mirror of
https://github.com/infiniflow/ragflow.git
synced 2025-12-08 20:42:30 +08:00
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12
.github/ISSUE_TEMPLATE/bug_report.yml
vendored
12
.github/ISSUE_TEMPLATE/bug_report.yml
vendored
@ -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
|
||||
|
||||
124
.github/workflows/release.yml
vendored
Normal file
124
.github/workflows/release.yml
vendored
Normal file
@ -0,0 +1,124 @@
|
||||
name: release
|
||||
|
||||
on:
|
||||
schedule:
|
||||
- cron: '0 13 * * *' # This schedule runs every 13:00:00Z(21:00:00+08:00)
|
||||
# The "create tags" trigger is specifically focused on the creation of new tags, while the "push tags" trigger is activated when tags are pushed, including both new tag creations and updates to existing tags.
|
||||
create:
|
||||
tags:
|
||||
- "v*.*.*" # normal release
|
||||
- "nightly" # the only one mutable tag
|
||||
|
||||
# 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:
|
||||
release:
|
||||
runs-on: [ "self-hosted", "overseas" ]
|
||||
steps:
|
||||
- name: Ensure workspace ownership
|
||||
run: echo "chown -R $USER $GITHUB_WORKSPACE" && sudo chown -R $USER $GITHUB_WORKSPACE
|
||||
|
||||
# https://github.com/actions/checkout/blob/v3/README.md
|
||||
- name: Check out code
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
token: ${{ secrets.MY_GITHUB_TOKEN }} # Use the secret as an environment variable
|
||||
fetch-depth: 0
|
||||
fetch-tags: true
|
||||
|
||||
- name: Prepare release body
|
||||
run: |
|
||||
if [[ $GITHUB_EVENT_NAME == 'create' ]]; then
|
||||
RELEASE_TAG=${GITHUB_REF#refs/tags/}
|
||||
if [[ $RELEASE_TAG == 'nightly' ]]; then
|
||||
PRERELEASE=true
|
||||
else
|
||||
PRERELEASE=false
|
||||
fi
|
||||
echo "Workflow triggered by create tag: $RELEASE_TAG"
|
||||
else
|
||||
RELEASE_TAG=nightly
|
||||
PRERELEASE=true
|
||||
echo "Workflow triggered by schedule"
|
||||
fi
|
||||
echo "RELEASE_TAG=$RELEASE_TAG" >> $GITHUB_ENV
|
||||
echo "PRERELEASE=$PRERELEASE" >> $GITHUB_ENV
|
||||
RELEASE_DATETIME=$(date --rfc-3339=seconds)
|
||||
echo Release $RELEASE_TAG created from $GITHUB_SHA at $RELEASE_DATETIME > release_body.md
|
||||
|
||||
- name: Move the existing mutable tag
|
||||
# https://github.com/softprops/action-gh-release/issues/171
|
||||
run: |
|
||||
git fetch --tags
|
||||
if [[ $GITHUB_EVENT_NAME == 'schedule' ]]; then
|
||||
# Determine if a given tag exists and matches a specific Git commit.
|
||||
# actions/checkout@v4 fetch-tags doesn't work when triggered by schedule
|
||||
if [ "$(git rev-parse -q --verify "refs/tags/$RELEASE_TAG")" = "$GITHUB_SHA" ]; then
|
||||
echo "mutable tag $RELEASE_TAG exists and matches $GITHUB_SHA"
|
||||
else
|
||||
git tag -f $RELEASE_TAG $GITHUB_SHA
|
||||
git push -f origin $RELEASE_TAG:refs/tags/$RELEASE_TAG
|
||||
echo "created/moved mutable tag $RELEASE_TAG to $GITHUB_SHA"
|
||||
fi
|
||||
fi
|
||||
|
||||
- name: Create or overwrite a release
|
||||
# https://github.com/actions/upload-release-asset has been replaced by https://github.com/softprops/action-gh-release
|
||||
uses: softprops/action-gh-release@v2
|
||||
with:
|
||||
token: ${{ secrets.MY_GITHUB_TOKEN }} # Use the secret as an environment variable
|
||||
prerelease: ${{ env.PRERELEASE }}
|
||||
tag_name: ${{ env.RELEASE_TAG }}
|
||||
# The body field does not support environment variable substitution directly.
|
||||
body_path: release_body.md
|
||||
|
||||
- name: Set up QEMU
|
||||
uses: docker/setup-qemu-action@v3
|
||||
|
||||
- name: Set up Docker Buildx
|
||||
uses: docker/setup-buildx-action@v3
|
||||
|
||||
# https://github.com/marketplace/actions/docker-login
|
||||
- name: Login to Docker Hub
|
||||
uses: docker/login-action@v3
|
||||
with:
|
||||
username: infiniflow
|
||||
password: ${{ secrets.DOCKERHUB_TOKEN }}
|
||||
|
||||
# https://github.com/marketplace/actions/build-and-push-docker-images
|
||||
- name: Build and push full image
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
tags: infiniflow/ragflow:${{ env.RELEASE_TAG }}
|
||||
file: Dockerfile
|
||||
platforms: linux/amd64
|
||||
|
||||
# https://github.com/marketplace/actions/build-and-push-docker-images
|
||||
- name: Build and push slim image
|
||||
uses: docker/build-push-action@v6
|
||||
with:
|
||||
context: .
|
||||
push: true
|
||||
tags: infiniflow/ragflow:${{ env.RELEASE_TAG }}-slim
|
||||
file: Dockerfile
|
||||
build-args: LIGHTEN=1
|
||||
platforms: linux/amd64
|
||||
|
||||
- name: Build ragflow-sdk
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
run: |
|
||||
cd sdk/python && \
|
||||
poetry build
|
||||
|
||||
- name: Publish package distributions to PyPI
|
||||
if: startsWith(github.ref, 'refs/tags/v')
|
||||
uses: pypa/gh-action-pypi-publish@release/v1
|
||||
with:
|
||||
packages-dir: dist/
|
||||
password: ${{ secrets.PYPI_API_TOKEN }}
|
||||
verbose: true
|
||||
77
.github/workflows/tests.yml
vendored
77
.github/workflows/tests.yml
vendored
@ -42,35 +42,46 @@ jobs:
|
||||
- name: Ensure workspace ownership
|
||||
run: echo "chown -R $USER $GITHUB_WORKSPACE" && sudo chown -R $USER $GITHUB_WORKSPACE
|
||||
|
||||
# https://github.com/actions/checkout/issues/1781
|
||||
- name: Check out code
|
||||
uses: actions/checkout@v4
|
||||
with:
|
||||
fetch-depth: 0
|
||||
fetch-tags: true
|
||||
|
||||
- name: Build ragflow:dev-slim
|
||||
# https://github.com/astral-sh/ruff-action
|
||||
- name: Static check with Ruff
|
||||
uses: astral-sh/ruff-action@v2
|
||||
with:
|
||||
version: ">=0.8.2"
|
||||
args: "check --ignore E402"
|
||||
|
||||
- name: Build ragflow:nightly-slim
|
||||
run: |
|
||||
RUNNER_WORKSPACE_PREFIX=${RUNNER_WORKSPACE_PREFIX:-$HOME}
|
||||
cp -r ${RUNNER_WORKSPACE_PREFIX}/huggingface.co ${RUNNER_WORKSPACE_PREFIX}/nltk_data ${RUNNER_WORKSPACE_PREFIX}/libssl*.deb .
|
||||
sudo docker pull ubuntu:24.04
|
||||
sudo docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
|
||||
sudo docker pull ubuntu:22.04
|
||||
sudo docker build --progress=plain --build-arg LIGHTEN=1 --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
|
||||
|
||||
- name: Build ragflow:dev
|
||||
- name: Build ragflow:nightly
|
||||
run: |
|
||||
sudo docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
sudo docker build --progress=plain --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:nightly .
|
||||
|
||||
- name: Start ragflow:dev-slim
|
||||
- name: Start ragflow:nightly-slim
|
||||
run: |
|
||||
echo "RAGFLOW_IMAGE=infiniflow/ragflow:nightly-slim" >> docker/.env
|
||||
sudo docker compose -f docker/docker-compose.yml up -d
|
||||
|
||||
- name: Stop ragflow:dev-slim
|
||||
- name: Stop ragflow:nightly-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
|
||||
- name: Start ragflow:nightly
|
||||
run: |
|
||||
echo "RAGFLOW_IMAGE=infiniflow/ragflow:dev" >> docker/.env
|
||||
echo "RAGFLOW_IMAGE=infiniflow/ragflow:nightly" >> docker/.env
|
||||
sudo docker compose -f docker/docker-compose.yml up -d
|
||||
|
||||
- name: Run tests
|
||||
- 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
|
||||
@ -78,9 +89,49 @@ jobs:
|
||||
echo "Waiting for service to be available..."
|
||||
sleep 5
|
||||
done
|
||||
cd sdk/python && poetry install && source .venv/bin/activate && cd test && pytest t_dataset.py t_chat.py t_session.py
|
||||
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: Stop ragflow:dev
|
||||
- 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:nightly
|
||||
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:nightly
|
||||
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 ${HOST_ADDRESS} > /dev/null; do
|
||||
echo "Waiting for service to be available..."
|
||||
sleep 5
|
||||
done
|
||||
cd sdk/python && poetry install && source .venv/bin/activate && cd test/test_frontend_api && pytest -s --tb=short get_email.py test_dataset.py
|
||||
|
||||
- name: Stop ragflow:nightly
|
||||
if: always() # always run this step even if previous steps failed
|
||||
run: |
|
||||
sudo DOC_ENGINE=infinity docker compose -f docker/docker-compose.yml down -v
|
||||
|
||||
4
.gitignore
vendored
4
.gitignore
vendored
@ -35,4 +35,6 @@ rag/res/deepdoc
|
||||
sdk/python/ragflow.egg-info/
|
||||
sdk/python/build/
|
||||
sdk/python/dist/
|
||||
sdk/python/ragflow_sdk.egg-info/
|
||||
sdk/python/ragflow_sdk.egg-info/
|
||||
huggingface.co/
|
||||
nltk_data/
|
||||
|
||||
206
Dockerfile
206
Dockerfile
@ -1,78 +1,177 @@
|
||||
# base stage
|
||||
FROM ubuntu:24.04 AS base
|
||||
FROM ubuntu:22.04 AS base
|
||||
USER root
|
||||
SHELL ["/bin/bash", "-c"]
|
||||
|
||||
ARG ARCH=amd64
|
||||
ENV LIGHTEN=0
|
||||
ARG NEED_MIRROR=0
|
||||
ARG LIGHTEN=0
|
||||
ENV LIGHTEN=${LIGHTEN}
|
||||
|
||||
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
|
||||
# Copy models downloaded via download_deps.py
|
||||
RUN mkdir -p /ragflow/rag/res/deepdoc /root/.ragflow
|
||||
RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/huggingface.co,target=/huggingface.co \
|
||||
cp /huggingface.co/InfiniFlow/huqie/huqie.txt.trie /ragflow/rag/res/ && \
|
||||
tar --exclude='.*' -cf - \
|
||||
/huggingface.co/InfiniFlow/text_concat_xgb_v1.0 \
|
||||
/huggingface.co/InfiniFlow/deepdoc \
|
||||
| tar -xf - --strip-components=3 -C /ragflow/rag/res/deepdoc
|
||||
RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/huggingface.co,target=/huggingface.co \
|
||||
if [ "$LIGHTEN" != "1" ]; then \
|
||||
(tar -cf - \
|
||||
/huggingface.co/BAAI/bge-large-zh-v1.5 \
|
||||
/huggingface.co/BAAI/bge-reranker-v2-m3 \
|
||||
/huggingface.co/maidalun1020/bce-embedding-base_v1 \
|
||||
/huggingface.co/maidalun1020/bce-reranker-base_v1 \
|
||||
| tar -xf - --strip-components=2 -C /root/.ragflow) \
|
||||
fi
|
||||
|
||||
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
|
||||
# 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.
|
||||
RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/,target=/deps \
|
||||
cp -r /deps/nltk_data /root/ && \
|
||||
cp /deps/tika-server-standard-3.0.0.jar /deps/tika-server-standard-3.0.0.jar.md5 /ragflow/ && \
|
||||
cp /deps/cl100k_base.tiktoken /ragflow/9b5ad71b2ce5302211f9c61530b329a4922fc6a4
|
||||
|
||||
# If you download Python modules too slow, you can use a pip mirror site to speed up apt and poetry
|
||||
RUN sed -i 's|http://archive.ubuntu.com|https://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list.d/ubuntu.sources
|
||||
ENV POETRY_PYPI_MIRROR_URL=https://pypi.tuna.tsinghua.edu.cn/simple/
|
||||
ENV TIKA_SERVER_JAR="file:///ragflow/tika-server-standard-3.0.0.jar"
|
||||
ENV DEBIAN_FRONTEND=noninteractive
|
||||
|
||||
RUN --mount=type=cache,id=ragflow_base_apt,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 python3-pip python3-poetry \
|
||||
&& pip3 install --user --break-system-packages poetry-plugin-pypi-mirror --index-url https://pypi.tuna.tsinghua.edu.cn/simple/ \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
# Setup apt
|
||||
# Python package and implicit dependencies:
|
||||
# opencv-python: libglib2.0-0 libglx-mesa0 libgl1
|
||||
# aspose-slides: pkg-config libicu-dev libgdiplus libssl1.1_1.1.1f-1ubuntu2_amd64.deb
|
||||
# python-pptx: default-jdk tika-server-standard-3.0.0.jar
|
||||
# selenium: libatk-bridge2.0-0 chrome-linux64-121-0-6167-85
|
||||
# Building C extensions: libpython3-dev libgtk-4-1 libnss3 xdg-utils libgbm-dev
|
||||
RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
|
||||
if [ "$NEED_MIRROR" == "1" ]; then \
|
||||
sed -i 's|http://archive.ubuntu.com|https://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list; \
|
||||
fi; \
|
||||
rm -f /etc/apt/apt.conf.d/docker-clean && \
|
||||
echo 'Binary::apt::APT::Keep-Downloaded-Packages "true";' > /etc/apt/apt.conf.d/keep-cache && \
|
||||
chmod 1777 /tmp && \
|
||||
apt update && \
|
||||
apt --no-install-recommends install -y ca-certificates && \
|
||||
apt update && \
|
||||
apt install -y libglib2.0-0 libglx-mesa0 libgl1 && \
|
||||
apt install -y pkg-config libicu-dev libgdiplus && \
|
||||
apt install -y default-jdk && \
|
||||
apt install -y libatk-bridge2.0-0 && \
|
||||
apt install -y libpython3-dev libgtk-4-1 libnss3 xdg-utils libgbm-dev && \
|
||||
apt install -y python3-pip pipx nginx unzip curl wget git vim less
|
||||
|
||||
# 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 \
|
||||
if [ "${ARCH}" = "amd64" ]; then \
|
||||
dpkg -i /root/libssl1.1_1.1.1f-1ubuntu2_amd64.deb; \
|
||||
RUN if [ "$NEED_MIRROR" == "1" ]; then \
|
||||
pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && \
|
||||
pip3 config set global.trusted-host pypi.tuna.tsinghua.edu.cn; \
|
||||
fi; \
|
||||
pipx install poetry; \
|
||||
if [ "$NEED_MIRROR" == "1" ]; then \
|
||||
pipx inject poetry poetry-plugin-pypi-mirror; \
|
||||
fi
|
||||
|
||||
ENV PYTHONDONTWRITEBYTECODE=1 DOTNET_SYSTEM_GLOBALIZATION_INVARIANT=1
|
||||
|
||||
ENV PATH=/root/.local/bin:$PATH
|
||||
# Configure Poetry
|
||||
ENV POETRY_NO_INTERACTION=1
|
||||
ENV POETRY_VIRTUALENVS_IN_PROJECT=true
|
||||
ENV POETRY_VIRTUALENVS_CREATE=true
|
||||
ENV POETRY_REQUESTS_TIMEOUT=15
|
||||
|
||||
# nodejs 12.22 on Ubuntu 22.04 is too old
|
||||
RUN --mount=type=cache,id=ragflow_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
|
||||
|
||||
|
||||
# Add msssql ODBC driver
|
||||
# macOS ARM64 environment, install msodbcsql18.
|
||||
# general x86_64 environment, install msodbcsql17.
|
||||
RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
|
||||
curl https://packages.microsoft.com/keys/microsoft.asc | apt-key add - && \
|
||||
curl https://packages.microsoft.com/config/ubuntu/22.04/prod.list > /etc/apt/sources.list.d/mssql-release.list && \
|
||||
apt update && \
|
||||
if [ -n "$ARCH" ] && [ "$ARCH" = "arm64" ]; then \
|
||||
# MacOS ARM64
|
||||
ACCEPT_EULA=Y apt install -y unixodbc-dev msodbcsql18; \
|
||||
else \
|
||||
# (x86_64)
|
||||
ACCEPT_EULA=Y apt install -y unixodbc-dev msodbcsql17; \
|
||||
fi || \
|
||||
{ echo "Failed to install ODBC driver"; exit 1; }
|
||||
|
||||
|
||||
|
||||
# Add dependencies of selenium
|
||||
RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,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,from=infiniflow/ragflow_deps:latest,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
|
||||
|
||||
# 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,from=infiniflow/ragflow_deps:latest,source=/,target=/deps \
|
||||
if [ "$(uname -m)" = "x86_64" ]; then \
|
||||
dpkg -i /deps/libssl1.1_1.1.1f-1ubuntu2_amd64.deb; \
|
||||
elif [ "$(uname -m)" = "aarch64" ]; then \
|
||||
dpkg -i /deps/libssl1.1_1.1.1f-1ubuntu2_arm64.deb; \
|
||||
fi
|
||||
|
||||
|
||||
# builder stage
|
||||
FROM base AS builder
|
||||
USER root
|
||||
|
||||
WORKDIR /ragflow
|
||||
|
||||
RUN --mount=type=cache,id=ragflow_builder_apt,target=/var/cache/apt,sharing=locked \
|
||||
apt update && apt install -y nodejs npm cargo && \
|
||||
rm -rf /var/lib/apt/lists/*
|
||||
|
||||
COPY web web
|
||||
COPY docs docs
|
||||
RUN --mount=type=cache,id=ragflow_builder_npm,target=/root/.npm,sharing=locked \
|
||||
cd web && npm i --force && npm run build
|
||||
|
||||
# install dependencies from poetry.lock file
|
||||
COPY pyproject.toml poetry.toml poetry.lock ./
|
||||
|
||||
RUN --mount=type=cache,id=ragflow_builder_poetry,target=/root/.cache/pypoetry,sharing=locked \
|
||||
if [ "$LIGHTEN" -eq 0 ]; then \
|
||||
poetry install --sync --no-root --with=full; \
|
||||
RUN --mount=type=cache,id=ragflow_poetry,target=/root/.cache/pypoetry,sharing=locked \
|
||||
if [ "$NEED_MIRROR" == "1" ]; then \
|
||||
export POETRY_PYPI_MIRROR_URL=https://pypi.tuna.tsinghua.edu.cn/simple/; \
|
||||
fi; \
|
||||
if [ "$LIGHTEN" == "1" ]; then \
|
||||
poetry install --no-root; \
|
||||
else \
|
||||
poetry install --sync --no-root; \
|
||||
poetry install --no-root --with=full; \
|
||||
fi
|
||||
|
||||
COPY web web
|
||||
COPY docs docs
|
||||
RUN --mount=type=cache,id=ragflow_npm,target=/root/.npm,sharing=locked \
|
||||
cd web && npm install --force && npm run build
|
||||
|
||||
COPY .git /ragflow/.git
|
||||
|
||||
RUN version_info=$(git describe --tags --match=v* --first-parent --always); \
|
||||
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
|
||||
|
||||
# production stage
|
||||
FROM base AS production
|
||||
USER root
|
||||
|
||||
WORKDIR /ragflow
|
||||
|
||||
# Install python packages' dependencies
|
||||
# cv2 requires libGL.so.1
|
||||
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/*
|
||||
# Copy Python environment and packages
|
||||
ENV VIRTUAL_ENV=/ragflow/.venv
|
||||
COPY --from=builder ${VIRTUAL_ENV} ${VIRTUAL_ENV}
|
||||
ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"
|
||||
|
||||
ENV PYTHONPATH=/ragflow/
|
||||
|
||||
COPY web web
|
||||
COPY api api
|
||||
@ -83,35 +182,12 @@ COPY agent agent
|
||||
COPY graphrag graphrag
|
||||
COPY pyproject.toml poetry.toml poetry.lock ./
|
||||
|
||||
# Copy models downloaded via download_deps.py
|
||||
RUN mkdir -p /ragflow/rag/res/deepdoc /root/.ragflow
|
||||
RUN --mount=type=bind,source=huggingface.co,target=/huggingface.co \
|
||||
tar --exclude='.*' -cf - \
|
||||
/huggingface.co/InfiniFlow/text_concat_xgb_v1.0 \
|
||||
/huggingface.co/InfiniFlow/deepdoc \
|
||||
| tar -xf - --strip-components=3 -C /ragflow/rag/res/deepdoc
|
||||
RUN --mount=type=bind,source=huggingface.co,target=/huggingface.co \
|
||||
tar -cf - \
|
||||
/huggingface.co/BAAI/bge-large-zh-v1.5 \
|
||||
/huggingface.co/BAAI/bge-reranker-v2-m3 \
|
||||
/huggingface.co/maidalun1020/bce-embedding-base_v1 \
|
||||
/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
|
||||
COPY docker/service_conf.yaml.template ./conf/service_conf.yaml.template
|
||||
COPY docker/entrypoint.sh ./entrypoint.sh
|
||||
RUN chmod +x ./entrypoint.sh
|
||||
|
||||
# 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:${PATH}"
|
||||
|
||||
ENV PYTHONPATH=/ragflow/
|
||||
|
||||
COPY docker/entrypoint.sh ./entrypoint.sh
|
||||
RUN chmod +x ./entrypoint.sh
|
||||
|
||||
COPY --from=builder /ragflow/VERSION /ragflow/VERSION
|
||||
ENTRYPOINT ["./entrypoint.sh"]
|
||||
|
||||
10
Dockerfile.deps
Normal file
10
Dockerfile.deps
Normal file
@ -0,0 +1,10 @@
|
||||
# This builds an image that contains the resources needed by Dockerfile
|
||||
#
|
||||
FROM scratch
|
||||
|
||||
# Copy resources downloaded via download_deps.py
|
||||
COPY chromedriver-linux64-121-0-6167-85 chrome-linux64-121-0-6167-85 cl100k_base.tiktoken libssl1.1_1.1.1f-1ubuntu2_amd64.deb libssl1.1_1.1.1f-1ubuntu2_arm64.deb tika-server-standard-3.0.0.jar tika-server-standard-3.0.0.jar.md5 libssl*.deb /
|
||||
|
||||
COPY nltk_data /nltk_data
|
||||
|
||||
COPY huggingface.co /huggingface.co
|
||||
@ -53,6 +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
|
||||
|
||||
|
||||
109
Dockerfile.slim
109
Dockerfile.slim
@ -1,109 +0,0 @@
|
||||
# base stage
|
||||
FROM ubuntu:24.04 AS base
|
||||
USER root
|
||||
|
||||
ARG ARCH=amd64
|
||||
ENV LIGHTEN=1
|
||||
|
||||
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,id=ragflow_base_apt,target=/var/cache/apt,sharing=locked \
|
||||
apt update && apt-get --no-install-recommends install -y ca-certificates
|
||||
|
||||
# If you download Python modules too slow, you can use a pip mirror site to speed up apt and poetry
|
||||
RUN sed -i 's|http://archive.ubuntu.com|https://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list.d/ubuntu.sources
|
||||
ENV POETRY_PYPI_MIRROR_URL=https://pypi.tuna.tsinghua.edu.cn/simple/
|
||||
|
||||
RUN --mount=type=cache,id=ragflow_base_apt,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 python3-pip python3-poetry \
|
||||
&& pip3 install --user --break-system-packages poetry-plugin-pypi-mirror --index-url https://pypi.tuna.tsinghua.edu.cn/simple/ \
|
||||
&& rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# 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 if [ "${ARCH}" = "amd64" ]; then \
|
||||
curl -o libssl1.deb http://archive.ubuntu.com/ubuntu/pool/main/o/openssl/libssl1.1_1.1.1f-1ubuntu2_amd64.deb && dpkg -i libssl1.deb && rm -f libssl1.deb; \
|
||||
fi
|
||||
|
||||
ENV PYTHONDONTWRITEBYTECODE=1 DOTNET_SYSTEM_GLOBALIZATION_INVARIANT=1
|
||||
|
||||
# Configure Poetry
|
||||
ENV POETRY_NO_INTERACTION=1
|
||||
ENV POETRY_VIRTUALENVS_IN_PROJECT=true
|
||||
ENV POETRY_VIRTUALENVS_CREATE=true
|
||||
ENV POETRY_REQUESTS_TIMEOUT=15
|
||||
|
||||
# builder stage
|
||||
FROM base AS builder
|
||||
USER root
|
||||
|
||||
WORKDIR /ragflow
|
||||
|
||||
RUN --mount=type=cache,id=ragflow_builder_apt,target=/var/cache/apt,sharing=locked \
|
||||
apt update && apt install -y nodejs npm cargo && \
|
||||
rm -rf /var/lib/apt/lists/*
|
||||
|
||||
COPY web web
|
||||
COPY docs docs
|
||||
RUN --mount=type=cache,id=ragflow_builder_npm,target=/root/.npm,sharing=locked \
|
||||
cd web && npm i && npm run build
|
||||
|
||||
# install dependencies from poetry.lock file
|
||||
COPY pyproject.toml poetry.toml poetry.lock ./
|
||||
|
||||
RUN --mount=type=cache,id=ragflow_builder_poetry,target=/root/.cache/pypoetry,sharing=locked \
|
||||
if [ "$LIGHTEN" -eq 0 ]; then \
|
||||
poetry install --sync --no-root --with=full; \
|
||||
else \
|
||||
poetry install --sync --no-root; \
|
||||
fi
|
||||
|
||||
# production stage
|
||||
FROM base AS production
|
||||
USER root
|
||||
|
||||
WORKDIR /ragflow
|
||||
|
||||
# Install python packages' dependencies
|
||||
# cv2 requires libGL.so.1
|
||||
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/*
|
||||
|
||||
COPY web web
|
||||
COPY api api
|
||||
COPY conf conf
|
||||
COPY deepdoc deepdoc
|
||||
COPY rag rag
|
||||
COPY agent agent
|
||||
COPY graphrag graphrag
|
||||
COPY pyproject.toml poetry.toml poetry.lock ./
|
||||
|
||||
# Copy models downloaded via download_deps.py
|
||||
RUN mkdir -p /ragflow/rag/res/deepdoc /root/.ragflow
|
||||
RUN --mount=type=bind,source=huggingface.co,target=/huggingface.co \
|
||||
tar --exclude='.*' -cf - \
|
||||
/huggingface.co/InfiniFlow/text_concat_xgb_v1.0 \
|
||||
/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
|
||||
|
||||
# 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:${PATH}"
|
||||
|
||||
ENV PYTHONPATH=/ragflow/
|
||||
|
||||
COPY docker/entrypoint.sh ./entrypoint.sh
|
||||
RUN chmod +x ./entrypoint.sh
|
||||
|
||||
ENTRYPOINT ["./entrypoint.sh"]
|
||||
103
README.md
103
README.md
@ -8,7 +8,8 @@
|
||||
<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">
|
||||
@ -19,7 +20,7 @@
|
||||
<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:v0.13.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.13.0">
|
||||
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.15.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.15.0">
|
||||
</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">
|
||||
@ -69,14 +70,15 @@ data.
|
||||
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.
|
||||
- 2024-09-13 Adds search mode for knowledge base Q&A.
|
||||
- 2024-09-09 Adds a medical consultant agent template.
|
||||
- 2024-12-18 Upgrades Document Layout Analysis model in Deepdoc.
|
||||
- 2024-12-04 Adds support for pagerank score in knowledge base.
|
||||
- 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.
|
||||
- 2024-08-22 Support text to SQL statements through RAG.
|
||||
- 2024-08-02 Supports GraphRAG inspired by [graphrag](https://github.com/microsoft/graphrag) and mind map.
|
||||
|
||||
@ -164,29 +166,21 @@ releases! 🌟
|
||||
$ git clone https://github.com/infiniflow/ragflow.git
|
||||
```
|
||||
|
||||
3. Build the pre-built Docker images and start up the server:
|
||||
3. Start up the server using the pre-built Docker images:
|
||||
|
||||
> 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.
|
||||
> The command below downloads the `v0.15.0-slim` edition of the RAGFlow Docker image. Refer to the following table for descriptions of different RAGFlow editions. To download an RAGFlow edition different from `v0.14.1-slim`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server. For example: set `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1` for the full edition `v0.14.1`.
|
||||
|
||||
```bash
|
||||
$ cd ragflow/docker
|
||||
$ docker compose -f docker-compose.yml up -d
|
||||
$ cd ragflow
|
||||
$ docker compose -f docker/docker-compose.yml up -d
|
||||
```
|
||||
|
||||
> - 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:v0.13.0-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:v0.13.0`. 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.
|
||||
| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
|
||||
| ----------------- | --------------- | --------------------- | ------------------------ |
|
||||
| v0.15.0 | ≈9 | :heavy_check_mark: | Stable release |
|
||||
| v0.15.0-slim | ≈2 | ❌ | Stable release |
|
||||
| nightly | ≈9 | :heavy_check_mark: | *Unstable* nightly build |
|
||||
| nightly-slim | ≈2 | ❌ | *Unstable* nightly build |
|
||||
|
||||
4. Check the server status after having the server up and running:
|
||||
|
||||
@ -209,13 +203,13 @@ releases! 🌟
|
||||
* 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`
|
||||
> 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
|
||||
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.
|
||||
@ -228,17 +222,11 @@ When it comes to system configurations, you will need to manage the following fi
|
||||
|
||||
- [.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.
|
||||
- [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.
|
||||
- [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.
|
||||
|
||||
> 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.
|
||||
> configurations which can be used as `${ENV_VARS}` in the [service_conf.yaml.template](./docker/service_conf.yaml.template) 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`.
|
||||
@ -249,16 +237,35 @@ Updates to the above configurations require a reboot of all containers to take e
|
||||
> $ docker compose -f docker/docker-compose.yml up -d
|
||||
> ```
|
||||
|
||||
### 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.
|
||||
This image is approximately 2 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 nltk
|
||||
python3 download_deps.py
|
||||
docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
|
||||
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
|
||||
```
|
||||
|
||||
## 🔧 Build a Docker image including embedding models
|
||||
@ -268,24 +275,22 @@ This image is approximately 9 GB in size. As it includes embedding models, it re
|
||||
```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 .
|
||||
docker build -f Dockerfile -t infiniflow/ragflow:nightly .
|
||||
```
|
||||
|
||||
## 🔨 Launch service from source for development
|
||||
|
||||
1. Install Poetry, or skip this step if it is already installed:
|
||||
```bash
|
||||
curl -sSL https://install.python-poetry.org | python3 -
|
||||
pipx install poetry
|
||||
export POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true
|
||||
```
|
||||
|
||||
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:
|
||||
@ -293,11 +298,10 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
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**.
