error:
+              type: string
+              description: Error message.
+    """
     res = {}
     st = timer()
     try:
-        res["es"] = ELASTICSEARCH.health()
-        res["es"]["elapsed"] = "{:.1f}".format((timer() - st)*1000.)
+        res["doc_engine"] = settings.docStoreConn.health()
+        res["doc_engine"]["elapsed"] = "{:.1f}".format((timer() - st) * 1000.0)
     except Exception as e:
-        res["es"] = {"status": "red", "elapsed": "{:.1f}".format((timer() - st)*1000.), "error": str(e)}
+        res["doc_engine"] = {
+            "type": "unknown",
+            "status": "red",
+            "elapsed": "{:.1f}".format((timer() - st) * 1000.0),
+            "error": str(e),
+        }
 
     st = timer()
     try:
         STORAGE_IMPL.health()
-        res["storage"] = {"storage": STORAGE_IMPL_TYPE.lower(), "status": "green", "elapsed": "{:.1f}".format((timer() - st)*1000.)}
+        res["storage"] = {
+            "storage": STORAGE_IMPL_TYPE.lower(),
+            "status": "green",
+            "elapsed": "{:.1f}".format((timer() - st) * 1000.0),
+        }
     except Exception as e:
-        res["storage"] = {"storage": STORAGE_IMPL_TYPE.lower(), "status": "red", "elapsed": "{:.1f}".format((timer() - st)*1000.), "error": str(e)}
+        res["storage"] = {
+            "storage": STORAGE_IMPL_TYPE.lower(),
+            "status": "red",
+            "elapsed": "{:.1f}".format((timer() - st) * 1000.0),
+            "error": str(e),
+        }
 
     st = timer()
     try:
         KnowledgebaseService.get_by_id("x")
-        res["database"] = {"database": DATABASE_TYPE.lower(), "status": "green", "elapsed": "{:.1f}".format((timer() - st)*1000.)}
+        res["database"] = {
+            "database": settings.DATABASE_TYPE.lower(),
+            "status": "green",
+            "elapsed": "{:.1f}".format((timer() - st) * 1000.0),
+        }
     except Exception as e:
-        res["database"] = {"database": DATABASE_TYPE.lower(), "status": "red", "elapsed": "{:.1f}".format((timer() - st)*1000.), "error": str(e)}
+        res["database"] = {
+            "database": settings.DATABASE_TYPE.lower(),
+            "status": "red",
+            "elapsed": "{:.1f}".format((timer() - st) * 1000.0),
+            "error": str(e),
+        }
 
     st = timer()
     try:
         if not REDIS_CONN.health():
             raise Exception("Lost connection!")
-        res["redis"] = {"status": "green", "elapsed": "{:.1f}".format((timer() - st)*1000.)}
+        res["redis"] = {
+            "status": "green",
+            "elapsed": "{:.1f}".format((timer() - st) * 1000.0),
+        }
     except Exception as e:
-        res["redis"] = {"status": "red", "elapsed": "{:.1f}".format((timer() - st)*1000.), "error": str(e)}
+        res["redis"] = {
+            "status": "red",
+            "elapsed": "{:.1f}".format((timer() - st) * 1000.0),
+            "error": str(e),
+        }
 
+    task_executor_heartbeats = {}
     try:
-        v = REDIS_CONN.get("TASKEXE")
-        if not v:
-            raise Exception("No task executor running!")
-        obj = json.loads(v)
-        color = "green"
-        for id in obj.keys():
-            arr = obj[id]
-            if len(arr) == 1:
-                obj[id] = [0]
-            else:
-                obj[id] = [arr[i+1]-arr[i] for i in range(len(arr)-1)]
-            elapsed = max(obj[id])
-            if elapsed > 50: color = "yellow"
-            if elapsed > 120: color = "red"
-        res["task_executor"] = {"status": color, "elapsed": obj}
-    except Exception as e:
-        res["task_executor"] = {"status": "red", "error": str(e)}
+        task_executors = REDIS_CONN.smembers("TASKEXE")
+        now = datetime.now().timestamp()
+        for task_executor_id in task_executors:
+            heartbeats = REDIS_CONN.zrangebyscore(task_executor_id, now - 60*30, now)
+            heartbeats = [json.loads(heartbeat) for heartbeat in heartbeats]
+            task_executor_heartbeats[task_executor_id] = heartbeats
+    except Exception:
+        logging.exception("get task executor heartbeats failed!")
+    res["task_executor_heartbeats"] = task_executor_heartbeats
 
     return get_json_result(data=res)
+
+
+@manager.route("/new_token", methods=["POST"])
+@login_required
+def new_token():
+    """
+    Generate a new API token.
+    ---
+    tags:
+      - API Tokens
+    security:
+      - ApiKeyAuth: []
+    parameters:
+      - in: query
+        name: name
+        type: string
+        required: false
+        description: Name of the token.
+    responses:
+      200:
+        description: Token generated successfully.
+        schema:
+          type: object
+          properties:
+            token:
+              type: string
+              description: The generated API token.
+    """
+    try:
+        tenants = UserTenantService.query(user_id=current_user.id)
+        if not tenants:
+            return get_data_error_result(message="Tenant not found!")
+
+        tenant_id = tenants[0].tenant_id
+        obj = {
+            "tenant_id": tenant_id,
+            "token": generate_confirmation_token(tenant_id),
+            "create_time": current_timestamp(),
+            "create_date": datetime_format(datetime.now()),
+            "update_time": None,
+            "update_date": None,
+        }
+
+        if not APITokenService.save(**obj):
+            return get_data_error_result(message="Fail to new a dialog!")
+
+        return get_json_result(data=obj)
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route("/token_list", methods=["GET"])
+@login_required
+def token_list():
+    """
+    List all API tokens for the current user.
+    ---
+    tags:
+      - API Tokens
+    security:
+      - ApiKeyAuth: []
+    responses:
+      200:
+        description: List of API tokens.
+        schema:
+          type: object
+          properties:
+            tokens:
+              type: array
+              items:
+                type: object
+                properties:
+                  token:
+                    type: string
+                    description: The API token.
+                  name:
+                    type: string
+                    description: Name of the token.
+                  create_time:
+                    type: string
+                    description: Token creation time.
+    """
+    try:
+        tenants = UserTenantService.query(user_id=current_user.id)
+        if not tenants:
+            return get_data_error_result(message="Tenant not found!")
+
+        objs = APITokenService.query(tenant_id=tenants[0].tenant_id)
+        return get_json_result(data=[o.to_dict() for o in objs])
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route("/token/<token>", methods=["DELETE"])
+@login_required
+def rm(token):
+    """
+    Remove an API token.
+    ---
+    tags:
+      - API Tokens
+    security:
+      - ApiKeyAuth: []
+    parameters:
+      - in: path
+        name: token
+        type: string
+        required: true
+        description: The API token to remove.
+    responses:
+      200:
+        description: Token removed successfully.
+        schema:
+          type: object
+          properties:
+            success:
+              type: boolean
+              description: Deletion status.
+    """
+    APITokenService.filter_delete(
+        [APIToken.tenant_id == current_user.id, APIToken.token == token]
+    )
+    return get_json_result(data=True)

api/apps/tenant_app.py

@@ -15,32 +15,30 @@
 #
 
 from flask import request
-from flask_login import current_user, login_required
+from flask_login import login_required, current_user
 
+from api import settings
 from api.db import UserTenantRole, StatusEnum
 from api.db.db_models import UserTenant
-from api.db.services.user_service import TenantService, UserTenantService
-from api.settings import RetCode
+from api.db.services.user_service import UserTenantService, UserService
 
-from api.utils import get_uuid
-from api.utils.api_utils import get_json_result, validate_request, server_error_response
-
-
-@manager.route("/list", methods=["GET"])
-@login_required
-def tenant_list():
-    try:
-        tenants = TenantService.get_by_user_id(current_user.id)
-        return get_json_result(data=tenants)
-    except Exception as e:
-        return server_error_response(e)
+from api.utils import get_uuid, delta_seconds
+from api.utils.api_utils import get_json_result, validate_request, server_error_response, get_data_error_result
 
 
 @manager.route("/<tenant_id>/user/list", methods=["GET"])
 @login_required
 def user_list(tenant_id):
+    if current_user.id != tenant_id:
+        return get_json_result(
+            data=False,
+            message='No authorization.',
+            code=settings.RetCode.AUTHENTICATION_ERROR)
+
     try:
         users = UserTenantService.get_by_tenant_id(tenant_id)
+        for u in users:
+            u["delta_seconds"] = delta_seconds(str(u["update_date"]))
         return get_json_result(data=users)
     except Exception as e:
         return server_error_response(e)
@@ -48,38 +46,73 @@ def user_list(tenant_id):
 
 @manager.route('/<tenant_id>/user', methods=['POST'])
 @login_required
-@validate_request("user_id")
+@validate_request("email")
 def create(tenant_id):
-    user_id = request.json.get("user_id")
-    if not user_id:
+    if current_user.id != tenant_id:
         return get_json_result(
-            data=False, retmsg='Lack of "USER ID"', retcode=RetCode.ARGUMENT_ERROR)
+            data=False,
+            message='No authorization.',
+            code=settings.RetCode.AUTHENTICATION_ERROR)
 
-    try:
-        user_tenants = UserTenantService.query(user_id=user_id, tenant_id=tenant_id)
-        if user_tenants:
-            uuid = user_tenants[0].id
-            return get_json_result(data={"id": uuid})
+    req = request.json
+    usrs = UserService.query(email=req["email"])
+    if not usrs:
+        return get_data_error_result(message="User not found.")
 
-        uuid = get_uuid()
-        UserTenantService.save(
-            id = uuid,
-            user_id = user_id,
-            tenant_id = tenant_id,
-            role = UserTenantRole.NORMAL.value,
-            status = StatusEnum.VALID.value)
+    user_id = usrs[0].id
+    user_tenants = UserTenantService.query(user_id=user_id, tenant_id=tenant_id)
+    if user_tenants:
+        if user_tenants[0].status == UserTenantRole.NORMAL.value:
+            return get_data_error_result(message="This user is in the team already.")
+        return get_data_error_result(message="Invitation notification is sent.")
 
-        return get_json_result(data={"id": uuid})
-    except Exception as e:
-        return server_error_response(e)
+    UserTenantService.save(
+        id=get_uuid(),
+        user_id=user_id,
+        tenant_id=tenant_id,
+        invited_by=current_user.id,
+        role=UserTenantRole.INVITE,
+        status=StatusEnum.VALID.value)
+
+    usr = usrs[0].to_dict()
+    usr = {k: v for k, v in usr.items() if k in ["id", "avatar", "email", "nickname"]}
+
+    return get_json_result(data=usr)
 
 
 @manager.route('/<tenant_id>/user/<user_id>', methods=['DELETE'])
 @login_required
 def rm(tenant_id, user_id):
+    if current_user.id != tenant_id and current_user.id != user_id:
+        return get_json_result(
+            data=False,
+            message='No authorization.',
+            code=settings.RetCode.AUTHENTICATION_ERROR)
+
     try:
         UserTenantService.filter_delete([UserTenant.tenant_id == tenant_id, UserTenant.user_id == user_id])
         return get_json_result(data=True)
     except Exception as e:
         return server_error_response(e)
-    
+
+
+@manager.route("/list", methods=["GET"])
+@login_required
+def tenant_list():
+    try:
+        users = UserTenantService.get_tenants_by_user_id(current_user.id)
+        for u in users:
+            u["delta_seconds"] = delta_seconds(str(u["update_date"]))
+        return get_json_result(data=users)
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route("/agree/<tenant_id>", methods=["PUT"])
+@login_required
+def agree(tenant_id):
+    try:
+        UserTenantService.filter_update([UserTenant.tenant_id == tenant_id, UserTenant.user_id == current_user.id], {"role": UserTenantRole.NORMAL})
+        return get_json_result(data=True)
+    except Exception as e:
+        return server_error_response(e)

api/apps/user_app.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import json
 import re
 from datetime import datetime
@@ -23,65 +24,127 @@ from flask_login import login_required, current_user, login_user, logout_user
 
 from api.db.db_models import TenantLLM
 from api.db.services.llm_service import TenantLLMService, LLMService
-from api.utils.api_utils import server_error_response, validate_request
-from api.utils import get_uuid, get_format_time, decrypt, download_img, current_timestamp, datetime_format
-from api.db import UserTenantRole, LLMType, FileType
-from api.settings import RetCode, GITHUB_OAUTH, FEISHU_OAUTH, CHAT_MDL, EMBEDDING_MDL, ASR_MDL, IMAGE2TEXT_MDL, PARSERS, \
-    API_KEY, \
-    LLM_FACTORY, LLM_BASE_URL, RERANK_MDL
+from api.utils.api_utils import (
+    server_error_response,
+    validate_request,
+    get_data_error_result,
+)
+from api.utils import (
+    get_uuid,
+    get_format_time,
+    decrypt,
+    download_img,
+    current_timestamp,
+    datetime_format,
+)
+from api.db import UserTenantRole, FileType
+from api import settings
 from api.db.services.user_service import UserService, TenantService, UserTenantService
 from api.db.services.file_service import FileService
-from api.settings import stat_logger
 from api.utils.api_utils import get_json_result, construct_response
 
 
-@manager.route('/login', methods=['POST', 'GET'])
+@manager.route("/login", methods=["POST", "GET"])
 def login():
+    """
+    User login endpoint.
+    ---
+    tags:
+      - User
+    parameters:
+      - in: body
+        name: body
+        description: Login credentials.
+        required: true
+        schema:
+          type: object
+          properties:
+            email:
+              type: string
+              description: User email.
+            password:
+              type: string
+              description: User password.
+    responses:
+      200:
+        description: Login successful.
+        schema:
+          type: object
+      401:
+        description: Authentication failed.
+        schema:
+          type: object
+    """
     if not request.json:
-        return get_json_result(data=False,
-                               retcode=RetCode.AUTHENTICATION_ERROR,
-                               retmsg='Unauthorized!')
+        return get_json_result(
+            data=False, code=settings.RetCode.AUTHENTICATION_ERROR, message="Unauthorized!"
+        )
 
-    email = request.json.get('email', "")
+    email = request.json.get("email", "")
     users = UserService.query(email=email)
     if not users:
-        return get_json_result(data=False,
-                               retcode=RetCode.AUTHENTICATION_ERROR,
-                               retmsg=f'Email: {email} is not registered!')
+        return get_json_result(
+            data=False,
+            code=settings.RetCode.AUTHENTICATION_ERROR,
+            message=f"Email: {email} is not registered!",
+        )
 
-    password = request.json.get('password')
+    password = request.json.get("password")
     try:
         password = decrypt(password)
     except BaseException:
-        return get_json_result(data=False,
-                               retcode=RetCode.SERVER_ERROR,
-                               retmsg='Fail to crypt password')
+        return get_json_result(
+            data=False, code=settings.RetCode.SERVER_ERROR, message="Fail to crypt password"
+        )
 
     user = UserService.query_user(email, password)
     if user:
         response_data = user.to_json()
         user.access_token = get_uuid()
         login_user(user)
-        user.update_time = current_timestamp(),
-        user.update_date = datetime_format(datetime.now()),
+        user.update_time = (current_timestamp(),)
+        user.update_date = (datetime_format(datetime.now()),)
         user.save()
         msg = "Welcome back!"
-        return construct_response(data=response_data, auth=user.get_id(), retmsg=msg)
+        return construct_response(data=response_data, auth=user.get_id(), message=msg)
     else:
-        return get_json_result(data=False,
-                               retcode=RetCode.AUTHENTICATION_ERROR,
-                               retmsg='Email and password do not match!')
+        return get_json_result(
+            data=False,
+            code=settings.RetCode.AUTHENTICATION_ERROR,
+            message="Email and password do not match!",
+        )
 
 
-@manager.route('/github_callback', methods=['GET'])
+@manager.route("/github_callback", methods=["GET"])
 def github_callback():
+    """
+    GitHub OAuth callback endpoint.
+    ---
+    tags:
+      - OAuth
+    parameters:
+      - in: query
+        name: code
+        type: string
+        required: true
+        description: Authorization code from GitHub.
+    responses:
+      200:
+        description: Authentication successful.
+        schema:
+          type: object
+    """
     import requests
-    res = requests.post(GITHUB_OAUTH.get("url"),
-                        data={
-                            "client_id": GITHUB_OAUTH.get("client_id"),
-                            "client_secret": GITHUB_OAUTH.get("secret_key"),
-                            "code": request.args.get('code')},
-                        headers={"Accept": "application/json"})
+
+    res = requests.post(
+        settings.GITHUB_OAUTH.get("url"),
+        data={
+            "client_id": settings.GITHUB_OAUTH.get("client_id"),
+            "client_secret": settings.GITHUB_OAUTH.get("secret_key"),
+            "code": request.args.get("code"),
+        },
+        headers={"Accept": "application/json"},
+    )
     res = res.json()
     if "error" in res:
         return redirect("/?error=%s" % res["error_description"])
@@ -101,21 +164,24 @@ def github_callback():
             try:
                 avatar = download_img(user_info["avatar_url"])
             except Exception as e:
-                stat_logger.exception(e)
+                logging.exception(e)
                 avatar = ""
-            users = user_register(user_id, {
-                "access_token": session["access_token"],
-                "email": email_address,
-                "avatar": avatar,
-                "nickname": user_info["login"],
-                "login_channel": "github",
-                "last_login_time": get_format_time(),
-                "is_superuser": False,
-            })
+            users = user_register(
+                user_id,
+                {
+                    "access_token": session["access_token"],
+                    "email": email_address,
+                    "avatar": avatar,
+                    "nickname": user_info["login"],
+                    "login_channel": "github",
+                    "last_login_time": get_format_time(),
+                    "is_superuser": False,
+                },
+            )
             if not users:
-                raise Exception(f'Fail to register {email_address}.')
+                raise Exception(f"Fail to register {email_address}.")
             if len(users) > 1:
-                raise Exception(f'Same email: {email_address} exists!')
+                raise Exception(f"Same email: {email_address} exists!")
 
             # Try to log in
             user = users[0]
@@ -123,7 +189,7 @@ def github_callback():
             return redirect("/?auth=%s" % user.get_id())
         except Exception as e:
             rollback_user_registration(user_id)
-            stat_logger.exception(e)
+            logging.exception(e)
             return redirect("/?error=%s" % str(e))
 
     # User has already registered, try to log in
@@ -134,30 +200,56 @@ def github_callback():
     return redirect("/?auth=%s" % user.get_id())
 
 
-@manager.route('/feishu_callback', methods=['GET'])
+@manager.route("/feishu_callback", methods=["GET"])
 def feishu_callback():
+    """
+    Feishu OAuth callback endpoint.
+    ---
+    tags:
+      - OAuth
+    parameters:
+      - in: query
+        name: code
+        type: string
+        required: true
+        description: Authorization code from Feishu.
+    responses:
+      200:
+        description: Authentication successful.
+        schema:
+          type: object
+    """
     import requests
-    app_access_token_res = requests.post(FEISHU_OAUTH.get("app_access_token_url"),
-                                         data=json.dumps({
-                                             "app_id": FEISHU_OAUTH.get("app_id"),
-                                             "app_secret": FEISHU_OAUTH.get("app_secret")
-                                         }),
-                                         headers={"Content-Type": "application/json; charset=utf-8"})
+
+    app_access_token_res = requests.post(
+        settings.FEISHU_OAUTH.get("app_access_token_url"),
+        data=json.dumps(
+            {
+                "app_id": settings.FEISHU_OAUTH.get("app_id"),
+                "app_secret": settings.FEISHU_OAUTH.get("app_secret"),
+            }
+        ),
+        headers={"Content-Type": "application/json; charset=utf-8"},
+    )
     app_access_token_res = app_access_token_res.json()
-    if app_access_token_res['code'] != 0:
+    if app_access_token_res["code"] != 0:
         return redirect("/?error=%s" % app_access_token_res)
 
-    res = requests.post(FEISHU_OAUTH.get("user_access_token_url"),
-                        data=json.dumps({
-                            "grant_type": FEISHU_OAUTH.get("grant_type"),
-                            "code": request.args.get('code')
-                        }),
-                        headers={
-                            "Content-Type": "application/json; charset=utf-8",
-                            'Authorization': f"Bearer {app_access_token_res['app_access_token']}"
-                        })
+    res = requests.post(
+        settings.FEISHU_OAUTH.get("user_access_token_url"),
+        data=json.dumps(
+            {
+                "grant_type": settings.FEISHU_OAUTH.get("grant_type"),
+                "code": request.args.get("code"),
+            }
+        ),
+        headers={
+            "Content-Type": "application/json; charset=utf-8",
+            "Authorization": f"Bearer {app_access_token_res['app_access_token']}",
+        },
+    )
     res = res.json()
-    if res['code'] != 0:
+    if res["code"] != 0:
         return redirect("/?error=%s" % res["message"])
 
     if "contact:user.email:readonly" not in res["data"]["scope"].split(" "):
@@ -174,21 +266,24 @@ def feishu_callback():
             try:
                 avatar = download_img(user_info["avatar_url"])
             except Exception as e:
-                stat_logger.exception(e)
+                logging.exception(e)
                 avatar = ""
-            users = user_register(user_id, {
-                "access_token": session["access_token"],
-                "email": email_address,
-                "avatar": avatar,
-                "nickname": user_info["en_name"],
-                "login_channel": "feishu",
-                "last_login_time": get_format_time(),
-                "is_superuser": False,
-            })
+            users = user_register(
+                user_id,
+                {
+                    "access_token": session["access_token"],
+                    "email": email_address,
+                    "avatar": avatar,
+                    "nickname": user_info["en_name"],
+                    "login_channel": "feishu",
+                    "last_login_time": get_format_time(),
+                    "is_superuser": False,
+                },
+            )
             if not users:
-                raise Exception(f'Fail to register {email_address}.')
+                raise Exception(f"Fail to register {email_address}.")
             if len(users) > 1:
-                raise Exception(f'Same email: {email_address} exists!')
+                raise Exception(f"Same email: {email_address} exists!")
 
