Include document_id in knowledgebase info retrieval (#12041)

### What problem does this PR solve?
After a file in the file list is associated with a knowledge base, the
knowledge base document ID is returned


### Type of change

- [x] New Feature (non-breaking change which adds functionality)

.github/copilot-instructions.md

@@ -0,0 +1 @@
+Refer to [AGENTS.MD](../AGENTS.md) for all repo instructions.

.github/workflows/release.yml

@@ -3,11 +3,12 @@ name: release
 on:
   schedule:
     - cron: '0 13 * * *'  # This schedule runs every 13:00:00Z(21:00:00+08:00)
+  # https://github.com/orgs/community/discussions/26286?utm_source=chatgpt.com#discussioncomment-3251208
+  # "The create event does not support branch filter and tag filter."
   # 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:
+  push:
     tags:
       - "v*.*.*"                  # normal release
-      - "nightly"                 # the only one mutable tag
 
 # https://docs.github.com/en/actions/using-jobs/using-concurrency
 concurrency:
@@ -21,9 +22,9 @@ jobs:
       - 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
+      # https://github.com/actions/checkout/blob/v6/README.md
       - name: Check out code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           token: ${{ secrets.GITHUB_TOKEN }}  # Use the secret as an environment variable
           fetch-depth: 0
@@ -31,12 +32,12 @@ jobs:
 
       - name: Prepare release body
         run: |
-          if [[ ${GITHUB_EVENT_NAME} == "create" ]]; then
+          if [[ ${GITHUB_EVENT_NAME} != "schedule" ]]; then
             RELEASE_TAG=${GITHUB_REF#refs/tags/}
-            if [[ ${RELEASE_TAG} == "nightly" ]]; then
+            if [[ ${RELEASE_TAG} == v* ]]; then
-              PRERELEASE=true
-            else
               PRERELEASE=false
+            else
+              PRERELEASE=true
             fi
             echo "Workflow triggered by create tag: ${RELEASE_TAG}"
           else
@@ -55,7 +56,7 @@ jobs:
           git fetch --tags
           if [[ ${GITHUB_EVENT_NAME} == "schedule" ]]; then
             # Determine if a given tag exists and matches a specific Git commit.
-            # actions/checkout@v4 fetch-tags doesn't work when triggered by schedule
+            # actions/checkout@v6 fetch-tags doesn't work when triggered by schedule
             if [ "$(git rev-parse -q --verify "refs/tags/${RELEASE_TAG}")" = "${GITHUB_SHA}" ]; then
               echo "mutable tag ${RELEASE_TAG} exists and matches ${GITHUB_SHA}"
             else
@@ -88,7 +89,7 @@ jobs:
       - name: Build and push image
         run: |
           sudo docker login --username infiniflow --password-stdin <<< ${{ secrets.DOCKERHUB_TOKEN }}
-          sudo docker build --build-arg NEED_MIRROR=1 -t infiniflow/ragflow:${RELEASE_TAG} -f Dockerfile .
+          sudo docker build --build-arg NEED_MIRROR=1 --build-arg HTTPS_PROXY=${HTTPS_PROXY} --build-arg HTTP_PROXY=${HTTP_PROXY} -t infiniflow/ragflow:${RELEASE_TAG} -f Dockerfile .
           sudo docker tag infiniflow/ragflow:${RELEASE_TAG} infiniflow/ragflow:latest
           sudo docker push infiniflow/ragflow:${RELEASE_TAG}
           sudo docker push infiniflow/ragflow:latest

.github/workflows/tests.yml

@@ -1,4 +1,6 @@
 name: tests
+permissions:
+  contents: read
 
 on:
   push:
@@ -12,7 +14,7 @@ on:
   # The only difference between pull_request and pull_request_target is the context in which the workflow runs:
   # — pull_request_target workflows use the workflow files from the default branch, and secrets are available.
   # — pull_request workflows use the workflow files from the pull request branch, and secrets are unavailable.
-  pull_request_target:
+  pull_request:
     types: [ synchronize, ready_for_review ]
     paths-ignore:
       - 'docs/**'
@@ -31,12 +33,9 @@ jobs:
     name: ragflow_tests
     # https://docs.github.com/en/actions/using-jobs/using-conditions-to-control-job-execution
     # https://github.com/orgs/community/discussions/26261
-    if: ${{ github.event_name != 'pull_request_target' || (contains(github.event.pull_request.labels.*.name, 'ci') && github.event.pull_request.mergeable == true) }}
+    if: ${{ github.event_name != 'pull_request' || (github.event.pull_request.draft == false && contains(github.event.pull_request.labels.*.name, 'ci')) }}
     runs-on: [ "self-hosted", "ragflow-test" ]
     steps:
-      # https://github.com/hmarr/debug-action
-      #- uses: hmarr/debug-action@v2
-
       - name: Ensure workspace ownership
         run: |
           echo "Workflow triggered by ${{ github.event_name }}"
@@ -44,7 +43,7 @@ jobs:
 
       # https://github.com/actions/checkout/issues/1781
       - name: Check out code
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
         with:
           ref: ${{ (github.event_name == 'pull_request' || github.event_name == 'pull_request_target') && format('refs/pull/{0}/merge', github.event.pull_request.number) || github.sha }}
           fetch-depth: 0
@@ -53,7 +52,7 @@ jobs:
       - name: Check workflow duplication
         if: ${{ !cancelled() && !failure() }}
         run: |
-          if [[ ${GITHUB_EVENT_NAME} != "pull_request_target" && ${GITHUB_EVENT_NAME} != "schedule" ]]; then
+          if [[ ${GITHUB_EVENT_NAME} != "pull_request" && ${GITHUB_EVENT_NAME} != "schedule" ]]; then
             HEAD=$(git rev-parse HEAD)
             # Find a PR that introduced a given commit
             gh auth login --with-token <<< "${{ secrets.GITHUB_TOKEN }}"
@@ -78,7 +77,7 @@ jobs:
                 fi
               fi
             fi
-          elif [[ ${GITHUB_EVENT_NAME} == "pull_request_target" ]]; then
+          elif [[ ${GITHUB_EVENT_NAME} == "pull_request" ]]; then
             PR_NUMBER=${{ github.event.pull_request.number }}
             PR_SHA_FP=${RUNNER_WORKSPACE_PREFIX}/artifacts/${GITHUB_REPOSITORY}/PR_${PR_NUMBER}
             # Calculate the hash of the current workspace content
@@ -98,7 +97,7 @@ jobs:
       - name: Check comments of changed Python files
         if: ${{ false }}
         run: |
-          if [[ ${{ github.event_name }} == 'pull_request_target' ]]; then
+          if [[ ${{ github.event_name }} == 'pull_request' || ${{ github.event_name }} == 'pull_request_target' ]]; then
             CHANGED_FILES=$(git diff --name-only ${{ github.event.pull_request.base.sha }}...${{ github.event.pull_request.head.sha }} \
               | grep -E '\.(py)$' || true)
 
@@ -127,13 +126,21 @@ jobs:
             fi
           fi
 
+      - name: Run unit test
+        run: |
+          uv sync --python 3.12 --group test --frozen
+          source .venv/bin/activate
+          which pytest || echo "pytest not in PATH"
+          echo "Start to run unit test"
+          python3 run_tests.py
+
       - name: Build ragflow:nightly
         run: |
           RUNNER_WORKSPACE_PREFIX=${RUNNER_WORKSPACE_PREFIX:-${HOME}}
           RAGFLOW_IMAGE=infiniflow/ragflow:${GITHUB_RUN_ID}
           echo "RAGFLOW_IMAGE=${RAGFLOW_IMAGE}" >> ${GITHUB_ENV}
           sudo docker pull ubuntu:22.04
-          sudo DOCKER_BUILDKIT=1 docker build --build-arg NEED_MIRROR=1 -f Dockerfile -t ${RAGFLOW_IMAGE} .
+          sudo DOCKER_BUILDKIT=1 docker build --build-arg NEED_MIRROR=1 --build-arg HTTPS_PROXY=${HTTPS_PROXY} --build-arg HTTP_PROXY=${HTTP_PROXY} -f Dockerfile -t ${RAGFLOW_IMAGE} .
           if [[ ${GITHUB_EVENT_NAME} == "schedule" ]]; then
             export HTTP_API_TEST_LEVEL=p3
           else
@@ -193,7 +200,7 @@ jobs:
           echo "HOST_ADDRESS=http://host.docker.internal:${SVR_HTTP_PORT}" >> ${GITHUB_ENV}
 
           sudo docker compose -f docker/docker-compose.yml -p ${GITHUB_RUN_ID} up -d
-          uv sync --python 3.10 --only-group test --no-default-groups --frozen && uv pip install sdk/python --group test
+          uv sync --python 3.12 --only-group test --no-default-groups --frozen && uv pip install sdk/python --group test
 
       - name: Run sdk tests against Elasticsearch
         run: |

.gitignore

@@ -195,3 +195,6 @@ ragflow_cli.egg-info
 
 # Default backup dir
 backup
+
+
+.hypothesis

AGENTS.md

@@ -0,0 +1,110 @@
+# RAGFlow Project Instructions for GitHub Copilot
+
+This file provides context, build instructions, and coding standards for the RAGFlow project.
+It is structured to follow GitHub Copilot's [customization guidelines](https://docs.github.com/en/copilot/concepts/prompting/response-customization).
+
+## 1. Project Overview
+RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It is a full-stack application with a Python backend and a React/TypeScript frontend.
+
+- **Backend**: Python 3.10+ (Flask/Quart)
+- **Frontend**: TypeScript, React, UmiJS
+- **Architecture**: Microservices based on Docker.
+  - `api/`: Backend API server.
+  - `rag/`: Core RAG logic (indexing, retrieval).
+  - `deepdoc/`: Document parsing and OCR.
+  - `web/`: Frontend application.
+
+## 2. Directory Structure
+- `api/`: Backend API server (Flask/Quart).
+  - `apps/`: API Blueprints (Knowledge Base, Chat, etc.).
+  - `db/`: Database models and services.
+- `rag/`: Core RAG logic.
+  - `llm/`: LLM, Embedding, and Rerank model abstractions.
+- `deepdoc/`: Document parsing and OCR modules.
+- `agent/`: Agentic reasoning components.
+- `web/`: Frontend application (React + UmiJS).
+- `docker/`: Docker deployment configurations.
+- `sdk/`: Python SDK.
+- `test/`: Backend tests.
+
+## 3. Build Instructions
+
+### Backend (Python)
+The project uses **uv** for dependency management.
+
+1. **Setup Environment**:
+   ```bash
+   uv sync --python 3.12 --all-extras
+   uv run download_deps.py
+   ```
+
+2. **Run Server**:
+   - **Pre-requisite**: Start dependent services (MySQL, ES/Infinity, Redis, MinIO).
+     ```bash
+     docker compose -f docker/docker-compose-base.yml up -d
+     ```
+   - **Launch**:
+     ```bash
+     source .venv/bin/activate
+     export PYTHONPATH=$(pwd)
+     bash docker/launch_backend_service.sh
+     ```
+
+### Frontend (TypeScript/React)
+Located in `web/`.
+
+1. **Install Dependencies**:
+   ```bash
+   cd web
+   npm install
+   ```
+
+2. **Run Dev Server**:
+   ```bash
+   npm run dev
+   ```
+   Runs on port 8000 by default.
+
+### Docker Deployment
+To run the full stack using Docker:
+```bash
+cd docker
+docker compose -f docker-compose.yml up -d
+```
+
+## 4. Testing Instructions
+
+### Backend Tests
+- **Run All Tests**:
+  ```bash
+  uv run pytest
+  ```
+- **Run Specific Test**:
+  ```bash
+  uv run pytest test/test_api.py
+  ```
+
+### Frontend Tests
+- **Run Tests**:
+  ```bash
+  cd web
+  npm run test
+  ```
+
+## 5. Coding Standards & Guidelines
+- **Python Formatting**: Use `ruff` for linting and formatting.
+  ```bash
+  ruff check
+  ruff format
+  ```
+- **Frontend Linting**:
+  ```bash
+  cd web
+  npm run lint
+  ```
+- **Pre-commit**: Ensure pre-commit hooks are installed.
+  ```bash
+  pre-commit install
+  pre-commit run --all-files
+  ```
+