|
||||
|
||||
4. If you cannot access HuggingFace, set the `HF_ENDPOINT` environment variable to use a mirror site:
|
||||
|
||||
@ -317,8 +321,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
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:
|
||||
7. Launch frontend service:
|
||||
```bash
|
||||
npm run dev
|
||||
```
|
||||
|
||||
322
README_id.md
Normal file
322
README_id.md
Normal file
@ -0,0 +1,322 @@
|
||||
<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:v0.15.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.15.0">
|
||||
</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
|
||||
|
||||
- 2024-12-18 Meningkatkan model Analisis Tata Letak Dokumen di Deepdoc.
|
||||
- 2024-12-04 Mendukung skor pagerank ke basis pengetahuan.
|
||||
- 2024-11-22 Peningkatan definisi dan penggunaan variabel di Agen.
|
||||
- 2024-11-01 Penambahan ekstraksi kata kunci dan pembuatan pertanyaan terkait untuk meningkatkan akurasi pengambilan.
|
||||
- 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 mengunduh edisi v0.15.0-slim dari gambar Docker RAGFlow. Silakan merujuk ke tabel berikut untuk deskripsi berbagai edisi RAGFlow. Untuk mengunduh edisi RAGFlow yang berbeda dari v0.14.1-slim, perbarui variabel RAGFLOW_IMAGE di docker/.env sebelum menggunakan docker compose untuk memulai server. Misalnya, atur RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1 untuk edisi lengkap v0.14.1.
|
||||
|
||||
```bash
|
||||
$ cd ragflow
|
||||
$ docker compose -f docker/docker-compose.yml up -d
|
||||
```
|
||||
|
||||
| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
|
||||
| ----------------- | --------------- | --------------------- | ------------------------ |
|
||||
| v0.15.0 | ≈9 | :heavy_check_mark: | Stable release |
|
||||
| v0.15.0-slim | ≈2 | ❌ | Stable release |
|
||||
| nightly | ≈9 | :heavy_check_mark: | *Unstable* nightly build |
|
||||
| nightly-slim | ≈2 | ❌ | *Unstable* nightly build |
|
||||
|
||||
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.template](./docker/service_conf.yaml.template), 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.template](./docker/service_conf.yaml.template): Mengonfigurasi aplikasi backend.
|
||||
- [docker-compose.yml](./docker/docker-compose.yml): Sistem ini bergantung pada [docker-compose.yml](./docker/docker-compose.yml) untuk memulai.
|
||||
|
||||
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 2 GB dan bergantung pada aplikasi LLM eksternal dan embedding.
|
||||
|
||||
```bash
|
||||
git clone https://github.com/infiniflow/ragflow.git
|
||||
cd ragflow/
|
||||
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-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/
|
||||
docker build -f Dockerfile -t infiniflow/ragflow:nightly .
|
||||
```
|
||||
|
||||
## 🔨 Menjalankan Aplikasi dari untuk Pengembangan
|
||||
|
||||
1. Instal Poetry, atau lewati langkah ini jika sudah terinstal:
|
||||
```bash
|
||||
pipx install poetry
|
||||
export POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true
|
||||
```
|
||||
|
||||
2. Clone kode sumber dan instal dependensi Python:
|
||||
```bash
|
||||
git clone https://github.com/infiniflow/ragflow.git
|
||||
cd ragflow/
|
||||
~/.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 **conf/service_conf.yaml** ke `127.0.0.1`:
|
||||
```
|
||||
127.0.0.1 es01 infinity mysql minio redis
|
||||
```
|
||||
|
||||
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. Jalankan aplikasi frontend:
|
||||
```bash
|
||||
npm run dev
|
||||
```
|
||||
|
||||
_Output berikut menandakan bahwa sistem berhasil diluncurkan:_
|
||||
|
||||

|
||||
|
||||
## 📚 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).
|
||||
76
README_ja.md
76
README_ja.md
@ -8,7 +8,8 @@
|
||||
<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">
|
||||
@ -19,7 +20,7 @@
|
||||
<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:v0.13.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.13.0">
|
||||
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.15.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.15.0">
|
||||
</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">
|
||||
@ -47,15 +48,16 @@
|
||||
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。
|
||||
- 2024-09-13 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。
|
||||
- 2024-12-18 Deepdoc のドキュメント レイアウト分析モデルをアップグレードします。
|
||||
- 2024-12-04 ナレッジ ベースへのページランク スコアをサポートしました。
|
||||
- 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。
|
||||
- 2024-08-22 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。
|
||||
|
||||
@ -140,18 +142,19 @@
|
||||
|
||||
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。
|
||||
> 以下のコマンドは、RAGFlow Dockerイメージの v0.15.0-slim エディションをダウンロードします。異なる RAGFlow エディションの説明については、以下の表を参照してください。v0.15.0-slim とは異なるエディションをダウンロードするには、docker/.env ファイルの RAGFLOW_IMAGE 変数を適宜更新し、docker compose を使用してサーバーを起動してください。例えば、完全版 v0.14.1 をダウンロードするには、RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1 と設定します。
|
||||
|
||||
```bash
|
||||
$ cd ragflow/docker
|
||||
$ docker compose -f docker-compose.yml up -d
|
||||
$ cd ragflow
|
||||
$ docker compose -f docker/docker-compose.yml up -d
|
||||
```
|
||||
|
||||
> - 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:v0.13.0`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:v0.13.0`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。
|
||||
| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
|
||||
| ----------------- | --------------- | --------------------- | ------------------------ |
|
||||
| v0.15.0 | ≈9 | :heavy_check_mark: | Stable release |
|
||||
| v0.15.0-slim | ≈2 | ❌ | Stable release |
|
||||
| nightly | ≈9 | :heavy_check_mark: | *Unstable* nightly build |
|
||||
| nightly-slim | ≈2 | ❌ | *Unstable* nightly build |
|
||||
|
||||
4. サーバーを立ち上げた後、サーバーの状態を確認する:
|
||||
|
||||
@ -177,7 +180,7 @@
|
||||
|
||||
5. ウェブブラウザで、プロンプトに従ってサーバーの IP アドレスを入力し、RAGFlow にログインします。
|
||||
> デフォルトの設定を使用する場合、デフォルトの HTTP サービングポート `80` は省略できるので、与えられたシナリオでは、`http://IP_OF_YOUR_MACHINE`(ポート番号は省略)だけを入力すればよい。
|
||||
6. [service_conf.yaml](./docker/service_conf.yaml) で、`user_default_llm` で希望の LLM ファクトリを選択し、`API_KEY` フィールドを対応する API キーで更新する。
|
||||
6. [service_conf.yaml.template](./docker/service_conf.yaml.template) で、`user_default_llm` で希望の LLM ファクトリを選択し、`API_KEY` フィールドを対応する API キーで更新する。
|
||||
|
||||
> 詳しくは [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) を参照してください。
|
||||
|
||||
@ -188,12 +191,12 @@
|
||||
システムコンフィグに関しては、以下のファイルを管理する必要がある:
|
||||
|
||||
- [.env](./docker/.env): `SVR_HTTP_PORT`、`MYSQL_PASSWORD`、`MINIO_PASSWORD` などのシステムの基本設定を保持する。
|
||||
- [service_conf.yaml](./docker/service_conf.yaml): バックエンドのサービスを設定します。
|
||||
- [service_conf.yaml.template](./docker/service_conf.yaml.template): バックエンドのサービスを設定します。
|
||||
- [docker-compose.yml](./docker/docker-compose.yml): システムの起動は [docker-compose.yml](./docker/docker-compose.yml) に依存している。
|
||||
|
||||
[.env](./docker/.env) ファイルの変更が [service_conf.yaml](./docker/service_conf.yaml) ファイルの内容と一致していることを確認する必要があります。
|
||||
[.env](./docker/.env) ファイルの変更が [service_conf.yaml.template](./docker/service_conf.yaml.template) ファイルの内容と一致していることを確認する必要があります。
|
||||
|
||||
> [./docker/README](./docker/README.md) ファイルは環境設定とサービスコンフィグの詳細な説明を提供し、[./docker/README](./docker/README.md) ファイルに記載されている全ての環境設定が [service_conf.yaml](./docker/service_conf.yaml) ファイルの対応するコンフィグと一致していることを確認することが義務付けられています。
|
||||
> [./docker/README](./docker/README.md) ファイル ./docker/README には、service_conf.yaml.template ファイルで ${ENV_VARS} として使用できる環境設定とサービス構成の詳細な説明が含まれています。
|
||||
|
||||
デフォルトの HTTP サービングポート(80)を更新するには、[docker-compose.yml](./docker/docker-compose.yml) にアクセスして、`80:80` を `<YOUR_SERVING_PORT>:80` に変更します。
|
||||
|
||||
@ -203,6 +206,23 @@
|
||||
> $ docker compose -f docker/docker-compose.yml up -d
|
||||
> ```
|
||||
|
||||
### 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。
|
||||
@ -210,9 +230,7 @@
|
||||
```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 .
|
||||
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-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)
|
||||
@ -222,23 +240,21 @@ docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
|
||||
```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 .
|
||||
docker build -f Dockerfile -t infiniflow/ragflow:nightly .
|
||||
```
|
||||
|
||||
## 🔨 ソースコードからサービスを起動する方法
|
||||
|
||||
1. Poetry をインストールする。すでにインストールされている場合は、このステップをスキップしてください:
|
||||
```bash
|
||||
curl -sSL https://install.python-poetry.org | python3 -
|
||||
pipx install poetry
|
||||
export POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true
|
||||
```
|
||||
|
||||
2. ソースコードをクローンし、Python の依存関係をインストールする:
|
||||
```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
|
||||
```
|
||||
|
||||
@ -247,11 +263,10 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
docker compose -f docker/docker-compose-base.yml up -d
|
||||
```
|
||||
|
||||
`/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:
|
||||
`/etc/hosts` に以下の行を追加して、**conf/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).
|
||||
|
||||
4. HuggingFace にアクセスできない場合は、`HF_ENDPOINT` 環境変数を設定してミラーサイトを使用してください:
|
||||
|
||||
@ -271,8 +286,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
cd web
|
||||
npm install --force
|
||||
```
|
||||
7. フロントエンドを設定し、**.umirc.ts** の `proxy.target` を `http://127.0.0.1:9380` に更新します:
|
||||
8. フロントエンドサービスを起動する:
|
||||
7. フロントエンドサービスを起動する:
|
||||
```bash
|
||||
npm run dev
|
||||
```
|
||||
|
||||
76
README_ko.md
76
README_ko.md
@ -9,6 +9,7 @@
|
||||
<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">
|
||||
@ -19,7 +20,7 @@
|
||||
<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:v0.13.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.13.0">
|
||||
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.15.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.15.0">
|
||||
</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">
|
||||
@ -49,17 +50,19 @@
|
||||
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.
|
||||
- 2024-12-18 Deepdoc의 문서 레이아웃 분석 모델 업그레이드.
|
||||
|
||||
- 2024-09-13 지식베이스 Q&A 검색 모드를 추가합니다.
|
||||
- 2024-12-04 지식베이스에 대한 페이지랭크 점수를 지원합니다.
|
||||
|
||||
- 2024-11-22 에이전트의 변수 정의 및 사용을 개선했습니다.
|
||||
|
||||
- 2024-09-09 Agent에 의료상담 템플릿을 추가하였습니다.
|
||||
- 2024-11-01 파싱된 청크에 키워드 추출 및 관련 질문 생성을 추가하여 재현율을 향상시킵니다.
|
||||
|
||||
- 2024-08-22 RAG를 통해 SQL 문에 텍스트를 지원합니다.
|
||||
|
||||
@ -144,19 +147,19 @@
|
||||
|
||||
3. 미리 빌드된 Docker 이미지를 생성하고 서버를 시작하세요:
|
||||
|
||||
> 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.
|
||||
> 아래 명령어는 RAGFlow Docker 이미지의 v0.15.0-slim 버전을 다운로드합니다. 다양한 RAGFlow 버전에 대한 설명은 다음 표를 참조하십시오. v0.15.0-slim과 다른 RAGFlow 버전을 다운로드하려면, docker/.env 파일에서 RAGFLOW_IMAGE 변수를 적절히 업데이트한 후 docker compose를 사용하여 서버를 시작하십시오. 예를 들어, 전체 버전인 v0.14.1을 다운로드하려면 RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1로 설정합니다.
|
||||
|
||||
```bash
|
||||
$ cd ragflow/docker
|
||||
$ docker compose -f docker-compose.yml up -d
|
||||
$ cd ragflow
|
||||
$ docker compose -f docker/docker-compose.yml up -d
|
||||
```
|
||||
|
||||
> - 특정 버전의 RAGFlow slim Docker 이미지를 다운로드하려면, **docker/.env**에서 `RAGFlow_IMAGE` 변수를 원하는 버전으로 업데이트하세요. 예를 들어, `RAGFLOW_IMAGE=infiniflow/ragflow:v0.13.0-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:v0.13.0` 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.
|
||||
|
||||
| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
|
||||
| ----------------- | --------------- | --------------------- | ------------------------ |
|
||||
| v0.15.0 | ≈9 | :heavy_check_mark: | Stable release |
|
||||
| v0.15.0-slim | ≈2 | ❌ | Stable release |
|
||||
| nightly | ≈9 | :heavy_check_mark: | *Unstable* nightly build |
|
||||
| nightly-slim | ≈2 | ❌ | *Unstable* nightly build |
|
||||
|
||||
4. 서버가 시작된 후 서버 상태를 확인하세요:
|
||||
|
||||
@ -178,11 +181,11 @@
|
||||
* 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.
|
||||
6. [service_conf.yaml](./docker/service_conf.yaml) 파일에서 원하는 LLM 팩토리를 `user_default_llm`에 선택하고, `API_KEY` 필드를 해당 API 키로 업데이트하세요.
|
||||
6. [service_conf.yaml.template](./docker/service_conf.yaml.template) 파일에서 원하는 LLM 팩토리를 `user_default_llm`에 선택하고, `API_KEY` 필드를 해당 API 키로 업데이트하세요.
|
||||
> 자세한 내용은 [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup)를 참조하세요.
|
||||
|
||||
_이제 쇼가 시작됩니다!_
|
||||
@ -192,12 +195,12 @@
|
||||
시스템 설정과 관련하여 다음 파일들을 관리해야 합니다:
|
||||
|
||||
- [.env](./docker/.env): `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, `MINIO_PASSWORD`와 같은 시스템의 기본 설정을 포함합니다.
|
||||
- [service_conf.yaml](./docker/service_conf.yaml): 백엔드 서비스를 구성합니다.
|
||||
- [service_conf.yaml.template](./docker/service_conf.yaml.template): 백엔드 서비스를 구성합니다.
|
||||
- [docker-compose.yml](./docker/docker-compose.yml): 시스템은 [docker-compose.yml](./docker/docker-compose.yml)을 사용하여 시작됩니다.
|
||||
|
||||
[.env](./docker/.env) 파일의 변경 사항이 [service_conf.yaml](./docker/service_conf.yaml) 파일의 내용과 일치하도록 해야 합니다.
|
||||
[.env](./docker/.env) 파일의 변경 사항이 [service_conf.yaml.template](./docker/service_conf.yaml.template) 파일의 내용과 일치하도록 해야 합니다.
|
||||
|
||||
> [./docker/README](./docker/README.md) 파일에는 환경 설정과 서비스 구성에 대한 자세한 설명이 있으며, [./docker/README](./docker/README.md) 파일에 나열된 모든 환경 설정이 [service_conf.yaml](./docker/service_conf.yaml) 파일의 해당 구성과 일치하도록 해야 합니다.
|
||||
> [./docker/README](./docker/README.md) 파일 ./docker/README은 service_conf.yaml.template 파일에서 ${ENV_VARS}로 사용할 수 있는 환경 설정과 서비스 구성에 대한 자세한 설명을 제공합니다.
|
||||
|
||||
기본 HTTP 서비스 포트(80)를 업데이트하려면 [docker-compose.yml](./docker/docker-compose.yml) 파일에서 `80:80`을 `<YOUR_SERVING_PORT>:80`으로 변경하세요.
|
||||
|
||||
@ -207,6 +210,21 @@
|
||||
> $ docker compose -f docker/docker-compose.yml up -d
|
||||
> ```
|
||||
|
||||
### 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.
|
||||
@ -214,9 +232,7 @@
|
||||
```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 .
|
||||
docker build --build-arg LIGHTEN=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
|
||||
```
|
||||
|
||||
## 🔧 소스 코드로 Docker 이미지를 컴파일합니다(임베딩 모델 포함)
|
||||
@ -226,23 +242,21 @@ docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
|
||||
```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 .
|
||||
docker build -f Dockerfile -t infiniflow/ragflow:nightly .
|
||||
```
|
||||
|
||||
## 🔨 소스 코드로 서비스를 시작합니다.
|
||||
|
||||
1. Poetry를 설치하거나 이미 설치된 경우 이 단계를 건너뜁니다:
|
||||
```bash
|
||||
curl -sSL https://install.python-poetry.org | python3 -
|
||||
pipx install poetry
|
||||
export POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true
|
||||
```
|
||||
|
||||
2. 소스 코드를 클론하고 Python 의존성을 설치합니다:
|
||||
```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
|
||||
```
|
||||
|
||||
@ -251,11 +265,10 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
docker compose -f docker/docker-compose-base.yml up -d
|
||||
```
|
||||
|
||||
`/etc/hosts` 에 다음 줄을 추가하여 **docker/service_conf.yaml** 에 지정된 모든 호스트를 `127.0.0.1` 로 해결합니다:
|
||||
`/etc/hosts` 에 다음 줄을 추가하여 **conf/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).
|
||||
|
||||
4. HuggingFace에 접근할 수 없는 경우, `HF_ENDPOINT` 환경 변수를 설정하여 미러 사이트를 사용하세요:
|
||||
|
||||
@ -275,8 +288,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
cd web
|
||||
npm install --force
|
||||
```
|
||||
7. **.umirc.ts** 에서 `proxy.target` 을 `http://127.0.0.1:9380` 으로 업데이트합니다:
|
||||
8. 프론트엔드 서비스를 시작합니다:
|
||||
7. 프론트엔드 서비스를 시작합니다:
|
||||
```bash
|
||||
npm run dev
|
||||
```
|
||||
|
||||
97
README_zh.md
97
README_zh.md
@ -8,7 +8,8 @@
|
||||
<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">
|
||||
@ -19,7 +20,7 @@
|
||||
<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:v0.13.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.13.0">
|
||||
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.15.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.15.0">
|
||||
</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">
|
||||
@ -47,15 +48,16 @@
|
||||
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.
|
||||
- 2024-09-13 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。
|
||||
- 2024-12-18 升级了 Deepdoc 的文档布局分析模型。
|
||||
- 2024-12-04 支持知识库的 Pagerank 分数。
|
||||
- 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。
|
||||
- 2024-08-22 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。
|
||||
|
||||
@ -141,18 +143,25 @@
|
||||
|
||||
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。
|
||||
> 运行以下命令会自动下载 RAGFlow slim Docker 镜像 `v0.15.0-slim`。请参考下表查看不同 Docker 发行版的描述。如需下载不同于 `v0.15.0-slim` 的 Docker 镜像,请在运行 `docker compose` 启动服务之前先更新 **docker/.env** 文件内的 `RAGFLOW_IMAGE` 变量。比如,你可以通过设置 `RAGFLOW_IMAGE=infiniflow/ragflow:v0.14.1` 来下载 RAGFlow 镜像的 `v0.14.1` 完整发行版。
|
||||
|
||||
```bash
|
||||
$ cd ragflow/docker
|
||||
$ docker compose -f docker-compose.yml up -d
|
||||
$ cd ragflow
|
||||
$ docker compose -f docker/docker-compose.yml up -d
|
||||
```
|
||||
|
||||
> - 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:v0.13.0-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:v0.13.0`。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。
|
||||
|
||||
| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
|
||||
| ----------------- | --------------- | --------------------- | ------------------------ |
|
||||
| v0.15.0 | ≈9 | :heavy_check_mark: | Stable release |
|
||||
| v0.15.0-slim | ≈2 | ❌ | Stable release |
|
||||
| nightly | ≈9 | :heavy_check_mark: | *Unstable* nightly build |
|
||||
| nightly-slim | ≈2 | ❌ | *Unstable* nightly build |
|
||||
|
||||
> [!TIP]
|
||||
> 如果你遇到 Docker 镜像拉不下来的问题,可以在 **docker/.env** 文件内根据变量 `RAGFLOW_IMAGE` 的注释提示选择华为云或者阿里云的相应镜像。
|
||||
> - 华为云镜像名:`swr.cn-north-4.myhuaweicloud.com/infiniflow/ragflow`
|
||||
> - 阿里云镜像名:`registry.cn-hangzhou.aliyuncs.com/infiniflow/ragflow`
|
||||
|
||||
4. 服务器启动成功后再次确认服务器状态:
|
||||
|
||||
```bash
|
||||
@ -173,11 +182,11 @@
|
||||
* 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)。
|
||||
6. 在 [service_conf.yaml](./docker/service_conf.yaml) 文件的 `user_default_llm` 栏配置 LLM factory,并在 `API_KEY` 栏填写和你选择的大模型相对应的 API key。
|
||||
6. 在 [service_conf.yaml.template](./docker/service_conf.yaml.template) 文件的 `user_default_llm` 栏配置 LLM factory,并在 `API_KEY` 栏填写和你选择的大模型相对应的 API key。
|
||||
|
||||
> 详见 [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup)。
|
||||
|
||||
@ -188,33 +197,53 @@
|
||||
系统配置涉及以下三份文件:
|
||||
|
||||
- [.env](./docker/.env):存放一些基本的系统环境变量,比如 `SVR_HTTP_PORT`、`MYSQL_PASSWORD`、`MINIO_PASSWORD` 等。
|
||||
- [service_conf.yaml](./docker/service_conf.yaml):配置各类后台服务。
|
||||
- [service_conf.yaml.template](./docker/service_conf.yaml.template):配置各类后台服务。
|
||||
- [docker-compose.yml](./docker/docker-compose.yml): 系统依赖该文件完成启动。
|
||||
|
||||
请务必确保 [.env](./docker/.env) 文件中的变量设置与 [service_conf.yaml](./docker/service_conf.yaml) 文件中的配置保持一致!
|
||||
请务必确保 [.env](./docker/.env) 文件中的变量设置与 [service_conf.yaml.template](./docker/service_conf.yaml.template) 文件中的配置保持一致!
|
||||
|
||||
如果不能访问镜像站点hub.docker.com或者模型站点huggingface.co,请按照[.env](./docker/.env)注释修改`RAGFLOW_IMAGE`和`HF_ENDPOINT`。
|
||||
如果不能访问镜像站点 hub.docker.com 或者模型站点 huggingface.co,请按照 [.env](./docker/.env) 注释修改 `RAGFLOW_IMAGE` 和 `HF_ENDPOINT`。
|
||||
|
||||
> [./docker/README](./docker/README.md) 文件提供了环境变量设置和服务配置的详细信息。请**一定要**确保 [./docker/README](./docker/README.md) 文件当中列出来的环境变量的值与 [service_conf.yaml](./docker/service_conf.yaml) 文件当中的系统配置保持一致。
|
||||
> [./docker/README](./docker/README.md) 解释了 [service_conf.yaml.template](./docker/service_conf.yaml.template) 用到的环境变量设置和服务配置。
|
||||
|
||||
如需更新默认的 HTTP 服务端口(80), 可以在 [docker-compose.yml](./docker/docker-compose.yml) 文件中将配置 `80:80` 改为 `<YOUR_SERVING_PORT>:80`。
|
||||
|
||||
> 所有系统配置都需要通过系统重启生效:
|
||||
>
|
||||
> ```bash
|
||||
> $ docker compose -f docker-compose.yml up -d
|
||||
> $ docker compose -f docker/docker-compose.yml up -d
|
||||
> ```
|
||||
|
||||
### 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。
|
||||
本 Docker 镜像大小约 2 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 nltk
|
||||
python3 download_deps.py
|
||||
docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
|
||||
docker build --build-arg LIGHTEN=1 --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:nightly-slim .
|
||||
```
|
||||
|
||||
## 🔧 源码编译 Docker 镜像(包含 embedding 模型)
|
||||
@ -224,23 +253,23 @@ docker build -f Dockerfile.slim -t infiniflow/ragflow:dev-slim .
|
||||
```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 .
|
||||
docker build --build-arg NEED_MIRROR=1 -f Dockerfile -t infiniflow/ragflow:nightly .
|
||||
```
|
||||
|
||||
## 🔨 以源代码启动服务
|
||||
|
||||
1. 安装 Poetry。如已经安装,可跳过本步骤:
|
||||
```bash
|
||||
curl -sSL https://install.python-poetry.org | python3 -
|
||||
pipx install poetry
|
||||
pipx inject poetry poetry-plugin-pypi-mirror
|
||||
export POETRY_VIRTUALENVS_CREATE=true POETRY_VIRTUALENVS_IN_PROJECT=true
|
||||
export POETRY_PYPI_MIRROR_URL=https://pypi.tuna.tsinghua.edu.cn/simple/
|
||||
```
|
||||
|
||||
2. 下载源代码并安装 Python 依赖:
|
||||
```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
|
||||
```
|
||||
|
||||
@ -249,11 +278,10 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
docker compose -f docker/docker-compose-base.yml up -d
|
||||
```
|
||||
|
||||
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`:
|
||||
在 `/etc/hosts` 中添加以下代码,将 **conf/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`。
|
||||
|
||||
4. 如果无法访问 HuggingFace,可以把环境变量 `HF_ENDPOINT` 设成相应的镜像站点:
|
||||
|
||||
@ -273,8 +301,7 @@ docker build -f Dockerfile -t infiniflow/ragflow:dev .
|
||||
cd web
|
||||
npm install --force
|
||||
```
|
||||
7. 配置前端,将 **.umirc.ts** 的 `proxy.target` 更新为 `http://127.0.0.1:9380`:
|
||||
8. 启动前端服务:
|
||||
7. 启动前端服务:
|
||||
```bash
|
||||
npm run dev
|
||||
```
|
||||
|
||||
@ -10,7 +10,7 @@ It is used to compose a complex work flow or agent.
|
||||
And this graph is beyond the DAG that we can use circles to describe our agent or work flow.
|
||||
Under this folder, we propose a test tool ./test/client.py which can test the DSLs such as json files in folder ./test/dsl_examples.
|
||||
Please use this client at the same folder you start RAGFlow. If it's run by Docker, please go into the container before running the client.
|
||||
Otherwise, correct configurations in conf/service_conf.yaml is essential.
|
||||
Otherwise, correct configurations in service_conf.yaml is essential.