             # Try to log in
             user = users[0]
@@ -196,7 +291,7 @@ def feishu_callback():
             return redirect("/?auth=%s" % user.get_id())
         except Exception as e:
             rollback_user_registration(user_id)
-            stat_logger.exception(e)
+            logging.exception(e)
             return redirect("/?error=%s" % str(e))
 
     # User has already registered, try to log in
@@ -209,11 +304,14 @@ def feishu_callback():
 
 def user_info_from_feishu(access_token):
     import requests
-    headers = {"Content-Type": "application/json; charset=utf-8",
-               'Authorization': f"Bearer {access_token}"}
+
+    headers = {
+        "Content-Type": "application/json; charset=utf-8",
+        "Authorization": f"Bearer {access_token}",
+    }
     res = requests.get(
-        f"https://open.feishu.cn/open-apis/authen/v1/user_info",
-        headers=headers)
+        "https://open.feishu.cn/open-apis/authen/v1/user_info", headers=headers
+    )
     user_info = res.json()["data"]
     user_info["email"] = None if user_info.get("email") == "" else user_info["email"]
     return user_info
@@ -221,24 +319,38 @@ def user_info_from_feishu(access_token):
 
 def user_info_from_github(access_token):
     import requests
-    headers = {"Accept": "application/json",
-               'Authorization': f"token {access_token}"}
+
+    headers = {"Accept": "application/json", "Authorization": f"token {access_token}"}
     res = requests.get(
-        f"https://api.github.com/user?access_token={access_token}",
-        headers=headers)
+        f"https://api.github.com/user?access_token={access_token}", headers=headers
+    )
     user_info = res.json()
     email_info = requests.get(
         f"https://api.github.com/user/emails?access_token={access_token}",
-        headers=headers).json()
+        headers=headers,
+    ).json()
     user_info["email"] = next(
-        (email for email in email_info if email['primary'] == True),
-        None)["email"]
+        (email for email in email_info if email["primary"] == True), None
+    )["email"]
     return user_info
 
 
-@manager.route("/logout", methods=['GET'])
+@manager.route("/logout", methods=["GET"])
 @login_required
 def log_out():
+    """
+    User logout endpoint.
+    ---
+    tags:
+      - User
+    security:
+      - ApiKeyAuth: []
+    responses:
+      200:
+        description: Logout successful.
+        schema:
+          type: object
+    """
     current_user.access_token = ""
     current_user.save()
     logout_user()
@@ -248,19 +360,62 @@ def log_out():
 @manager.route("/setting", methods=["POST"])
 @login_required
 def setting_user():
+    """
+    Update user settings.
+    ---
+    tags:
+      - User
+    security:
+      - ApiKeyAuth: []
+    parameters:
+      - in: body
+        name: body
+        description: User settings to update.
+        required: true
+        schema:
+          type: object
+          properties:
+            nickname:
+              type: string
+              description: New nickname.
+            email:
+              type: string
+              description: New email.
+    responses:
+      200:
+        description: Settings updated successfully.
+        schema:
+          type: object
+    """
     update_dict = {}
     request_data = request.json
     if request_data.get("password"):
         new_password = request_data.get("new_password")
         if not check_password_hash(
-                current_user.password, decrypt(request_data["password"])):
-            return get_json_result(data=False, retcode=RetCode.AUTHENTICATION_ERROR, retmsg='Password error!')
+                current_user.password, decrypt(request_data["password"])
+        ):
+            return get_json_result(
+                data=False,
+                code=settings.RetCode.AUTHENTICATION_ERROR,
+                message="Password error!",
+            )
 
         if new_password:
             update_dict["password"] = generate_password_hash(decrypt(new_password))
 
     for k in request_data.keys():
-        if k in ["password", "new_password"]:
+        if k in [
+            "password",
+            "new_password",
+            "email",
+            "status",
+            "is_superuser",
+            "login_channel",
+            "is_anonymous",
+            "is_active",
+            "is_authenticated",
+            "last_login_time",
+        ]:
             continue
         update_dict[k] = request_data[k]
 
@@ -268,34 +423,59 @@ def setting_user():
         UserService.update_by_id(current_user.id, update_dict)
         return get_json_result(data=True)
     except Exception as e:
-        stat_logger.exception(e)
-        return get_json_result(data=False, retmsg='Update failure!', retcode=RetCode.EXCEPTION_ERROR)
+        logging.exception(e)
+        return get_json_result(
+            data=False, message="Update failure!", code=settings.RetCode.EXCEPTION_ERROR
+        )
 
 
 @manager.route("/info", methods=["GET"])
 @login_required
 def user_profile():
+    """
+    Get user profile information.
+    ---
+    tags:
+      - User
+    security:
+      - ApiKeyAuth: []
+    responses:
+      200:
+        description: User profile retrieved successfully.
+        schema:
+          type: object
+          properties:
+            id:
+              type: string
+              description: User ID.
+            nickname:
+              type: string
+              description: User nickname.
+            email:
+              type: string
+              description: User email.
+    """
     return get_json_result(data=current_user.to_dict())
 
 
 def rollback_user_registration(user_id):
     try:
         UserService.delete_by_id(user_id)
-    except Exception as e:
+    except Exception:
         pass
     try:
         TenantService.delete_by_id(user_id)
-    except Exception as e:
+    except Exception:
         pass
     try:
         u = UserTenantService.query(tenant_id=user_id)
         if u:
             UserTenantService.delete_by_id(u[0].id)
-    except Exception as e:
+    except Exception:
         pass
     try:
         TenantLLM.delete().where(TenantLLM.tenant_id == user_id).execute()
-    except Exception as e:
+    except Exception:
         pass
 
 
@@ -304,18 +484,18 @@ def user_register(user_id, user):
     tenant = {
         "id": user_id,
         "name": user["nickname"] + "‘s Kingdom",
-        "llm_id": CHAT_MDL,
-        "embd_id": EMBEDDING_MDL,
-        "asr_id": ASR_MDL,
-        "parser_ids": PARSERS,
-        "img2txt_id": IMAGE2TEXT_MDL,
-        "rerank_id": RERANK_MDL
+        "llm_id": settings.CHAT_MDL,
+        "embd_id": settings.EMBEDDING_MDL,
+        "asr_id": settings.ASR_MDL,
+        "parser_ids": settings.PARSERS,
+        "img2txt_id": settings.IMAGE2TEXT_MDL,
+        "rerank_id": settings.RERANK_MDL,
     }
     usr_tenant = {
         "tenant_id": user_id,
         "user_id": user_id,
         "invited_by": user_id,
-        "role": UserTenantRole.OWNER
+        "role": UserTenantRole.OWNER,
     }
     file_id = get_uuid()
     file = {
@@ -329,14 +509,18 @@ def user_register(user_id, user):
         "location": "",
     }
     tenant_llm = []
-    for llm in LLMService.query(fid=LLM_FACTORY):
-        tenant_llm.append({"tenant_id": user_id,
-                           "llm_factory": LLM_FACTORY,
-                           "llm_name": llm.llm_name,
-                           "model_type": llm.model_type,
-                           "api_key": API_KEY,
-                           "api_base": LLM_BASE_URL
-                           })
+    for llm in LLMService.query(fid=settings.LLM_FACTORY):
+        tenant_llm.append(
+            {
+                "tenant_id": user_id,
+                "llm_factory": settings.LLM_FACTORY,
+                "llm_name": llm.llm_name,
+                "model_type": llm.model_type,
+                "api_key": settings.API_KEY,
+                "api_base": settings.LLM_BASE_URL,
+                "max_tokens": llm.max_tokens if llm.max_tokens else 8192
+            }
+        )
 
     if not UserService.save(**user):
         return
@@ -350,21 +534,52 @@ def user_register(user_id, user):
 @manager.route("/register", methods=["POST"])
 @validate_request("nickname", "email", "password")
 def user_add():
+    """
+    Register a new user.
+    ---
+    tags:
+      - User
+    parameters:
+      - in: body
+        name: body
+        description: Registration details.
+        required: true
+        schema:
+          type: object
+          properties:
+            nickname:
+              type: string
+              description: User nickname.
+            email:
+              type: string
+              description: User email.
+            password:
+              type: string
+              description: User password.
+    responses:
+      200:
+        description: Registration successful.
+        schema:
+          type: object
+    """
     req = request.json
     email_address = req["email"]
 
     # Validate the email address
-    if not re.match(r"^[\w\._-]+@([\w_-]+\.)+[\w-]{2,4}$", email_address):
-        return get_json_result(data=False,
-                               retmsg=f'Invalid email address: {email_address}!',
-                               retcode=RetCode.OPERATING_ERROR)
+    if not re.match(r"^[\w\._-]+@([\w_-]+\.)+[\w-]{2,5}$", email_address):
+        return get_json_result(
+            data=False,
+            message=f"Invalid email address: {email_address}!",
+            code=settings.RetCode.OPERATING_ERROR,
+        )
 
     # Check if the email address is already used
     if UserService.query(email=email_address):
         return get_json_result(
             data=False,
-            retmsg=f'Email: {email_address} has already registered!',
-            retcode=RetCode.OPERATING_ERROR)
+            message=f"Email: {email_address} has already registered!",
+            code=settings.RetCode.OPERATING_ERROR,
+        )
 
     # Construct user info data
     nickname = req["nickname"]
@@ -382,28 +597,60 @@ def user_add():
     try:
         users = user_register(user_id, user_dict)
         if not users:
-            raise Exception(f'Fail to register {email_address}.')
+            raise Exception(f"Fail to register {email_address}.")
         if len(users) > 1:
-            raise Exception(f'Same email: {email_address} exists!')
+            raise Exception(f"Same email: {email_address} exists!")
         user = users[0]
         login_user(user)
-        return construct_response(data=user.to_json(),
-                                  auth=user.get_id(),
-                                  retmsg=f"{nickname}, welcome aboard!")
+        return construct_response(
+            data=user.to_json(),
+            auth=user.get_id(),
+            message=f"{nickname}, welcome aboard!",
+        )
     except Exception as e:
         rollback_user_registration(user_id)
-        stat_logger.exception(e)
-        return get_json_result(data=False,
-                               retmsg=f'User registration failure, error: {str(e)}',
-                               retcode=RetCode.EXCEPTION_ERROR)
+        logging.exception(e)
+        return get_json_result(
+            data=False,
+            message=f"User registration failure, error: {str(e)}",
+            code=settings.RetCode.EXCEPTION_ERROR,
+        )
 
 
 @manager.route("/tenant_info", methods=["GET"])
 @login_required
 def tenant_info():
+    """
+    Get tenant information.
+    ---
+    tags:
+      - Tenant
+    security:
+      - ApiKeyAuth: []
+    responses:
+      200:
+        description: Tenant information retrieved successfully.
+        schema:
+          type: object
+          properties:
+            tenant_id:
+              type: string
+              description: Tenant ID.
+            name:
+              type: string
+              description: Tenant name.
+            llm_id:
+              type: string
+              description: LLM ID.
+            embd_id:
+              type: string
+              description: Embedding model ID.
+    """
     try:
-        tenants = TenantService.get_by_user_id(current_user.id)[0]
-        return get_json_result(data=tenants)
+        tenants = TenantService.get_info_by(current_user.id)
+        if not tenants:
+            return get_data_error_result(message="Tenant not found!")
+        return get_json_result(data=tenants[0])
     except Exception as e:
         return server_error_response(e)
 
@@ -412,10 +659,45 @@ def tenant_info():
 @login_required
 @validate_request("tenant_id", "asr_id", "embd_id", "img2txt_id", "llm_id")
 def set_tenant_info():
+    """
+    Update tenant information.
+    ---
+    tags:
+      - Tenant
+    security:
+      - ApiKeyAuth: []
+    parameters:
+      - in: body
+        name: body
+        description: Tenant information to update.
+        required: true
+        schema:
+          type: object
+          properties:
+            tenant_id:
+              type: string
+              description: Tenant ID.
+            llm_id:
+              type: string
+              description: LLM ID.
+            embd_id:
+              type: string
+              description: Embedding model ID.
+            asr_id:
+              type: string
+              description: ASR model ID.
+            img2txt_id:
+              type: string
+              description: Image to Text model ID.
+    responses:
+      200:
+        description: Tenant information updated successfully.
+        schema:
+          type: object
+    """
     req = request.json
     try:
-        tid = req["tenant_id"]
-        del req["tenant_id"]
+        tid = req.pop("tenant_id")
         TenantService.update_by_id(tid, req)
         return get_json_result(data=True)
     except Exception as e:

api/constants.py

@@ -12,10 +12,14 @@
 #  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
-#
 
-import operator
-import time
-import typing
-from api.utils.log_utils import sql_logger
-import peewee
+NAME_LENGTH_LIMIT = 2 ** 10
+
+IMG_BASE64_PREFIX = 'data:image/png;base64,'
+
+SERVICE_CONF = "service_conf.yaml"
+
+API_VERSION = "v1"
+RAG_FLOW_SERVICE_NAME = "ragflow"
+REQUEST_WAIT_SEC = 2
+REQUEST_MAX_WAIT_SEC = 300

api/contants.py

@@ -1,16 +0,0 @@
-#
-#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
-#
-#  Licensed under the Apache License, Version 2.0 (the "License");
-#  you may not use this file except in compliance with the License.
-#  You may obtain a copy of the License at
-#
-#      http://www.apache.org/licenses/LICENSE-2.0
-#
-#  Unless required by applicable law or agreed to in writing, software
-#  distributed under the License is distributed on an "AS IS" BASIS,
-#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-#  See the License for the specific language governing permissions and
-#  limitations under the License.
-
-NAME_LENGTH_LIMIT = 2 ** 10

api/db/__init__.py

@@ -27,6 +27,7 @@ class UserTenantRole(StrEnum):
     OWNER = 'owner'
     ADMIN = 'admin'
     NORMAL = 'normal'
+    INVITE = 'invite'
 
 
 class TenantPermission(StrEnum):

api/db/db_models.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import inspect
 import os
 import sys
@@ -29,12 +30,11 @@ from peewee import (
     Field, Model, Metadata
 )
 from playhouse.pool import PooledMySQLDatabase, PooledPostgresqlDatabase
-from api.db import SerializedType, ParserType
-from api.settings import DATABASE, stat_logger, SECRET_KEY, DATABASE_TYPE
-from api.utils.log_utils import getLogger
-from api import utils
 
-LOGGER = getLogger()
+
+from api.db import SerializedType, ParserType
+from api import settings
+from api import utils
 
 
 def singleton(cls, *args, **kw):
@@ -65,7 +65,7 @@ class TextFieldType(Enum):
 
 
 class LongTextField(TextField):
-    field_type = TextFieldType[DATABASE_TYPE.upper()].value
+    field_type = TextFieldType[settings.DATABASE_TYPE.upper()].value
 
 
 class JSONField(LongTextField):
@@ -272,6 +272,7 @@ class JsonSerializedField(SerializedField):
         super(JsonSerializedField, self).__init__(serialized_type=SerializedType.JSON, object_hook=object_hook,
                                                   object_pairs_hook=object_pairs_hook, **kwargs)
 
+
 class PooledDatabase(Enum):
     MYSQL = PooledMySQLDatabase
     POSTGRES = PooledPostgresqlDatabase
@@ -285,10 +286,11 @@ class DatabaseMigrator(Enum):
 @singleton
 class BaseDataBase:
     def __init__(self):
-        database_config = DATABASE.copy()
+        database_config = settings.DATABASE.copy()
         db_name = database_config.pop("name")
-        self.database_connection = PooledDatabase[DATABASE_TYPE.upper()].value(db_name, **database_config)
-        stat_logger.info('init database on cluster mode successfully')
+        self.database_connection = PooledDatabase[settings.DATABASE_TYPE.upper()].value(db_name, **database_config)
+        logging.info('init database on cluster mode successfully')
+
 
 class PostgresDatabaseLock:
     def __init__(self, lock_name, timeout=10, db=None):
@@ -334,6 +336,7 @@ class PostgresDatabaseLock:
 
         return magic
 
+
 class MysqlDatabaseLock:
     def __init__(self, lock_name, timeout=10, db=None):
         self.lock_name = lock_name
@@ -388,7 +391,7 @@ class DatabaseLock(Enum):
 
 
 DB = BaseDataBase().database_connection
-DB.lock = DatabaseLock[DATABASE_TYPE.upper()].value
+DB.lock = DatabaseLock[settings.DATABASE_TYPE.upper()].value
 
 
 def close_connection():
@@ -396,7 +399,7 @@ def close_connection():
         if DB:
             DB.close_stale(age=30)
     except Exception as e:
-        LOGGER.exception(e)
+        logging.exception(e)
 
 
 class DataBaseModel(BaseModel):
@@ -412,15 +415,15 @@ def init_database_tables(alter_fields=[]):
     for name, obj in members:
         if obj != DataBaseModel and issubclass(obj, DataBaseModel):
             table_objs.append(obj)
-            LOGGER.info(f"start create table {obj.__name__}")
+            logging.debug(f"start create table {obj.__name__}")
             try:
                 obj.create_table()
-                LOGGER.info(f"create table success: {obj.__name__}")
+                logging.debug(f"create table success: {obj.__name__}")
             except Exception as e:
-                LOGGER.exception(e)
+                logging.exception(e)
                 create_failed_list.append(obj.__name__)
     if create_failed_list:
-        LOGGER.info(f"create tables failed: {create_failed_list}")
+        logging.error(f"create tables failed: {create_failed_list}")
         raise Exception(f"create tables failed: {create_failed_list}")
     migrate_db()
 
@@ -470,7 +473,7 @@ class User(DataBaseModel, UserMixin):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
     is_superuser = BooleanField(null=True, help_text="is root", default=False, index=True)
@@ -479,7 +482,7 @@ class User(DataBaseModel, UserMixin):
         return self.email
 
     def get_id(self):
-        jwt = Serializer(secret_key=SECRET_KEY)
+        jwt = Serializer(secret_key=settings.SECRET_KEY)
         return jwt.dumps(str(self.access_token))
 
     class Meta:
@@ -525,7 +528,7 @@ class Tenant(DataBaseModel):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
 
@@ -542,7 +545,7 @@ class UserTenant(DataBaseModel):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
 
@@ -559,7 +562,7 @@ class InvitationCode(DataBaseModel):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
 
@@ -582,7 +585,7 @@ class LLMFactories(DataBaseModel):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
 
@@ -616,7 +619,7 @@ class LLM(DataBaseModel):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
 
@@ -648,7 +651,7 @@ class TenantLLM(DataBaseModel):
         index=True)
     api_key = CharField(max_length=1024, null=True, help_text="API KEY", index=True)
     api_base = CharField(max_length=255, null=True, help_text="API Base")
-
+    max_tokens = IntegerField(default=8192, index=True)
     used_tokens = IntegerField(default=0, index=True)
 
     def __str__(self):
@@ -703,7 +706,7 @@ class Knowledgebase(DataBaseModel):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
 
@@ -767,7 +770,7 @@ class Document(DataBaseModel):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
 
@@ -840,7 +843,7 @@ class Task(DataBaseModel):
     doc_id = CharField(max_length=32, null=False, index=True)
     from_page = IntegerField(default=0)
 
-    to_page = IntegerField(default=-1)
+    to_page = IntegerField(default=100000000)
 
     begin_at = DateTimeField(null=True, index=True)
     process_duation = FloatField(default=0)
@@ -879,8 +882,10 @@ class Dialog(DataBaseModel):
         default="simple",
         help_text="simple|advanced",
         index=True)
-    prompt_config = JSONField(null=False, default={"system": "", "prologue": "您好，我是您的助手小樱，长得可爱又善良，can I help you?",
-                                                   "parameters": [], "empty_response": "Sorry! 知识库中未找到相关内容！"})
+    prompt_config = JSONField(null=False,
+                              default={"system": "", "prologue": "Hi! I'm your assistant, what can I do for you?",
+                                       "parameters": [],
+                                       "empty_response": "Sorry! No relevant content was found in the knowledge base!"})
 
     similarity_threshold = FloatField(default=0.2)
     vector_similarity_weight = FloatField(default=0.3)
@@ -894,7 +899,7 @@ class Dialog(DataBaseModel):
         null=False,
         default="1",
         help_text="it needs to insert reference index into answer or not")
-    
+
     rerank_id = CharField(
         max_length=128,
         null=False,
@@ -904,7 +909,7 @@ class Dialog(DataBaseModel):
     status = CharField(
         max_length=1,
         null=True,
-        help_text="is it validate(0: wasted，1: validate)",
+        help_text="is it validate(0: wasted, 1: validate)",
         default="1",
         index=True)
 
@@ -980,14 +985,14 @@ class CanvasTemplate(DataBaseModel):
 
 def migrate_db():
     with DB.transaction():
-        migrator = DatabaseMigrator[DATABASE_TYPE.upper()].value(DB)
+        migrator = DatabaseMigrator[settings.DATABASE_TYPE.upper()].value(DB)
         try:
             migrate(
                 migrator.add_column('file', 'source_type', CharField(max_length=128, null=False, default="",
                                                                      help_text="where dose this document come from",
                                                                      index=True))
             )
-        except Exception as e:
+        except Exception:
             pass
         try:
             migrate(
@@ -996,7 +1001,7 @@ def migrate_db():
                                               help_text="default rerank model ID"))
 
             )
-        except Exception as e:
+        except Exception:
             pass
         try:
             migrate(
@@ -1004,52 +1009,64 @@ def migrate_db():
                                                                      help_text="default rerank model ID"))
 
             )
-        except Exception as e:
+        except Exception:
             pass
         try:
             migrate(
                 migrator.add_column('dialog', 'top_k', IntegerField(default=1024))
 
             )
-        except Exception as e:
+        except Exception:
             pass
         try:
             migrate(
                 migrator.alter_column_type('tenant_llm', 'api_key',
                                            CharField(max_length=1024, null=True, help_text="API KEY", index=True))
             )
-        except Exception as e:
+        except Exception:
             pass
         try:
             migrate(
                 migrator.add_column('api_token', 'source',
                                     CharField(max_length=16, null=True, help_text="none|agent|dialog", index=True))
             )
-        except Exception as e:
+        except Exception:
             pass
         try:
             migrate(
-                migrator.add_column("tenant","tts_id",
-                    CharField(max_length=256,null=True,help_text="default tts model ID",index=True))
+                migrator.add_column("tenant", "tts_id",
+                                    CharField(max_length=256, null=True, help_text="default tts model ID", index=True))
             )
-        except Exception as e:
+        except Exception:
             pass
         try:
             migrate(
                 migrator.add_column('api_4_conversation', 'source',
                                     CharField(max_length=16, null=True, help_text="none|agent|dialog", index=True))
             )
-        except Exception as e:
+        except Exception:
             pass
         try:
             DB.execute_sql('ALTER TABLE llm DROP PRIMARY KEY;')
             DB.execute_sql('ALTER TABLE llm ADD PRIMARY KEY (llm_name,fid);')
-        except Exception as e:
+        except Exception:
             pass
         try:
             migrate(
                 migrator.add_column('task', 'retry_count', IntegerField(default=0))
             )
-        except Exception as e:
+        except Exception:
+            pass
+        try:
+            migrate(
+                migrator.alter_column_type('api_token', 'dialog_id',
+                                           CharField(max_length=32, null=True, index=True))
+            )
+        except Exception:
+            pass
+        try:
+            migrate(
+                migrator.add_column("tenant_llm","max_tokens",IntegerField(default=8192,index=True))
+            )
+        except Exception:
             pass
-

api/db/db_utils.py

@@ -15,19 +15,12 @@
 #
 import operator
 from functools import reduce
-from typing import Dict, Type, Union
 
 from playhouse.pool import PooledMySQLDatabase
 
 from api.utils import current_timestamp, timestamp_to_date
 
 from api.db.db_models import DB, DataBaseModel
-from api.db.runtime_config import RuntimeConfig
-from api.utils.log_utils import getLogger
-from enum import Enum
-
-
-LOGGER = getLogger()
 
 
 @DB.connection_context()
@@ -93,7 +86,7 @@ supported_operators = {
 
 
 def query_dict2expression(
-        model: Type[DataBaseModel], query: Dict[str, Union[bool, int, str, list, tuple]]):
+        model: type[DataBaseModel], query: dict[str, bool | int | str | list | tuple]):
     expression = []
 
     for field, value in query.items():
@@ -111,8 +104,8 @@ def query_dict2expression(
     return reduce(operator.iand, expression)
 