CLAUDE.md

@@ -45,7 +45,7 @@ RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on d
 ### Backend Development
 ```bash
 # Install Python dependencies
-uv sync --python 3.10 --all-extras
+uv sync --python 3.12 --all-extras
 uv run download_deps.py
 pre-commit install
 

Dockerfile

@@ -1,5 +1,5 @@
 # base stage
-FROM ubuntu:22.04 AS base
+FROM ubuntu:24.04 AS base
 USER root
 SHELL ["/bin/bash", "-c"]
 
@@ -10,7 +10,6 @@ WORKDIR /ragflow
 # 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 \
@@ -34,36 +33,41 @@ ENV DEBIAN_FRONTEND=noninteractive
 # 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 \
+    apt update && \
+    apt --no-install-recommends install -y ca-certificates; \
     if [ "$NEED_MIRROR" == "1" ]; then \
-        sed -i 's|http://ports.ubuntu.com|http://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list; \
+        sed -i 's|http://archive.ubuntu.com/ubuntu|https://mirrors.tuna.tsinghua.edu.cn/ubuntu|g' /etc/apt/sources.list.d/ubuntu.sources; \
-        sed -i 's|http://archive.ubuntu.com|http://mirrors.tuna.tsinghua.edu.cn|g' /etc/apt/sources.list; \
+        sed -i 's|http://security.ubuntu.com/ubuntu|https://mirrors.tuna.tsinghua.edu.cn/ubuntu|g' /etc/apt/sources.list.d/ubuntu.sources; \
     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 libjemalloc-dev && \
-    apt install -y python3-pip pipx nginx unzip curl wget git vim less && \
+    apt install -y nginx unzip curl wget git vim less && \
     apt install -y ghostscript && \
     apt install -y pandoc && \
-    apt install -y texlive
+    apt install -y texlive && \
+    apt install -y fonts-freefont-ttf fonts-noto-cjk
 
-RUN if [ "$NEED_MIRROR" == "1" ]; then \
+# Install uv
-        pip3 config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple && \
+RUN --mount=type=bind,from=infiniflow/ragflow_deps:latest,source=/,target=/deps \
-        pip3 config set global.trusted-host pypi.tuna.tsinghua.edu.cn; \
+    if [ "$NEED_MIRROR" == "1" ]; then \
         mkdir -p /etc/uv && \
-        echo "[[index]]" > /etc/uv/uv.toml && \
+        echo 'python-install-mirror = "https://registry.npmmirror.com/-/binary/python-build-standalone/"' > /etc/uv/uv.toml && \
+        echo '[[index]]' >> /etc/uv/uv.toml && \
         echo 'url = "https://pypi.tuna.tsinghua.edu.cn/simple"' >> /etc/uv/uv.toml && \
-        echo "default = true" >> /etc/uv/uv.toml; \
+        echo 'default = true' >> /etc/uv/uv.toml; \
     fi; \
-    pipx install uv
+    tar xzf /deps/uv-x86_64-unknown-linux-gnu.tar.gz \
+    && cp uv-x86_64-unknown-linux-gnu/* /usr/local/bin/ \
+    && rm -rf uv-x86_64-unknown-linux-gnu \
+    && uv python install 3.11
 
 ENV PYTHONDONTWRITEBYTECODE=1 DOTNET_SYSTEM_GLOBALIZATION_INVARIANT=1
 ENV PATH=/root/.local/bin:$PATH
@@ -79,12 +83,12 @@ RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
 # A modern version of cargo is needed for the latest version of the Rust compiler.
 RUN apt update && apt install -y curl build-essential \
     && if [ "$NEED_MIRROR" == "1" ]; then \
-         # Use TUNA mirrors for rustup/rust dist files
+         # Use TUNA mirrors for rustup/rust dist files \
          export RUSTUP_DIST_SERVER="https://mirrors.tuna.tsinghua.edu.cn/rustup"; \
          export RUSTUP_UPDATE_ROOT="https://mirrors.tuna.tsinghua.edu.cn/rustup/rustup"; \
          echo "Using TUNA mirrors for Rustup."; \
        fi; \
-    # Force curl to use HTTP/1.1
+    # Force curl to use HTTP/1.1 \
     curl --proto '=https' --tlsv1.2 --http1.1 -sSf https://sh.rustup.rs | bash -s -- -y --profile minimal \
     && echo 'export PATH="/root/.cargo/bin:${PATH}"' >> /root/.bashrc
 
@@ -101,10 +105,10 @@ RUN --mount=type=cache,id=ragflow_apt,target=/var/cache/apt,sharing=locked \
     apt update && \
     arch="$(uname -m)"; \
     if [ "$arch" = "arm64" ] || [ "$arch" = "aarch64" ]; then \
-        # ARM64 (macOS/Apple Silicon or Linux aarch64)
+        # ARM64 (macOS/Apple Silicon or Linux aarch64) \
         ACCEPT_EULA=Y apt install -y unixodbc-dev msodbcsql18; \
     else \
-        # x86_64 or others
+        # x86_64 or others \
         ACCEPT_EULA=Y apt install -y unixodbc-dev msodbcsql17; \
     fi || \
     { echo "Failed to install ODBC driver"; exit 1; }
@@ -148,7 +152,7 @@ RUN --mount=type=cache,id=ragflow_uv,target=/root/.cache/uv,sharing=locked \
     else \
         sed -i 's|pypi.tuna.tsinghua.edu.cn|pypi.org|g' uv.lock; \
     fi; \
-    uv sync --python 3.10 --frozen
+    uv sync --python 3.12 --frozen
 
 COPY web web
 COPY docs docs

Dockerfile.deps

@@ -3,7 +3,7 @@
 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 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 uv-x86_64-unknown-linux-gnu.tar.gz /
 
 COPY nltk_data /nltk_data
 

README.md

@@ -194,7 +194,7 @@ releases! 🌟
   
    # git checkout v0.22.1
    # Optional: use a stable tag (see releases: https://github.com/infiniflow/ragflow/releases)
-   # This steps ensures the **entrypoint.sh** file in the code matches the Docker image version.
+   # This step ensures the **entrypoint.sh** file in the code matches the Docker image version.
    
    # Use CPU for DeepDoc tasks:
    $ docker compose -f docker-compose.yml up -d
@@ -207,7 +207,7 @@ releases! 🌟
 > Note: Prior to `v0.22.0`, we provided both images with embedding models and slim images without embedding models. Details as follows:
 
 | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
-| ----------------- | --------------- | --------------------- | ------------------------ |
+|-------------------|-----------------|-----------------------|----------------|
 | v0.21.1           | ≈9       | ✔️                    | Stable release |
 | v0.21.1-slim      | ≈2       | ❌                     | Stable release |
 
@@ -314,7 +314,7 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
    ```bash
    git clone https://github.com/infiniflow/ragflow.git
    cd ragflow/
-   uv sync --python 3.10 # install RAGFlow dependent python modules
+   uv sync --python 3.12 # install RAGFlow dependent python modules
    uv run download_deps.py
    pre-commit install
    ```

README_id.md

@@ -207,7 +207,7 @@ Coba demo kami di [https://demo.ragflow.io](https://demo.ragflow.io).
 > Catatan: Sebelum `v0.22.0`, kami menyediakan image dengan model embedding dan image slim tanpa model embedding. Detailnya sebagai berikut:
 
 | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
-| ----------------- | --------------- | --------------------- | ------------------------ |
+|-------------------|-----------------|-----------------------|----------------|
 | v0.21.1           | ≈9       | ✔️                    | Stable release |
 | v0.21.1-slim      | ≈2       | ❌                     | Stable release |
 
@@ -288,7 +288,7 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
    ```bash
    git clone https://github.com/infiniflow/ragflow.git
    cd ragflow/
-   uv sync --python 3.10 # install RAGFlow dependent python modules
+   uv sync --python 3.12 # install RAGFlow dependent python modules
    uv run download_deps.py
    pre-commit install
    ```

README_ja.md

@@ -187,7 +187,7 @@
 > 注意：`v0.22.0` より前のバージョンでは、embedding モデルを含むイメージと、embedding モデルを含まない slim イメージの両方を提供していました。詳細は以下の通りです：
 
 | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
-| ----------------- | --------------- | --------------------- | ------------------------ |
+|-------------------|-----------------|-----------------------|----------------|
 | v0.21.1           | ≈9       | ✔️                    | Stable release |
 | v0.21.1-slim      | ≈2       | ❌                     | Stable release |
 
@@ -288,7 +288,7 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
    ```bash
    git clone https://github.com/infiniflow/ragflow.git
    cd ragflow/
-   uv sync --python 3.10 # install RAGFlow dependent python modules
+   uv sync --python 3.12 # install RAGFlow dependent python modules
    uv run download_deps.py
    pre-commit install
    ```

README_ko.md

@@ -189,7 +189,7 @@
 > 참고: `v0.22.0` 이전 버전에서는 embedding 모델이 포함된 이미지와 embedding 모델이 포함되지 않은 slim 이미지를 모두 제공했습니다. 자세한 내용은 다음과 같습니다:
 
 | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
-| ----------------- | --------------- | --------------------- | ------------------------ |
+|-------------------|-----------------|-----------------------|----------------|
 | v0.21.1           | ≈9       | ✔️                    | Stable release |
 | v0.21.1-slim      | ≈2       | ❌                     | Stable release |
 
@@ -283,7 +283,7 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
    ```bash
    git clone https://github.com/infiniflow/ragflow.git
    cd ragflow/
-   uv sync --python 3.10 # install RAGFlow dependent python modules
+   uv sync --python 3.12 # install RAGFlow dependent python modules
    uv run download_deps.py
    pre-commit install
    ```

README_pt_br.md

@@ -207,7 +207,7 @@ Experimente nossa demo em [https://demo.ragflow.io](https://demo.ragflow.io).
 > Nota: Antes da `v0.22.0`, fornecíamos imagens com modelos de embedding e imagens slim sem modelos de embedding. Detalhes a seguir:
 
 | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
-| ----------------- | --------------- | --------------------- | ------------------------ |
+|-------------------|-----------------|-----------------------|----------------|
 | v0.21.1           | ≈9       | ✔️                    | Stable release |
 | v0.21.1-slim      | ≈2       | ❌                     | Stable release |
 
@@ -305,7 +305,7 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
    ```bash
    git clone https://github.com/infiniflow/ragflow.git
    cd ragflow/
-   uv sync --python 3.10 # instala os módulos Python dependentes do RAGFlow
+   uv sync --python 3.12 # instala os módulos Python dependentes do RAGFlow
    uv run download_deps.py
    pre-commit install
    ```

README_tzh.md

@@ -206,7 +206,7 @@
 > 注意：在 `v0.22.0` 之前的版本，我們會同時提供包含 embedding 模型的映像和不含 embedding 模型的 slim 映像。具體如下：
 
 | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
-| ----------------- | --------------- | --------------------- | ------------------------ |
+|-------------------|-----------------|-----------------------|----------------|
 | v0.21.1           | ≈9       | ✔️                    | Stable release |
 | v0.21.1-slim      | ≈2       | ❌                     | Stable release |
 
@@ -315,7 +315,7 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
    ```bash
    git clone https://github.com/infiniflow/ragflow.git
    cd ragflow/
-   uv sync --python 3.10 # install RAGFlow dependent python modules
+   uv sync --python 3.12 # install RAGFlow dependent python modules
    uv run download_deps.py
    pre-commit install
    ```

README_zh.md

@@ -207,7 +207,7 @@
    > 注意：在 `v0.22.0` 之前的版本，我们会同时提供包含 embedding 模型的镜像和不含 embedding 模型的 slim 镜像。具体如下：
 
    | RAGFlow image tag | Image size (GB) | Has embedding models? | Stable?        |
-   | ----------------- | --------------- | --------------------- | ------------------------ |
+   |-------------------|-----------------|-----------------------|----------------|
    | v0.21.1           | ≈9       | ✔️                    | Stable release |
    | v0.21.1-slim      | ≈2       | ❌                     | Stable release |
 
@@ -315,7 +315,7 @@ docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly
    ```bash
    git clone https://github.com/infiniflow/ragflow.git
    cd ragflow/
-   uv sync --python 3.10 # install RAGFlow dependent python modules
+   uv sync --python 3.12 # install RAGFlow dependent python modules
    uv run download_deps.py
    pre-commit install
    ```

SECURITY.md

@@ -6,7 +6,7 @@ Use this section to tell people about which versions of your project are
 currently being supported with security updates.
 
 | Version | Supported          |
-| ------- | ------------------ |
+|---------|--------------------|
 | <=0.7.0 | :white_check_mark: |
 
 ## Reporting a Vulnerability

admin/client/admin_client.py

@@ -351,7 +351,7 @@ class AdminCLI(Cmd):
     def verify_admin(self, arguments: dict, single_command: bool):
         self.host = arguments['host']
         self.port = arguments['port']
-        print(f"Attempt to access ip: {self.host}, port: {self.port}")
+        print("Attempt to access server for admin login")
         url = f"http://{self.host}:{self.port}/api/v1/admin/login"
 
         attempt_count = 3
@@ -390,7 +390,7 @@ class AdminCLI(Cmd):
                     print(f"Bad response，status: {response.status_code}, password is wrong")
             except Exception as e:
                 print(str(e))
-                print(f"Can't access {self.host}, port: {self.port}")
+                print("Can't access server for admin login (connection failed)")
 
     def _format_service_detail_table(self, data):
         if isinstance(data, list):
@@ -674,7 +674,7 @@ class AdminCLI(Cmd):
         user_name: str = user_name_tree.children[0].strip("'\"")
         password_tree: Tree = command['password']
         password: str = password_tree.children[0].strip("'\"")
-        print(f"Alter user: {user_name}, password: {password}")
+        print(f"Alter user: {user_name}, password: ******")
         url = f'http://{self.host}:{self.port}/api/v1/admin/users/{user_name}/password'
         response = self.session.put(url, json={'new_password': encrypt(password)})
         res_json = response.json()
@@ -689,7 +689,7 @@ class AdminCLI(Cmd):
         password_tree: Tree = command['password']
         password: str = password_tree.children[0].strip("'\"")
         role: str = command['role']
-        print(f"Create user: {user_name}, password: {password}, role: {role}")
+        print(f"Create user: {user_name}, password: ******, role: {role}")
         url = f'http://{self.host}:{self.port}/api/v1/admin/users'
         response = self.session.post(
             url,
@@ -951,7 +951,7 @@ def main():
 
     args = cli.parse_connection_args(sys.argv)
     if 'error' in args:
-        print(f"Error: {args['error']}")
+        print("Error: Invalid connection arguments")
         return
 
     if 'command' in args:
@@ -960,7 +960,7 @@ def main():
             return
         if cli.verify_admin(args, single_command=True):
             command: str = args['command']
-            print(f"Run single command: {command}")
+            # print(f"Run single command: {command}")
             cli.run_single_command(command)
     else:
         if cli.verify_admin(args, single_command=False):

admin/client/pyproject.toml

@@ -5,7 +5,7 @@ description = "Admin Service's client of [RAGFlow](https://github.com/infiniflow
 authors = [{ name = "Lynn", email = "lynn_inf@hotmail.com" }]
 license = { text = "Apache License, Version 2.0" }
 readme = "README.md"
-requires-python = ">=3.10,<3.13"
+requires-python = ">=3.12,<3.15"
 dependencies = [
     "requests>=2.30.0,<3.0.0",
     "beartype>=0.20.0,<1.0.0",

admin/server/auth.py

@@ -176,11 +176,11 @@ def login_verify(f):
                     "message": "Access denied",
                     "data": None
                 }), 200
-        except Exception as e:
+        except Exception:
-            error_msg = str(e)
+            logging.exception("An error occurred during admin login verification.")
             return jsonify({
                 "code": 500,
-                "message": error_msg
+                "message": "An internal server error occurred."
             }), 200
 
         return f(*args, **kwargs)

agent/__init__.py

@@ -13,6 +13,3 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-
-from beartype.claw import beartype_this_package
-beartype_this_package()

agent/canvas.py

@@ -13,7 +13,10 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
 import base64
+import inspect
+import binascii
 import json
 import logging
 import re
@@ -25,7 +28,10 @@ from typing import Any, Union, Tuple
 
 from agent.component import component_class
 from agent.component.base import ComponentBase
+from api.db.services.file_service import FileService
+from api.db.services.llm_service import LLMBundle
 from api.db.services.task_service import has_canceled
+from common.constants import LLMType
 from common.misc_utils import get_uuid, hash_str2int
 from common.exceptions import TaskCanceledException
 from rag.prompts.generator import chunks_format
@@ -79,14 +85,12 @@ class Graph:
         self.dsl = json.loads(dsl)
         self._tenant_id = tenant_id
         self.task_id = task_id if task_id else get_uuid()
+        self._thread_pool = ThreadPoolExecutor(max_workers=5)
         self.load()
 
     def load(self):
         self.components = self.dsl["components"]
         cpn_nms = set([])
-        for k, cpn in self.components.items():
-            cpn_nms.add(cpn["obj"]["component_name"])
-
         for k, cpn in self.components.items():
             cpn_nms.add(cpn["obj"]["component_name"])
             param = component_class(cpn["obj"]["component_name"] + "Param")()
@@ -156,7 +160,7 @@ class Graph:
         return self._tenant_id
 
     def get_value_with_variable(self,value: str) -> Any:
-        pat = re.compile(r"\{* *\{([a-zA-Z:0-9]+@[A-Za-z0-9_.]+|sys\.[A-Za-z0-9_.]+|env\.[A-Za-z0-9_.]+)\} *\}*")
+        pat = re.compile(r"\{* *\{([a-zA-Z:0-9]+@[A-Za-z0-9_.-]+|sys\.[A-Za-z0-9_.]+|env\.[A-Za-z0-9_.]+)\} *\}*")
         out_parts = []
         last = 0
 
@@ -281,6 +285,7 @@ class Canvas(Graph):
             "sys.conversation_turns": 0,
             "sys.files": []
         }
+        self.variables = {}
         super().__init__(dsl, tenant_id, task_id)
 
     def load(self):
@@ -295,6 +300,10 @@ class Canvas(Graph):
             "sys.conversation_turns": 0,
             "sys.files": []
         }
+        if "variables" in self.dsl:
+            self.variables = self.dsl["variables"]
+        else:
+            self.variables = {}
 
         self.retrieval = self.dsl["retrieval"]
         self.memory = self.dsl.get("memory", [])
@@ -311,8 +320,9 @@ class Canvas(Graph):
             self.history = []
             self.retrieval = []
             self.memory = []
+        print(self.variables)
         for k in self.globals.keys():
-            if k.startswith("sys.") or k.startswith("env."):
+            if k.startswith("sys."):
                 if isinstance(self.globals[k], str):
                     self.globals[k] = ""
                 elif isinstance(self.globals[k], int):
@@ -325,9 +335,31 @@ class Canvas(Graph):
                     self.globals[k] = {}
                 else:
                     self.globals[k] = None
+            if k.startswith("env."):
+                key = k[4:]
+                if key in self.variables:
+                    variable = self.variables[key]
+                    if variable["value"]:
+                        self.globals[k] = variable["value"]
+                    else:
+                        if variable["type"] == "string":
+                            self.globals[k] = ""
+                        elif variable["type"] == "number":
+                            self.globals[k] = 0
+                        elif variable["type"] == "boolean":
+                            self.globals[k] = False
+                        elif variable["type"] == "object":
+                            self.globals[k] = {}
+                        elif variable["type"].startswith("array"):
+                            self.globals[k] = []
+                        else:
+                            self.globals[k] = ""
+                else:
+                    self.globals[k] = ""
 
     async def run(self, **kwargs):
         st = time.perf_counter()
+        self._loop = asyncio.get_running_loop()
         self.message_id = get_uuid()
         created_at = int(time.time())
         self.add_user_input(kwargs.get("query"))
@@ -336,14 +368,19 @@ class Canvas(Graph):
 
         if kwargs.get("webhook_payload"):
             for k, cpn in self.components.items():
-                if self.components[k]["obj"].component_name.lower() == "webhook":
+                if self.components[k]["obj"].component_name.lower() == "begin"  and self.components[k]["obj"]._param.mode == "Webhook":
-                    for kk, vv in kwargs["webhook_payload"].items():
+                    payload = kwargs.get("webhook_payload", {})
+                    if "input" in payload:
+                        self.components[k]["obj"].set_input_value("request", payload["input"])
+                    for kk, vv in payload.items():
+                        if kk == "input":
+                            continue
                         self.components[k]["obj"].set_output(kk, vv)
 
         for k in kwargs.keys():
             if k in ["query", "user_id", "files"] and kwargs[k]:
                 if k == "files":
-                    self.globals[f"sys.{k}"] = self.get_files(kwargs[k])
+                    self.globals[f"sys.{k}"] = await self.get_files_async(kwargs[k])
                 else:
                     self.globals[f"sys.{k}"] = kwargs[k]
         if not self.globals["sys.conversation_turns"] :
@@ -373,19 +410,27 @@ class Canvas(Graph):
         yield decorate("workflow_started", {"inputs": kwargs.get("inputs")})
         self.retrieval.append({"chunks": {}, "doc_aggs": {}})
 
-        def _run_batch(f, t):
+        async def _run_batch(f, t):
             if self.is_canceled():
                 msg = f"Task {self.task_id} has been canceled during batch execution."
                 logging.info(msg)
                 raise TaskCanceledException(msg)
 
-            with ThreadPoolExecutor(max_workers=5) as executor:
+            loop = asyncio.get_running_loop()
-                thr = []
+            tasks = []
+
+            def _run_async_in_thread(coro_func, **call_kwargs):
+                return asyncio.run(coro_func(**call_kwargs))
+
             i = f
             while i < t:
                 cpn = self.get_component_obj(self.path[i])
+                task_fn = None
+                call_kwargs = None
+
                 if cpn.component_name.lower() in ["begin", "userfillup"]:
-                        thr.append(executor.submit(cpn.invoke, inputs=kwargs.get("inputs", {})))
+                    call_kwargs = {"inputs": kwargs.get("inputs", {})}
+                    task_fn = cpn.invoke
                     i += 1
                 else:
                     for _, ele in cpn.get_input_elements().items():
@@ -394,10 +439,21 @@ class Canvas(Graph):
                             t -= 1
                             break
                     else:
-                            thr.append(executor.submit(cpn.invoke, **cpn.get_input()))
+                        call_kwargs = cpn.get_input()
+                        task_fn = cpn.invoke
                         i += 1
-                for t in thr:
+
-                    t.result()
+                if task_fn is None:
+                    continue
+
+                invoke_async = getattr(cpn, "invoke_async", None)
+                if invoke_async and asyncio.iscoroutinefunction(invoke_async):
+                    tasks.append(loop.run_in_executor(self._thread_pool, partial(_run_async_in_thread, invoke_async, **(call_kwargs or {}))))
+                else:
+                    tasks.append(loop.run_in_executor(self._thread_pool, partial(task_fn, **(call_kwargs or {}))))
+
+            if tasks:
+                await asyncio.gather(*tasks)
 
         def _node_finished(cpn_obj):
             return decorate("node_finished",{
@@ -414,6 +470,7 @@ class Canvas(Graph):
         self.error = ""
         idx = len(self.path) - 1
         partials = []
+        tts_mdl = None
         while idx < len(self.path):
             to = len(self.path)
             for i in range(idx, to):
@@ -424,35 +481,70 @@ class Canvas(Graph):
                     "component_type": self.get_component_type(self.path[i]),
                     "thoughts": self.get_component_thoughts(self.path[i])
                 })
-            _run_batch(idx, to)
+            await _run_batch(idx, to)
             to = len(self.path)
-            # post processing of components invocation
+            # post-processing of components invocation
             for i in range(idx, to):
                 cpn = self.get_component(self.path[i])
                 cpn_obj = self.get_component_obj(self.path[i])
                 if cpn_obj.component_name.lower() == "message":
+                    if cpn_obj.get_param("auto_play"):
+                        tts_mdl = LLMBundle(self._tenant_id, LLMType.TTS)
                     if isinstance(cpn_obj.output("content"), partial):
                         _m = ""
-                        for m in cpn_obj.output("content")():
+                        buff_m = ""
+                        stream = cpn_obj.output("content")()
+                        async def _process_stream(m):
+                            nonlocal buff_m, _m, tts_mdl
                             if not m:
-                                continue
+                                return
                             if m == "<think>":
-                                yield decorate("message", {"content": "", "start_to_think": True})
+                                return decorate("message", {"content": "", "start_to_think": True})
+
                             elif m == "</think>":
-                                yield decorate("message", {"content": "", "end_to_think": True})
+                                return decorate("message", {"content": "", "end_to_think": True})
-                            else:
+
-                                yield decorate("message", {"content": m})
+                            buff_m += m
                             _m += m
+
+                            if len(buff_m) > 16:
+                                ev = decorate(
+                                    "message",
+                                    {
+                                        "content": m,
+                                        "audio_binary": self.tts(tts_mdl, buff_m)
+                                    }
+                                )
+                                buff_m = ""
+                                return ev
+
+                            return decorate("message", {"content": m})
+
+                        if inspect.isasyncgen(stream):
+                            async for m in stream:
+                                ev= await _process_stream(m)
+                                if ev:
+                                    yield ev
+                        else:
+                            for m in stream:
+                                ev= await _process_stream(m)
+                                if ev:
+                                    yield ev
+                        if buff_m:
+                            yield decorate("message", {"content": "", "audio_binary": self.tts(tts_mdl, buff_m)})
+                            buff_m = ""
                         cpn_obj.set_output("content", _m)
                         cite = re.search(r"\[ID:[ 0-9]+\]", _m)
                     else:
                         yield decorate("message", {"content": cpn_obj.output("content")})
                         cite = re.search(r"\[ID:[ 0-9]+\]",  cpn_obj.output("content"))
 
-                    if isinstance(cpn_obj.output("attachment"), tuple):
+                    message_end = {}
-                        yield decorate("message", {"attachment": cpn_obj.output("attachment")})
+                    if isinstance(cpn_obj.output("attachment"), dict):
-
+                        message_end["attachment"] = cpn_obj.output("attachment")
-                    yield decorate("message_end", {"reference": self.get_reference() if cite else None})
+                    if cite:
+                        message_end["reference"] = self.get_reference()
+                    yield decorate("message_end", message_end)
 
                     while partials:
                         _cpn_obj = self.get_component_obj(partials[0])
@@ -473,7 +565,7 @@ class Canvas(Graph):
                     else:
                         self.error = cpn_obj.error()
 
-                if cpn_obj.component_name.lower() != "iteration":
+                if cpn_obj.component_name.lower() not in ("iteration","loop"):
                     if isinstance(cpn_obj.output("content"), partial):
                         if self.error:
                             cpn_obj.set_output("content", None)
@@ -498,14 +590,16 @@ class Canvas(Graph):
                     for cpn_id in cpn_ids:
                         _append_path(cpn_id)
 
-                if cpn_obj.component_name.lower() == "iterationitem" and cpn_obj.end():
+                if cpn_obj.component_name.lower() in ("iterationitem","loopitem") and cpn_obj.end():
                     iter = cpn_obj.get_parent()
                     yield _node_finished(iter)
                     _extend_path(self.get_component(cpn["parent_id"])["downstream"])
                 elif cpn_obj.component_name.lower() in ["categorize", "switch"]:
                     _extend_path(cpn_obj.output("_next"))
-                elif cpn_obj.component_name.lower() == "iteration":
+                elif cpn_obj.component_name.lower() in ("iteration", "loop"):
                     _append_path(cpn_obj.get_start())
+                elif cpn_obj.component_name.lower() == "exitloop" and cpn_obj.get_parent().component_name.lower() == "loop":
+                    _extend_path(self.get_component(cpn["parent_id"])["downstream"])
                 elif not cpn["downstream"] and cpn_obj.get_parent():
                     _append_path(cpn_obj.get_parent().get_start())
                 else:
@@ -561,6 +655,50 @@ class Canvas(Graph):
             return False
         return True
 
+
+    def tts(self,tts_mdl, text):
+        def clean_tts_text(text: str) -> str:
+            if not text:
+                return ""
+
+            text = text.encode("utf-8", "ignore").decode("utf-8", "ignore")
+
+            text = re.sub(r"[\x00-\x08\x0B-\x0C\x0E-\x1F\x7F]", "", text)
+
+            emoji_pattern = re.compile(
+                "[\U0001F600-\U0001F64F"
+                "\U0001F300-\U0001F5FF"
+                "\U0001F680-\U0001F6FF"
+                "\U0001F1E0-\U0001F1FF"
+                "\U00002700-\U000027BF"
+                "\U0001F900-\U0001F9FF"
+                "\U0001FA70-\U0001FAFF"
+                "\U0001FAD0-\U0001FAFF]+",
+                flags=re.UNICODE
+            )
+            text = emoji_pattern.sub("", text)
+
+            text = re.sub(r"\s+", " ", text).strip()
+
+            MAX_LEN = 500
+            if len(text) > MAX_LEN:
+                text = text[:MAX_LEN]
+
+            return text
+        if not tts_mdl or not text:
+            return None
+        text = clean_tts_text(text)
+        if not text:
+            return None
+        bin = b""
+        try:
+            for chunk in tts_mdl.tts(text):
+                bin += chunk
+        except Exception as e:
+            logging.error(f"TTS failed: {e}, text={text!r}")
+            return None
+        return binascii.hexlify(bin).decode("utf-8")
+
     def get_history(self, window_size):
         convs = []
         if window_size <= 0:
@@ -590,21 +728,30 @@ class Canvas(Graph):
     def get_component_input_elements(self, cpnnm):
         return self.components[cpnnm]["obj"].get_input_elements()
 
-    def get_files(self, files: Union[None, list[dict]]) -> list[str]:
+    async def get_files_async(self, files: Union[None, list[dict]]) -> list[str]:
-        from api.db.services.file_service import FileService
         if not files:
             return  []
         def image_to_base64(file):
             return "data:{};base64,{}".format(file["mime_type"],
                                         base64.b64encode(FileService.get_blob(file["created_by"], file["id"])).decode("utf-8"))
-        exe = ThreadPoolExecutor(max_workers=5)
+        loop = asyncio.get_running_loop()
-        threads = []
+        tasks = []
         for file in files:
             if file["mime_type"].find("image") >=0:
-                threads.append(exe.submit(image_to_base64, file))
+                tasks.append(loop.run_in_executor(self._thread_pool, image_to_base64, file))
                 continue
-            threads.append(exe.submit(FileService.parse, file["name"], FileService.get_blob(file["created_by"], file["id"]), True, file["created_by"]))
+            tasks.append(loop.run_in_executor(self._thread_pool, FileService.parse, file["name"], FileService.get_blob(file["created_by"], file["id"]), True, file["created_by"]))
-        return [th.result() for th in threads]
+        return await asyncio.gather(*tasks)
+
+    def get_files(self, files: Union[None, list[dict]]) -> list[str]:
+        """
+        Synchronous wrapper for get_files_async, used by sync component invoke paths.
+        """
+        loop = getattr(self, "_loop", None)
+        if loop and loop.is_running():
+            return asyncio.run_coroutine_threadsafe(self.get_files_async(files), loop).result()
+
+        return asyncio.run(self.get_files_async(files))
 
     def tool_use_callback(self, agent_id: str, func_name: str, params: dict, result: Any, elapsed_time=None):
         agent_ids = agent_id.split("-->")

agent/component/agent_with_tools.py

@@ -13,10 +13,11 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
+import json
 import logging
 import os
 import re
-from concurrent.futures import ThreadPoolExecutor
 from copy import deepcopy
 from functools import partial
 from typing import Any
@@ -28,8 +29,8 @@ from api.db.services.llm_service import LLMBundle
 from api.db.services.tenant_llm_service import TenantLLMService
 from api.db.services.mcp_server_service import MCPServerService
 from common.connection_utils import timeout
-from rag.prompts.generator import next_step, COMPLETE_TASK, analyze_task, \
+from rag.prompts.generator import next_step_async, COMPLETE_TASK, analyze_task_async, \
-    citation_prompt, reflect, rank_memories, kb_prompt, citation_plus, full_question, message_fit_in
+    citation_prompt, reflect_async, kb_prompt, citation_plus, full_question, message_fit_in, structured_output_prompt
 from common.mcp_tool_call_conn import MCPToolCallSession, mcp_tool_metadata_to_openai_tool
 from agent.component.llm import LLMParam, LLM
 
@@ -137,8 +138,34 @@ class Agent(LLM, ToolBase):
             res.update(cpn.get_input_form())
         return res
 
-    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 20*60)))
+    def _get_output_schema(self):
+        try:
+            cand = self._param.outputs.get("structured")
+        except Exception:
+            return None
+
+        if isinstance(cand, dict):
+            if isinstance(cand.get("properties"), dict) and len(cand["properties"]) > 0:
+                return cand
+            for k in ("schema", "structured"):
+                if isinstance(cand.get(k), dict) and isinstance(cand[k].get("properties"), dict) and len(cand[k]["properties"]) > 0:
+                    return cand[k]
+
+        return None
+
+    async def _force_format_to_schema_async(self, text: str, schema_prompt: str) -> str:
+        fmt_msgs = [
+            {"role": "system", "content": schema_prompt + "\nIMPORTANT: Output ONLY valid JSON. No markdown, no extra text."},
+            {"role": "user", "content": text},
+        ]
+        _, fmt_msgs = message_fit_in(fmt_msgs, int(self.chat_mdl.max_length * 0.97))
+        return await self._generate_async(fmt_msgs)
+
     def _invoke(self, **kwargs):
+        return asyncio.run(self._invoke_async(**kwargs))
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 20*60)))
+    async def _invoke_async(self, **kwargs):
         if self.check_if_canceled("Agent processing"):
             return
 
@@ -157,20 +184,25 @@ class Agent(LLM, ToolBase):
         if not self.tools:
             if self.check_if_canceled("Agent processing"):
                 return
-            return LLM._invoke(self, **kwargs)
+            return await LLM._invoke_async(self, **kwargs)
 
         prompt, msg, user_defined_prompt = self._prepare_prompt_variables()
+        output_schema = self._get_output_schema()
+        schema_prompt = ""
+        if output_schema:
+            schema = json.dumps(output_schema, ensure_ascii=False, indent=2)
+            schema_prompt = structured_output_prompt(schema)
 
         downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
         ex = self.exception_handler()
-        if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not (ex and ex["goto"]):