|
||||
|
||||
```bash
|
||||
PYTHONPATH=path/to/ragflow python graph/test/client.py -h
|
||||
|
||||
@ -11,7 +11,7 @@
|
||||
在这个文件夹下,我们提出了一个测试工具 ./test/client.py,
|
||||
它可以测试像文件夹./test/dsl_examples下一样的DSL文件。
|
||||
请在启动 RAGFlow 的同一文件夹中使用此客户端。如果它是通过 Docker 运行的,请在运行客户端之前进入容器。
|
||||
否则,正确配置 conf/service_conf.yaml 文件是必不可少的。
|
||||
否则,正确配置 service_conf.yaml 文件是必不可少的。
|
||||
|
||||
```bash
|
||||
PYTHONPATH=path/to/ragflow python graph/test/client.py -h
|
||||
|
||||
@ -0,0 +1,2 @@
|
||||
from beartype.claw import beartype_this_package
|
||||
beartype_this_package()
|
||||
|
||||
136
agent/canvas.py
136
agent/canvas.py
@ -13,18 +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):
|
||||
@ -139,7 +134,8 @@ class Canvas(ABC):
|
||||
"components": {}
|
||||
}
|
||||
for k in self.dsl.keys():
|
||||
if k in ["components"]:continue
|
||||
if k in ["components"]:
|
||||
continue
|
||||
dsl[k] = deepcopy(self.dsl[k])
|
||||
|
||||
for k, cpn in self.components.items():
|
||||
@ -162,8 +158,13 @@ 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)
|
||||
@ -173,71 +174,80 @@ 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)
|
||||
self.path.append(["begin"])
|
||||
|
||||
self.path.append([])
|
||||
|
||||
ran = -1
|
||||
waiting = []
|
||||
without_dependent_checking = []
|
||||
|
||||
def prepare2run(cpns):
|
||||
nonlocal ran, ans
|
||||
for c in cpns:
|
||||
if self.path[-1] and c == self.path[-1][-1]: continue
|
||||
if self.path[-1] and c == self.path[-1][-1]:
|
||||
continue
|
||||
cpn = self.components[c]["obj"]
|
||||
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
|
||||
ans = cpn.run(self.history, **kwargs)
|
||||
yield "*'{}'* is running...🕞".format(self.get_compnent_name(c))
|
||||
try:
|
||||
ans = cpn.run(self.history, **kwargs)
|
||||
except Exception as e:
|
||||
logging.exception(f"Canvas.run got exception: {e}")
|
||||
self.path[-1].append(c)
|
||||
ran += 1
|
||||
raise e
|
||||
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
|
||||
if not cpn["downstream"]:
|
||||
break
|
||||
|
||||
loop = self._find_loop()
|
||||
if loop: raise OverflowError(f"Too much loops: {loop}")
|
||||
if loop:
|
||||
raise OverflowError(f"Too much loops: {loop}")
|
||||
|
||||
if cpn["obj"].component_name.lower() in ["switch", "categorize", "relevant"]:
|
||||
switch_out = cpn["obj"].output()[1].iloc[0, 0]
|
||||
assert switch_out in self.components, \
|
||||
"{}'s output: {} not valid.".format(cpn_id, switch_out)
|
||||
try:
|
||||
prepare2run([switch_out])
|
||||
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
|
||||
for m in prepare2run([switch_out]):
|
||||
yield {"content": m, "running_status": True}
|
||||
continue
|
||||
|
||||
try:
|
||||
prepare2run(cpn["downstream"])
|
||||
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
|
||||
for m in prepare2run(cpn["downstream"]):
|
||||
yield {"content": m, "running_status": True}
|
||||
|
||||
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 +256,13 @@ 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]
|
||||
@ -261,8 +273,10 @@ class Canvas(ABC):
|
||||
def get_history(self, window_size):
|
||||
convs = []
|
||||
for role, obj in self.history[window_size * -1:]:
|
||||
convs.append({"role": role, "content": (obj if role == "user" else
|
||||
'\n'.join([str(s) for s in pd.DataFrame(obj)['content']]))})
|
||||
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):
|
||||
@ -276,19 +290,22 @@ class Canvas(ABC):
|
||||
|
||||
def _find_loop(self, max_loops=6):
|
||||
path = self.path[-1][::-1]
|
||||
if len(path) < 2: return False
|
||||
if len(path) < 2:
|
||||
return False
|
||||
|
||||
for i in range(len(path)):
|
||||
if path[i].lower().find("answer") >= 0:
|
||||
path = path[:i]
|
||||
break
|
||||
|
||||
if len(path) < 2: return False
|
||||
if len(path) < 2:
|
||||
return False
|
||||
|
||||
for l in range(2, len(path) // 2):
|
||||
pat = ",".join(path[0:l])
|
||||
for loc in range(2, len(path) // 2):
|
||||
pat = ",".join(path[0:loc])
|
||||
path_str = ",".join(path)
|
||||
if len(pat) >= len(path_str): return False
|
||||
if len(pat) >= len(path_str):
|
||||
return False
|
||||
loop = max_loops
|
||||
while path_str.find(pat) == 0 and loop >= 0:
|
||||
loop -= 1
|
||||
@ -296,10 +313,23 @@ class Canvas(ABC):
|
||||
return False
|
||||
path_str = path_str[len(pat)+1:]
|
||||
if loop < 0:
|
||||
pat = " => ".join([p.split(":")[0] for p in path[0:l]])
|
||||
pat = " => ".join([p.split(":")[0] for p in path[0:loc]])
|
||||
return pat + " => " + pat
|
||||
|
||||
return False
|
||||
|
||||
def get_prologue(self):
|
||||
return self.components["begin"]["obj"]._param.prologue
|
||||
|
||||
def set_global_param(self, **kwargs):
|
||||
for k, v in kwargs.items():
|
||||
for q in self.components["begin"]["obj"]._param.query:
|
||||
if k != q["key"]:
|
||||
continue
|
||||
q["value"] = v
|
||||
|
||||
def get_preset_param(self):
|
||||
return self.components["begin"]["obj"]._param.query
|
||||
|
||||
def get_component_input_elements(self, cpnnm):
|
||||
return self.components[cpnnm]["obj"].get_input_elements()
|
||||
@ -30,9 +30,82 @@ 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
|
||||
from .email import Email, EmailParam
|
||||
|
||||
|
||||
|
||||
def component_class(class_name):
|
||||
m = importlib.import_module("agent.component")
|
||||
c = getattr(m, class_name)
|
||||
return c
|
||||
|
||||
__all__ = [
|
||||
"Begin",
|
||||
"BeginParam",
|
||||
"Generate",
|
||||
"GenerateParam",
|
||||
"Retrieval",
|
||||
"RetrievalParam",
|
||||
"Answer",
|
||||
"AnswerParam",
|
||||
"Categorize",
|
||||
"CategorizeParam",
|
||||
"Switch",
|
||||
"SwitchParam",
|
||||
"Relevant",
|
||||
"RelevantParam",
|
||||
"Message",
|
||||
"MessageParam",
|
||||
"RewriteQuestion",
|
||||
"RewriteQuestionParam",
|
||||
"KeywordExtract",
|
||||
"KeywordExtractParam",
|
||||
"Concentrator",
|
||||
"ConcentratorParam",
|
||||
"Baidu",
|
||||
"BaiduParam",
|
||||
"DuckDuckGo",
|
||||
"DuckDuckGoParam",
|
||||
"Wikipedia",
|
||||
"WikipediaParam",
|
||||
"PubMed",
|
||||
"PubMedParam",
|
||||
"ArXiv",
|
||||
"ArXivParam",
|
||||
"Google",
|
||||
"GoogleParam",
|
||||
"Bing",
|
||||
"BingParam",
|
||||
"GoogleScholar",
|
||||
"GoogleScholarParam",
|
||||
"DeepL",
|
||||
"DeepLParam",
|
||||
"GitHub",
|
||||
"GitHubParam",
|
||||
"BaiduFanyi",
|
||||
"BaiduFanyiParam",
|
||||
"QWeather",
|
||||
"QWeatherParam",
|
||||
"ExeSQL",
|
||||
"ExeSQLParam",
|
||||
"YahooFinance",
|
||||
"YahooFinanceParam",
|
||||
"WenCai",
|
||||
"WenCaiParam",
|
||||
"Jin10",
|
||||
"Jin10Param",
|
||||
"TuShare",
|
||||
"TuShareParam",
|
||||
"AkShare",
|
||||
"AkShareParam",
|
||||
"Crawler",
|
||||
"CrawlerParam",
|
||||
"Invoke",
|
||||
"InvokeParam",
|
||||
"Template",
|
||||
"TemplateParam",
|
||||
"Email",
|
||||
"EmailParam",
|
||||
"component_class"
|
||||
]
|
||||
|
||||
@ -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
|
||||
|
||||
@ -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
|
||||
|
||||
|
||||
@ -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 +35,9 @@ class ComponentParamBase(ABC):
|
||||
def __init__(self):
|
||||
self.output_var_name = "output"
|
||||
self.message_history_window_size = 22
|
||||
self.query = []
|
||||
self.inputs = []
|
||||
self.debug_inputs = []
|
||||
|
||||
def set_name(self, name: str):
|
||||
self._name = name
|
||||
@ -81,7 +83,6 @@ 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 +360,13 @@ 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 +386,14 @@ 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
|
||||
@ -396,9 +401,17 @@ 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)))
|
||||
self._param.debug_inputs = []
|
||||
try:
|
||||
res = self._run(history, **kwargs)
|
||||
self.set_output(res)
|
||||
@ -414,7 +427,8 @@ class ComponentBase(ABC):
|
||||
def output(self, allow_partial=True) -> Tuple[str, Union[pd.DataFrame, partial]]:
|
||||
o = getattr(self._param, self._param.output_var_name)
|
||||
if not isinstance(o, partial) and not isinstance(o, pd.DataFrame):
|
||||
if not isinstance(o, list): o = [o]
|
||||
if not isinstance(o, list):
|
||||
o = [o]
|
||||
o = pd.DataFrame(o)
|
||||
|
||||
if allow_partial or not isinstance(o, partial):
|
||||
@ -426,53 +440,112 @@ class ComponentBase(ABC):
|
||||
for oo in o():
|
||||
if not isinstance(oo, pd.DataFrame):
|
||||
outs = pd.DataFrame(oo if isinstance(oo, list) else [oo])
|
||||
else: outs = oo
|
||||
else:
|
||||
outs = oo
|
||||
return self._param.output_var_name, outs
|
||||
|
||||
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):
|
||||
setattr(self._param, self._param.output_var_name, v)
|
||||
|
||||
def get_input(self):
|
||||
upstream_outs = []
|
||||
if self._param.debug_inputs:
|
||||
return pd.DataFrame([{"content": v["value"]} for v in self._param.debug_inputs])
|
||||
|
||||
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.get("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.get("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.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_input_elements(self):
|
||||
assert self._param.query, "Please identify input parameters firstly."
|
||||
eles = []
|
||||
for q in self._param.query:
|
||||
if q.get("component_id"):
|
||||
cpn_id = q["component_id"]
|
||||
if cpn_id.split("@")[0].lower().find("begin") >= 0:
|
||||
cpn_id, key = cpn_id.split("@")
|
||||
eles.extend(self._canvas.get_component(cpn_id)["obj"]._param.query)
|
||||
continue
|
||||
|
||||
eles.append({"name": self._canvas.get_compnent_name(cpn_id), "key": cpn_id})
|
||||
else:
|
||||
eles.append({"key": q["value"], "name": q["value"], "value": q["value"]})
|
||||
return eles
|
||||
|
||||
def get_stream_input(self):
|
||||
reversed_cpnts = []
|
||||
@ -481,7 +554,8 @@ class ComponentBase(ABC):
|
||||
reversed_cpnts.extend(self._canvas.path[-1])
|
||||
|
||||
for u in reversed_cpnts[::-1]:
|
||||
if self.get_component_name(u) in ["switch", "answer"]: continue
|
||||
if self.get_component_name(u) in ["switch", "answer"]:
|
||||
continue
|
||||
return self._canvas.get_component(u)["obj"].output()[1]
|
||||
|
||||
@staticmethod
|
||||
@ -490,3 +564,6 @@ class ComponentBase(ABC):
|
||||
|
||||
def get_component_name(self, cpn_id):
|
||||
return self._canvas.get_component(cpn_id)["obj"].component_name.lower()
|
||||
|
||||
def debug(self, **kwargs):
|
||||
return self._run([], **kwargs)
|
||||
@ -26,6 +26,7 @@ class BeginParam(ComponentParamBase):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.prologue = "Hi! I'm your smart assistant. What can I do for you?"
|
||||
self.query = []
|
||||
|
||||
def check(self):
|
||||
return True
|
||||
@ -42,7 +43,7 @@ class Begin(ComponentBase):
|
||||
def stream_output(self):
|
||||
res = {"content": self._param.prologue}
|
||||
yield res
|
||||
self.set_output(res)
|
||||
self.set_output(self.be_output(res))
|
||||
|
||||
|
||||
|
||||
|
||||
@ -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
|
||||
|
||||
@ -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):
|
||||
@ -34,15 +34,18 @@ 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 v.get("to"): raise ValueError(f"[Categorize] 'To' of category {k} 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):
|
||||
cate_lines = []
|
||||
for c, desc in self.category_description.items():
|
||||
for l in desc.get("examples", "").split("\n"):
|
||||
if not l: continue
|
||||
cate_lines.append("Question: {}\tCategory: {}".format(l, c))
|
||||
for line in desc.get("examples", "").split("\n"):
|
||||
if not line:
|
||||
continue
|
||||
cate_lines.append("Question: {}\tCategory: {}".format(line, c))
|
||||
descriptions = []
|
||||
for c, desc in self.category_description.items():
|
||||
if desc.get("description"):
|
||||
@ -77,11 +80,15 @@ class Categorize(Generate, ABC):
|
||||
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"])
|
||||
|
||||
return Categorize.be_output(list(self._param.category_description.items())[-1][1]["to"])
|
||||
|
||||
def debug(self, **kwargs):
|
||||
df = self._run([], **kwargs)
|
||||
cpn_id = df.iloc[0, 0]
|
||||
return Categorize.be_output(self._canvas.get_compnent_name(cpn_id))
|
||||
|
||||
|
||||
@ -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
|
||||
|
||||
|
||||
@ -17,6 +17,7 @@ from abc import ABC
|
||||
import asyncio
|
||||
from crawl4ai import AsyncWebCrawler
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
from api.utils.web_utils import is_valid_url
|
||||
|
||||
|
||||
class CrawlerParam(ComponentParamBase):
|
||||
@ -39,7 +40,7 @@ class Crawler(ComponentBase, ABC):
|
||||
def _run(self, history, **kwargs):
|
||||
ans = self.get_input()
|
||||
ans = " - ".join(ans["content"]) if "content" in ans else ""
|
||||
if not ans:
|
||||
if not is_valid_url(ans):
|
||||
return Crawler.be_output("")
|
||||
try:
|
||||
result = asyncio.run(self.get_web(ans))
|
||||
@ -64,7 +65,3 @@ class Crawler(ComponentBase, ABC):
|
||||
elif self._param.extract_type == 'content':
|
||||
result.extracted_content
|
||||
return result.markdown
|
||||
|
||||
|
||||
|
||||
|
||||
@ -14,7 +14,6 @@
|
||||
# limitations under the License.
|
||||
#
|
||||
from abc import ABC
|
||||
import re
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
import deepl
|
||||
|
||||
|
||||
@ -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
|
||||
|
||||
138
agent/component/email.py
Normal file
138
agent/component/email.py
Normal file
@ -0,0 +1,138 @@
|
||||
#
|
||||
# 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 json
|
||||
import smtplib
|
||||
import logging
|
||||
from email.mime.text import MIMEText
|
||||
from email.mime.multipart import MIMEMultipart
|
||||
from email.header import Header
|
||||
from email.utils import formataddr
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
|
||||
class EmailParam(ComponentParamBase):
|
||||
"""
|
||||
Define the Email component parameters.
|
||||
"""
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
# Fixed configuration parameters
|
||||
self.smtp_server = "" # SMTP server address
|
||||
self.smtp_port = 465 # SMTP port
|
||||
self.email = "" # Sender email
|
||||
self.password = "" # Email authorization code
|
||||
self.sender_name = "" # Sender name
|
||||
|
||||
def check(self):
|
||||
# Check required parameters
|
||||
self.check_empty(self.smtp_server, "SMTP Server")
|
||||
self.check_empty(self.email, "Email")
|
||||
self.check_empty(self.password, "Password")
|
||||
self.check_empty(self.sender_name, "Sender Name")
|
||||
|
||||
class Email(ComponentBase, ABC):
|
||||
component_name = "Email"
|
||||
|
||||
def _run(self, history, **kwargs):
|
||||
# Get upstream component output and parse JSON
|
||||
ans = self.get_input()
|
||||
content = "".join(ans["content"]) if "content" in ans else ""
|
||||
if not content:
|
||||
return Email.be_output("No content to send")
|
||||
|
||||
success = False
|
||||
try:
|
||||
# Parse JSON string passed from upstream
|
||||
email_data = json.loads(content)
|
||||
|
||||
# Validate required fields
|
||||
if "to_email" not in email_data:
|
||||
return Email.be_output("Missing required field: to_email")
|
||||
|
||||
# Create email object
|
||||
msg = MIMEMultipart('alternative')
|
||||
|
||||
# Properly handle sender name encoding
|
||||
msg['From'] = formataddr((str(Header(self._param.sender_name,'utf-8')), self._param.email))
|
||||
msg['To'] = email_data["to_email"]
|
||||
if "cc_email" in email_data and email_data["cc_email"]:
|
||||
msg['Cc'] = email_data["cc_email"]
|
||||
msg['Subject'] = Header(email_data.get("subject", "No Subject"), 'utf-8').encode()
|
||||
|
||||
# Use content from email_data or default content
|
||||
email_content = email_data.get("content", "No content provided")
|
||||
# msg.attach(MIMEText(email_content, 'plain', 'utf-8'))
|
||||
msg.attach(MIMEText(email_content, 'html', 'utf-8'))
|
||||
|
||||
# Connect to SMTP server and send
|
||||
logging.info(f"Connecting to SMTP server {self._param.smtp_server}:{self._param.smtp_port}")
|
||||
|
||||
context = smtplib.ssl.create_default_context()
|
||||
with smtplib.SMTP_SSL(self._param.smtp_server, self._param.smtp_port, context=context) as server:
|
||||
# Login
|
||||
logging.info(f"Attempting to login with email: {self._param.email}")
|
||||
server.login(self._param.email, self._param.password)
|
||||
|
||||
# Get all recipient list
|
||||
recipients = [email_data["to_email"]]
|
||||
if "cc_email" in email_data and email_data["cc_email"]:
|
||||
recipients.extend(email_data["cc_email"].split(','))
|
||||
|
||||
# Send email
|
||||
logging.info(f"Sending email to recipients: {recipients}")
|
||||
try:
|
||||
server.send_message(msg, self._param.email, recipients)
|
||||
success = True
|
||||
except Exception as e:
|
||||
logging.error(f"Error during send_message: {str(e)}")
|
||||
# Try alternative method
|
||||
server.sendmail(self._param.email, recipients, msg.as_string())
|
||||
success = True
|
||||
|
||||
try:
|
||||
server.quit()
|
||||
except Exception as e:
|
||||
# Ignore errors when closing connection
|
||||
logging.warning(f"Non-fatal error during connection close: {str(e)}")
|
||||
|
||||
if success:
|
||||
return Email.be_output("Email sent successfully")
|
||||
|
||||
except json.JSONDecodeError:
|
||||
error_msg = "Invalid JSON format in input"
|
||||
logging.error(error_msg)
|
||||
return Email.be_output(error_msg)
|
||||
|
||||
except smtplib.SMTPAuthenticationError:
|
||||
error_msg = "SMTP Authentication failed. Please check your email and authorization code."
|
||||
logging.error(error_msg)
|
||||
return Email.be_output(f"Failed to send email: {error_msg}")
|
||||
|
||||
except smtplib.SMTPConnectError:
|
||||
error_msg = f"Failed to connect to SMTP server {self._param.smtp_server}:{self._param.smtp_port}"
|
||||
logging.error(error_msg)
|
||||
return Email.be_output(f"Failed to send email: {error_msg}")
|
||||
|
||||
except smtplib.SMTPException as e:
|
||||
error_msg = f"SMTP error occurred: {str(e)}"
|
||||
logging.error(error_msg)
|
||||
return Email.be_output(f"Failed to send email: {error_msg}")
|
||||
|
||||
except Exception as e:
|
||||
error_msg = f"Unexpected error: {str(e)}"
|
||||
logging.error(error_msg)
|
||||
return Email.be_output(f"Failed to send email: {error_msg}")
|
||||
@ -19,7 +19,8 @@ import pandas as pd
|
||||
import pymysql
|
||||
import psycopg2
|
||||
from agent.component.base import ComponentBase, ComponentParamBase
|
||||
|
||||
import pyodbc
|
||||
import logging
|
||||
|
||||
class ExeSQLParam(ComponentParamBase):
|
||||
"""
|
||||
@ -38,7 +39,7 @@ class ExeSQLParam(ComponentParamBase):
|
||||
self.top_n = 30
|
||||
|
||||
def check(self):
|
||||
self.check_valid_value(self.db_type, "Choose DB type", ['mysql', 'postgresql', 'mariadb'])
|
||||
self.check_valid_value(self.db_type, "Choose DB type", ['mysql', 'postgresql', 'mariadb', 'mssql'])
|
||||
self.check_empty(self.database, "Database name")
|
||||
self.check_empty(self.username, "database username")
|
||||
self.check_empty(self.host, "IP Address")
|
||||
@ -46,8 +47,10 @@ class ExeSQLParam(ComponentParamBase):
|
||||
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.")
|
||||
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):
|
||||
@ -62,20 +65,41 @@ class ExeSQL(ComponentBase, ABC):
|
||||
self._loop += 1
|
||||
|
||||
ans = self.get_input()
|
||||
ans = "".join(ans["content"]) if "content" in ans else ""
|
||||
ans = re.sub(r'^.*?SELECT ', 'SELECT ', repr(ans), flags=re.IGNORECASE)
|
||||
|
||||
|
||||
ans = "".join([str(a) for a in ans["content"]]) if "content" in ans else ""
|
||||
if self._param.db_type == 'mssql':
|
||||
# improve the information extraction, most llm return results in markdown format ```sql query ```
|
||||
match = re.search(r"```sql\s*(.*?)\s*```", ans, re.DOTALL)
|
||||
if match:
|
||||
ans = match.group(1) # Query content
|
||||
print(ans)
|
||||
else:
|
||||
print("no markdown")
|
||||
ans = re.sub(r'^.*?SELECT ', 'SELECT ', (ans), flags=re.IGNORECASE)
|
||||
else:
|
||||
ans = re.sub(r'^.*?SELECT ', 'SELECT ', repr(ans), flags=re.IGNORECASE)
|
||||
ans = re.sub(r';.*?SELECT ', '; SELECT ', ans, flags=re.IGNORECASE)
|
||||
ans = re.sub(r';[^;]*$', r';', ans)
|
||||
if not ans:
|
||||
raise Exception("SQL statement not found!")
|
||||
|
||||
logging.info("db_type: ",self._param.db_type)
|
||||
if self._param.db_type in ["mysql", "mariadb"]:
|
||||
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 = psycopg2.connect(dbname=self._param.database, user=self._param.username, host=self._param.host,
|
||||
port=self._param.port, password=self._param.password)
|
||||
|
||||
elif self._param.db_type == 'mssql':
|
||||
conn_str = (
|
||||
r'DRIVER={ODBC Driver 17 for SQL Server};'
|
||||
r'SERVER=' + self._param.host + ',' + str(self._param.port) + ';'
|
||||
r'DATABASE=' + self._param.database + ';'
|
||||
r'UID=' + self._param.username + ';'
|
||||
r'PWD=' + self._param.password
|
||||
)
|
||||
db = pyodbc.connect(conn_str)
|
||||
try:
|
||||
cursor = db.cursor()
|
||||
except Exception as e:
|
||||
@ -85,11 +109,12 @@ class ExeSQL(ComponentBase, ABC):
|
||||
if not single_sql:
|
||||
continue
|
||||
try:
|
||||
logging.info("single_sql: ",single_sql)
|
||||
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 cursor.fetchmany(size=self._param.top_n)])
|
||||
single_res = pd.DataFrame([i for i in cursor.fetchmany(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:
|
||||
|
||||
@ -17,9 +17,10 @@ import re
|
||||
from functools import partial
|
||||
import pandas as pd
|
||||
from api.db import LLMType
|
||||
from api.db.services.conversation_service import structure_answer
|
||||
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
|
||||
|
||||
|
||||
@ -51,11 +52,16 @@ class GenerateParam(ComponentParamBase):
|
||||
|
||||
def gen_conf(self):
|
||||
conf = {}
|
||||
if self.max_tokens > 0: conf["max_tokens"] = self.max_tokens
|
||||
if self.temperature > 0: conf["temperature"] = self.temperature
|
||||
if self.top_p > 0: conf["top_p"] = self.top_p
|
||||
if self.presence_penalty > 0: conf["presence_penalty"] = self.presence_penalty
|
||||
if self.frequency_penalty > 0: conf["frequency_penalty"] = self.frequency_penalty
|
||||
if self.max_tokens > 0:
|
||||
conf["max_tokens"] = self.max_tokens
|
||||
if self.temperature > 0:
|
||||
conf["temperature"] = self.temperature
|
||||
if self.top_p > 0:
|
||||
conf["top_p"] = self.top_p
|
||||
if self.presence_penalty > 0:
|
||||
conf["presence_penalty"] = self.presence_penalty
|
||||
if self.frequency_penalty > 0:
|
||||
conf["frequency_penalty"] = self.frequency_penalty
|
||||
return conf
|
||||
|
||||
|
||||
@ -63,23 +69,28 @@ 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:
|
||||
did = retrieval_res.loc[int(i), "doc_id"]
|
||||
if did in doc_ids: continue
|
||||
if did in doc_ids:
|
||||
continue
|
||||
doc_ids.add(did)
|
||||
recall_docs.append({"doc_id": did, "doc_name": retrieval_res.loc[int(i), "docnm_kwd"]})
|
||||
|
||||
@ -92,31 +103,71 @@ class Generate(ComponentBase):
|
||||
}
|
||||
|
||||
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'"
|
||||
answer += " Please set LLM API-Key in 'User Setting -> Model providers -> API-Key'"
|
||||
res = {"content": answer, "reference": reference}
|
||||
res = structure_answer(None, res, "", "")
|
||||
|
||||
return res
|
||||
|
||||
def get_input_elements(self):
|
||||
if self._param.parameters:
|
||||
return [{"key": "user", "name": "User"}, *self._param.parameters]
|
||||
|
||||
return [{"key": "user", "name": "User"}]
|
||||
|
||||
def _run(self, history, **kwargs):
|
||||
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([c for c in retrieval_res["content"] if isinstance(c, str)])) 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":
|
||||
kwargs[para["key"]] = self._canvas.get_history(1)[0]["content"]
|
||||
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:
|
||||
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\}" % re.escape(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])[
|
||||
@ -129,7 +180,11 @@ class Generate(ComponentBase):
|
||||
return pd.DataFrame([res])
|
||||
|
||||
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:
|
||||
@ -148,7 +203,11 @@ class Generate(ComponentBase):
|
||||
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(msg[0]["content"], msg[1:], self._param.gen_conf()):
|
||||
res = {"content": ans, "reference": []}
|
||||
@ -159,4 +218,17 @@ class Generate(ComponentBase):
|
||||
res = self.set_cite(retrieval_res, answer)
|
||||
yield res
|
||||
|
||||
self.set_output(res)
|
||||
self.set_output(Generate.be_output(res))
|
||||
|
||||
def debug(self, **kwargs):
|
||||
chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT, self._param.llm_id)
|
||||
prompt = self._param.prompt
|
||||
|
||||
for para in self._param.debug_inputs:
|
||||
kwargs[para["key"]] = para.get("value", "")
|
||||
|
||||
for n, v in kwargs.items():
|
||||
prompt = re.sub(r"\{%s\}" % re.escape(n), str(v).replace("\\", " "), prompt)
|
||||
|
||||
ans = chat_mdl.chat(prompt, [{"role": "user", "content": kwargs.get("user", "")}], self._param.gen_conf())
|
||||
return pd.DataFrame([ans])
|
||||
|
||||
@ -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
|
||||
|
||||
@ -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
|
||||
|
||||
@ -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
|
||||
|
||||
@ -51,6 +51,9 @@ class Invoke(ComponentBase, ABC):
|
||||
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:
|
||||
|
||||
@ -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 +50,16 @@ 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)
|
||||
|
||||
def debug(self, **kwargs):
|
||||
return self._run([], **kwargs)
|
||||
@ -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
|
||||
|
||||
@ -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
|
||||
@ -70,11 +71,13 @@ 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:
|
||||
return Relevant.be_output(self._param.no)
|
||||
assert False, f"Relevant component got: {ans}"
|
||||
|
||||
def debug(self, **kwargs):
|
||||
return self._run([], **kwargs)
|
||||
|
||||
|
||||
@ -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
|
||||
|
||||
|
||||
@ -66,7 +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)
|
||||
@ -80,7 +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
|
||||
|
||||
|
||||
|
||||
@ -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
|
||||
@ -94,7 +95,8 @@ class RewriteQuestion(Generate, ABC):
|
||||
hist = self._canvas.get_history(4)
|
||||
conv = []
|
||||
for m in hist:
|
||||
if m["role"] not in ["user", "assistant"]: continue
|
||||
if m["role"] not in ["user", "assistant"]:
|
||||
continue
|
||||
conv.append("{}: {}".format(m["role"].upper(), m["content"]))
|
||||
conv = "\n".join(conv)
|
||||
|
||||
@ -104,7 +106,8 @@ class RewriteQuestion(Generate, ABC):
|
||||
self._canvas.history.pop()
|
||||
self._canvas.history.append(("user", ans))
|
||||
|
||||
print(ans, ":::::::::::::::::::::::::::::::::")
|
||||
logging.debug(ans)
|
||||
return RewriteQuestion.be_output(ans)
|
||||
|
||||
|
||||
|
||||
|
||||
@ -41,19 +41,44 @@ class SwitchParam(ComponentParamBase):
|
||||
def check(self):
|
||||
self.check_empty(self.conditions, "[Switch] conditions")
|
||||
for cond in self.conditions:
|
||||
if not cond["to"]: raise ValueError(f"[Switch] 'To' can not be empty!")
|
||||
if not cond["to"]:
|
||||
raise ValueError("[Switch] 'To' can not be empty!")
|
||||
|
||||
|
||||
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"])
|
||||
|
||||
@ -85,22 +110,22 @@ class Switch(ComponentBase, ABC):
|
||||
elif operator == ">":
|
||||
try:
|
||||
return True if float(input) > float(value) else False
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
return True if input > value else False
|
||||
elif operator == "<":
|
||||
try:
|
||||
return True if float(input) < float(value) else False
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
return True if input < value else False
|
||||
elif operator == "≥":
|
||||
try:
|
||||
return True if float(input) >= float(value) else False
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
return True if input >= value else False
|
||||
elif operator == "≤":
|
||||
try:
|
||||
return True if float(input) <= float(value) else False
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
return True if input <= value else False
|
||||
|
||||
raise ValueError('Not supported operator' + operator)
|
||||
86
agent/component/template.py
Normal file
86
agent/component/template.py
Normal file
@ -0,0 +1,86 @@
|
||||
#
|
||||
# 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)
|
||||
|
||||
@ -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
|
||||
|
||||
@ -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("")
|
||||
|
||||
@ -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
|
||||
|
||||
@ -620,7 +620,7 @@
|
||||
"text": "Searches for description about meanings of tables and fields."
|
||||
},
|
||||
"label": "Note",
|
||||
"name": "N:DB Desctription"
|
||||
"name": "N:DB Description"
|
||||
},
|
||||
"dragging": false,
|
||||
"height": 128,
|
||||
@ -679,7 +679,7 @@
|
||||
{
|
||||
"data": {
|
||||
"form": {
|
||||
"text": "DDL(Data Definition Language).\n\nSearches for relevent database creation statements.\n\nIt should bind with a KB to which DDL is dumped in.\nYou could use 'General' as parsing method and ';' as delimiter."
|
||||
"text": "DDL(Data Definition Language).\n\nSearches for relevant database creation statements.\n\nIt should bind with a KB to which DDL is dumped in.\nYou could use 'General' as parsing method and ';' as delimiter."