 
-def query_db(model: Type[DataBaseModel], limit: int = 0, offset: int = 0,
-             query: dict = None, order_by: Union[str, list, tuple] = None):
+def query_db(model: type[DataBaseModel], limit: int = 0, offset: int = 0,
+             query: dict = None, order_by: str | list | tuple | None = None):
     data = model.select()
     if query:
         data = data.where(query_dict2expression(model, query))

api/db/init_data.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import base64
 import json
 import os
@@ -28,7 +29,7 @@ from api.db.services.document_service import DocumentService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMFactoriesService, LLMService, TenantLLMService, LLMBundle
 from api.db.services.user_service import TenantService, UserTenantService
-from api.settings import CHAT_MDL, EMBEDDING_MDL, ASR_MDL, IMAGE2TEXT_MDL, PARSERS, LLM_FACTORY, API_KEY, LLM_BASE_URL
+from api import settings
 from api.utils.file_utils import get_project_base_directory
 
 
@@ -50,11 +51,11 @@ def init_superuser():
     tenant = {
         "id": user_info["id"],
         "name": user_info["nickname"] + "‘s Kingdom",
-        "llm_id": CHAT_MDL,
-        "embd_id": EMBEDDING_MDL,
-        "asr_id": ASR_MDL,
-        "parser_ids": PARSERS,
-        "img2txt_id": IMAGE2TEXT_MDL
+        "llm_id": settings.CHAT_MDL,
+        "embd_id": settings.EMBEDDING_MDL,
+        "asr_id": settings.ASR_MDL,
+        "parser_ids": settings.PARSERS,
+        "img2txt_id": settings.IMAGE2TEXT_MDL
     }
     usr_tenant = {
         "tenant_id": user_info["id"],
@@ -63,42 +64,43 @@ def init_superuser():
         "role": UserTenantRole.OWNER
     }
     tenant_llm = []
-    for llm in LLMService.query(fid=LLM_FACTORY):
+    for llm in LLMService.query(fid=settings.LLM_FACTORY):
         tenant_llm.append(
-            {"tenant_id": user_info["id"], "llm_factory": LLM_FACTORY, "llm_name": llm.llm_name, "model_type": llm.model_type,
-             "api_key": API_KEY, "api_base": LLM_BASE_URL})
+            {"tenant_id": user_info["id"], "llm_factory": settings.LLM_FACTORY, "llm_name": llm.llm_name,
+             "model_type": llm.model_type,
+             "api_key": settings.API_KEY, "api_base": settings.LLM_BASE_URL})
 
     if not UserService.save(**user_info):
-        print("\033[93m【ERROR】\033[0mcan't init admin.")
+        logging.error("can't init admin.")
         return
     TenantService.insert(**tenant)
     UserTenantService.insert(**usr_tenant)
     TenantLLMService.insert_many(tenant_llm)
-    print(
-        "【INFO】Super user initialized. \033[93memail: admin@ragflow.io, password: admin\033[0m. Changing the password after logining is strongly recomanded.")
+    logging.info(
+        "Super user initialized. email: admin@ragflow.io, password: admin. Changing the password after login is strongly recommended.")
 
     chat_mdl = LLMBundle(tenant["id"], LLMType.CHAT, tenant["llm_id"])
     msg = chat_mdl.chat(system="", history=[
-                        {"role": "user", "content": "Hello!"}], gen_conf={})
+        {"role": "user", "content": "Hello!"}], gen_conf={})
     if msg.find("ERROR: ") == 0:
-        print(
-            "\33[91m【ERROR】\33[0m: ",
+        logging.error(
             "'{}' dosen't work. {}".format(
                 tenant["llm_id"],
                 msg))
     embd_mdl = LLMBundle(tenant["id"], LLMType.EMBEDDING, tenant["embd_id"])
     v, c = embd_mdl.encode(["Hello!"])
     if c == 0:
-        print(
-            "\33[91m【ERROR】\33[0m:",
-            " '{}' dosen't work!".format(
+        logging.error(
+            "'{}' dosen't work!".format(
                 tenant["embd_id"]))
 
 
 def init_llm_factory():
     try:
         LLMService.filter_delete([(LLM.fid == "MiniMax" or LLM.fid == "Minimax")])
-    except Exception as e:
+        LLMService.filter_delete([(LLM.fid == "cohere")])
+        LLMFactoriesService.filter_delete([LLMFactories.name == "cohere"])
+    except Exception:
         pass
 
     factory_llm_infos = json.load(
@@ -111,14 +113,14 @@ def init_llm_factory():
         llm_infos = factory_llm_info.pop("llm")
         try:
             LLMFactoriesService.save(**factory_llm_info)
-        except Exception as e:
+        except Exception:
             pass
         LLMService.filter_delete([LLM.fid == factory_llm_info["name"]])
         for llm_info in llm_infos:
             llm_info["fid"] = factory_llm_info["name"]
             try:
                 LLMService.save(**llm_info)
-            except Exception as e:
+            except Exception:
                 pass
 
     LLMFactoriesService.filter_delete([LLMFactories.name == "Local"])
@@ -129,10 +131,11 @@ def init_llm_factory():
     LLMFactoriesService.filter_delete([LLMFactoriesService.model.name == "QAnything"])
     LLMService.filter_delete([LLMService.model.fid == "QAnything"])
     TenantLLMService.filter_update([TenantLLMService.model.llm_factory == "QAnything"], {"llm_factory": "Youdao"})
+    TenantLLMService.filter_update([TenantLLMService.model.llm_factory == "cohere"], {"llm_factory": "Cohere"})
     TenantService.filter_update([1 == 1], {
         "parser_ids": "naive:General,qa:Q&A,resume:Resume,manual:Manual,table:Table,paper:Paper,book:Book,laws:Laws,presentation:Presentation,picture:Picture,one:One,audio:Audio,knowledge_graph:Knowledge Graph,email:Email"})
     ## insert openai two embedding models to the current openai user.
-    print("Start to insert 2 OpenAI embedding models...")
+    # print("Start to insert 2 OpenAI embedding models...")
     tenant_ids = set([row["tenant_id"] for row in TenantLLMService.get_openai_models()])
     for tid in tenant_ids:
         for row in TenantLLMService.query(llm_factory="OpenAI", tenant_id=tid):
@@ -145,7 +148,7 @@ def init_llm_factory():
                 row = deepcopy(row)
                 row["llm_name"] = "text-embedding-3-large"
                 TenantLLMService.save(**row)
-            except Exception as e:
+            except Exception:
                 pass
             break
     for kb_id in KnowledgebaseService.get_all_ids():
@@ -169,20 +172,19 @@ def add_graph_templates():
                 CanvasTemplateService.save(**cnvs)
             except:
                 CanvasTemplateService.update_by_id(cnvs["id"], cnvs)
-        except Exception as e:
-            print("Add graph templates error: ", e)
-            print("------------", flush=True)
+        except Exception:
+            logging.exception("Add graph templates error: ")
 
 
 def init_web_data():
     start_time = time.time()
 
     init_llm_factory()
-    #if not UserService.get_all().count():
+    # if not UserService.get_all().count():
     #    init_superuser()
 
     add_graph_templates()
-    print("init web data success:{}".format(time.time() - start_time))
+    logging.info("init web data success:{}".format(time.time() - start_time))
 
 
 if __name__ == '__main__':

api/db/runtime_config.py

@@ -13,7 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-from api.versions import get_versions
+from api.versions import get_ragflow_version
 from .reload_config_base import ReloadConfigBase
 
 
@@ -35,7 +35,7 @@ class RuntimeConfig(ReloadConfigBase):
 
     @classmethod
     def init_env(cls):
-        cls.ENV.update(get_versions())
+        cls.ENV.update({"version": get_ragflow_version()})
 
     @classmethod
     def load_config_manager(cls):

api/db/services/canvas_service.py

@@ -22,5 +22,6 @@ from api.db.services.common_service import CommonService
 class CanvasTemplateService(CommonService):
     model = CanvasTemplate
 
+
 class UserCanvasService(CommonService):
     model = UserCanvas

api/db/services/dialog_service.py

@@ -13,20 +13,22 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import binascii
 import os
 import json
 import re
 from copy import deepcopy
 from timeit import default_timer as timer
-from api.db import LLMType, ParserType
-from api.db.db_models import Dialog, Conversation
+import datetime
+from datetime import timedelta
+from api.db import LLMType, ParserType,StatusEnum
+from api.db.db_models import Dialog, Conversation,DB
 from api.db.services.common_service import CommonService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMService, TenantLLMService, LLMBundle
-from api.settings import chat_logger, retrievaler, kg_retrievaler
+from api import settings
 from rag.app.resume import forbidden_select_fields4resume
-from rag.nlp import keyword_extraction
 from rag.nlp.search import index_name
 from rag.utils import rmSpace, num_tokens_from_string, encoder
 from api.utils.file_utils import get_project_base_directory
@@ -35,10 +37,49 @@ from api.utils.file_utils import get_project_base_directory
 class DialogService(CommonService):
     model = Dialog
 
+    @classmethod
+    @DB.connection_context()
+    def get_list(cls, tenant_id,
+                 page_number, items_per_page, orderby, desc, id , name):
+        chats = cls.model.select()
+        if id:
+            chats = chats.where(cls.model.id == id)
+        if name:
+            chats = chats.where(cls.model.name == name)
+        chats = chats.where(
+              (cls.model.tenant_id == tenant_id)
+            & (cls.model.status == StatusEnum.VALID.value)
+        )
+        if desc:
+            chats = chats.order_by(cls.model.getter_by(orderby).desc())
+        else:
+            chats = chats.order_by(cls.model.getter_by(orderby).asc())
+
+        chats = chats.paginate(page_number, items_per_page)
+
+        return list(chats.dicts())
+
 
 class ConversationService(CommonService):
     model = Conversation
 
+    @classmethod
+    @DB.connection_context()
+    def get_list(cls,dialog_id,page_number, items_per_page, orderby, desc, id , name):
+        sessions = cls.model.select().where(cls.model.dialog_id ==dialog_id)
+        if id:
+            sessions = sessions.where(cls.model.id == id)
+        if name:
+            sessions = sessions.where(cls.model.name == name)
+        if desc:
+            sessions = sessions.order_by(cls.model.getter_by(orderby).desc())
+        else:
+            sessions = sessions.order_by(cls.model.getter_by(orderby).asc())
+
+        sessions = sessions.paginate(page_number, items_per_page)
+
+        return list(sessions.dicts())
+
 
 def message_fit_in(msg, max_length=4000):
     def count():
@@ -57,7 +98,8 @@ def message_fit_in(msg, max_length=4000):
         return c, msg
 
     msg_ = [m for m in msg[:-1] if m["role"] == "system"]
-    msg_.append(msg[-1])
+    if len(msg) > 1:
+        msg_.append(msg[-1])
     msg = msg_
     c = count()
     if c < max_length:
@@ -85,7 +127,7 @@ def llm_id2llm_type(llm_id):
         for llm in llm_factory["llm"]:
             if llm_id == llm["llm_name"]:
                 return llm["model_type"].strip(",")[-1]
-                
+
 
 def chat(dialog, messages, stream=True, **kwargs):
     assert messages[-1]["role"] == "user", "The last content of this conversation is not from user."
@@ -111,7 +153,7 @@ def chat(dialog, messages, stream=True, **kwargs):
         return {"answer": "**ERROR**: Knowledge bases use different embedding models.", "reference": []}
 
     is_kg = all([kb.parser_id == ParserType.KG for kb in kbs])
-    retr = retrievaler if not is_kg else kg_retrievaler
+    retr = settings.retrievaler if not is_kg else settings.kg_retrievaler
 
     questions = [m["content"] for m in messages if m["role"] == "user"][-3:]
     attachments = kwargs["doc_ids"].split(",") if "doc_ids" in kwargs else None
@@ -122,6 +164,9 @@ def chat(dialog, messages, stream=True, **kwargs):
                 attachments.extend(m["doc_ids"])
 
     embd_mdl = LLMBundle(dialog.tenant_id, LLMType.EMBEDDING, embd_nms[0])
+    if not embd_mdl:
+        raise LookupError("Embedding model(%s) not found" % embd_nms[0])
+
     if llm_id2llm_type(dialog.llm_id) == "image2text":
         chat_mdl = LLMBundle(dialog.tenant_id, LLMType.IMAGE2TEXT, dialog.llm_id)
     else:
@@ -134,7 +179,7 @@ def chat(dialog, messages, stream=True, **kwargs):
         tts_mdl = LLMBundle(dialog.tenant_id, LLMType.TTS)
     # try to use sql if field mapping is good to go
     if field_map:
-        chat_logger.info("Use SQL to retrieval:{}".format(questions[-1]))
+        logging.debug("Use SQL to retrieval:{}".format(questions[-1]))
         ans = use_sql(questions[-1], field_map, dialog.tenant_id, chat_mdl, prompt_config.get("quote", True))
         if ans:
             yield ans
@@ -153,6 +198,8 @@ def chat(dialog, messages, stream=True, **kwargs):
         questions = [full_question(dialog.tenant_id, dialog.llm_id, messages)]
     else:
         questions = questions[-1:]
+    refineQ_tm = timer()
+    keyword_tm = timer()
 
     rerank_mdl = None
     if dialog.rerank_id:
@@ -165,13 +212,16 @@ def chat(dialog, messages, stream=True, **kwargs):
     else:
         if prompt_config.get("keyword", False):
             questions[-1] += keyword_extraction(chat_mdl, questions[-1])
-        kbinfos = retr.retrieval(" ".join(questions), embd_mdl, dialog.tenant_id, dialog.kb_ids, 1, dialog.top_n,
+            keyword_tm = timer()
+
+        tenant_ids = list(set([kb.tenant_id for kb in kbs]))
+        kbinfos = retr.retrieval(" ".join(questions), embd_mdl, tenant_ids, dialog.kb_ids, 1, dialog.top_n,
                                         dialog.similarity_threshold,
                                         dialog.vector_similarity_weight,
                                         doc_ids=attachments,
                                         top=dialog.top_k, aggs=False, rerank_mdl=rerank_mdl)
     knowledges = [ck["content_with_weight"] for ck in kbinfos["chunks"]]
-    chat_logger.info(
+    logging.debug(
         "{}->{}".format(" ".join(questions), "\n->".join(knowledges)))
     retrieval_tm = timer()
 
@@ -189,6 +239,7 @@ def chat(dialog, messages, stream=True, **kwargs):
     used_token_count, msg = message_fit_in(msg, int(max_tokens * 0.97))
     assert len(msg) >= 2, f"message_fit_in has bug: {msg}"
     prompt = msg[0]["content"]
+    prompt += "\n\n### Query:\n%s" % " ".join(questions)
 
     if "max_tokens" in gen_conf:
         gen_conf["max_tokens"] = min(
@@ -221,7 +272,9 @@ def chat(dialog, messages, stream=True, **kwargs):
         if answer.lower().find("invalid key") >= 0 or answer.lower().find("invalid api") >= 0:
             answer += " Please set LLM API-Key in 'User Setting -> Model Providers -> API-Key'"
         done_tm = timer()
-        prompt += "\n\n### Elapsed\n  - Retrieval: %.1f ms\n  - LLM: %.1f ms"%((retrieval_tm-st)*1000, (done_tm-st)*1000)
+        prompt += "\n\n### Elapsed\n  - Refine Question: %.1f ms\n  - Keywords: %.1f ms\n  - Retrieval: %.1f ms\n  - LLM: %.1f ms" % (
+            (refineQ_tm - st) * 1000, (keyword_tm - refineQ_tm) * 1000, (retrieval_tm - keyword_tm) * 1000,
+            (done_tm - retrieval_tm) * 1000)
         return {"answer": answer, "reference": refs, "prompt": prompt}
 
     if stream:
@@ -240,7 +293,7 @@ def chat(dialog, messages, stream=True, **kwargs):
         yield decorate_answer(answer)
     else:
         answer = chat_mdl.chat(prompt, msg[1:], gen_conf)
-        chat_logger.info("User: {}|Assistant: {}".format(
+        logging.debug("User: {}|Assistant: {}".format(
             msg[-1]["content"], answer))
         res = decorate_answer(answer)
         res["audio_binary"] = tts(tts_mdl, answer)
@@ -268,8 +321,7 @@ def use_sql(question, field_map, tenant_id, chat_mdl, quota=True):
         nonlocal sys_prompt, user_promt, question, tried_times
         sql = chat_mdl.chat(sys_prompt, [{"role": "user", "content": user_promt}], {
             "temperature": 0.06})
-        print(user_promt, sql)
-        chat_logger.info(f"“{question}”==>{user_promt} get SQL: {sql}")
+        logging.debug(f"{question} ==> {user_promt} get SQL: {sql}")
         sql = re.sub(r"[\r\n]+", " ", sql.lower())
         sql = re.sub(r".*select ", "select ", sql.lower())
         sql = re.sub(r" +", " ", sql)
@@ -289,11 +341,9 @@ def use_sql(question, field_map, tenant_id, chat_mdl, quota=True):
                     flds.append(k)
                 sql = "select doc_id,docnm_kwd," + ",".join(flds) + sql[8:]
 
-        print(f"“{question}” get SQL(refined): {sql}")
-
-        chat_logger.info(f"“{question}” get SQL(refined): {sql}")
+        logging.debug(f"{question} get SQL(refined): {sql}")
         tried_times += 1
-        return retrievaler.sql_retrieval(sql, format="json"), sql
+        return settings.retrievaler.sql_retrieval(sql, format="json"), sql
 
     tbl, sql = get_table()
     if tbl is None:
@@ -320,10 +370,9 @@ def use_sql(question, field_map, tenant_id, chat_mdl, quota=True):
             question, sql, tbl["error"]
         )
         tbl, sql = get_table()
-        chat_logger.info("TRY it again: {}".format(sql))
+        logging.debug("TRY it again: {}".format(sql))
 
-    chat_logger.info("GET table: {}".format(tbl))
-    print(tbl)
+    logging.debug("GET table: {}".format(tbl))
     if tbl.get("error") or len(tbl["rows"]) == 0:
         return None
 
@@ -345,6 +394,7 @@ def use_sql(question, field_map, tenant_id, chat_mdl, quota=True):
     rows = ["|" +
             "|".join([rmSpace(str(r[i])) for i in clmn_idx]).replace("None", " ") +
             "|" for r in tbl["rows"]]
+    rows = [r for r in rows if re.sub(r"[ |]+", "", r)]
     if quota:
         rows = "\n".join([r + f" ##{ii}$$ |" for ii, r in enumerate(rows)])
     else:
@@ -352,7 +402,7 @@ def use_sql(question, field_map, tenant_id, chat_mdl, quota=True):
     rows = re.sub(r"T[0-9]{2}:[0-9]{2}:[0-9]{2}(\.[0-9]+Z)?\|", "|", rows)
 
     if not docid_idx or not docnm_idx:
-        chat_logger.warning("SQL missing field: " + sql)
+        logging.warning("SQL missing field: " + sql)
         return {
             "answer": "\n".join([clmns, line, rows]),
             "reference": {"chunks": [], "doc_aggs": []},
@@ -415,6 +465,58 @@ def rewrite(tenant_id, llm_id, question):
     return ans
 
 
+def keyword_extraction(chat_mdl, content, topn=3):
+    prompt = f"""
+Role: You're a text analyzer. 
+Task: extract the most important keywords/phrases of a given piece of text content.
+Requirements: 
+  - Summarize the text content, and give top {topn} important keywords/phrases.
+  - The keywords MUST be in language of the given piece of text content.
+  - The keywords are delimited by ENGLISH COMMA.
+  - Keywords ONLY in output.
+
+### Text Content 
+{content}
+
+"""
+    msg = [
+        {"role": "system", "content": prompt},
+        {"role": "user", "content": "Output: "}
+    ]
+    _, msg = message_fit_in(msg, chat_mdl.max_length)
+    kwd = chat_mdl.chat(prompt, msg[1:], {"temperature": 0.2})
+    if isinstance(kwd, tuple): kwd = kwd[0]
+    if kwd.find("**ERROR**") >=0: return ""
+    return kwd
+
+
+def question_proposal(chat_mdl, content, topn=3):
+    prompt = f"""
+Role: You're a text analyzer. 
+Task:  propose {topn} questions about a given piece of text content.
+Requirements: 
+  - Understand and summarize the text content, and propose top {topn} important questions.
+  - The questions SHOULD NOT have overlapping meanings.
+  - The questions SHOULD cover the main content of the text as much as possible.
+  - The questions MUST be in language of the given piece of text content.
+  - One question per line.
+  - Question ONLY in output.
+
+### Text Content 
+{content}
+
+"""
+    msg = [
+        {"role": "system", "content": prompt},
+        {"role": "user", "content": "Output: "}
+    ]
+    _, msg = message_fit_in(msg, chat_mdl.max_length)
+    kwd = chat_mdl.chat(prompt, msg[1:], {"temperature": 0.2})
+    if isinstance(kwd, tuple): kwd = kwd[0]
+    if kwd.find("**ERROR**") >= 0: return ""
+    return kwd
+
+
 def full_question(tenant_id, llm_id, messages):
     if llm_id2llm_type(llm_id) == "image2text":
         chat_mdl = LLMBundle(tenant_id, LLMType.IMAGE2TEXT, llm_id)
@@ -425,9 +527,16 @@ def full_question(tenant_id, llm_id, messages):
         if m["role"] not in ["user", "assistant"]: continue
         conv.append("{}: {}".format(m["role"].upper(), m["content"]))
     conv = "\n".join(conv)
+    today = datetime.date.today().isoformat()
+    yesterday = (datetime.date.today() - timedelta(days=1)).isoformat()
+    tomorrow = (datetime.date.today() + timedelta(days=1)).isoformat()
     prompt = f"""
 Role: A helpful assistant
-Task: Generate a full user question that would follow the conversation.
+
+Task and steps: 
+    1. Generate a full user question that would follow the conversation.
+    2. If the user's question involves relative date, you need to convert it into absolute date based on the current date, which is {today}. For example: 'yesterday' would be converted to {yesterday}.
+    
 Requirements & Restrictions:
   - Text generated MUST be in the same language of the original user's question.
   - If the user's latest question is completely, don't do anything, just return the original question.
@@ -456,6 +565,14 @@ User: What's her full name?
 ###############
 Output: What's the full name of Donald Trump's mother Mary Trump?
 