+        if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not (ex and ex["goto"]) and not output_schema:
-            self.set_output("content", partial(self.stream_output_with_tools, prompt, msg, user_defined_prompt))
+            self.set_output("content", partial(self.stream_output_with_tools_async, prompt, deepcopy(msg), user_defined_prompt))
             return
 
         _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
         use_tools = []
         ans = ""
-        for delta_ans, tk in self._react_with_tools_streamly(prompt, msg, use_tools, user_defined_prompt):
+        async for delta_ans, _tk in self._react_with_tools_streamly_async(prompt, msg, use_tools, user_defined_prompt,schema_prompt=schema_prompt):
             if self.check_if_canceled("Agent processing"):
                 return
             ans += delta_ans
@@ -183,16 +215,38 @@ class Agent(LLM, ToolBase):
                 self.set_output("_ERROR", ans)
             return
 
+        if output_schema:
+            error = ""
+            for _ in range(self._param.max_retries + 1):
+                try:
+                    def clean_formated_answer(ans: str) -> str:
+                        ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
+                        ans = re.sub(r"^.*```json", "", ans, flags=re.DOTALL)
+                        return re.sub(r"```\n*$", "", ans, flags=re.DOTALL)
+                    obj = json_repair.loads(clean_formated_answer(ans))
+                    self.set_output("structured", obj)
+                    if use_tools:
+                        self.set_output("use_tools", use_tools)
+                    return obj
+                except Exception:
+                    error = "The answer cannot be parsed as JSON"
+                    ans = await self._force_format_to_schema_async(ans, schema_prompt)
+                    if ans.find("**ERROR**") >= 0:
+                        continue
+
+            self.set_output("_ERROR", error)
+            return
+
         self.set_output("content", ans)
         if use_tools:
             self.set_output("use_tools", use_tools)
         return ans
 
-    def stream_output_with_tools(self, prompt, msg, user_defined_prompt={}):
+    async def stream_output_with_tools_async(self, prompt, msg, user_defined_prompt={}):
         _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
         answer_without_toolcall = ""
         use_tools = []
-        for delta_ans,_ in self._react_with_tools_streamly(prompt, msg, use_tools, user_defined_prompt):
+        async for delta_ans, _ in self._react_with_tools_streamly_async(prompt, msg, use_tools, user_defined_prompt):
             if self.check_if_canceled("Agent streaming"):
                 return
 
@@ -210,39 +264,23 @@ class Agent(LLM, ToolBase):
         if use_tools:
             self.set_output("use_tools", use_tools)
 
-    def _gen_citations(self, text):
+    async def _react_with_tools_streamly_async(self, prompt, history: list[dict], use_tools, user_defined_prompt={}, schema_prompt: str = ""):
-        retrievals = self._canvas.get_reference()
-        retrievals = {"chunks": list(retrievals["chunks"].values()), "doc_aggs": list(retrievals["doc_aggs"].values())}
-        formated_refer = kb_prompt(retrievals, self.chat_mdl.max_length, True)
-        for delta_ans in self._generate_streamly([{"role": "system", "content": citation_plus("\n\n".join(formated_refer))},
-                                                  {"role": "user", "content": text}
-                                                  ]):
-            yield delta_ans
-
-    def _react_with_tools_streamly(self, prompt, history: list[dict], use_tools, user_defined_prompt={}):
         token_count = 0
         tool_metas = self.tool_meta
         hist = deepcopy(history)
         last_calling = ""
         if len(hist) > 3:
             st = timer()
-            user_request = full_question(messages=history, chat_mdl=self.chat_mdl)
+            user_request = await full_question(messages=history, chat_mdl=self.chat_mdl)
             self.callback("Multi-turn conversation optimization", {}, user_request, elapsed_time=timer()-st)
         else:
             user_request = history[-1]["content"]
 
-        def use_tool(name, args):
+        async def use_tool_async(name, args):
-            nonlocal hist, use_tools, token_count,last_calling,user_request
+            nonlocal hist, use_tools, last_calling
             logging.info(f"{last_calling=} == {name=}")
-            # Summarize of function calling
-            #if all([
-            #    isinstance(self.toolcall_session.get_tool_obj(name), Agent),
-            #    last_calling,
-            #    last_calling != name
-            #]):
-            #    self.toolcall_session.get_tool_obj(name).add2system_prompt(f"The chat history with other agents are as following: \n" + self.get_useful_memory(user_request, str(args["user_prompt"]),user_defined_prompt))
             last_calling = name
-            tool_response = self.toolcall_session.tool_call(name, args)
+            tool_response = await self.toolcall_session.tool_call_async(name, args)
             use_tools.append({
                 "name": name,
                 "arguments": args,
@@ -253,12 +291,16 @@ class Agent(LLM, ToolBase):
 
             return name, tool_response
 
-        def complete():
+        async def complete():
             nonlocal hist
             need2cite = self._param.cite and self._canvas.get_reference()["chunks"] and self._id.find("-->") < 0
+            if schema_prompt:
+                need2cite = False
             cited = False
-            if hist[0]["role"] == "system" and need2cite:
+            if hist and hist[0]["role"] == "system":
-                if len(hist) < 7:
+                if schema_prompt:
+                    hist[0]["content"] += "\n" + schema_prompt
+                if need2cite and len(hist) < 7:
                     hist[0]["content"] += citation_prompt()
                     cited = True
             yield "", token_count
@@ -267,7 +309,7 @@ class Agent(LLM, ToolBase):
             if len(hist) > 12:
                 _hist = [hist[0], hist[1], *hist[-10:]]
             entire_txt = ""
-            for delta_ans in self._generate_streamly(_hist):
+            async for delta_ans in self._generate_streamly(_hist):
                 if not need2cite or cited:
                     yield delta_ans, 0
                 entire_txt += delta_ans
@@ -276,7 +318,7 @@ class Agent(LLM, ToolBase):
 
             st = timer()
             txt = ""
-            for delta_ans in self._gen_citations(entire_txt):
+            async for delta_ans in self._gen_citations_async(entire_txt):
                 if self.check_if_canceled("Agent streaming"):
                     return
                 yield delta_ans, 0
@@ -291,14 +333,14 @@ class Agent(LLM, ToolBase):
                 hist.append({"role": "user", "content": content})
 
         st = timer()
-        task_desc = analyze_task(self.chat_mdl, prompt, user_request, tool_metas, user_defined_prompt)
+        task_desc = await analyze_task_async(self.chat_mdl, prompt, user_request, tool_metas, user_defined_prompt)
         self.callback("analyze_task", {}, task_desc, elapsed_time=timer()-st)
         for _ in range(self._param.max_rounds + 1):
             if self.check_if_canceled("Agent streaming"):
                 return
-            response, tk = next_step(self.chat_mdl, hist, tool_metas, task_desc, user_defined_prompt)
+            response, tk = await next_step_async(self.chat_mdl, hist, tool_metas, task_desc, user_defined_prompt)
             # self.callback("next_step", {}, str(response)[:256]+"...")
-            token_count += tk
+            token_count += tk or 0
             hist.append({"role": "assistant", "content": response})
             try:
                 functions = json_repair.loads(re.sub(r"```.*", "", response))
@@ -307,21 +349,22 @@ class Agent(LLM, ToolBase):
                 for f in functions:
                     if not isinstance(f, dict):
                         raise TypeError(f"An object type should be returned, but `{f}`")
-                with ThreadPoolExecutor(max_workers=5) as executor:
+
-                    thr = []
+                tool_tasks = []
                 for func in functions:
                     name = func["name"]
                     args = func["arguments"]
                     if name == COMPLETE_TASK:
                         append_user_content(hist, f"Respond with a formal answer. FORGET(DO NOT mention) about `{COMPLETE_TASK}`. The language for the response MUST be as the same as the first user request.\n")
-                            for txt, tkcnt in complete():
+                        async for txt, tkcnt in complete():
                             yield txt, tkcnt
                         return
 
-                        thr.append(executor.submit(use_tool, name, args))
+                    tool_tasks.append(asyncio.create_task(use_tool_async(name, args)))
 
+                results = await asyncio.gather(*tool_tasks) if tool_tasks else []
                 st = timer()
-                    reflection = reflect(self.chat_mdl, hist, [th.result() for th in thr], user_defined_prompt)
+                reflection = await reflect_async(self.chat_mdl, hist, results, user_defined_prompt)
                 append_user_content(hist, reflection)
                 self.callback("reflection", {}, str(reflection), elapsed_time=timer()-st)
 
@@ -347,21 +390,17 @@ Respond immediately with your final comprehensive answer.
             return
         append_user_content(hist, final_instruction)
 
-        for txt, tkcnt in complete():
+        async for txt, tkcnt in complete():
             yield txt, tkcnt
 
-    def get_useful_memory(self, goal: str, sub_goal:str, topn=3, user_defined_prompt:dict={}) -> str:
+    async def _gen_citations_async(self, text):
-        # self.callback("get_useful_memory", {"topn": 3}, "...")
+        retrievals = self._canvas.get_reference()
-        mems = self._canvas.get_memory()
+        retrievals = {"chunks": list(retrievals["chunks"].values()), "doc_aggs": list(retrievals["doc_aggs"].values())}
-        rank = rank_memories(self.chat_mdl, goal, sub_goal, [summ for (user, assist, summ) in mems], user_defined_prompt)
+        formated_refer = kb_prompt(retrievals, self.chat_mdl.max_length, True)
-        try:
+        async for delta_ans in self._generate_streamly([{"role": "system", "content": citation_plus("\n\n".join(formated_refer))},
-            rank = json_repair.loads(re.sub(r"```.*", "", rank))[:topn]
+                                                  {"role": "user", "content": text}
-            mems = [mems[r] for r in rank]
+                                                  ]):
-            return "\n\n".join([f"User: {u}\nAgent: {a}" for u, a,_ in mems])
+            yield delta_ans
-        except Exception as e:
-            logging.exception(e)
-
-        return "Error occurred."
 
     def reset(self, only_output=False):
         """
@@ -378,4 +417,3 @@ Respond immediately with your final comprehensive answer.
         for k in self._param.inputs.keys():
             self._param.inputs[k]["value"] = None
         self._param.debug_inputs = {}
-

agent/component/base.py

@@ -14,6 +14,7 @@
 #  limitations under the License.
 #
 
+import asyncio
 import re
 import time
 from abc import ABC
@@ -23,11 +24,9 @@ import os
 import logging
 from typing import Any, List, Union
 import pandas as pd
-import trio
 from agent import settings
 from common.connection_utils import timeout
 
-
 _FEEDED_DEPRECATED_PARAMS = "_feeded_deprecated_params"
 _DEPRECATED_PARAMS = "_deprecated_params"
 _USER_FEEDED_PARAMS = "_user_feeded_params"
@@ -253,96 +252,65 @@ class ComponentParamBase(ABC):
                 self._validate_param(attr, validation_json)
 
     @staticmethod
-    def check_string(param, descr):
+    def check_string(param, description):
         if type(param).__name__ not in ["str"]:
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be string type".format(param))
-                descr + " {} not supported, should be string type".format(param)
-            )
 
     @staticmethod
-    def check_empty(param, descr):
+    def check_empty(param, description):
         if not param:
-            raise ValueError(
+            raise ValueError(description + " does not support empty value.")
-                descr + " does not support empty value."
-            )
 
     @staticmethod
-    def check_positive_integer(param, descr):
+    def check_positive_integer(param, description):
         if type(param).__name__ not in ["int", "long"] or param <= 0:
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be positive integer".format(param))
-                descr + " {} not supported, should be positive integer".format(param)
-            )
 
     @staticmethod
-    def check_positive_number(param, descr):
+    def check_positive_number(param, description):
         if type(param).__name__ not in ["float", "int", "long"] or param <= 0:
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be positive numeric".format(param))
-                descr + " {} not supported, should be positive numeric".format(param)
-            )
 
     @staticmethod
-    def check_nonnegative_number(param, descr):
+    def check_nonnegative_number(param, description):
         if type(param).__name__ not in ["float", "int", "long"] or param < 0:
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be non-negative numeric".format(param))
-                descr
-                + " {} not supported, should be non-negative numeric".format(param)
-            )
 
     @staticmethod
-    def check_decimal_float(param, descr):
+    def check_decimal_float(param, description):
         if type(param).__name__ not in ["float", "int"] or param < 0 or param > 1:
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be a float number in range [0, 1]".format(param))
-                descr
-                + " {} not supported, should be a float number in range [0, 1]".format(
-                    param
-                )
-            )
 
     @staticmethod
-    def check_boolean(param, descr):
+    def check_boolean(param, description):
         if type(param).__name__ != "bool":
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be bool type".format(param))
-                descr + " {} not supported, should be bool type".format(param)
-            )
 
     @staticmethod
-    def check_open_unit_interval(param, descr):
+    def check_open_unit_interval(param, description):
         if type(param).__name__ not in ["float"] or param <= 0 or param >= 1:
-            raise ValueError(
+            raise ValueError(description + " should be a numeric number between 0 and 1 exclusively")
-                descr + " should be a numeric number between 0 and 1 exclusively"
-            )
 
     @staticmethod
-    def check_valid_value(param, descr, valid_values):
+    def check_valid_value(param, description, valid_values):
         if param not in valid_values:
-            raise ValueError(
+            raise ValueError(description + " {} is not supported, it should be in {}".format(param, valid_values))
-                descr
-                + " {} is not supported, it should be in {}".format(param, valid_values)
-            )
 
     @staticmethod
-    def check_defined_type(param, descr, types):
+    def check_defined_type(param, description, types):
         if type(param).__name__ not in types:
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be one of {}".format(param, types))
-                descr + " {} not supported, should be one of {}".format(param, types)
-            )
 
     @staticmethod
-    def check_and_change_lower(param, valid_list, descr=""):
+    def check_and_change_lower(param, valid_list, description=""):
         if type(param).__name__ != "str":
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be one of {}".format(param, valid_list))
-                descr
-                + " {} not supported, should be one of {}".format(param, valid_list)
-            )
 
         lower_param = param.lower()
         if lower_param in valid_list:
             return lower_param
         else:
-            raise ValueError(
+            raise ValueError(description + " {} not supported, should be one of {}".format(param, valid_list))
-                descr
-                + " {} not supported, should be one of {}".format(param, valid_list)
-            )
 
     @staticmethod
     def _greater_equal_than(value, limit):
@@ -374,16 +342,16 @@ class ComponentParamBase(ABC):
     def _not_in(value, wrong_value_list):
         return value not in wrong_value_list
 
-    def _warn_deprecated_param(self, param_name, descr):
+    def _warn_deprecated_param(self, param_name, description):
         if self._deprecated_params_set.get(param_name):
             logging.warning(
-                f"{descr} {param_name} is deprecated and ignored in this version."
+                f"{description} {param_name} is deprecated and ignored in this version."
             )
 
-    def _warn_to_deprecate_param(self, param_name, descr, new_param):
+    def _warn_to_deprecate_param(self, param_name, description, new_param):
         if self._deprecated_params_set.get(param_name):
             logging.warning(
-                f"{descr} {param_name} will be deprecated in future release; "
+                f"{description} {param_name} will be deprecated in future release; "
                 f"please use {new_param} instead."
             )
             return True
@@ -392,8 +360,8 @@ class ComponentParamBase(ABC):
 
 class ComponentBase(ABC):
     component_name: str
-    thread_limiter = trio.CapacityLimiter(int(os.environ.get('MAX_CONCURRENT_CHATS', 10)))
+    thread_limiter = asyncio.Semaphore(int(os.environ.get("MAX_CONCURRENT_CHATS", 10)))
-    variable_ref_patt = r"\{* *\{([a-zA-Z:0-9]+@[A-Za-z0-9_.]+|sys\.[A-Za-z0-9_.]+|env\.[A-Za-z0-9_.]+)\} *\}*"
+    variable_ref_patt = r"\{* *\{([a-zA-Z:0-9]+@[A-Za-z0-9_.-]+|sys\.[A-Za-z0-9_.]+|env\.[A-Za-z0-9_.]+)\} *\}*"
 
     def __str__(self):
         """
@@ -445,6 +413,34 @@ class ComponentBase(ABC):
         self.set_output("_elapsed_time", time.perf_counter() - self.output("_created_time"))
         return self.output()
 
+    async def invoke_async(self, **kwargs) -> dict[str, Any]:
+        """
+        Async wrapper for component invocation.
+        Prefers coroutine `_invoke_async` if present; otherwise falls back to `_invoke`.
+        Handles timing and error recording consistently with `invoke`.
+        """
+        self.set_output("_created_time", time.perf_counter())
+        try:
+            if self.check_if_canceled("Component processing"):
+                return
+
+            fn_async = getattr(self, "_invoke_async", None)
+            if fn_async and asyncio.iscoroutinefunction(fn_async):
+                await fn_async(**kwargs)
+            elif asyncio.iscoroutinefunction(self._invoke):
+                await self._invoke(**kwargs)
+            else:
+                await asyncio.to_thread(self._invoke, **kwargs)
+        except Exception as e:
+            if self.get_exception_default_value():
+                self.set_exception_default_value()
+            else:
+                self.set_output("_ERROR", str(e))
+            logging.exception(e)
+        self._param.debug_inputs = {}
+        self.set_output("_elapsed_time", time.perf_counter() - self.output("_created_time"))
+        return self.output()
+
     @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10 * 60)))
     def _invoke(self, **kwargs):
         raise NotImplementedError()
@@ -504,7 +500,7 @@ class ComponentBase(ABC):
             res[exp] = {
                 "name": (self._canvas.get_component_name(cpn_id) + f"@{var_nm}") if cpn_id else exp,
                 "value": self._canvas.get_variable_value(exp),
-                "_retrival": self._canvas.get_variable_value(f"{cpn_id}@_references") if cpn_id else None,
+                "_retrieval": self._canvas.get_variable_value(f"{cpn_id}@_references") if cpn_id else None,
                 "_cpn_id": cpn_id
             }
         return res
@@ -555,6 +551,7 @@ class ComponentBase(ABC):
         for n, v in kv.items():
             def repl(_match, val=v):
                 return str(val) if val is not None else ""
+
             content = re.sub(
                 r"\{%s\}" % re.escape(n),
                 repl,

agent/component/begin.py

@@ -14,6 +14,7 @@
 #  limitations under the License.
 #
 from agent.component.fillup import UserFillUpParam, UserFillUp
+from api.db.services.file_service import FileService
 
 
 class BeginParam(UserFillUpParam):
@@ -27,7 +28,7 @@ class BeginParam(UserFillUpParam):
         self.prologue = "Hi! I'm your smart assistant. What can I do for you?"
 
     def check(self):
-        self.check_valid_value(self.mode, "The 'mode' should be either `conversational` or `task`", ["conversational", "task"])
+        self.check_valid_value(self.mode, "The 'mode' should be either `conversational` or `task`", ["conversational", "task","Webhook"])
 
     def get_input_form(self) -> dict[str, dict]:
         return getattr(self, "inputs")
@@ -48,7 +49,7 @@ class Begin(UserFillUp):
                 if v.get("optional") and v.get("value", None) is None:
                     v = None
                 else:
-                    v = self._canvas.get_files([v["value"]])
+                    v = FileService.get_files([v["value"]])
             else:
                 v = v.get("value")
             self.set_output(k, v)

agent/component/categorize.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
 import logging
 import os
 import re
@@ -97,7 +98,7 @@ class Categorize(LLM, ABC):
     component_name = "Categorize"
 
     @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60)))
-    def _invoke(self, **kwargs):
+    async def _invoke_async(self, **kwargs):
         if self.check_if_canceled("Categorize processing"):
             return
 
@@ -121,7 +122,7 @@ class Categorize(LLM, ABC):
         if self.check_if_canceled("Categorize processing"):
             return
 
-        ans = chat_mdl.chat(self._param.sys_prompt, [{"role": "user", "content": user_prompt}], self._param.gen_conf())
+        ans = await chat_mdl.async_chat(self._param.sys_prompt, [{"role": "user", "content": user_prompt}], self._param.gen_conf())
         logging.info(f"input: {user_prompt}, answer: {str(ans)}")
         if ERROR_PREFIX in ans:
             raise Exception(ans)
@@ -144,5 +145,9 @@ class Categorize(LLM, ABC):
         self.set_output("category_name", max_category)
         self.set_output("_next", cpn_ids)
 
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60)))
+    def _invoke(self, **kwargs):
+        return asyncio.run(self._invoke_async(**kwargs))
+
     def thoughts(self) -> str:
         return "Which should it falls into {}? ...".format(",".join([f"`{c}`" for c, _ in self._param.category_description.items()]))

agent/component/excel_processor.py

@@ -0,0 +1,401 @@
+#
+#  Copyright 2025 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.
+#
+
+"""
+ExcelProcessor Component
+
+A component for reading, processing, and generating Excel files in RAGFlow agents.
+Supports multiple Excel file inputs, data transformation, and Excel output generation.
+"""
+
+import logging
+import os
+from abc import ABC
+from io import BytesIO
+
+import pandas as pd
+
+from agent.component.base import ComponentBase, ComponentParamBase
+from api.db.services.file_service import FileService
+from api.utils.api_utils import timeout
+from common import settings
+from common.misc_utils import get_uuid
+
+
+class ExcelProcessorParam(ComponentParamBase):
+    """
+    Define the ExcelProcessor component parameters.
+    """
+    def __init__(self):
+        super().__init__()
+        # Input configuration
+        self.input_files = []  # Variable references to uploaded files
+        self.operation = "read"  # read, merge, transform, output
+        
+        # Processing options
+        self.sheet_selection = "all"  # all, first, or comma-separated sheet names
+        self.merge_strategy = "concat"  # concat, join
+        self.join_on = ""  # Column name for join operations
+        
+        # Transform options (for LLM-guided transformations)
+        self.transform_instructions = ""
+        self.transform_data = ""  # Variable reference to transformation data
+        
+        # Output options
+        self.output_format = "xlsx"  # xlsx, csv
+        self.output_filename = "output"
+        
+        # Component outputs
+        self.outputs = {
+            "data": {
+                "type": "object",
+                "value": {}
+            },
+            "summary": {
+                "type": "str",
+                "value": ""
+            },
+            "markdown": {
+                "type": "str",
+                "value": ""
+            }
+        }
+    
+    def check(self):
+        self.check_valid_value(
+            self.operation, 
+            "[ExcelProcessor] Operation", 
+            ["read", "merge", "transform", "output"]
+        )
+        self.check_valid_value(
+            self.output_format,
+            "[ExcelProcessor] Output format",
+            ["xlsx", "csv"]
+        )
+        return True
+
+
+class ExcelProcessor(ComponentBase, ABC):
+    """
+    Excel processing component for RAGFlow agents.
+    
+    Operations:
+    - read: Parse Excel files into structured data
+    - merge: Combine multiple Excel files
+    - transform: Apply data transformations based on instructions
+    - output: Generate Excel file output
+    """
+    component_name = "ExcelProcessor"
+
+    def get_input_form(self) -> dict[str, dict]:
+        """Define input form for the component."""
+        res = {}
+        for ref in (self._param.input_files or []):
+            for k, o in self.get_input_elements_from_text(ref).items():
+                res[k] = {"name": o.get("name", ""), "type": "file"}
+        if self._param.transform_data:
+            for k, o in self.get_input_elements_from_text(self._param.transform_data).items():
+                res[k] = {"name": o.get("name", ""), "type": "object"}
+        return res
+
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60)))
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("ExcelProcessor processing"):
+            return
+
+        operation = self._param.operation.lower()
+        
+        if operation == "read":
+            self._read_excels()
+        elif operation == "merge":
+            self._merge_excels()
+        elif operation == "transform":
+            self._transform_data()
+        elif operation == "output":
+            self._output_excel()
+        else:
+            self.set_output("summary", f"Unknown operation: {operation}")
+
+    def _get_file_content(self, file_ref: str) -> tuple[bytes, str]:
+        """
+        Get file content from a variable reference.
+        Returns (content_bytes, filename).
+        """
+        value = self._canvas.get_variable_value(file_ref)
+        if value is None:
+            return None, None
+            
+        # Handle different value formats
+        if isinstance(value, dict):
+            # File reference from Begin/UserFillUp component
+            file_id = value.get("id") or value.get("file_id")
+            created_by = value.get("created_by") or self._canvas.get_tenant_id()
+            filename = value.get("name") or value.get("filename", "unknown.xlsx")
+            if file_id:
+                content = FileService.get_blob(created_by, file_id)
+                return content, filename
+        elif isinstance(value, list) and len(value) > 0:
+            # List of file references - return first
+            return self._get_file_content_from_list(value[0])
+        elif isinstance(value, str):
+            # Could be base64 encoded or a path
+            if value.startswith("data:"):
+                import base64
+                # Extract base64 content
+                _, encoded = value.split(",", 1)
+                return base64.b64decode(encoded), "uploaded.xlsx"
+                
+        return None, None
+    
+    def _get_file_content_from_list(self, item) -> tuple[bytes, str]:
+        """Extract file content from a list item."""
+        if isinstance(item, dict):
+            return self._get_file_content(item)
+        return None, None
+
+    def _parse_excel_to_dataframes(self, content: bytes, filename: str) -> dict[str, pd.DataFrame]:
+        """Parse Excel content into a dictionary of DataFrames (one per sheet)."""
+        try:
+            excel_file = BytesIO(content)
+            
+            if filename.lower().endswith(".csv"):
+                df = pd.read_csv(excel_file)
+                return {"Sheet1": df}
+            else:
+                # Read all sheets
+                xlsx = pd.ExcelFile(excel_file, engine='openpyxl')
+                sheet_selection = self._param.sheet_selection
+                
+                if sheet_selection == "all":
+                    sheets_to_read = xlsx.sheet_names
+                elif sheet_selection == "first":
+                    sheets_to_read = [xlsx.sheet_names[0]] if xlsx.sheet_names else []
+                else:
+                    # Comma-separated sheet names
+                    requested = [s.strip() for s in sheet_selection.split(",")]
+                    sheets_to_read = [s for s in requested if s in xlsx.sheet_names]
+                
+                dfs = {}
+                for sheet in sheets_to_read:
+                    dfs[sheet] = pd.read_excel(xlsx, sheet_name=sheet)
+                return dfs
+                
+        except Exception as e:
+            logging.error(f"Error parsing Excel file {filename}: {e}")
+            return {}
+
+    def _read_excels(self):
+        """Read and parse Excel files into structured data."""
+        all_data = {}
+        summaries = []
+        markdown_parts = []
+        
+        for file_ref in (self._param.input_files or []):
+            if self.check_if_canceled("ExcelProcessor reading"):
+                return
+                
+            # Get variable value
+            value = self._canvas.get_variable_value(file_ref)
+            self.set_input_value(file_ref, str(value)[:200] if value else "")
+            
+            if value is None:
+                continue
+            
+            # Handle file content
+            content, filename = self._get_file_content(file_ref)
+            if content is None:
+                continue
+                
+            # Parse Excel
+            dfs = self._parse_excel_to_dataframes(content, filename)
+            
+            for sheet_name, df in dfs.items():
+                key = f"{filename}_{sheet_name}" if len(dfs) > 1 else filename
+                all_data[key] = df.to_dict(orient="records")
+                
+                # Build summary
+                summaries.append(f"**{key}**: {len(df)} rows, {len(df.columns)} columns ({', '.join(df.columns.tolist()[:5])}{'...' if len(df.columns) > 5 else ''})")
+                
+                # Build markdown table
+                markdown_parts.append(f"### {key}\n\n{df.head(10).to_markdown(index=False)}\n")
+        
+        # Set outputs
+        self.set_output("data", all_data)
+        self.set_output("summary", "\n".join(summaries) if summaries else "No Excel files found")
+        self.set_output("markdown", "\n\n".join(markdown_parts) if markdown_parts else "No data")
+
+    def _merge_excels(self):
+        """Merge multiple Excel files/sheets into one."""
+        all_dfs = []
+        
+        for file_ref in (self._param.input_files or []):
+            if self.check_if_canceled("ExcelProcessor merging"):
+                return
+                
+            value = self._canvas.get_variable_value(file_ref)
+            self.set_input_value(file_ref, str(value)[:200] if value else "")
+            
+            if value is None:
+                continue
+                
+            content, filename = self._get_file_content(file_ref)
+            if content is None:
+                continue
+                
+            dfs = self._parse_excel_to_dataframes(content, filename)
+            all_dfs.extend(dfs.values())
+        
+        if not all_dfs:
+            self.set_output("data", {})
+            self.set_output("summary", "No data to merge")
+            return
+        
+        # Merge strategy
+        if self._param.merge_strategy == "concat":
+            merged_df = pd.concat(all_dfs, ignore_index=True)
+        elif self._param.merge_strategy == "join" and self._param.join_on:
+            # Join on specified column
+            merged_df = all_dfs[0]
+            for df in all_dfs[1:]:
+                merged_df = merged_df.merge(df, on=self._param.join_on, how="outer")
+        else:
+            merged_df = pd.concat(all_dfs, ignore_index=True)
+        
+        self.set_output("data", {"merged": merged_df.to_dict(orient="records")})
+        self.set_output("summary", f"Merged {len(all_dfs)} sources into {len(merged_df)} rows, {len(merged_df.columns)} columns")
+        self.set_output("markdown", merged_df.head(20).to_markdown(index=False))
+
+    def _transform_data(self):
+        """Apply transformations to data based on instructions or input data."""
+        # Get the data to transform
+        transform_ref = self._param.transform_data
+        if not transform_ref:
+            self.set_output("summary", "No transform data reference provided")
+            return
+            
+        data = self._canvas.get_variable_value(transform_ref)
+        self.set_input_value(transform_ref, str(data)[:300] if data else "")
+        
+        if data is None:
+            self.set_output("summary", "Transform data is empty")
+            return
+        
+        # Convert to DataFrame
+        if isinstance(data, dict):
+            # Could be {"sheet": [rows]} format
+            if all(isinstance(v, list) for v in data.values()):
+                # Multiple sheets
+                all_markdown = []
+                for sheet_name, rows in data.items():
+                    df = pd.DataFrame(rows)
+                    all_markdown.append(f"### {sheet_name}\n\n{df.to_markdown(index=False)}")
+                self.set_output("data", data)
+                self.set_output("markdown", "\n\n".join(all_markdown))
+            else:
+                df = pd.DataFrame([data])
+                self.set_output("data", df.to_dict(orient="records"))
+                self.set_output("markdown", df.to_markdown(index=False))
+        elif isinstance(data, list):
+            df = pd.DataFrame(data)
+            self.set_output("data", df.to_dict(orient="records"))
+            self.set_output("markdown", df.to_markdown(index=False))
+        else:
+            self.set_output("data", {"raw": str(data)})
+            self.set_output("markdown", str(data))
+        
+        self.set_output("summary", "Transformed data ready for processing")
+
+    def _output_excel(self):
+        """Generate Excel file output from data."""
+        # Get data from transform_data reference
+        transform_ref = self._param.transform_data
+        if not transform_ref:
+            self.set_output("summary", "No data reference for output")
+            return
+            
+        data = self._canvas.get_variable_value(transform_ref)
+        self.set_input_value(transform_ref, str(data)[:300] if data else "")
+        
+        if data is None:
+            self.set_output("summary", "No data to output")
+            return
+        
+        try:
+            # Prepare DataFrames
+            if isinstance(data, dict):
+                if all(isinstance(v, list) for v in data.values()):
+                    # Multi-sheet format
+                    dfs = {k: pd.DataFrame(v) for k, v in data.items()}
+                else:
+                    dfs = {"Sheet1": pd.DataFrame([data])}
+            elif isinstance(data, list):
+                dfs = {"Sheet1": pd.DataFrame(data)}
+            else:
+                self.set_output("summary", "Invalid data format for Excel output")
+                return
+            
+            # Generate output
+            doc_id = get_uuid()
+            