|
||||
},
|
||||
"label": "Note",
|
||||
"name": "N: DDL"
|
||||
|
||||
@ -152,7 +152,8 @@
|
||||
"Generate:ToughLawsCheat",
|
||||
"Generate:KindCarrotsSit",
|
||||
"Generate:DirtyToolsTrain",
|
||||
"Generate:FluffyPillowsGrow"
|
||||
"Generate:FluffyPillowsGrow",
|
||||
"Generate:ProudEarsWorry"
|
||||
]
|
||||
},
|
||||
"Retrieval:ShaggyRadiosRetire": {
|
||||
@ -212,7 +213,9 @@
|
||||
"top_p": 0.3
|
||||
}
|
||||
},
|
||||
"downstream": [],
|
||||
"downstream": [
|
||||
"Answer:TwentyMugsDeny"
|
||||
],
|
||||
"upstream": [
|
||||
"categorize:0"
|
||||
]
|
||||
@ -331,9 +334,9 @@
|
||||
"message_history_window_size": 12,
|
||||
"parameters": [
|
||||
{
|
||||
"component_id": "Retrieval:ColdEelsArrive",
|
||||
"id": "5166a107-e859-4c71-99a2-3a216c775347",
|
||||
"key": "jd",
|
||||
"component_id": "Retrieval:ColdEelsArrive"
|
||||
"key": "jd"
|
||||
}
|
||||
],
|
||||
"presence_penalty": 0.4,
|
||||
@ -1266,9 +1269,9 @@
|
||||
"parameter": "Precise",
|
||||
"parameters": [
|
||||
{
|
||||
"component_id": "Retrieval:ColdEelsArrive",
|
||||
"id": "5166a107-e859-4c71-99a2-3a216c775347",
|
||||
"key": "jd",
|
||||
"component_id": "Retrieval:ColdEelsArrive"
|
||||
"key": "jd"
|
||||
}
|
||||
],
|
||||
"presencePenaltyEnabled": true,
|
||||
@ -1541,6 +1544,19 @@
|
||||
"target": "Answer:TwentyMugsDeny",
|
||||
"targetHandle": "c",
|
||||
"type": "buttonEdge"
|
||||
},
|
||||
{
|
||||
"type": "buttonEdge",
|
||||
"markerEnd": "logo",
|
||||
"style": {
|
||||
"strokeWidth": 2,
|
||||
"stroke": "rgb(202 197 245)"
|
||||
},
|
||||
"source": "Generate:ProudEarsWorry",
|
||||
"sourceHandle": "b",
|
||||
"target": "Answer:TwentyMugsDeny",
|
||||
"targetHandle": "c",
|
||||
"id": "reactflow__edge-Generate:ProudEarsWorryb-Answer:TwentyMugsDenyc"
|
||||
}
|
||||
]
|
||||
},
|
||||
|
||||
@ -90,7 +90,7 @@
|
||||
"message_history_window_size": 12,
|
||||
"parameters": [],
|
||||
"presence_penalty": 0.4,
|
||||
"prompt": "Role: You are a customer support. \n\nTask: Please answer the question based on content of knowledge base. \n\nReuirements & restrictions:\n - DO NOT make things up when all knowledge base content is irrelevant to the question. \n - Answers need to consider chat history.\n - Request about customer's contact information like, Wechat number, LINE number, twitter, discord, etc,. , when knowlegebase content can't answer his question. So, product expert could contact him soon to solve his problem.\n\n Knowledge base content is as following:\n {input}\n The above is the content of knowledge base.",
|
||||
"prompt": "Role: You are a customer support. \n\nTask: Please answer the question based on content of knowledge base. \n\nRequirements & restrictions:\n - DO NOT make things up when all knowledge base content is irrelevant to the question. \n - Answers need to consider chat history.\n - Request about customer's contact information like, Wechat number, LINE number, twitter, discord, etc,. , when knowledge base content can't answer his question. So, product expert could contact him soon to solve his problem.\n\n Knowledge base content is as following:\n {input}\n The above is the content of knowledge base.",
|
||||
"temperature": 0.1,
|
||||
"top_p": 0.3
|
||||
}
|
||||
|
||||
@ -70,8 +70,8 @@
|
||||
"to": "QWeather:DeepKiwisTeach"
|
||||
},
|
||||
"2. finance": {
|
||||
"description": "Question is about finace/economic information, stock market, economic news.",
|
||||
"examples": "昨日涨幅大于5%的军工股?\nStocks have MACD buyin signals?\nWhen is the next interest rate cut by the Federal Reserve?\n国家救市都有哪些举措?",
|
||||
"description": "Question is about finance/economic information, stock market, economic news.",
|
||||
"examples": "Stocks have MACD buy signals?\nWhen is the next interest rate cut by the Federal Reserve?\n",
|
||||
"to": "Concentrator:TrueGeckosSlide"
|
||||
},
|
||||
"3. medical": {
|
||||
@ -268,7 +268,7 @@
|
||||
"message_history_window_size": 12,
|
||||
"parameters": [],
|
||||
"presence_penalty": 0.4,
|
||||
"prompt": "Role: You‘re warm-hearted lovely young girl, 22 years old, located at Shanghai in China. Your name is R. Who are talking to you is your very good old friend of yours.\n\nTask: \n- Chat with the friend.\n- Ask question and care about them.\n- Provide useful advice to your friend.\n- Tell jokes to make your firend happy.\n\nThe following is the weatcher information:\n{weather}",
|
||||
"prompt": "Role: You‘re warm-hearted lovely young girl, 22 years old, located at Shanghai in China. Your name is R. Who are talking to you is your very good old friend of yours.\n\nTask: \n- Chat with the friend.\n- Ask question and care about them.\n- Provide useful advice to your friend.\n- Tell jokes to make your friend happy.\n\nThe following is the weather information:\n{weather}",
|
||||
"temperature": 0.1,
|
||||
"top_p": 0.3
|
||||
}
|
||||
@ -497,7 +497,7 @@
|
||||
}
|
||||
],
|
||||
"presence_penalty": 0.4,
|
||||
"prompt": "Role: You‘re warm-hearted lovely young girl, 22 years old, located at Shanghai in China. Your name is R. Who are talking to you is your very good old friend of yours.\n\nTask: \n- Chat with the friend.\n- Ask question and care about them.\n- Tell your friend the weather if there's weather information provided. If your friend did not provide region information, ask about where he/she is.\n\nThe following is the weatcher information:\n{weather}\n",
|
||||
"prompt": "Role: You‘re warm-hearted lovely young girl, 22 years old, located at Shanghai in China. Your name is R. Who are talking to you is your very good old friend of yours.\n\nTask: \n- Chat with the friend.\n- Ask question and care about them.\n- Tell your friend the weather if there's weather information provided. If your friend did not provide region information, ask about where he/she is.\n\nThe following is the weather information:\n{weather}\n",
|
||||
"temperature": 0.1,
|
||||
"top_p": 0.3
|
||||
}
|
||||
@ -622,8 +622,8 @@
|
||||
"to": "QWeather:DeepKiwisTeach"
|
||||
},
|
||||
"2. finance": {
|
||||
"description": "Question is about finace/economic information, stock market, economic news.",
|
||||
"examples": "昨日涨幅大于5%的军工股?\nStocks have MACD buyin signals?\nWhen is the next interest rate cut by the Federal Reserve?\n国家救市都有哪些举措?",
|
||||
"description": "Question is about finance/economic information, stock market, economic news.",
|
||||
"examples": "Stocks have MACD buy signals?\nWhen is the next interest rate cut by the Federal Reserve?\n",
|
||||
"to": "Concentrator:TrueGeckosSlide"
|
||||
},
|
||||
"3. medical": {
|
||||
@ -927,7 +927,7 @@
|
||||
"parameters": [],
|
||||
"presencePenaltyEnabled": true,
|
||||
"presence_penalty": 0.4,
|
||||
"prompt": "Role: You‘re warm-hearted lovely young girl, 22 years old, located at Shanghai in China. Your name is R. Who are talking to you is your very good old friend of yours.\n\nTask: \n- Chat with the friend.\n- Ask question and care about them.\n- Provide useful advice to your friend.\n- Tell jokes to make your firend happy.\n\nThe following is the weatcher information:\n{weather}",
|
||||
"prompt": "Role: You‘re warm-hearted lovely young girl, 22 years old, located at Shanghai in China. Your name is R. Who are talking to you is your very good old friend of yours.\n\nTask: \n- Chat with the friend.\n- Ask question and care about them.\n- Provide useful advice to your friend.\n- Tell jokes to make your friend happy.\n\nThe following is the weather information:\n{weather}",
|
||||
"temperature": 0.1,
|
||||
"temperatureEnabled": true,
|
||||
"topPEnabled": true,
|
||||
@ -1011,7 +1011,7 @@
|
||||
"top_p": 0.3
|
||||
},
|
||||
"label": "Generate",
|
||||
"name": "tranlate to Chinese"
|
||||
"name": "translate to Chinese"
|
||||
},
|
||||
"dragging": false,
|
||||
"height": 86,
|
||||
@ -1276,7 +1276,7 @@
|
||||
],
|
||||
"presencePenaltyEnabled": true,
|
||||
"presence_penalty": 0.4,
|
||||
"prompt": "Role: You‘re warm-hearted lovely young girl, 22 years old, located at Shanghai in China. Your name is R. Who are talking to you is your very good old friend of yours.\n\nTask: \n- Chat with the friend.\n- Ask question and care about them.\n- Tell your friend the weather if there's weather information provided. If your friend did not provide region information, ask about where he/she is.\n\nThe following is the weatcher information:\n{weather}\n",
|
||||
"prompt": "Role: You‘re warm-hearted lovely young girl, 22 years old, located at Shanghai in China. Your name is R. Who are talking to you is your very good old friend of yours.\n\nTask: \n- Chat with the friend.\n- Ask question and care about them.\n- Tell your friend the weather if there's weather information provided. If your friend did not provide region information, ask about where he/she is.\n\nThe following is the weather information:\n{weather}\n",
|
||||
"temperature": 0.1,
|
||||
"temperatureEnabled": true,
|
||||
"topPEnabled": true,
|
||||
|
||||
File diff suppressed because one or more lines are too long
@ -1,7 +1,7 @@
|
||||
{
|
||||
"id": 8,
|
||||
"title": "Intelligent investment advisor",
|
||||
"description": "An intelligent investment advisor that can answer your financial questions based on real-time domestic financial data and financial information.",
|
||||
"description": "An intelligent investment advisor that answers your financial questions using real-time domestic financial data.",
|
||||
"canvas_type": "chatbot",
|
||||
"dsl": {
|
||||
"answer": [],
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
{
|
||||
"id": 7,
|
||||
"title": "Medical consultation",
|
||||
"description": "Medical Consultation Assistant, can provide you with some professional consultation suggestions for your reference. Please note that the content provided by the medical assistant is for reference only and may not be authentic or available. Knowledge Base Content Reference: <a href = 'https://huggingface.co/datasets/InfiniFlow/medical_QA/tree/main'> Medical Knowledge Base Reference</a>",
|
||||
"description": "A consultant that offers medical suggestions using an internal QA dataset and PubMed search results. Note that this agent's answers are for reference only and may not be valid. The dataset can be found at https://huggingface.co/datasets/InfiniFlow/medical_QA/tree/main",
|
||||
"canvas_type": "chatbot",
|
||||
"dsl": {
|
||||
"answer": [],
|
||||
@ -534,7 +534,7 @@
|
||||
{
|
||||
"data": {
|
||||
"form": {
|
||||
"text": "A prompt sumerize content from search result from PubMed and Q&A dataset."
|
||||
"text": "A prompt summarize content from search result from PubMed and Q&A dataset."
|
||||
},
|
||||
"label": "Note",
|
||||
"name": "N: LLM"
|
||||
|
||||
1410
agent/templates/seo_blog.json
Normal file
1410
agent/templates/seo_blog.json
Normal file
File diff suppressed because one or more lines are too long
@ -440,7 +440,7 @@
|
||||
{
|
||||
"data": {
|
||||
"form": {
|
||||
"text": "DDL(Data Definition Language).\n\nSearches for relevent database creation statements.\n\nIt should bind with a KB to which DDL is dumped in.\nYou could use 'General' as parsing method and ';' as delimiter."
|
||||
"text": "DDL(Data Definition Language).\n\nSearches for relevant database creation statements.\n\nIt should bind with a KB to which DDL is dumped in.\nYou could use 'General' as parsing method and ';' as delimiter."
|
||||
},
|
||||
"label": "Note",
|
||||
"name": "N: DDL"
|
||||
|
||||
@ -577,7 +577,7 @@
|
||||
"text": "Based on the keywords, searches on Wikipedia and returns the found content."
|
||||
},
|
||||
"label": "Note",
|
||||
"name": "N: Wiukipedia"
|
||||
"name": "N: Wikipedia"
|
||||
},
|
||||
"dragging": false,
|
||||
"height": 128,
|
||||
|
||||
@ -43,6 +43,7 @@ if __name__ == '__main__':
|
||||
else:
|
||||
print(ans["content"])
|
||||
|
||||
if DEBUG: print(canvas.path)
|
||||
if DEBUG:
|
||||
print(canvas.path)
|
||||
question = input("\n==================== User =====================\n> ")
|
||||
canvas.add_user_input(question)
|
||||
|
||||
@ -0,0 +1,2 @@
|
||||
from beartype.claw import beartype_this_package
|
||||
beartype_this_package()
|
||||
|
||||
@ -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}' 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()
|
||||
|
||||
@ -32,7 +32,7 @@ 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, \
|
||||
generate_confirmation_token
|
||||
@ -45,14 +45,14 @@ from agent.canvas import Canvas
|
||||
from functools import partial
|
||||
|
||||
|
||||
@manager.route('/new_token', methods=['POST'])
|
||||
@manager.route('/new_token', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
def new_token():
|
||||
req = request.json
|
||||
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),
|
||||
@ -68,20 +68,20 @@ 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:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/token_list', methods=['GET'])
|
||||
@manager.route('/token_list', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
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)
|
||||
@ -90,7 +90,7 @@ def token_list():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/rm', methods=['POST'])
|
||||
@manager.route('/rm', methods=['POST']) # noqa: F821
|
||||
@validate_request("tokens", "tenant_id")
|
||||
@login_required
|
||||
def rm():
|
||||
@ -104,13 +104,13 @@ def rm():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/stats', methods=['GET'])
|
||||
@manager.route('/stats', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
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(
|
||||
@ -135,14 +135,13 @@ def stats():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/new_conversation', methods=['GET'])
|
||||
@manager.route('/new_conversation', methods=['GET']) # noqa: F821
|
||||
def set_conversation():
|
||||
token = request.headers.get('Authorization').split()[1]
|
||||
objs = APIToken.query(token=token)
|
||||
if not objs:
|
||||
return get_json_result(
|
||||
data=False, retmsg='Token is not valid!"', retcode=RetCode.AUTHENTICATION_ERROR)
|
||||
req = request.json
|
||||
data=False, message='Token is not valid!"', code=settings.RetCode.AUTHENTICATION_ERROR)
|
||||
try:
|
||||
if objs[0].source == "agent":
|
||||
e, cvs = UserCanvasService.get_by_id(objs[0].dialog_id)
|
||||
@ -163,7 +162,7 @@ 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,
|
||||
@ -176,19 +175,20 @@ def set_conversation():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/completion', methods=['POST'])
|
||||
@manager.route('/completion', methods=['POST']) # noqa: F821
|
||||
@validate_request("conversation_id", "messages")
|
||||
def completion():
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
req = request.json
|
||||
e, conv = API4ConversationService.get_by_id(req["conversation_id"])
|
||||
if not e:
|
||||
return get_data_error_result(retmsg="Conversation not found!")
|
||||
if "quote" not in req: req["quote"] = False
|
||||
return get_data_error_result(message="Conversation not found!")
|
||||
if "quote" not in req:
|
||||
req["quote"] = False
|
||||
|
||||
msg = []
|
||||
for m in req["messages"]:
|
||||
@ -197,7 +197,8 @@ def completion():
|
||||
if m["role"] == "assistant" and not msg:
|
||||
continue
|
||||
msg.append(m)
|
||||
if not msg[-1].get("id"): msg[-1]["id"] = get_uuid()
|
||||
if not msg[-1].get("id"):
|
||||
msg[-1]["id"] = get_uuid()
|
||||
message_id = msg[-1]["id"]
|
||||
|
||||
def fillin_conv(ans):
|
||||
@ -257,19 +258,20 @@ 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")
|
||||
@ -289,12 +291,12 @@ 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"]
|
||||
|
||||
@ -309,14 +311,14 @@ 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")
|
||||
@ -325,7 +327,7 @@ 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
|
||||
@ -339,25 +341,25 @@ def completion():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/conversation/<conversation_id>', methods=['GET'])
|
||||
@manager.route('/conversation/<conversation_id>', methods=['GET']) # noqa: F821
|
||||
# @login_required
|
||||
def get(conversation_id):
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
|
||||
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
|
||||
@ -370,14 +372,14 @@ def get(conversation_id):
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/document/upload', methods=['POST'])
|
||||
@manager.route('/document/upload', methods=['POST']) # noqa: F821
|
||||
@validate_request("kb_name")
|
||||
def upload():
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
|
||||
kb_name = request.form.get("kb_name").strip()
|
||||
tenant_id = objs[0].tenant_id
|
||||
@ -386,19 +388,19 @@ 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"]
|
||||
@ -409,7 +411,7 @@ 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,
|
||||
@ -418,7 +420,7 @@ 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):
|
||||
@ -467,7 +469,7 @@ 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"]])
|
||||
@ -482,37 +484,37 @@ def upload():
|
||||
return get_json_result(data=doc_result.to_json())
|
||||
|
||||
|
||||
@manager.route('/document/upload_and_parse', methods=['POST'])
|
||||
@manager.route('/document/upload_and_parse', methods=['POST']) # noqa: F821
|
||||
@validate_request("conversation_id")
|
||||
def upload_parse():
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/list_chunks', methods=['POST'])
|
||||
@manager.route('/list_chunks', methods=['POST']) # noqa: F821
|
||||
# @login_required
|
||||
def list_chunks():
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
|
||||
req = request.json
|
||||
|
||||
@ -526,15 +528,16 @@ 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
|
||||
]
|
||||
|
||||
@ -544,14 +547,14 @@ def list_chunks():
|
||||
return get_json_result(data=res)
|
||||
|
||||
|
||||
@manager.route('/list_kb_docs', methods=['POST'])
|
||||
@manager.route('/list_kb_docs', methods=['POST']) # noqa: F821
|
||||
# @login_required
|
||||
def list_kb_docs():
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
|
||||
req = request.json
|
||||
tenant_id = objs[0].tenant_id
|
||||
@ -561,7 +564,7 @@ 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:
|
||||
@ -583,28 +586,29 @@ def list_kb_docs():
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
@manager.route('/document/infos', methods=['POST'])
|
||||
|
||||
@manager.route('/document/infos', methods=['POST']) # noqa: F821
|
||||
@validate_request("doc_ids")
|
||||
def docinfos():
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
req = request.json
|
||||
doc_ids = req["doc_ids"]
|
||||
docs = DocumentService.get_by_ids(doc_ids)
|
||||
return get_json_result(data=list(docs.dicts()))
|
||||
|
||||
|
||||
@manager.route('/document', methods=['DELETE'])
|
||||
@manager.route('/document', methods=['DELETE']) # noqa: F821
|
||||
# @login_required
|
||||
def document_rm():
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
|
||||
tenant_id = objs[0].tenant_id
|
||||
req = request.json
|
||||
@ -616,7 +620,7 @@ 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:
|
||||
@ -631,16 +635,16 @@ 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])
|
||||
@ -651,12 +655,12 @@ 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)
|
||||
|
||||
|
||||
@manager.route('/completion_aibotk', methods=['POST'])
|
||||
@manager.route('/completion_aibotk', methods=['POST']) # noqa: F821
|
||||
@validate_request("Authorization", "conversation_id", "word")
|
||||
def completion_faq():
|
||||
import base64
|
||||
@ -666,16 +670,18 @@ 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!")
|
||||
if "quote" not in req: req["quote"] = True
|
||||
return get_data_error_result(message="Conversation not found!")
|
||||
if "quote" not in req:
|
||||
req["quote"] = True
|
||||
|
||||
msg = []
|
||||
msg.append({"role": "user", "content": req["word"]})
|
||||
if not msg[-1].get("id"): msg[-1]["id"] = get_uuid()
|
||||
if not msg[-1].get("id"):
|
||||
msg[-1]["id"] = get_uuid()
|
||||
message_id = msg[-1]["id"]
|
||||
|
||||
def fillin_conv(ans):
|
||||
@ -751,7 +757,7 @@ 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:
|
||||
@ -796,17 +802,17 @@ def completion_faq():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/retrieval', methods=['POST'])
|
||||
@manager.route('/retrieval', methods=['POST']) # noqa: F821
|
||||
@validate_request("kb_id", "question")
|
||||
def retrieval():
|
||||
token = request.headers.get('Authorization').split()[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)
|
||||
|
||||
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))
|
||||
@ -820,26 +826,26 @@ 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)
|
||||
|
||||
@ -14,7 +14,7 @@
|
||||
# limitations under the License.
|
||||
#
|
||||
import json
|
||||
from functools import partial
|
||||
import traceback
|
||||
from flask import request, Response
|
||||
from flask_login import login_required, current_user
|
||||
from api.db.services.canvas_service import CanvasTemplateService, UserCanvasService
|
||||
@ -23,15 +23,16 @@ from api.utils import get_uuid
|
||||
from api.utils.api_utils import get_json_result, server_error_response, validate_request, get_data_error_result
|
||||
from agent.canvas import Canvas
|
||||
from peewee import MySQLDatabase, PostgresqlDatabase
|
||||
from api.db.db_models import APIToken
|
||||
|
||||
|
||||
@manager.route('/templates', methods=['GET'])
|
||||
@manager.route('/templates', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def templates():
|
||||
return get_json_result(data=[c.to_dict() for c in CanvasTemplateService.get_all()])
|
||||
|
||||
|
||||
@manager.route('/list', methods=['GET'])
|
||||
@manager.route('/list', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def canvas_list():
|
||||
return get_json_result(data=sorted([c.to_dict() for c in \
|
||||
@ -39,53 +40,68 @@ def canvas_list():
|
||||
)
|
||||
|
||||
|
||||
@manager.route('/rm', methods=['POST'])
|
||||
@manager.route('/rm', methods=['POST']) # noqa: F821
|
||||
@validate_request("canvas_ids")
|
||||
@login_required
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/set', methods=['POST'])
|
||||
@manager.route('/set', methods=['POST']) # noqa: F821
|
||||
@validate_request("dsl", "title")
|
||||
@login_required
|
||||
def save():
|
||||
req = request.json
|
||||
req["user_id"] = current_user.id
|
||||
if not isinstance(req["dsl"], str): req["dsl"] = json.dumps(req["dsl"], ensure_ascii=False)
|
||||
if not isinstance(req["dsl"], str):
|
||||
req["dsl"] = json.dumps(req["dsl"], ensure_ascii=False)
|
||||
|
||||
req["dsl"] = json.loads(req["dsl"])
|
||||
if "id" not in req:
|
||||
if UserCanvasService.query(user_id=current_user.id, title=req["title"].strip()):
|
||||
return server_error_response(ValueError("Duplicated title."))
|
||||
return get_data_error_result(f"{req['title'].strip()} already exists.")
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/get/<canvas_id>', methods=['GET'])
|
||||
@manager.route('/get/<canvas_id>', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
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())
|
||||
|
||||
@manager.route('/getsse/<canvas_id>', methods=['GET']) # type: ignore # noqa: F821
|
||||
def getsse(canvas_id):
|
||||
token = request.headers.get('Authorization').split()
|
||||
if len(token) != 2:
|
||||
return get_data_error_result(message='Authorization is not valid!"')
|
||||
token = token[1]
|
||||
objs = APIToken.query(beta=token)
|
||||
if not objs:
|
||||
return get_data_error_result(message='Token is not valid!"')
|
||||
e, c = UserCanvasService.get_by_id(canvas_id)
|
||||
if not e:
|
||||
return get_data_error_result(message="canvas not found.")
|
||||
return get_json_result(data=c.to_dict())
|
||||
|
||||
|
||||
@manager.route('/completion', methods=['POST'])
|
||||
@manager.route('/completion', methods=['POST']) # noqa: F821
|
||||
@validate_request("id")
|
||||
@login_required
|
||||
def run():
|
||||
@ -93,11 +109,11 @@ 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)
|
||||
@ -108,40 +124,40 @@ 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_info_by(current_user.id)[0]
|
||||
#req["message"] = full_question(ten["tenant_id"], ten["llm_id"], canvas.messages)
|
||||
pass
|
||||
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")
|
||||
@ -150,16 +166,19 @@ 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'])
|
||||
@manager.route('/reset', methods=['POST']) # noqa: F821
|
||||
@validate_request("id")
|
||||
@login_required
|
||||
def reset():
|
||||
@ -167,11 +186,11 @@ 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()
|
||||
@ -182,7 +201,51 @@ def reset():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/test_db_connect', methods=['POST'])
|
||||
@manager.route('/input_elements', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def input_elements():
|
||||
cvs_id = request.args.get("id")
|
||||
cpn_id = request.args.get("component_id")
|
||||
try:
|
||||
e, user_canvas = UserCanvasService.get_by_id(cvs_id)
|
||||
if not e:
|
||||
return get_data_error_result(message="canvas not found.")
|
||||
if not UserCanvasService.query(user_id=current_user.id, id=cvs_id):
|
||||
return get_json_result(
|
||||
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)
|
||||
return get_json_result(data=canvas.get_component_input_elements(cpn_id))
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/debug', methods=['POST']) # noqa: F821
|
||||
@validate_request("id", "component_id", "params")
|
||||
@login_required
|
||||
def debug():
|
||||
req = request.json
|
||||
for p in req["params"]:
|
||||
assert p.get("key")
|
||||
try:
|
||||
e, user_canvas = UserCanvasService.get_by_id(req["id"])
|
||||
if not e:
|
||||
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, message='Only owner of canvas authorized for this operation.',
|
||||
code=RetCode.OPERATING_ERROR)
|
||||
|
||||
canvas = Canvas(json.dumps(user_canvas.dsl), current_user.id)
|
||||
canvas.get_component(req["component_id"])["obj"]._param.debug_inputs = req["params"]
|
||||
df = canvas.get_component(req["component_id"])["obj"].debug()
|
||||
return get_json_result(data=df.to_dict(orient="records"))
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/test_db_connect', methods=['POST']) # noqa: F821
|
||||
@validate_request("db_type", "database", "username", "host", "port", "password")
|
||||
@login_required
|
||||
def test_db_connect():
|
||||
@ -194,8 +257,26 @@ def test_db_connect():
|
||||
elif req["db_type"] == 'postgresql':
|
||||
db = PostgresqlDatabase(req["database"], user=req["username"], host=req["host"], port=req["port"],
|
||||
password=req["password"])
|
||||
db.connect()
|
||||
elif req["db_type"] == 'mssql':
|
||||
import pyodbc
|
||||
connection_string = (
|
||||
f"DRIVER={{ODBC Driver 17 for SQL Server}};"
|
||||
f"SERVER={req['host']},{req['port']};"
|
||||
f"DATABASE={req['database']};"
|
||||
f"UID={req['username']};"
|
||||
f"PWD={req['password']};"
|
||||
)
|
||||
db = pyodbc.connect(connection_string)
|
||||
cursor = db.cursor()
|
||||
cursor.execute("SELECT 1")
|
||||
cursor.close()
|
||||
else:
|
||||
return server_error_response("Unsupported database type.")
|
||||
if req["db_type"] != 'mssql':
|
||||
db.connect()
|
||||
db.close()
|
||||
|
||||
return get_json_result(data="Database Connection Successful!")
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@ -15,16 +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
|
||||
from rag.utils.es_conn import ELASTICSEARCH
|
||||
from rag.utils import rmSpace
|
||||
from api.db import LLMType, ParserType
|
||||
from api.db.services.knowledgebase_service import KnowledgebaseService
|
||||
@ -32,13 +29,13 @@ 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 xxhash
|
||||
import re
|
||||
|
||||
|
||||
@manager.route('/list', methods=['POST'])
|
||||
@manager.route('/list', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("doc_id")
|
||||
def list_chunk():
|
||||
@ -50,16 +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 = {
|
||||
@ -70,60 +68,55 @@ 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", ""),
|
||||
"available_int": sres.field[id].get("available_int", 1),
|
||||
"positions": sres.field[id].get("position_int", "").split("\t")
|
||||
"question_kwd": sres.field[id].get("question_kwd", []),
|
||||
"image_id": sres.field[id].get("img_id", ""),
|
||||
"available_int": int(sres.field[id].get("available_int", 1)),
|
||||
"positions": sres.field[id].get("position_int", []),
|
||||
}
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/get', methods=['GET'])
|
||||
@manager.route('/get', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def get():
|
||||
chunk_id = request.args["chunk_id"]
|
||||
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 server_error_response("Chunk not found")
|
||||
id = res["_id"]
|
||||
res = res["_source"]
|
||||
res["chunk_id"] = id
|
||||
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(Exception("Chunk not found"))
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/set', methods=['POST'])
|
||||
@manager.route('/set', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("doc_id", "chunk_id", "content_with_weight",
|
||||
"important_kwd")
|
||||
"important_kwd", "question_kwd")
|
||||
def set():
|
||||
req = request.json
|
||||
d = {
|
||||
@ -133,20 +126,22 @@ def set():
|
||||
d["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(d["content_ltks"])
|
||||
d["important_kwd"] = req["important_kwd"]
|
||||
d["important_tks"] = rag_tokenizer.tokenize(" ".join(req["important_kwd"]))
|
||||
d["question_kwd"] = req["question_kwd"]
|
||||
d["question_tks"] = rag_tokenizer.tokenize("\n".join(req["question_kwd"]))
|
||||
if "available_int" in req:
|
||||
d["available_int"] = req["available_int"]
|
||||
|
||||
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 = [
|
||||
@ -155,49 +150,51 @@ 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]))
|
||||
|
||||
v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
|
||||
v, c = embd_mdl.encode([doc.name, req["content_with_weight"] if not d["question_kwd"] else "\n".join(d["question_kwd"])])
|
||||
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.update({"id": req["chunk_id"]}, d, search.index_name(tenant_id), doc.kb_id)
|
||||
return get_json_result(data=True)
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/switch', methods=['POST'])
|
||||
@manager.route('/switch', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("chunk_ids", "available_int", "doc_id")
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/rm', methods=['POST'])
|
||||
@manager.route('/rm', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("chunk_ids", "doc_id")
|
||||
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)
|
||||
@ -206,41 +203,48 @@ def rm():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/create', methods=['POST'])
|
||||
@manager.route('/create', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("doc_id", "content_with_weight")
|
||||
def create():
|
||||
req = request.json
|
||||
md5 = hashlib.md5()
|
||||
md5.update((req["content_with_weight"] + req["doc_id"]).encode("utf-8"))
|
||||
chunck_id = md5.hexdigest()
|
||||
chunck_id = xxhash.xxh64((req["content_with_weight"] + req["doc_id"]).encode("utf-8")).hexdigest()
|
||||
d = {"id": chunck_id, "content_ltks": rag_tokenizer.tokenize(req["content_with_weight"]),
|
||||
"content_with_weight": req["content_with_weight"]}
|
||||
d["content_sm_ltks"] = rag_tokenizer.fine_grained_tokenize(d["content_ltks"])
|
||||
d["important_kwd"] = req.get("important_kwd", [])
|
||||
d["important_tks"] = rag_tokenizer.tokenize(" ".join(req.get("important_kwd", [])))
|
||||
d["question_kwd"] = req.get("question_kwd", [])
|
||||
d["question_tks"] = rag_tokenizer.tokenize("\n".join(req.get("question_kwd", [])))
|
||||
d["create_time"] = str(datetime.datetime.now()).replace("T", " ")[:19]
|
||||
d["create_timestamp_flt"] = datetime.datetime.now().timestamp()
|
||||
|
||||
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["title_tks"] = rag_tokenizer.tokenize(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!")
|
||||
|
||||
e, kb = KnowledgebaseService.get_by_id(doc.kb_id)
|
||||
if not e:
|
||||
return get_data_error_result(message="Knowledgebase not found!")
|
||||
if kb.pagerank:
|
||||
d["pagerank_fea"] = kb.pagerank
|
||||
|
||||
embd_id = DocumentService.get_embd_id(req["doc_id"])
|
||||
embd_mdl = LLMBundle(tenant_id, LLMType.EMBEDDING.value, embd_id)
|
||||
|
||||
v, c = embd_mdl.encode([doc.name, req["content_with_weight"]])
|
||||
v, c = embd_mdl.encode([doc.name, req["content_with_weight"] if not d["question_kwd"] else "\n".join(d["question_kwd"])])
|
||||
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)
|
||||
@ -249,7 +253,7 @@ def create():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/retrieval_test', methods=['POST'])
|
||||
@manager.route('/retrieval_test', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("kb_id", "question")
|
||||
def retrieval_test():
|
||||
@ -257,28 +261,31 @@ 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)
|
||||
|
||||
@ -290,38 +297,38 @@ 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)
|
||||
|
||||
|
||||
@manager.route('/knowledge_graph', methods=['GET'])
|
||||
@manager.route('/knowledge_graph', methods=['GET']) # noqa: F821
|
||||
@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:
|
||||
content_json = json.loads(sres.field[id]["content_with_weight"])
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
continue
|
||||
|
||||
if ty == 'mind_map':
|
||||
@ -344,4 +351,3 @@ def knowledge_graph():
|
||||
obj[ty] = content_json
|
||||
|
||||
return get_json_result(data=obj)
|
||||
|
||||
|
||||
@ -17,21 +17,23 @@ import json
|
||||
import re
|
||||
import traceback
|
||||
from copy import deepcopy
|
||||
from api.db.db_models import APIToken
|
||||
|
||||
from api.db.services.conversation_service import ConversationService, structure_answer
|
||||
from api.db.services.user_service import UserTenantService
|
||||
from flask import request, Response
|
||||
from flask_login import login_required, current_user
|
||||
|
||||
from api.db import LLMType
|
||||
from api.db.services.dialog_service import DialogService, ConversationService, chat, ask
|
||||
from api.db.services.dialog_service import DialogService, 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 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
|
||||
|
||||
|
||||
@manager.route('/set', methods=['POST'])
|
||||
@manager.route('/set', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
def set_conversation():
|
||||
req = request.json
|
||||
@ -42,11 +44,11 @@ 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:
|
||||
@ -55,7 +57,7 @@ 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"],
|
||||
@ -65,36 +67,78 @@ 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:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/get', methods=['GET'])
|
||||
@manager.route('/get', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def get():
|
||||
conv_id = request.args["conversation_id"]
|
||||
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)
|
||||
avatar =None
|
||||
for tenant in tenants:
|
||||
if DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id):
|
||||
dialog = DialogService.query(tenant_id=tenant.tenant_id, id=conv.dialog_id)
|
||||
if dialog and len(dialog)>0:
|
||||
avatar = dialog[0].icon
|
||||
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)
|
||||
|
||||
def get_value(d, k1, k2):
|
||||
return d.get(k1, d.get(k2))
|
||||
|
||||
for ref in conv.reference:
|
||||
if isinstance(ref, list):
|
||||
continue
|
||||
ref["chunks"] = [{
|
||||
"id": get_value(ck, "chunk_id", "id"),
|
||||
"content": get_value(ck, "content", "content_with_weight"),
|
||||
"document_id": get_value(ck, "doc_id", "document_id"),
|
||||
"document_name": get_value(ck, "docnm_kwd", "document_name"),
|
||||
"dataset_id": get_value(ck, "kb_id", "dataset_id"),
|
||||
"image_id": get_value(ck, "image_id", "img_id"),
|
||||
"positions": get_value(ck, "positions", "position_int"),
|
||||
} for ck in ref.get("chunks", [])]
|
||||
|
||||
conv = conv.to_dict()
|
||||
conv["avatar"]=avatar
|
||||
return get_json_result(data=conv)
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
@manager.route('/getsse/<dialog_id>', methods=['GET']) # type: ignore # noqa: F821
|
||||
def getsse(dialog_id):
|
||||
|
||||
token = request.headers.get('Authorization').split()
|
||||
if len(token) != 2:
|
||||
return get_data_error_result(message='Authorization is not valid!"')