+------------
+# Example 3
+## Conversation
+USER: What's the weather today in London?
+ASSISTANT:  Cloudy.
+USER: What's about tomorrow in Rochester?
+###############
+Output: What's the weather in Rochester on {tomorrow}?
 ######################
 
 # Real Data
@@ -477,16 +594,17 @@ def tts(tts_mdl, text):
 
 def ask(question, kb_ids, tenant_id):
     kbs = KnowledgebaseService.get_by_ids(kb_ids)
+    tenant_ids = [kb.tenant_id for kb in kbs]
     embd_nms = list(set([kb.embd_id for kb in kbs]))
 
     is_kg = all([kb.parser_id == ParserType.KG for kb in kbs])
-    retr = retrievaler if not is_kg else kg_retrievaler
+    retr = settings.retrievaler if not is_kg else settings.kg_retrievaler
 
     embd_mdl = LLMBundle(tenant_id, LLMType.EMBEDDING, embd_nms[0])
     chat_mdl = LLMBundle(tenant_id, LLMType.CHAT)
     max_tokens = chat_mdl.max_length
 
-    kbinfos = retr.retrieval(question, embd_mdl, tenant_id, kb_ids, 1, 12, 0.1, 0.3, aggs=False)
+    kbinfos = retr.retrieval(question, embd_mdl, tenant_ids, kb_ids, 1, 12, 0.1, 0.3, aggs=False)
     knowledges = [ck["content_with_weight"] for ck in kbinfos["chunks"]]
 
     used_token_count = 0

api/db/services/document_service.py

@@ -13,32 +13,28 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import hashlib
 import json
-import os
 import random
 import re
-import traceback
 from concurrent.futures import ThreadPoolExecutor
 from copy import deepcopy
 from datetime import datetime
 from io import BytesIO
 
-from elasticsearch_dsl import Q
 from peewee import fn
 
 from api.db.db_utils import bulk_insert_into_db
-from api.settings import stat_logger
+from api import settings
 from api.utils import current_timestamp, get_format_time, get_uuid
-from api.utils.file_utils import get_project_base_directory
 from graphrag.mind_map_extractor import MindMapExtractor
 from rag.settings import SVR_QUEUE_NAME
-from rag.utils.es_conn import ELASTICSEARCH
 from rag.utils.storage_factory import STORAGE_IMPL
 from rag.nlp import search, rag_tokenizer
 
 from api.db import FileType, TaskStatus, ParserType, LLMType
-from api.db.db_models import DB, Knowledgebase, Tenant, Task
+from api.db.db_models import DB, Knowledgebase, Tenant, Task, UserTenant
 from api.db.db_models import Document
 from api.db.services.common_service import CommonService
 from api.db.services.knowledgebase_service import KnowledgebaseService
@@ -49,6 +45,31 @@ from rag.utils.redis_conn import REDIS_CONN
 class DocumentService(CommonService):
     model = Document
 
+    @classmethod
+    @DB.connection_context()
+    def get_list(cls, kb_id, page_number, items_per_page,
+                 orderby, desc, keywords, id, name):
+        docs = cls.model.select().where(cls.model.kb_id == kb_id)
+        if id:
+            docs = docs.where(
+                cls.model.id == id)
+        if name:
+            docs = docs.where(
+                cls.model.name == name
+            )
+        if keywords:
+            docs = docs.where(
+                fn.LOWER(cls.model.name).contains(keywords.lower())
+            )
+        if desc:
+            docs = docs.order_by(cls.model.getter_by(orderby).desc())
+        else:
+            docs = docs.order_by(cls.model.getter_by(orderby).asc())
+
+        docs = docs.paginate(page_number, items_per_page)
+        count = docs.count()
+        return list(docs.dicts()), count
+
     @classmethod
     @DB.connection_context()
     def get_by_kb_id(cls, kb_id, page_number, items_per_page,
@@ -70,35 +91,6 @@ class DocumentService(CommonService):
 
         return list(docs.dicts()), count
 
-    @classmethod
-    @DB.connection_context()
-    def list_documents_in_dataset(cls, dataset_id, offset, count, order_by, descend, keywords):
-        if keywords:
-            docs = cls.model.select().where(
-                (cls.model.kb_id == dataset_id),
-                (fn.LOWER(cls.model.name).contains(keywords.lower()))
-            )
-        else:
-            docs = cls.model.select().where(cls.model.kb_id == dataset_id)
-
-        total = docs.count()
-
-        if descend == 'True':
-            docs = docs.order_by(cls.model.getter_by(order_by).desc())
-        if descend == 'False':
-            docs = docs.order_by(cls.model.getter_by(order_by).asc())
-
-        docs = list(docs.dicts())
-        docs_length = len(docs)
-
-        if offset < 0 or offset > docs_length:
-            raise IndexError("Offset is out of the valid range.")
-
-        if count == -1:
-            return docs[offset:], total
-
-        return docs[offset:offset + count], total
-
     @classmethod
     @DB.connection_context()
     def insert(cls, doc):
@@ -116,8 +108,7 @@ class DocumentService(CommonService):
     @classmethod
     @DB.connection_context()
     def remove_document(cls, doc, tenant_id):
-        ELASTICSEARCH.deleteByQuery(
-                Q("match", doc_id=doc.id), idxnm=search.index_name(tenant_id))
+        settings.docStoreConn.delete({"doc_id": doc.id}, search.index_name(tenant_id), doc.kb_id)
         cls.clear_chunk_num(doc.id)
         return cls.delete_by_id(doc.id)
 
@@ -140,26 +131,27 @@ class DocumentService(CommonService):
             cls.model.update_time]
         docs = cls.model.select(*fields) \
             .join(Knowledgebase, on=(cls.model.kb_id == Knowledgebase.id)) \
-            .join(Tenant, on=(Knowledgebase.tenant_id == Tenant.id))\
+            .join(Tenant, on=(Knowledgebase.tenant_id == Tenant.id)) \
             .where(
-                cls.model.status == StatusEnum.VALID.value,
-                ~(cls.model.type == FileType.VIRTUAL.value),
-                cls.model.progress == 0,
-                cls.model.update_time >= current_timestamp() - 1000 * 600,
-                cls.model.run == TaskStatus.RUNNING.value)\
+            cls.model.status == StatusEnum.VALID.value,
+            ~(cls.model.type == FileType.VIRTUAL.value),
+            cls.model.progress == 0,
+            cls.model.update_time >= current_timestamp() - 1000 * 600,
+            cls.model.run == TaskStatus.RUNNING.value) \
             .order_by(cls.model.update_time.asc())
         return list(docs.dicts())
 
     @classmethod
     @DB.connection_context()
     def get_unfinished_docs(cls):
-        fields = [cls.model.id, cls.model.process_begin_at, cls.model.parser_config, cls.model.progress_msg, cls.model.run]
+        fields = [cls.model.id, cls.model.process_begin_at, cls.model.parser_config, cls.model.progress_msg,
+                  cls.model.run]
         docs = cls.model.select(*fields) \
             .where(
-                cls.model.status == StatusEnum.VALID.value,
-                ~(cls.model.type == FileType.VIRTUAL.value),
-                cls.model.progress < 1,
-                cls.model.progress > 0)
+            cls.model.status == StatusEnum.VALID.value,
+            ~(cls.model.type == FileType.VIRTUAL.value),
+            cls.model.progress < 1,
+            cls.model.progress > 0)
         return list(docs.dicts())
 
     @classmethod
@@ -174,12 +166,12 @@ class DocumentService(CommonService):
                 "Document not found which is supposed to be there")
         num = Knowledgebase.update(
             token_num=Knowledgebase.token_num +
-            token_num,
+                      token_num,
             chunk_num=Knowledgebase.chunk_num +
-            chunk_num).where(
+                      chunk_num).where(
             Knowledgebase.id == kb_id).execute()
         return num
-    
+
     @classmethod
     @DB.connection_context()
     def decrement_chunk_num(cls, doc_id, kb_id, token_num, chunk_num, duation):
@@ -192,13 +184,13 @@ class DocumentService(CommonService):
                 "Document not found which is supposed to be there")
         num = Knowledgebase.update(
             token_num=Knowledgebase.token_num -
-            token_num,
+                      token_num,
             chunk_num=Knowledgebase.chunk_num -
-            chunk_num
+                      chunk_num
         ).where(
             Knowledgebase.id == kb_id).execute()
         return num
-    
+
     @classmethod
     @DB.connection_context()
     def clear_chunk_num(cls, doc_id):
@@ -207,10 +199,10 @@ class DocumentService(CommonService):
 
         num = Knowledgebase.update(
             token_num=Knowledgebase.token_num -
-            doc.token_num,
+                      doc.token_num,
             chunk_num=Knowledgebase.chunk_num -
-            doc.chunk_num,
-            doc_num=Knowledgebase.doc_num-1
+                      doc.chunk_num,
+            doc_num=Knowledgebase.doc_num - 1
         ).where(
             Knowledgebase.id == doc.kb_id).execute()
         return num
@@ -221,13 +213,22 @@ class DocumentService(CommonService):
         docs = cls.model.select(
             Knowledgebase.tenant_id).join(
             Knowledgebase, on=(
-                Knowledgebase.id == cls.model.kb_id)).where(
-                cls.model.id == doc_id, Knowledgebase.status == StatusEnum.VALID.value)
+                    Knowledgebase.id == cls.model.kb_id)).where(
+            cls.model.id == doc_id, Knowledgebase.status == StatusEnum.VALID.value)
         docs = docs.dicts()
         if not docs:
             return
         return docs[0]["tenant_id"]
 
+    @classmethod
+    @DB.connection_context()
+    def get_knowledgebase_id(cls, doc_id):
+        docs = cls.model.select(cls.model.kb_id).where(cls.model.id == doc_id)
+        docs = docs.dicts()
+        if not docs:
+            return
+        return docs[0]["kb_id"]
+
     @classmethod
     @DB.connection_context()
     def get_tenant_id_by_name(cls, name):
@@ -241,19 +242,46 @@ class DocumentService(CommonService):
             return
         return docs[0]["tenant_id"]
 
+    @classmethod
+    @DB.connection_context()
+    def accessible(cls, doc_id, user_id):
+        docs = cls.model.select(
+            cls.model.id).join(
+            Knowledgebase, on=(
+                    Knowledgebase.id == cls.model.kb_id)
+        ).join(UserTenant, on=(UserTenant.tenant_id == Knowledgebase.tenant_id)
+               ).where(cls.model.id == doc_id, UserTenant.user_id == user_id).paginate(0, 1)
+        docs = docs.dicts()
+        if not docs:
+            return False
+        return True
+
+    @classmethod
+    @DB.connection_context()
+    def accessible4deletion(cls, doc_id, user_id):
+        docs = cls.model.select(
+            cls.model.id).join(
+            Knowledgebase, on=(
+                    Knowledgebase.id == cls.model.kb_id)
+        ).where(cls.model.id == doc_id, Knowledgebase.created_by == user_id).paginate(0, 1)
+        docs = docs.dicts()
+        if not docs:
+            return False
+        return True
+
     @classmethod
     @DB.connection_context()
     def get_embd_id(cls, doc_id):
         docs = cls.model.select(
             Knowledgebase.embd_id).join(
             Knowledgebase, on=(
-                Knowledgebase.id == cls.model.kb_id)).where(
-                cls.model.id == doc_id, Knowledgebase.status == StatusEnum.VALID.value)
+                    Knowledgebase.id == cls.model.kb_id)).where(
+            cls.model.id == doc_id, Knowledgebase.status == StatusEnum.VALID.value)
         docs = docs.dicts()
         if not docs:
             return
         return docs[0]["embd_id"]
-    
+
     @classmethod
     @DB.connection_context()
     def get_doc_id_by_doc_name(cls, doc_name):
@@ -268,7 +296,7 @@ class DocumentService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_thumbnails(cls, docids):
-        fields = [cls.model.id, cls.model.thumbnail]
+        fields = [cls.model.id, cls.model.kb_id, cls.model.thumbnail]
         return list(cls.model.select(
             *fields).where(cls.model.id.in_(docids)).dicts())
 
@@ -289,6 +317,7 @@ class DocumentService(CommonService):
                     dfs_update(old[k], v)
                 else:
                     old[k] = v
+
         dfs_update(d.parser_config, config)
         cls.update_by_id(id, {"parser_config": d.parser_config})
 
@@ -305,7 +334,7 @@ class DocumentService(CommonService):
     def begin2parse(cls, docid):
         cls.update_by_id(
             docid, {"progress": random.random() * 1 / 100.,
-                    "progress_msg": "Task dispatched...",
+                    "progress_msg": "Task is queued...",
                     "process_begin_at": get_format_time()
                     })
 
@@ -323,7 +352,7 @@ class DocumentService(CommonService):
                 finished = True
                 bad = 0
                 e, doc = DocumentService.get_by_id(d["id"])
-                status = doc.run#TaskStatus.RUNNING.value
+                status = doc.run  # TaskStatus.RUNNING.value
                 for t in tsks:
                     if 0 <= t.progress < 1:
                         finished = False
@@ -337,9 +366,10 @@ class DocumentService(CommonService):
                     prg = -1
                     status = TaskStatus.FAIL.value
                 elif finished:
-                    if d["parser_config"].get("raptor", {}).get("use_raptor") and d["progress_msg"].lower().find(" raptor")<0:
+                    if d["parser_config"].get("raptor", {}).get("use_raptor") and d["progress_msg"].lower().find(
+                            " raptor") < 0:
                         queue_raptor_tasks(d)
-                        prg *= 0.98
+                        prg = 0.98 * len(tsks) / (len(tsks) + 1)
                         msg.append("------ RAPTOR -------")
                     else:
                         status = TaskStatus.DONE.value
@@ -356,7 +386,8 @@ class DocumentService(CommonService):
                     info["progress_msg"] = msg
                 cls.update_by_id(d["id"], info)
             except Exception as e:
-                stat_logger.error("fetch task exception:" + str(e))
+                if str(e).find("'0'") < 0:
+                    logging.exception("fetch task exception")
 
     @classmethod
     @DB.connection_context()
@@ -364,14 +395,13 @@ class DocumentService(CommonService):
         return len(cls.model.select(cls.model.id).where(
             cls.model.kb_id == kb_id).dicts())
 
-
     @classmethod
     @DB.connection_context()
     def do_cancel(cls, doc_id):
         try:
             _, doc = DocumentService.get_by_id(doc_id)
             return doc.run == TaskStatus.CANCEL.value or doc.progress < 0
-        except Exception as e:
+        except Exception:
             pass
         return False
 
@@ -384,7 +414,7 @@ def queue_raptor_tasks(doc):
             "doc_id": doc["id"],
             "from_page": 0,
             "to_page": -1,
-            "progress_msg": "Start to do RAPTOR (Recursive Abstractive Processing For Tree-Organized Retrieval)."
+            "progress_msg": "Start to do RAPTOR (Recursive Abstractive Processing for Tree-Organized Retrieval)."
         }
 
     task = new_task()
@@ -412,11 +442,6 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
     if not e:
         raise LookupError("Can't find this knowledgebase!")
 
-    idxnm = search.index_name(kb.tenant_id)
-    if not ELASTICSEARCH.indexExist(idxnm):
-        ELASTICSEARCH.createIdx(idxnm, json.load(
-            open(os.path.join(get_project_base_directory(), "conf", "mapping.json"), "r")))
-
     embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING, llm_name=kb.embd_id, lang=kb.language)
 
     err, files = FileService.upload_document(kb, file_objs, user_id)
@@ -460,7 +485,7 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
             md5 = hashlib.md5()
             md5.update((ck["content_with_weight"] +
                         str(d["doc_id"])).encode("utf-8"))
-            d["_id"] = md5.hexdigest()
+            d["id"] = md5.hexdigest()
             d["create_time"] = str(datetime.now()).replace("T", " ")[:19]
             d["create_timestamp_flt"] = datetime.now().timestamp()
             if not d.get("image"):
@@ -473,9 +498,9 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
             else:
                 d["image"].save(output_buffer, format='JPEG')
 
-            STORAGE_IMPL.put(kb.id, d["_id"], output_buffer.getvalue())
-            d["img_id"] = "{}-{}".format(kb.id, d["_id"])
-            del d["image"]
+            STORAGE_IMPL.put(kb.id, d["id"], output_buffer.getvalue())
+            d["img_id"] = "{}-{}".format(kb.id, d["id"])
+            d.pop("image", None)
             docs.append(d)
 
     parser_ids = {d["id"]: d["parser_id"] for d, _ in files}
@@ -494,6 +519,9 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
             token_counts[doc_id] += c
         return vects
 
+    idxnm = search.index_name(kb.tenant_id)
+    try_create_idx = True
+
     _, tenant = TenantService.get_by_id(kb.tenant_id)
     llm_bdl = LLMBundle(kb.tenant_id, LLMType.CHAT, tenant.llm_id)
     for doc_id in docids:
@@ -516,7 +544,7 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
                     "knowledge_graph_kwd": "mind_map"
                 })
             except Exception as e:
-                stat_logger.error("Mind map generation error:", traceback.format_exc())
+                logging.exception("Mind map generation error")
 
         vects = embedding(doc_id, [c["content_with_weight"] for c in cks])
         assert len(cks) == len(vects)
@@ -524,9 +552,13 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
             v = vects[i]
             d["q_%d_vec" % len(v)] = v
         for b in range(0, len(cks), es_bulk_size):
-            ELASTICSEARCH.bulk(cks[b:b + es_bulk_size], idxnm)
+            if try_create_idx:
+                if not settings.docStoreConn.indexExist(idxnm, kb_id):
+                    settings.docStoreConn.createIdx(idxnm, kb_id, len(vects[0]))
+                try_create_idx = False
+            settings.docStoreConn.insert(cks[b:b + es_bulk_size], idxnm, kb_id)
 
         DocumentService.increment_chunk_num(
             doc_id, kb.id, token_counts[doc_id], chunk_counts[doc_id], 0)
 
-    return [d["id"] for d,_ in files]
+    return [d["id"] for d, _ in files]

api/db/services/file_service.py

@@ -13,8 +13,11 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import re
 import os
+from concurrent.futures import ThreadPoolExecutor
+
 from flask_login import current_user
 from peewee import fn
 
@@ -26,7 +29,7 @@ from api.db.services.common_service import CommonService
 from api.db.services.document_service import DocumentService
 from api.db.services.file2document_service import File2DocumentService
 from api.utils import get_uuid
-from api.utils.file_utils import filename_type, thumbnail
+from api.utils.file_utils import filename_type, thumbnail_img
 from rag.utils.storage_factory import STORAGE_IMPL
 
 
@@ -272,8 +275,8 @@ class FileService(CommonService):
                 cls.delete_folder_by_pf_id(user_id, file.id)
             return cls.model.delete().where((cls.model.tenant_id == user_id)
                                             & (cls.model.id == folder_id)).execute(),
-        except Exception as e:
-            print(e)
+        except Exception:
+            logging.exception("delete_folder_by_pf_id")
             raise RuntimeError("Database error (File retrieval)!")
 
     @classmethod
@@ -321,8 +324,8 @@ class FileService(CommonService):
     def move_file(cls, file_ids, folder_id):
         try:
             cls.filter_update((cls.model.id << file_ids, ), { 'parent_id': folder_id })
-        except Exception as e:
-            print(e)
+        except Exception:
+            logging.exception("move_file")
             raise RuntimeError("Database error (File move)!")
 
     @classmethod
@@ -354,8 +357,17 @@ class FileService(CommonService):
                     location += "_"
                 blob = file.read()
                 STORAGE_IMPL.put(kb.id, location, blob)
+
+                doc_id = get_uuid()
+
+                img = thumbnail_img(filename, blob)
+                thumbnail_location = ''
+                if img is not None:
+                    thumbnail_location = f'thumbnail_{doc_id}.png'
+                    STORAGE_IMPL.put(kb.id, thumbnail_location, img)
+
                 doc = {
-                    "id": get_uuid(),
+                    "id": doc_id,
                     "kb_id": kb.id,
                     "parser_id": self.get_parser(filetype, filename, kb.parser_id),
                     "parser_config": kb.parser_config,
@@ -364,7 +376,7 @@ class FileService(CommonService):
                     "name": filename,
                     "location": location,
                     "size": len(blob),
-                    "thumbnail": thumbnail(filename, blob)
+                    "thumbnail": thumbnail_location
                 }
                 DocumentService.insert(doc)
 
@@ -375,6 +387,41 @@ class FileService(CommonService):
 
         return err, files
 
+    @staticmethod
+    def parse_docs(file_objs, user_id):
+        from rag.app import presentation, picture, naive, audio, email
+
+        def dummy(prog=None, msg=""):
+            pass
+
+        FACTORY = {
+            ParserType.PRESENTATION.value: presentation,
+            ParserType.PICTURE.value: picture,
+            ParserType.AUDIO.value: audio,
+            ParserType.EMAIL.value: email
+        }
+        parser_config = {"chunk_token_num": 16096, "delimiter": "\n!?;。；！？", "layout_recognize": False}
+        exe = ThreadPoolExecutor(max_workers=12)
+        threads = []
+        for file in file_objs:
+            kwargs = {
+                "lang": "English",
+                "callback": dummy,
+                "parser_config": parser_config,
+                "from_page": 0,
+                "to_page": 100000,
+                "tenant_id": user_id
+            }
+            filetype = filename_type(file.filename)
+            blob = file.read()
+            threads.append(exe.submit(FACTORY.get(FileService.get_parser(filetype, file.filename, ""), naive).chunk, file.filename, blob, **kwargs))
+
+        res = []
+        for th in threads:
+            res.append("\n".join([ck["content_with_weight"] for ck in th.result()]))
+
+        return "\n\n".join(res)
+
     @staticmethod
     def get_parser(doc_type, filename, default):
         if doc_type == FileType.VISUAL:

api/db/services/knowledgebase_service.py

@@ -14,21 +14,47 @@
 #  limitations under the License.
 #
 from api.db import StatusEnum, TenantPermission
-from api.db.db_models import Knowledgebase, DB, Tenant
+from api.db.db_models import Knowledgebase, DB, Tenant, User, UserTenant,Document
 from api.db.services.common_service import CommonService
 
 
 class KnowledgebaseService(CommonService):
     model = Knowledgebase
 
+    @classmethod
+    @DB.connection_context()
+    def list_documents_by_ids(cls,kb_ids):
+        doc_ids=cls.model.select(Document.id.alias("document_id")).join(Document,on=(cls.model.id == Document.kb_id)).where(
+            cls.model.id.in_(kb_ids)
+        )
+        doc_ids =list(doc_ids.dicts())
+        doc_ids = [doc["document_id"] for doc in doc_ids]
+        return doc_ids
+
     @classmethod
     @DB.connection_context()
     def get_by_tenant_ids(cls, joined_tenant_ids, user_id,
                           page_number, items_per_page, orderby, desc):
-        kbs = cls.model.select().where(
+        fields = [
+            cls.model.id,
+            cls.model.avatar,
+            cls.model.name,
+            cls.model.language,
+            cls.model.description,
+            cls.model.permission,
+            cls.model.doc_num,
+            cls.model.token_num,
+            cls.model.chunk_num,
+            cls.model.parser_id,
+            cls.model.embd_id,
+            User.nickname,
+            User.avatar.alias('tenant_avatar'),
+            cls.model.update_time
+        ]
+        kbs = cls.model.select(*fields).join(User, on=(cls.model.tenant_id == User.id)).where(
             ((cls.model.tenant_id.in_(joined_tenant_ids) & (cls.model.permission ==
                                                             TenantPermission.TEAM.value)) | (
-                         cls.model.tenant_id == user_id))
+                     cls.model.tenant_id == user_id))
             & (cls.model.status == StatusEnum.VALID.value)
         )
         if desc:
@@ -42,35 +68,20 @@ class KnowledgebaseService(CommonService):
 
     @classmethod
     @DB.connection_context()
-    def get_by_tenant_ids_by_offset(cls, joined_tenant_ids, user_id, offset, count, orderby, desc):
-        kbs = cls.model.select().where(
-            ((cls.model.tenant_id.in_(joined_tenant_ids) & (cls.model.permission ==
-                                                            TenantPermission.TEAM.value)) | (
-                     cls.model.tenant_id == user_id))
-            & (cls.model.status == StatusEnum.VALID.value)
-        )
-        if desc:
-            kbs = kbs.order_by(cls.model.getter_by(orderby).desc())
-        else:
-            kbs = kbs.order_by(cls.model.getter_by(orderby).asc())
-
-        kbs = list(kbs.dicts())
-
-        kbs_length = len(kbs)
-        if offset < 0 or offset > kbs_length:
-            raise IndexError("Offset is out of the valid range.")
-
-        if count == -1:
-            return kbs[offset:]
-
-        return kbs[offset:offset+count]
+    def get_kb_ids(cls, tenant_id):
+        fields = [
+            cls.model.id,
+        ]
+        kbs = cls.model.select(*fields).where(cls.model.tenant_id == tenant_id)
+        kb_ids = [kb.id for kb in kbs]
+        return kb_ids
 