+            if self._param.output_format == "csv":
+                # For CSV, only output first sheet
+                first_df = list(dfs.values())[0]
+                binary_content = first_df.to_csv(index=False).encode("utf-8")
+                filename = f"{self._param.output_filename}.csv"
+            else:
+                # Excel output
+                excel_io = BytesIO()
+                with pd.ExcelWriter(excel_io, engine='openpyxl') as writer:
+                    for sheet_name, df in dfs.items():
+                        # Sanitize sheet name (max 31 chars, no special chars)
+                        safe_name = sheet_name[:31].replace("/", "_").replace("\\", "_")
+                        df.to_excel(writer, sheet_name=safe_name, index=False)
+                excel_io.seek(0)
+                binary_content = excel_io.read()
+                filename = f"{self._param.output_filename}.xlsx"
+            
+            # Store file
+            settings.STORAGE_IMPL.put(self._canvas._tenant_id, doc_id, binary_content)
+            
+            # Set attachment output
+            self.set_output("attachment", {
+                "doc_id": doc_id,
+                "format": self._param.output_format,
+                "file_name": filename
+            })
+            
+            total_rows = sum(len(df) for df in dfs.values())
+            self.set_output("summary", f"Generated {filename} with {len(dfs)} sheet(s), {total_rows} total rows")
+            self.set_output("data", {k: v.to_dict(orient="records") for k, v in dfs.items()})
+            
+            logging.info(f"ExcelProcessor: Generated {filename} as {doc_id}")
+            
+        except Exception as e:
+            logging.error(f"ExcelProcessor output error: {e}")
+            self.set_output("summary", f"Error generating output: {str(e)}")
+
+    def thoughts(self) -> str:
+        """Return component thoughts for UI display."""
+        op = self._param.operation
+        if op == "read":
+            return "Reading Excel files..."
+        elif op == "merge":
+            return "Merging Excel data..."
+        elif op == "transform":
+            return "Transforming data..."
+        elif op == "output":
+            return "Generating Excel output..."
+        return "Processing Excel..."

agent/component/exit_loop.py

@@ -13,23 +13,17 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-from agent.component.base import ComponentParamBase, ComponentBase
+from abc import ABC
+from agent.component.base import ComponentBase, ComponentParamBase
 
 
-class WebhookParam(ComponentParamBase):
+class ExitLoopParam(ComponentParamBase, ABC):
-
+    def check(self):
-    """
+        return True
-    Define the Begin component parameters.
-    """
-    def __init__(self):
-        super().__init__()
-
-    def get_input_form(self) -> dict[str, dict]:
-        return getattr(self, "inputs")
 
 
-class Webhook(ComponentBase):
+class ExitLoop(ComponentBase, ABC):
-    component_name = "Webhook"
+    component_name = "ExitLoop"
 
     def _invoke(self, **kwargs):
         pass

agent/component/fillup.py

@@ -18,6 +18,7 @@ import re
 from functools import partial
 
 from agent.component.base import ComponentParamBase, ComponentBase
+from api.db.services.file_service import FileService
 
 
 class UserFillUpParam(ComponentParamBase):
@@ -63,6 +64,13 @@ class UserFillUp(ComponentBase):
         for k, v in kwargs.get("inputs", {}).items():
             if self.check_if_canceled("UserFillUp processing"):
                 return
+            if isinstance(v, dict) and v.get("type", "").lower().find("file") >=0:
+                if v.get("optional") and v.get("value", None) is None:
+                    v = None
+                else:
+                    v = FileService.get_files([v["value"]])
+            else:
+                v = v.get("value")
             self.set_output(k, v)
 
     def thoughts(self) -> str:

agent/component/llm.py

@@ -13,12 +13,13 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
 import json
 import logging
 import os
 import re
 from copy import deepcopy
-from typing import Any, Generator
+from typing import Any, AsyncGenerator
 import json_repair
 from functools import partial
 from common.constants import LLMType
@@ -166,15 +167,17 @@ class LLM(ComponentBase):
             sys_prompt = re.sub(rf"<{tag}>(.*?)</{tag}>", "", sys_prompt, flags=re.DOTALL|re.IGNORECASE)
         return pts, sys_prompt
 
-    def _generate(self, msg:list[dict], **kwargs) -> str:
+    async def _generate_async(self, msg: list[dict], **kwargs) -> str:
         if not self.imgs:
-            return self.chat_mdl.chat(msg[0]["content"], msg[1:], self._param.gen_conf(), **kwargs)
+            return await self.chat_mdl.async_chat(msg[0]["content"], msg[1:], self._param.gen_conf(), **kwargs)
-        return self.chat_mdl.chat(msg[0]["content"], msg[1:], self._param.gen_conf(), images=self.imgs, **kwargs)
+        return await self.chat_mdl.async_chat(msg[0]["content"], msg[1:], self._param.gen_conf(), images=self.imgs, **kwargs)
 
-    def _generate_streamly(self, msg:list[dict], **kwargs) -> Generator[str, None, None]:
+    async def _generate_streamly(self, msg: list[dict], **kwargs) -> AsyncGenerator[str, None]:
+        async def delta_wrapper(txt_iter):
             ans = ""
             last_idx = 0
             endswith_think = False
+
             def delta(txt):
                 nonlocal ans, last_idx, endswith_think
                 delta_ans = txt[last_idx:]
@@ -198,15 +201,68 @@ class LLM(ComponentBase):
                     last_idx -= len("</think>")
                 return re.sub(r"(<think>|</think>)", "", delta_ans)
 
+            async for t in txt_iter:
+                yield delta(t)
+
         if not self.imgs:
-            for txt in self.chat_mdl.chat_streamly(msg[0]["content"], msg[1:], self._param.gen_conf(), **kwargs):
+            async for t in delta_wrapper(self.chat_mdl.async_chat_streamly(msg[0]["content"], msg[1:], self._param.gen_conf(), **kwargs)):
-                yield delta(txt)
+                yield t
+            return
+
+        async for t in delta_wrapper(self.chat_mdl.async_chat_streamly(msg[0]["content"], msg[1:], self._param.gen_conf(), images=self.imgs, **kwargs)):
+            yield t
+
+    async def _stream_output_async(self, prompt, msg):
+        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
+        answer = ""
+        last_idx = 0
+        endswith_think = False
+
+        def delta(txt):
+            nonlocal answer, last_idx, endswith_think
+            delta_ans = txt[last_idx:]
+            answer = txt
+
+            if delta_ans.find("<think>") == 0:
+                last_idx += len("<think>")
+                return "<think>"
+            elif delta_ans.find("<think>") > 0:
+                delta_ans = txt[last_idx:last_idx + delta_ans.find("<think>")]
+                last_idx += delta_ans.find("<think>")
+                return delta_ans
+            elif delta_ans.endswith("</think>"):
+                endswith_think = True
+            elif endswith_think:
+                endswith_think = False
+                return "</think>"
+
+            last_idx = len(answer)
+            if answer.endswith("</think>"):
+                last_idx -= len("</think>")
+            return re.sub(r"(<think>|</think>)", "", delta_ans)
+
+        stream_kwargs = {"images": self.imgs} if self.imgs else {}
+        async for ans in self.chat_mdl.async_chat_streamly(msg[0]["content"], msg[1:], self._param.gen_conf(), **stream_kwargs):
+            if self.check_if_canceled("LLM streaming"):
+                return
+
+            if isinstance(ans, int):
+                continue
+
+            if ans.find("**ERROR**") >= 0:
+                if self.get_exception_default_value():
+                    self.set_output("content", self.get_exception_default_value())
+                    yield self.get_exception_default_value()
                 else:
-            for txt in self.chat_mdl.chat_streamly(msg[0]["content"], msg[1:], self._param.gen_conf(), images=self.imgs, **kwargs):
+                    self.set_output("_ERROR", ans)
-                yield delta(txt)
+                return
+
+            yield delta(ans)
+
+        self.set_output("content", answer)
 
     @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60)))
-    def _invoke(self, **kwargs):
+    async def _invoke_async(self, **kwargs):
         if self.check_if_canceled("LLM processing"):
             return
 
@@ -219,20 +275,23 @@ class LLM(ComponentBase):
         error: str = ""
         output_structure = None
         try:
-            output_structure = self._param.outputs['structured']
+            output_structure = self._param.outputs["structured"]
         except Exception:
             pass
-        if output_structure and isinstance(output_structure, dict) and output_structure.get("properties"):
+        if output_structure and isinstance(output_structure, dict) and output_structure.get("properties") and len(output_structure["properties"]) > 0:
             schema = json.dumps(output_structure, ensure_ascii=False, indent=2)
-            prompt += structured_output_prompt(schema)
+            prompt_with_schema = prompt + structured_output_prompt(schema)
             for _ in range(self._param.max_retries + 1):
                 if self.check_if_canceled("LLM processing"):
                     return
 
-                _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
+                _, msg_fit = message_fit_in(
+                    [{"role": "system", "content": prompt_with_schema}, *deepcopy(msg)],
+                    int(self.chat_mdl.max_length * 0.97),
+                )
                 error = ""
-                ans = self._generate(msg)
+                ans = await self._generate_async(msg_fit)
-                msg.pop(0)
+                msg_fit.pop(0)
                 if ans.find("**ERROR**") >= 0:
                     logging.error(f"LLM response error: {ans}")
                     error = ans
@@ -241,7 +300,7 @@ class LLM(ComponentBase):
                     self.set_output("structured", json_repair.loads(clean_formated_answer(ans)))
                     return
                 except Exception:
-                    msg.append({"role": "user", "content": "The answer can't not be parsed as JSON"})
+                    msg_fit.append({"role": "user", "content": "The answer can't not be parsed as JSON"})
                     error = "The answer can't not be parsed as JSON"
             if error:
                 self.set_output("_ERROR", error)
@@ -249,18 +308,23 @@ class LLM(ComponentBase):
 
         downstreams = self._canvas.get_component(self._id)["downstream"] if self._canvas.get_component(self._id) else []
         ex = self.exception_handler()
-        if any([self._canvas.get_component_obj(cid).component_name.lower()=="message" for cid in downstreams]) and not (ex and ex["goto"]):
+        if any([self._canvas.get_component_obj(cid).component_name.lower() == "message" for cid in downstreams]) and not (
-            self.set_output("content", partial(self._stream_output, prompt, msg))
+            ex and ex["goto"]
+        ):
+            self.set_output("content", partial(self._stream_output_async, prompt, deepcopy(msg)))
             return
 
+        error = ""
         for _ in range(self._param.max_retries + 1):
             if self.check_if_canceled("LLM processing"):
                 return
 
-            _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
+            _, msg_fit = message_fit_in(
+                [{"role": "system", "content": prompt}, *deepcopy(msg)], int(self.chat_mdl.max_length * 0.97)
+            )
             error = ""
-            ans = self._generate(msg)
+            ans = await self._generate_async(msg_fit)
-            msg.pop(0)
+            msg_fit.pop(0)
             if ans.find("**ERROR**") >= 0:
                 logging.error(f"LLM response error: {ans}")
                 error = ans
@@ -274,26 +338,12 @@ class LLM(ComponentBase):
             else:
                 self.set_output("_ERROR", error)
 
-    def _stream_output(self, prompt, msg):
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 10*60)))
-        _, msg = message_fit_in([{"role": "system", "content": prompt}, *msg], int(self.chat_mdl.max_length * 0.97))
+    def _invoke(self, **kwargs):
-        answer = ""
+        return asyncio.run(self._invoke_async(**kwargs))
-        for ans in self._generate_streamly(msg):
-            if self.check_if_canceled("LLM streaming"):
-                return
 
-            if ans.find("**ERROR**") >= 0:
+    async def add_memory(self, user:str, assist:str, func_name: str, params: dict, results: str, user_defined_prompt:dict={}):
-                if self.get_exception_default_value():
+        summ = await tool_call_summary(self.chat_mdl, func_name, params, results, user_defined_prompt)
-                    self.set_output("content", self.get_exception_default_value())
-                    yield self.get_exception_default_value()
-                else:
-                    self.set_output("_ERROR", ans)
-                return
-            yield ans
-            answer += ans
-        self.set_output("content", answer)
-
-    def add_memory(self, user:str, assist:str, func_name: str, params: dict, results: str, user_defined_prompt:dict={}):
-        summ = tool_call_summary(self.chat_mdl, func_name, params, results, user_defined_prompt)
         logging.info(f"[MEMORY]: {summ}")
         self._canvas.add_memory(user, assist, summ)
 

agent/component/loop.py

@@ -0,0 +1,80 @@
+#
+#  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
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class LoopParam(ComponentParamBase):
+    """
+    Define the Loop component parameters.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self.loop_variables = []
+        self.loop_termination_condition=[]
+        self.maximum_loop_count = 0
+
+    def get_input_form(self) -> dict[str, dict]:
+        return {
+            "items": {
+                "type": "json",
+                "name": "Items"
+            }
+        }
+
+    def check(self):
+        return True
+
+
+class Loop(ComponentBase, ABC):
+    component_name = "Loop"
+
+    def get_start(self):
+        for cid in self._canvas.components.keys():
+            if self._canvas.get_component(cid)["obj"].component_name.lower() != "loopitem":
+                continue
+            if self._canvas.get_component(cid)["parent_id"] == self._id:
+                return cid
+
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("Loop processing"):
+            return
+
+        for item in self._param.loop_variables:
+            if any([not item.get("variable"), not item.get("input_mode"), not item.get("value"),not item.get("type")]):
+                assert "Loop Variable is not complete."
+            if item["input_mode"]=="variable":
+                self.set_output(item["variable"],self._canvas.get_variable_value(item["value"]))
+            elif item["input_mode"]=="constant":
+                self.set_output(item["variable"],item["value"])
+            else:
+                if item["type"] == "number":
+                    self.set_output(item["variable"], 0)
+                elif item["type"] == "string":
+                    self.set_output(item["variable"], "")
+                elif item["type"] == "boolean":
+                    self.set_output(item["variable"], False)
+                elif item["type"].startswith("object"):
+                    self.set_output(item["variable"], {})
+                elif item["type"].startswith("array"):
+                    self.set_output(item["variable"], [])
+                else:
+                    self.set_output(item["variable"], "")
+
+
+    def thoughts(self) -> str:
+        return "Loop from canvas."

agent/component/loopitem.py

@@ -0,0 +1,163 @@
+#
+#  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
+from agent.component.base import ComponentBase, ComponentParamBase
+
+
+class LoopItemParam(ComponentParamBase):
+    """
+    Define the LoopItem component parameters.
+    """
+    def check(self):
+        return True
+
+class LoopItem(ComponentBase, ABC):
+    component_name = "LoopItem"
+
+    def __init__(self, canvas, id, param: ComponentParamBase):
+        super().__init__(canvas, id, param)
+        self._idx = 0
+
+
+    def _invoke(self, **kwargs):
+        if self.check_if_canceled("LoopItem processing"):
+            return
+        parent = self.get_parent()
+        maximum_loop_count = parent._param.maximum_loop_count
+        if self._idx >= maximum_loop_count:
+            self._idx = -1
+            return
+        if self._idx > 0:
+            if self.check_if_canceled("LoopItem processing"):
+                return
+        self._idx += 1
+
+    def evaluate_condition(self,var, operator, value):
+        if isinstance(var, str):
+            if operator == "contains":
+                return value in var
+            elif operator == "not contains":
+                return value not in var
+            elif operator == "start with":
+                return var.startswith(value)
+            elif operator == "end with":
+                return var.endswith(value)
+            elif operator == "is":
+                return var == value
+            elif operator == "is not":
+                return var != value
+            elif operator == "empty":
+                return var == ""
+            elif operator == "not empty":
+                return var != ""
+
+        elif isinstance(var, (int, float)):
+            if operator == "=":
+                return var == value
+            elif operator == "≠":
+                return var != value
+            elif operator == ">":
+                return var > value
+            elif operator == "<":
+                return var < value
+            elif operator == "≥":
+                return var >= value
+            elif operator == "≤":
+                return var <= value
+            elif operator == "empty":
+                return var is None
+            elif operator == "not empty":
+                return var is not None
+
+        elif isinstance(var, bool):
+            if operator == "is":
+                return var is value
+            elif operator == "is not":
+                return var is not value
+            elif operator == "empty":
+                return var is None
+            elif operator == "not empty":
+                return var is not None
+
+        elif isinstance(var, dict):
+            if operator == "empty":
+                return len(var) == 0
+            elif operator == "not empty":
+                return len(var) > 0
+
+        elif isinstance(var, list):
+            if operator == "contains":
+                return value in var
+            elif operator == "not contains":
+                return value not in var
+
+            elif operator == "is":
+                return var == value
+            elif operator == "is not":
+                return var != value
+
+            elif operator == "empty":
+                return len(var) == 0
+            elif operator == "not empty":
+                return len(var) > 0
+
+        raise Exception(f"Invalid operator: {operator}")
+
+    def end(self):
+        if self._idx == -1:
+            return True
+        parent = self.get_parent()
+        logical_operator = parent._param.logical_operator if hasattr(parent._param, "logical_operator") else "and"
+        conditions = []
+        for item in parent._param.loop_termination_condition:
+            if not item.get("variable") or not item.get("operator"):
+                raise ValueError("Loop condition is incomplete.")
+            var = self._canvas.get_variable_value(item["variable"])
+            operator = item["operator"]
+            input_mode = item.get("input_mode", "constant")
+
+            if input_mode == "variable":
+                value = self._canvas.get_variable_value(item.get("value", ""))
+            elif input_mode == "constant":
+                value = item.get("value", "")
+            else:
+                raise ValueError("Invalid input mode.")
+            conditions.append(self.evaluate_condition(var, operator, value))
+        should_end = (
+            all(conditions) if logical_operator == "and"
+            else any(conditions) if logical_operator == "or"
+            else None
+        )
+        if should_end is None:
+            raise ValueError("Invalid logical operator,should be 'and' or 'or'.")
+
+        if should_end:
+            self._idx = -1
+            return True
+
+        return False
+
+    def next(self):
+        if self._idx == -1:
+            self._idx = 0
+        else:
+            self._idx += 1
+            if self._idx >= len(self._items):
+                self._idx = -1
+        return False
+
+    def thoughts(self) -> str:
+        return "Next turn..."

agent/component/message.py

@@ -13,6 +13,10 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
+import nest_asyncio
+nest_asyncio.apply()
+import inspect
 import json
 import os
 import random
@@ -39,6 +43,7 @@ class MessageParam(ComponentParamBase):
         self.content = []
         self.stream = True
         self.output_format = None  # default output format
+        self.auto_play = False
         self.outputs = {
             "content": {
                 "type": "str"
@@ -66,7 +71,11 @@ class Message(ComponentBase):
                 v = ""
             ans = ""
             if isinstance(v, partial):
-                for t in v():
+                iter_obj = v()
+                if inspect.isasyncgen(iter_obj):
+                    ans = asyncio.run(self._consume_async_gen(iter_obj))
+                else:
+                    for t in iter_obj:
                         ans += t
             elif isinstance(v, list) and delimiter:
                 ans = delimiter.join([str(vv) for vv in v])
@@ -89,7 +98,13 @@ class Message(ComponentBase):
             _kwargs[_n] = v
         return script, _kwargs
 
-    def _stream(self, rand_cnt:str):
+    async def _consume_async_gen(self, agen):
+        buf = ""
+        async for t in agen:
+            buf += t
+        return buf
+
+    async def _stream(self, rand_cnt:str):
         s = 0
         all_content = ""
         cache = {}
@@ -111,7 +126,17 @@ class Message(ComponentBase):
                 v = ""
             if isinstance(v, partial):
                 cnt = ""
-                for t in v():
+                iter_obj = v()
+                if inspect.isasyncgen(iter_obj):
+                    async for t in iter_obj:
+                        if self.check_if_canceled("Message streaming"):
+                            return
+
+                        all_content += t
+                        cnt += t
+                        yield t
+                else:
+                    for t in iter_obj:
                         if self.check_if_canceled("Message streaming"):
                             return
 
@@ -120,6 +145,8 @@ class Message(ComponentBase):
                         yield t
                 self.set_input_value(exp, cnt)
                 continue
+            elif inspect.isawaitable(v):
+                v = await v
             elif not isinstance(v, str):
                 try:
                     v = json.dumps(v, ensure_ascii=False)
@@ -175,6 +202,48 @@ class Message(ComponentBase):
     def thoughts(self) -> str:
         return ""
 
+    def _parse_markdown_table_lines(self, table_lines: list):
+        """
+        Parse a list of Markdown table lines into a pandas DataFrame.
+        
+        Args:
+            table_lines: List of strings, each representing a row in the Markdown table
+                        (excluding separator lines like |---|---|)
+        
+        Returns:
+            pandas DataFrame with the table data, or None if parsing fails
+        """
+        import pandas as pd
+        
+        if not table_lines:
+            return None
+        
+        rows = []
+        headers = None
+        
+        for line in table_lines:
+            # Split by | and clean up
+            cells = [cell.strip() for cell in line.split('|')]
+            # Remove empty first and last elements from split (caused by leading/trailing |)
+            cells = [c for c in cells if c]
+            
+            if headers is None:
+                headers = cells
+            else:
+                rows.append(cells)
+        
+        if headers and rows:
+            # Ensure all rows have same number of columns as headers
+            normalized_rows = []
+            for row in rows:
+                while len(row) < len(headers):
+                    row.append('')
+                normalized_rows.append(row[:len(headers)])
+            
+            return pd.DataFrame(normalized_rows, columns=headers)
+        
+        return None
+
     def _convert_content(self, content):
         if not self._param.output_format:
             return
@@ -182,7 +251,7 @@ class Message(ComponentBase):
         import pypandoc
         doc_id = get_uuid()
 
-        if self._param.output_format.lower() not in {"markdown", "html", "pdf", "docx"}:
+        if self._param.output_format.lower() not in {"markdown", "html", "pdf", "docx", "xlsx"}:
             self._param.output_format = "markdown"
 
         try:
@@ -202,6 +271,119 @@ class Message(ComponentBase):
 
                 binary_content = converted.encode("utf-8")
 
+            elif self._param.output_format == "xlsx":
+                import pandas as pd
+                from io import BytesIO
+
+                # Debug: log the content being parsed
+                logging.info(f"XLSX Parser: Content length={len(content) if content else 0}, first 500 chars: {content[:500] if content else 'None'}")
+                
+                # Try to parse ALL Markdown tables from the content
+                # Each table will be written to a separate sheet
+                tables = []  # List of (sheet_name, dataframe)
+                
+                if isinstance(content, str):
+                    lines = content.strip().split('\n')
+                    logging.info(f"XLSX Parser: Total lines={len(lines)}, lines starting with '|': {sum(1 for line in lines if line.strip().startswith('|'))}")
+                    current_table_lines = []
+                    current_table_title = None
+                    pending_title = None
+                    in_table = False
+                    table_count = 0
+                    
+                    for i, line in enumerate(lines):
+                        stripped = line.strip()
+                        
+                        # Check for potential table title (lines before a table)
+                        # Look for patterns like "Table 1:", "## Table", or markdown headers
+                        if not in_table and stripped and not stripped.startswith('|'):
+                            # Check if this could be a table title
+                            lower_stripped = stripped.lower()
+                            if (lower_stripped.startswith('table') or 
+                                stripped.startswith('#') or
+                                ':' in stripped):
+                                pending_title = stripped.lstrip('#').strip()
+                        
+                        if stripped.startswith('|') and '|' in stripped[1:]:
+                            # Check if this is a separator line (|---|---|)
+                            cleaned = stripped.replace(' ', '').replace('|', '').replace('-', '').replace(':', '')
+                            if cleaned == '':
+                                continue  # Skip separator line
+                            
+                            if not in_table:
+                                # Starting a new table
+                                in_table = True
+                                current_table_lines = []
+                                current_table_title = pending_title
+                                pending_title = None
+                            
+                            current_table_lines.append(stripped)
+                        
+                        elif in_table and not stripped.startswith('|'):
+                            # End of current table - save it
+                            if current_table_lines:
+                                df = self._parse_markdown_table_lines(current_table_lines)
+                                if df is not None and not df.empty:
+                                    table_count += 1
+                                    # Generate sheet name
+                                    if current_table_title:
+                                        # Clean and truncate title for sheet name
+                                        sheet_name = current_table_title[:31]
+                                        sheet_name = sheet_name.replace('/', '_').replace('\\', '_').replace('*', '').replace('?', '').replace('[', '').replace(']', '').replace(':', '')
+                                    else:
+                                        sheet_name = f"Table_{table_count}"
+                                    tables.append((sheet_name, df))
+                            
+                            # Reset for next table
+                            in_table = False
+                            current_table_lines = []
+                            current_table_title = None
+                            
+                            # Check if this line could be a title for the next table
+                            if stripped:
+                                lower_stripped = stripped.lower()
+                                if (lower_stripped.startswith('table') or 
+                                    stripped.startswith('#') or
+                                    ':' in stripped):
+                                    pending_title = stripped.lstrip('#').strip()
+                    
+                    # Don't forget the last table if content ends with a table
+                    if in_table and current_table_lines:
+                        df = self._parse_markdown_table_lines(current_table_lines)
+                        if df is not None and not df.empty:
+                            table_count += 1
+                            if current_table_title:
+                                sheet_name = current_table_title[:31]
+                                sheet_name = sheet_name.replace('/', '_').replace('\\', '_').replace('*', '').replace('?', '').replace('[', '').replace(']', '').replace(':', '')
+                            else:
+                                sheet_name = f"Table_{table_count}"
+                            tables.append((sheet_name, df))
+                
+                # Fallback: if no tables found, create single sheet with content
+                if not tables:
+                    df = pd.DataFrame({"Content": [content if content else ""]})
+                    tables = [("Data", df)]
+
+                # Write all tables to Excel, each in a separate sheet
+                excel_io = BytesIO()
+                with pd.ExcelWriter(excel_io, engine='openpyxl') as writer:
+                    used_names = set()
+                    for sheet_name, df in tables:
+                        # Ensure unique sheet names
+                        original_name = sheet_name
+                        counter = 1
+                        while sheet_name in used_names:
+                            suffix = f"_{counter}"
+                            sheet_name = original_name[:31-len(suffix)] + suffix
+                            counter += 1
+                        used_names.add(sheet_name)
+                        df.to_excel(writer, sheet_name=sheet_name, index=False)
+                
+                excel_io.seek(0)
+                binary_content = excel_io.read()
+                
+                logging.info(f"Generated Excel with {len(tables)} sheet(s): {[t[0] for t in tables]}")
+
             else:  # pdf, docx
                 with tempfile.NamedTemporaryFile(suffix=f".{self._param.output_format}", delete=False) as tmp:
                     tmp_name = tmp.name

agent/templates/advanced_ingestion_pipeline.json

@@ -193,7 +193,7 @@
                         "presence_penalty": 0.4,
                         "prompts": [
                             {
-                                "content": "Text Content:\n{Splitter:KindDingosJam@chunks}\n",
+                                "content": "Text Content:\n{Splitter:NineTiesSin@chunks}\n",
                                 "role": "user"
                             }
                         ],
@@ -226,7 +226,7 @@
                         "presence_penalty": 0.4,
                         "prompts": [
                             {
-                                "content": "Text Content:\n\n{Splitter:KindDingosJam@chunks}\n",
+                                "content": "Text Content:\n\n{Splitter:TastyPointsLay@chunks}\n",
                                 "role": "user"
                             }
                         ],
@@ -259,7 +259,7 @@
                         "presence_penalty": 0.4,
                         "prompts": [
                             {
-                                "content": "Content: \n\n{Splitter:KindDingosJam@chunks}",
+                                "content": "Content: \n\n{Splitter:CuteBusesBet@chunks}",
                                 "role": "user"
                             }
                         ],
@@ -485,7 +485,7 @@
                             "outputs": {},
                             "presencePenaltyEnabled": false,
                             "presence_penalty": 0.4,
-                            "prompts": "Text Content:\n{Splitter:KindDingosJam@chunks}\n",
+                            "prompts": "Text Content:\n{Splitter:NineTiesSin@chunks}\n",
                             "sys_prompt": "Role\nYou are a text analyzer.\n\nTask\nExtract the most important keywords/phrases of a given piece of text content.\n\nRequirements\n- Summarize the text content, and give the top 5 important keywords/phrases.\n- The keywords MUST be in the same language as the given piece of text content.\n- The keywords are delimited by ENGLISH COMMA.\n- Output keywords ONLY.",
                             "temperature": 0.1,
                             "temperatureEnabled": false,
@@ -522,7 +522,7 @@
                             "outputs": {},
                             "presencePenaltyEnabled": false,
                             "presence_penalty": 0.4,
-                            "prompts": "Text Content:\n\n{Splitter:KindDingosJam@chunks}\n",
+                            "prompts": "Text Content:\n\n{Splitter:TastyPointsLay@chunks}\n",
                             "sys_prompt": "Role\nYou are a text analyzer.\n\nTask\nPropose 3 questions about a given piece of text content.\n\nRequirements\n- Understand and summarize the text content, and propose the top 3 important questions.\n- The questions SHOULD NOT have overlapping meanings.\n- The questions SHOULD cover the main content of the text as much as possible.\n- The questions MUST be in the same language as the given piece of text content.\n- One question per line.\n- Output questions ONLY.",
                             "temperature": 0.1,
                             "temperatureEnabled": false,
@@ -559,7 +559,7 @@
                             "outputs": {},
                             "presencePenaltyEnabled": false,
                             "presence_penalty": 0.4,
-                            "prompts": "Content: \n\n{Splitter:KindDingosJam@chunks}",
+                            "prompts": "Content: \n\n{Splitter:BlueResultsWink@chunks}",
                             "sys_prompt": "Extract important structured information from the given content. Output ONLY a valid JSON string with no additional text. If no important structured information is found, output an empty JSON object: {}.\n\nImportant structured information may include: names, dates, locations, events, key facts, numerical data, or other extractable entities.",
                             "temperature": 0.1,
                             "temperatureEnabled": false,

agent/templates/sql_assistant.json