|
||||
token = token[1]
|
||||
objs = APIToken.query(beta=token)
|
||||
if not objs:
|
||||
return get_data_error_result(message='Token is not valid!"')
|
||||
try:
|
||||
e, conv = DialogService.get_by_id(dialog_id)
|
||||
if not e:
|
||||
return get_data_error_result(message="Dialog not found!")
|
||||
conv = conv.to_dict()
|
||||
conv["avatar"]= conv["icon"]
|
||||
del conv["icon"]
|
||||
return get_json_result(data=conv)
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
@manager.route('/rm', methods=['POST'])
|
||||
@manager.route('/rm', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
def rm():
|
||||
conv_ids = request.json["conversation_ids"]
|
||||
@ -102,41 +146,42 @@ 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:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/list', methods=['GET'])
|
||||
@manager.route('/list', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def list_convsersation():
|
||||
dialog_id = request.args["dialog_id"]
|
||||
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,
|
||||
reverse=True)
|
||||
|
||||
convs = [d.to_dict() for d in convs]
|
||||
return get_json_result(data=convs)
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/completion', methods=['POST'])
|
||||
@manager.route('/completion', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("conversation_id", "messages")
|
||||
def completion():
|
||||
@ -152,42 +197,49 @@ 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"]
|
||||
|
||||
if not conv.reference:
|
||||
conv.reference = []
|
||||
conv.message.append({"role": "assistant", "content": "", "id": message_id})
|
||||
else:
|
||||
def get_value(d, k1, k2):
|
||||
return d.get(k1, d.get(k2))
|
||||
|
||||
for ref in conv.reference:
|
||||
if isinstance(ref, list):
|
||||
continue
|
||||
ref["chunks"] = [{
|
||||
"id": get_value(ck, "chunk_id", "id"),
|
||||
"content": get_value(ck, "content", "content_with_weight"),
|
||||
"document_id": get_value(ck, "doc_id", "document_id"),
|
||||
"document_name": get_value(ck, "docnm_kwd", "document_name"),
|
||||
"dataset_id": get_value(ck, "kb_id", "dataset_id"),
|
||||
"image_id": get_value(ck, "image_id", "img_id"),
|
||||
"positions": get_value(ck, "positions", "position_int"),
|
||||
} for ck in ref.get("chunks", [])]
|
||||
|
||||
if not conv.reference:
|
||||
conv.reference = []
|
||||
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, True, **req):
|
||||
fillin_conv(ans)
|
||||
yield "data:" + json.dumps({"retcode": 0, "retmsg": "", "data": ans}, ensure_ascii=False) + "\n\n"
|
||||
ans = structure_answer(conv, ans, message_id, conv.id)
|
||||
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:
|
||||
traceback.print_exc()
|
||||
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")
|
||||
@ -200,8 +252,7 @@ def completion():
|
||||
else:
|
||||
answer = None
|
||||
for ans in chat(dia, msg, **req):
|
||||
answer = ans
|
||||
fillin_conv(ans)
|
||||
answer = structure_answer(conv, ans, message_id, req["conversation_id"])
|
||||
ConversationService.update_by_id(conv.id, conv.to_dict())
|
||||
break
|
||||
return get_json_result(data=answer)
|
||||
@ -209,7 +260,7 @@ def completion():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/tts', methods=['POST'])
|
||||
@manager.route('/tts', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
def tts():
|
||||
req = request.json
|
||||
@ -217,11 +268,11 @@ def tts():
|
||||
|
||||
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)
|
||||
|
||||
@ -231,7 +282,7 @@ 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')
|
||||
|
||||
@ -243,14 +294,14 @@ def tts():
|
||||
return resp
|
||||
|
||||
|
||||
@manager.route('/delete_msg', methods=['POST'])
|
||||
@manager.route('/delete_msg', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("conversation_id", "message_id")
|
||||
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"]):
|
||||
@ -266,14 +317,14 @@ def delete_msg():
|
||||
return get_json_result(data=conv)
|
||||
|
||||
|
||||
@manager.route('/thumbup', methods=['POST'])
|
||||
@manager.route('/thumbup', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("conversation_id", "message_id")
|
||||
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()
|
||||
@ -281,32 +332,35 @@ def thumbup():
|
||||
if req["message_id"] == msg.get("id", "") and msg.get("role", "") == "assistant":
|
||||
if up_down:
|
||||
msg["thumbup"] = True
|
||||
if "feedback" in msg: del msg["feedback"]
|
||||
if "feedback" in msg:
|
||||
del msg["feedback"]
|
||||
else:
|
||||
msg["thumbup"] = False
|
||||
if feedback: msg["feedback"] = feedback
|
||||
if feedback:
|
||||
msg["feedback"] = feedback
|
||||
break
|
||||
|
||||
ConversationService.update_by_id(conv["id"], conv)
|
||||
return get_json_result(data=conv)
|
||||
|
||||
|
||||
@manager.route('/ask', methods=['POST'])
|
||||
@manager.route('/ask', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("question", "kb_ids")
|
||||
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")
|
||||
@ -316,7 +370,7 @@ def ask_about():
|
||||
return resp
|
||||
|
||||
|
||||
@manager.route('/mindmap', methods=['POST'])
|
||||
@manager.route('/mindmap', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("question", "kb_ids")
|
||||
def mindmap():
|
||||
@ -324,13 +378,13 @@ 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:
|
||||
@ -338,7 +392,7 @@ def mindmap():
|
||||
return get_json_result(data=mind_map)
|
||||
|
||||
|
||||
@manager.route('/related_questions', methods=['POST'])
|
||||
@manager.route('/related_questions', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("question")
|
||||
def related_questions():
|
||||
|
||||
@ -20,27 +20,27 @@ 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
|
||||
|
||||
|
||||
@manager.route('/set', methods=['POST'])
|
||||
@manager.route('/set', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
def set_dialog():
|
||||
req = request.json
|
||||
dialog_id = req.get("dialog_id")
|
||||
name = req.get("name", "New Dialog")
|
||||
description = req.get("description", "A helpful Dialog")
|
||||
description = req.get("description", "A helpful dialog")
|
||||
icon = req.get("icon", "")
|
||||
top_n = req.get("top_n", 6)
|
||||
top_k = req.get("top_k", 1024)
|
||||
rerank_id = req.get("rerank_id", "")
|
||||
if not rerank_id: req["rerank_id"] = ""
|
||||
if not rerank_id:
|
||||
req["rerank_id"] = ""
|
||||
similarity_threshold = req.get("similarity_threshold", 0.1)
|
||||
vector_similarity_weight = req.get("vector_similarity_weight", 0.3)
|
||||
if vector_similarity_weight is None: vector_similarity_weight = 0.3
|
||||
llm_setting = req.get("llm_setting", {})
|
||||
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。
|
||||
@ -68,17 +68,23 @@ 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!")
|
||||
kbs = KnowledgebaseService.get_by_ids(req.get("kb_ids"))
|
||||
embd_count = len(set([kb.embd_id for kb in kbs]))
|
||||
if embd_count != 1:
|
||||
return get_data_error_result(message=f'Datasets use different embedding models: {[kb.embd_id for kb in kbs]}"')
|
||||
|
||||
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 +102,20 @@ 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)
|
||||
@ -117,14 +123,14 @@ def set_dialog():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/get', methods=['GET'])
|
||||
@manager.route('/get', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def get():
|
||||
dialog_id = request.args["dialog_id"]
|
||||
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)
|
||||
@ -143,7 +149,7 @@ def get_kb_names(kb_ids):
|
||||
return ids, nms
|
||||
|
||||
|
||||
@manager.route('/list', methods=['GET'])
|
||||
@manager.route('/list', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def list_dialogs():
|
||||
try:
|
||||
@ -160,7 +166,7 @@ def list_dialogs():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/rm', methods=['POST'])
|
||||
@manager.route('/rm', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("dialog_ids")
|
||||
def rm():
|
||||
@ -174,8 +180,8 @@ 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)
|
||||
|
||||
@ -13,52 +13,58 @@
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License
|
||||
#
|
||||
import os.path
|
||||
import pathlib
|
||||
import re
|
||||
|
||||
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 deepdoc.parser.html_parser import RAGFlowHtmlParser
|
||||
from rag.nlp import search
|
||||
|
||||
from api.db import FileType, TaskStatus, ParserType, FileSource
|
||||
from api.db.db_models import File, Task
|
||||
from api.db.services.file2document_service import File2DocumentService
|
||||
from api.db.services.file_service import FileService
|
||||
from api.db.services.task_service import TaskService, queue_tasks
|
||||
from api.db.services.task_service import queue_tasks
|
||||
from api.db.services.user_service import UserTenantService
|
||||
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
|
||||
from api.db.services.task_service import TaskService
|
||||
from api.db.services.document_service import DocumentService, doc_upload_and_parse
|
||||
from api.settings import RetCode
|
||||
from api.utils.api_utils import (
|
||||
server_error_response,
|
||||
get_data_error_result,
|
||||
validate_request,
|
||||
)
|
||||
from api.utils import get_uuid
|
||||
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
|
||||
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.contants import IMG_BASE64_PREFIX
|
||||
from api.constants import IMG_BASE64_PREFIX
|
||||
|
||||
|
||||
@manager.route('/upload', methods=['POST'])
|
||||
@manager.route('/upload', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("kb_id")
|
||||
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:
|
||||
@ -67,29 +73,30 @@ 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)
|
||||
|
||||
|
||||
@manager.route('/web_crawl', methods=['POST'])
|
||||
@manager.route('/web_crawl', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("kb_id", "name", "url")
|
||||
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!")
|
||||
|
||||
blob = html2pdf(url)
|
||||
if not blob: return server_error_response(ValueError("Download failure."))
|
||||
if not blob:
|
||||
return server_error_response(ValueError("Download failure."))
|
||||
|
||||
root_folder = FileService.get_root_folder(current_user.id)
|
||||
pf_id = root_folder["id"]
|
||||
@ -137,7 +144,7 @@ def web_crawl():
|
||||
return get_json_result(data=True)
|
||||
|
||||
|
||||
@manager.route('/create', methods=['POST'])
|
||||
@manager.route('/create', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("name", "kb_id")
|
||||
def create():
|
||||
@ -145,17 +152,17 @@ 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(),
|
||||
@ -173,13 +180,13 @@ def create():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/list', methods=['GET'])
|
||||
@manager.route('/list', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
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(
|
||||
@ -187,8 +194,8 @@ 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))
|
||||
@ -208,7 +215,7 @@ def list_docs():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/infos', methods=['POST'])
|
||||
@manager.route('/infos', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
def docinfos():
|
||||
req = request.json
|
||||
@ -217,20 +224,20 @@ def docinfos():
|
||||
if not DocumentService.accessible(doc_id, current_user.id):
|
||||
return get_json_result(
|
||||
data=False,
|
||||
retmsg='No authorization.',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR
|
||||
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
|
||||
@manager.route('/thumbnails', methods=['GET']) # noqa: F821
|
||||
# @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)
|
||||
@ -244,7 +251,7 @@ def thumbnails():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/change_status', methods=['POST'])
|
||||
@manager.route('/change_status', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("doc_id", "status")
|
||||
def change_status():
|
||||
@ -252,60 +259,52 @@ def change_status():
|
||||
if str(req["status"]) not in ["0", "1"]:
|
||||
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,
|
||||
retmsg='No authorization.',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR)
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/rm', methods=['POST'])
|
||||
@manager.route('/rm', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("doc_id")
|
||||
def rm():
|
||||
req = request.json
|
||||
doc_ids = req["doc_id"]
|
||||
if isinstance(doc_ids, str): doc_ids = [doc_ids]
|
||||
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,
|
||||
retmsg='No authorization.',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR
|
||||
message='No authorization.',
|
||||
code=settings.RetCode.AUTHENTICATION_ERROR
|
||||
)
|
||||
|
||||
root_folder = FileService.get_root_folder(current_user.id)
|
||||
@ -316,16 +315,17 @@ 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)
|
||||
|
||||
TaskService.filter_delete([Task.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])
|
||||
@ -336,12 +336,12 @@ 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)
|
||||
|
||||
|
||||
@manager.route('/run', methods=['POST'])
|
||||
@manager.route('/run', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("doc_ids", "run")
|
||||
def run():
|
||||
@ -350,26 +350,29 @@ def run():
|
||||
if not DocumentService.accessible(doc_id, current_user.id):
|
||||
return get_json_result(
|
||||
data=False,
|
||||
retmsg='No authorization.',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR
|
||||
message='No authorization.',
|
||||
code=settings.RetCode.AUTHENTICATION_ERROR
|
||||
)
|
||||
try:
|
||||
for id in req["doc_ids"]:
|
||||
info = {"run": str(req["run"]), "progress": 0}
|
||||
if str(req["run"]) == TaskStatus.RUNNING.value:
|
||||
if str(req["run"]) == TaskStatus.RUNNING.value and req.get("delete", False):
|
||||
info["progress_msg"] = ""
|
||||
info["chunk_num"] = 0
|
||||
info["token_num"] = 0
|
||||
DocumentService.update_by_id(id, info)
|
||||
# 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 req.get("delete", False):
|
||||
TaskService.filter_delete([Task.doc_id == id])
|
||||
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])
|
||||
e, doc = DocumentService.get_by_id(id)
|
||||
doc = doc.to_dict()
|
||||
doc["tenant_id"] = tenant_id
|
||||
@ -381,7 +384,7 @@ def run():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/rename', methods=['POST'])
|
||||
@manager.route('/rename', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("doc_id", "name")
|
||||
def rename():
|
||||
@ -389,28 +392,28 @@ def rename():
|
||||
if not DocumentService.accessible(req["doc_id"], current_user.id):
|
||||
return get_json_result(
|
||||
data=False,
|
||||
retmsg='No authorization.',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR
|
||||
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:
|
||||
@ -422,13 +425,13 @@ def rename():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/get/<doc_id>', methods=['GET'])
|
||||
@manager.route('/get/<doc_id>', methods=['GET']) # noqa: F821
|
||||
# @login_required
|
||||
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))
|
||||
@ -447,7 +450,7 @@ def get(doc_id):
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/change_parser', methods=['POST'])
|
||||
@manager.route('/change_parser', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("doc_id", "parser_id")
|
||||
def change_parser():
|
||||
@ -456,13 +459,13 @@ def change_parser():
|
||||
if not DocumentService.accessible(req["doc_id"], current_user.id):
|
||||
return get_json_result(
|
||||
data=False,
|
||||
retmsg='No authorization.',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR
|
||||
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:
|
||||
@ -473,35 +476,38 @@ def change_parser():
|
||||
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(retmsg="Not supported yet!")
|
||||
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:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/image/<image_id>', methods=['GET'])
|
||||
@manager.route('/image/<image_id>', methods=['GET']) # noqa: F821
|
||||
# @login_required
|
||||
def get_image(image_id):
|
||||
try:
|
||||
arr = image_id.split("-")
|
||||
if len(arr) != 2:
|
||||
return get_data_error_result(message="Image not found.")
|
||||
bkt, nm = image_id.split("-")
|
||||
response = flask.make_response(STORAGE_IMPL.get(bkt, nm))
|
||||
response.headers.set('Content-Type', 'image/JPEG')
|
||||
@ -510,20 +516,80 @@ def get_image(image_id):
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/upload_and_parse', methods=['POST'])
|
||||
@manager.route('/upload_and_parse', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("conversation_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']) # noqa: F821
|
||||
@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 r and r.response]
|
||||
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)
|
||||
|
||||
@ -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
|
||||
|
||||
@ -26,13 +24,11 @@ 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'])
|
||||
@manager.route('/convert', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("file_ids", "kb_ids")
|
||||
def convert():
|
||||
@ -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(),
|
||||
@ -96,7 +92,7 @@ def convert():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/rm', methods=['POST'])
|
||||
@manager.route('/rm', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("file_ids")
|
||||
def rm():
|
||||
@ -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)
|
||||
|
||||
@ -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
|
||||
|
||||
@ -29,15 +28,13 @@ 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
|
||||
|
||||
|
||||
@manager.route('/upload', methods=['POST'])
|
||||
@manager.route('/upload', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
# @validate_request("parent_id")
|
||||
def upload():
|
||||
@ -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)
|
||||
|
||||
@ -123,7 +120,7 @@ def upload():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/create', methods=['POST'])
|
||||
@manager.route('/create', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("name")
|
||||
def create():
|
||||
@ -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
|
||||
@ -163,7 +160,7 @@ def create():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/list', methods=['GET'])
|
||||
@manager.route('/list', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def list_files():
|
||||
pf_id = request.args.get("parent_id")
|
||||
@ -181,21 +178,21 @@ 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:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/root_folder', methods=['GET'])
|
||||
@manager.route('/root_folder', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def get_root_folder():
|
||||
try:
|
||||
@ -205,14 +202,14 @@ def get_root_folder():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/parent_folder', methods=['GET'])
|
||||
@manager.route('/parent_folder', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def get_parent_folder():
|
||||
file_id = request.args.get("file_id")
|
||||
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()})
|
||||
@ -220,14 +217,14 @@ def get_parent_folder():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/all_parent_folder', methods=['GET'])
|
||||
@manager.route('/all_parent_folder', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def get_all_parent_folders():
|
||||
file_id = request.args.get("file_id")
|
||||
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 = []
|
||||
@ -238,7 +235,7 @@ def get_all_parent_folders():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/rm', methods=['POST'])
|
||||
@manager.route('/rm', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("file_ids")
|
||||
def rm():
|
||||
@ -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)
|
||||
@ -287,7 +284,7 @@ def rm():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/rename', methods=['POST'])
|
||||
@manager.route('/rename', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("file_id", "name")
|
||||
def rename():
|
||||
@ -295,45 +292,50 @@ 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:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/get/<file_id>', methods=['GET'])
|
||||
# @login_required
|
||||
@manager.route('/get/<file_id>', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
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!")
|
||||
b, n = File2DocumentService.get_storage_address(file_id=file_id)
|
||||
response = flask.make_response(STORAGE_IMPL.get(b, n))
|
||||
return get_data_error_result(message="Document not found!")
|
||||
|
||||
blob = STORAGE_IMPL.get(file.parent_id, file.location)
|
||||
if not blob:
|
||||
b, n = File2DocumentService.get_storage_address(file_id=file_id)
|
||||
blob = STORAGE_IMPL.get(b, n)
|
||||
|
||||
response = flask.make_response(blob)
|
||||
ext = re.search(r"\.([^.]+)$", file.name)
|
||||
if ext:
|
||||
if file.type == FileType.VISUAL.value:
|
||||
@ -348,7 +350,7 @@ def get(file_id):
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/mv', methods=['POST'])
|
||||
@manager.route('/mv', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("src_file_ids", "dest_file_id")
|
||||
def move():
|
||||
@ -359,12 +361,12 @@ 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:
|
||||
|
||||
@ -21,24 +21,35 @@ 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.user_service import TenantService, UserTenantService
|
||||
from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
|
||||
from api.utils.api_utils import server_error_response, get_data_error_result, validate_request, not_allowed_parameters
|
||||
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 File
|
||||
from api.settings import RetCode
|
||||
from api.utils.api_utils import get_json_result
|
||||
from api import settings
|
||||
from rag.nlp import search
|
||||
from api.constants import DATASET_NAME_LIMIT
|
||||
|
||||
|
||||
@manager.route('/create', methods=['post'])
|
||||
@manager.route('/create', methods=['post']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("name")
|
||||
def create():
|
||||
req = request.json
|
||||
req["name"] = req["name"].strip()
|
||||
req["name"] = duplicate_name(
|
||||
dataset_name = req["name"]
|
||||
if not isinstance(dataset_name, str):
|
||||
return get_data_error_result(message="Dataset name must be string.")
|
||||
if dataset_name == "":
|
||||
return get_data_error_result(message="Dataset name can't be empty.")
|
||||
if len(dataset_name) >= DATASET_NAME_LIMIT:
|
||||
return get_data_error_result(
|
||||
message=f"Dataset name length is {len(dataset_name)} which is large than {DATASET_NAME_LIMIT}")
|
||||
|
||||
dataset_name = dataset_name.strip()
|
||||
dataset_name = duplicate_name(
|
||||
KnowledgebaseService.query,
|
||||
name=req["name"],
|
||||
name=dataset_name,
|
||||
tenant_id=current_user.id,
|
||||
status=StatusEnum.VALID.value)
|
||||
try:
|
||||
@ -47,7 +58,7 @@ 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()
|
||||
@ -56,49 +67,61 @@ def create():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/update', methods=['post'])
|
||||
@manager.route('/update', methods=['post']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("kb_id", "name", "description", "permission", "parser_id")
|
||||
@not_allowed_parameters("id", "tenant_id", "created_by", "create_time", "update_time", "create_date", "update_date", "created_by")
|
||||
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,
|
||||
retmsg='No authorization.',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR
|
||||
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:
|
||||
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):
|
||||
return get_data_error_result()
|
||||
|
||||
if kb.pagerank != req.get("pagerank", 0):
|
||||
if req.get("pagerank", 0) > 0:
|
||||
settings.docStoreConn.update({"kb_id": kb.id}, {"pagerank_fea": req["pagerank"]},
|
||||
search.index_name(kb.tenant_id), kb.id)
|
||||
else:
|
||||
# Elasticsearch requires pagerank_fea be non-zero!
|
||||
settings.docStoreConn.update({"exist": "pagerank_fea"}, {"remove": "pagerank_fea"},
|
||||
search.index_name(kb.tenant_id), kb.id)
|
||||
|
||||
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:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/detail', methods=['GET'])
|
||||
@manager.route('/detail', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def detail():
|
||||
kb_id = request.args["kb_id"]
|
||||
@ -110,34 +133,35 @@ 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)
|
||||
|
||||
|
||||
@manager.route('/list', methods=['GET'])
|
||||
@manager.route('/list', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def list_kbs():
|
||||
page_number = request.args.get("page", 1)
|
||||
items_per_page = request.args.get("page_size", 150)
|
||||
keywords = request.args.get("keywords", "")
|
||||
page_number = int(request.args.get("page", 1))
|
||||
items_per_page = int(request.args.get("page_size", 150))
|
||||
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)
|
||||
kbs = KnowledgebaseService.get_by_tenant_ids(
|
||||
[m["tenant_id"] for m in tenants], current_user.id, page_number, items_per_page, orderby, desc)
|
||||
return get_json_result(data=kbs)
|
||||
kbs, total = KnowledgebaseService.get_by_tenant_ids(
|
||||
[m["tenant_id"] for m in tenants], current_user.id, page_number, items_per_page, orderby, desc, keywords)
|
||||
return get_json_result(data={"kbs": kbs, "total": total})
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/rm', methods=['post'])
|
||||
@manager.route('/rm', methods=['post']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("kb_id")
|
||||
def rm():
|
||||
@ -145,27 +169,32 @@ def rm():
|
||||
if not KnowledgebaseService.accessible4deletion(req["kb_id"], current_user.id):
|
||||
return get_json_result(
|
||||
data=False,
|
||||
retmsg='No authorization.',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR
|
||||
message='No authorization.',
|
||||
code=settings.RetCode.AUTHENTICATION_ERROR
|
||||
)
|
||||
try:
|
||||
kbs = KnowledgebaseService.query(
|
||||
created_by=current_user.id, id=req["kb_id"])
|
||||
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])
|
||||
File2DocumentService.delete_by_document_id(doc.id)
|
||||
|
||||
FileService.filter_delete(
|
||||
[File.source_type == FileSource.KNOWLEDGEBASE, File.type == "folder", File.name == kbs[0].name])
|
||||
if not KnowledgebaseService.delete_by_id(req["kb_id"]):
|
||||
return get_data_error_result(
|
||||
retmsg="Database error (Knowledgebase removal)!")
|
||||
message="Database error (Knowledgebase removal)!")
|
||||
for kb in kbs:
|
||||
settings.docStoreConn.delete({"kb_id": kb.id}, search.index_name(kb.tenant_id), kb.id)
|
||||
settings.docStoreConn.deleteIdx(search.index_name(kb.tenant_id), kb.id)
|
||||
return get_json_result(data=True)
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
@ -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
|
||||
@ -27,7 +28,7 @@ from rag.llm import EmbeddingModel, ChatModel, RerankModel, CvModel, TTSModel
|
||||
import requests
|
||||
|
||||
|
||||
@manager.route('/factories', methods=['GET'])
|
||||
@manager.route('/factories', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def factories():
|
||||
try:
|
||||
@ -49,7 +50,7 @@ def factories():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/set_api_key', methods=['POST'])
|
||||
@manager.route('/set_api_key', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("llm_factory", "api_key")
|
||||
def set_api_key():
|
||||
@ -73,9 +74,9 @@ 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:
|
||||
@ -89,7 +90,7 @@ def set_api_key():
|
||||
if len(arr) == 0 or tc == 0:
|
||||
raise Exception("Fail")
|
||||
rerank_passed = True
|
||||
print(f'passed model rerank{llm.llm_name}',flush=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)
|
||||
@ -98,7 +99,7 @@ def set_api_key():
|
||||
break
|
||||
|
||||
if msg:
|
||||
return get_data_error_result(retmsg=msg)
|
||||
return get_data_error_result(message=msg)
|
||||
|
||||
llm_config = {
|
||||
"api_key": req["api_key"],
|
||||
@ -109,6 +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,
|
||||
@ -120,13 +122,14 @@ 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)
|
||||
|
||||
|
||||
@manager.route('/add_llm', methods=['POST'])
|
||||
@manager.route('/add_llm', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("llm_factory")
|
||||
def add_llm():
|
||||
@ -157,23 +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"]
|
||||
@ -201,18 +204,19 @@ 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"])
|
||||
if len(arr[0]) == 0 or tc == 0:
|
||||
if len(arr[0]) == 0:
|
||||
raise Exception("Fail")
|
||||
except Exception as e:
|
||||
msg += f"\nFail to access embedding model({llm['llm_name']})." + str(e)
|
||||
@ -224,7 +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:
|
||||
@ -232,28 +236,26 @@ 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!"])
|
||||
if len(arr) == 0 or tc == 0:
|
||||
arr, tc = mdl.similarity("Hello~ Ragflower!", ["Hi, there!", "Ohh, my friend!"])
|
||||
if len(arr) == 0:
|
||||
raise Exception("Not known.")
|
||||
except Exception as e:
|
||||
msg += f"\nFail to access model({llm['llm_name']})." + str(
|
||||
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:
|
||||
img_url = (
|
||||
"https://upload.wikimedia.org/wikipedia/comm"
|
||||
"ons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/256"
|
||||
"0px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
|
||||
"https://www.8848seo.cn/zb_users/upload/2022/07/20220705101240_99378.jpg"
|
||||
)
|
||||
res = requests.get(img_url)
|
||||
if res.status_code == 200:
|
||||
@ -278,36 +280,38 @@ 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)
|
||||
|
||||
|
||||
@manager.route('/delete_llm', methods=['POST'])
|
||||
@manager.route('/delete_llm', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("llm_factory", "llm_name")
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/delete_factory', methods=['POST'])
|
||||
@manager.route('/delete_factory', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("llm_factory")
|
||||
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)
|
||||
|
||||
|
||||
@manager.route('/my_llms', methods=['GET'])
|
||||
@manager.route('/my_llms', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def my_llms():
|
||||
try:
|
||||
@ -328,11 +332,11 @@ def my_llms():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/list', methods=['GET'])
|
||||
@manager.route('/list', methods=['GET']) # noqa: F821
|
||||
@login_required
|
||||
def list_app():
|
||||
self_deploied = ["Youdao","FastEmbed", "BAAI", "Ollama", "Xinference", "LocalAI", "LM-Studio"]
|
||||
weighted = ["Youdao","FastEmbed", "BAAI"] if LIGHTEN != 0 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)
|
||||
@ -343,15 +347,17 @@ 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"]+"@"+m["fid"] 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+"@"+o.llm_factory 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"]] = []
|
||||
@ -359,4 +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)
|
||||
39
api/apps/sdk/agent.py
Normal file
39
api/apps/sdk/agent.py
Normal file
@ -0,0 +1,39 @@
|
||||
#
|
||||
# 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 api.db.services.canvas_service import UserCanvasService
|
||||
from api.utils.api_utils import get_error_data_result, token_required
|
||||
from api.utils.api_utils import get_result
|
||||
from flask import request
|
||||
|
||||
@manager.route('/agents', methods=['GET']) # noqa: F821
|
||||
@token_required
|
||||
def list_agents(tenant_id):
|
||||
id = request.args.get("id")
|
||||
title = request.args.get("title")
|
||||
if id or title:
|
||||
canvas = UserCanvasService.query(id=id, title=title, user_id=tenant_id)
|
||||
if not canvas:
|
||||
return get_error_data_result("The agent 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", "update_time")
|
||||
if request.args.get("desc") == "False" or request.args.get("desc") == "false":
|
||||
desc = False
|
||||
else:
|
||||
desc = True
|
||||
canvas = UserCanvasService.get_list(tenant_id,page_number,items_per_page,orderby,desc,id,title)
|
||||
return get_result(data=canvas)
|
||||
@ -14,7 +14,7 @@
|
||||
# limitations under the License.
|
||||
#
|
||||
from flask import request
|
||||
from api.settings import RetCode
|
||||
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
|
||||
@ -26,24 +26,25 @@ from api.utils.api_utils import get_result
|
||||
|
||||
|
||||
|
||||
@manager.route('/chats', methods=['POST'])
|
||||
@manager.route('/chats', methods=['POST']) # noqa: F821
|
||||
@token_required
|
||||
def create(tenant_id):
|
||||
req=request.json
|
||||
ids= req.get("dataset_ids")
|
||||
if not ids:
|
||||
return get_error_data_result(retmsg="`dataset_ids` is required")
|
||||
return get_error_data_result(message="`dataset_ids` is required")
|
||||
for kb_id in ids:
|
||||
kbs = KnowledgebaseService.query(id=kb_id,tenant_id=tenant_id)
|
||||
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}")
|
||||
kb=kbs[0]
|
||||
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(retmsg='Datasets use different embedding models."',retcode=RetCode.AUTHENTICATION_ERROR)
|
||||
return get_result(message='Datasets use different embedding models."',code=settings.RetCode.AUTHENTICATION_ERROR)
|
||||
req["kb_ids"] = ids
|
||||
# llm
|
||||
llm = req.get("llm")
|
||||
@ -55,7 +56,7 @@ def create(tenant_id):
|
||||
req["llm_setting"] = req.pop("llm")
|
||||
e, tenant = TenantService.get_by_id(tenant_id)
|
||||
if not e:
|
||||
return get_error_data_result(retmsg="Tenant not found!")