     @classmethod
     @DB.connection_context()
     def get_detail(cls, kb_id):
         fields = [
             cls.model.id,
-            #Tenant.embd_id,
+            # Tenant.embd_id,
             cls.model.embd_id,
             cls.model.avatar,
             cls.model.name,
@@ -83,14 +94,14 @@ class KnowledgebaseService(CommonService):
             cls.model.parser_id,
             cls.model.parser_config]
         kbs = cls.model.select(*fields).join(Tenant, on=(
-                    (Tenant.id == cls.model.tenant_id) & (Tenant.status == StatusEnum.VALID.value))).where(
+                (Tenant.id == cls.model.tenant_id) & (Tenant.status == StatusEnum.VALID.value))).where(
             (cls.model.id == kb_id),
             (cls.model.status == StatusEnum.VALID.value)
         )
         if not kbs:
             return
         d = kbs[0].to_dict()
-        #d["embd_id"] = kbs[0].tenant.embd_id
+        # d["embd_id"] = kbs[0].tenant.embd_id
         return d
 
     @classmethod
@@ -142,3 +153,65 @@ class KnowledgebaseService(CommonService):
     @DB.connection_context()
     def get_all_ids(cls):
         return [m["id"] for m in cls.model.select(cls.model.id).dicts()]
+
+    @classmethod
+    @DB.connection_context()
+    def get_list(cls, joined_tenant_ids, user_id,
+                 page_number, items_per_page, orderby, desc, id, name):
+        kbs = cls.model.select()
+        if id:
+            kbs = kbs.where(cls.model.id == id)
+        if name:
+            kbs = kbs.where(cls.model.name == name)
+        kbs = kbs.where(
+            ((cls.model.tenant_id.in_(joined_tenant_ids) & (cls.model.permission ==
+                                                            TenantPermission.TEAM.value)) | (
+                     cls.model.tenant_id == user_id))
+            & (cls.model.status == StatusEnum.VALID.value)
+        )
+        if desc:
+            kbs = kbs.order_by(cls.model.getter_by(orderby).desc())
+        else:
+            kbs = kbs.order_by(cls.model.getter_by(orderby).asc())
+
+        kbs = kbs.paginate(page_number, items_per_page)
+
+        return list(kbs.dicts())
+
+    @classmethod
+    @DB.connection_context()
+    def accessible(cls, kb_id, user_id):
+        docs = cls.model.select(
+            cls.model.id).join(UserTenant, on=(UserTenant.tenant_id == Knowledgebase.tenant_id)
+            ).where(cls.model.id == kb_id, UserTenant.user_id == user_id).paginate(0, 1)
+        docs = docs.dicts()
+        if not docs:
+            return False
+        return True
+
+    @classmethod
+    @DB.connection_context()
+    def get_kb_by_id(cls, kb_id, user_id):
+        kbs = cls.model.select().join(UserTenant, on=(UserTenant.tenant_id == Knowledgebase.tenant_id)
+            ).where(cls.model.id == kb_id, UserTenant.user_id == user_id).paginate(0, 1)
+        kbs = kbs.dicts()
+        return list(kbs)
+
+    @classmethod
+    @DB.connection_context()
+    def get_kb_by_name(cls, kb_name, user_id):
+        kbs = cls.model.select().join(UserTenant, on=(UserTenant.tenant_id == Knowledgebase.tenant_id)
+            ).where(cls.model.name == kb_name, UserTenant.user_id == user_id).paginate(0, 1)
+        kbs = kbs.dicts()
+        return list(kbs)
+
+    @classmethod
+    @DB.connection_context()
+    def accessible4deletion(cls, kb_id, user_id):
+        docs = cls.model.select(
+            cls.model.id).where(cls.model.id == kb_id, cls.model.created_by == user_id).paginate(0, 1)
+        docs = docs.dicts()
+        if not docs:
+            return False
+        return True
+

api/db/services/llm_service.py

@@ -13,8 +13,8 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 from api.db.services.user_service import TenantService
-from api.settings import database_logger
 from rag.llm import EmbeddingModel, CvModel, ChatModel, RerankModel, Seq2txtModel, TTSModel
 from api.db import LLMType
 from api.db.db_models import DB
@@ -133,7 +133,8 @@ class TenantLLMService(CommonService):
             if model_config["llm_factory"] not in Seq2txtModel:
                 return
             return Seq2txtModel[model_config["llm_factory"]](
-                model_config["api_key"], model_config["llm_name"], lang,
+                key=model_config["api_key"], model_name=model_config["llm_name"],
+                lang=lang,
                 base_url=model_config["api_base"]
             )
         if llm_type == LLMType.TTS:
@@ -167,11 +168,13 @@ class TenantLLMService(CommonService):
         else:
             assert False, "LLM type error"
 
+        llm_name = mdlnm.split("@")[0] if "@" in mdlnm else mdlnm
+
         num = 0
         try:
-            for u in cls.query(tenant_id=tenant_id, llm_name=mdlnm):
+            for u in cls.query(tenant_id=tenant_id, llm_name=llm_name):
                 num += cls.model.update(used_tokens=u.used_tokens + used_tokens)\
-                    .where(cls.model.tenant_id == tenant_id, cls.model.llm_name == mdlnm)\
+                    .where(cls.model.tenant_id == tenant_id, cls.model.llm_name == llm_name)\
                     .execute()
         except Exception as e:
             pass
@@ -195,7 +198,7 @@ class LLMBundle(object):
         self.llm_name = llm_name
         self.mdl = TenantLLMService.model_instance(
             tenant_id, llm_type, llm_name, lang=lang)
-        assert self.mdl, "Can't find mole for {}/{}/{}".format(
+        assert self.mdl, "Can't find model for {}/{}/{}".format(
             tenant_id, llm_type, llm_name)
         self.max_length = 8192
         for lm in LLMService.query(llm_name=llm_name):
@@ -206,40 +209,40 @@ class LLMBundle(object):
         emd, used_tokens = self.mdl.encode(texts, batch_size)
         if not TenantLLMService.increase_usage(
                 self.tenant_id, self.llm_type, used_tokens):
-            database_logger.error(
-                "Can't update token usage for {}/EMBEDDING".format(self.tenant_id))
+            logging.error(
+                "LLMBundle.encode can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens))
         return emd, used_tokens
 
     def encode_queries(self, query: str):
         emd, used_tokens = self.mdl.encode_queries(query)
         if not TenantLLMService.increase_usage(
                 self.tenant_id, self.llm_type, used_tokens):
-            database_logger.error(
-                "Can't update token usage for {}/EMBEDDING".format(self.tenant_id))
+            logging.error(
+                "LLMBundle.encode_queries can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens))
         return emd, used_tokens
 
     def similarity(self, query: str, texts: list):
         sim, used_tokens = self.mdl.similarity(query, texts)
         if not TenantLLMService.increase_usage(
                 self.tenant_id, self.llm_type, used_tokens):
-            database_logger.error(
-                "Can't update token usage for {}/RERANK".format(self.tenant_id))
+            logging.error(
+                "LLMBundle.similarity can't update token usage for {}/RERANK used_tokens: {}".format(self.tenant_id, used_tokens))
         return sim, used_tokens
 
     def describe(self, image, max_tokens=300):
         txt, used_tokens = self.mdl.describe(image, max_tokens)
         if not TenantLLMService.increase_usage(
                 self.tenant_id, self.llm_type, used_tokens):
-            database_logger.error(
-                "Can't update token usage for {}/IMAGE2TEXT".format(self.tenant_id))
+            logging.error(
+                "LLMBundle.describe can't update token usage for {}/IMAGE2TEXT used_tokens: {}".format(self.tenant_id, used_tokens))
         return txt
 
     def transcription(self, audio):
         txt, used_tokens = self.mdl.transcription(audio)
         if not TenantLLMService.increase_usage(
                 self.tenant_id, self.llm_type, used_tokens):
-            database_logger.error(
-                "Can't update token usage for {}/SEQUENCE2TXT".format(self.tenant_id))
+            logging.error(
+                "LLMBundle.transcription can't update token usage for {}/SEQUENCE2TXT used_tokens: {}".format(self.tenant_id, used_tokens))
         return txt
 
     def tts(self, text):
@@ -247,17 +250,17 @@ class LLMBundle(object):
             if isinstance(chunk,int):
                 if not TenantLLMService.increase_usage(
                     self.tenant_id, self.llm_type, chunk, self.llm_name):
-                        database_logger.error(
-                            "Can't update token usage for {}/TTS".format(self.tenant_id))
+                        logging.error(
+                            "LLMBundle.tts can't update token usage for {}/TTS".format(self.tenant_id))
                 return
             yield chunk     
 
     def chat(self, system, history, gen_conf):
         txt, used_tokens = self.mdl.chat(system, history, gen_conf)
-        if not TenantLLMService.increase_usage(
+        if isinstance(txt, int) and not TenantLLMService.increase_usage(
                 self.tenant_id, self.llm_type, used_tokens, self.llm_name):
-            database_logger.error(
-                "Can't update token usage for {}/CHAT".format(self.tenant_id))
+            logging.error(
+                "LLMBundle.chat can't update token usage for {}/CHAT llm_name: {}, used_tokens: {}".format(self.tenant_id, self.llm_name, used_tokens))
         return txt
 
     def chat_streamly(self, system, history, gen_conf):
@@ -265,7 +268,7 @@ class LLMBundle(object):
             if isinstance(txt, int):
                 if not TenantLLMService.increase_usage(
                         self.tenant_id, self.llm_type, txt, self.llm_name):
-                    database_logger.error(
-                        "Can't update token usage for {}/CHAT".format(self.tenant_id))
+                    logging.error(
+                        "LLMBundle.chat_streamly can't update token usage for {}/CHAT llm_name: {}, content: {}".format(self.tenant_id, self.llm_name, txt))
                 return
             yield txt

api/db/services/task_service.py

@@ -36,7 +36,7 @@ class TaskService(CommonService):
 
     @classmethod
     @DB.connection_context()
-    def get_tasks(cls, task_id):
+    def get_task(cls, task_id):
         fields = [
             cls.model.id,
             cls.model.doc_id,
@@ -63,7 +63,7 @@ class TaskService(CommonService):
             .join(Tenant, on=(Knowledgebase.tenant_id == Tenant.id)) \
             .where(cls.model.id == task_id)
         docs = list(docs.dicts())
-        if not docs: return []
+        if not docs: return None
 
         msg = "\nTask has been received."
         prog = random.random() / 10.
@@ -77,9 +77,9 @@ class TaskService(CommonService):
                          ).where(
             cls.model.id == docs[0]["id"]).execute()
 
-        if docs[0]["retry_count"] >= 3: return []
+        if docs[0]["retry_count"] >= 3: return None
 
-        return docs
+        return docs[0]
 
     @classmethod
     @DB.connection_context()
@@ -108,7 +108,7 @@ class TaskService(CommonService):
             task = cls.model.get_by_id(id)
             _, doc = DocumentService.get_by_id(task.doc_id)
             return doc.run == TaskStatus.CANCEL.value or doc.progress < 0
-        except Exception as e:
+        except Exception:
             pass
         return False
 

api/db/services/user_service.py

@@ -87,7 +87,7 @@ class TenantService(CommonService):
 
     @classmethod
     @DB.connection_context()
-    def get_by_user_id(cls, user_id):
+    def get_info_by(cls, user_id):
         fields = [
             cls.model.id.alias("tenant_id"),
             cls.model.name,
@@ -100,7 +100,7 @@ class TenantService(CommonService):
             cls.model.parser_ids,
             UserTenant.role]
         return list(cls.model.select(*fields)
-                    .join(UserTenant, on=((cls.model.id == UserTenant.tenant_id) & (UserTenant.user_id == user_id) & (UserTenant.status == StatusEnum.VALID.value)))
+                    .join(UserTenant, on=((cls.model.id == UserTenant.tenant_id) & (UserTenant.user_id == user_id) & (UserTenant.status == StatusEnum.VALID.value) & (UserTenant.role == UserTenantRole.OWNER)))
                     .where(cls.model.status == StatusEnum.VALID.value).dicts())
 
     @classmethod
@@ -115,7 +115,7 @@ class TenantService(CommonService):
             cls.model.img2txt_id,
             UserTenant.role]
         return list(cls.model.select(*fields)
-                    .join(UserTenant, on=((cls.model.id == UserTenant.tenant_id) & (UserTenant.user_id == user_id) & (UserTenant.status == StatusEnum.VALID.value) & (UserTenant.role == UserTenantRole.NORMAL.value)))
+                    .join(UserTenant, on=((cls.model.id == UserTenant.tenant_id) & (UserTenant.user_id == user_id) & (UserTenant.status == StatusEnum.VALID.value) & (UserTenant.role == UserTenantRole.NORMAL)))
                     .where(cls.model.status == StatusEnum.VALID.value).dicts())
 
     @classmethod
@@ -143,9 +143,8 @@ class UserTenantService(CommonService):
     def get_by_tenant_id(cls, tenant_id):
         fields = [
             cls.model.user_id,
-            cls.model.tenant_id,
-            cls.model.role,
             cls.model.status,
+            cls.model.role,
             User.nickname,
             User.email,
             User.avatar,
@@ -153,8 +152,24 @@ class UserTenantService(CommonService):
             User.is_active,
             User.is_anonymous,
             User.status,
+            User.update_date,
             User.is_superuser]
         return list(cls.model.select(*fields)
-                    .join(User, on=((cls.model.user_id == User.id) & (cls.model.status == StatusEnum.VALID.value)))
+                    .join(User, on=((cls.model.user_id == User.id) & (cls.model.status == StatusEnum.VALID.value) & (cls.model.role != UserTenantRole.OWNER)))
                     .where(cls.model.tenant_id == tenant_id)
-                    .dicts())
+                    .dicts())
+
+    @classmethod
+    @DB.connection_context()
+    def get_tenants_by_user_id(cls, user_id):
+        fields = [
+            cls.model.tenant_id,
+            cls.model.role,
+            User.nickname,
+            User.email,
+            User.avatar,
+            User.update_date
+        ]
+        return list(cls.model.select(*fields)
+                    .join(User, on=((cls.model.tenant_id == User.id) & (UserTenant.user_id == user_id) & (UserTenant.status == StatusEnum.VALID.value)))
+                    .where(cls.model.status == StatusEnum.VALID.value).dicts())

api/ragflow_server.py

@@ -14,7 +14,21 @@
 #  limitations under the License.
 #
 
+# from beartype import BeartypeConf
+# from beartype.claw import beartype_all  # <-- you didn't sign up for this
+# beartype_all(conf=BeartypeConf(violation_type=UserWarning))    # <-- emit warnings from all code
+
 import logging
+from api.utils.log_utils import initRootLogger
+initRootLogger("ragflow_server")
+for module in ["pdfminer"]:
+    module_logger = logging.getLogger(module)
+    module_logger.setLevel(logging.WARNING)
+for module in ["peewee"]:
+    module_logger = logging.getLogger(module)
+    module_logger.handlers.clear()
+    module_logger.propagate = True
+
 import os
 import signal
 import sys
@@ -23,77 +37,84 @@ import traceback
 from concurrent.futures import ThreadPoolExecutor
 
 from werkzeug.serving import run_simple
+from api import settings
 from api.apps import app
 from api.db.runtime_config import RuntimeConfig
 from api.db.services.document_service import DocumentService
-from api.settings import (
-    HOST, HTTP_PORT, access_logger, database_logger, stat_logger,
-)
 from api import utils
 
 from api.db.db_models import init_database_tables as init_web_db
 from api.db.init_data import init_web_data
-from api.versions import get_versions
+from api.versions import get_ragflow_version
+from api.utils import show_configs
 
 
 def update_progress():
     while True:
-        time.sleep(1)
+        time.sleep(3)
         try:
             DocumentService.update_progress()
-        except Exception as e:
-            stat_logger.error("update_progress exception:" + str(e))
+        except Exception:
+            logging.exception("update_progress exception")
 
 
 if __name__ == '__main__':
-    print(r"""
+    logging.info(r"""
         ____   ___    ______ ______ __               
        / __ \ /   |  / ____// ____// /____  _      __
       / /_/ // /| | / / __ / /_   / // __ \| | /| / /
      / _, _// ___ |/ /_/ // __/  / // /_/ /| |/ |/ / 
     /_/ |_|/_/  |_|\____//_/    /_/ \____/ |__/|__/                             
 
-    """, flush=True)
-    stat_logger.info(
+    """)
+    logging.info(
+        f'RAGFlow version: {get_ragflow_version()}'
+    )
+    logging.info(
         f'project base: {utils.file_utils.get_project_base_directory()}'
     )
+    show_configs()
+    settings.init_settings()
 
     # init db
     init_web_db()
     init_web_data()
     # init runtime config
     import argparse
+
     parser = argparse.ArgumentParser()
-    parser.add_argument('--version', default=False, help="rag flow version", action='store_true')
-    parser.add_argument('--debug', default=False, help="debug mode", action='store_true')
+    parser.add_argument(
+        "--version", default=False, help="RAGFlow version", action="store_true"
+    )
+    parser.add_argument(
+        "--debug", default=False, help="debug mode", action="store_true"
+    )
     args = parser.parse_args()
     if args.version:
-        print(get_versions())
+        print(get_ragflow_version())
         sys.exit(0)
 
     RuntimeConfig.DEBUG = args.debug
     if RuntimeConfig.DEBUG:
-        stat_logger.info("run on debug mode")
+        logging.info("run on debug mode")
 
     RuntimeConfig.init_env()
-    RuntimeConfig.init_config(JOB_SERVER_HOST=HOST, HTTP_PORT=HTTP_PORT)
+    RuntimeConfig.init_config(JOB_SERVER_HOST=settings.HOST_IP, HTTP_PORT=settings.HOST_PORT)
 
-    peewee_logger = logging.getLogger('peewee')
-    peewee_logger.propagate = False
-    # rag_arch.common.log.ROpenHandler
-    peewee_logger.addHandler(database_logger.handlers[0])
-    peewee_logger.setLevel(database_logger.level)
-
-    thr = ThreadPoolExecutor(max_workers=1)
-    thr.submit(update_progress)
+    thread = ThreadPoolExecutor(max_workers=1)
+    thread.submit(update_progress)
 
     # start http server
     try:
-        stat_logger.info("RAG Flow http server start...")
-        werkzeug_logger = logging.getLogger("werkzeug")
-        for h in access_logger.handlers:
-            werkzeug_logger.addHandler(h)
-        run_simple(hostname=HOST, port=HTTP_PORT, application=app, threaded=True, use_reloader=RuntimeConfig.DEBUG, use_debugger=RuntimeConfig.DEBUG)
+        logging.info("RAGFlow HTTP server start...")
+        run_simple(
+            hostname=settings.HOST_IP,
+            port=settings.HOST_PORT,
+            application=app,
+            threaded=True,
+            use_reloader=RuntimeConfig.DEBUG,
+            use_debugger=RuntimeConfig.DEBUG,
+        )
     except Exception:
         traceback.print_exc()
-        os.kill(os.getpid(), signal.SIGKILL)
+        os.kill(os.getpid(), signal.SIGKILL)

api/settings.py

@@ -14,199 +14,164 @@
 #  limitations under the License.
 #
 import os
+from datetime import date
 from enum import IntEnum, Enum
-from api.utils.file_utils import get_project_base_directory
-from api.utils.log_utils import LoggerFactory, getLogger
+import rag.utils.es_conn
+import rag.utils.infinity_conn
 
-# Logger
-LoggerFactory.set_directory(
-    os.path.join(
-        get_project_base_directory(),
-        "logs",
-        "api"))
-# {CRITICAL: 50, FATAL:50, ERROR:40, WARNING:30, WARN:30, INFO:20, DEBUG:10, NOTSET:0}
-LoggerFactory.LEVEL = 30
-
-stat_logger = getLogger("stat")
-access_logger = getLogger("access")
-database_logger = getLogger("database")
-chat_logger = getLogger("chat")
-
-from rag.utils.es_conn import ELASTICSEARCH
+import rag.utils
 from rag.nlp import search
 from graphrag import search as kg_search
 from api.utils import get_base_config, decrypt_database_config
+from api.constants import RAG_FLOW_SERVICE_NAME
 
-API_VERSION = "v1"
-RAG_FLOW_SERVICE_NAME = "ragflow"
-SERVER_MODULE = "rag_flow_server.py"
-TEMP_DIRECTORY = os.path.join(get_project_base_directory(), "temp")
-RAG_FLOW_CONF_PATH = os.path.join(get_project_base_directory(), "conf")
-LIGHTEN = os.environ.get('LIGHTEN')
+LIGHTEN = int(os.environ.get('LIGHTEN', "0"))
 
-SUBPROCESS_STD_LOG_NAME = "std.log"
-
-ERROR_REPORT = True
-ERROR_REPORT_WITH_PATH = False
-
-MAX_TIMESTAMP_INTERVAL = 60
-SESSION_VALID_PERIOD = 7 * 24 * 60 * 60
-
-REQUEST_TRY_TIMES = 3
-REQUEST_WAIT_SEC = 2
-REQUEST_MAX_WAIT_SEC = 300
-
-USE_REGISTRY = get_base_config("use_registry")
-
-LLM = get_base_config("user_default_llm", {})
-LLM_FACTORY = LLM.get("factory", "Tongyi-Qianwen")
-LLM_BASE_URL = LLM.get("base_url")
-
-if not LIGHTEN:
-    default_llm = {
-        "Tongyi-Qianwen": {
-            "chat_model": "qwen-plus",
-            "embedding_model": "text-embedding-v2",
-            "image2text_model": "qwen-vl-max",
-            "asr_model": "paraformer-realtime-8k-v1",
-        },
-        "OpenAI": {
-            "chat_model": "gpt-3.5-turbo",
-            "embedding_model": "text-embedding-ada-002",
-            "image2text_model": "gpt-4-vision-preview",
-            "asr_model": "whisper-1",
-        },
-        "Azure-OpenAI": {
-            "chat_model": "gpt-35-turbo",
-            "embedding_model": "text-embedding-ada-002",
-            "image2text_model": "gpt-4-vision-preview",
-            "asr_model": "whisper-1",
-        },
-        "ZHIPU-AI": {
-            "chat_model": "glm-3-turbo",
-            "embedding_model": "embedding-2",
-            "image2text_model": "glm-4v",
-            "asr_model": "",
-        },
-        "Ollama": {
-            "chat_model": "qwen-14B-chat",
-            "embedding_model": "flag-embedding",
-            "image2text_model": "",
-            "asr_model": "",
-        },
-        "Moonshot": {
-            "chat_model": "moonshot-v1-8k",
-            "embedding_model": "",
-            "image2text_model": "",
-            "asr_model": "",
-        },
-        "DeepSeek": {
-            "chat_model": "deepseek-chat",
-            "embedding_model": "",
-            "image2text_model": "",
-            "asr_model": "",
-        },
-        "VolcEngine": {
-            "chat_model": "",
-            "embedding_model": "",
-            "image2text_model": "",
-            "asr_model": "",
-        },
-        "BAAI": {
-            "chat_model": "",
-            "embedding_model": "BAAI/bge-large-zh-v1.5",
-            "image2text_model": "",
-            "asr_model": "",
-            "rerank_model": "BAAI/bge-reranker-v2-m3",
-        }
-    }
-
-    CHAT_MDL = default_llm[LLM_FACTORY]["chat_model"]
-    EMBEDDING_MDL = default_llm["BAAI"]["embedding_model"]
-    RERANK_MDL = default_llm["BAAI"]["rerank_model"] if not LIGHTEN else ""
-    ASR_MDL = default_llm[LLM_FACTORY]["asr_model"]
-    IMAGE2TEXT_MDL = default_llm[LLM_FACTORY]["image2text_model"]
-else:
-    CHAT_MDL = EMBEDDING_MDL = RERANK_MDL = ASR_MDL = IMAGE2TEXT_MDL = ""
-
-API_KEY = LLM.get("api_key", "")
-PARSERS = LLM.get(
-    "parsers",
-    "naive:General,qa:Q&A,resume:Resume,manual:Manual,table:Table,paper:Paper,book:Book,laws:Laws,presentation:Presentation,picture:Picture,one:One,audio:Audio,knowledge_graph:Knowledge Graph,email:Email")
-
-# distribution
-DEPENDENT_DISTRIBUTION = get_base_config("dependent_distribution", False)
-RAG_FLOW_UPDATE_CHECK = False
-
-HOST = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("host", "127.0.0.1")
-HTTP_PORT = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("http_port")
-
-SECRET_KEY = get_base_config(
-    RAG_FLOW_SERVICE_NAME,
-    {}).get(
-        "secret_key",
-    "infiniflow")
-TOKEN_EXPIRE_IN = get_base_config(
-    RAG_FLOW_SERVICE_NAME, {}).get(
-        "token_expires_in", 3600)
-
-NGINX_HOST = get_base_config(
-    RAG_FLOW_SERVICE_NAME, {}).get(
-        "nginx", {}).get("host") or HOST
-NGINX_HTTP_PORT = get_base_config(
-    RAG_FLOW_SERVICE_NAME, {}).get(
-        "nginx", {}).get("http_port") or HTTP_PORT
-
-RANDOM_INSTANCE_ID = get_base_config(
-    RAG_FLOW_SERVICE_NAME, {}).get(
-        "random_instance_id", False)
-
-PROXY = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("proxy")
-PROXY_PROTOCOL = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("protocol")
+LLM = None
+LLM_FACTORY = None
+LLM_BASE_URL = None
+CHAT_MDL = ""
+EMBEDDING_MDL = ""
+RERANK_MDL = ""
+ASR_MDL = ""
+IMAGE2TEXT_MDL = ""
+API_KEY = None
+PARSERS = None
+HOST_IP = None
+HOST_PORT = None
+SECRET_KEY = None
 