@@ -578,7 +578,7 @@
                     {
                         "data": {
                             "form": {
-                                "text": "Searches for relevant database creation statements.\n\nIt should label with a knowledgebase to which the schema is dumped in. You could use \" General \" as parsing method, \" 2 \" as chunk size and \" ; \"  as delimiter."
+                                "text": "Searches for relevant database creation statements.\n\nIt should label with a dataset to which the schema is dumped in. You could use \" General \" as parsing method, \" 2 \" as chunk size and \" ; \"  as delimiter."
                             },
                             "label": "Note",
                             "name": "Note Schema"

agent/test/dsl_examples/categorize_and_agent_with_tavily.json

@@ -75,7 +75,7 @@
   },
   "history": [],
   "path": [],
-  "retrival": {"chunks": [], "doc_aggs": []},
+  "retrieval": {"chunks": [], "doc_aggs": []},
   "globals": {
     "sys.query": "",
     "sys.user_id": "",

agent/test/dsl_examples/iteration.json

@@ -82,7 +82,7 @@
   },
   "history": [],
   "path": [],
-  "retrival": {"chunks": [], "doc_aggs": []},
+  "retrieval": {"chunks": [], "doc_aggs": []},
   "globals": {
     "sys.query": "",
     "sys.user_id": "",

agent/test/dsl_examples/retrieval_and_generate.json

@@ -31,7 +31,7 @@
                     "component_name": "LLM",
                     "params": {
                       "llm_id": "deepseek-chat",
-                      "sys_prompt": "You are an intelligent assistant. Please summarize the content of the knowledge base to answer the question. Please list the data in the knowledge base and answer in detail. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\" Answers need to consider chat history.\n      Here is the knowledge base:\n      {retrieval:0@formalized_content}\n      The above is the knowledge base.",
+                      "sys_prompt": "You are an intelligent assistant. Please summarize the content of the knowledge base to answer the question. Please list the data in the knowledge base and answer in detail. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\" Answers need to consider chat history.\n      Here is the knowledge base:\n      {retrieval:0@formalized_content}\n      Above is the knowledge base.",
                       "temperature": 0.2
                     }
                 },
@@ -51,7 +51,7 @@
   },
   "history": [],
   "path": [],
-  "retrival": {"chunks": [], "doc_aggs": []},
+  "retrieval": {"chunks": [], "doc_aggs": []},
   "globals": {
     "sys.query": "",
     "sys.user_id": "",

agent/test/dsl_examples/retrieval_categorize_and_generate.json

@@ -65,7 +65,7 @@
                     "component_name": "Agent",
                     "params": {
                       "llm_id": "deepseek-chat",
-                      "sys_prompt": "You are an intelligent assistant. Please summarize the content of the knowledge base to answer the question. Please list the data in the knowledge base and answer in detail. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\" Answers need to consider chat history.\n      Here is the knowledge base:\n      {retrieval:0@formalized_content}\n      The above is the knowledge base.",
+                      "sys_prompt": "You are an intelligent assistant. Please summarize the content of the dataset to answer the question. Please list the data in the knowledge base and answer in detail. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\" Answers need to consider chat history.\n      Here is the knowledge base:\n      {retrieval:0@formalized_content}\n      The above is the knowledge base.",
                       "temperature": 0.2
                     }
                 },
@@ -85,7 +85,7 @@
   },
   "history": [],
   "path": [],
-  "retrival": {"chunks": [], "doc_aggs": []},
+  "retrieval": {"chunks": [], "doc_aggs": []},
   "globals": {
     "sys.query": "",
     "sys.user_id": "",

agent/test/dsl_examples/tavily_and_generate.json

@@ -25,7 +25,7 @@
                     "component_name": "LLM",
                     "params": {
                       "llm_id": "deepseek-chat",
-                      "sys_prompt": "You are an intelligent assistant. Please summarize the content of the knowledge base to answer the question. Please list the data in the knowledge base and answer in detail. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\" Answers need to consider chat history.\n      Here is the knowledge base:\n      {tavily:0@formalized_content}\n      The above is the knowledge base.",
+                      "sys_prompt": "You are an intelligent assistant. Please summarize the content of the knowledge base to answer the question. Please list the data in the knowledge base and answer in detail. When all knowledge base content is irrelevant to the question, your answer must include the sentence \"The answer you are looking for is not found in the knowledge base!\" Answers need to consider chat history.\n      Here is the knowledge base:\n      {tavily:0@formalized_content}\n      Above is the knowledge base.",
                       "temperature": 0.2
                     }
                 },
@@ -45,7 +45,7 @@
   },
   "history": [],
   "path": [],
-  "retrival": {"chunks": [], "doc_aggs": []},
+  "retrieval": {"chunks": [], "doc_aggs": []},
   "globals": {
     "sys.query": "",
     "sys.user_id": "",

agent/tools/base.py

@@ -17,6 +17,7 @@ import logging
 import re
 import time
 from copy import deepcopy
+import asyncio
 from functools import partial
 from typing import TypedDict, List, Any
 from agent.component.base import ComponentParamBase, ComponentBase
@@ -48,12 +49,19 @@ class LLMToolPluginCallSession(ToolCallSession):
         self.callback = callback
 
     def tool_call(self, name: str, arguments: dict[str, Any]) -> Any:
+        return asyncio.run(self.tool_call_async(name, arguments))
+
+    async def tool_call_async(self, name: str, arguments: dict[str, Any]) -> Any:
         assert name in self.tools_map, f"LLM tool {name} does not exist"
         st = timer()
-        if isinstance(self.tools_map[name], MCPToolCallSession):
+        tool_obj = self.tools_map[name]
-            resp = self.tools_map[name].tool_call(name, arguments, 60)
+        if isinstance(tool_obj, MCPToolCallSession):
+            resp = await asyncio.to_thread(tool_obj.tool_call, name, arguments, 60)
         else:
-            resp = self.tools_map[name].invoke(**arguments)
+            if hasattr(tool_obj, "invoke_async") and asyncio.iscoroutinefunction(tool_obj.invoke_async):
+                resp = await tool_obj.invoke_async(**arguments)
+            else:
+                resp = await asyncio.to_thread(tool_obj.invoke, **arguments)
 
         self.callback(name, arguments, resp, elapsed_time=timer()-st)
         return resp
@@ -139,6 +147,33 @@ class ToolBase(ComponentBase):
         self.set_output("_elapsed_time", time.perf_counter() - self.output("_created_time"))
         return res
 
+    async def invoke_async(self, **kwargs):
+        """
+        Async wrapper for tool invocation.
+        If `_invoke` is a coroutine, await it directly; otherwise run in a thread to avoid blocking.
+        Mirrors the exception handling of `invoke`.
+        """
+        if self.check_if_canceled("Tool processing"):
+            return
+
+        self.set_output("_created_time", time.perf_counter())
+        try:
+            fn_async = getattr(self, "_invoke_async", None)
+            if fn_async and asyncio.iscoroutinefunction(fn_async):
+                res = await fn_async(**kwargs)
+            elif asyncio.iscoroutinefunction(self._invoke):
+                res = await self._invoke(**kwargs)
+            else:
+                res = await asyncio.to_thread(self._invoke, **kwargs)
+        except Exception as e:
+            self._param.outputs["_ERROR"] = {"value": str(e)}
+            logging.exception(e)
+            res = str(e)
+        self._param.debug_inputs = []
+
+        self.set_output("_elapsed_time", time.perf_counter() - self.output("_created_time"))
+        return res
+
     def _retrieve_chunks(self, res_list: list, get_title, get_url, get_content, get_score=None):
         chunks = []
         aggs = []

agent/tools/code_exec.py

@@ -69,7 +69,7 @@ class CodeExecParam(ToolParamBase):
         self.meta: ToolMeta = {
             "name": "execute_code",
             "description": """
-This tool has a sandbox that can execute code written in 'Python'/'Javascript'. It recieves a piece of code and return a Json string.
+This tool has a sandbox that can execute code written in 'Python'/'Javascript'. It receives a piece of code and return a Json string.
 Here's a code example for Python(`main` function MUST be included):
 def main() -> dict:
     \"\"\"

agent/tools/retrieval.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
 from functools import partial
 import json
 import os
@@ -21,13 +22,13 @@ from abc import ABC
 from agent.tools.base import ToolParamBase, ToolBase, ToolMeta
 from common.constants import LLMType
 from api.db.services.document_service import DocumentService
-from api.db.services.dialog_service import meta_filter
+from common.metadata_utils import apply_meta_data_filter
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMBundle
 from common import settings
 from common.connection_utils import timeout
 from rag.app.tag import label_question
-from rag.prompts.generator import cross_languages, kb_prompt, gen_meta_filter
+from rag.prompts.generator import cross_languages, kb_prompt
 
 
 class RetrievalParam(ToolParamBase):
@@ -81,7 +82,7 @@ class Retrieval(ToolBase, ABC):
     component_name = "Retrieval"
 
     @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 12)))
-    def _invoke(self, **kwargs):
+    async def _invoke_async(self, **kwargs):
         if self.check_if_canceled("Retrieval processing"):
             return
 
@@ -130,17 +131,10 @@ class Retrieval(ToolBase, ABC):
         doc_ids=[]
         if self._param.meta_data_filter!={}:
             metas = DocumentService.get_meta_by_kbs(kb_ids)
-            if self._param.meta_data_filter.get("method") == "auto":
+
-                chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT)
+            def _resolve_manual_filter(flt: dict) -> dict:
-                filters: dict = gen_meta_filter(chat_mdl, metas, query)
-                doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
-                if not doc_ids:
-                    doc_ids = None
-            elif self._param.meta_data_filter.get("method") == "manual":
-                filters = self._param.meta_data_filter["manual"]
-                for flt in filters:
                 pat = re.compile(self.variable_ref_patt)
-                    s = flt["value"]
+                s = flt.get("value", "")
                 out_parts = []
                 last = 0
 
@@ -165,12 +159,23 @@ class Retrieval(ToolBase, ABC):
 
                 out_parts.append(s[last:])
                 flt["value"] = "".join(out_parts)
-                doc_ids.extend(meta_filter(metas, filters, self._param.meta_data_filter.get("logic", "and")))
+                return flt
-                if filters and not doc_ids:
+
-                    doc_ids = ["-999"]
+            chat_mdl = None
+            if self._param.meta_data_filter.get("method") in ["auto", "semi_auto"]:
+                chat_mdl = LLMBundle(self._canvas.get_tenant_id(), LLMType.CHAT)
+
+            doc_ids = await apply_meta_data_filter(
+                self._param.meta_data_filter,
+                metas,
+                query,
+                chat_mdl,
+                doc_ids,
+                _resolve_manual_filter if self._param.meta_data_filter.get("method") == "manual" else None,
+            )
 
         if self._param.cross_languages:
-            query = cross_languages(kbs[0].tenant_id, None, query, self._param.cross_languages)
+            query = await cross_languages(kbs[0].tenant_id, None, query, self._param.cross_languages)
 
         if kbs:
             query = re.sub(r"^user[:：\s]*", "", query, flags=re.IGNORECASE)
@@ -198,6 +203,7 @@ class Retrieval(ToolBase, ABC):
                     return
                 if cks:
                     kbinfos["chunks"] = cks
+            kbinfos["chunks"] = settings.retriever.retrieval_by_children(kbinfos["chunks"], [kb.tenant_id for kb in kbs])
             if self._param.use_kg:
                 ck = settings.kg_retriever.retrieval(query,
                                                        [kb.tenant_id for kb in kbs],
@@ -242,6 +248,10 @@ class Retrieval(ToolBase, ABC):
 
         return form_cnt
 
+    @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 12)))
+    def _invoke(self, **kwargs):
+        return asyncio.run(self._invoke_async(**kwargs))
+
     def thoughts(self) -> str:
         return """
 Keywords: {}

agent/tools/yahoofinance.py

@@ -75,7 +75,7 @@ class YahooFinance(ToolBase, ABC):
     @timeout(int(os.environ.get("COMPONENT_EXEC_TIMEOUT", 60)))
     def _invoke(self, **kwargs):
         if self.check_if_canceled("YahooFinance processing"):
-            return
+            return None
 
         if not kwargs.get("stock_code"):
             self.set_output("report", "")
@@ -84,33 +84,33 @@ class YahooFinance(ToolBase, ABC):
         last_e = ""
         for _ in range(self._param.max_retries+1):
             if self.check_if_canceled("YahooFinance processing"):
-                return
+                return None
 
-            yohoo_res = []
+            yahoo_res = []
             try:
                 msft = yf.Ticker(kwargs["stock_code"])
                 if self.check_if_canceled("YahooFinance processing"):
-                    return
+                    return None
 
                 if self._param.info:
-                    yohoo_res.append("# Information:\n" + pd.Series(msft.info).to_markdown() + "\n")
+                    yahoo_res.append("# Information:\n" + pd.Series(msft.info).to_markdown() + "\n")
                 if self._param.history:
-                    yohoo_res.append("# History:\n" + msft.history().to_markdown() + "\n")
+                    yahoo_res.append("# History:\n" + msft.history().to_markdown() + "\n")
                 if self._param.financials:
-                    yohoo_res.append("# Calendar:\n" + pd.DataFrame(msft.calendar).to_markdown() + "\n")
+                    yahoo_res.append("# Calendar:\n" + pd.DataFrame(msft.calendar).to_markdown() + "\n")
                 if self._param.balance_sheet:
-                    yohoo_res.append("# Balance sheet:\n" + msft.balance_sheet.to_markdown() + "\n")
+                    yahoo_res.append("# Balance sheet:\n" + msft.balance_sheet.to_markdown() + "\n")
-                    yohoo_res.append("# Quarterly balance sheet:\n" + msft.quarterly_balance_sheet.to_markdown() + "\n")
+                    yahoo_res.append("# Quarterly balance sheet:\n" + msft.quarterly_balance_sheet.to_markdown() + "\n")
                 if self._param.cash_flow_statement:
-                    yohoo_res.append("# Cash flow statement:\n" + msft.cashflow.to_markdown() + "\n")
+                    yahoo_res.append("# Cash flow statement:\n" + msft.cashflow.to_markdown() + "\n")
-                    yohoo_res.append("# Quarterly cash flow statement:\n" + msft.quarterly_cashflow.to_markdown() + "\n")
+                    yahoo_res.append("# Quarterly cash flow statement:\n" + msft.quarterly_cashflow.to_markdown() + "\n")
                 if self._param.news:
-                    yohoo_res.append("# News:\n" + pd.DataFrame(msft.news).to_markdown() + "\n")
+                    yahoo_res.append("# News:\n" + pd.DataFrame(msft.news).to_markdown() + "\n")
-                self.set_output("report", "\n\n".join(yohoo_res))
+                self.set_output("report", "\n\n".join(yahoo_res))
                 return self.output("report")
             except Exception as e:
                 if self.check_if_canceled("YahooFinance processing"):
-                    return
+                    return None
 
                 last_e = e
                 logging.exception(f"YahooFinance error: {e}")

agentic_reasoning/deep_research.py

@@ -51,7 +51,7 @@ class DeepResearcher:
         """Remove Result Tags"""
         return DeepResearcher._remove_tags(text, BEGIN_SEARCH_RESULT, END_SEARCH_RESULT)
 
-    def _generate_reasoning(self, msg_history):
+    async def _generate_reasoning(self, msg_history):
         """Generate reasoning steps"""
         query_think = ""
         if msg_history[-1]["role"] != "user":
@@ -59,13 +59,14 @@ class DeepResearcher:
         else:
             msg_history[-1]["content"] += "\n\nContinues reasoning with the new information.\n"
             
-        for ans in self.chat_mdl.chat_streamly(REASON_PROMPT, msg_history, {"temperature": 0.7}):
+        async for ans in self.chat_mdl.async_chat_streamly(REASON_PROMPT, msg_history, {"temperature": 0.7}):
             ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
             if not ans:
                 continue
             query_think = ans
             yield query_think
-        return query_think
+            query_think = ""
+        yield query_think
 
     def _extract_search_queries(self, query_think, question, step_index):
         """Extract search queries from thinking"""
@@ -143,10 +144,10 @@ class DeepResearcher:
                 if d["doc_id"] not in dids:
                     chunk_info["doc_aggs"].append(d)
 
-    def _extract_relevant_info(self, truncated_prev_reasoning, search_query, kbinfos):
+    async def _extract_relevant_info(self, truncated_prev_reasoning, search_query, kbinfos):
         """Extract and summarize relevant information"""
         summary_think = ""
-        for ans in self.chat_mdl.chat_streamly(
+        async for ans in self.chat_mdl.async_chat_streamly(
                 RELEVANT_EXTRACTION_PROMPT.format(
                     prev_reasoning=truncated_prev_reasoning,
                     search_query=search_query,
@@ -160,10 +161,11 @@ class DeepResearcher:
                 continue
             summary_think = ans
             yield summary_think
+            summary_think = ""
         
-        return summary_think
+        yield summary_think
 
-    def thinking(self, chunk_info: dict, question: str):
+    async def thinking(self, chunk_info: dict, question: str):
         executed_search_queries = []
         msg_history = [{"role": "user", "content": f'Question:\"{question}\"\n'}]
         all_reasoning_steps = []
@@ -180,7 +182,7 @@ class DeepResearcher:
 
             # Step 1: Generate reasoning
             query_think = ""
-            for ans in self._generate_reasoning(msg_history):
+            async for ans in self._generate_reasoning(msg_history):
                 query_think = ans
                 yield {"answer": think + self._remove_query_tags(query_think) + "</think>", "reference": {}, "audio_binary": None}
 
@@ -223,7 +225,7 @@ class DeepResearcher:
                 # Step 6: Extract relevant information
                 think += "\n\n"
                 summary_think = ""
-                for ans in self._extract_relevant_info(truncated_prev_reasoning, search_query, kbinfos):
+                async for ans in self._extract_relevant_info(truncated_prev_reasoning, search_query, kbinfos):
                     summary_think = ans
                     yield {"answer": think + self._remove_result_tags(summary_think) + "</think>", "reference": {}, "audio_binary": None}
 

api/__init__.py

@@ -14,5 +14,5 @@
 #  limitations under the License.
 #
 
-from beartype.claw import beartype_this_package
+# from beartype.claw import beartype_this_package
-beartype_this_package()
+# beartype_this_package()

api/apps/__init__.py

@@ -13,13 +13,12 @@
 #  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 quart import Blueprint, Quart, request, g, current_app, session
-from werkzeug.wrappers.request import Request
 from flasgger import Swagger
 from itsdangerous.url_safe import URLSafeTimedSerializer as Serializer
 from quart_cors import cors
@@ -29,7 +28,6 @@ from api.db.services import UserService
 from api.utils.json_encode import CustomJSONEncoder
 from api.utils import commands
 
-from flask_mail import Mail
 from quart_auth import Unauthorized
 from common import settings
 from api.utils.api_utils import server_error_response
@@ -40,11 +38,9 @@ settings.init_settings()
 
 __all__ = ["app"]
 
-Request.json = property(lambda self: self.get_json(force=True, silent=True))
 
 app = Quart(__name__)
 app = cors(app, allow_origin="*")
-smtp_mail_server = Mail()
 
 # Add this at the beginning of your file to configure Swagger UI
 swagger_config = {
@@ -82,6 +78,11 @@ app.url_map.strict_slashes = False
 app.json_encoder = CustomJSONEncoder
 app.errorhandler(Exception)(server_error_response)
 
+# Configure Quart timeouts for slow LLM responses (e.g., local Ollama on CPU)
+# Default Quart timeouts are 60 seconds which is too short for many LLM backends
+app.config["RESPONSE_TIMEOUT"] = int(os.environ.get("QUART_RESPONSE_TIMEOUT", 600))
+app.config["BODY_TIMEOUT"] = int(os.environ.get("QUART_BODY_TIMEOUT", 600))
+
 ## convince for dev and debug
 # app.config["LOGIN_DISABLED"] = True
 app.config["SESSION_PERMANENT"] = False

api/apps/api_app.py

@@ -18,8 +18,7 @@ from quart import request
 from api.db.db_models import APIToken
 from api.db.services.api_service import APITokenService, API4ConversationService
 from api.db.services.user_service import UserTenantService
-from api.utils.api_utils import server_error_response, get_data_error_result, get_json_result, validate_request, \
+from api.utils.api_utils import generate_confirmation_token, get_data_error_result, get_json_result, get_request_json, server_error_response, validate_request
-    generate_confirmation_token
 from common.time_utils import current_timestamp, datetime_format
 from api.apps import login_required, current_user
 
@@ -27,7 +26,7 @@ from api.apps import login_required, current_user
 @manager.route('/new_token', methods=['POST'])  # noqa: F821
 @login_required
 async def new_token():
-    req = await request.json
+    req = await get_request_json()
     try:
         tenants = UserTenantService.query(user_id=current_user.id)
         if not tenants:
@@ -73,7 +72,7 @@ def token_list():
 @validate_request("tokens", "tenant_id")
 @login_required
 async def rm():
-    req = await request.json
+    req = await get_request_json()
     try:
         for token in req["tokens"]:
             APITokenService.filter_delete(
@@ -116,4 +115,3 @@ def stats():
         return get_json_result(data=res)
     except Exception as e:
         return server_error_response(e)
-

api/apps/auth/github.py

@@ -14,7 +14,7 @@
 #  limitations under the License.
 #
 
-import requests
+from common.http_client import async_request, sync_request
 from .oauth import OAuthClient, UserInfo
 
 
@@ -34,24 +34,49 @@ class GithubOAuthClient(OAuthClient):
 
     def fetch_user_info(self, access_token, **kwargs):
         """
-        Fetch GitHub user info.
+        Fetch GitHub user info (synchronous).
         """
         user_info = {}
         try:
             headers = {"Authorization": f"Bearer {access_token}"}
-            # user info
+            response = sync_request("GET", self.userinfo_url, headers=headers, timeout=self.http_request_timeout)
-            response = requests.get(self.userinfo_url, headers=headers, timeout=self.http_request_timeout)
             response.raise_for_status()
             user_info.update(response.json())
-            # email info
+            email_response = sync_request(
-            response = requests.get(self.userinfo_url+"/emails", headers=headers, timeout=self.http_request_timeout)
+                "GET", self.userinfo_url + "/emails", headers=headers, timeout=self.http_request_timeout
-            response.raise_for_status()
+            )
-            email_info = response.json()
+            email_response.raise_for_status()
-            user_info["email"] = next(
+            email_info = email_response.json()
-                (email for email in email_info if email["primary"]), None
+            user_info["email"] = next((email for email in email_info if email["primary"]), None)["email"]
-            )["email"]
             return self.normalize_user_info(user_info)
-        except requests.exceptions.RequestException as e:
+        except Exception as e:
+            raise ValueError(f"Failed to fetch github user info: {e}")
+
+    async def async_fetch_user_info(self, access_token, **kwargs):
+        """Async variant of fetch_user_info using httpx."""
+        user_info = {}
+        headers = {"Authorization": f"Bearer {access_token}"}
+        try:
+            response = await async_request(
+                "GET",
+                self.userinfo_url,
+                headers=headers,
+                timeout=self.http_request_timeout,
+            )
+            response.raise_for_status()
+            user_info.update(response.json())
+
+            email_response = await async_request(
+                "GET",
+                self.userinfo_url + "/emails",
+                headers=headers,
+                timeout=self.http_request_timeout,
+            )
+            email_response.raise_for_status()
+            email_info = email_response.json()
+            user_info["email"] = next((email for email in email_info if email["primary"]), None)["email"]
+            return self.normalize_user_info(user_info)
+        except Exception as e:
             raise ValueError(f"Failed to fetch github user info: {e}")
 
 

api/apps/auth/oauth.py

@@ -14,8 +14,8 @@
 #  limitations under the License.
 #
 
-import requests
 import urllib.parse
+from common.http_client import async_request, sync_request
 
 
 class UserInfo:
@@ -74,15 +74,40 @@ class OAuthClient:
                 "redirect_uri": self.redirect_uri,
                 "grant_type": "authorization_code"
             }
-            response = requests.post(
+            response = sync_request(
+                "POST",
                 self.token_url,
                 data=payload,
                 headers={"Accept": "application/json"},
-                timeout=self.http_request_timeout
+                timeout=self.http_request_timeout,
             )
             response.raise_for_status()
             return response.json()
-        except requests.exceptions.RequestException as e:
+        except Exception as e:
+            raise ValueError(f"Failed to exchange authorization code for token: {e}")
+
+    async def async_exchange_code_for_token(self, code):
+        """
+        Async variant of exchange_code_for_token using httpx.
+        """
+        payload = {
+            "client_id": self.client_id,
+            "client_secret": self.client_secret,
+            "code": code,
+            "redirect_uri": self.redirect_uri,
+            "grant_type": "authorization_code",
+        }
+        try:
+            response = await async_request(
+                "POST",
+                self.token_url,
+                data=payload,
+                headers={"Accept": "application/json"},
+                timeout=self.http_request_timeout,
+            )
+            response.raise_for_status()
+            return response.json()
+        except Exception as e:
             raise ValueError(f"Failed to exchange authorization code for token: {e}")
 
 
@@ -92,11 +117,27 @@ class OAuthClient:
         """
         try:
             headers = {"Authorization": f"Bearer {access_token}"}
-            response = requests.get(self.userinfo_url, headers=headers, timeout=self.http_request_timeout)
+            response = sync_request("GET", self.userinfo_url, headers=headers, timeout=self.http_request_timeout)
             response.raise_for_status()
             user_info = response.json()
             return self.normalize_user_info(user_info)
-        except requests.exceptions.RequestException as e:
+        except Exception as e:
+            raise ValueError(f"Failed to fetch user info: {e}")
+
+    async def async_fetch_user_info(self, access_token, **kwargs):
+        """Async variant of fetch_user_info using httpx."""
+        headers = {"Authorization": f"Bearer {access_token}"}
+        try:
+            response = await async_request(
+                "GET",
+                self.userinfo_url,
+                headers=headers,
+                timeout=self.http_request_timeout,
+            )
+            response.raise_for_status()
+            user_info = response.json()
+            return self.normalize_user_info(user_info)
+        except Exception as e:
             raise ValueError(f"Failed to fetch user info: {e}")
 
 

api/apps/auth/oidc.py

@@ -15,7 +15,7 @@
 #
 
 import jwt
-import requests
+from common.http_client import sync_request
 from .oauth import OAuthClient
 
 
@@ -50,10 +50,10 @@ class OIDCClient(OAuthClient):
         """
         try:
             metadata_url = f"{issuer}/.well-known/openid-configuration"
-            response = requests.get(metadata_url, timeout=7)
+            response = sync_request("GET", metadata_url, timeout=7)
             response.raise_for_status()
             return response.json()
-        except requests.exceptions.RequestException as e:
+        except Exception as e:
             raise ValueError(f"Failed to fetch OIDC metadata: {e}")
 
 
@@ -95,6 +95,13 @@ class OIDCClient(OAuthClient):
         user_info.update(super().fetch_user_info(access_token).to_dict())
         return self.normalize_user_info(user_info)
 
+    async def async_fetch_user_info(self, access_token, id_token=None, **kwargs):
+        user_info = {}
+        if id_token:
+            user_info = self.parse_id_token(id_token)
+        user_info.update((await super().async_fetch_user_info(access_token)).to_dict())
+        return self.normalize_user_info(user_info)
+
 
     def normalize_user_info(self, user_info):
         return super().normalize_user_info(user_info)

api/apps/canvas_app.py

@@ -13,15 +13,14 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
+import inspect
 import json
 import logging
-import re
-import sys
 from functools import partial
-import trio
 from quart import request, Response, make_response
 from agent.component import LLM
-from api.db import CanvasCategory, FileType
+from api.db import CanvasCategory
 from api.db.services.canvas_service import CanvasTemplateService, UserCanvasService, API4ConversationService
 from api.db.services.document_service import DocumentService
 from api.db.services.file_service import FileService
@@ -32,13 +31,12 @@ from api.db.services.user_canvas_version import UserCanvasVersionService
 from common.constants import RetCode
 from common.misc_utils import get_uuid
 from api.utils.api_utils import get_json_result, server_error_response, validate_request, get_data_error_result, \
-    request_json
+    get_request_json
 from agent.canvas import Canvas
 from peewee import MySQLDatabase, PostgresqlDatabase
 from api.db.db_models import APIToken, Task
 import time
 
-from api.utils.file_utils import filename_type, read_potential_broken_pdf
 from rag.flow.pipeline import Pipeline
 from rag.nlp import search
 from rag.utils.redis_conn import REDIS_CONN
@@ -56,7 +54,7 @@ def templates():
 @validate_request("canvas_ids")
 @login_required
 async def rm():
-    req = await request_json()
+    req = await get_request_json()
     for i in req["canvas_ids"]:
         if not UserCanvasService.accessible(i, current_user.id):
             return get_json_result(
@@ -70,7 +68,7 @@ async def rm():
 @validate_request("dsl", "title")
 @login_required
 async def save():
-    req = await request_json()
+    req = await get_request_json()
     if not isinstance(req["dsl"], str):
         req["dsl"] = json.dumps(req["dsl"], ensure_ascii=False)
     req["dsl"] = json.loads(req["dsl"])
@@ -129,17 +127,17 @@ def getsse(canvas_id):
 @validate_request("id")
 @login_required
 async def run():
-    req = await request_json()
+    req = await get_request_json()
     query = req.get("query", "")
     files = req.get("files", [])
     inputs = req.get("inputs", {})
     user_id = req.get("user_id", current_user.id)
-    if not UserCanvasService.accessible(req["id"], current_user.id):
+    if not await asyncio.to_thread(UserCanvasService.accessible, req["id"], current_user.id):
         return get_json_result(
             data=False, message='Only owner of canvas authorized for this operation.',
             code=RetCode.OPERATING_ERROR)
 
-    e, cvs = UserCanvasService.get_by_id(req["id"])
+    e, cvs = await asyncio.to_thread(UserCanvasService.get_by_id, req["id"])
     if not e:
         return get_data_error_result(message="canvas not found.")
 
@@ -149,7 +147,7 @@ async def run():
     if cvs.canvas_category == CanvasCategory.DataFlow:
         task_id = get_uuid()
         Pipeline(cvs.dsl, tenant_id=current_user.id, doc_id=CANVAS_DEBUG_DOC_ID, task_id=task_id, flow_id=req["id"])
-        ok, error_message = queue_dataflow(tenant_id=user_id, flow_id=req["id"], task_id=task_id, file=files[0], priority=0)
+        ok, error_message = await asyncio.to_thread(queue_dataflow, user_id, req["id"], task_id, CANVAS_DEBUG_DOC_ID, files[0], 0)
         if not ok:
             return get_data_error_result(message=error_message)
         return get_json_result(data={"message_id": task_id})
@@ -186,7 +184,7 @@ async def run():
 @validate_request("id", "dsl", "component_id")
 @login_required
 async def rerun():
-    req = await request_json()
+    req = await get_request_json()
     doc = PipelineOperationLogService.get_documents_info(req["id"])
     if not doc:
         return get_data_error_result(message="Document not found.")
@@ -224,7 +222,7 @@ def cancel(task_id):
 @validate_request("id")
 @login_required
 async def reset():
-    req = await request_json()
+    req = await get_request_json()
     if not UserCanvasService.accessible(req["id"], current_user.id):
         return get_json_result(
             data=False, message='Only owner of canvas authorized for this operation.',
@@ -250,71 +248,10 @@ async def upload(canvas_id):
         return get_data_error_result(message="canvas not found.")
 
     user_id = cvs["user_id"]
-    def structured(filename, filetype, blob, content_type):
-        nonlocal user_id
-        if filetype == FileType.PDF.value:
-            blob = read_potential_broken_pdf(blob)
-
-        location = get_uuid()
-        FileService.put_blob(user_id, location, blob)
-
-        return {
-            "id": location,
-            "name": filename,
-            "size": sys.getsizeof(blob),
-            "extension": filename.split(".")[-1].lower(),
-            "mime_type": content_type,
-            "created_by": user_id,
-            "created_at": time.time(),
-            "preview_url": None
-        }
-
-    if request.args.get("url"):
-        from crawl4ai import (
-            AsyncWebCrawler,
-            BrowserConfig,
-            CrawlerRunConfig,
-            DefaultMarkdownGenerator,
-            PruningContentFilter,
-            CrawlResult
-        )
-        try:
-            url = request.args.get("url")
-            filename = re.sub(r"\?.*", "", url.split("/")[-1])
-            async def adownload():
-                browser_config = BrowserConfig(
-                    headless=True,
-                    verbose=False,
-                )
-                async with AsyncWebCrawler(config=browser_config) as crawler:
-                    crawler_config = CrawlerRunConfig(
-                        markdown_generator=DefaultMarkdownGenerator(
-                            content_filter=PruningContentFilter()
-                        ),
-                        pdf=True,
-                        screenshot=False
-                    )
-                    result: CrawlResult = await crawler.arun(
-                        url=url,
-                        config=crawler_config
-                    )
-                    return result
-            page = trio.run(adownload())
-            if page.pdf:
-                if filename.split(".")[-1].lower() != "pdf":
-                    filename += ".pdf"
-                return get_json_result(data=structured(filename, "pdf", page.pdf, page.response_headers["content-type"]))
-
-            return get_json_result(data=structured(filename, "html", str(page.markdown).encode("utf-8"), page.response_headers["content-type"], user_id))