|
||||
return get_error_data_result(message="Tenant not found!")
|
||||
# prompt
|
||||
prompt = req.get("prompt")
|
||||
key_mapping = {"parameters": "variables",
|
||||
@ -81,17 +82,18 @@ def create(tenant_id):
|
||||
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"):
|
||||
value_rerank_model = ["BAAI/bge-reranker-v2-m3","maidalun1020/bce-reranker-base_v1"]
|
||||
if req["rerank_id"] not in value_rerank_model and 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(retmsg="`name` is required.")
|
||||
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(retmsg="Duplicated chat name in creating chat.")
|
||||
return get_error_data_result(message="Duplicated chat name in creating chat.")
|
||||
# tenant_id
|
||||
if req.get("tenant_id"):
|
||||
return get_error_data_result(retmsg="`tenant_id` must not be provided.")
|
||||
return get_error_data_result(message="`tenant_id` must not be provided.")
|
||||
req["tenant_id"] = tenant_id
|
||||
# prompt more parameter
|
||||
default_prompt = {
|
||||
@ -103,28 +105,31 @@ def create(tenant_id):
|
||||
"parameters": [
|
||||
{"key": "knowledge", "optional": False}
|
||||
],
|
||||
"empty_response": "Sorry! No relevant content was found in the knowledge base!"
|
||||
"empty_response": "Sorry! No relevant content was found in the knowledge base!",
|
||||
"quote":True,
|
||||
"tts":False,
|
||||
"refine_multiturn":True
|
||||
}
|
||||
key_list_2 = ["system", "prologue", "parameters", "empty_response"]
|
||||
key_list_2 = ["system", "prologue", "parameters", "empty_response","quote","tts","refine_multiturn"]
|
||||
if "prompt_config" not in req:
|
||||
req['prompt_config'] = {}
|
||||
for key in key_list_2:
|
||||
temp = req['prompt_config'].get(key)
|
||||
if not temp:
|
||||
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(
|
||||
retmsg="Parameter '{}' is not used".format(p["key"]))
|
||||
message="Parameter '{}' is not used".format(p["key"]))
|
||||
# save
|
||||
if not DialogService.save(**req):
|
||||
return get_error_data_result(retmsg="Fail to new a chat!")
|
||||
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(retmsg="Fail to new a chat!")
|
||||
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():
|
||||
@ -146,23 +151,24 @@ def create(tenant_id):
|
||||
res["avatar"] = res.pop("icon")
|
||||
return get_result(data=res)
|
||||
|
||||
@manager.route('/chats/<chat_id>', methods=['PUT'])
|
||||
@manager.route('/chats/<chat_id>', methods=['PUT']) # noqa: F821
|
||||
@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(retmsg='You do not own the chat')
|
||||
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")
|
||||
return get_error_data_result("`dataset_ids` can't be empty")
|
||||
if ids:
|
||||
for kb_id in ids:
|
||||
kbs = KnowledgebaseService.query(id=kb_id, tenant_id=tenant_id)
|
||||
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")
|
||||
@ -170,8 +176,8 @@ def update(tenant_id,chat_id):
|
||||
embd_count=list(set([kb.embd_id for kb in kbs]))
|
||||
if len(embd_count) != 1 :
|
||||
return get_result(
|
||||
retmsg='Datasets use different embedding models."',
|
||||
retcode=RetCode.AUTHENTICATION_ERROR)
|
||||
message='Datasets use different embedding models."',
|
||||
code=settings.RetCode.AUTHENTICATION_ERROR)
|
||||
req["kb_ids"] = ids
|
||||
llm = req.get("llm")
|
||||
if llm:
|
||||
@ -182,10 +188,7 @@ def update(tenant_id,chat_id):
|
||||
req["llm_setting"] = req.pop("llm")
|
||||
e, tenant = TenantService.get_by_id(tenant_id)
|
||||
if not e:
|
||||
return get_error_data_result(retmsg="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")
|
||||
return get_error_data_result(message="Tenant not found!")
|
||||
# prompt
|
||||
prompt = req.get("prompt")
|
||||
key_mapping = {"parameters": "variables",
|
||||
@ -205,20 +208,24 @@ def update(tenant_id,chat_id):
|
||||
req["prompt_config"] = req.pop("prompt")
|
||||
e, res = DialogService.get_by_id(chat_id)
|
||||
res = res.to_json()
|
||||
if req.get("rerank_id"):
|
||||
value_rerank_model = ["BAAI/bge-reranker-v2-m3","maidalun1020/bce-reranker-base_v1"]
|
||||
if req["rerank_id"] not in value_rerank_model and 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 "name" in req:
|
||||
if not req.get("name"):
|
||||
return get_error_data_result(retmsg="`name` is not empty.")
|
||||
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(retmsg="Duplicated chat name in updating dataset.")
|
||||
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(retmsg="Parameter '{}' is not used".format(p["key"]))
|
||||
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"]
|
||||
@ -229,11 +236,11 @@ def update(tenant_id,chat_id):
|
||||
if "dataset_ids" in req:
|
||||
req.pop("dataset_ids")
|
||||
if not DialogService.update_by_id(chat_id, req):
|
||||
return get_error_data_result(retmsg="Chat not found!")
|
||||
return get_error_data_result(message="Chat not found!")
|
||||
return get_result()
|
||||
|
||||
|
||||
@manager.route('/chats', methods=['DELETE'])
|
||||
@manager.route('/chats', methods=['DELETE']) # noqa: F821
|
||||
@token_required
|
||||
def delete(tenant_id):
|
||||
req = request.json
|
||||
@ -250,21 +257,21 @@ def delete(tenant_id):
|
||||
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(retmsg=f"You don't own the chat {id}")
|
||||
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'])
|
||||
@manager.route('/chats', methods=['GET']) # noqa: F821
|
||||
@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)
|
||||
chat = DialogService.query(id=id,name=name,status=StatusEnum.VALID.value,tenant_id=tenant_id)
|
||||
if not chat:
|
||||
return get_error_data_result(retmsg="The chat doesn't exist")
|
||||
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", 1024))
|
||||
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
|
||||
@ -302,10 +309,10 @@ def list_chat(tenant_id):
|
||||
for kb_id in res["kb_ids"]:
|
||||
kb = KnowledgebaseService.query(id=kb_id)
|
||||
if not kb :
|
||||
return get_error_data_result(retmsg=f"Don't exist the kb {kb_id}")
|
||||
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)
|
||||
return get_result(data=list_assts)
|
||||
@ -1,232 +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.llm_service import TenantLLMService,LLMService
|
||||
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_result, token_required, get_error_data_result, valid,get_parser_config
|
||||
|
||||
|
||||
@manager.route('/datasets', methods=['POST'])
|
||||
@token_required
|
||||
def create(tenant_id):
|
||||
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(
|
||||
retmsg="`tenant_id` must not be provided")
|
||||
if "chunk_count" in req or "document_count" in req:
|
||||
return get_error_data_result(retmsg="`chunk_count` or `document_count` must not be provided")
|
||||
if "name" not in req:
|
||||
return get_error_data_result(
|
||||
retmsg="`name` is not empty!")
|
||||
req['id'] = get_uuid()
|
||||
req["name"] = req["name"].strip()
|
||||
if req["name"] == "":
|
||||
return get_error_data_result(
|
||||
retmsg="`name` is not empty string!")
|
||||
if KnowledgebaseService.query(name=req["name"], tenant_id=tenant_id, status=StatusEnum.VALID.value):
|
||||
return get_error_data_result(
|
||||
retmsg="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 not embd_model:
|
||||
return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
|
||||
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")
|
||||
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(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_result(data=renamed_data)
|
||||
|
||||
@manager.route('/datasets', 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 = []
|
||||
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(retmsg=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(
|
||||
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(id):
|
||||
return get_error_data_result(
|
||||
retmsg="Delete dataset error.(Database error)")
|
||||
return get_result(retcode=RetCode.SUCCESS)
|
||||
|
||||
@manager.route('/datasets/<dataset_id>', methods=['PUT'])
|
||||
@token_required
|
||||
def update(tenant_id,dataset_id):
|
||||
if not KnowledgebaseService.query(id=dataset_id,tenant_id=tenant_id):
|
||||
return get_error_data_result(retmsg="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(retmsg="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(
|
||||
retmsg="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(
|
||||
retmsg="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(
|
||||
retmsg="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(
|
||||
retmsg="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(
|
||||
retmsg="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 not embd_model:
|
||||
return get_error_data_result(f"`embedding_model` {req.get('embedding_model')} doesn't exist")
|
||||
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")
|
||||
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(
|
||||
retmsg="Duplicated dataset name in updating dataset.")
|
||||
if not KnowledgebaseService.update_by_id(kb.id, req):
|
||||
return get_error_data_result(retmsg="Update dataset error.(Database error)")
|
||||
return get_result(retcode=RetCode.SUCCESS)
|
||||
|
||||
@manager.route('/datasets', methods=['GET'])
|
||||
@token_required
|
||||
def list(tenant_id):
|
||||
id = request.args.get("id")
|
||||
name = request.args.get("name")
|
||||
kbs = KnowledgebaseService.query(id=id,name=name,status=1)
|
||||
if not kbs:
|
||||
return get_error_data_result(retmsg="The dataset doesn't exist")
|
||||
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")
|
||||
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)
|
||||
#
|
||||
# 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"]) # noqa: F821
|
||||
@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"]) # noqa: F821
|
||||
@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,
|
||||
]
|
||||
)
|
||||
File2DocumentService.delete_by_document_id(doc.id)
|
||||
FileService.filter_delete(
|
||||
[File.source_type == FileSource.KNOWLEDGEBASE, File.type == "folder", File.name == kbs[0].name])
|
||||
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"]) # noqa: F821
|
||||
@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"]) # noqa: F821
|
||||
@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)
|
||||
|
||||
@ -18,11 +18,11 @@ 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.settings import retrievaler, kg_retrievaler, RetCode
|
||||
from api import settings
|
||||
from api.utils.api_utils import validate_request, build_error_result, apikey_required
|
||||
|
||||
|
||||
@manager.route('/dify/retrieval', methods=['POST'])
|
||||
@manager.route('/dify/retrieval', methods=['POST']) # noqa: F821
|
||||
@apikey_required
|
||||
@validate_request("knowledge_id", "query")
|
||||
def retrieval(tenant_id):
|
||||
@ -37,14 +37,14 @@ def retrieval(tenant_id):
|
||||
|
||||
e, kb = KnowledgebaseService.get_by_id(kb_id)
|
||||
if not e:
|
||||
return build_error_result(error_msg="Knowledgebase not found!", retcode=RetCode.NOT_FOUND)
|
||||
return build_error_result(message="Knowledgebase not found!", code=settings.RetCode.NOT_FOUND)
|
||||
|
||||
if kb.tenant_id != tenant_id:
|
||||
return build_error_result(error_msg="Knowledgebase not found!", retcode=RetCode.NOT_FOUND)
|
||||
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 = retrievaler if kb.parser_id != ParserType.KG else kg_retrievaler
|
||||
retr = settings.retrievaler if kb.parser_id != ParserType.KG else settings.kg_retrievaler
|
||||
ranks = retr.retrieval(
|
||||
question,
|
||||
embd_mdl,
|
||||
@ -58,8 +58,7 @@ def retrieval(tenant_id):
|
||||
)
|
||||
records = []
|
||||
for c in ranks["chunks"]:
|
||||
if "vector" in c:
|
||||
del c["vector"]
|
||||
c.pop("vector", None)
|
||||
records.append({
|
||||
"content": c["content_ltks"],
|
||||
"score": c["similarity"],
|
||||
@ -71,7 +70,7 @@ def retrieval(tenant_id):
|
||||
except Exception as e:
|
||||
if str(e).find("not_found") > 0:
|
||||
return build_error_result(
|
||||
error_msg=f'No chunk found! Check the chunk status please!',
|
||||
retcode=RetCode.NOT_FOUND
|
||||
message='No chunk found! Check the chunk status please!',
|
||||
code=settings.RetCode.NOT_FOUND
|
||||
)
|
||||
return build_error_result(error_msg=str(e), retcode=RetCode.SERVER_ERROR)
|
||||
return build_error_result(message=str(e), code=settings.RetCode.SERVER_ERROR)
|
||||
|
||||
1264
api/apps/sdk/doc.py
1264
api/apps/sdk/doc.py
File diff suppressed because it is too large
Load Diff
@ -1,237 +1,433 @@
|
||||
#
|
||||
# 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.utils import get_uuid
|
||||
from api.utils.api_utils import get_error_data_result
|
||||
from api.utils.api_utils import get_result, token_required
|
||||
|
||||
@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(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_error_data_result(retmsg="`name` can not be empty.")
|
||||
ConversationService.save(**conv)
|
||||
e, conv = ConversationService.get_by_id(conv["id"])
|
||||
if not e:
|
||||
return get_error_data_result(retmsg="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('/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(retmsg="Session does not exist")
|
||||
if not DialogService.query(id=chat_id, tenant_id=tenant_id, status=StatusEnum.VALID.value):
|
||||
return get_error_data_result(retmsg="You do not own the session")
|
||||
if "message" in req or "messages" in req:
|
||||
return get_error_data_result(retmsg="`message` can not be change")
|
||||
if "reference" in req:
|
||||
return get_error_data_result(retmsg="`reference` can not be change")
|
||||
if "name" in req and not req.get("name"):
|
||||
return get_error_data_result(retmsg="`name` can not be empty.")
|
||||
if not ConversationService.update_by_id(conv_id, req):
|
||||
return get_error_data_result(retmsg="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(retmsg="`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(retmsg="Please input your question.")
|
||||
conv = ConversationService.query(id=session_id,dialog_id=chat_id)
|
||||
if not conv:
|
||||
return get_error_data_result(retmsg="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(retmsg="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):
|
||||
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
|
||||
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('/chats/<chat_id>/sessions', methods=['GET'])
|
||||
@token_required
|
||||
def list(chat_id,tenant_id):
|
||||
if not DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value):
|
||||
return get_error_data_result(retmsg=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", 1024))
|
||||
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"] = 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["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_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(retmsg="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(retmsg="The chat doesn't own the session")
|
||||
ConversationService.delete_by_id(id)
|
||||
return get_result()
|
||||
#
|
||||
# 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 api.db import LLMType
|
||||
from flask import request, Response
|
||||
|
||||
from api.db.services.conversation_service import ConversationService, iframe_completion
|
||||
from api.db.services.conversation_service import completion as rag_completion
|
||||
from api.db.services.canvas_service import completion as agent_completion
|
||||
from api.db.services.dialog_service import ask
|
||||
from agent.canvas import Canvas
|
||||
from api.db import StatusEnum
|
||||
from api.db.db_models import APIToken
|
||||
from api.db.services.api_service import API4ConversationService
|
||||
from api.db.services.canvas_service import UserCanvasService
|
||||
from api.db.services.dialog_service import DialogService
|
||||
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']) # noqa: F821
|
||||
@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": dia[0].prompt_config.get("prologue")}]
|
||||
}
|
||||
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']) # noqa: F821
|
||||
@token_required
|
||||
def create_agent_session(tenant_id, agent_id):
|
||||
e, cvs = UserCanvasService.get_by_id(agent_id)
|
||||
if not e:
|
||||
return get_error_data_result("Agent not found.")
|
||||
|
||||
if not isinstance(cvs.dsl, str):
|
||||
cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False)
|
||||
|
||||
canvas = Canvas(cvs.dsl, tenant_id)
|
||||
if canvas.get_preset_param():
|
||||
return get_error_data_result("The agent can't create a session directly")
|
||||
conv = {
|
||||
"id": get_uuid(),
|
||||
"dialog_id": cvs.id,
|
||||
"user_id": tenant_id,
|
||||
"message": [{"role": "assistant", "content": canvas.get_prologue()}],
|
||||
"source": "agent",
|
||||
"dsl": json.loads(cvs.dsl)
|
||||
}
|
||||
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']) # noqa: F821
|
||||
@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']) # noqa: F821
|
||||
@token_required
|
||||
def chat_completion(tenant_id, chat_id):
|
||||
req = request.json
|
||||
if not req or not req.get("session_id"):
|
||||
req = {"question":""}
|
||||
if not DialogService.query(tenant_id=tenant_id,id=chat_id,status=StatusEnum.VALID.value):
|
||||
return get_error_data_result(f"You don't own the chat {chat_id}")
|
||||
if req.get("session_id"):
|
||||
if not ConversationService.query(id=req["session_id"],dialog_id=chat_id):
|
||||
return get_error_data_result(f"You don't own the session {req['session_id']}")
|
||||
if req.get("stream", True):
|
||||
resp = Response(rag_completion(tenant_id, chat_id, **req), 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 rag_completion(tenant_id, chat_id, **req):
|
||||
answer = ans
|
||||
break
|
||||
return get_result(data=answer)
|
||||
|
||||
|
||||
@manager.route('/agents/<agent_id>/completions', methods=['POST']) # noqa: F821
|
||||
@token_required
|
||||
def agent_completions(tenant_id, agent_id):
|
||||
req = request.json
|
||||
cvs = UserCanvasService.query(user_id=tenant_id, id=agent_id)
|
||||
if not cvs:
|
||||
return get_error_data_result(f"You don't own the agent {agent_id}")
|
||||
if req.get("session_id"):
|
||||
conv = API4ConversationService.query(id=req["session_id"], dialog_id=agent_id)
|
||||
if not conv:
|
||||
return get_error_data_result(f"You don't own the session {req['session_id']}")
|
||||
else:
|
||||
req["question"]=""
|
||||
if req.get("stream", True):
|
||||
resp = Response(agent_completion(tenant_id, agent_id, **req), 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
|
||||
try:
|
||||
for answer in agent_completion(tenant_id, agent_id, **req):
|
||||
return get_result(data=answer)
|
||||
except Exception as e:
|
||||
return get_error_data_result(str(e))
|
||||
|
||||
|
||||
@manager.route('/chats/<chat_id>/sessions', methods=['GET']) # noqa: F821
|
||||
@token_required
|
||||
def list_session(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=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.get("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('/agents/<agent_id>/sessions', methods=['GET']) # noqa: F821
|
||||
@token_required
|
||||
def list_agent_session(tenant_id, agent_id):
|
||||
if not UserCanvasService.query(user_id=tenant_id, id=agent_id):
|
||||
return get_error_data_result(message=f"You don't own the agent {agent_id}.")
|
||||
id = request.args.get("id")
|
||||
if not API4ConversationService.query(id=id, user_id=tenant_id):
|
||||
return get_error_data_result(f"You don't own the session {id}")
|
||||
page_number = int(request.args.get("page", 1))
|
||||
items_per_page = int(request.args.get("page_size", 30))
|
||||
orderby = request.args.get("orderby", "update_time")
|
||||
if request.args.get("desc") == "False" or request.args.get("desc") == "false":
|
||||
desc = False
|
||||
else:
|
||||
desc = True
|
||||
convs = API4ConversationService.get_list(agent_id, tenant_id, page_number, items_per_page, orderby, desc, id)
|
||||
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["agent_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"],
|
||||
"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["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"]) # noqa: F821
|
||||
@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']) # noqa: F821
|
||||
@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']) # noqa: F821
|
||||
@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)])
|
||||
|
||||
|
||||
@manager.route('/chatbots/<dialog_id>/completions', methods=['POST']) # noqa: F821
|
||||
def chatbot_completions(dialog_id):
|
||||
req = request.json
|
||||
|
||||
token = request.headers.get('Authorization').split()
|
||||
if len(token) != 2:
|
||||
return get_error_data_result(message='Authorization is not valid!"')
|
||||
token = token[1]
|
||||
objs = APIToken.query(beta=token)
|
||||
if not objs:
|
||||
return get_error_data_result(message='Token is not valid!"')
|
||||
|
||||
if "quote" not in req:
|
||||
req["quote"] = False
|
||||
|
||||
if req.get("stream", True):
|
||||
resp = Response(iframe_completion(dialog_id, **req), 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 iframe_completion(dialog_id, **req):
|
||||
return get_result(data=answer)
|
||||
|
||||
|
||||
@manager.route('/agentbots/<agent_id>/completions', methods=['POST']) # noqa: F821
|
||||
def agent_bot_completions(agent_id):
|
||||
req = request.json
|
||||
|
||||
token = request.headers.get('Authorization').split()
|
||||
if len(token) != 2:
|
||||
return get_error_data_result(message='Authorization is not valid!"')
|
||||
token = token[1]
|
||||
objs = APIToken.query(beta=token)
|
||||
if not objs:
|
||||
return get_error_data_result(message='Token is not valid!"')
|
||||
|
||||
if "quote" not in req:
|
||||
req["quote"] = False
|
||||
|
||||
if req.get("stream", True):
|
||||
resp = Response(agent_completion(objs[0].tenant_id, agent_id, **req), 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 agent_completion(objs[0].tenant_id, agent_id, **req):
|
||||
return get_result(data=answer)
|
||||
|
||||
|
||||
|
||||
@ -13,8 +13,9 @@
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License
|
||||
#
|
||||
import json
|
||||
import logging
|
||||
from datetime import datetime
|
||||
import json
|
||||
|
||||
from flask_login import login_required, current_user
|
||||
|
||||
@ -22,120 +23,278 @@ 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.db.services.user_service import UserTenantService
|
||||
from api.settings import DATABASE_TYPE
|
||||
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, request, validate_request
|
||||
from api.versions import get_rag_version
|
||||
from rag.utils.es_conn import ELASTICSEARCH
|
||||
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"]) # noqa: F821
|
||||
@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"]) # noqa: F821
|
||||
@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'])
|
||||
@manager.route("/new_token", methods=["POST"]) # noqa: F821
|
||||
@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(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),
|
||||
"create_time": current_timestamp(),
|
||||
"create_date": datetime_format(datetime.now()),
|
||||
"update_time": None,
|
||||
"update_date": None
|
||||
}
|
||||
obj = {
|
||||
"tenant_id": tenant_id,
|
||||
"token": generate_confirmation_token(tenant_id),
|
||||
"beta": generate_confirmation_token(generate_confirmation_token(tenant_id)).replace("ragflow-", "")[:32],
|
||||
"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(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:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/token_list', methods=['GET'])
|
||||
@manager.route("/token_list", methods=["GET"]) # noqa: F821
|
||||
@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(retmsg="Tenant not found!")
|
||||
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])
|
||||
tenant_id = tenants[0].tenant_id
|
||||
objs = APITokenService.query(tenant_id=tenant_id)
|
||||
objs = [o.to_dict() for o in objs]
|
||||
for o in objs:
|
||||
if not o["beta"]:
|
||||
o["beta"] = generate_confirmation_token(generate_confirmation_token(tenants[0].tenant_id)).replace("ragflow-", "")[:32]
|
||||
APITokenService.filter_update([APIToken.tenant_id == tenant_id, APIToken.token == o["token"]], o)
|
||||
return get_json_result(data=objs)
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/token/<token>', methods=['DELETE'])
|
||||
@manager.route("/token/<token>", methods=["DELETE"]) # noqa: F821
|
||||
@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)
|
||||
[APIToken.tenant_id == current_user.id, APIToken.token == token]
|
||||
)
|
||||
return get_json_result(data=True)
|
||||
|
||||
@ -17,6 +17,7 @@
|
||||
from flask import request
|
||||
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 UserTenantService, UserService
|
||||
@ -25,9 +26,15 @@ 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"])
|
||||
@manager.route("/<tenant_id>/user/list", methods=["GET"]) # noqa: F821
|
||||
@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:
|
||||
@ -37,39 +44,55 @@ def user_list(tenant_id):
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route('/<tenant_id>/user', methods=['POST'])
|
||||
@manager.route('/<tenant_id>/user', methods=['POST']) # noqa: F821
|
||||
@login_required
|
||||
@validate_request("email")
|
||||
def create(tenant_id):
|
||||
req = request.json
|
||||
usrs = UserService.query(email=req["email"])
|
||||
if not usrs:
|
||||
return get_data_error_result(retmsg="User not found.")
|
||||
if current_user.id != tenant_id:
|
||||
return get_json_result(
|
||||
data=False,
|
||||
message='No authorization.',
|
||||
code=settings.RetCode.AUTHENTICATION_ERROR)
|
||||
|
||||
user_id = usrs[0].id
|
||||
user_tenants = UserTenantService.query(user_id=user_id, tenant_id=tenant_id)
|
||||
req = request.json
|
||||
invite_user_email = req["email"]
|
||||
invite_users = UserService.query(email=invite_user_email)
|
||||
if not invite_users:
|
||||
return get_data_error_result(message="User not found.")
|
||||
|
||||
user_id_to_invite = invite_users[0].id
|
||||
user_tenants = UserTenantService.query(user_id=user_id_to_invite, tenant_id=tenant_id)
|
||||
if user_tenants:
|
||||
if user_tenants[0].status == UserTenantRole.NORMAL.value:
|
||||
return get_data_error_result(retmsg="This user is in the team already.")
|
||||
return get_data_error_result(retmsg="Invitation notification is sent.")
|
||||
user_tenant_role = user_tenants[0].role
|
||||
if user_tenant_role == UserTenantRole.NORMAL:
|
||||
return get_data_error_result(message=f"{invite_user_email} is already in the team.")
|
||||
if user_tenant_role == UserTenantRole.OWNER:
|
||||
return get_data_error_result(message=f"{invite_user_email} is the owner of the team.")
|
||||
return get_data_error_result(message=f"{invite_user_email} is in the team, but the role: {user_tenant_role} is invalid.")
|
||||
|
||||
UserTenantService.save(
|
||||
id=get_uuid(),
|
||||
user_id=user_id,
|
||||
user_id=user_id_to_invite,
|
||||
tenant_id=tenant_id,
|
||||
invited_by=current_user.id,
|
||||
role=UserTenantRole.INVITE,
|
||||
status=StatusEnum.VALID.value)
|
||||
|
||||
usr = usrs[0].to_dict()
|
||||
usr = invite_users[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'])
|
||||
@manager.route('/<tenant_id>/user/<user_id>', methods=['DELETE']) # noqa: F821
|
||||
@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)
|
||||
@ -77,7 +100,7 @@ def rm(tenant_id, user_id):
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route("/list", methods=["GET"])
|
||||
@manager.route("/list", methods=["GET"]) # noqa: F821
|
||||
@login_required
|
||||
def tenant_list():
|
||||
try:
|
||||
@ -89,7 +112,7 @@ def tenant_list():
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route("/agree/<tenant_id>", methods=["PUT"])
|
||||
@manager.route("/agree/<tenant_id>", methods=["PUT"]) # noqa: F821
|
||||
@login_required
|
||||
def agree(tenant_id):
|
||||
try:
|
||||
|
||||
@ -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, 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, 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"]) # noqa: F821
|
||||
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"]) # noqa: F821
|
||||
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
|
||||
@ -134,33 +200,59 @@ def github_callback():
|
||||
return redirect("/?auth=%s" % user.get_id())
|
||||
|
||||
|
||||
@manager.route('/feishu_callback', methods=['GET'])
|
||||
@manager.route("/feishu_callback", methods=["GET"]) # noqa: F821
|
||||
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(" "):
|
||||
if "contact:user.email:readonly" not in res["data"]["scope"].split():
|
||||
return redirect("/?error=contact:user.email:readonly not in scope")
|
||||
session["access_token"] = res["data"]["access_token"]
|
||||
session["access_token_from"] = "feishu"
|
||||
@ -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
|
||||
@ -221,47 +319,103 @@ 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"]), None
|
||||
)["email"]
|
||||
return user_info
|
||||
|
||||
|
||||
@manager.route("/logout", methods=['GET'])
|
||||
@manager.route("/logout", methods=["GET"]) # noqa: F821
|
||||
@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()
|
||||
return get_json_result(data=True)
|
||||
|
||||
|
||||
@manager.route("/setting", methods=["POST"])
|
||||
@manager.route("/setting", methods=["POST"]) # noqa: F821
|
||||
@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", "email", "status", "is_superuser", "login_channel", "is_anonymous",
|
||||
"is_active", "is_authenticated", "last_login_time"]:
|
||||
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]
|
||||
|
||||
@ -269,34 +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"])
|
||||
@manager.route("/info", methods=["GET"]) # noqa: F821
|
||||
@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
|
||||
|
||||
|
||||
@ -305,18 +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 = {
|
||||
@ -330,14 +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
|
||||
@ -348,24 +531,55 @@ def user_register(user_id, user):
|
||||
return UserService.query(email=user["email"])
|
||||
|
||||
|
||||
@manager.route("/register", methods=["POST"])
|
||||
@manager.route("/register", methods=["POST"]) # noqa: F821
|
||||
@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-]{2,5}$", email_address):
|
||||
return get_json_result(data=False,
|
||||
retmsg=f'Invalid email address: {email_address}!',
|
||||
retcode=RetCode.OPERATING_ERROR)
|
||||
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"]
|
||||
@ -383,42 +597,107 @@ 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"])
|
||||
@manager.route("/tenant_info", methods=["GET"]) # noqa: F821
|
||||
@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_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!")