 DATABASE_TYPE = os.getenv("DB_TYPE", 'mysql')
 DATABASE = decrypt_database_config(name=DATABASE_TYPE)
 
-# Switch
-# upload
-UPLOAD_DATA_FROM_CLIENT = True
-
 # authentication
-AUTHENTICATION_CONF = get_base_config("authentication", {})
+AUTHENTICATION_CONF = None
 
 # client
-CLIENT_AUTHENTICATION = AUTHENTICATION_CONF.get(
-    "client", {}).get(
+CLIENT_AUTHENTICATION = None
+HTTP_APP_KEY = None
+GITHUB_OAUTH = None
+FEISHU_OAUTH = None
+
+DOC_ENGINE = None
+docStoreConn = None
+
+retrievaler = None
+kg_retrievaler = None
+
+
+def init_settings():
+    global LLM, LLM_FACTORY, LLM_BASE_URL, LIGHTEN, DATABASE_TYPE, DATABASE
+    LIGHTEN = int(os.environ.get('LIGHTEN', "0"))
+    DATABASE_TYPE = os.getenv("DB_TYPE", 'mysql')
+    DATABASE = decrypt_database_config(name=DATABASE_TYPE)
+    LLM = get_base_config("user_default_llm", {})
+    LLM_FACTORY = LLM.get("factory", "Tongyi-Qianwen")
+    LLM_BASE_URL = LLM.get("base_url")
+
+    global CHAT_MDL, EMBEDDING_MDL, RERANK_MDL, ASR_MDL, IMAGE2TEXT_MDL
+    if not LIGHTEN:
+        default_llm = {
+            "Tongyi-Qianwen": {
+                "chat_model": "qwen-plus",
+                "embedding_model": "text-embedding-v2",
+                "image2text_model": "qwen-vl-max",
+                "asr_model": "paraformer-realtime-8k-v1",
+            },
+            "OpenAI": {
+                "chat_model": "gpt-3.5-turbo",
+                "embedding_model": "text-embedding-ada-002",
+                "image2text_model": "gpt-4-vision-preview",
+                "asr_model": "whisper-1",
+            },
+            "Azure-OpenAI": {
+                "chat_model": "gpt-35-turbo",
+                "embedding_model": "text-embedding-ada-002",
+                "image2text_model": "gpt-4-vision-preview",
+                "asr_model": "whisper-1",
+            },
+            "ZHIPU-AI": {
+                "chat_model": "glm-3-turbo",
+                "embedding_model": "embedding-2",
+                "image2text_model": "glm-4v",
+                "asr_model": "",
+            },
+            "Ollama": {
+                "chat_model": "qwen-14B-chat",
+                "embedding_model": "flag-embedding",
+                "image2text_model": "",
+                "asr_model": "",
+            },
+            "Moonshot": {
+                "chat_model": "moonshot-v1-8k",
+                "embedding_model": "",
+                "image2text_model": "",
+                "asr_model": "",
+            },
+            "DeepSeek": {
+                "chat_model": "deepseek-chat",
+                "embedding_model": "",
+                "image2text_model": "",
+                "asr_model": "",
+            },
+            "VolcEngine": {
+                "chat_model": "",
+                "embedding_model": "",
+                "image2text_model": "",
+                "asr_model": "",
+            },
+            "BAAI": {
+                "chat_model": "",
+                "embedding_model": "BAAI/bge-large-zh-v1.5",
+                "image2text_model": "",
+                "asr_model": "",
+                "rerank_model": "BAAI/bge-reranker-v2-m3",
+            }
+        }
+
+        if LLM_FACTORY:
+            CHAT_MDL = default_llm[LLM_FACTORY]["chat_model"] + f"@{LLM_FACTORY}"
+            ASR_MDL = default_llm[LLM_FACTORY]["asr_model"] + f"@{LLM_FACTORY}"
+            IMAGE2TEXT_MDL = default_llm[LLM_FACTORY]["image2text_model"] + f"@{LLM_FACTORY}"
+        EMBEDDING_MDL = default_llm["BAAI"]["embedding_model"] + "@BAAI"
+        RERANK_MDL = default_llm["BAAI"]["rerank_model"] + "@BAAI"
+
+    global API_KEY, PARSERS, HOST_IP, HOST_PORT, SECRET_KEY
+    API_KEY = LLM.get("api_key", "")
+    PARSERS = LLM.get(
+        "parsers",
+        "naive:General,qa:Q&A,resume:Resume,manual:Manual,table:Table,paper:Paper,book:Book,laws:Laws,presentation:Presentation,picture:Picture,one:One,audio:Audio,knowledge_graph:Knowledge Graph,email:Email")
+
+    HOST_IP = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("host", "127.0.0.1")
+    HOST_PORT = get_base_config(RAG_FLOW_SERVICE_NAME, {}).get("http_port")
+
+    SECRET_KEY = get_base_config(
+        RAG_FLOW_SERVICE_NAME,
+        {}).get("secret_key", str(date.today()))
+
+    global AUTHENTICATION_CONF, CLIENT_AUTHENTICATION, HTTP_APP_KEY, GITHUB_OAUTH, FEISHU_OAUTH
+    # authentication
+    AUTHENTICATION_CONF = get_base_config("authentication", {})
+
+    # client
+    CLIENT_AUTHENTICATION = AUTHENTICATION_CONF.get(
+        "client", {}).get(
         "switch", False)
-HTTP_APP_KEY = AUTHENTICATION_CONF.get("client", {}).get("http_app_key")
-GITHUB_OAUTH = get_base_config("oauth", {}).get("github")
-FEISHU_OAUTH = get_base_config("oauth", {}).get("feishu")
-WECHAT_OAUTH = get_base_config("oauth", {}).get("wechat")
+    HTTP_APP_KEY = AUTHENTICATION_CONF.get("client", {}).get("http_app_key")
+    GITHUB_OAUTH = get_base_config("oauth", {}).get("github")
+    FEISHU_OAUTH = get_base_config("oauth", {}).get("feishu")
 
-# site
-SITE_AUTHENTICATION = AUTHENTICATION_CONF.get("site", {}).get("switch", False)
+    global DOC_ENGINE, docStoreConn, retrievaler, kg_retrievaler
+    DOC_ENGINE = os.environ.get('DOC_ENGINE', "elasticsearch")
+    if DOC_ENGINE == "elasticsearch":
+        docStoreConn = rag.utils.es_conn.ESConnection()
+    elif DOC_ENGINE == "infinity":
+        docStoreConn = rag.utils.infinity_conn.InfinityConnection()
+    else:
+        raise Exception(f"Not supported doc engine: {DOC_ENGINE}")
 
-# permission
-PERMISSION_CONF = get_base_config("permission", {})
-PERMISSION_SWITCH = PERMISSION_CONF.get("switch")
-COMPONENT_PERMISSION = PERMISSION_CONF.get("component")
-DATASET_PERMISSION = PERMISSION_CONF.get("dataset")
-
-HOOK_MODULE = get_base_config("hook_module")
-HOOK_SERVER_NAME = get_base_config("hook_server_name")
-
-ENABLE_MODEL_STORE = get_base_config('enable_model_store', False)
-# authentication
-USE_AUTHENTICATION = False
-USE_DATA_AUTHENTICATION = False
-AUTOMATIC_AUTHORIZATION_OUTPUT_DATA = True
-USE_DEFAULT_TIMEOUT = False
-AUTHENTICATION_DEFAULT_TIMEOUT = 7 * 24 * 60 * 60  # s
-PRIVILEGE_COMMAND_WHITELIST = []
-CHECK_NODES_IDENTITY = False
-
-retrievaler = search.Dealer(ELASTICSEARCH)
-kg_retrievaler = kg_search.KGSearch(ELASTICSEARCH)
+    retrievaler = search.Dealer(docStoreConn)
+    kg_retrievaler = kg_search.KGSearch(docStoreConn)
 
 
 class CustomEnum(Enum):
@@ -227,16 +192,6 @@ class CustomEnum(Enum):
         return [member.name for member in cls.__members__.values()]
 
 
-class PythonDependenceName(CustomEnum):
-    Rag_Source_Code = "python"
-    Python_Env = "miniconda"
-
-
-class ModelStorage(CustomEnum):
-    REDIS = "redis"
-    MYSQL = "mysql"
-
-
 class RetCode(IntEnum, CustomEnum):
     SUCCESS = 0
     NOT_EFFECTIVE = 10
@@ -250,3 +205,5 @@ class RetCode(IntEnum, CustomEnum):
     AUTHENTICATION_ERROR = 109
     UNAUTHORIZED = 401
     SERVER_ERROR = 500
+    FORBIDDEN = 403
+    NOT_FOUND = 404

api/utils/__init__.py

@@ -23,56 +23,64 @@ import socket
 import time
 import uuid
 import requests
+import logging
 from enum import Enum, IntEnum
 import importlib
 from Cryptodome.PublicKey import RSA
 from Cryptodome.Cipher import PKCS1_v1_5 as Cipher_pkcs1_v1_5
-
 from filelock import FileLock
+from api.constants import SERVICE_CONF
 
 from . import file_utils
 
-SERVICE_CONF = "service_conf.yaml"
-
 
 def conf_realpath(conf_name):
     conf_path = f"conf/{conf_name}"
     return os.path.join(file_utils.get_project_base_directory(), conf_path)
 
 
-def get_base_config(key, default=None, conf_name=SERVICE_CONF) -> dict:
+def read_config(conf_name=SERVICE_CONF):
     local_config = {}
     local_path = conf_realpath(f'local.{conf_name}')
-    if default is None:
-        default = os.environ.get(key.upper())
 
+    # load local config file
     if os.path.exists(local_path):
         local_config = file_utils.load_yaml_conf(local_path)
         if not isinstance(local_config, dict):
             raise ValueError(f'Invalid config file: "{local_path}".')
 
-        if key is not None and key in local_config:
-            return local_config[key]
+    global_config_path = conf_realpath(conf_name)
+    global_config = file_utils.load_yaml_conf(global_config_path)
 
-    config_path = conf_realpath(conf_name)
-    config = file_utils.load_yaml_conf(config_path)
+    if not isinstance(global_config, dict):
+        raise ValueError(f'Invalid config file: "{global_config_path}".')
 
-    if not isinstance(config, dict):
-        raise ValueError(f'Invalid config file: "{config_path}".')
+    global_config.update(local_config)
+    return global_config
 
-    config.update(local_config)
-    return config.get(key, default) if key is not None else config
+
+CONFIGS = read_config()
+
+
+def show_configs():
+    msg = f"Current configs, from {conf_realpath(SERVICE_CONF)}:"
+    for k, v in CONFIGS.items():
+        msg += f"\n\t{k}: {v}"
+    logging.info(msg)
+
+
+def get_base_config(key, default=None):
+    if key is None:
+        return None
+    if default is None:
+        default = os.environ.get(key.upper())
+    return CONFIGS.get(key, default)
 
 
 use_deserialize_safe_module = get_base_config(
     'use_deserialize_safe_module', False)
 
 
-class CoordinationCommunicationProtocol(object):
-    HTTP = "http"
-    GRPC = "grpc"
-
-
 class BaseType:
     def to_dict(self):
         return dict([(k.lstrip("_"), v) for k, v in self.__dict__.items()])
@@ -98,6 +106,7 @@ class BaseType:
                 data = obj
             return {"type": obj.__class__.__name__,
                     "data": data, "module": module}
+
         return _dict(self)
 
 
@@ -245,7 +254,7 @@ def get_lan_ip():
             try:
                 ip = get_interface_ip(ifname)
                 break
-            except IOError as e:
+            except IOError:
                 pass
     return ip or ''
 
@@ -342,5 +351,10 @@ def download_img(url):
         return ""
     response = requests.get(url)
     return "data:" + \
-           response.headers.get('Content-Type', 'image/jpg') + ";" + \
-           "base64," + base64.b64encode(response.content).decode("utf-8")
+        response.headers.get('Content-Type', 'image/jpg') + ";" + \
+        "base64," + base64.b64encode(response.content).decode("utf-8")
+
+
+def delta_seconds(date_string: str):
+    dt = datetime.datetime.strptime(date_string, "%Y-%m-%d %H:%M:%S")
+    return (datetime.datetime.now() - dt).total_seconds()

api/utils/api_utils.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import logging
 import functools
 import json
 import random
@@ -29,16 +30,16 @@ from flask import (
     Response, jsonify, send_file, make_response,
     request as flask_request,
 )
+from itsdangerous import URLSafeTimedSerializer
 from werkzeug.http import HTTP_STATUS_CODES
 
 from api.db.db_models import APIToken
-from api.settings import (
-    REQUEST_MAX_WAIT_SEC, REQUEST_WAIT_SEC,
-    stat_logger, CLIENT_AUTHENTICATION, HTTP_APP_KEY, SECRET_KEY
-)
-from api.settings import RetCode
-from api.utils import CustomJSONEncoder
+from api import settings
+
+from api import settings
+from api.utils import CustomJSONEncoder, get_uuid
 from api.utils import json_dumps
+from api.constants import REQUEST_WAIT_SEC, REQUEST_MAX_WAIT_SEC
 
 requests.models.complexjson.dumps = functools.partial(
     json.dumps, cls=CustomJSONEncoder)
@@ -52,18 +53,18 @@ def request(**kwargs):
         k.replace(
             '_',
             '-').upper(): v for k,
-        v in kwargs.get(
+                                v in kwargs.get(
             'headers',
             {}).items()}
     prepped = requests.Request(**kwargs).prepare()
 
-    if CLIENT_AUTHENTICATION and HTTP_APP_KEY and SECRET_KEY:
+    if settings.CLIENT_AUTHENTICATION and settings.HTTP_APP_KEY and settings.SECRET_KEY:
         timestamp = str(round(time() * 1000))
         nonce = str(uuid1())
-        signature = b64encode(HMAC(SECRET_KEY.encode('ascii'), b'\n'.join([
+        signature = b64encode(HMAC(settings.SECRET_KEY.encode('ascii'), b'\n'.join([
             timestamp.encode('ascii'),
             nonce.encode('ascii'),
-            HTTP_APP_KEY.encode('ascii'),
+            settings.HTTP_APP_KEY.encode('ascii'),
             prepped.path_url.encode('ascii'),
             prepped.body if kwargs.get('json') else b'',
             urlencode(
@@ -77,7 +78,7 @@ def request(**kwargs):
         prepped.headers.update({
             'TIMESTAMP': timestamp,
             'NONCE': nonce,
-            'APP-KEY': HTTP_APP_KEY,
+            'APP-KEY': settings.HTTP_APP_KEY,
             'SIGNATURE': signature,
         })
 
@@ -96,39 +97,19 @@ def get_exponential_backoff_interval(retries, full_jitter=False):
     return max(0, countdown)
 
 
-def get_json_result(retcode=RetCode.SUCCESS, retmsg='success',
-                    data=None, job_id=None, meta=None):
-    result_dict = {
-        "retcode": retcode,
-        "retmsg": retmsg,
-        # "retmsg": re.sub(r"rag", "seceum", retmsg, flags=re.IGNORECASE),
-        "data": data,
-        "jobId": job_id,
-        "meta": meta,
-    }
-
-    response = {}
-    for key, value in result_dict.items():
-        if value is None and key != "retcode":
-            continue
-        else:
-            response[key] = value
-    return jsonify(response)
-
-
-def get_data_error_result(retcode=RetCode.DATA_ERROR,
-                          retmsg='Sorry! Data missing!'):
+def get_data_error_result(code=settings.RetCode.DATA_ERROR,
+                          message='Sorry! Data missing!'):
     import re
     result_dict = {
-        "retcode": retcode,
-        "retmsg": re.sub(
+        "code": code,
+        "message": re.sub(
             r"rag",
             "seceum",
-            retmsg,
+            message,
             flags=re.IGNORECASE)}
     response = {}
     for key, value in result_dict.items():
-        if value is None and key != "retcode":
+        if value is None and key != "code":
             continue
         else:
             response[key] = value
@@ -136,29 +117,25 @@ def get_data_error_result(retcode=RetCode.DATA_ERROR,
 
 
 def server_error_response(e):
-    stat_logger.exception(e)
+    logging.exception(e)
     try:
         if e.code == 401:
-            return get_json_result(retcode=401, retmsg=repr(e))
+            return get_json_result(code=401, message=repr(e))
     except BaseException:
         pass
     if len(e.args) > 1:
         return get_json_result(
-            retcode=RetCode.EXCEPTION_ERROR, retmsg=repr(e.args[0]), data=e.args[1])
-    if repr(e).find("index_not_found_exception") >= 0:
-        return get_json_result(retcode=RetCode.EXCEPTION_ERROR,
-                               retmsg="No chunk found, please upload file and parse it.")
-
-    return get_json_result(retcode=RetCode.EXCEPTION_ERROR, retmsg=repr(e))
+            code=settings.RetCode.EXCEPTION_ERROR, message=repr(e.args[0]), data=e.args[1])
+    return get_json_result(code=settings.RetCode.EXCEPTION_ERROR, message=repr(e))
 
 
-def error_response(response_code, retmsg=None):
-    if retmsg is None:
-        retmsg = HTTP_STATUS_CODES.get(response_code, 'Unknown Error')
+def error_response(response_code, message=None):
+    if message is None:
+        message = HTTP_STATUS_CODES.get(response_code, 'Unknown Error')
 
     return Response(json.dumps({
-        'retmsg': retmsg,
-        'retcode': response_code,
+        'message': message,
+        'code': response_code,
     }), status=response_code, mimetype='application/json')
 
 
@@ -190,7 +167,7 @@ def validate_request(*args, **kwargs):
                     error_string += "required argument values: {}".format(
                         ",".join(["{}={}".format(a[0], a[1]) for a in error_arguments]))
                 return get_json_result(
-                    retcode=RetCode.ARGUMENT_ERROR, retmsg=error_string)
+                    code=settings.RetCode.ARGUMENT_ERROR, message=error_string)
             return func(*_args, **_kwargs)
 
         return decorated_function
@@ -215,17 +192,38 @@ def send_file_in_mem(data, filename):
     return send_file(f, as_attachment=True, attachment_filename=filename)
 
 
-def get_json_result(retcode=RetCode.SUCCESS, retmsg='success', data=None):
-    response = {"retcode": retcode, "retmsg": retmsg, "data": data}
+def get_json_result(code=settings.RetCode.SUCCESS, message='success', data=None):
+    response = {"code": code, "message": message, "data": data}
     return jsonify(response)
 
+def apikey_required(func):
+    @wraps(func)
+    def decorated_function(*args, **kwargs):
+        token = flask_request.headers.get('Authorization').split()[1]
+        objs = APIToken.query(token=token)
+        if not objs:
+            return build_error_result(
+                message='API-KEY is invalid!', code=settings.RetCode.FORBIDDEN
+            )
+        kwargs['tenant_id'] = objs[0].tenant_id
+        return func(*args, **kwargs)
 
-def construct_response(retcode=RetCode.SUCCESS,
-                       retmsg='success', data=None, auth=None):
-    result_dict = {"retcode": retcode, "retmsg": retmsg, "data": data}
+    return decorated_function
+
+
+def build_error_result(code=settings.RetCode.FORBIDDEN, message='success'):
+    response = {"code": code, "message": message}
+    response = jsonify(response)
+    response.status_code = code
+    return response
+
+
+def construct_response(code=settings.RetCode.SUCCESS,
+                       message='success', data=None, auth=None):
+    result_dict = {"code": code, "message": message, "data": data}
     response_dict = {}
     for key, value in result_dict.items():
-        if value is None and key != "retcode":
+        if value is None and key != "code":
             continue
         else:
             response_dict[key] = value
@@ -240,7 +238,7 @@ def construct_response(retcode=RetCode.SUCCESS,
     return response
 
 
-def construct_result(code=RetCode.DATA_ERROR, message='data is missing'):
+def construct_result(code=settings.RetCode.DATA_ERROR, message='data is missing'):
     import re
     result_dict = {"code": code, "message": re.sub(r"rag", "seceum", message, flags=re.IGNORECASE)}
     response = {}
@@ -252,7 +250,7 @@ def construct_result(code=RetCode.DATA_ERROR, message='data is missing'):
     return jsonify(response)
 