-
-        except Exception as e:
-            return  server_error_response(e)
-
     files = await request.files
-    file = files['file']
+    file = files['file'] if files and files.get("file") else None
     try:
-        DocumentService.check_doc_health(user_id, file.filename)
+        return get_json_result(data=FileService.upload_info(user_id, file, request.args.get("url")))
-        return get_json_result(data=structured(file.filename, filename_type(file.filename), file.read(), file.content_type))
     except Exception as e:
         return  server_error_response(e)
 
@@ -343,7 +280,7 @@ def input_form():
 @validate_request("id", "component_id", "params")
 @login_required
 async def debug():
-    req = await request_json()
+    req = await get_request_json()
     if not UserCanvasService.accessible(req["id"], current_user.id):
         return get_json_result(
             data=False, message='Only owner of canvas authorized for this operation.',
@@ -363,7 +300,12 @@ async def debug():
         for k in outputs.keys():
             if isinstance(outputs[k], partial):
                 txt = ""
-                for c in outputs[k]():
+                iter_obj = outputs[k]()
+                if inspect.isasyncgen(iter_obj):
+                    async for c in iter_obj:
+                        txt += c
+                else:
+                    for c in iter_obj:
                         txt += c
                 outputs[k] = txt
         return get_json_result(data=outputs)
@@ -375,7 +317,7 @@ async def debug():
 @validate_request("db_type", "database", "username", "host", "port", "password")
 @login_required
 async def test_db_connect():
-    req = await request_json()
+    req = await get_request_json()
     try:
         if req["db_type"] in ["mysql", "mariadb"]:
             db = MySQLDatabase(req["database"], user=req["username"], host=req["host"], port=req["port"],
@@ -406,7 +348,15 @@ async def test_db_connect():
                 f"UID={req['username']};"
                 f"PWD={req['password']};"
             )
-            logging.info(conn_str)
+            redacted_conn_str = (
+                f"DATABASE={req['database']};"
+                f"HOSTNAME={req['host']};"
+                f"PORT={req['port']};"
+                f"PROTOCOL=TCPIP;"
+                f"UID={req['username']};"
+                f"PWD=****;"
+            )
+            logging.info(redacted_conn_str)
             conn = ibm_db.connect(conn_str, "", "")
             stmt = ibm_db.exec_immediate(conn, "SELECT 1 FROM sysibm.sysdummy1")
             ibm_db.fetch_assoc(stmt)
@@ -520,7 +470,7 @@ def list_canvas():
 @validate_request("id", "title", "permission")
 @login_required
 async def setting():
-    req = await request_json()
+    req = await get_request_json()
     req["user_id"] = current_user.id
 
     if not UserCanvasService.accessible(req["id"], current_user.id):

api/apps/chunk_app.py

@@ -13,25 +13,26 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
 import datetime
 import json
 import re
-
+import base64
 import xxhash
 from quart import request
 
-from api.db.services.dialog_service import meta_filter
 from api.db.services.document_service import DocumentService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMBundle
+from common.metadata_utils import apply_meta_data_filter
 from api.db.services.search_service import SearchService
 from api.db.services.user_service import UserTenantService
 from api.utils.api_utils import get_data_error_result, get_json_result, server_error_response, validate_request, \
-    request_json
+    get_request_json
 from rag.app.qa import beAdoc, rmPrefix
 from rag.app.tag import label_question
 from rag.nlp import rag_tokenizer, search
-from rag.prompts.generator import gen_meta_filter, cross_languages, keyword_extraction
+from rag.prompts.generator import cross_languages, keyword_extraction
 from common.string_utils import remove_redundant_spaces
 from common.constants import RetCode, LLMType, ParserType, PAGERANK_FLD
 from common import settings
@@ -42,7 +43,7 @@ from api.apps import login_required, current_user
 @login_required
 @validate_request("doc_id")
 async def list_chunk():
-    req = await request_json()
+    req = await get_request_json()
     doc_id = req["doc_id"]
     page = int(req.get("page", 1))
     size = int(req.get("size", 30))
@@ -123,7 +124,7 @@ def get():
 @login_required
 @validate_request("doc_id", "chunk_id", "content_with_weight")
 async def set():
-    req = await request_json()
+    req = await get_request_json()
     d = {
         "id": req["chunk_id"],
         "content_with_weight": req["content_with_weight"]}
@@ -147,6 +148,7 @@ async def set():
         d["available_int"] = req["available_int"]
 
     try:
+        def _set_sync():
             tenant_id = DocumentService.get_tenant_id(req["doc_id"])
             if not tenant_id:
                 return get_data_error_result(message="Tenant not found!")
@@ -158,20 +160,31 @@ async def set():
             if not e:
                 return get_data_error_result(message="Document not found!")
 
+            _d = d
             if doc.parser_id == ParserType.QA:
                 arr = [
                     t for t in re.split(
                         r"[\n\t]",
                         req["content_with_weight"]) if len(t) > 1]
                 q, a = rmPrefix(arr[0]), rmPrefix("\n".join(arr[1:]))
-            d = beAdoc(d, q, a, not any(
+                _d = beAdoc(d, q, a, not any(
                     [rag_tokenizer.is_chinese(t) for t in q + a]))
 
-        v, c = embd_mdl.encode([doc.name, req["content_with_weight"] if not d.get("question_kwd") else "\n".join(d["question_kwd"])])
+            v, c = embd_mdl.encode([doc.name, req["content_with_weight"] if not _d.get("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()
+            _d["q_%d_vec" % len(v)] = v.tolist()
-        settings.docStoreConn.update({"id": req["chunk_id"]}, d, search.index_name(tenant_id), doc.kb_id)
+            settings.docStoreConn.update({"id": req["chunk_id"]}, _d, search.index_name(tenant_id), doc.kb_id)
+
+            # update image
+            image_id = req.get("img_id")
+            bkt, name = image_id.split("-")
+            image_base64 = req.get("image_base64", None)
+            if image_base64:
+                image_binary = base64.b64decode(image_base64)
+                settings.STORAGE_IMPL.put(bkt, name, image_binary)
             return get_json_result(data=True)
+
+        return await asyncio.to_thread(_set_sync)
     except Exception as e:
         return server_error_response(e)
 
@@ -180,8 +193,9 @@ async def set():
 @login_required
 @validate_request("chunk_ids", "available_int", "doc_id")
 async def switch():
-    req = await request_json()
+    req = await get_request_json()
     try:
+        def _switch_sync():
             e, doc = DocumentService.get_by_id(req["doc_id"])
             if not e:
                 return get_data_error_result(message="Document not found!")
@@ -192,6 +206,8 @@ async def switch():
                                                     doc.kb_id):
                     return get_data_error_result(message="Index updating failure")
             return get_json_result(data=True)
+
+        return await asyncio.to_thread(_switch_sync)
     except Exception as e:
         return server_error_response(e)
 
@@ -200,8 +216,9 @@ async def switch():
 @login_required
 @validate_request("chunk_ids", "doc_id")
 async def rm():
-    req = await request_json()
+    req = await get_request_json()
     try:
+        def _rm_sync():
             e, doc = DocumentService.get_by_id(req["doc_id"])
             if not e:
                 return get_data_error_result(message="Document not found!")
@@ -216,6 +233,8 @@ async def rm():
                 if settings.STORAGE_IMPL.obj_exist(doc.kb_id, cid):
                     settings.STORAGE_IMPL.rm(doc.kb_id, cid)
             return get_json_result(data=True)
+
+        return await asyncio.to_thread(_rm_sync)
     except Exception as e:
         return server_error_response(e)
 
@@ -224,7 +243,7 @@ async def rm():
 @login_required
 @validate_request("doc_id", "content_with_weight")
 async def create():
-    req = await request_json()
+    req = await get_request_json()
     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"]}
@@ -245,6 +264,7 @@ async def create():
         d["tag_feas"] = req["tag_feas"]
 
     try:
+        def _create_sync():
             e, doc = DocumentService.get_by_id(req["doc_id"])
             if not e:
                 return get_data_error_result(message="Document not found!")
@@ -274,6 +294,8 @@ async def create():
             DocumentService.increment_chunk_num(
                 doc.id, doc.kb_id, c, 1, 0)
             return get_json_result(data={"chunk_id": chunck_id})
+
+        return await asyncio.to_thread(_create_sync)
     except Exception as e:
         return server_error_response(e)
 
@@ -282,7 +304,7 @@ async def create():
 @login_required
 @validate_request("kb_id", "question")
 async def retrieval_test():
-    req = await request_json()
+    req = await get_request_json()
     page = int(req.get("page", 1))
     size = int(req.get("size", 30))
     question = req["question"]
@@ -297,25 +319,29 @@ async def retrieval_test():
     use_kg = req.get("use_kg", False)
     top = int(req.get("top_k", 1024))
     langs = req.get("cross_languages", [])
+    user_id = current_user.id
+
+    async def _retrieval():
+        local_doc_ids = list(doc_ids) if doc_ids else []
         tenant_ids = []
 
+        meta_data_filter = {}
+        chat_mdl = None
         if req.get("search_id", ""):
             search_config = SearchService.get_detail(req.get("search_id", "")).get("search_config", {})
             meta_data_filter = search_config.get("meta_data_filter", {})
-        metas = DocumentService.get_meta_by_kbs(kb_ids)
+            if meta_data_filter.get("method") in ["auto", "semi_auto"]:
-        if meta_data_filter.get("method") == "auto":
+                chat_mdl = LLMBundle(user_id, LLMType.CHAT, llm_name=search_config.get("chat_id", ""))
-            chat_mdl = LLMBundle(current_user.id, LLMType.CHAT, llm_name=search_config.get("chat_id", ""))
+        else:
-            filters: dict = gen_meta_filter(chat_mdl, metas, question)
+            meta_data_filter = req.get("meta_data_filter") or {}
-            doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
+            if meta_data_filter.get("method") in ["auto", "semi_auto"]:
-            if not doc_ids:
+                chat_mdl = LLMBundle(user_id, LLMType.CHAT)
-                doc_ids = None
-        elif meta_data_filter.get("method") == "manual":
-            doc_ids.extend(meta_filter(metas, meta_data_filter["manual"], meta_data_filter.get("logic", "and")))
-            if meta_data_filter["manual"] and not doc_ids:
-                doc_ids = ["-999"]
 
-    try:
+        if meta_data_filter:
-        tenants = UserTenantService.query(user_id=current_user.id)
+            metas = DocumentService.get_meta_by_kbs(kb_ids)
+            local_doc_ids = await apply_meta_data_filter(meta_data_filter, metas, question, chat_mdl, local_doc_ids)
+
+        tenants = UserTenantService.query(user_id=user_id)
         for kb_id in kb_ids:
             for tenant in tenants:
                 if KnowledgebaseService.query(
@@ -324,15 +350,16 @@ async def retrieval_test():
                     break
             else:
                 return get_json_result(
-                    data=False, message='Only owner of knowledgebase authorized for this operation.',
+                    data=False, message='Only owner of dataset authorized for this operation.',
                     code=RetCode.OPERATING_ERROR)
 
         e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
         if not e:
             return get_data_error_result(message="Knowledgebase not found!")
 
+        _question = question
         if langs:
-            question = cross_languages(kb.tenant_id, None, question, langs)
+            _question = await cross_languages(kb.tenant_id, None, _question, langs)
 
         embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
 
@@ -342,31 +369,35 @@ async def retrieval_test():
 
         if req.get("keyword", False):
             chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
-            question += keyword_extraction(chat_mdl, question)
+            _question += await keyword_extraction(chat_mdl, _question)
 
-        labels = label_question(question, [kb])
+        labels = label_question(_question, [kb])
-        ranks = settings.retriever.retrieval(question, embd_mdl, tenant_ids, kb_ids, page, size,
+        ranks = settings.retriever.retrieval(_question, embd_mdl, tenant_ids, kb_ids, page, size,
                                float(req.get("similarity_threshold", 0.0)),
                                float(req.get("vector_similarity_weight", 0.3)),
                                top,
-                               doc_ids, rerank_mdl=rerank_mdl,
+                               local_doc_ids, rerank_mdl=rerank_mdl,
                                              highlight=req.get("highlight", False),
                                rank_feature=labels
                                )
         if use_kg:
-            ck = settings.kg_retriever.retrieval(question,
+            ck = settings.kg_retriever.retrieval(_question,
                                                    tenant_ids,
                                                    kb_ids,
                                                    embd_mdl,
                                                    LLMBundle(kb.tenant_id, LLMType.CHAT))
             if ck["content_with_weight"]:
                 ranks["chunks"].insert(0, ck)
+        ranks["chunks"] = settings.retriever.retrieval_by_children(ranks["chunks"], tenant_ids)
 
         for c in ranks["chunks"]:
             c.pop("vector", None)
         ranks["labels"] = labels
 
         return get_json_result(data=ranks)
+
+    try:
+        return await _retrieval()
     except Exception as e:
         if str(e).find("not_found") > 0:
             return get_json_result(data=False, message='No chunk found! Check the chunk status please!',

api/apps/connector_app.py

@@ -26,19 +26,20 @@ from google_auth_oauthlib.flow import Flow
 
 from api.db import InputType
 from api.db.services.connector_service import ConnectorService, SyncLogsService
-from api.utils.api_utils import get_data_error_result, get_json_result, validate_request
+from api.utils.api_utils import get_data_error_result, get_json_result, get_request_json, validate_request
 from common.constants import RetCode, TaskStatus
-from common.data_source.config import GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI, DocumentSource
+from common.data_source.config import GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI, GMAIL_WEB_OAUTH_REDIRECT_URI, BOX_WEB_OAUTH_REDIRECT_URI, DocumentSource
-from common.data_source.google_util.constant import GOOGLE_DRIVE_WEB_OAUTH_POPUP_TEMPLATE, GOOGLE_SCOPES
+from common.data_source.google_util.constant import WEB_OAUTH_POPUP_TEMPLATE, GOOGLE_SCOPES
 from common.misc_utils import get_uuid
 from rag.utils.redis_conn import REDIS_CONN
 from api.apps import login_required, current_user
+from box_sdk_gen import BoxOAuth, OAuthConfig, GetAuthorizeUrlOptions
 
 
 @manager.route("/set", methods=["POST"])  # noqa: F821
 @login_required
 async def set_connector():
-    req = await request.json
+    req = await get_request_json()
     if req.get("id"):
         conn = {fld: req[fld] for fld in ["prune_freq", "refresh_freq", "config", "timeout_secs"] if fld in req}
         ConnectorService.update_by_id(req["id"], conn)
@@ -90,7 +91,7 @@ def list_logs(connector_id):
 @manager.route("/<connector_id>/resume", methods=["PUT"])  # noqa: F821
 @login_required
 async def resume(connector_id):
-    req = await request.json
+    req = await get_request_json()
     if req.get("resume"):
         ConnectorService.resume(connector_id, TaskStatus.SCHEDULE)
     else:
@@ -102,7 +103,7 @@ async def resume(connector_id):
 @login_required
 @validate_request("kb_id")
 async def rebuild(connector_id):
-    req = await request.json
+    req = await get_request_json()
     err = ConnectorService.rebuild(req["kb_id"], connector_id, current_user.id)
     if err:
         return get_json_result(data=False, message=err, code=RetCode.SERVER_ERROR)
@@ -117,17 +118,27 @@ def rm_connector(connector_id):
     return get_json_result(data=True)
 
 
-GOOGLE_WEB_FLOW_STATE_PREFIX = "google_drive_web_flow_state"
-GOOGLE_WEB_FLOW_RESULT_PREFIX = "google_drive_web_flow_result"
 WEB_FLOW_TTL_SECS = 15 * 60
 
 
-def _web_state_cache_key(flow_id: str) -> str:
+def _web_state_cache_key(flow_id: str, source_type: str | None = None) -> str:
-    return f"{GOOGLE_WEB_FLOW_STATE_PREFIX}:{flow_id}"
+    """Return Redis key for web OAuth state.
+
+    The default prefix keeps backward compatibility for Google Drive.
+    When source_type == "gmail", a different prefix is used so that
+    Drive/Gmail flows don't clash in Redis.
+    """
+    prefix = f"{source_type}_web_flow_state"
+    return f"{prefix}:{flow_id}"
 
 
-def _web_result_cache_key(flow_id: str) -> str:
+def _web_result_cache_key(flow_id: str, source_type: str | None = None) -> str:
-    return f"{GOOGLE_WEB_FLOW_RESULT_PREFIX}:{flow_id}"
+    """Return Redis key for web OAuth result.
+
+    Mirrors _web_state_cache_key logic for result storage.
+    """
+    prefix = f"{source_type}_web_flow_result"
+    return f"{prefix}:{flow_id}"
 
 
 def _load_credentials(payload: str | dict[str, Any]) -> dict[str, Any]:
@@ -146,19 +157,24 @@ def _get_web_client_config(credentials: dict[str, Any]) -> dict[str, Any]:
     return {"web": web_section}
 
 
-async def _render_web_oauth_popup(flow_id: str, success: bool, message: str):
+async def _render_web_oauth_popup(flow_id: str, success: bool, message: str, source="drive"):
     status = "success" if success else "error"
     auto_close = "window.close();" if success else ""
     escaped_message = escape(message)
+    #   Drive: ragflow-google-drive-oauth
+    #   Gmail: ragflow-gmail-oauth
+    payload_type = f"ragflow-{source}-oauth"
     payload_json = json.dumps(
         {
-            "type": "ragflow-google-drive-oauth",
+            "type": payload_type,
             "status": status,
             "flowId": flow_id or "",
             "message": message,
         }
     )
-    html = GOOGLE_DRIVE_WEB_OAUTH_POPUP_TEMPLATE.format(
+    # TODO(google-oauth): title/heading/message may need to reflect drive/gmail based on cached type
+    html = WEB_OAUTH_POPUP_TEMPLATE.format(
+        title=f"Google {source.capitalize()} Authorization",
         heading="Authorization complete" if success else "Authorization failed",
         message=escaped_message,
         payload_json=payload_json,
@@ -169,20 +185,33 @@ async def _render_web_oauth_popup(flow_id: str, success: bool, message: str):
     return response
 
 
-@manager.route("/google-drive/oauth/web/start", methods=["POST"])  # noqa: F821
+@manager.route("/google/oauth/web/start", methods=["POST"])  # noqa: F821
 @login_required
 @validate_request("credentials")
-async def start_google_drive_web_oauth():
+async def start_google_web_oauth():
-    if not GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI:
+    source = request.args.get("type", "google-drive")
+    if source not in ("google-drive", "gmail"):
+        return get_json_result(code=RetCode.ARGUMENT_ERROR, message="Invalid Google OAuth type.")
+
+    if source == "gmail":
+        redirect_uri = GMAIL_WEB_OAUTH_REDIRECT_URI
+        scopes = GOOGLE_SCOPES[DocumentSource.GMAIL]
+    else:
+        redirect_uri = GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI
+        scopes = GOOGLE_SCOPES[DocumentSource.GOOGLE_DRIVE]
+
+    if not redirect_uri:
         return get_json_result(
             code=RetCode.SERVER_ERROR,
-            message="Google Drive OAuth redirect URI is not configured on the server.",
+            message="Google OAuth redirect URI is not configured on the server.",
         )
 
-    req = await request.json or {}
+    req = await get_request_json()
     raw_credentials = req.get("credentials", "")
+
     try:
         credentials = _load_credentials(raw_credentials)
+        print(credentials)
     except ValueError as exc:
         return get_json_result(code=RetCode.ARGUMENT_ERROR, message=str(exc))
 
@@ -199,8 +228,8 @@ async def start_google_drive_web_oauth():
 
     flow_id = str(uuid.uuid4())
     try:
-        flow = Flow.from_client_config(client_config, scopes=GOOGLE_SCOPES[DocumentSource.GOOGLE_DRIVE])
+        flow = Flow.from_client_config(client_config, scopes=scopes)
-        flow.redirect_uri = GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI
+        flow.redirect_uri = redirect_uri
         authorization_url, _ = flow.authorization_url(
             access_type="offline",
             include_granted_scopes="true",
@@ -219,7 +248,7 @@ async def start_google_drive_web_oauth():
         "client_config": client_config,
         "created_at": int(time.time()),
     }
-    REDIS_CONN.set_obj(_web_state_cache_key(flow_id), cache_payload, WEB_FLOW_TTL_SECS)
+    REDIS_CONN.set_obj(_web_state_cache_key(flow_id, source), cache_payload, WEB_FLOW_TTL_SECS)
 
     return get_json_result(
         data={
@@ -230,60 +259,115 @@ async def start_google_drive_web_oauth():
     )
 
 
-@manager.route("/google-drive/oauth/web/callback", methods=["GET"])  # noqa: F821
+@manager.route("/gmail/oauth/web/callback", methods=["GET"])  # noqa: F821
-async def google_drive_web_oauth_callback():
+async def google_gmail_web_oauth_callback():
     state_id = request.args.get("state")
     error = request.args.get("error")
+    source = "gmail"
+
     error_description = request.args.get("error_description") or error
 
     if not state_id:
-        return await _render_web_oauth_popup("", False, "Missing OAuth state parameter.")
+        return await _render_web_oauth_popup("", False, "Missing OAuth state parameter.", source)
 
-    state_cache = REDIS_CONN.get(_web_state_cache_key(state_id))
+    state_cache = REDIS_CONN.get(_web_state_cache_key(state_id, source))
     if not state_cache:
-        return await _render_web_oauth_popup(state_id, False, "Authorization session expired. Please restart from the main window.")
+        return await _render_web_oauth_popup(state_id, False, "Authorization session expired. Please restart from the main window.", source)
 
     state_obj = json.loads(state_cache)
     client_config = state_obj.get("client_config")
     if not client_config:
-        REDIS_CONN.delete(_web_state_cache_key(state_id))
+        REDIS_CONN.delete(_web_state_cache_key(state_id, source))
-        return await _render_web_oauth_popup(state_id, False, "Authorization session was invalid. Please retry.")
+        return await _render_web_oauth_popup(state_id, False, "Authorization session was invalid. Please retry.", source)
 
     if error:
-        REDIS_CONN.delete(_web_state_cache_key(state_id))
+        REDIS_CONN.delete(_web_state_cache_key(state_id, source))
-        return await _render_web_oauth_popup(state_id, False, error_description or "Authorization was cancelled.")
+        return await _render_web_oauth_popup(state_id, False, error_description or "Authorization was cancelled.", source)
 
     code = request.args.get("code")
     if not code:
-        return await _render_web_oauth_popup(state_id, False, "Missing authorization code from Google.")
+        return await _render_web_oauth_popup(state_id, False, "Missing authorization code from Google.", source)
 
     try:
-        flow = Flow.from_client_config(client_config, scopes=GOOGLE_SCOPES[DocumentSource.GOOGLE_DRIVE])
+        # TODO(google-oauth): branch scopes/redirect_uri based on source_type (drive vs gmail)
-        flow.redirect_uri = GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI
+        flow = Flow.from_client_config(client_config, scopes=GOOGLE_SCOPES[DocumentSource.GMAIL])
+        flow.redirect_uri = GMAIL_WEB_OAUTH_REDIRECT_URI
         flow.fetch_token(code=code)
     except Exception as exc:  # pragma: no cover - defensive
         logging.exception("Failed to exchange Google OAuth code: %s", exc)
-        REDIS_CONN.delete(_web_state_cache_key(state_id))
+        REDIS_CONN.delete(_web_state_cache_key(state_id, source))
-        return await _render_web_oauth_popup(state_id, False, "Failed to exchange tokens with Google. Please retry.")
+        return await _render_web_oauth_popup(state_id, False, "Failed to exchange tokens with Google. Please retry.", source)
 
     creds_json = flow.credentials.to_json()
     result_payload = {
         "user_id": state_obj.get("user_id"),
         "credentials": creds_json,
     }
-    REDIS_CONN.set_obj(_web_result_cache_key(state_id), result_payload, WEB_FLOW_TTL_SECS)
+    REDIS_CONN.set_obj(_web_result_cache_key(state_id, source), result_payload, WEB_FLOW_TTL_SECS)
-    REDIS_CONN.delete(_web_state_cache_key(state_id))
+    REDIS_CONN.delete(_web_state_cache_key(state_id, source))
 
-    return await _render_web_oauth_popup(state_id, True, "Authorization completed successfully.")
+    return await _render_web_oauth_popup(state_id, True, "Authorization completed successfully.", source)
 
 
-@manager.route("/google-drive/oauth/web/result", methods=["POST"])  # noqa: F821
+@manager.route("/google-drive/oauth/web/callback", methods=["GET"])  # noqa: F821
+async def google_drive_web_oauth_callback():
+    state_id = request.args.get("state")
+    error = request.args.get("error")
+    source = "google-drive"
+
+    error_description = request.args.get("error_description") or error
+
+    if not state_id:
+        return await _render_web_oauth_popup("", False, "Missing OAuth state parameter.", source)
+
+    state_cache = REDIS_CONN.get(_web_state_cache_key(state_id, source))
+    if not state_cache:
+        return await _render_web_oauth_popup(state_id, False, "Authorization session expired. Please restart from the main window.", source)
+
+    state_obj = json.loads(state_cache)
+    client_config = state_obj.get("client_config")
+    if not client_config:
+        REDIS_CONN.delete(_web_state_cache_key(state_id, source))
+        return await _render_web_oauth_popup(state_id, False, "Authorization session was invalid. Please retry.", source)
+
+    if error:
+        REDIS_CONN.delete(_web_state_cache_key(state_id, source))
+        return await _render_web_oauth_popup(state_id, False, error_description or "Authorization was cancelled.", source)
+
+    code = request.args.get("code")
+    if not code:
+        return await _render_web_oauth_popup(state_id, False, "Missing authorization code from Google.", source)
+
+    try:
+        # TODO(google-oauth): branch scopes/redirect_uri based on source_type (drive vs gmail)
+        flow = Flow.from_client_config(client_config, scopes=GOOGLE_SCOPES[DocumentSource.GOOGLE_DRIVE])
+        flow.redirect_uri = GOOGLE_DRIVE_WEB_OAUTH_REDIRECT_URI
+        flow.fetch_token(code=code)
+    except Exception as exc:  # pragma: no cover - defensive
+        logging.exception("Failed to exchange Google OAuth code: %s", exc)
+        REDIS_CONN.delete(_web_state_cache_key(state_id, source))
+        return await _render_web_oauth_popup(state_id, False, "Failed to exchange tokens with Google. Please retry.", source)
+
+    creds_json = flow.credentials.to_json()
+    result_payload = {
+        "user_id": state_obj.get("user_id"),
+        "credentials": creds_json,
+    }
+    REDIS_CONN.set_obj(_web_result_cache_key(state_id, source), result_payload, WEB_FLOW_TTL_SECS)
+    REDIS_CONN.delete(_web_state_cache_key(state_id, source))
+
+    return await _render_web_oauth_popup(state_id, True, "Authorization completed successfully.", source)
+
+@manager.route("/google/oauth/web/result", methods=["POST"])  # noqa: F821
 @login_required
 @validate_request("flow_id")
-async def poll_google_drive_web_result():
+async def poll_google_web_result():
     req = await request.json or {}
+    source = request.args.get("type")
+    if source not in ("google-drive", "gmail"):
+        return get_json_result(code=RetCode.ARGUMENT_ERROR, message="Invalid Google OAuth type.")
     flow_id = req.get("flow_id")
-    cache_raw = REDIS_CONN.get(_web_result_cache_key(flow_id))
+    cache_raw = REDIS_CONN.get(_web_result_cache_key(flow_id, source))
     if not cache_raw:
         return get_json_result(code=RetCode.RUNNING, message="Authorization is still pending.")
 
@@ -291,5 +375,109 @@ async def poll_google_drive_web_result():
     if result.get("user_id") != current_user.id:
         return get_json_result(code=RetCode.PERMISSION_ERROR, message="You are not allowed to access this authorization result.")
 
-    REDIS_CONN.delete(_web_result_cache_key(flow_id))
+    REDIS_CONN.delete(_web_result_cache_key(flow_id, source))
     return get_json_result(data={"credentials": result.get("credentials")})
+
+@manager.route("/box/oauth/web/start", methods=["POST"])  # noqa: F821
+@login_required
+async def start_box_web_oauth():
+    req = await get_request_json()
+
+    client_id = req.get("client_id")
+    client_secret = req.get("client_secret")    
+    redirect_uri = req.get("redirect_uri", BOX_WEB_OAUTH_REDIRECT_URI)
+
+    if not client_id or not client_secret:
+        return get_json_result(code=RetCode.ARGUMENT_ERROR, message="Box client_id and client_secret are required.")
+
+    flow_id = str(uuid.uuid4())
+
+    box_auth = BoxOAuth(
+        OAuthConfig(
+            client_id=client_id,
+            client_secret=client_secret,
+        )
+    )
+
+    auth_url = box_auth.get_authorize_url(
+        options=GetAuthorizeUrlOptions(
+            redirect_uri=redirect_uri,
+            state=flow_id,
+        )
+    )
+
+    cache_payload = {
+        "user_id": current_user.id,
+        "auth_url": auth_url,
+        "client_id": client_id,
+        "client_secret": client_secret,
+        "created_at": int(time.time()),
+    }
+    REDIS_CONN.set_obj(_web_state_cache_key(flow_id, "box"), cache_payload, WEB_FLOW_TTL_SECS)
+    return get_json_result(
+        data = {
+            "flow_id": flow_id,
+            "authorization_url": auth_url,
+            "expires_in": WEB_FLOW_TTL_SECS,}
+    )
+
+@manager.route("/box/oauth/web/callback", methods=["GET"])  # noqa: F821
+async def box_web_oauth_callback():
+    flow_id = request.args.get("state")
+    if not flow_id:
+        return await _render_web_oauth_popup("", False, "Missing OAuth parameters.", "box")
+    
+    code = request.args.get("code")
+    if not code:
+        return await _render_web_oauth_popup(flow_id, False, "Missing authorization code from Box.", "box")
+
+    cache_payload = json.loads(REDIS_CONN.get(_web_state_cache_key(flow_id, "box")))
+    if not cache_payload:
+        return get_json_result(code=RetCode.ARGUMENT_ERROR, message="Box OAuth session expired or invalid.")
+
+    error = request.args.get("error")
+    error_description = request.args.get("error_description") or error
+    if error:
+        REDIS_CONN.delete(_web_state_cache_key(flow_id, "box"))
+        return await _render_web_oauth_popup(flow_id, False, error_description or "Authorization failed.", "box")
+    
+    auth = BoxOAuth(
+        OAuthConfig(
+            client_id=cache_payload.get("client_id"),
+            client_secret=cache_payload.get("client_secret"),
+        )
+    )
+
+    auth.get_tokens_authorization_code_grant(code)
+    token = auth.retrieve_token()
+    result_payload = {
+        "user_id": cache_payload.get("user_id"),
+        "client_id": cache_payload.get("client_id"),
+        "client_secret": cache_payload.get("client_secret"),
+        "access_token": token.access_token,
+        "refresh_token": token.refresh_token,
+    }
+
+    REDIS_CONN.set_obj(_web_result_cache_key(flow_id, "box"), result_payload, WEB_FLOW_TTL_SECS)
+    REDIS_CONN.delete(_web_state_cache_key(flow_id, "box"))
+
+    return await _render_web_oauth_popup(flow_id, True, "Authorization completed successfully.", "box")
+
+@manager.route("/box/oauth/web/result", methods=["POST"])  # noqa: F821
+@login_required
+@validate_request("flow_id")
+async def poll_box_web_result():
+    req = await get_request_json()
+    flow_id = req.get("flow_id")
+
+    cache_blob = REDIS_CONN.get(_web_result_cache_key(flow_id, "box"))
+    if not cache_blob:
+        return get_json_result(code=RetCode.RUNNING, message="Authorization is still pending.")
+
+    cache_raw = json.loads(cache_blob)
+    if cache_raw.get("user_id") != current_user.id:
+        return get_json_result(code=RetCode.PERMISSION_ERROR, message="You are not allowed to access this authorization result.")
+    
+    REDIS_CONN.delete(_web_result_cache_key(flow_id, "box"))
+
+    return get_json_result(data={"credentials": cache_raw})

api/apps/conversation_app.py

@@ -14,19 +14,21 @@
 #  limitations under the License.
 #
 import json
+import os
 import re
 import logging
 from copy import deepcopy
+import tempfile
 from quart import Response, request
 from api.apps import current_user, login_required
 from api.db.db_models import APIToken
 from api.db.services.conversation_service import ConversationService, structure_answer
-from api.db.services.dialog_service import DialogService, ask, chat, gen_mindmap
+from api.db.services.dialog_service import DialogService, async_ask, async_chat, gen_mindmap
 from api.db.services.llm_service import LLMBundle
 from api.db.services.search_service import SearchService
 from api.db.services.tenant_llm_service import TenantLLMService
 from api.db.services.user_service import TenantService, UserTenantService
-from api.utils.api_utils import get_data_error_result, get_json_result, server_error_response, validate_request
+from api.utils.api_utils import get_data_error_result, get_json_result, get_request_json, server_error_response, validate_request
 from rag.prompts.template import load_prompt
 from rag.prompts.generator import chunks_format
 from common.constants import RetCode, LLMType
@@ -35,7 +37,7 @@ from common.constants import RetCode, LLMType
 @manager.route("/set", methods=["POST"])  # noqa: F821
 @login_required
 async def set_conversation():
-    req = await request.json
+    req = await get_request_json()
     conv_id = req.get("conversation_id")
     is_new = req.get("is_new")
     name = req.get("name", "New conversation")
@@ -78,7 +80,7 @@ async def set_conversation():
 
 @manager.route("/get", methods=["GET"])  # noqa: F821
 @login_required
-def get():
+async def get():
     conv_id = request.args["conversation_id"]
     try:
         e, conv = ConversationService.get_by_id(conv_id)
@@ -129,7 +131,7 @@ def getsse(dialog_id):
 @manager.route("/rm", methods=["POST"])  # noqa: F821
 @login_required
 async def rm():
-    req = await request.json
+    req = await get_request_json()
     conv_ids = req["conversation_ids"]
     try:
         for cid in conv_ids:
@@ -150,7 +152,7 @@ async def rm():
 
 @manager.route("/list", methods=["GET"])  # noqa: F821
 @login_required
-def list_conversation():
+async def list_conversation():
     dialog_id = request.args["dialog_id"]
     try:
         if not DialogService.query(tenant_id=current_user.id, id=dialog_id):
@@ -167,7 +169,7 @@ def list_conversation():
 @login_required
 @validate_request("conversation_id", "messages")
 async def completion():
-    req = await request.json
+    req = await get_request_json()
     msg = []
     for m in req["messages"]:
         if m["role"] == "system":
@@ -216,10 +218,10 @@ async def completion():
             dia.llm_setting = chat_model_config
 
         is_embedded = bool(chat_model_id)
-        def stream():
+        async def stream():
             nonlocal dia, msg, req, conv
             try:
-                for ans in chat(dia, msg, True, **req):
+                async for ans in async_chat(dia, msg, True, **req):
                     ans = structure_answer(conv, ans, message_id, conv.id)
                     yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
                 if not is_embedded:
@@ -239,7 +241,7 @@ async def completion():
 
         else:
             answer = None
-            for ans in chat(dia, msg, **req):
+            async for ans in async_chat(dia, msg, **req):