|
||||
return get_json_result(data=tenants[0])
|
||||
except Exception as e:
|
||||
return server_error_response(e)
|
||||
|
||||
|
||||
@manager.route("/set_tenant_info", methods=["POST"])
|
||||
@manager.route("/set_tenant_info", methods=["POST"]) # noqa: F821
|
||||
@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:
|
||||
|
||||
@ -15,4 +15,13 @@
|
||||
|
||||
NAME_LENGTH_LIMIT = 2 ** 10
|
||||
|
||||
IMG_BASE64_PREFIX = 'data:image/png;base64,'
|
||||
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
|
||||
|
||||
DATASET_NAME_LIMIT = 128
|
||||
@ -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):
|
||||
@ -130,7 +130,7 @@ def is_continuous_field(cls: typing.Type) -> bool:
|
||||
for p in cls.__bases__:
|
||||
if p in CONTINUOUS_FIELD_TYPE:
|
||||
return True
|
||||
elif p != Field and p != object:
|
||||
elif p is not Field and p is not object:
|
||||
if is_continuous_field(p):
|
||||
return True
|
||||
else:
|
||||
@ -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):
|
||||
@ -700,10 +703,11 @@ class Knowledgebase(DataBaseModel):
|
||||
default=ParserType.NAIVE.value,
|
||||
index=True)
|
||||
parser_config = JSONField(null=False, default={"pages": [[1, 1000000]]})
|
||||
pagerank = IntegerField(default=0, index=False)
|
||||
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 +771,7 @@ 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 +844,7 @@ 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)
|
||||
@ -851,6 +855,8 @@ class Task(DataBaseModel):
|
||||
help_text="process message",
|
||||
default="")
|
||||
retry_count = IntegerField(default=0)
|
||||
digest = TextField(null=True, help_text="task digest", default="")
|
||||
chunk_ids = LongTextField(null=True, help_text="chunk ids", default="")
|
||||
|
||||
|
||||
class Dialog(DataBaseModel):
|
||||
@ -879,8 +885,10 @@ class Dialog(DataBaseModel):
|
||||
default="simple",
|
||||
help_text="simple|advanced",
|
||||
index=True)
|
||||
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!"})
|
||||
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 +902,7 @@ 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 +912,7 @@ 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)
|
||||
|
||||
@ -928,6 +936,7 @@ class APIToken(DataBaseModel):
|
||||
token = CharField(max_length=255, null=False, index=True)
|
||||
dialog_id = CharField(max_length=32, null=False, index=True)
|
||||
source = CharField(max_length=16, null=True, help_text="none|agent|dialog", index=True)
|
||||
beta = CharField(max_length=255, null=True, index=True)
|
||||
|
||||
class Meta:
|
||||
db_table = "api_token"
|
||||
@ -942,7 +951,7 @@ class API4Conversation(DataBaseModel):
|
||||
reference = JSONField(null=True, default=[])
|
||||
tokens = IntegerField(default=0)
|
||||
source = CharField(max_length=16, null=True, help_text="none|agent|dialog", index=True)
|
||||
|
||||
dsl = JSONField(null=True, default={})
|
||||
duration = FloatField(default=0, index=True)
|
||||
round = IntegerField(default=0, index=True)
|
||||
thumb_up = IntegerField(default=0, index=True)
|
||||
@ -980,14 +989,14 @@ 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 +1005,7 @@ def migrate_db():
|
||||
help_text="default rerank model ID"))
|
||||
|
||||
)
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
migrate(
|
||||
@ -1004,59 +1013,95 @@ 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 as e:
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
migrate(
|
||||
migrator.add_column("tenant_llm","max_tokens",IntegerField(default=8192,index=True))
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
migrate(
|
||||
migrator.add_column("api_4_conversation","dsl",JSONField(null=True, default={}))
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
migrate(
|
||||
migrator.add_column("knowledgebase", "pagerank", IntegerField(default=0, index=False))
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
migrate(
|
||||
migrator.add_column("api_token", "beta", CharField(max_length=255, null=True, index=True))
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
migrate(
|
||||
migrator.add_column("task", "digest", TextField(null=True, help_text="task digest", default=""))
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
try:
|
||||
migrate(
|
||||
migrator.add_column("task", "chunk_ids", LongTextField(null=True, help_text="chunk ids", default=""))
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
@ -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))
|
||||
|
||||
@ -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"])
|
||||
@ -129,6 +131,7 @@ 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.
|
||||
@ -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():
|
||||
@ -167,22 +170,21 @@ def add_graph_templates():
|
||||
cnvs = json.load(open(os.path.join(dir, fnm), "r"))
|
||||
try:
|
||||
CanvasTemplateService.save(**cnvs)
|
||||
except:
|
||||
except Exception:
|
||||
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__':
|
||||
|
||||
@ -1,21 +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 operator
|
||||
import time
|
||||
import typing
|
||||
from api.utils.log_utils import sql_logger
|
||||
import peewee
|
||||
@ -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):
|
||||
|
||||
@ -15,13 +15,14 @@
|
||||
#
|
||||
import pathlib
|
||||
import re
|
||||
from .user_service import UserService
|
||||
from .user_service import UserService as UserService
|
||||
|
||||
|
||||
def duplicate_name(query_func, **kwargs):
|
||||
fnm = kwargs["name"]
|
||||
objs = query_func(**kwargs)
|
||||
if not objs: return fnm
|
||||
if not objs:
|
||||
return fnm
|
||||
ext = pathlib.Path(fnm).suffix #.jpg
|
||||
nm = re.sub(r"%s$"%ext, "", fnm)
|
||||
r = re.search(r"\(([0-9]+)\)$", nm)
|
||||
@ -31,8 +32,8 @@ def duplicate_name(query_func, **kwargs):
|
||||
nm = re.sub(r"\([0-9]+\)$", "", nm)
|
||||
c += 1
|
||||
nm = f"{nm}({c})"
|
||||
if ext: nm += f"{ext}"
|
||||
if ext:
|
||||
nm += f"{ext}"
|
||||
|
||||
kwargs["name"] = nm
|
||||
return duplicate_name(query_func, **kwargs)
|
||||
|
||||
|
||||
@ -39,6 +39,22 @@ class APITokenService(CommonService):
|
||||
class API4ConversationService(CommonService):
|
||||
model = API4Conversation
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def get_list(cls,dialog_id, tenant_id,
|
||||
page_number, items_per_page, orderby, desc, id):
|
||||
sessions = cls.model.select().where(cls.model.dialog_id ==dialog_id)
|
||||
if id:
|
||||
sessions = sessions.where(cls.model.id == id)
|
||||
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.where(cls.model.user_id == tenant_id)
|
||||
sessions = sessions.paginate(page_number, items_per_page)
|
||||
|
||||
return list(sessions.dicts())
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def append_message(cls, id, conversation):
|
||||
@ -48,7 +64,8 @@ class API4ConversationService(CommonService):
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def stats(cls, tenant_id, from_date, to_date, source=None):
|
||||
if len(to_date) == 10: to_date += " 23:59:59"
|
||||
if len(to_date) == 10:
|
||||
to_date += " 23:59:59"
|
||||
return cls.model.select(
|
||||
cls.model.create_date.truncate("day").alias("dt"),
|
||||
peewee.fn.COUNT(
|
||||
|
||||
@ -13,14 +13,143 @@
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
#
|
||||
from datetime import datetime
|
||||
import peewee
|
||||
from api.db.db_models import DB, API4Conversation, APIToken, Dialog, CanvasTemplate, UserCanvas
|
||||
import json
|
||||
import traceback
|
||||
from uuid import uuid4
|
||||
from agent.canvas import Canvas
|
||||
from api.db.db_models import DB, CanvasTemplate, UserCanvas, API4Conversation
|
||||
from api.db.services.api_service import API4ConversationService
|
||||
from api.db.services.common_service import CommonService
|
||||
from api.db.services.conversation_service import structure_answer
|
||||
from api.utils import get_uuid
|
||||
|
||||
|
||||
class CanvasTemplateService(CommonService):
|
||||
model = CanvasTemplate
|
||||
|
||||
|
||||
class UserCanvasService(CommonService):
|
||||
model = UserCanvas
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def get_list(cls, tenant_id,
|
||||
page_number, items_per_page, orderby, desc, id, title):
|
||||
agents = cls.model.select()
|
||||
if id:
|
||||
agents = agents.where(cls.model.id == id)
|
||||
if title:
|
||||
agents = agents.where(cls.model.title == title)
|
||||
agents = agents.where(cls.model.user_id == tenant_id)
|
||||
if desc:
|
||||
agents = agents.order_by(cls.model.getter_by(orderby).desc())
|
||||
else:
|
||||
agents = agents.order_by(cls.model.getter_by(orderby).asc())
|
||||
|
||||
agents = agents.paginate(page_number, items_per_page)
|
||||
|
||||
return list(agents.dicts())
|
||||
|
||||
|
||||
def completion(tenant_id, agent_id, question, session_id=None, stream=True, **kwargs):
|
||||
e, cvs = UserCanvasService.get_by_id(agent_id)
|
||||
assert e, "Agent not found."
|
||||
assert cvs.user_id == tenant_id, "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)
|
||||
canvas.reset()
|
||||
message_id = str(uuid4())
|
||||
if not session_id:
|
||||
query = canvas.get_preset_param()
|
||||
if query:
|
||||
for ele in query:
|
||||
if not ele["optional"]:
|
||||
if not kwargs.get(ele["key"]):
|
||||
assert False, f"`{ele['key']}` is required"
|
||||
ele["value"] = kwargs[ele["key"]]
|
||||
if ele["optional"]:
|
||||
if kwargs.get(ele["key"]):
|
||||
ele["value"] = kwargs[ele['key']]
|
||||
else:
|
||||
if "value" in ele:
|
||||
ele.pop("value")
|
||||
cvs.dsl = json.loads(str(canvas))
|
||||
temp_dsl = cvs.dsl
|
||||
UserCanvasService.update_by_id(agent_id, cvs.to_dict())
|
||||
else:
|
||||
temp_dsl = json.loads(cvs.dsl)
|
||||
session_id = get_uuid()
|
||||
conv = {
|
||||
"id": session_id,
|
||||
"dialog_id": cvs.id,
|
||||
"user_id": kwargs.get("user_id", ""),
|
||||
"source": "agent",
|
||||
"dsl": temp_dsl
|
||||
}
|
||||
API4ConversationService.save(**conv)
|
||||
conv = API4Conversation(**conv)
|
||||
else:
|
||||
e, conv = API4ConversationService.get_by_id(session_id)
|
||||
assert e, "Session not found!"
|
||||
canvas = Canvas(json.dumps(conv.dsl), tenant_id)
|
||||
canvas.messages.append({"role": "user", "content": question, "id": message_id})
|
||||
canvas.add_user_input(question)
|
||||
if not conv.message:
|
||||
conv.message = []
|
||||
conv.message.append({
|
||||
"role": "user",
|
||||
"content": question,
|
||||
"id": message_id
|
||||
})
|
||||
if not conv.reference:
|
||||
conv.reference = []
|
||||
conv.reference.append({"chunks": [], "doc_aggs": []})
|
||||
|
||||
final_ans = {"reference": [], "content": ""}
|
||||
if stream:
|
||||
try:
|
||||
for ans in canvas.run(stream=stream):
|
||||
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", [])}
|
||||
ans = structure_answer(conv, ans, message_id, session_id)
|
||||
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"])
|
||||
conv.dsl = json.loads(str(canvas))
|
||||
API4ConversationService.append_message(conv.id, conv.to_dict())
|
||||
except Exception as e:
|
||||
traceback.print_exc()
|
||||
conv.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"
|
||||
|
||||
else:
|
||||
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"])
|
||||
conv.dsl = json.loads(str(canvas))
|
||||
|
||||
result = {"answer": final_ans["content"], "reference": final_ans.get("reference", [])}
|
||||
result = structure_answer(conv, result, message_id, session_id)
|
||||
API4ConversationService.append_message(conv.id, conv.to_dict())
|
||||
yield result
|
||||
break
|
||||
@ -115,7 +115,7 @@ class CommonService:
|
||||
try:
|
||||
obj = cls.model.query(id=pid)[0]
|
||||
return True, obj
|
||||
except Exception as e:
|
||||
except Exception:
|
||||
return False, None
|
||||
|
||||
@classmethod
|
||||
|
||||
229
api/db/services/conversation_service.py
Normal file
229
api/db/services/conversation_service.py
Normal file
@ -0,0 +1,229 @@
|
||||
#
|
||||
# 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 uuid import uuid4
|
||||
from api.db import StatusEnum
|
||||
from api.db.db_models import Conversation, DB
|
||||
from api.db.services.api_service import API4ConversationService
|
||||
from api.db.services.common_service import CommonService
|
||||
from api.db.services.dialog_service import DialogService, chat
|
||||
from api.utils import get_uuid
|
||||
import json
|
||||
|
||||
|
||||
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 structure_answer(conv, ans, message_id, session_id):
|
||||
reference = ans["reference"]
|
||||
if not isinstance(reference, dict):
|
||||
reference = {}
|
||||
ans["reference"] = {}
|
||||
|
||||
def get_value(d, k1, k2):
|
||||
return d.get(k1, d.get(k2))
|
||||
chunk_list = [{
|
||||
"id": get_value(chunk, "chunk_id", "id"),
|
||||
"content": get_value(chunk, "content", "content_with_weight"),
|
||||
"document_id": get_value(chunk, "doc_id", "document_id"),
|
||||
"document_name": get_value(chunk, "docnm_kwd", "document_name"),
|
||||
"dataset_id": get_value(chunk, "kb_id", "dataset_id"),
|
||||
"image_id": get_value(chunk, "image_id", "img_id"),
|
||||
"positions": get_value(chunk, "positions", "position_int"),
|
||||
} for chunk in reference.get("chunks", [])]
|
||||
|
||||
reference["chunks"] = chunk_list
|
||||
ans["id"] = message_id
|
||||
ans["session_id"] = session_id
|
||||
|
||||
if not conv:
|
||||
return ans
|
||||
|
||||
if not conv.message:
|
||||
conv.message = []
|
||||
if not conv.message or conv.message[-1].get("role", "") != "assistant":
|
||||
conv.message.append({"role": "assistant", "content": ans["answer"], "id": message_id})
|
||||
else:
|
||||
conv.message[-1] = {"role": "assistant", "content": ans["answer"], "id": message_id}
|
||||
if conv.reference:
|
||||
conv.reference[-1] = reference
|
||||
return ans
|
||||
|
||||
|
||||
def completion(tenant_id, chat_id, question, name="New session", session_id=None, stream=True, **kwargs):
|
||||
assert name, "`name` can not be empty."
|
||||
dia = DialogService.query(id=chat_id, tenant_id=tenant_id, status=StatusEnum.VALID.value)
|
||||
assert dia, "You do not own the chat."
|
||||
|
||||
if not session_id:
|
||||
session_id = get_uuid()
|
||||
conv = {
|
||||
"id":session_id ,
|
||||
"dialog_id": chat_id,
|
||||
"name": name,
|
||||
"message": [{"role": "assistant", "content": dia[0].prompt_config.get("prologue")}]
|
||||
}
|
||||
ConversationService.save(**conv)
|
||||
yield "data:" + json.dumps({"code": 0, "message": "",
|
||||
"data": {
|
||||
"answer": conv["message"][0]["content"],
|
||||
"reference": {},
|
||||
"audio_binary": None,
|
||||
"id": None,
|
||||
"session_id": session_id
|
||||
}},
|
||||
ensure_ascii=False) + "\n\n"
|
||||
yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
|
||||
return
|
||||
|
||||
conv = ConversationService.query(id=session_id, dialog_id=chat_id)
|
||||
if not conv:
|
||||
raise LookupError("Session does not exist")
|
||||
|
||||
conv = conv[0]
|
||||
msg = []
|
||||
question = {
|
||||
"content": 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": []})
|
||||
|
||||
if stream:
|
||||
try:
|
||||
for ans in chat(dia, msg, True, **kwargs):
|
||||
ans = structure_answer(conv, ans, message_id, session_id)
|
||||
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"
|
||||
|
||||
else:
|
||||
answer = None
|
||||
for ans in chat(dia, msg, False, **kwargs):
|
||||
answer = structure_answer(conv, ans, message_id, session_id)
|
||||
ConversationService.update_by_id(conv.id, conv.to_dict())
|
||||
break
|
||||
yield answer
|
||||
|
||||
|
||||
def iframe_completion(dialog_id, question, session_id=None, stream=True, **kwargs):
|
||||
e, dia = DialogService.get_by_id(dialog_id)
|
||||
assert e, "Dialog not found"
|
||||
if not session_id:
|
||||
session_id = get_uuid()
|
||||
conv = {
|
||||
"id": session_id,
|
||||
"dialog_id": dialog_id,
|
||||
"user_id": kwargs.get("user_id", ""),
|
||||
"message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}]
|
||||
}
|
||||
API4ConversationService.save(**conv)
|
||||
yield "data:" + json.dumps({"code": 0, "message": "",
|
||||
"data": {
|
||||
"answer": conv["message"][0]["content"],
|
||||
"reference": {},
|
||||
"audio_binary": None,
|
||||
"id": None,
|
||||
"session_id": session_id
|
||||
}},
|
||||
ensure_ascii=False) + "\n\n"
|
||||
yield "data:" + json.dumps({"code": 0, "message": "", "data": True}, ensure_ascii=False) + "\n\n"
|
||||
return
|
||||
else:
|
||||
session_id = session_id
|
||||
e, conv = API4ConversationService.get_by_id(session_id)
|
||||
assert e, "Session not found!"
|
||||
|
||||
if not conv.message:
|
||||
conv.message = []
|
||||
messages = conv.message
|
||||
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 not conv.reference:
|
||||
conv.reference = []
|
||||
conv.reference.append({"chunks": [], "doc_aggs": []})
|
||||
|
||||
if stream:
|
||||
try:
|
||||
for ans in chat(dia, msg, True, **kwargs):
|
||||
ans = structure_answer(conv, ans, message_id, session_id)
|
||||
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({"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"
|
||||
|
||||
else:
|
||||
answer = None
|
||||
for ans in chat(dia, msg, False, **kwargs):
|
||||
answer = structure_answer(conv, ans, message_id, session_id)
|
||||
API4ConversationService.append_message(conv.id, conv.to_dict())
|
||||
break
|
||||
yield answer
|
||||
|
||||
@ -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 collections import defaultdict
|
||||
from copy import deepcopy
|
||||
from timeit import default_timer as timer
|
||||
|
||||
|
||||
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.db_models import Dialog, 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.search import index_name
|
||||
from rag.utils import rmSpace, num_tokens_from_string, encoder
|
||||
@ -59,27 +61,6 @@ class DialogService(CommonService):
|
||||
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():
|
||||
nonlocal msg
|
||||
@ -97,28 +78,29 @@ 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:
|
||||
return c, msg
|
||||
|
||||
ll = num_tokens_from_string(msg_[0]["content"])
|
||||
l = num_tokens_from_string(msg_[-1]["content"])
|
||||
if ll / (ll + l) > 0.8:
|
||||
ll2 = num_tokens_from_string(msg_[-1]["content"])
|
||||
if ll / (ll + ll2) > 0.8:
|
||||
m = msg_[0]["content"]
|
||||
m = encoder.decode(encoder.encode(m)[:max_length - l])
|
||||
m = encoder.decode(encoder.encode(m)[:max_length - ll2])
|
||||
msg[0]["content"] = m
|
||||
return max_length, msg
|
||||
|
||||
m = msg_[1]["content"]
|
||||
m = encoder.decode(encoder.encode(m)[:max_length - l])
|
||||
m = encoder.decode(encoder.encode(m)[:max_length - ll2])
|
||||
msg[1]["content"] = m
|
||||
return max_length, msg
|
||||
|
||||
|
||||
def llm_id2llm_type(llm_id):
|
||||
llm_id = llm_id.split("@")[0]
|
||||
llm_id, _ = TenantLLMService.split_model_name_and_factory(llm_id)
|
||||
fnm = os.path.join(get_project_base_directory(), "conf")
|
||||
llm_factories = json.load(open(os.path.join(fnm, "llm_factories.json"), "r"))
|
||||
for llm_factory in llm_factories["factory_llm_infos"]:
|
||||
@ -127,14 +109,36 @@ def llm_id2llm_type(llm_id):
|
||||
return llm["model_type"].strip(",")[-1]
|
||||
|
||||
|
||||
def kb_prompt(kbinfos, max_tokens):
|
||||
knowledges = [ck["content_with_weight"] for ck in kbinfos["chunks"]]
|
||||
used_token_count = 0
|
||||
chunks_num = 0
|
||||
for i, c in enumerate(knowledges):
|
||||
used_token_count += num_tokens_from_string(c)
|
||||
chunks_num += 1
|
||||
if max_tokens * 0.97 < used_token_count:
|
||||
knowledges = knowledges[:i]
|
||||
break
|
||||
|
||||
doc2chunks = defaultdict(list)
|
||||
for i, ck in enumerate(kbinfos["chunks"]):
|
||||
if i >= chunks_num:
|
||||
break
|
||||
doc2chunks["docnm_kwd"].append(ck["content_with_weight"])
|
||||
|
||||
knowledges = []
|
||||
for nm, chunks in doc2chunks.items():
|
||||
txt = f"Document: {nm} \nContains the following relevant fragments:\n"
|
||||
for i, chunk in enumerate(chunks, 1):
|
||||
txt += f"{i}. {chunk}\n"
|
||||
knowledges.append(txt)
|
||||
return knowledges
|
||||
|
||||
|
||||
def chat(dialog, messages, stream=True, **kwargs):
|
||||
assert messages[-1]["role"] == "user", "The last content of this conversation is not from user."
|
||||
st = timer()
|
||||
tmp = dialog.llm_id.split("@")
|
||||
fid = None
|
||||
llm_id = tmp[0]
|
||||
if len(tmp)>1: fid = tmp[1]
|
||||
|
||||
llm_id, fid = TenantLLMService.split_model_name_and_factory(dialog.llm_id)
|
||||
llm = LLMService.query(llm_name=llm_id) if not fid else LLMService.query(llm_name=llm_id, fid=fid)
|
||||
if not llm:
|
||||
llm = TenantLLMService.query(tenant_id=dialog.tenant_id, llm_name=llm_id) if not fid else \
|
||||
@ -151,7 +155,7 @@ 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
|
||||
@ -162,6 +166,9 @@ 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:
|
||||
@ -174,7 +181,7 @@ 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
|
||||
@ -193,6 +200,8 @@ 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:
|
||||
@ -205,6 +214,7 @@ def chat(dialog, messages, stream=True, **kwargs):
|
||||
else:
|
||||
if prompt_config.get("keyword", False):
|
||||
questions[-1] += keyword_extraction(chat_mdl, questions[-1])
|
||||
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,
|
||||
@ -212,8 +222,8 @@ def chat(dialog, messages, stream=True, **kwargs):
|
||||
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(
|
||||
knowledges = kb_prompt(kbinfos, max_tokens)
|
||||
logging.debug(
|
||||
"{}->{}".format(" ".join(questions), "\n->".join(knowledges)))
|
||||
retrieval_tm = timer()
|
||||
|
||||
@ -253,7 +263,8 @@ def chat(dialog, messages, stream=True, **kwargs):
|
||||
idx = set([kbinfos["chunks"][int(i)]["doc_id"] for i in idx])
|
||||
recall_docs = [
|
||||
d for d in kbinfos["doc_aggs"] if d["doc_id"] in idx]
|
||||
if not recall_docs: recall_docs = kbinfos["doc_aggs"]
|
||||
if not recall_docs:
|
||||
recall_docs = kbinfos["doc_aggs"]
|
||||
kbinfos["doc_aggs"] = recall_docs
|
||||
|
||||
refs = deepcopy(kbinfos)
|
||||
@ -262,9 +273,11 @@ def chat(dialog, messages, stream=True, **kwargs):
|
||||
del c["vector"]
|
||||
|
||||
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'"
|
||||
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:
|
||||
@ -283,7 +296,7 @@ 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)
|
||||
@ -311,8 +324,7 @@ 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)
|
||||
@ -332,11 +344,9 @@ 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:
|
||||
@ -363,10 +373,9 @@ 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
|
||||
|
||||
@ -388,6 +397,7 @@ 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:
|
||||
@ -395,7 +405,7 @@ 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": []},
|
||||
@ -430,13 +440,15 @@ def relevant(tenant_id, llm_id, question, contents: list):
|
||||
Give a binary score 'yes' or 'no' score to indicate whether the document is relevant to the question.
|
||||
No other words needed except 'yes' or 'no'.
|
||||
"""
|
||||
if not contents:return False
|
||||
if not contents:
|
||||
return False
|
||||
contents = "Documents: \n" + " - ".join(contents)
|
||||
contents = f"Question: {question}\n" + contents
|
||||
if num_tokens_from_string(contents) >= chat_mdl.max_length - 4:
|
||||
contents = encoder.decode(encoder.encode(contents)[:chat_mdl.max_length - 4])
|
||||
ans = chat_mdl.chat(prompt, [{"role": "user", "content": contents}], {"temperature": 0.01})
|
||||
if ans.lower().find("yes") >= 0: return True
|
||||
if ans.lower().find("yes") >= 0:
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
@ -478,8 +490,10 @@ Requirements:
|
||||
]
|
||||
_, 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 ""
|
||||
if isinstance(kwd, tuple):
|
||||
kwd = kwd[0]
|
||||
if kwd.find("**ERROR**") >=0:
|
||||
return ""
|
||||
return kwd
|
||||
|
||||
|
||||
@ -505,8 +519,10 @@ Requirements:
|
||||
]
|
||||
_, 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 ""
|
||||
if isinstance(kwd, tuple):
|
||||
kwd = kwd[0]
|
||||
if kwd.find("**ERROR**") >= 0:
|
||||
return ""
|
||||
return kwd
|
||||
|
||||
|
||||
@ -517,12 +533,20 @@ def full_question(tenant_id, llm_id, messages):
|
||||
chat_mdl = LLMBundle(tenant_id, LLMType.CHAT, llm_id)
|
||||
conv = []
|
||||
for m in messages:
|
||||
if m["role"] not in ["user", "assistant"]: continue
|
||||
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.
|
||||
@ -551,6 +575,14 @@ 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
|
||||
@ -563,7 +595,8 @@ Output: What's the full name of Donald Trump's mother Mary Trump?
|
||||
|
||||
|
||||
def tts(tts_mdl, text):
|
||||
if not tts_mdl or not text: return
|
||||
if not tts_mdl or not text:
|
||||
return
|
||||
bin = b""
|
||||
for chunk in tts_mdl.tts(text):
|
||||
bin += chunk
|
||||
@ -575,22 +608,14 @@ def ask(question, kb_ids, tenant_id):
|
||||
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)
|
||||
knowledges = [ck["content_with_weight"] for ck in kbinfos["chunks"]]
|
||||
|
||||
used_token_count = 0
|
||||
for i, c in enumerate(knowledges):
|
||||
used_token_count += num_tokens_from_string(c)
|
||||
if max_tokens * 0.97 < used_token_count:
|
||||
knowledges = knowledges[:i]
|
||||
break
|
||||
|
||||
tenant_ids = list(set([kb.tenant_id for kb in kbs]))
|
||||
kbinfos = retr.retrieval(question, embd_mdl, tenant_ids, kb_ids, 1, 12, 0.1, 0.3, aggs=False)
|
||||
knowledges = kb_prompt(kbinfos, max_tokens)
|
||||
prompt = """
|
||||
Role: You're a smart assistant. Your name is Miss R.
|
||||
Task: Summarize the information from knowledge bases and answer user's question.
|
||||
@ -600,29 +625,30 @@ def ask(question, kb_ids, tenant_id):
|
||||
- Answer with markdown format text.
|
||||
- Answer in language of user's question.
|
||||
- DO NOT make things up, especially for numbers.
|
||||
|
||||
|
||||
### Information from knowledge bases
|
||||
%s
|
||||
|
||||
|
||||
The above is information from knowledge bases.
|
||||
|
||||
"""%"\n".join(knowledges)
|
||||
|
||||
""" % "\n".join(knowledges)
|
||||
msg = [{"role": "user", "content": question}]
|
||||
|
||||
def decorate_answer(answer):
|
||||
nonlocal knowledges, kbinfos, prompt
|
||||
answer, idx = retr.insert_citations(answer,
|
||||
[ck["content_ltks"]
|
||||
for ck in kbinfos["chunks"]],
|
||||
[ck["vector"]
|
||||
for ck in kbinfos["chunks"]],
|
||||
embd_mdl,
|
||||
tkweight=0.7,
|
||||
vtweight=0.3)
|
||||
[ck["content_ltks"]
|
||||
for ck in kbinfos["chunks"]],
|
||||
[ck["vector"]
|
||||
for ck in kbinfos["chunks"]],
|
||||
embd_mdl,
|
||||
tkweight=0.7,
|
||||
vtweight=0.3)
|
||||
idx = set([kbinfos["chunks"][int(i)]["doc_id"] for i in idx])
|
||||
recall_docs = [
|
||||
d for d in kbinfos["doc_aggs"] if d["doc_id"] in idx]
|
||||
if not recall_docs: recall_docs = kbinfos["doc_aggs"]
|
||||
if not recall_docs:
|
||||
recall_docs = kbinfos["doc_aggs"]
|
||||
kbinfos["doc_aggs"] = recall_docs
|
||||
refs = deepcopy(kbinfos)
|
||||
for c in refs["chunks"]:
|
||||
|
||||
@ -13,27 +13,23 @@
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
#
|
||||
import hashlib
|
||||
import logging
|
||||
import xxhash
|
||||
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
|
||||
|
||||
@ -52,11 +48,15 @@ class DocumentService(CommonService):
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def get_list(cls, kb_id, page_number, items_per_page,
|
||||
orderby, desc, keywords, id):
|
||||
docs =cls.model.select().where(cls.model.kb_id==kb_id)
|
||||
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 )
|
||||
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())
|
||||
@ -70,7 +70,6 @@ class DocumentService(CommonService):
|
||||
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,
|
||||
@ -92,35 +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):
|
||||
@ -138,8 +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)
|
||||
|
||||
@ -162,26 +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
|
||||
@ -196,12 +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):
|
||||
@ -214,13 +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):
|
||||
@ -229,10 +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
|
||||
@ -243,13 +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):
|
||||
@ -270,8 +249,8 @@ class DocumentService(CommonService):
|
||||
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)
|
||||
).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
|
||||
@ -284,7 +263,7 @@ class DocumentService(CommonService):
|
||||
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)
|
||||
).where(cls.model.id == doc_id, Knowledgebase.created_by == user_id).paginate(0, 1)
|
||||
docs = docs.dicts()
|
||||
if not docs:
|
||||
return False
|
||||
@ -296,13 +275,38 @@ class DocumentService(CommonService):
|
||||
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_chunking_config(cls, doc_id):
|
||||
configs = (
|
||||
cls.model.select(
|
||||
cls.model.id,
|
||||
cls.model.kb_id,
|
||||
cls.model.parser_id,
|
||||
cls.model.parser_config,
|
||||
Knowledgebase.language,
|
||||
Knowledgebase.embd_id,
|
||||
Tenant.id.alias("tenant_id"),
|
||||
Tenant.img2txt_id,
|
||||
Tenant.asr_id,
|
||||
Tenant.llm_id,
|
||||
)
|
||||
.join(Knowledgebase, on=(cls.model.kb_id == Knowledgebase.id))
|
||||
.join(Tenant, on=(Knowledgebase.tenant_id == Tenant.id))
|
||||
.where(cls.model.id == doc_id)
|
||||
)
|
||||
configs = configs.dicts()
|
||||
if not configs:
|
||||
return None
|
||||
return configs[0]
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def get_doc_id_by_doc_name(cls, doc_name):
|
||||
@ -338,7 +342,10 @@ class DocumentService(CommonService):
|
||||
dfs_update(old[k], v)
|
||||
else:
|
||||
old[k] = v
|
||||
|
||||
dfs_update(d.parser_config, config)
|
||||
if not config.get("raptor") and d.parser_config.get("raptor"):
|
||||
del d.parser_config["raptor"]
|
||||
cls.update_by_id(id, {"parser_config": d.parser_config})
|
||||
|
||||
@classmethod
|
||||
@ -354,7 +361,7 @@ 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()
|
||||
})
|
||||
|
||||
@ -372,7 +379,7 @@ 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
|
||||
@ -386,9 +393,10 @@ 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 * len(tsks)/(len(tsks)+1)
|
||||
prg = 0.98 * len(tsks) / (len(tsks) + 1)
|
||||
msg.append("------ RAPTOR -------")
|
||||
else:
|
||||
status = TaskStatus.DONE.value
|
||||
@ -406,7 +414,7 @@ class DocumentService(CommonService):
|
||||
cls.update_by_id(d["id"], info)
|
||||
except Exception as e:
|
||||
if str(e).find("'0'") < 0:
|
||||
stat_logger.error("fetch task exception:" + str(e))
|
||||
logging.exception("fetch task exception")
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
@ -414,30 +422,37 @@ 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
|
||||
|
||||
|
||||
def queue_raptor_tasks(doc):
|
||||
chunking_config = DocumentService.get_chunking_config(doc["id"])
|
||||
hasher = xxhash.xxh64()
|
||||
for field in sorted(chunking_config.keys()):
|
||||
hasher.update(str(chunking_config[field]).encode("utf-8"))
|
||||
|
||||
def new_task():
|
||||
nonlocal doc
|
||||
return {
|
||||
"id": get_uuid(),
|
||||
"doc_id": doc["id"],
|
||||
"from_page": 0,
|
||||
"to_page": -1,
|
||||
"progress_msg": "Start to do RAPTOR (Recursive Abstractive Processing For Tree-Organized Retrieval)."