 
-def construct_json_result(code=RetCode.SUCCESS, message='success', data=None):
+def construct_json_result(code=settings.RetCode.SUCCESS, message='success', data=None):
     if data is None:
         return jsonify({"code": code, "message": message})
     else:
@@ -260,31 +258,99 @@ def construct_json_result(code=RetCode.SUCCESS, message='success', data=None):
 
 
 def construct_error_response(e):
-    stat_logger.exception(e)
+    logging.exception(e)
     try:
         if e.code == 401:
-            return construct_json_result(code=RetCode.UNAUTHORIZED, message=repr(e))
+            return construct_json_result(code=settings.RetCode.UNAUTHORIZED, message=repr(e))
     except BaseException:
         pass
     if len(e.args) > 1:
-        return construct_json_result(code=RetCode.EXCEPTION_ERROR, message=repr(e.args[0]), data=e.args[1])
-    if repr(e).find("index_not_found_exception") >= 0:
-        return construct_json_result(code=RetCode.EXCEPTION_ERROR,
-                                     message="No chunk found, please upload file and parse it.")
-
-    return construct_json_result(code=RetCode.EXCEPTION_ERROR, message=repr(e))
+        return construct_json_result(code=settings.RetCode.EXCEPTION_ERROR, message=repr(e.args[0]), data=e.args[1])
+    return construct_json_result(code=settings.RetCode.EXCEPTION_ERROR, message=repr(e))
 
 
 def token_required(func):
     @wraps(func)
     def decorated_function(*args, **kwargs):
-        token = flask_request.headers.get('Authorization').split()[1]
+        authorization_list=flask_request.headers.get('Authorization').split()
+        if len(authorization_list) < 2:
+            return get_json_result(data=False,message="Please check your authorization format.")
+        token = authorization_list[1]
         objs = APIToken.query(token=token)
         if not objs:
             return get_json_result(
-                data=False, retmsg='Token is not valid!', retcode=RetCode.AUTHENTICATION_ERROR
+                data=False, message='Token is not valid!', code=settings.RetCode.AUTHENTICATION_ERROR
             )
         kwargs['tenant_id'] = objs[0].tenant_id
         return func(*args, **kwargs)
 
     return decorated_function
+
+
+def get_result(code=settings.RetCode.SUCCESS, message="", data=None):
+    if code == 0:
+        if data is not None:
+            response = {"code": code, "data": data}
+        else:
+            response = {"code": code}
+    else:
+        response = {"code": code, "message": message}
+    return jsonify(response)
+
+
+def get_error_data_result(message='Sorry! Data missing!', code=settings.RetCode.DATA_ERROR,
+                          ):
+    import re
+    result_dict = {
+        "code": code,
+        "message": re.sub(
+            r"rag",
+            "seceum",
+            message,
+            flags=re.IGNORECASE)}
+    response = {}
+    for key, value in result_dict.items():
+        if value is None and key != "code":
+            continue
+        else:
+            response[key] = value
+    return jsonify(response)
+
+
+def generate_confirmation_token(tenent_id):
+    serializer = URLSafeTimedSerializer(tenent_id)
+    return "ragflow-" + serializer.dumps(get_uuid(), salt=tenent_id)[2:34]
+
+
+def valid(permission,valid_permission,language,valid_language,chunk_method,valid_chunk_method):
+    if valid_parameter(permission,valid_permission):
+        return valid_parameter(permission,valid_permission)
+    if valid_parameter(language,valid_language):
+        return valid_parameter(language,valid_language)
+    if valid_parameter(chunk_method,valid_chunk_method):
+        return valid_parameter(chunk_method,valid_chunk_method)
+
+def valid_parameter(parameter,valid_values):
+    if parameter and parameter not in valid_values:
+       return get_error_data_result(f"'{parameter}' is not in {valid_values}")
+
+def get_parser_config(chunk_method,parser_config):
+    if parser_config:
+        return parser_config
+    if not chunk_method:
+        chunk_method = "naive"
+    key_mapping={"naive":{"chunk_token_num": 128, "delimiter": "\\n!?;。；！？", "html4excel": False,"layout_recognize": True, "raptor": {"use_raptor": False}},
+                 "qa":{"raptor":{"use_raptor":False}},
+                 "resume":None,
+                 "manual":{"raptor":{"use_raptor":False}},
+                 "table":None,
+                 "paper":{"raptor":{"use_raptor":False}},
+                 "book":{"raptor":{"use_raptor":False}},
+                 "laws":{"raptor":{"use_raptor":False}},
+                 "presentation":{"raptor":{"use_raptor":False}},
+                 "one":None,
+                 "knowledge_graph":{"chunk_token_num":8192,"delimiter":"\\n!?;。；！？","entity_types":["organization","person","location","event","time"]},
+                 "email":None,
+                 "picture":None}
+    parser_config=key_mapping[chunk_method]
+    return parser_config

api/utils/file_utils.py

@@ -25,6 +25,7 @@ from cachetools import LRUCache, cached
 from ruamel.yaml import YAML
 
 from api.db import FileType
+from api.constants import IMG_BASE64_PREFIX
 
 PROJECT_BASE = os.getenv("RAG_PROJECT_BASE") or os.getenv("RAG_DEPLOY_BASE")
 RAG_BASE = os.getenv("RAG_BASE")
@@ -70,7 +71,7 @@ def get_home_cache_dir():
     dir = os.path.join(os.path.expanduser('~'), ".ragflow")
     try:
         os.mkdir(dir)
-    except OSError as error:
+    except OSError:
         pass
     return dir
 
@@ -168,23 +169,20 @@ def filename_type(filename):
 
     return FileType.OTHER.value
 
-
-def thumbnail(filename, blob):
+def thumbnail_img(filename, blob):
     filename = filename.lower()
     if re.match(r".*\.pdf$", filename):
         pdf = pdfplumber.open(BytesIO(blob))
         buffered = BytesIO()
         pdf.pages[0].to_image(resolution=32).annotated.save(buffered, format="png")
-        return "data:image/png;base64," + \
-            base64.b64encode(buffered.getvalue()).decode("utf-8")
+        return buffered.getvalue()
 
     if re.match(r".*\.(jpg|jpeg|png|tif|gif|icon|ico|webp)$", filename):
         image = Image.open(BytesIO(blob))
         image.thumbnail((30, 30))
         buffered = BytesIO()
         image.save(buffered, format="png")
-        return "data:image/png;base64," + \
-            base64.b64encode(buffered.getvalue()).decode("utf-8")
+        return buffered.getvalue()
 
     if re.match(r".*\.(ppt|pptx)$", filename):
         import aspose.slides as slides
@@ -194,10 +192,19 @@ def thumbnail(filename, blob):
                 buffered = BytesIO()
                 presentation.slides[0].get_thumbnail(0.03, 0.03).save(
                     buffered, drawing.imaging.ImageFormat.png)
-                return "data:image/png;base64," + \
-                    base64.b64encode(buffered.getvalue()).decode("utf-8")
-        except Exception as e:
+                return buffered.getvalue()
+        except Exception:
             pass
+    return None
+
+
+def thumbnail(filename, blob):
+    img = thumbnail_img(filename, blob)
+    if img is not None:
+        return IMG_BASE64_PREFIX + \
+            base64.b64encode(img).decode("utf-8")
+    else:
+        return ''
 
 
 def traversal_files(base):

api/utils/log_utils.py

@@ -14,300 +14,41 @@
 #  limitations under the License.
 #
 import os
-import typing
-import traceback
+import os.path
 import logging
-import inspect
-from logging.handlers import TimedRotatingFileHandler
-from threading import RLock
+from logging.handlers import RotatingFileHandler
 
-from api.utils import file_utils
+def get_project_base_directory():
+    PROJECT_BASE = os.path.abspath(
+        os.path.join(
+            os.path.dirname(os.path.realpath(__file__)),
+            os.pardir,
+            os.pardir,
+        )
+    )
+    return PROJECT_BASE
 
+def initRootLogger(logfile_basename: str, log_level: int = logging.INFO, log_format: str = "%(asctime)-15s %(levelname)-8s %(process)d %(message)s"):
+    logger = logging.getLogger()
+    if logger.hasHandlers():
+        return
 
-class LoggerFactory(object):
-    TYPE = "FILE"
-    LOG_FORMAT = "[%(levelname)s] [%(asctime)s] [%(module)s.%(funcName)s] [line:%(lineno)d]: %(message)s"
-    logging.basicConfig(format=LOG_FORMAT)
-    LEVEL = logging.DEBUG
-    logger_dict = {}
-    global_handler_dict = {}
+    log_path = os.path.abspath(os.path.join(get_project_base_directory(), "logs", f"{logfile_basename}.log"))
 
-    LOG_DIR = None
-    PARENT_LOG_DIR = None
-    log_share = True
+    os.makedirs(os.path.dirname(log_path), exist_ok=True)
+    logger.setLevel(log_level)
+    formatter = logging.Formatter(log_format)
 
-    append_to_parent_log = None
+    handler1 = RotatingFileHandler(log_path, maxBytes=10*1024*1024, backupCount=5)
+    handler1.setLevel(log_level)
+    handler1.setFormatter(formatter)
+    logger.addHandler(handler1)
 
-    lock = RLock()
-    # CRITICAL = 50
-    # FATAL = CRITICAL
-    # ERROR = 40
-    # WARNING = 30
-    # WARN = WARNING
-    # INFO = 20
-    # DEBUG = 10
-    # NOTSET = 0
-    levels = (10, 20, 30, 40)
-    schedule_logger_dict = {}
+    handler2 = logging.StreamHandler()
+    handler2.setLevel(log_level)
+    handler2.setFormatter(formatter)
+    logger.addHandler(handler2)
 
-    @staticmethod
-    def set_directory(directory=None, parent_log_dir=None,
-                      append_to_parent_log=None, force=False):
-        if parent_log_dir:
-            LoggerFactory.PARENT_LOG_DIR = parent_log_dir
-        if append_to_parent_log:
-            LoggerFactory.append_to_parent_log = append_to_parent_log
-        with LoggerFactory.lock:
-            if not directory:
-                directory = file_utils.get_project_base_directory("logs")
-            if not LoggerFactory.LOG_DIR or force:
-                LoggerFactory.LOG_DIR = directory
-            if LoggerFactory.log_share:
-                oldmask = os.umask(000)
-                os.makedirs(LoggerFactory.LOG_DIR, exist_ok=True)
-                os.umask(oldmask)
-            else:
-                os.makedirs(LoggerFactory.LOG_DIR, exist_ok=True)
-            for loggerName, ghandler in LoggerFactory.global_handler_dict.items():
-                for className, (logger,
-                                handler) in LoggerFactory.logger_dict.items():
-                    logger.removeHandler(ghandler)
-                ghandler.close()
-            LoggerFactory.global_handler_dict = {}
-            for className, (logger,
-                            handler) in LoggerFactory.logger_dict.items():
-                logger.removeHandler(handler)
-                _handler = None
-                if handler:
-                    handler.close()
-                if className != "default":
-                    _handler = LoggerFactory.get_handler(className)
-                    logger.addHandler(_handler)
-                LoggerFactory.assemble_global_handler(logger)
-                LoggerFactory.logger_dict[className] = logger, _handler
-
-    @staticmethod
-    def new_logger(name):
-        logger = logging.getLogger(name)
-        logger.propagate = False
-        logger.setLevel(LoggerFactory.LEVEL)
-        return logger
-
-    @staticmethod
-    def get_logger(class_name=None):
-        with LoggerFactory.lock:
-            if class_name in LoggerFactory.logger_dict.keys():
-                logger, handler = LoggerFactory.logger_dict[class_name]
-                if not logger:
-                    logger, handler = LoggerFactory.init_logger(class_name)
-            else:
-                logger, handler = LoggerFactory.init_logger(class_name)
-            return logger
-
-    @staticmethod
-    def get_global_handler(logger_name, level=None, log_dir=None):
-        if not LoggerFactory.LOG_DIR:
-            return logging.StreamHandler()
-        if log_dir:
-            logger_name_key = logger_name + "_" + log_dir
-        else:
-            logger_name_key = logger_name + "_" + LoggerFactory.LOG_DIR
-        # if loggerName not in LoggerFactory.globalHandlerDict:
-        if logger_name_key not in LoggerFactory.global_handler_dict:
-            with LoggerFactory.lock:
-                if logger_name_key not in LoggerFactory.global_handler_dict:
-                    handler = LoggerFactory.get_handler(
-                        logger_name, level, log_dir)
-                    LoggerFactory.global_handler_dict[logger_name_key] = handler
-        return LoggerFactory.global_handler_dict[logger_name_key]
-
-    @staticmethod
-    def get_handler(class_name, level=None, log_dir=None,
-                    log_type=None, job_id=None):
-        if not log_type:
-            if not LoggerFactory.LOG_DIR or not class_name:
-                return logging.StreamHandler()
-                # return Diy_StreamHandler()
-
-            if not log_dir:
-                log_file = os.path.join(
-                    LoggerFactory.LOG_DIR,
-                    "{}.log".format(class_name))
-            else:
-                log_file = os.path.join(log_dir, "{}.log".format(class_name))
-        else:
-            log_file = os.path.join(log_dir, "rag_flow_{}.log".format(
-                log_type) if level == LoggerFactory.LEVEL else 'rag_flow_{}_error.log'.format(log_type))
-
-        os.makedirs(os.path.dirname(log_file), exist_ok=True)
-        if LoggerFactory.log_share:
-            handler = ROpenHandler(log_file,
-                                   when='D',
-                                   interval=1,
-                                   backupCount=14,
-                                   delay=True)
-        else:
-            handler = TimedRotatingFileHandler(log_file,
-                                               when='D',
-                                               interval=1,
-                                               backupCount=14,
-                                               delay=True)
-        if level:
-            handler.level = level
-
-        return handler
-
-    @staticmethod
-    def init_logger(class_name):
-        with LoggerFactory.lock:
-            logger = LoggerFactory.new_logger(class_name)
-            handler = None
-            if class_name:
-                handler = LoggerFactory.get_handler(class_name)
-                logger.addHandler(handler)
-                LoggerFactory.logger_dict[class_name] = logger, handler
-
-            else:
-                LoggerFactory.logger_dict["default"] = logger, handler
-
-            LoggerFactory.assemble_global_handler(logger)
-            return logger, handler
-
-    @staticmethod
-    def assemble_global_handler(logger):
-        if LoggerFactory.LOG_DIR:
-            for level in LoggerFactory.levels:
-                if level >= LoggerFactory.LEVEL:
-                    level_logger_name = logging._levelToName[level]
-                    logger.addHandler(
-                        LoggerFactory.get_global_handler(
-                            level_logger_name, level))
-        if LoggerFactory.append_to_parent_log and LoggerFactory.PARENT_LOG_DIR:
-            for level in LoggerFactory.levels:
-                if level >= LoggerFactory.LEVEL:
-                    level_logger_name = logging._levelToName[level]
-                    logger.addHandler(
-                        LoggerFactory.get_global_handler(level_logger_name, level, LoggerFactory.PARENT_LOG_DIR))
-
-
-def setDirectory(directory=None):
-    LoggerFactory.set_directory(directory)
-
-
-def setLevel(level):
-    LoggerFactory.LEVEL = level
-
-
-def getLogger(className=None, useLevelFile=False):
-    if className is None:
-        frame = inspect.stack()[1]
-        module = inspect.getmodule(frame[0])
-        className = 'stat'
-    return LoggerFactory.get_logger(className)
-
-
-def exception_to_trace_string(ex):
-    return "".join(traceback.TracebackException.from_exception(ex).format())
-
-
-class ROpenHandler(TimedRotatingFileHandler):
-    def _open(self):
-        prevumask = os.umask(000)
-        rtv = TimedRotatingFileHandler._open(self)
-        os.umask(prevumask)
-        return rtv
-
-
-def sql_logger(job_id='', log_type='sql'):
-    key = job_id + log_type
-    if key in LoggerFactory.schedule_logger_dict.keys():
-        return LoggerFactory.schedule_logger_dict[key]
-    return get_job_logger(job_id=job_id, log_type=log_type)
-
-
-def ready_log(msg, job=None, task=None, role=None, party_id=None, detail=None):
-    prefix, suffix = base_msg(job, task, role, party_id, detail)
-    return f"{prefix}{msg} ready{suffix}"
-
-
-def start_log(msg, job=None, task=None, role=None, party_id=None, detail=None):
-    prefix, suffix = base_msg(job, task, role, party_id, detail)
-    return f"{prefix}start to {msg}{suffix}"
-
-
-def successful_log(msg, job=None, task=None, role=None,
-                   party_id=None, detail=None):
-    prefix, suffix = base_msg(job, task, role, party_id, detail)
-    return f"{prefix}{msg} successfully{suffix}"
-
-
-def warning_log(msg, job=None, task=None, role=None,
-                party_id=None, detail=None):
-    prefix, suffix = base_msg(job, task, role, party_id, detail)
-    return f"{prefix}{msg} is not effective{suffix}"
-
-
-def failed_log(msg, job=None, task=None, role=None,
-               party_id=None, detail=None):
-    prefix, suffix = base_msg(job, task, role, party_id, detail)
-    return f"{prefix}failed to {msg}{suffix}"
-
-
-def base_msg(job=None, task=None, role: str = None,
-             party_id: typing.Union[str, int] = None, detail=None):
-    if detail:
-        detail_msg = f" detail: \n{detail}"
-    else:
-        detail_msg = ""
-    if task is not None:
-        return f"task {task.f_task_id} {task.f_task_version} ", f" on {task.f_role} {task.f_party_id}{detail_msg}"
-    elif job is not None:
-        return "", f" on {job.f_role} {job.f_party_id}{detail_msg}"
-    elif role and party_id:
-        return "", f" on {role} {party_id}{detail_msg}"
-    else:
-        return "", f"{detail_msg}"
-
-
-def exception_to_trace_string(ex):
-    return "".join(traceback.TracebackException.from_exception(ex).format())
-
-
-def get_logger_base_dir():
-    job_log_dir = file_utils.get_rag_flow_directory('logs')
-    return job_log_dir
-
-
-def get_job_logger(job_id, log_type):
-    rag_flow_log_dir = file_utils.get_rag_flow_directory('logs', 'rag_flow')
-    job_log_dir = file_utils.get_rag_flow_directory('logs', job_id)
-    if not job_id:
-        log_dirs = [rag_flow_log_dir]
-    else:
-        if log_type == 'audit':
-            log_dirs = [job_log_dir, rag_flow_log_dir]
-        else:
-            log_dirs = [job_log_dir]
-    if LoggerFactory.log_share:
-        oldmask = os.umask(000)
-        os.makedirs(job_log_dir, exist_ok=True)
-        os.makedirs(rag_flow_log_dir, exist_ok=True)
-        os.umask(oldmask)
-    else:
-        os.makedirs(job_log_dir, exist_ok=True)
-        os.makedirs(rag_flow_log_dir, exist_ok=True)
-    logger = LoggerFactory.new_logger(f"{job_id}_{log_type}")
-    for job_log_dir in log_dirs:
-        handler = LoggerFactory.get_handler(class_name=None, level=LoggerFactory.LEVEL,
-                                            log_dir=job_log_dir, log_type=log_type, job_id=job_id)
-        error_handler = LoggerFactory.get_handler(
-            class_name=None,
-            level=logging.ERROR,
-            log_dir=job_log_dir,
-            log_type=log_type,
-            job_id=job_id)
-        logger.addHandler(handler)
-        logger.addHandler(error_handler)
-    with LoggerFactory.lock:
-        LoggerFactory.schedule_logger_dict[job_id + log_type] = logger
-    return logger
+    logging.captureWarnings(True)
+    msg = f"{logfile_basename} log path: {log_path}"
+    logger.info(msg)

api/utils/web_utils.py

@@ -77,4 +77,4 @@ def __get_pdf_from_html(
 
 
 def is_valid_url(url: str) -> bool:
-    return bool(re.match(r"(https?|ftp|file)://[-A-Za-z0-9+&@#/%?=~_|!:,.;]+[-A-Za-z0-9+&@#/%=~_|]", url))
+    return bool(re.match(r"(https?)://[-A-Za-z0-9+&@#/%?=~_|!:,.;]+[-A-Za-z0-9+&@#/%=~_|]", url))

api/validation.py

@@ -0,0 +1,49 @@
+#
+#  Copyright 2024 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import logging
+import sys
+
+
+def python_version_validation():
+    # Check python version
+    required_python_version = (3, 10)
+    if sys.version_info < required_python_version:
+        logging.info(
+            f"Required Python: >= {required_python_version[0]}.{required_python_version[1]}. Current Python version: {sys.version_info[0]}.{sys.version_info[1]}."
+        )
+        sys.exit(1)
+    else:
+        logging.info(f"Python version: {sys.version_info[0]}.{sys.version_info[1]}")
+
+
+python_version_validation()
+
+
+# Download nltk data
+def download_nltk_data():
+    import nltk
+    nltk.download('wordnet', halt_on_error=False, quiet=True)
+    nltk.download('punkt_tab', halt_on_error=False, quiet=True)
+
+
+try:
+    from multiprocessing import Pool
+    pool = Pool(processes=1)
+    thread = pool.apply_async(download_nltk_data)
+    binary = thread.get(timeout=60)
+except Exception as e:
+    print('\x1b[6;37;41m WARNING \x1b[0m' + "Downloading NLTK data failure.", flush=True)

api/versions.py

@@ -13,14 +13,57 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-import dotenv
-import typing
+
+import os
+import subprocess
+
+RAGFLOW_VERSION_INFO = "unknown"
 
 
-def get_versions() -> typing.Mapping[str, typing.Any]:
-    dotenv.load_dotenv(dotenv.find_dotenv())
-    return dotenv.dotenv_values()
+def get_ragflow_version() -> str:
+    global RAGFLOW_VERSION_INFO
+    if RAGFLOW_VERSION_INFO != "unknown":
+        return RAGFLOW_VERSION_INFO
+    version_path = os.path.abspath(
+        os.path.join(
+            os.path.dirname(os.path.realpath(__file__)), os.pardir, "VERSION"
+        )
+    )
+    if os.path.exists(version_path):
+        with open(version_path, "r") as f:
+            RAGFLOW_VERSION_INFO = f.read().strip()
+    else:
+        RAGFLOW_VERSION_INFO = get_closest_tag_and_count()
+        LIGHTEN = int(os.environ.get("LIGHTEN", "0"))
+        RAGFLOW_VERSION_INFO += " slim" if LIGHTEN == 1 else " full"
+    return RAGFLOW_VERSION_INFO
 