                 answer = structure_answer(conv, ans, message_id, conv.id)
                 if not is_embedded:
                     ConversationService.update_by_id(conv.id, conv.to_dict())
@@ -248,11 +250,69 @@ async def completion():
     except Exception as e:
         return server_error_response(e)
 
+@manager.route("/sequence2txt", methods=["POST"])  # noqa: F821
+@login_required
+async def sequence2txt():
+    req = await request.form
+    stream_mode = req.get("stream", "false").lower() == "true"
+    files = await request.files
+    if "file" not in files:
+        return get_data_error_result(message="Missing 'file' in multipart form-data")
+
+    uploaded = files["file"]
+
+    ALLOWED_EXTS = {
+        ".wav", ".mp3", ".m4a", ".aac",
+        ".flac", ".ogg", ".webm",
+        ".opus", ".wma"
+    }
+
+    filename = uploaded.filename or ""
+    suffix = os.path.splitext(filename)[-1].lower()
+    if suffix not in ALLOWED_EXTS:
+        return get_data_error_result(message=
+            f"Unsupported audio format: {suffix}. "
+            f"Allowed: {', '.join(sorted(ALLOWED_EXTS))}"
+        )
+    fd, temp_audio_path = tempfile.mkstemp(suffix=suffix)
+    os.close(fd)
+    await uploaded.save(temp_audio_path)
+
+    tenants = TenantService.get_info_by(current_user.id)
+    if not tenants:
+        return get_data_error_result(message="Tenant not found!")
+
+    asr_id = tenants[0]["asr_id"]
+    if not asr_id:
+        return get_data_error_result(message="No default ASR model is set")
+
+    asr_mdl=LLMBundle(tenants[0]["tenant_id"], LLMType.SPEECH2TEXT, asr_id)
+    if not stream_mode:
+        text = asr_mdl.transcription(temp_audio_path)
+        try:
+            os.remove(temp_audio_path)
+        except Exception as e:
+            logging.error(f"Failed to remove temp audio file: {str(e)}")
+        return get_json_result(data={"text": text})
+    async def event_stream():
+        try:
+            for evt in asr_mdl.stream_transcription(temp_audio_path):
+                yield f"data: {json.dumps(evt, ensure_ascii=False)}\n\n"
+        except Exception as e:
+            err = {"event": "error", "text": str(e)}
+            yield f"data: {json.dumps(err, ensure_ascii=False)}\n\n"
+        finally:
+            try:
+                os.remove(temp_audio_path)
+            except Exception as e:
+                logging.error(f"Failed to remove temp audio file: {str(e)}")
+
+    return Response(event_stream(), content_type="text/event-stream")
 
 @manager.route("/tts", methods=["POST"])  # noqa: F821
 @login_required
 async def tts():
-    req = await request.json
+    req = await get_request_json()
     text = req["text"]
 
     tenants = TenantService.get_info_by(current_user.id)
@@ -285,7 +345,7 @@ async def tts():
 @login_required
 @validate_request("conversation_id", "message_id")
 async def delete_msg():
-    req = await request.json
+    req = await get_request_json()
     e, conv = ConversationService.get_by_id(req["conversation_id"])
     if not e:
         return get_data_error_result(message="Conversation not found!")
@@ -308,7 +368,7 @@ async def delete_msg():
 @login_required
 @validate_request("conversation_id", "message_id")
 async def thumbup():
-    req = await request.json
+    req = await get_request_json()
     e, conv = ConversationService.get_by_id(req["conversation_id"])
     if not e:
         return get_data_error_result(message="Conversation not found!")
@@ -335,7 +395,7 @@ async def thumbup():
 @login_required
 @validate_request("question", "kb_ids")
 async def ask_about():
-    req = await request.json
+    req = await get_request_json()
     uid = current_user.id
 
     search_id = req.get("search_id", "")
@@ -346,10 +406,10 @@ async def ask_about():
     if search_app:
         search_config = search_app.get("search_config", {})
 
-    def stream():
+    async def stream():
         nonlocal req, uid
         try:
-            for ans in ask(req["question"], req["kb_ids"], uid, search_config=search_config):
+            async for ans in async_ask(req["question"], req["kb_ids"], uid, search_config=search_config):
                 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"
@@ -367,7 +427,7 @@ async def ask_about():
 @login_required
 @validate_request("question", "kb_ids")
 async def mindmap():
-    req = await request.json
+    req = await get_request_json()
     search_id = req.get("search_id", "")
     search_app = SearchService.get_detail(search_id) if search_id else {}
     search_config = search_app.get("search_config", {}) if search_app else {}
@@ -375,7 +435,7 @@ async def mindmap():
     kb_ids.extend(req["kb_ids"])
     kb_ids = list(set(kb_ids))
 
-    mind_map = gen_mindmap(req["question"], kb_ids, search_app.get("tenant_id", current_user.id), search_config)
+    mind_map = await gen_mindmap(req["question"], kb_ids, search_app.get("tenant_id", current_user.id), search_config)
     if "error" in mind_map:
         return server_error_response(Exception(mind_map["error"]))
     return get_json_result(data=mind_map)
@@ -385,7 +445,7 @@ async def mindmap():
 @login_required
 @validate_request("question")
 async def related_questions():
-    req = await request.json
+    req = await get_request_json()
 
     search_id = req.get("search_id", "")
     search_config = {}
@@ -402,7 +462,7 @@ async def related_questions():
     if "parameter" in gen_conf:
         del gen_conf["parameter"]
     prompt = load_prompt("related_question")
-    ans = chat_mdl.chat(
+    ans = await chat_mdl.async_chat(
         prompt,
         [
             {

api/apps/dialog_app.py

@@ -21,10 +21,9 @@ from common.constants import StatusEnum
 from api.db.services.tenant_llm_service import TenantLLMService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 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 get_data_error_result, get_json_result, get_request_json, server_error_response, validate_request
 from common.misc_utils import get_uuid
 from common.constants import RetCode
-from api.utils.api_utils import get_json_result
 from api.apps import login_required, current_user
 
 
@@ -32,7 +31,7 @@ from api.apps import login_required, current_user
 @validate_request("prompt_config")
 @login_required
 async def set_dialog():
-    req = await request.json
+    req = await get_request_json()
     dialog_id = req.get("dialog_id", "")
     is_create = not dialog_id
     name = req.get("name", "New Dialog")
@@ -66,7 +65,7 @@ async def set_dialog():
 
     if not is_create:
         if not req.get("kb_ids", []) and not prompt_config.get("tavily_api_key") and "{knowledge}" in prompt_config['system']:
-            return get_data_error_result(message="Please remove `{knowledge}` in system prompt since no knowledge base / Tavily used here.")
+            return get_data_error_result(message="Please remove `{knowledge}` in system prompt since no dataset / Tavily used here.")
 
         for p in prompt_config["parameters"]:
             if p["optional"]:
@@ -181,7 +180,7 @@ async def list_dialogs_next():
     else:
         desc = True
 
-    req = await request.get_json()
+    req = await get_request_json()
     owner_ids = req.get("owner_ids", [])
     try:
         if not owner_ids:
@@ -209,7 +208,7 @@ async def list_dialogs_next():
 @login_required
 @validate_request("dialog_ids")
 async def rm():
-    req = await request.json
+    req = await get_request_json()
     dialog_list=[]
     tenants = UserTenantService.query(user_id=current_user.id)
     try:

api/apps/document_app.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License
 #
+import asyncio
 import json
 import os.path
 import pathlib
@@ -26,6 +27,7 @@ from api.db import VALID_FILE_TYPES, FileType
 from api.db.db_models import Task
 from api.db.services import duplicate_name
 from api.db.services.document_service import DocumentService, doc_upload_and_parse
+from common.metadata_utils import meta_filter, convert_conditions
 from api.db.services.file2document_service import File2DocumentService
 from api.db.services.file_service import FileService
 from api.db.services.knowledgebase_service import KnowledgebaseService
@@ -36,7 +38,7 @@ from api.utils.api_utils import (
     get_data_error_result,
     get_json_result,
     server_error_response,
-    validate_request, request_json,
+    validate_request, get_request_json,
 )
 from api.utils.file_utils import filename_type, thumbnail
 from common.file_utils import get_project_base_directory
@@ -68,11 +70,11 @@ async def upload():
 
     e, kb = KnowledgebaseService.get_by_id(kb_id)
     if not e:
-        raise LookupError("Can't find this knowledgebase!")
+        raise LookupError("Can't find this dataset!")
     if not check_kb_team_permission(kb, current_user.id):
         return get_json_result(data=False, message="No authorization.", code=RetCode.AUTHENTICATION_ERROR)
 
-    err, files = FileService.upload_document(kb, file_objs, current_user.id)
+    err, files = await asyncio.to_thread(FileService.upload_document, kb, file_objs, current_user.id)
     if err:
         return get_json_result(data=files, message="\n".join(err), code=RetCode.SERVER_ERROR)
 
@@ -97,7 +99,7 @@ async def web_crawl():
         return get_json_result(data=False, message="The URL format is invalid", code=RetCode.ARGUMENT_ERROR)
     e, kb = KnowledgebaseService.get_by_id(kb_id)
     if not e:
-        raise LookupError("Can't find this knowledgebase!")
+        raise LookupError("Can't find this dataset!")
     if check_kb_team_permission(kb, current_user.id):
         return get_json_result(data=False, message="No authorization.", code=RetCode.AUTHENTICATION_ERROR)
 
@@ -153,7 +155,7 @@ async def web_crawl():
 @login_required
 @validate_request("name", "kb_id")
 async def create():
-    req = await request_json()
+    req = await get_request_json()
     kb_id = req["kb_id"]
     if not kb_id:
         return get_json_result(data=False, message='Lack of "KB ID"', code=RetCode.ARGUMENT_ERROR)
@@ -167,10 +169,10 @@ async def create():
     try:
         e, kb = KnowledgebaseService.get_by_id(kb_id)
         if not e:
-            return get_data_error_result(message="Can't find this knowledgebase!")
+            return get_data_error_result(message="Can't find this dataset!")
 
         if DocumentService.query(name=req["name"], kb_id=kb_id):
-            return get_data_error_result(message="Duplicated document name in the same knowledgebase.")
+            return get_data_error_result(message="Duplicated document name in the same dataset.")
 
         kb_root_folder = FileService.get_kb_folder(kb.tenant_id)
         if not kb_root_folder:
@@ -217,7 +219,7 @@ async def list_docs():
         if KnowledgebaseService.query(tenant_id=tenant.tenant_id, id=kb_id):
             break
     else:
-        return get_json_result(data=False, message="Only owner of knowledgebase authorized for this operation.", code=RetCode.OPERATING_ERROR)
+        return get_json_result(data=False, message="Only owner of dataset authorized for this operation.", code=RetCode.OPERATING_ERROR)
     keywords = request.args.get("keywords", "")
 
     page_number = int(request.args.get("page", 0))
@@ -230,7 +232,7 @@ async def list_docs():
     create_time_from = int(request.args.get("create_time_from", 0))
     create_time_to = int(request.args.get("create_time_to", 0))
 
-    req = await request.get_json()
+    req = await get_request_json()
 
     run_status = req.get("run_status", [])
     if run_status:
@@ -245,9 +247,19 @@ async def list_docs():
             return get_data_error_result(message=f"Invalid filter conditions: {', '.join(invalid_types)} type{'s' if len(invalid_types) > 1 else ''}")
 
     suffix = req.get("suffix", [])
+    metadata_condition = req.get("metadata_condition", {}) or {}
+    if metadata_condition and not isinstance(metadata_condition, dict):
+        return get_data_error_result(message="metadata_condition must be an object.")
+
+    doc_ids_filter = None
+    if metadata_condition:
+        metas = DocumentService.get_flatted_meta_by_kbs([kb_id])
+        doc_ids_filter = meta_filter(metas, convert_conditions(metadata_condition), metadata_condition.get("logic", "and"))
+        if metadata_condition.get("conditions") and not doc_ids_filter:
+            return get_json_result(data={"total": 0, "docs": []})
 
     try:
-        docs, tol = DocumentService.get_by_kb_id(kb_id, page_number, items_per_page, orderby, desc, keywords, run_status, types, suffix)
+        docs, tol = DocumentService.get_by_kb_id(kb_id, page_number, items_per_page, orderby, desc, keywords, run_status, types, suffix, doc_ids_filter)
 
         if create_time_from or create_time_to:
             filtered_docs = []
@@ -271,7 +283,7 @@ async def list_docs():
 @manager.route("/filter", methods=["POST"])  # noqa: F821
 @login_required
 async def get_filter():
-    req = await request.get_json()
+    req = await get_request_json()
 
     kb_id = req.get("kb_id")
     if not kb_id:
@@ -281,7 +293,7 @@ async def get_filter():
         if KnowledgebaseService.query(tenant_id=tenant.tenant_id, id=kb_id):
             break
     else:
-        return get_json_result(data=False, message="Only owner of knowledgebase authorized for this operation.", code=RetCode.OPERATING_ERROR)
+        return get_json_result(data=False, message="Only owner of dataset authorized for this operation.", code=RetCode.OPERATING_ERROR)
 
     keywords = req.get("keywords", "")
 
@@ -309,7 +321,7 @@ async def get_filter():
 @manager.route("/infos", methods=["POST"])  # noqa: F821
 @login_required
 async def doc_infos():
-    req = await request_json()
+    req = await get_request_json()
     doc_ids = req["doc_ids"]
     for doc_id in doc_ids:
         if not DocumentService.accessible(doc_id, current_user.id):
@@ -318,6 +330,87 @@ async def doc_infos():
     return get_json_result(data=list(docs.dicts()))
 
 
+@manager.route("/metadata/summary", methods=["POST"])  # noqa: F821
+@login_required
+async def metadata_summary():
+    req = await get_request_json()
+    kb_id = req.get("kb_id")
+    if not kb_id:
+        return get_json_result(data=False, message='Lack of "KB ID"', code=RetCode.ARGUMENT_ERROR)
+
+    tenants = UserTenantService.query(user_id=current_user.id)
+    for tenant in tenants:
+        if KnowledgebaseService.query(tenant_id=tenant.tenant_id, id=kb_id):
+            break
+    else:
+        return get_json_result(data=False, message="Only owner of dataset authorized for this operation.", code=RetCode.OPERATING_ERROR)
+
+    try:
+        summary = DocumentService.get_metadata_summary(kb_id)
+        return get_json_result(data={"summary": summary})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route("/metadata/update", methods=["POST"])  # noqa: F821
+@login_required
+async def metadata_update():
+    req = await get_request_json()
+    kb_id = req.get("kb_id")
+    if not kb_id:
+        return get_json_result(data=False, message='Lack of "KB ID"', code=RetCode.ARGUMENT_ERROR)
+
+    tenants = UserTenantService.query(user_id=current_user.id)
+    for tenant in tenants:
+        if KnowledgebaseService.query(tenant_id=tenant.tenant_id, id=kb_id):
+            break
+    else:
+        return get_json_result(data=False, message="Only owner of dataset authorized for this operation.", code=RetCode.OPERATING_ERROR)
+
+    selector = req.get("selector", {}) or {}
+    updates = req.get("updates", []) or []
+    deletes = req.get("deletes", []) or []
+
+    if not isinstance(selector, dict):
+        return get_json_result(data=False, message="selector must be an object.", code=RetCode.ARGUMENT_ERROR)
+    if not isinstance(updates, list) or not isinstance(deletes, list):
+        return get_json_result(data=False, message="updates and deletes must be lists.", code=RetCode.ARGUMENT_ERROR)
+
+    metadata_condition = selector.get("metadata_condition", {}) or {}
+    if metadata_condition and not isinstance(metadata_condition, dict):
+        return get_json_result(data=False, message="metadata_condition must be an object.", code=RetCode.ARGUMENT_ERROR)
+
+    document_ids = selector.get("document_ids", []) or []
+    if document_ids and not isinstance(document_ids, list):
+        return get_json_result(data=False, message="document_ids must be a list.", code=RetCode.ARGUMENT_ERROR)
+
+    for upd in updates:
+        if not isinstance(upd, dict) or not upd.get("key") or "value" not in upd:
+            return get_json_result(data=False, message="Each update requires key and value.", code=RetCode.ARGUMENT_ERROR)
+    for d in deletes:
+        if not isinstance(d, dict) or not d.get("key"):
+            return get_json_result(data=False, message="Each delete requires key.", code=RetCode.ARGUMENT_ERROR)
+
+    kb_doc_ids = KnowledgebaseService.list_documents_by_ids([kb_id])
+    target_doc_ids = set(kb_doc_ids)
+    if document_ids:
+        invalid_ids = set(document_ids) - set(kb_doc_ids)
+        if invalid_ids:
+            return get_json_result(data=False, message=f"These documents do not belong to dataset {kb_id}: {', '.join(invalid_ids)}", code=RetCode.ARGUMENT_ERROR)
+        target_doc_ids = set(document_ids)
+
+    if metadata_condition:
+        metas = DocumentService.get_flatted_meta_by_kbs([kb_id])
+        filtered_ids = set(meta_filter(metas, convert_conditions(metadata_condition), metadata_condition.get("logic", "and")))
+        target_doc_ids = target_doc_ids & filtered_ids
+        if metadata_condition.get("conditions") and not target_doc_ids:
+            return get_json_result(data={"updated": 0, "matched_docs": 0})
+
+    target_doc_ids = list(target_doc_ids)
+    updated = DocumentService.batch_update_metadata(kb_id, target_doc_ids, updates, deletes)
+    return get_json_result(data={"updated": updated, "matched_docs": len(target_doc_ids)})
+
+
 @manager.route("/thumbnails", methods=["GET"])  # noqa: F821
 # @login_required
 def thumbnails():
@@ -341,7 +434,7 @@ def thumbnails():
 @login_required
 @validate_request("doc_ids", "status")
 async def change_status():
-    req = await request.get_json()
+    req = await get_request_json()
     doc_ids = req.get("doc_ids", [])
     status = str(req.get("status", ""))
 
@@ -361,7 +454,7 @@ async def change_status():
                 continue
             e, kb = KnowledgebaseService.get_by_id(doc.kb_id)
             if not e:
-                result[doc_id] = {"error": "Can't find this knowledgebase!"}
+                result[doc_id] = {"error": "Can't find this dataset!"}
                 continue
             if not DocumentService.update_by_id(doc_id, {"status": str(status)}):
                 result[doc_id] = {"error": "Database error (Document update)!"}
@@ -381,7 +474,7 @@ async def change_status():
 @login_required
 @validate_request("doc_id")
 async def rm():
-    req = await request_json()
+    req = await get_request_json()
     doc_ids = req["doc_id"]
     if isinstance(doc_ids, str):
         doc_ids = [doc_ids]
@@ -390,7 +483,7 @@ async def rm():
         if not DocumentService.accessible4deletion(doc_id, current_user.id):
             return get_json_result(data=False, message="No authorization.", code=RetCode.AUTHENTICATION_ERROR)
 
-    errors = FileService.delete_docs(doc_ids, current_user.id)
+    errors = await asyncio.to_thread(FileService.delete_docs, doc_ids, current_user.id)
 
     if errors:
         return get_json_result(data=False, message=errors, code=RetCode.SERVER_ERROR)
@@ -402,11 +495,13 @@ async def rm():
 @login_required
 @validate_request("doc_ids", "run")
 async def run():
-    req = await request_json()
+    req = await get_request_json()
+    try:
+        def _run_sync():
             for doc_id in req["doc_ids"]:
                 if not DocumentService.accessible(doc_id, current_user.id):
                     return get_json_result(data=False, message="No authorization.", code=RetCode.AUTHENTICATION_ERROR)
-    try:
+
             kb_table_num_map = {}
             for id in req["doc_ids"]:
                 info = {"run": str(req["run"]), "progress": 0}
@@ -437,10 +532,12 @@ async def run():
                         settings.docStoreConn.delete({"doc_id": id}, search.index_name(tenant_id), doc.kb_id)
 
                 if str(req["run"]) == TaskStatus.RUNNING.value:
-                doc = doc.to_dict()
+                    doc_dict = doc.to_dict()
-                DocumentService.run(tenant_id, doc, kb_table_num_map)
+                    DocumentService.run(tenant_id, doc_dict, kb_table_num_map)
 
             return get_json_result(data=True)
+
+        return await asyncio.to_thread(_run_sync)
     except Exception as e:
         return server_error_response(e)
 
@@ -449,10 +546,12 @@ async def run():
 @login_required
 @validate_request("doc_id", "name")
 async def rename():
-    req = await request_json()
+    req = await get_request_json()
+    try:
+        def _rename_sync():
             if not DocumentService.accessible(req["doc_id"], current_user.id):
                 return get_json_result(data=False, message="No authorization.", code=RetCode.AUTHENTICATION_ERROR)
-    try:
+
             e, doc = DocumentService.get_by_id(req["doc_id"])
             if not e:
                 return get_data_error_result(message="Document not found!")
@@ -463,7 +562,7 @@ async def rename():
 
             for d in DocumentService.query(name=req["name"], kb_id=doc.kb_id):
                 if d.name == req["name"]:
-                return get_data_error_result(message="Duplicated document name in the same knowledgebase.")
+                    return get_data_error_result(message="Duplicated document name in the same dataset.")
 
             if not DocumentService.update_by_id(req["doc_id"], {"name": req["name"]}):
                 return get_data_error_result(message="Database error (Document rename)!")
@@ -487,8 +586,10 @@ async def rename():
                     search.index_name(tenant_id),
                     doc.kb_id,
                 )
-
             return get_json_result(data=True)
+
+        return await asyncio.to_thread(_rename_sync)
+
     except Exception as e:
         return server_error_response(e)
 
@@ -502,7 +603,8 @@ async def get(doc_id):
             return get_data_error_result(message="Document not found!")
 
         b, n = File2DocumentService.get_storage_address(doc_id=doc_id)
-        response = await make_response(settings.STORAGE_IMPL.get(b, n))
+        data = await asyncio.to_thread(settings.STORAGE_IMPL.get, b, n)
+        response = await make_response(data)
 
         ext = re.search(r"\.([^.]+)$", doc.name.lower())
         ext = ext.group(1) if ext else None
@@ -523,8 +625,7 @@ async def get(doc_id):
 async def download_attachment(attachment_id):
     try:
         ext = request.args.get("ext", "markdown")
-        data = settings.STORAGE_IMPL.get(current_user.id, attachment_id)
+        data = await asyncio.to_thread(settings.STORAGE_IMPL.get, current_user.id, attachment_id)
-        # data = settings.STORAGE_IMPL.get("eb500d50bb0411f0907561d2782adda5", attachment_id)
         response = await make_response(data)
         response.headers.set("Content-Type", CONTENT_TYPE_MAP.get(ext, f"application/{ext}"))
 
@@ -539,7 +640,7 @@ async def download_attachment(attachment_id):
 @validate_request("doc_id")
 async def change_parser():
 
-    req = await request_json()
+    req = await get_request_json()
     if not DocumentService.accessible(req["doc_id"], current_user.id):
         return get_json_result(data=False, message="No authorization.", code=RetCode.AUTHENTICATION_ERROR)
 
@@ -596,7 +697,8 @@ async def get_image(image_id):
         if len(arr) != 2:
             return get_data_error_result(message="Image not found.")
         bkt, nm = image_id.split("-")
-        response = await make_response(settings.STORAGE_IMPL.get(bkt, nm))
+        data = await asyncio.to_thread(settings.STORAGE_IMPL.get, bkt, nm)
+        response = await make_response(data)
         response.headers.set("Content-Type", "image/JPEG")
         return response
     except Exception as e:
@@ -607,7 +709,7 @@ async def get_image(image_id):
 @login_required
 @validate_request("conversation_id")
 async def upload_and_parse():
-    files = await request.file
+    files = await request.files
     if "file" not in files:
         return get_json_result(data=False, message="No file part!", code=RetCode.ARGUMENT_ERROR)
 
@@ -624,7 +726,8 @@ async def upload_and_parse():
 @manager.route("/parse", methods=["POST"])  # noqa: F821
 @login_required
 async def parse():
-    url = await request.json.get("url") if await request.json else ""
+    req = await get_request_json()
+    url = req.get("url", "")
     if url:
         if not is_valid_url(url):
             return get_json_result(data=False, message="The URL format is invalid", code=RetCode.ARGUMENT_ERROR)
@@ -679,7 +782,7 @@ async def parse():
 @login_required
 @validate_request("doc_id", "meta")
 async def set_meta():
-    req = await request_json()
+    req = await get_request_json()
     if not DocumentService.accessible(req["doc_id"], current_user.id):
         return get_json_result(data=False, message="No authorization.", code=RetCode.AUTHENTICATION_ERROR)
     try:
@@ -687,7 +790,10 @@ async def set_meta():
         if not isinstance(meta, dict):
             return get_json_result(data=False, message="Only dictionary type supported.", code=RetCode.ARGUMENT_ERROR)
         for k, v in meta.items():
-            if not isinstance(v, str) and not isinstance(v, int) and not isinstance(v, float):
+            if isinstance(v, list):
+                if not all(isinstance(i, (str, int, float)) for i in v):
+                    return get_json_result(data=False, message=f"The type is not supported in list: {v}", code=RetCode.ARGUMENT_ERROR)
+            elif not isinstance(v, (str, int, float)):
                 return get_json_result(data=False, message=f"The type is not supported: {v}", code=RetCode.ARGUMENT_ERROR)
     except Exception as e:
         return get_json_result(data=False, message=f"Json syntax error: {e}", code=RetCode.ARGUMENT_ERROR)
@@ -705,3 +811,13 @@ async def set_meta():
         return get_json_result(data=True)
     except Exception as e:
         return server_error_response(e)
+
+
+@manager.route("/upload_info", methods=["POST"])  # noqa: F821
+async def upload_info():
+    files = await request.files
+    file = files['file'] if files and files.get("file") else None
+    try:
+        return get_json_result(data=FileService.upload_info(current_user.id, file, request.args.get("url")))
+    except Exception as e:
+        return  server_error_response(e)

api/apps/evaluation_app.py

@@ -0,0 +1,479 @@
+#
+#  Copyright 2025 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.
+#
+
+"""
+RAG Evaluation API Endpoints
+
+Provides REST API for RAG evaluation functionality including:
+- Dataset management
+- Test case management
+- Evaluation execution
+- Results retrieval
+- Configuration recommendations
+"""
+
+from quart import request
+from api.apps import login_required, current_user
+from api.db.services.evaluation_service import EvaluationService
+from api.utils.api_utils import (
+    get_data_error_result,
+    get_json_result,
+    get_request_json,
+    server_error_response,
+    validate_request
+)
+from common.constants import RetCode
+
+
+# ==================== Dataset Management ====================
+
+@manager.route('/dataset/create', methods=['POST'])  # noqa: F821
+@login_required
+@validate_request("name", "kb_ids")
+async def create_dataset():
+    """
+    Create a new evaluation dataset.
+    
+    Request body:
+    {
+        "name": "Dataset name",
+        "description": "Optional description",
+        "kb_ids": ["kb_id1", "kb_id2"]
+    }
+    """
+    try:
+        req = await get_request_json()
+        name = req.get("name", "").strip()
+        description = req.get("description", "")
+        kb_ids = req.get("kb_ids", [])
+        
+        if not name:
+            return get_data_error_result(message="Dataset name cannot be empty")
+        
+        if not kb_ids or not isinstance(kb_ids, list):
+            return get_data_error_result(message="kb_ids must be a non-empty list")
+        
+        success, result = EvaluationService.create_dataset(
+            name=name,
+            description=description,
+            kb_ids=kb_ids,
+            tenant_id=current_user.id,
+            user_id=current_user.id
+        )
+        
+        if not success:
+            return get_data_error_result(message=result)
+        
+        return get_json_result(data={"dataset_id": result})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/dataset/list', methods=['GET'])  # noqa: F821
+@login_required
+async def list_datasets():
+    """
+    List evaluation datasets for current tenant.
+    
+    Query params:
+    - page: Page number (default: 1)
+    - page_size: Items per page (default: 20)
+    """
+    try:
+        page = int(request.args.get("page", 1))
+        page_size = int(request.args.get("page_size", 20))
+        
+        result = EvaluationService.list_datasets(
+            tenant_id=current_user.id,
+            user_id=current_user.id,
+            page=page,
+            page_size=page_size
+        )
+        
+        return get_json_result(data=result)
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/dataset/<dataset_id>', methods=['GET'])  # noqa: F821
+@login_required
+async def get_dataset(dataset_id):
+    """Get dataset details by ID"""
+    try:
+        dataset = EvaluationService.get_dataset(dataset_id)
+        if not dataset:
+            return get_data_error_result(
+                message="Dataset not found",
+                code=RetCode.DATA_ERROR
+            )
+        
+        return get_json_result(data=dataset)
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/dataset/<dataset_id>', methods=['PUT'])  # noqa: F821
+@login_required
+async def update_dataset(dataset_id):
+    """
+    Update dataset.
+    
+    Request body:
+    {
+        "name": "New name",
+        "description": "New description",
+        "kb_ids": ["kb_id1", "kb_id2"]
+    }
+    """
+    try:
+        req = await get_request_json()
+        
+        # Remove fields that shouldn't be updated
+        req.pop("id", None)
+        req.pop("tenant_id", None)
+        req.pop("created_by", None)
+        req.pop("create_time", None)
+        
+        success = EvaluationService.update_dataset(dataset_id, **req)
+        
+        if not success:
+            return get_data_error_result(message="Failed to update dataset")
+        
+        return get_json_result(data={"dataset_id": dataset_id})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/dataset/<dataset_id>', methods=['DELETE'])  # noqa: F821
+@login_required
+async def delete_dataset(dataset_id):
+    """Delete dataset (soft delete)"""
+    try:
+        success = EvaluationService.delete_dataset(dataset_id)
+        
+        if not success:
+            return get_data_error_result(message="Failed to delete dataset")
+        
+        return get_json_result(data={"dataset_id": dataset_id})
+    except Exception as e:
+        return server_error_response(e)
+
+
+# ==================== Test Case Management ====================
+
+@manager.route('/dataset/<dataset_id>/case/add', methods=['POST'])  # noqa: F821
+@login_required
+@validate_request("question")
+async def add_test_case(dataset_id):
+    """
+    Add a test case to a dataset.
+    
+    Request body:
+    {
+        "question": "Test question",
+        "reference_answer": "Optional ground truth answer",
+        "relevant_doc_ids": ["doc_id1", "doc_id2"],
+        "relevant_chunk_ids": ["chunk_id1", "chunk_id2"],
+        "metadata": {"key": "value"}
+    }
+    """
+    try:
+        req = await get_request_json()
+        question = req.get("question", "").strip()
+        
+        if not question:
+            return get_data_error_result(message="Question cannot be empty")
+        
+        success, result = EvaluationService.add_test_case(
+            dataset_id=dataset_id,
+            question=question,
+            reference_answer=req.get("reference_answer"),
+            relevant_doc_ids=req.get("relevant_doc_ids"),
+            relevant_chunk_ids=req.get("relevant_chunk_ids"),
+            metadata=req.get("metadata")
+        )
+        
+        if not success:
+            return get_data_error_result(message=result)
+        
+        return get_json_result(data={"case_id": result})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/dataset/<dataset_id>/case/import', methods=['POST'])  # noqa: F821
+@login_required
+@validate_request("cases")
+async def import_test_cases(dataset_id):
+    """
+    Bulk import test cases.
+    
+    Request body:
+    {
+        "cases": [
+            {
+                "question": "Question 1",
+                "reference_answer": "Answer 1",
+                ...
+            },
+            {
+                "question": "Question 2",
+                ...
+            }
+        ]
+    }
+    """
+    try:
+        req = await get_request_json()
+        cases = req.get("cases", [])
+        
+        if not cases or not isinstance(cases, list):
+            return get_data_error_result(message="cases must be a non-empty list")
+        
+        success_count, failure_count = EvaluationService.import_test_cases(
+            dataset_id=dataset_id,
+            cases=cases
+        )
+        
+        return get_json_result(data={
+            "success_count": success_count,
+            "failure_count": failure_count,
+            "total": len(cases)
+        })
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/dataset/<dataset_id>/cases', methods=['GET'])  # noqa: F821
+@login_required
+async def get_test_cases(dataset_id):
+    """Get all test cases for a dataset"""
+    try:
+        cases = EvaluationService.get_test_cases(dataset_id)
+        return get_json_result(data={"cases": cases, "total": len(cases)})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/case/<case_id>', methods=['DELETE'])  # noqa: F821
+@login_required
+async def delete_test_case(case_id):
+    """Delete a test case"""
+    try:
+        success = EvaluationService.delete_test_case(case_id)
+        
+        if not success:
+            return get_data_error_result(message="Failed to delete test case")
+        
+        return get_json_result(data={"case_id": case_id})
+    except Exception as e:
+        return server_error_response(e)
+
+
+# ==================== Evaluation Execution ====================
+
+@manager.route('/run/start', methods=['POST'])  # noqa: F821
+@login_required
+@validate_request("dataset_id", "dialog_id")
+async def start_evaluation():
+    """
+    Start an evaluation run.
+    
+    Request body:
+    {
+        "dataset_id": "dataset_id",
+        "dialog_id": "dialog_id",
+        "name": "Optional run name"
+    }
+    """
+    try:
+        req = await get_request_json()
+        dataset_id = req.get("dataset_id")
+        dialog_id = req.get("dialog_id")
+        name = req.get("name")
+        
+        success, result = EvaluationService.start_evaluation(
+            dataset_id=dataset_id,
+            dialog_id=dialog_id,
+            user_id=current_user.id,
+            name=name
+        )
+        
+        if not success:
+            return get_data_error_result(message=result)
+        
+        return get_json_result(data={"run_id": result})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/run/<run_id>', methods=['GET'])  # noqa: F821
+@login_required
+async def get_evaluation_run(run_id):
+    """Get evaluation run details"""
+    try:
+        result = EvaluationService.get_run_results(run_id)
+        
+        if not result:
+            return get_data_error_result(
+                message="Evaluation run not found",
+                code=RetCode.DATA_ERROR
+            )
+        
+        return get_json_result(data=result)
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/run/<run_id>/results', methods=['GET'])  # noqa: F821
+@login_required
+async def get_run_results(run_id):
+    """Get detailed results for an evaluation run"""
+    try:
+        result = EvaluationService.get_run_results(run_id)
+        
+        if not result:
+            return get_data_error_result(
+                message="Evaluation run not found",
+                code=RetCode.DATA_ERROR