|
||||
"from_page": 100000000,
|
||||
"to_page": 100000000,
|
||||
"progress_msg": "Start to do RAPTOR (Recursive Abstractive Processing for Tree-Organized Retrieval)."
|
||||
}
|
||||
|
||||
task = new_task()
|
||||
for field in ["doc_id", "from_page", "to_page"]:
|
||||
hasher.update(str(task.get(field, "")).encode("utf-8"))
|
||||
task["digest"] = hasher.hexdigest()
|
||||
bulk_insert_into_db(Task, [task], True)
|
||||
task["type"] = "raptor"
|
||||
assert REDIS_CONN.queue_product(SVR_QUEUE_NAME, message=task), "Can't access Redis. Please check the Redis' status."
|
||||
@ -445,11 +460,12 @@ def queue_raptor_tasks(doc):
|
||||
|
||||
def doc_upload_and_parse(conversation_id, file_objs, user_id):
|
||||
from rag.app import presentation, picture, naive, audio, email
|
||||
from api.db.services.dialog_service import ConversationService, DialogService
|
||||
from api.db.services.dialog_service import DialogService
|
||||
from api.db.services.file_service import FileService
|
||||
from api.db.services.llm_service import LLMBundle
|
||||
from api.db.services.user_service import TenantService
|
||||
from api.db.services.api_service import API4ConversationService
|
||||
from api.db.services.conversation_service import ConversationService
|
||||
|
||||
e, conv = ConversationService.get_by_id(conversation_id)
|
||||
if not e:
|
||||
@ -462,11 +478,6 @@ 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)
|
||||
@ -507,10 +518,7 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
|
||||
for ck in th.result():
|
||||
d = deepcopy(doc)
|
||||
d.update(ck)
|
||||
md5 = hashlib.md5()
|
||||
md5.update((ck["content_with_weight"] +
|
||||
str(d["doc_id"])).encode("utf-8"))
|
||||
d["_id"] = md5.hexdigest()
|
||||
d["id"] = xxhash.xxh64((ck["content_with_weight"] + str(d["doc_id"])).encode("utf-8")).hexdigest()
|
||||
d["create_time"] = str(datetime.now()).replace("T", " ")[:19]
|
||||
d["create_timestamp_flt"] = datetime.now().timestamp()
|
||||
if not d.get("image"):
|
||||
@ -523,9 +531,9 @@ 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}
|
||||
@ -544,6 +552,9 @@ 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:
|
||||
@ -554,7 +565,8 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
|
||||
try:
|
||||
mind_map = json.dumps(mindmap([c["content_with_weight"] for c in docs if c["doc_id"] == doc_id]).output,
|
||||
ensure_ascii=False, indent=2)
|
||||
if len(mind_map) < 32: raise Exception("Few content: " + mind_map)
|
||||
if len(mind_map) < 32:
|
||||
raise Exception("Few content: " + mind_map)
|
||||
cks.append({
|
||||
"id": get_uuid(),
|
||||
"doc_id": doc_id,
|
||||
@ -566,7 +578,7 @@ 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)
|
||||
@ -574,9 +586,13 @@ 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]
|
||||
@ -20,7 +20,7 @@ from api.db.db_models import DB
|
||||
from api.db.db_models import File, File2Document
|
||||
from api.db.services.common_service import CommonService
|
||||
from api.db.services.document_service import DocumentService
|
||||
from api.utils import current_timestamp, datetime_format, get_uuid
|
||||
from api.utils import current_timestamp, datetime_format
|
||||
|
||||
|
||||
class File2DocumentService(CommonService):
|
||||
@ -63,7 +63,7 @@ class File2DocumentService(CommonService):
|
||||
def update_by_file_id(cls, file_id, obj):
|
||||
obj["update_time"] = current_timestamp()
|
||||
obj["update_date"] = datetime_format(datetime.now())
|
||||
num = cls.model.update(obj).where(cls.model.id == file_id).execute()
|
||||
# num = cls.model.update(obj).where(cls.model.id == file_id).execute()
|
||||
e, obj = cls.get_by_id(cls.model.id)
|
||||
return obj
|
||||
|
||||
|
||||
@ -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
|
||||
|
||||
@ -82,7 +85,8 @@ class FileService(CommonService):
|
||||
.join(Document, on=(File2Document.document_id == Document.id))
|
||||
.join(Knowledgebase, on=(Knowledgebase.id == Document.kb_id))
|
||||
.where(cls.model.id == file_id))
|
||||
if not kbs: return []
|
||||
if not kbs:
|
||||
return []
|
||||
kbs_info_list = []
|
||||
for kb in list(kbs.dicts()):
|
||||
kbs_info_list.append({"kb_id": kb['id'], "kb_name": kb['name']})
|
||||
@ -272,8 +276,8 @@ 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
|
||||
@ -301,7 +305,8 @@ class FileService(CommonService):
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def add_file_from_kb(cls, doc, kb_folder_id, tenant_id):
|
||||
for _ in File2DocumentService.get_by_document_id(doc["id"]): return
|
||||
for _ in File2DocumentService.get_by_document_id(doc["id"]):
|
||||
return
|
||||
file = {
|
||||
"id": get_uuid(),
|
||||
"parent_id": kb_folder_id,
|
||||
@ -321,8 +326,8 @@ 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
|
||||
@ -384,6 +389,41 @@ 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:
|
||||
|
||||
@ -16,6 +16,7 @@
|
||||
from api.db import StatusEnum, TenantPermission
|
||||
from api.db.db_models import Knowledgebase, DB, Tenant, User, UserTenant,Document
|
||||
from api.db.services.common_service import CommonService
|
||||
from peewee import fn
|
||||
|
||||
|
||||
class KnowledgebaseService(CommonService):
|
||||
@ -34,7 +35,7 @@ class KnowledgebaseService(CommonService):
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def get_by_tenant_ids(cls, joined_tenant_ids, user_id,
|
||||
page_number, items_per_page, orderby, desc):
|
||||
page_number, items_per_page, orderby, desc, keywords):
|
||||
fields = [
|
||||
cls.model.id,
|
||||
cls.model.avatar,
|
||||
@ -51,45 +52,41 @@ class KnowledgebaseService(CommonService):
|
||||
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.status == StatusEnum.VALID.value)
|
||||
)
|
||||
if keywords:
|
||||
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.status == StatusEnum.VALID.value),
|
||||
(fn.LOWER(cls.model.name).contains(keywords.lower()))
|
||||
)
|
||||
else:
|
||||
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.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())
|
||||
|
||||
count = kbs.count()
|
||||
|
||||
kbs = kbs.paginate(page_number, items_per_page)
|
||||
|
||||
return list(kbs.dicts())
|
||||
return list(kbs.dicts()), count
|
||||
|
||||
@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()
|
||||
@ -107,7 +104,8 @@ class KnowledgebaseService(CommonService):
|
||||
cls.model.token_num,
|
||||
cls.model.chunk_num,
|
||||
cls.model.parser_id,
|
||||
cls.model.parser_config]
|
||||
cls.model.parser_config,
|
||||
cls.model.pagerank]
|
||||
kbs = cls.model.select(*fields).join(Tenant, on=(
|
||||
(Tenant.id == cls.model.tenant_id) & (Tenant.status == StatusEnum.VALID.value))).where(
|
||||
(cls.model.id == kb_id),
|
||||
@ -204,6 +202,22 @@ class KnowledgebaseService(CommonService):
|
||||
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):
|
||||
|
||||
@ -13,8 +13,12 @@
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
#
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
|
||||
from api.db.services.user_service import TenantService
|
||||
from api.settings import database_logger
|
||||
from api.utils.file_utils import get_project_base_directory
|
||||
from rag.llm import EmbeddingModel, CvModel, ChatModel, RerankModel, Seq2txtModel, TTSModel
|
||||
from api.db import LLMType
|
||||
from api.db.db_models import DB
|
||||
@ -36,11 +40,11 @@ class TenantLLMService(CommonService):
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def get_api_key(cls, tenant_id, model_name):
|
||||
arr = model_name.split("@")
|
||||
if len(arr) < 2:
|
||||
objs = cls.query(tenant_id=tenant_id, llm_name=model_name)
|
||||
mdlnm, fid = TenantLLMService.split_model_name_and_factory(model_name)
|
||||
if not fid:
|
||||
objs = cls.query(tenant_id=tenant_id, llm_name=mdlnm)
|
||||
else:
|
||||
objs = cls.query(tenant_id=tenant_id, llm_name=arr[0], llm_factory=arr[1])
|
||||
objs = cls.query(tenant_id=tenant_id, llm_name=mdlnm, llm_factory=fid)
|
||||
if not objs:
|
||||
return
|
||||
return objs[0]
|
||||
@ -61,6 +65,23 @@ class TenantLLMService(CommonService):
|
||||
|
||||
return list(objs)
|
||||
|
||||
@staticmethod
|
||||
def split_model_name_and_factory(model_name):
|
||||
arr = model_name.split("@")
|
||||
if len(arr) < 2:
|
||||
return model_name, None
|
||||
if len(arr) > 2:
|
||||
return "@".join(arr[0:-1]), arr[-1]
|
||||
try:
|
||||
fact = json.load(open(os.path.join(get_project_base_directory(), "conf/llm_factories.json"), "r"))["factory_llm_infos"]
|
||||
fact = set([f["name"] for f in fact])
|
||||
if arr[-1] not in fact:
|
||||
return model_name, None
|
||||
return arr[0], arr[-1]
|
||||
except Exception as e:
|
||||
logging.exception(f"TenantLLMService.split_model_name_and_factory got exception: {e}")
|
||||
return model_name, None
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def model_instance(cls, tenant_id, llm_type,
|
||||
@ -85,10 +106,9 @@ class TenantLLMService(CommonService):
|
||||
assert False, "LLM type error"
|
||||
|
||||
model_config = cls.get_api_key(tenant_id, mdlnm)
|
||||
tmp = mdlnm.split("@")
|
||||
fid = None if len(tmp) < 2 else tmp[1]
|
||||
mdlnm = tmp[0]
|
||||
if model_config: model_config = model_config.to_dict()
|
||||
mdlnm, fid = TenantLLMService.split_model_name_and_factory(mdlnm)
|
||||
if model_config:
|
||||
model_config = model_config.to_dict()
|
||||
if not model_config:
|
||||
if llm_type in [LLMType.EMBEDDING, LLMType.RERANK]:
|
||||
llm = LLMService.query(llm_name=mdlnm) if not fid else LLMService.query(llm_name=mdlnm, fid=fid)
|
||||
@ -168,16 +188,23 @@ class TenantLLMService(CommonService):
|
||||
else:
|
||||
assert False, "LLM type error"
|
||||
|
||||
llm_name = mdlnm.split("@")[0] if "@" in mdlnm else mdlnm
|
||||
llm_name, llm_factory = TenantLLMService.split_model_name_and_factory(mdlnm)
|
||||
|
||||
num = 0
|
||||
try:
|
||||
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 == llm_name)\
|
||||
if llm_factory:
|
||||
tenant_llms = cls.query(tenant_id=tenant_id, llm_name=llm_name, llm_factory=llm_factory)
|
||||
else:
|
||||
tenant_llms = cls.query(tenant_id=tenant_id, llm_name=llm_name)
|
||||
if not tenant_llms:
|
||||
return num
|
||||
else:
|
||||
tenant_llm = tenant_llms[0]
|
||||
num = cls.model.update(used_tokens=tenant_llm.used_tokens + used_tokens)\
|
||||
.where(cls.model.tenant_id == tenant_id, cls.model.llm_factory == tenant_llm.llm_factory, cls.model.llm_name == llm_name)\
|
||||
.execute()
|
||||
except Exception as e:
|
||||
pass
|
||||
except Exception:
|
||||
logging.exception("TenantLLMService.increase_usage got exception")
|
||||
return num
|
||||
|
||||
@classmethod
|
||||
@ -205,44 +232,44 @@ class LLMBundle(object):
|
||||
self.max_length = lm.max_tokens
|
||||
break
|
||||
|
||||
def encode(self, texts: list, batch_size=32):
|
||||
emd, used_tokens = self.mdl.encode(texts, batch_size)
|
||||
def encode(self, texts: list):
|
||||
embeddings, used_tokens = self.mdl.encode(texts)
|
||||
if not TenantLLMService.increase_usage(
|
||||
self.tenant_id, self.llm_type, used_tokens):
|
||||
database_logger.error(
|
||||
"Can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens))
|
||||
return emd, used_tokens
|
||||
logging.error(
|
||||
"LLMBundle.encode can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens))
|
||||
return embeddings, 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 used_tokens: {}".format(self.tenant_id, used_tokens))
|
||||
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 used_tokens: {}".format(self.tenant_id, used_tokens))
|
||||
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 used_tokens: {}".format(self.tenant_id, used_tokens))
|
||||
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 used_tokens: {}".format(self.tenant_id, used_tokens))
|
||||
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):
|
||||
@ -250,17 +277,17 @@ 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
|
||||
yield chunk
|
||||
|
||||
def chat(self, system, history, gen_conf):
|
||||
txt, used_tokens = self.mdl.chat(system, history, gen_conf)
|
||||
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 llm_name: {}, used_tokens: {}".format(self.tenant_id, self.llm_name, used_tokens))
|
||||
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):
|
||||
@ -268,7 +295,7 @@ 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 llm_name: {}, content: {}".format(self.tenant_id, self.llm_name, txt))
|
||||
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
|
||||
|
||||
@ -15,6 +15,8 @@
|
||||
#
|
||||
import os
|
||||
import random
|
||||
import xxhash
|
||||
import bisect
|
||||
|
||||
from api.db.db_utils import bulk_insert_into_db
|
||||
from deepdoc.parser import PdfParser
|
||||
@ -29,6 +31,18 @@ from deepdoc.parser.excel_parser import RAGFlowExcelParser
|
||||
from rag.settings import SVR_QUEUE_NAME
|
||||
from rag.utils.storage_factory import STORAGE_IMPL
|
||||
from rag.utils.redis_conn import REDIS_CONN
|
||||
from api import settings
|
||||
from rag.nlp import search
|
||||
|
||||
|
||||
def trim_header_by_lines(text: str, max_length) -> str:
|
||||
len_text = len(text)
|
||||
if len_text <= max_length:
|
||||
return text
|
||||
for i in range(len_text):
|
||||
if text[i] == '\n' and len_text - i <= max_length:
|
||||
return text[i + 1:]
|
||||
return text
|
||||
|
||||
|
||||
class TaskService(CommonService):
|
||||
@ -36,7 +50,7 @@ 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,
|
||||
@ -53,92 +67,143 @@ class TaskService(CommonService):
|
||||
Knowledgebase.tenant_id,
|
||||
Knowledgebase.language,
|
||||
Knowledgebase.embd_id,
|
||||
Knowledgebase.pagerank,
|
||||
Tenant.img2txt_id,
|
||||
Tenant.asr_id,
|
||||
Tenant.llm_id,
|
||||
cls.model.update_time]
|
||||
docs = cls.model.select(*fields) \
|
||||
.join(Document, on=(cls.model.doc_id == Document.id)) \
|
||||
.join(Knowledgebase, on=(Document.kb_id == Knowledgebase.id)) \
|
||||
.join(Tenant, on=(Knowledgebase.tenant_id == Tenant.id)) \
|
||||
.where(cls.model.id == task_id)
|
||||
cls.model.update_time,
|
||||
]
|
||||
docs = (
|
||||
cls.model.select(*fields)
|
||||
.join(Document, on=(cls.model.doc_id == Document.id))
|
||||
.join(Knowledgebase, on=(Document.kb_id == Knowledgebase.id))
|
||||
.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.
|
||||
prog = random.random() / 10.0
|
||||
if docs[0]["retry_count"] >= 3:
|
||||
msg = "\nERROR: Task is abandoned after 3 times attempts."
|
||||
prog = -1
|
||||
|
||||
cls.model.update(progress_msg=cls.model.progress_msg + msg,
|
||||
progress=prog,
|
||||
retry_count=docs[0]["retry_count"]+1
|
||||
).where(
|
||||
cls.model.id == docs[0]["id"]).execute()
|
||||
cls.model.update(
|
||||
progress_msg=cls.model.progress_msg + msg,
|
||||
progress=prog,
|
||||
retry_count=docs[0]["retry_count"] + 1,
|
||||
).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()
|
||||
def get_tasks(cls, doc_id: str):
|
||||
fields = [
|
||||
cls.model.id,
|
||||
cls.model.from_page,
|
||||
cls.model.progress,
|
||||
cls.model.digest,
|
||||
cls.model.chunk_ids,
|
||||
]
|
||||
tasks = (
|
||||
cls.model.select(*fields).order_by(cls.model.from_page.asc(), cls.model.create_time.desc())
|
||||
.where(cls.model.doc_id == doc_id)
|
||||
)
|
||||
tasks = list(tasks.dicts())
|
||||
if not tasks:
|
||||
return None
|
||||
return tasks
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def update_chunk_ids(cls, id: str, chunk_ids: str):
|
||||
cls.model.update(chunk_ids=chunk_ids).where(cls.model.id == id).execute()
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def get_ongoing_doc_name(cls):
|
||||
with DB.lock("get_task", -1):
|
||||
docs = cls.model.select(*[Document.id, Document.kb_id, Document.location, File.parent_id]) \
|
||||
.join(Document, on=(cls.model.doc_id == Document.id)) \
|
||||
.join(File2Document, on=(File2Document.document_id == Document.id), join_type=JOIN.LEFT_OUTER) \
|
||||
.join(File, on=(File2Document.file_id == File.id), join_type=JOIN.LEFT_OUTER) \
|
||||
.where(
|
||||
docs = (
|
||||
cls.model.select(
|
||||
*[Document.id, Document.kb_id, Document.location, File.parent_id]
|
||||
)
|
||||
.join(Document, on=(cls.model.doc_id == Document.id))
|
||||
.join(
|
||||
File2Document,
|
||||
on=(File2Document.document_id == Document.id),
|
||||
join_type=JOIN.LEFT_OUTER,
|
||||
)
|
||||
.join(
|
||||
File,
|
||||
on=(File2Document.file_id == File.id),
|
||||
join_type=JOIN.LEFT_OUTER,
|
||||
)
|
||||
.where(
|
||||
Document.status == StatusEnum.VALID.value,
|
||||
Document.run == TaskStatus.RUNNING.value,
|
||||
~(Document.type == FileType.VIRTUAL.value),
|
||||
cls.model.progress < 1,
|
||||
cls.model.create_time >= current_timestamp() - 1000 * 600
|
||||
cls.model.create_time >= current_timestamp() - 1000 * 600,
|
||||
)
|
||||
)
|
||||
docs = list(docs.dicts())
|
||||
if not docs: return []
|
||||
if not docs:
|
||||
return []
|
||||
|
||||
return list(set([(d["parent_id"] if d["parent_id"] else d["kb_id"], d["location"]) for d in docs]))
|
||||
return list(
|
||||
set(
|
||||
[
|
||||
(
|
||||
d["parent_id"] if d["parent_id"] else d["kb_id"],
|
||||
d["location"],
|
||||
)
|
||||
for d in docs
|
||||
]
|
||||
)
|
||||
)
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def do_cancel(cls, id):
|
||||
try:
|
||||
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:
|
||||
pass
|
||||
return False
|
||||
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
|
||||
|
||||
@classmethod
|
||||
@DB.connection_context()
|
||||
def update_progress(cls, id, info):
|
||||
if os.environ.get("MACOS"):
|
||||
if info["progress_msg"]:
|
||||
cls.model.update(progress_msg=cls.model.progress_msg + "\n" + info["progress_msg"]).where(
|
||||
cls.model.id == id).execute()
|
||||
task = cls.model.get_by_id(id)
|
||||
progress_msg = trim_header_by_lines(task.progress_msg + "\n" + info["progress_msg"], 1000)
|
||||
cls.model.update(progress_msg=progress_msg).where(cls.model.id == id).execute()
|
||||
if "progress" in info:
|
||||
cls.model.update(progress=info["progress"]).where(
|
||||
cls.model.id == id).execute()
|
||||
cls.model.id == id
|
||||
).execute()
|
||||
return
|
||||
|
||||
with DB.lock("update_progress", -1):
|
||||
if info["progress_msg"]:
|
||||
cls.model.update(progress_msg=cls.model.progress_msg + "\n" + info["progress_msg"]).where(
|
||||
cls.model.id == id).execute()
|
||||
task = cls.model.get_by_id(id)
|
||||
progress_msg = trim_header_by_lines(task.progress_msg + "\n" + info["progress_msg"], 1000)
|
||||
cls.model.update(progress_msg=progress_msg).where(cls.model.id == id).execute()
|
||||
if "progress" in info:
|
||||
cls.model.update(progress=info["progress"]).where(
|
||||
cls.model.id == id).execute()
|
||||
cls.model.id == id
|
||||
).execute()
|
||||
|
||||
|
||||
def queue_tasks(doc: dict, bucket: str, name: str):
|
||||
def new_task():
|
||||
return {
|
||||
"id": get_uuid(),
|
||||
"doc_id": doc["id"]
|
||||
}
|
||||
return {"id": get_uuid(), "doc_id": doc["id"], "progress": 0.0, "from_page": 0, "to_page": 100000000}
|
||||
|
||||
tsks = []
|
||||
|
||||
if doc["type"] == FileType.PDF.value:
|
||||
@ -172,8 +237,57 @@ def queue_tasks(doc: dict, bucket: str, name: str):
|
||||
else:
|
||||
tsks.append(new_task())
|
||||
|
||||
chunking_config = DocumentService.get_chunking_config(doc["id"])
|
||||
for task in tsks:
|
||||
hasher = xxhash.xxh64()
|
||||
for field in sorted(chunking_config.keys()):
|
||||
hasher.update(str(chunking_config[field]).encode("utf-8"))
|
||||
for field in ["doc_id", "from_page", "to_page"]:
|
||||
hasher.update(str(task.get(field, "")).encode("utf-8"))
|
||||
task_digest = hasher.hexdigest()
|
||||
task["digest"] = task_digest
|
||||
task["progress"] = 0.0
|
||||
|
||||
prev_tasks = TaskService.get_tasks(doc["id"])
|
||||
ck_num = 0
|
||||
if prev_tasks:
|
||||
for task in tsks:
|
||||
ck_num += reuse_prev_task_chunks(task, prev_tasks, chunking_config)
|
||||
TaskService.filter_delete([Task.doc_id == doc["id"]])
|
||||
chunk_ids = []
|
||||
for task in prev_tasks:
|
||||
if task["chunk_ids"]:
|
||||
chunk_ids.extend(task["chunk_ids"].split())
|
||||
if chunk_ids:
|
||||
settings.docStoreConn.delete({"id": chunk_ids}, search.index_name(chunking_config["tenant_id"]),
|
||||
chunking_config["kb_id"])
|
||||
DocumentService.update_by_id(doc["id"], {"chunk_num": ck_num})
|
||||
|
||||
bulk_insert_into_db(Task, tsks, True)
|
||||
DocumentService.begin2parse(doc["id"])
|
||||
|
||||
tsks = [task for task in tsks if task["progress"] < 1.0]
|
||||
for t in tsks:
|
||||
assert REDIS_CONN.queue_product(SVR_QUEUE_NAME, message=t), "Can't access Redis. Please check the Redis' status."
|
||||
assert REDIS_CONN.queue_product(
|
||||
SVR_QUEUE_NAME, message=t
|
||||
), "Can't access Redis. Please check the Redis' status."
|
||||
|
||||
|
||||
def reuse_prev_task_chunks(task: dict, prev_tasks: list[dict], chunking_config: dict):
|
||||
idx = bisect.bisect_left(prev_tasks, (task.get("from_page", 0), task.get("digest", "")),
|
||||
key=lambda x: (x.get("from_page", 0), x.get("digest", "")))
|
||||
if idx >= len(prev_tasks):
|
||||
return 0
|
||||
prev_task = prev_tasks[idx]
|
||||
if prev_task["progress"] < 1.0 or prev_task["digest"] != task["digest"] or not prev_task["chunk_ids"]:
|
||||
return 0
|
||||
task["chunk_ids"] = prev_task["chunk_ids"]
|
||||
task["progress"] = 1.0
|
||||
if "from_page" in task and "to_page" in task:
|
||||
task["progress_msg"] = f"Page({task['from_page']}~{task['to_page']}): "
|
||||
else:
|
||||
task["progress_msg"] = ""
|
||||
task["progress_msg"] += "reused previous task's chunks."
|
||||
prev_task["chunk_ids"] = ""
|
||||
|
||||
return len(task["chunk_ids"].split())
|
||||
|
||||
@ -22,7 +22,7 @@ from api.db import UserTenantRole
|
||||
from api.db.db_models import DB, UserTenant
|
||||
from api.db.db_models import User, Tenant
|
||||
from api.db.services.common_service import CommonService
|
||||
from api.utils import get_uuid, get_format_time, current_timestamp, datetime_format
|
||||
from api.utils import get_uuid, current_timestamp, datetime_format
|
||||
from api.db import StatusEnum
|
||||
|
||||
|
||||
|
||||
@ -14,6 +14,13 @@
|
||||
# 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
|
||||
|
||||
from api.utils.log_utils import initRootLogger
|
||||
initRootLogger("ragflow_server")
|
||||
|
||||
import logging
|
||||
import os
|
||||
import signal
|
||||
@ -23,17 +30,17 @@ 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
|
||||
from rag.settings import print_rag_settings
|
||||
|
||||
|
||||
def update_progress():
|
||||
@ -41,59 +48,68 @@ def update_progress():
|
||||
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()
|
||||
print_rag_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)
|
||||
|
||||
324
api/settings.py
324
api/settings.py
@ -16,197 +16,163 @@
|
||||
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 = 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"]
|
||||
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", str(date.today()))
|
||||
|
||||
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")
|
||||
lower_case_doc_engine = DOC_ENGINE.lower()
|
||||
if lower_case_doc_engine == "elasticsearch":
|
||||
docStoreConn = rag.utils.es_conn.ESConnection()
|
||||
elif lower_case_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 +193,6 @@ 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
|
||||
|
||||
@ -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 ''
|
||||
|
||||
@ -342,8 +351,8 @@ 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):
|
||||
|
||||
@ -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
|
||||
@ -33,13 +34,11 @@ 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 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)
|
||||
@ -58,13 +57,13 @@ def request(**kwargs):
|
||||
{}).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(
|
||||
@ -78,7 +77,7 @@ def request(**kwargs):
|
||||
prepped.headers.update({
|
||||
'TIMESTAMP': timestamp,
|
||||
'NONCE': nonce,
|
||||
'APP-KEY': HTTP_APP_KEY,
|
||||
'APP-KEY': settings.HTTP_APP_KEY,
|
||||
'SIGNATURE': signature,
|
||||
})
|
||||
|
||||
@ -97,19 +96,19 @@ def get_exponential_backoff_interval(retries, full_jitter=False):
|
||||
return max(0, countdown)
|
||||
|
||||
|
||||
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
|
||||
@ -117,29 +116,25 @@ 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')
|
||||
|
||||
|
||||
@ -171,13 +166,25 @@ 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
|
||||
|
||||
return wrapper
|
||||
|
||||
def not_allowed_parameters(*params):
|
||||
def decorator(f):
|
||||
def wrapper(*args, **kwargs):
|
||||
input_arguments = flask_request.json or flask_request.form.to_dict()
|
||||
for param in params:
|
||||
if param in input_arguments:
|
||||
return get_json_result(
|
||||
code=settings.RetCode.ARGUMENT_ERROR, message=f"Parameter {param} isn't allowed")
|
||||
return f(*args, **kwargs)
|
||||
return wrapper
|
||||
return decorator
|
||||
|
||||
|
||||
def is_localhost(ip):
|
||||
return ip in {'127.0.0.1', '::1', '[::1]', 'localhost'}
|
||||
@ -196,8 +203,8 @@ 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):
|
||||
@ -207,7 +214,7 @@ def apikey_required(func):
|
||||
objs = APIToken.query(token=token)
|
||||
if not objs:
|
||||
return build_error_result(
|
||||
error_msg='API-KEY is invalid!', retcode=RetCode.FORBIDDEN
|
||||
message='API-KEY is invalid!', code=settings.RetCode.FORBIDDEN
|
||||
)
|
||||
kwargs['tenant_id'] = objs[0].tenant_id
|
||||
return func(*args, **kwargs)
|
||||
@ -215,19 +222,19 @@ def apikey_required(func):
|
||||
return decorated_function
|
||||
|
||||
|
||||
def build_error_result(retcode=RetCode.FORBIDDEN, error_msg='success'):
|
||||
response = {"error_code": retcode, "error_msg": error_msg}
|
||||
def build_error_result(code=settings.RetCode.FORBIDDEN, message='success'):
|
||||
response = {"code": code, "message": message}
|
||||
response = jsonify(response)
|
||||
response.status_code = retcode
|
||||
response.status_code = code
|
||||
return response
|
||||
|
||||
|
||||
def construct_response(retcode=RetCode.SUCCESS,
|
||||
retmsg='success', data=None, auth=None):
|
||||
result_dict = {"retcode": retcode, "retmsg": retmsg, "data": data}
|
||||
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
|
||||
@ -242,7 +249,7 @@ 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 = {}
|
||||
@ -254,7 +261,7 @@ 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:
|
||||
@ -262,29 +269,28 @@ 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)
|
||||
@ -292,26 +298,26 @@ def token_required(func):
|
||||
return decorated_function
|
||||
|
||||
|
||||
def get_result(retcode=RetCode.SUCCESS, retmsg='error', data=None):
|
||||
if retcode == 0:
|
||||
def get_result(code=settings.RetCode.SUCCESS, message="", data=None):
|
||||
if code == 0:
|
||||
if data is not None:
|
||||
response = {"code": retcode, "data": data}
|
||||
response = {"code": code, "data": data}
|
||||
else:
|
||||
response = {"code": retcode}
|
||||
response = {"code": code}
|
||||
else:
|
||||
response = {"code": retcode, "message": retmsg}
|
||||
response = {"code": code, "message": message}
|
||||
return jsonify(response)
|
||||
|
||||
|
||||
def get_error_data_result(retmsg='Sorry! Data missing!', retcode=RetCode.DATA_ERROR,
|
||||
def get_error_data_result(message='Sorry! Data missing!', code=settings.RetCode.DATA_ERROR,
|
||||
):
|
||||
import re
|
||||
result_dict = {
|
||||
"code": retcode,
|
||||
"code": code,
|
||||
"message": re.sub(
|
||||
r"rag",
|
||||
"seceum",
|
||||
retmsg,
|
||||
message,
|
||||
flags=re.IGNORECASE)}
|
||||
response = {}
|
||||
for key, value in result_dict.items():
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user