 
-def get_rag_version() -> typing.Optional[str]:
-    return get_versions().get("RAGFLOW_IMAGE", "infiniflow/ragflow:dev").split(":")[-1]
+def get_closest_tag_and_count():
+    try:
+        # Get the current commit hash
+        commit_id = (
+            subprocess.check_output(["git", "rev-parse", "--short", "HEAD"])
+            .strip()
+            .decode("utf-8")
+        )
+        # Get the closest tag
+        closest_tag = (
+            subprocess.check_output(["git", "describe", "--tags", "--abbrev=0"])
+            .strip()
+            .decode("utf-8")
+        )
+        # Get the commit count since the closest tag
+        process = subprocess.Popen(
+            ["git", "rev-list", "--count", f"{closest_tag}..HEAD"],
+            stdout=subprocess.PIPE,
+        )
+        commits_count, _ = process.communicate()
+        commits_count = int(commits_count.strip())
+
+        if commits_count == 0:
+            return closest_tag
+        else:
+            return f"{commit_id}({closest_tag}~{commits_count})"
+    except Exception:
+        return "unknown"

conf/infinity_mapping.json

@@ -0,0 +1,26 @@
+{
+	"id": {"type": "varchar", "default": ""},
+	"doc_id": {"type": "varchar", "default": ""},
+	"kb_id": {"type": "varchar", "default": ""},
+	"create_time": {"type": "varchar", "default": ""},
+	"create_timestamp_flt": {"type": "float", "default": 0.0},
+	"img_id": {"type": "varchar", "default": ""},
+	"docnm_kwd": {"type": "varchar", "default": ""},
+	"title_tks": {"type": "varchar", "default": ""},
+	"title_sm_tks": {"type": "varchar", "default": ""},
+	"name_kwd": {"type": "varchar", "default": ""},
+	"important_kwd": {"type": "varchar", "default": ""},
+	"important_tks": {"type": "varchar", "default": ""},
+	"content_with_weight": {"type": "varchar", "default": ""},
+	"content_ltks": {"type": "varchar", "default": ""},
+	"content_sm_ltks": {"type": "varchar", "default": ""},
+	"page_num_list": {"type": "varchar", "default": ""},
+	"top_list": {"type": "varchar", "default": ""},
+	"position_list": {"type": "varchar", "default": ""},
+	"weight_int": {"type": "integer", "default": 0},
+	"weight_flt": {"type": "float", "default": 0.0},
+	"rank_int": {"type": "integer", "default": 0},
+	"available_int": {"type": "integer", "default": 1},
+	"knowledge_graph_kwd": {"type": "varchar", "default": ""},
+	"entities_kwd": {"type": "varchar", "default": ""}
+}

conf/llm_factories.json

@@ -3,7 +3,7 @@
         {
             "name": "OpenAI",
             "logo": "",
-            "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+            "tags": "LLM,TEXT EMBEDDING,TTS,TEXT RE-RANK,SPEECH2TEXT,MODERATION",
             "status": "1",
             "llm": [
                 {
@@ -89,9 +89,15 @@
         {
             "name": "Tongyi-Qianwen",
             "logo": "",
-            "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+            "tags": "LLM,TEXT EMBEDDING,TEXT RE-RANK,TTS,SPEECH2TEXT,MODERATION",
             "status": "1",
             "llm": [
+                {
+                    "llm_name": "qwen-long",
+                    "tags": "LLM,CHAT,10000K",
+                    "max_tokens": 1000000,
+                    "model_type": "chat"
+                },
                 {
                     "llm_name": "qwen-turbo",
                     "tags": "LLM,CHAT,8K",
@@ -139,6 +145,12 @@
                     "tags": "LLM,CHAT,IMAGE2TEXT",
                     "max_tokens": 765,
                     "model_type": "image2text"
+                },
+                {
+                    "llm_name": "gte-rerank",
+                    "tags": "RE-RANK,4k",
+                    "max_tokens": 4000,
+                    "model_type": "rerank"
                 }
             ]
         },
@@ -148,6 +160,18 @@
             "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
             "status": "1",
             "llm": [
+                {
+                    "llm_name": "glm-4-plus",
+                    "tags": "LLM,CHAT,",
+                    "max_tokens": 128000,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "glm-4-0520",
+                    "tags": "LLM,CHAT,",
+                    "max_tokens": 128000,
+                    "model_type": "chat"
+                },
                 {
                     "llm_name": "glm-4",
                     "tags": "LLM,CHAT,",
@@ -172,6 +196,12 @@
                     "max_tokens": 128000,
                     "model_type": "chat"
                 },
+                {
+                    "llm_name": "glm-4-flashx",
+                    "tags": "LLM,CHAT,",
+                    "max_tokens": 128000,
+                    "model_type": "chat"
+                },
                 {
                     "llm_name": "glm-4-long",
                     "tags": "LLM,CHAT,",
@@ -190,6 +220,12 @@
                     "max_tokens": 2000,
                     "model_type": "image2text"
                 },
+                {
+                    "llm_name": "glm-4-9b",
+                    "tags": "LLM,CHAT,",
+                    "max_tokens": 8192,
+                    "model_type": "chat"
+                },
                 {
                     "llm_name": "embedding-2",
                     "tags": "TEXT EMBEDDING",
@@ -248,6 +284,12 @@
                     "tags": "LLM,CHAT",
                     "max_tokens": 128000,
                     "model_type": "chat"
+                },
+                {
+                    "llm_name": "moonshot-v1-auto",
+                    "tags": "LLM,CHAT,",
+                    "max_tokens": 128000,
+                    "model_type": "chat"
                 }
             ]
         },
@@ -310,7 +352,7 @@
         {
             "name": "Xinference",
             "logo": "",
-            "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION,TEXT RE-RANK",
+            "tags": "LLM,TEXT EMBEDDING,TTS,SPEECH2TEXT,MODERATION,TEXT RE-RANK",
             "status": "1",
             "llm": []
         },
@@ -616,16 +658,16 @@
                     "llm_name": "gpt-4o",
                     "tags": "LLM,CHAT,128K",
                     "max_tokens": 128000,
-                    "model_type": "chat,image2text"
+                    "model_type": "image2text"
                 },
                 {
-                    "llm_name": "gpt-35-turbo",
+                    "llm_name": "gpt-3.5-turbo",
                     "tags": "LLM,CHAT,4K",
                     "max_tokens": 4096,
                     "model_type": "chat"
                 },
                 {
-                    "llm_name": "gpt-35-turbo-16k",
+                    "llm_name": "gpt-3.5-turbo-16k",
                     "tags": "LLM,CHAT,16k",
                     "max_tokens": 16385,
                     "model_type": "chat"
@@ -1275,7 +1317,7 @@
             "llm": []
         },
         {
-            "name": "cohere",
+            "name": "Cohere",
             "logo": "",
             "tags": "LLM,TEXT EMBEDDING, TEXT RE-RANK",
             "status": "1",
@@ -1993,6 +2035,60 @@
                     "max_tokens": 32768,
                     "model_type": "chat"
                 },
+                {
+                    "llm_name": "Qwen/Qwen2.5-72B-Instruct-128K",
+                    "tags": "LLM,CHAT,128k",
+                    "max_tokens": 131072,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "Qwen/Qwen2.5-72B-Instruct",
+                    "tags": "LLM,CHAT,32k",
+                    "max_tokens": 32768,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "Qwen/Qwen2.5-7B-Instruct",
+                    "tags": "LLM,CHAT,32k",
+                    "max_tokens": 32768,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "Qwen/Qwen2.5-14B-Instruct",
+                    "tags": "LLM,CHAT,32k",
+                    "max_tokens": 32768,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "Qwen/Qwen2.5-32B-Instruct",
+                    "tags": "LLM,CHAT,32k",
+                    "max_tokens": 32768,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "Qwen/Qwen2.5-Math-72B-Instruct",
+                    "tags": "LLM,CHAT,Math,4k",
+                    "max_tokens": 4096,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "Qwen/Qwen2.5-Coder-7B-Instruct",
+                    "tags": "LLM,CHAT,FIM,Coder,32k",
+                    "max_tokens": 32768,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "Pro/Qwen/Qwen2.5-7B-Instruct",
+                    "tags": "LLM,CHAT,32k",
+                    "max_tokens": 32768,
+                    "model_type": "chat"
+                },
+                {
+                    "llm_name": "Pro/Qwen/Qwen2.5-Coder-7B-Instruct",
+                    "tags": "LLM,CHAT,FIM,Coder,32k",
+                    "max_tokens": 32768,
+                    "model_type": "chat"
+                },
                 {
                     "llm_name": "01-ai/Yi-1.5-34B-Chat-16K",
                     "tags": "LLM,CHAT,16k",
@@ -2097,6 +2193,12 @@
             "tags": "LLM,IMAGE2TEXT",
             "status": "1",
             "llm": [
+                {
+                    "llm_name": "yi-lightning",
+                    "tags": "LLM,CHAT,16k",
+                    "max_tokens": 16384,
+                    "model_type": "chat"
+                },
                 {
                     "llm_name": "yi-large",
                     "tags": "LLM,CHAT,32k",
@@ -2201,7 +2303,7 @@
         {
             "name": "XunFei Spark",
             "logo": "",
-            "tags": "LLM",
+            "tags": "LLM,TTS",
             "status": "1",
             "llm": []
         },
@@ -2238,6 +2340,12 @@
                     "max_tokens": 204800,
                     "model_type": "chat"
                 },
+                {
+                    "llm_name": "claude-3-5-sonnet-20241022",
+                    "tags": "LLM,CHAT,200k",
+                    "max_tokens": 204800,
+                    "model_type": "chat"
+                },
                 {
                     "llm_name": "claude-3-opus-20240229",
                     "tags": "LLM,CHAT,200k",
@@ -2269,8 +2377,8 @@
                     "model_type": "chat"
                 },
                 {
-                    "llm_name": "claude-instant-1.2",
-                    "tags": "LLM,CHAT,100k",
+                    "llm_name": "claude-3-5-sonnet-20241022",
+                    "tags": "LLM,CHAT,200k",
                     "max_tokens": 102400,
                     "model_type": "chat"
                 }
@@ -2346,11 +2454,11 @@
             "llm": []
         },
         {
-      "name": "HuggingFace",
-      "logo": "",
-      "tags": "TEXT EMBEDDING",
-      "status": "1",
-      "llm": []
-    }
+            "name": "HuggingFace",
+            "logo": "",
+            "tags": "TEXT EMBEDDING",
+            "status": "1",
+            "llm": []
+        }
     ]
 }

conf/mapping.json

@@ -1,200 +1,203 @@
- {
+{
   "settings": {
     "index": {
       "number_of_shards": 2,
       "number_of_replicas": 0,
-      "refresh_interval" : "1000ms"
+      "refresh_interval": "1000ms"
     },
     "similarity": {
-        "scripted_sim": {
-          "type": "scripted",
-          "script": {
-            "source": "double idf = Math.log(1+(field.docCount-term.docFreq+0.5)/(term.docFreq + 0.5))/Math.log(1+((field.docCount-0.5)/1.5)); return query.boost * idf * Math.min(doc.freq, 1);"
-          }
+      "scripted_sim": {
+        "type": "scripted",
+        "script": {
+          "source": "double idf = Math.log(1+(field.docCount-term.docFreq+0.5)/(term.docFreq + 0.5))/Math.log(1+((field.docCount-0.5)/1.5)); return query.boost * idf * Math.min(doc.freq, 1);"
         }
+      }
     }
   },
   "mappings": {
-      "properties": {
-        "lat_lon": {"type": "geo_point", "store":"true"}
-      },
-      "date_detection": "true",
-      "dynamic_templates": [
-        {
-          "int": {
-            "match": "*_int",
-            "mapping": {
-              "type": "integer",
-              "store": "true"
-            }
+    "properties": {
+      "lat_lon": {
+        "type": "geo_point",
+        "store": "true"
+      }
+    },
+    "date_detection": "true",
+    "dynamic_templates": [
+      {
+        "int": {
+          "match": "*_int",
+          "mapping": {
+            "type": "integer",
+            "store": "true"
           }
-        },
-        {
-          "ulong": {
-            "match": "*_ulong",
-            "mapping": {
-              "type": "unsigned_long",
-              "store": "true"
-            }
-          }
-        },
-        {
-          "long": {
-            "match": "*_long",
-            "mapping": {
-              "type": "long",
-              "store": "true"
-            }
-          }
-        },
-        {
-          "short": {
-            "match": "*_short",
-            "mapping": {
-              "type": "short",
-              "store": "true"
-            }
-          }
-        },
-        {
-          "numeric": {
-            "match": "*_flt",
-            "mapping": {
-              "type": "float",
-              "store": true
-            }
-          }
-        },
-        {
-          "tks": {
-            "match": "*_tks",
-            "mapping": {
-              "type": "text",
-              "similarity": "scripted_sim",
-              "analyzer": "whitespace",
-              "store": true
-            }
-          }
-        },
-        {
-          "ltks":{
-            "match": "*_ltks",
-            "mapping": {
-              "type": "text",
-              "analyzer": "whitespace",
-              "store": true
-            }
-          }
-        },
-        {
-          "kwd": {
-            "match_pattern": "regex",
-            "match": "^(.*_(kwd|id|ids|uid|uids)|uid)$",
-            "mapping": {
-              "type": "keyword",
-              "similarity": "boolean",
-              "store": true
-            }
-          }
-        },
-        {
-          "dt": {
-            "match_pattern": "regex",
-            "match": "^.*(_dt|_time|_at)$",
-            "mapping": {
-              "type": "date",
-              "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||yyyy-MM-dd_HH:mm:ss",
-              "store": true
-            }
-          }
-        },
-        {
-          "nested": {
-            "match": "*_nst",
-            "mapping": {
-              "type": "nested"
-            }
-          }
-        },
-          {
-            "object": {
-              "match": "*_obj",
-              "mapping": {
-                "type": "object",
-                "dynamic": "true"
-              }
-            }
-          },
-        {
-            "string": {
-              "match": "*_with_weight",
-              "mapping": {
-                "type": "text",
-                "index": "false",
-                "store": true
-              }
-            }
-        },
-        {
-            "string": {
-              "match": "*_fea",
-              "mapping": {
-                "type": "rank_feature"
-              }
-            }
-        },
-        {
-            "dense_vector": {
-              "match": "*_512_vec",
-              "mapping": {
-                "type": "dense_vector",
-                "index": true,
-                "similarity": "cosine",
-                "dims": 512
-              }
-            }
-        },
-        {
-            "dense_vector": {
-              "match": "*_768_vec",
-              "mapping": {
-                "type": "dense_vector",
-                "index": true,
-                "similarity": "cosine",
-                "dims": 768
-              }
-            }
-        },
-        {
-            "dense_vector": {
-              "match": "*_1024_vec",
-              "mapping": {
-                "type": "dense_vector",
-                "index": true,
-                "similarity": "cosine",
-                "dims": 1024
-              }
-            }
-        },
-        {
-            "dense_vector": {
-              "match": "*_1536_vec",
-              "mapping": {
-                "type": "dense_vector",
-                "index": true,
-                "similarity": "cosine",
-                "dims": 1536
-              }
-            }
-        },
-        {
-            "binary": {
-              "match": "*_bin",
-              "mapping": {
-                "type": "binary"
-              }
-            }
         }
-      ]
-    }
-}
+      },
+      {
+        "ulong": {
+          "match": "*_ulong",
+          "mapping": {
+            "type": "unsigned_long",
+            "store": "true"
+          }
+        }
+      },
+      {
+        "long": {
+          "match": "*_long",
+          "mapping": {
+            "type": "long",
+            "store": "true"
+          }
+        }
+      },
+      {
+        "short": {
+          "match": "*_short",
+          "mapping": {
+            "type": "short",
+            "store": "true"
+          }
+        }
+      },
+      {
+        "numeric": {
+          "match": "*_flt",
+          "mapping": {
+            "type": "float",
+            "store": true
+          }
+        }
+      },
+      {
+        "tks": {
+          "match": "*_tks",
+          "mapping": {
+            "type": "text",
+            "similarity": "scripted_sim",
+            "analyzer": "whitespace",
+            "store": true
+          }
+        }
+      },
+      {
+        "ltks": {
+          "match": "*_ltks",
+          "mapping": {
+            "type": "text",
+            "analyzer": "whitespace",
+            "store": true
+          }
+        }
+      },
+      {
+        "kwd": {
+          "match_pattern": "regex",
+          "match": "^(.*_(kwd|id|ids|uid|uids)|uid)$",
+          "mapping": {
+            "type": "keyword",
+            "similarity": "boolean",
+            "store": true
+          }
+        }
+      },
+      {
+        "dt": {
+          "match_pattern": "regex",
+          "match": "^.*(_dt|_time|_at)$",
+          "mapping": {
+            "type": "date",
+            "format": "yyyy-MM-dd HH:mm:ss||yyyy-MM-dd||yyyy-MM-dd_HH:mm:ss",
+            "store": true
+          }
+        }
+      },
+      {
+        "nested": {
+          "match": "*_nst",
+          "mapping": {
+            "type": "nested"
+          }
+        }
+      },
+      {
+        "object": {
+          "match": "*_obj",
+          "mapping": {
+            "type": "object",
+            "dynamic": "true"
+          }
+        }
+      },
+      {
+        "string": {
+          "match": "*_(with_weight|list)$",
+          "mapping": {
+            "type": "text",
+            "index": "false",
+            "store": true
+          }
+        }
+      },
+      {
+        "string": {
+          "match": "*_fea",
+          "mapping": {
+            "type": "rank_feature"
+          }
+        }
+      },
+      {
+        "dense_vector": {
+          "match": "*_512_vec",
+          "mapping": {
+            "type": "dense_vector",
+            "index": true,
+            "similarity": "cosine",
+            "dims": 512
+          }
+        }
+      },
+      {
+        "dense_vector": {
+          "match": "*_768_vec",
+          "mapping": {
+            "type": "dense_vector",
+            "index": true,
+            "similarity": "cosine",
+            "dims": 768
+          }
+        }
+      },
+      {
+        "dense_vector": {
+          "match": "*_1024_vec",
+          "mapping": {
+            "type": "dense_vector",
+            "index": true,
+            "similarity": "cosine",
+            "dims": 1024
+          }
+        }
+      },
+      {
+        "dense_vector": {
+          "match": "*_1536_vec",
+          "mapping": {
+            "type": "dense_vector",
+            "index": true,
+            "similarity": "cosine",
+            "dims": 1536
+          }
+        }
+      },
+      {
+        "binary": {
+          "match": "*_bin",
+          "mapping": {
+            "type": "binary"
+          }
+        }
+      }
+    ]
+  }
+}

conf/service_conf.yaml

@@ -1 +0,0 @@
-../docker/service_conf.yaml

conf/service_conf.yaml

@@ -0,0 +1,77 @@
+ragflow:
+  host: 0.0.0.0
+  http_port: 9380
+mysql:
+  name: 'rag_flow'
+  user: 'root'
+  password: 'infini_rag_flow'
+  host: 'mysql'
+  port: 5455
+  max_connections: 100
+  stale_timeout: 30
+minio:
+  user: 'rag_flow'
+  password: 'infini_rag_flow'
+  host: 'minio:9000'
+es:
+  hosts: 'http://es01:1200'
+  username: 'elastic'
+  password: 'infini_rag_flow'
+infinity:
+  uri: 'infinity:23817'
+  db_name: 'default_db'
+redis:
+  db: 1
+  password: 'infini_rag_flow' 
+  host: 'redis:6379'
+
+# postgres:
+#   name: 'rag_flow'
+#   user: 'rag_flow'
+#   password: 'infini_rag_flow'
+#   host: 'postgres'
+#   port: 5432
+#   max_connections: 100
+#   stale_timeout: 30
+# s3:
+#   endpoint: 'endpoint'
+#   access_key: 'access_key'
+#   secret_key: 'secret_key'
+#   region: 'region'
+# azure:
+#   auth_type: 'sas'
+#   container_url: 'container_url'
+#   sas_token: 'sas_token'
+# azure:
+#   auth_type: 'spn'
+#   account_url: 'account_url'
+#   client_id: 'client_id'
+#   secret: 'secret'
+#   tenant_id: 'tenant_id'
+#   container_name: 'container_name'
+# user_default_llm:
+#   factory: 'Tongyi-Qianwen'
+#   api_key: 'sk-xxxxxxxxxxxxx'
+#   base_url: ''
+# oauth:
+#   github:
+#     client_id: xxxxxxxxxxxxxxxxxxxxxxxxx
+#     secret_key: xxxxxxxxxxxxxxxxxxxxxxxxxxxx
+#     url: https://github.com/login/oauth/access_token
+#   feishu:
+#     app_id: cli_xxxxxxxxxxxxxxxxxxx
+#     app_secret: xxxxxxxxxxxxxxxxxxxxxxxxxxxx
+#     app_access_token_url: https://open.feishu.cn/open-apis/auth/v3/app_access_token/internal
+#     user_access_token_url: https://open.feishu.cn/open-apis/authen/v1/oidc/access_token
+#     grant_type: 'authorization_code'
+# authentication:
+#   client:
+#     switch: false
+#     http_app_key:
+#     http_secret_key:
+#   site:
+#     switch: false
+# permission:
+#   switch: false
+#   component: false
+#   dataset: false

deepdoc/parser/docx_parser.py

@@ -110,7 +110,7 @@ class RAGFlowDocxParser:
             return lines
         return ["\n".join(lines)]
 
-    def __call__(self, fnm, from_page=0, to_page=100000):
+    def __call__(self, fnm, from_page=0, to_page=100000000):
         self.doc = Document(fnm) if isinstance(
             fnm, str) else Document(BytesIO(fnm))
         pn = 0 # parsed page
@@ -130,7 +130,7 @@ class RAGFlowDocxParser:
                 if 'lastRenderedPageBreak' in run._element.xml:
                     pn += 1
 
-            secs.append(("".join(runs_within_single_paragraph), p.style.name)) # then concat run.text as part of the paragraph
+            secs.append(("".join(runs_within_single_paragraph), p.style.name if hasattr(p.style, 'name') else '')) # then concat run.text as part of the paragraph
 
         tbls = [self.__extract_table_content(tb) for tb in self.doc.tables]
         return secs, tbls

deepdoc/parser/html_parser.py

@@ -16,11 +16,13 @@ import readability
 import html_text
 import chardet
 
+
 def get_encoding(file):
     with open(file,'rb') as f:
         tmp = chardet.detect(f.read())
         return tmp['encoding']
 
+
 class RAGFlowHtmlParser:
     def __call__(self, fnm, binary=None):
         txt = ""

deepdoc/parser/json_parser.py

@@ -3,12 +3,11 @@
 # from https://github.com/langchain-ai/langchain/blob/master/libs/text-splitters/langchain_text_splitters/json.py
 
 import json
-from typing import Any, Dict, List, Optional
+from typing import Any
 from rag.nlp import find_codec
-
 class RAGFlowJsonParser:
     def __init__(
-        self, max_chunk_size: int = 2000, min_chunk_size: Optional[int] = None
+        self, max_chunk_size: int = 2000, min_chunk_size: int | None = None
     ):
         super().__init__()
         self.max_chunk_size = max_chunk_size * 2
@@ -27,12 +26,12 @@ class RAGFlowJsonParser:
         return sections
 
     @staticmethod
-    def _json_size(data: Dict) -> int:
+    def _json_size(data: dict) -> int:
         """Calculate the size of the serialized JSON object."""
         return len(json.dumps(data, ensure_ascii=False))
 
     @staticmethod
-    def _set_nested_dict(d: Dict, path: List[str], value: Any) -> None:
+    def _set_nested_dict(d: dict, path: list[str], value: Any) -> None:
         """Set a value in a nested dictionary based on the given path."""
         for key in path[:-1]:
             d = d.setdefault(key, {})
@@ -54,10 +53,10 @@ class RAGFlowJsonParser:
         
     def _json_split(
         self,
-        data: Dict[str, Any],
-        current_path: Optional[List[str]] = None,
-        chunks: Optional[List[Dict]] = None,
-    ) -> List[Dict]:
+        data: dict[str, Any],
+        current_path: list[str] | None,
+        chunks: list[dict] | None,
+    ) -> list[dict]:
         """
         Split json into maximum size dictionaries while preserving structure.
         """
@@ -87,9 +86,9 @@ class RAGFlowJsonParser:
 
     def split_json(
         self,
-        json_data: Dict[str, Any],
+        json_data: dict[str, Any],
         convert_lists: bool = False,
-    ) -> List[Dict]:
+    ) -> list[dict]:
         """Splits JSON into a list of JSON chunks"""
 
         if convert_lists:
@@ -104,10 +103,10 @@ class RAGFlowJsonParser:
 
     def split_text(
         self,
-        json_data: Dict[str, Any],
+        json_data: dict[str, Any],
         convert_lists: bool = False,
         ensure_ascii: bool = True,
-    ) -> List[str]:
+    ) -> list[str]:
         """Splits JSON into a list of JSON formatted strings"""
 
         chunks = self.split_json(json_data=json_data, convert_lists=convert_lists)