+            )
+        
+        return get_json_result(data=result)
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/run/list', methods=['GET'])  # noqa: F821
+@login_required
+async def list_evaluation_runs():
+    """
+    List evaluation runs.
+    
+    Query params:
+    - dataset_id: Filter by dataset (optional)
+    - dialog_id: Filter by dialog (optional)
+    - page: Page number (default: 1)
+    - page_size: Items per page (default: 20)
+    """
+    try:
+        # TODO: Implement list_runs in EvaluationService
+        return get_json_result(data={"runs": [], "total": 0})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/run/<run_id>', methods=['DELETE'])  # noqa: F821
+@login_required
+async def delete_evaluation_run(run_id):
+    """Delete an evaluation run"""
+    try:
+        # TODO: Implement delete_run in EvaluationService
+        return get_json_result(data={"run_id": run_id})
+    except Exception as e:
+        return server_error_response(e)
+
+
+# ==================== Analysis & Recommendations ====================
+
+@manager.route('/run/<run_id>/recommendations', methods=['GET'])  # noqa: F821
+@login_required
+async def get_recommendations(run_id):
+    """Get configuration recommendations based on evaluation results"""
+    try:
+        recommendations = EvaluationService.get_recommendations(run_id)
+        return get_json_result(data={"recommendations": recommendations})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/compare', methods=['POST'])  # noqa: F821
+@login_required
+@validate_request("run_ids")
+async def compare_runs():
+    """
+    Compare multiple evaluation runs.
+    
+    Request body:
+    {
+        "run_ids": ["run_id1", "run_id2", "run_id3"]
+    }
+    """
+    try:
+        req = await get_request_json()
+        run_ids = req.get("run_ids", [])
+        
+        if not run_ids or not isinstance(run_ids, list) or len(run_ids) < 2:
+            return get_data_error_result(
+                message="run_ids must be a list with at least 2 run IDs"
+            )
+        
+        # TODO: Implement compare_runs in EvaluationService
+        return get_json_result(data={"comparison": {}})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route('/run/<run_id>/export', methods=['GET'])  # noqa: F821
+@login_required
+async def export_results(run_id):
+    """Export evaluation results as JSON/CSV"""
+    try:
+        # format_type = request.args.get("format", "json")  # TODO: Use for CSV export
+        
+        result = EvaluationService.get_run_results(run_id)
+        
+        if not result:
+            return get_data_error_result(
+                message="Evaluation run not found",
+                code=RetCode.DATA_ERROR
+            )
+        
+        # TODO: Implement CSV export
+        return get_json_result(data=result)
+    except Exception as e:
+        return server_error_response(e)
+
+
+# ==================== Real-time Evaluation ====================
+
+@manager.route('/evaluate_single', methods=['POST'])  # noqa: F821
+@login_required
+@validate_request("question", "dialog_id")
+async def evaluate_single():
+    """
+    Evaluate a single question-answer pair in real-time.
+    
+    Request body:
+    {
+        "question": "Test question",
+        "dialog_id": "dialog_id",
+        "reference_answer": "Optional ground truth",
+        "relevant_chunk_ids": ["chunk_id1", "chunk_id2"]
+    }
+    """
+    try:
+        # req = await get_request_json()  # TODO: Use for single evaluation implementation
+        
+        # TODO: Implement single evaluation
+        # This would execute the RAG pipeline and return metrics immediately
+        
+        return get_json_result(data={
+            "answer": "",
+            "metrics": {},
+            "retrieved_chunks": []
+        })
+    except Exception as e:
+        return server_error_response(e)

api/apps/file2document_app.py

@@ -19,22 +19,20 @@ from pathlib import Path
 from api.db.services.file2document_service import File2DocumentService
 from api.db.services.file_service import FileService
 
-from quart import request
 from api.apps import login_required, current_user
 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.api_utils import get_data_error_result, get_json_result, get_request_json, server_error_response, validate_request
 from common.misc_utils import get_uuid
 from common.constants import RetCode
 from api.db import FileType
 from api.db.services.document_service import DocumentService
-from api.utils.api_utils import get_json_result
 
 
 @manager.route('/convert', methods=['POST'])  # noqa: F821
 @login_required
 @validate_request("file_ids", "kb_ids")
 async def convert():
-    req = await request.json
+    req = await get_request_json()
     kb_ids = req["kb_ids"]
     file_ids = req["file_ids"]
     file2documents = []
@@ -70,7 +68,7 @@ async def convert():
                     e, kb = KnowledgebaseService.get_by_id(kb_id)
                     if not e:
                         return get_data_error_result(
-                            message="Can't find this knowledgebase!")
+                            message="Can't find this dataset!")
                     e, file = FileService.get_by_id(id)
                     if not e:
                         return get_data_error_result(
@@ -79,7 +77,8 @@ async def convert():
                     doc = DocumentService.insert({
                         "id": get_uuid(),
                         "kb_id": kb.id,
-                        "parser_id": FileService.get_parser(file.type, file.name, kb.parser_id),
+                        "parser_id": kb.parser_id,
+                        "pipeline_id": kb.pipeline_id,
                         "parser_config": kb.parser_config,
                         "created_by": current_user.id,
                         "type": file.type,
@@ -104,7 +103,7 @@ async def convert():
 @login_required
 @validate_request("file_ids")
 async def rm():
-    req = await request.json
+    req = await get_request_json()
     file_ids = req["file_ids"]
     if not file_ids:
         return get_json_result(

api/apps/file_app.py

@@ -14,6 +14,7 @@
 #  limitations under the License
 #
 import logging
+import asyncio
 import os
 import pathlib
 import re
@@ -29,7 +30,7 @@ from common.constants import RetCode, FileSource
 from api.db import FileType
 from api.db.services import duplicate_name
 from api.db.services.file_service import FileService
-from api.utils.api_utils import get_json_result
+from api.utils.api_utils import get_json_result, get_request_json
 from api.utils.file_utils import filename_type
 from api.utils.web_utils import CONTENT_TYPE_MAP
 from common import settings
@@ -61,9 +62,10 @@ async def upload():
         e, pf_folder = FileService.get_by_id(pf_id)
         if not e:
             return get_data_error_result( message="Can't find this folder!")
-        for file_obj in file_objs:
+
+        async def _handle_single_file(file_obj):
             MAX_FILE_NUM_PER_USER: int = int(os.environ.get('MAX_FILE_NUM_PER_USER', 0))
-            if 0 < MAX_FILE_NUM_PER_USER <= DocumentService.get_doc_count(current_user.id):
+            if 0 < MAX_FILE_NUM_PER_USER <= await asyncio.to_thread(DocumentService.get_doc_count, current_user.id):
                 return get_data_error_result( message="Exceed the maximum file number of a free user!")
 
             # split file name path
@@ -75,35 +77,36 @@ async def upload():
             file_len = len(file_obj_names)
 
             # get folder
-            file_id_list = FileService.get_id_list_by_id(pf_id, file_obj_names, 1, [pf_id])
+            file_id_list = await asyncio.to_thread(FileService.get_id_list_by_id, pf_id, file_obj_names, 1, [pf_id])
             len_id_list = len(file_id_list)
 
             # create folder
             if file_len != len_id_list:
-                e, file = FileService.get_by_id(file_id_list[len_id_list - 1])
+                e, file = await asyncio.to_thread(FileService.get_by_id, file_id_list[len_id_list - 1])
                 if not e:
                     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,
+                last_folder = await asyncio.to_thread(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])
+                e, file = await asyncio.to_thread(FileService.get_by_id, file_id_list[len_id_list - 2])
                 if not e:
                     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,
+                last_folder = await asyncio.to_thread(FileService.create_folder, file, file_id_list[len_id_list - 2], file_obj_names,
                                                         len_id_list)
 
             # file type
             filetype = filename_type(file_obj_names[file_len - 1])
             location = file_obj_names[file_len - 1]
-            while settings.STORAGE_IMPL.obj_exist(last_folder.id, location):
+            while await asyncio.to_thread(settings.STORAGE_IMPL.obj_exist, last_folder.id, location):
                 location += "_"
-            blob = file_obj.read()
+            blob = await asyncio.to_thread(file_obj.read)
-            filename = duplicate_name(
+            filename = await asyncio.to_thread(
+                duplicate_name,
                 FileService.query,
                 name=file_obj_names[file_len - 1],
                 parent_id=last_folder.id)
-            settings.STORAGE_IMPL.put(last_folder.id, location, blob)
+            await asyncio.to_thread(settings.STORAGE_IMPL.put, last_folder.id, location, blob)
-            file = {
+            file_data = {
                 "id": get_uuid(),
                 "parent_id": last_folder.id,
                 "tenant_id": current_user.id,
@@ -113,8 +116,13 @@ async def upload():
                 "location": location,
                 "size": len(blob),
             }
-            file = FileService.insert(file)
+            inserted = await asyncio.to_thread(FileService.insert, file_data)
-            file_res.append(file.to_json())
+            return inserted.to_json()
+
+        for file_obj in file_objs:
+            res = await _handle_single_file(file_obj)
+            file_res.append(res)
+
         return get_json_result(data=file_res)
     except Exception as e:
         return server_error_response(e)
@@ -124,7 +132,7 @@ async def upload():
 @login_required
 @validate_request("name")
 async def create():
-    req = await request.json
+    req = await get_request_json()
     pf_id = req.get("parent_id")
     input_file_type = req.get("type")
     if not pf_id:
@@ -239,9 +247,10 @@ def get_all_parent_folders():
 @login_required
 @validate_request("file_ids")
 async def rm():
-    req = await request.json
+    req = await get_request_json()
     file_ids = req["file_ids"]
 
+    try:
         def _delete_single_file(file):
             try:
                 if file.location:
@@ -271,7 +280,7 @@ async def rm():
 
             FileService.delete(folder)
 
-    try:
+        def _rm_sync():
             for file_id in file_ids:
                 e, file = FileService.get_by_id(file_id)
                 if not e or not file:
@@ -292,6 +301,8 @@ async def rm():
 
             return get_json_result(data=True)
 
+        return await asyncio.to_thread(_rm_sync)
+
     except Exception as e:
         return server_error_response(e)
 
@@ -300,7 +311,7 @@ async def rm():
 @login_required
 @validate_request("file_id", "name")
 async def rename():
-    req = await request.json
+    req = await get_request_json()
     try:
         e, file = FileService.get_by_id(req["file_id"])
         if not e:
@@ -346,10 +357,10 @@ async def get(file_id):
         if not check_file_team_permission(file, current_user.id):
             return get_json_result(data=False, message='No authorization.', code=RetCode.AUTHENTICATION_ERROR)
 
-        blob = settings.STORAGE_IMPL.get(file.parent_id, file.location)
+        blob = await asyncio.to_thread(settings.STORAGE_IMPL.get, file.parent_id, file.location)
         if not blob:
             b, n = File2DocumentService.get_storage_address(file_id=file_id)
-            blob = settings.STORAGE_IMPL.get(b, n)
+            blob = await asyncio.to_thread(settings.STORAGE_IMPL.get, b, n)
 
         response = await make_response(blob)
         ext = re.search(r"\.([^.]+)$", file.name.lower())
@@ -369,7 +380,7 @@ async def get(file_id):
 @login_required
 @validate_request("src_file_ids", "dest_file_id")
 async def move():
-    req = await request.json
+    req = await get_request_json()
     try:
         file_ids = req["src_file_ids"]
         dest_parent_id = req["dest_file_id"]
@@ -444,10 +455,12 @@ async def move():
                 },
             )
 
+        def _move_sync():
             for file in files:
                 _move_entry_recursive(file, dest_folder)
-
             return get_json_result(data=True)
 
+        return await asyncio.to_thread(_move_sync)
+
     except Exception as e:
         return server_error_response(e)

api/apps/kb_app.py

@@ -17,6 +17,7 @@ import json
 import logging
 import random
 import re
+import asyncio
 
 from quart import request
 import numpy as np
@@ -30,7 +31,7 @@ from api.db.services.pipeline_operation_log_service import PipelineOperationLogS
 from api.db.services.task_service import TaskService, GRAPH_RAPTOR_FAKE_DOC_ID
 from api.db.services.user_service import TenantService, UserTenantService
 from api.utils.api_utils import get_error_data_result, server_error_response, get_data_error_result, validate_request, not_allowed_parameters, \
-    request_json
+    get_request_json
 from api.db import VALID_FILE_TYPES
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.db_models import File
@@ -48,7 +49,7 @@ from api.apps import login_required, current_user
 @login_required
 @validate_request("name")
 async def create():
-    req = await request_json()
+    req = await get_request_json()
     e, res = KnowledgebaseService.create_with_name(
         name = req.pop("name", None),
         tenant_id = current_user.id,
@@ -72,7 +73,7 @@ async def create():
 @validate_request("kb_id", "name", "description", "parser_id")
 @not_allowed_parameters("id", "tenant_id", "created_by", "create_time", "update_time", "create_date", "update_date", "created_by")
 async def update():
-    req = await request_json()
+    req = await get_request_json()
     if not isinstance(req["name"], str):
         return get_data_error_result(message="Dataset name must be string.")
     if req["name"].strip() == "":
@@ -92,19 +93,19 @@ async def update():
         if not KnowledgebaseService.query(
                 created_by=current_user.id, id=req["kb_id"]):
             return get_json_result(
-                data=False, message='Only owner of knowledgebase authorized for this operation.',
+                data=False, message='Only owner of dataset authorized for this operation.',
                 code=RetCode.OPERATING_ERROR)
 
         e, kb = KnowledgebaseService.get_by_id(req["kb_id"])
         if not e:
             return get_data_error_result(
-                message="Can't find this knowledgebase!")
+                message="Can't find this dataset!")
 
         if req["name"].lower() != kb.name.lower() \
                 and len(
             KnowledgebaseService.query(name=req["name"], tenant_id=current_user.id, status=StatusEnum.VALID.value)) >= 1:
             return get_data_error_result(
-                message="Duplicated knowledgebase name.")
+                message="Duplicated dataset name.")
 
         del req["kb_id"]
         connectors = []
@@ -116,12 +117,22 @@ async def update():
 
         if kb.pagerank != req.get("pagerank", 0):
             if req.get("pagerank", 0) > 0:
-                settings.docStoreConn.update({"kb_id": kb.id}, {PAGERANK_FLD: req["pagerank"]},
+                await asyncio.to_thread(
-                                         search.index_name(kb.tenant_id), kb.id)
+                    settings.docStoreConn.update,
+                    {"kb_id": kb.id},
+                    {PAGERANK_FLD: req["pagerank"]},
+                    search.index_name(kb.tenant_id),
+                    kb.id,
+                )
             else:
                 # Elasticsearch requires PAGERANK_FLD be non-zero!
-                settings.docStoreConn.update({"exists": PAGERANK_FLD}, {"remove": PAGERANK_FLD},
+                await asyncio.to_thread(
-                                         search.index_name(kb.tenant_id), kb.id)
+                    settings.docStoreConn.update,
+                    {"exists": PAGERANK_FLD},
+                    {"remove": PAGERANK_FLD},
+                    search.index_name(kb.tenant_id),
+                    kb.id,
+                )
 
         e, kb = KnowledgebaseService.get_by_id(kb.id)
         if not e:
@@ -151,12 +162,12 @@ def detail():
                 break
         else:
             return get_json_result(
-                data=False, message='Only owner of knowledgebase authorized for this operation.',
+                data=False, message='Only owner of dataset authorized for this operation.',
                 code=RetCode.OPERATING_ERROR)
         kb = KnowledgebaseService.get_detail(kb_id)
         if not kb:
             return get_data_error_result(
-                message="Can't find this knowledgebase!")
+                message="Can't find this dataset!")
         kb["size"] = DocumentService.get_total_size_by_kb_id(kb_id=kb["id"],keywords="", run_status=[], types=[])
         kb["connectors"] = Connector2KbService.list_connectors(kb_id)
 
@@ -182,7 +193,7 @@ async def list_kbs():
     else:
         desc = True
 
-    req = await request_json()
+    req = await get_request_json()
     owner_ids = req.get("owner_ids", [])
     try:
         if not owner_ids:
@@ -209,7 +220,7 @@ async def list_kbs():
 @login_required
 @validate_request("kb_id")
 async def rm():
-    req = await request_json()
+    req = await get_request_json()
     if not KnowledgebaseService.accessible4deletion(req["kb_id"], current_user.id):
         return get_json_result(
             data=False,
@@ -221,9 +232,10 @@ async def rm():
             created_by=current_user.id, id=req["kb_id"])
         if not kbs:
             return get_json_result(
-                data=False, message='Only owner of knowledgebase authorized for this operation.',
+                data=False, message='Only owner of dataset authorized for this operation.',
                 code=RetCode.OPERATING_ERROR)
 
+        def _rm_sync():
             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(
@@ -243,6 +255,8 @@ async def rm():
                 if hasattr(settings.STORAGE_IMPL, 'remove_bucket'):
                     settings.STORAGE_IMPL.remove_bucket(kb.id)
             return get_json_result(data=True)
+
+        return await asyncio.to_thread(_rm_sync)
     except Exception as e:
         return server_error_response(e)
 
@@ -286,7 +300,7 @@ def list_tags_from_kbs():
 @manager.route('/<kb_id>/rm_tags', methods=['POST'])  # noqa: F821
 @login_required
 async def rm_tags(kb_id):
-    req = await request_json()
+    req = await get_request_json()
     if not KnowledgebaseService.accessible(kb_id, current_user.id):
         return get_json_result(
             data=False,
@@ -306,7 +320,7 @@ async def rm_tags(kb_id):
 @manager.route('/<kb_id>/rename_tag', methods=['POST'])  # noqa: F821
 @login_required
 async def rename_tags(kb_id):
-    req = await request_json()
+    req = await get_request_json()
     if not KnowledgebaseService.accessible(kb_id, current_user.id):
         return get_json_result(
             data=False,
@@ -428,7 +442,7 @@ async def list_pipeline_logs():
     if create_date_to > create_date_from:
         return get_data_error_result(message="Create data filter is abnormal.")
 
-    req = await request_json()
+    req = await get_request_json()
 
     operation_status = req.get("operation_status", [])
     if operation_status:
@@ -470,7 +484,7 @@ async def list_pipeline_dataset_logs():
     if create_date_to > create_date_from:
         return get_data_error_result(message="Create data filter is abnormal.")
 
-    req = await request_json()
+    req = await get_request_json()
 
     operation_status = req.get("operation_status", [])
     if operation_status:
@@ -492,7 +506,7 @@ async def delete_pipeline_logs():
     if not kb_id:
         return get_json_result(data=False, message='Lack of "KB ID"', code=RetCode.ARGUMENT_ERROR)
 
-    req = await request_json()
+    req = await get_request_json()
     log_ids = req.get("log_ids", [])
 
     PipelineOperationLogService.delete_by_ids(log_ids)
@@ -517,7 +531,7 @@ def pipeline_log_detail():
 @manager.route("/run_graphrag", methods=["POST"])  # noqa: F821
 @login_required
 async def run_graphrag():
-    req = await request_json()
+    req = await get_request_json()
 
     kb_id = req.get("kb_id", "")
     if not kb_id:
@@ -586,7 +600,7 @@ def trace_graphrag():
 @manager.route("/run_raptor", methods=["POST"])  # noqa: F821
 @login_required
 async def run_raptor():
-    req = await request_json()
+    req = await get_request_json()
 
     kb_id = req.get("kb_id", "")
     if not kb_id:
@@ -655,7 +669,7 @@ def trace_raptor():
 @manager.route("/run_mindmap", methods=["POST"])  # noqa: F821
 @login_required
 async def run_mindmap():
-    req = await request_json()
+    req = await get_request_json()
 
     kb_id = req.get("kb_id", "")
     if not kb_id:
@@ -861,7 +875,7 @@ async def check_embedding():
     def _clean(s: str) -> str:
         s = re.sub(r"</?(table|td|caption|tr|th)( [^<>]{0,12})?>", " ", s or "")
         return s if s else "None"
-    req = await request_json()
+    req = await get_request_json()
     kb_id = req.get("kb_id", "")
     embd_id = req.get("embd_id", "")
     n = int(req.get("check_num", 5))
@@ -922,5 +936,3 @@ async def check_embedding():
     if summary["avg_cos_sim"] > 0.9:
         return get_json_result(data={"summary": summary, "results": results})
     return get_json_result(code=RetCode.NOT_EFFECTIVE, message="Embedding model switch failed: the average similarity between old and new vectors is below 0.9, indicating incompatible vector spaces.", data={"summary": summary, "results": results})
-
-

api/apps/langfuse_app.py

@@ -15,28 +15,28 @@
 #
 
 
-from quart import request
 from api.apps import current_user, login_required
 from langfuse import Langfuse
 
 from api.db.db_models import DB
 from api.db.services.langfuse_service import TenantLangfuseService
-from api.utils.api_utils import get_error_data_result, get_json_result, server_error_response, validate_request
+from api.utils.api_utils import get_error_data_result, get_json_result, get_request_json, server_error_response, validate_request
 
 
 @manager.route("/api_key", methods=["POST", "PUT"])  # noqa: F821
 @login_required
 @validate_request("secret_key", "public_key", "host")
 async def set_api_key():
-    req = await request.get_json()
+    req = await get_request_json()
     secret_key = req.get("secret_key", "")
     public_key = req.get("public_key", "")
     host = req.get("host", "")
     if not all([secret_key, public_key, host]):
         return get_error_data_result(message="Missing required fields")
 
+    current_user_id = current_user.id
     langfuse_keys = dict(
-        tenant_id=current_user.id,
+        tenant_id=current_user_id,
         secret_key=secret_key,
         public_key=public_key,
         host=host,
@@ -46,23 +46,24 @@ async def set_api_key():
     if not langfuse.auth_check():
         return get_error_data_result(message="Invalid Langfuse keys")
 
-    langfuse_entry = TenantLangfuseService.filter_by_tenant(tenant_id=current_user.id)
+    langfuse_entry = TenantLangfuseService.filter_by_tenant(tenant_id=current_user_id)
     with DB.atomic():
         try:
             if not langfuse_entry:
                 TenantLangfuseService.save(**langfuse_keys)
             else:
-                TenantLangfuseService.update_by_tenant(tenant_id=current_user.id, langfuse_keys=langfuse_keys)
+                TenantLangfuseService.update_by_tenant(tenant_id=current_user_id, langfuse_keys=langfuse_keys)
             return get_json_result(data=langfuse_keys)
         except Exception as e:
-            server_error_response(e)
+            return server_error_response(e)
 
 
 @manager.route("/api_key", methods=["GET"])  # noqa: F821
 @login_required
 @validate_request()
 def get_api_key():
-    langfuse_entry = TenantLangfuseService.filter_by_tenant_with_info(tenant_id=current_user.id)
+    current_user_id = current_user.id
+    langfuse_entry = TenantLangfuseService.filter_by_tenant_with_info(tenant_id=current_user_id)
     if not langfuse_entry:
         return get_json_result(message="Have not record any Langfuse keys.")
 
@@ -73,7 +74,7 @@ def get_api_key():
     except langfuse.api.core.api_error.ApiError as api_err:
         return get_json_result(message=f"Error from Langfuse: {api_err}")
     except Exception as e:
-        server_error_response(e)
+        return server_error_response(e)
 
     langfuse_entry["project_id"] = langfuse.api.projects.get().dict()["data"][0]["id"]
     langfuse_entry["project_name"] = langfuse.api.projects.get().dict()["data"][0]["name"]
@@ -85,7 +86,8 @@ def get_api_key():
 @login_required
 @validate_request()
 def delete_api_key():
-    langfuse_entry = TenantLangfuseService.filter_by_tenant(tenant_id=current_user.id)
+    current_user_id = current_user.id
+    langfuse_entry = TenantLangfuseService.filter_by_tenant(tenant_id=current_user_id)
     if not langfuse_entry:
         return get_json_result(message="Have not record any Langfuse keys.")
 
@@ -94,4 +96,4 @@ def delete_api_key():
             TenantLangfuseService.delete_model(langfuse_entry)
             return get_json_result(data=True)
         except Exception as e:
-            server_error_response(e)
+            return server_error_response(e)

api/apps/llm_app.py

@@ -21,12 +21,11 @@ from quart import request
 from api.apps import login_required, current_user
 from api.db.services.tenant_llm_service import LLMFactoriesService, TenantLLMService
 from api.db.services.llm_service import LLMService
-from api.utils.api_utils import server_error_response, get_data_error_result, validate_request
+from api.utils.api_utils import get_allowed_llm_factories, get_data_error_result, get_json_result, get_request_json, server_error_response, validate_request
 from common.constants import StatusEnum, LLMType
 from api.db.db_models import TenantLLM
-from api.utils.api_utils import get_json_result, get_allowed_llm_factories
 from rag.utils.base64_image import test_image
-from rag.llm import EmbeddingModel, ChatModel, RerankModel, CvModel, TTSModel
+from rag.llm import EmbeddingModel, ChatModel, RerankModel, CvModel, TTSModel, OcrModel
 
 
 @manager.route("/factories", methods=["GET"])  # noqa: F821
@@ -44,7 +43,13 @@ def factories():
                 mdl_types[m.fid] = set([])
             mdl_types[m.fid].add(m.model_type)
         for f in fac:
-            f["model_types"] = list(mdl_types.get(f["name"], [LLMType.CHAT, LLMType.EMBEDDING, LLMType.RERANK, LLMType.IMAGE2TEXT, LLMType.SPEECH2TEXT, LLMType.TTS]))
+            f["model_types"] = list(
+                mdl_types.get(
+                    f["name"],
+                    [LLMType.CHAT, LLMType.EMBEDDING, LLMType.RERANK, LLMType.IMAGE2TEXT, LLMType.SPEECH2TEXT, LLMType.TTS, LLMType.OCR],
+                )
+            )
+
         return get_json_result(data=fac)
     except Exception as e:
         return server_error_response(e)
@@ -54,7 +59,7 @@ def factories():
 @login_required
 @validate_request("llm_factory", "api_key")
 async def set_api_key():
-    req = await request.json
+    req = await get_request_json()
     # test if api key works
     chat_passed, embd_passed, rerank_passed = False, False, False
     factory = req["llm_factory"]
@@ -75,7 +80,7 @@ async def set_api_key():
             assert factory in ChatModel, f"Chat model from {factory} is not supported yet."
             mdl = ChatModel[factory](req["api_key"], llm.llm_name, base_url=req.get("base_url"), **extra)
             try:
-                m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], {"temperature": 0.9, "max_tokens": 50})
+                m, tc = await mdl.async_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
@@ -124,7 +129,7 @@ async def set_api_key():
 @login_required
 @validate_request("llm_factory")
 async def add_llm():
-    req = await request.json
+    req = await get_request_json()
     factory = req["llm_factory"]
     api_key = req.get("api_key", "x")
     llm_name = req.get("llm_name")
@@ -152,7 +157,7 @@ async def add_llm():
     elif factory == "Bedrock":
         # For Bedrock, due to its special authentication method
         # Assemble bedrock_ak, bedrock_sk, bedrock_region
-        api_key = apikey_json(["bedrock_ak", "bedrock_sk", "bedrock_region"])
+        api_key = apikey_json(["auth_mode", "bedrock_ak", "bedrock_sk", "bedrock_region", "aws_role_arn"])
 
     elif factory == "LocalAI":
         llm_name += "___LocalAI"
@@ -187,6 +192,9 @@ async def add_llm():
     elif factory == "OpenRouter":
         api_key = apikey_json(["api_key", "provider_order"])
 
+    elif factory == "MinerU":
+        api_key = apikey_json(["api_key", "provider_order"])
+
     llm = {
         "tenant_id": current_user.id,
         "llm_factory": factory,
@@ -218,7 +226,7 @@ async def add_llm():
             **extra,
         )
         try:
-            m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], {"temperature": 0.9})
+            m, tc = await mdl.async_chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], {"temperature": 0.9})
             if not tc and m.find("**ERROR**:") >= 0:
                 raise Exception(m)
         except Exception as e:
@@ -252,6 +260,15 @@ async def add_llm():
                 pass
         except RuntimeError as e:
             msg += f"\nFail to access model({factory}/{mdl_nm})." + str(e)
+    elif llm["model_type"] == LLMType.OCR.value:
+        assert factory in OcrModel, f"OCR model from {factory} is not supported yet."
+        try:
+            mdl = OcrModel[factory](key=llm["api_key"], model_name=mdl_nm, base_url=llm.get("api_base", ""))
+            ok, reason = mdl.check_available()
+            if not ok:
+                raise RuntimeError(reason or "Model not available")
+        except Exception as e:
+            msg += f"\nFail to access model({factory}/{mdl_nm})." + str(e)
     else:
         # TODO: check other type of models
         pass
@@ -269,7 +286,7 @@ async def add_llm():
 @login_required
 @validate_request("llm_factory", "llm_name")
 async def delete_llm():
-    req = await request.json
+    req = await get_request_json()
     TenantLLMService.filter_delete([TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"], TenantLLM.llm_name == req["llm_name"]])
     return get_json_result(data=True)
 
@@ -278,7 +295,7 @@ async def delete_llm():
 @login_required
 @validate_request("llm_factory", "llm_name")
 async def enable_llm():
-    req = await request.json
+    req = await get_request_json()
     TenantLLMService.filter_update(
         [TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"], TenantLLM.llm_name == req["llm_name"]], {"status": str(req.get("status", "1"))}
     )
@@ -289,7 +306,7 @@ async def enable_llm():
 @login_required
 @validate_request("llm_factory")
 async def delete_factory():
-    req = await request.json
+    req = await get_request_json()
     TenantLLMService.filter_delete([TenantLLM.tenant_id == current_user.id, TenantLLM.llm_factory == req["llm_factory"]])
     return get_json_result(data=True)
 
@@ -298,6 +315,7 @@ async def delete_factory():
 @login_required
 def my_llms():
     try:
+        TenantLLMService.ensure_mineru_from_env(current_user.id)
         include_details = request.args.get("include_details", "false").lower() == "true"
 
         if include_details:
@@ -345,6 +363,7 @@ def list_app():
     weighted = []
     model_type = request.args.get("model_type")
     try:
+        TenantLLMService.ensure_mineru_from_env(current_user.id)
         objs = TenantLLMService.query(tenant_id=current_user.id)
         facts = set([o.to_dict()["llm_factory"] for o in objs if o.api_key and o.status == StatusEnum.VALID.value])
         status = {(o.llm_name + "@" + o.llm_factory) for o in objs if o.status == StatusEnum.VALID.value}

api/apps/mcp_server_app.py

@@ -22,8 +22,7 @@ from api.db.services.user_service import TenantService
 from common.constants import RetCode, VALID_MCP_SERVER_TYPES
 
 from common.misc_utils import get_uuid
-from api.utils.api_utils import get_data_error_result, get_json_result, server_error_response, validate_request, \
+from api.utils.api_utils import get_data_error_result, get_json_result, get_mcp_tools, get_request_json, server_error_response, validate_request
-    get_mcp_tools
 from api.utils.web_utils import get_float, safe_json_parse
 from common.mcp_tool_call_conn import MCPToolCallSession, close_multiple_mcp_toolcall_sessions
 
@@ -40,7 +39,7 @@ async def list_mcp() -> Response:
     else:
         desc = True
 
-    req = await request.get_json()
+    req = await get_request_json()
     mcp_ids = req.get("mcp_ids", [])
     try:
         servers = MCPServerService.get_servers(current_user.id, mcp_ids, 0, 0, orderby, desc, keywords) or []
@@ -73,7 +72,7 @@ def detail() -> Response:
 @login_required
 @validate_request("name", "url", "server_type")
 async def create() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
 
     server_type = req.get("server_type", "")
     if server_type not in VALID_MCP_SERVER_TYPES:
@@ -128,7 +127,7 @@ async def create() -> Response:
 @login_required
 @validate_request("mcp_id")
 async def update() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
 
     mcp_id = req.get("mcp_id", "")
     e, mcp_server = MCPServerService.get_by_id(mcp_id)
@@ -184,7 +183,7 @@ async def update() -> Response:
 @login_required
 @validate_request("mcp_ids")
 async def rm() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
     mcp_ids = req.get("mcp_ids", [])
 
     try:
@@ -202,7 +201,7 @@ async def rm() -> Response:
 @login_required
 @validate_request("mcpServers")
 async def import_multiple() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
     servers = req.get("mcpServers", {})
     if not servers:
         return get_data_error_result(message="No MCP servers provided.")
@@ -269,7 +268,7 @@ async def import_multiple() -> Response:
 @login_required
 @validate_request("mcp_ids")
 async def export_multiple() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
     mcp_ids = req.get("mcp_ids", [])
 
     if not mcp_ids:
@@ -301,7 +300,7 @@ async def export_multiple() -> Response:
 @login_required
 @validate_request("mcp_ids")
 async def list_tools() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
     mcp_ids = req.get("mcp_ids", [])
     if not mcp_ids:
         return get_data_error_result(message="No MCP server IDs provided.")
@@ -348,7 +347,7 @@ async def list_tools() -> Response:
 @login_required
 @validate_request("mcp_id", "tool_name", "arguments")
 async def test_tool() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
     mcp_id = req.get("mcp_id", "")
     if not mcp_id:
         return get_data_error_result(message="No MCP server ID provided.")
@@ -381,7 +380,7 @@ async def test_tool() -> Response:
 @login_required
 @validate_request("mcp_id", "tools")
 async def cache_tool() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
     mcp_id = req.get("mcp_id", "")
     if not mcp_id:
         return get_data_error_result(message="No MCP server ID provided.")
@@ -404,7 +403,7 @@ async def cache_tool() -> Response:
 @manager.route("/test_mcp", methods=["POST"])  # noqa: F821
 @validate_request("url", "server_type")
 async def test_mcp() -> Response:
-    req = await request.get_json()
+    req = await get_request_json()
 
     url = req.get("url", "")
     if not url:

api/apps/memories_app.py

@@ -0,0 +1,185 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+import logging
+
+from quart import request
+from api.apps import login_required, current_user
+from api.db import TenantPermission
+from api.db.services.memory_service import MemoryService
+from api.db.services.user_service import UserTenantService
+from api.utils.api_utils import validate_request, get_request_json, get_error_argument_result, get_json_result, \
+    not_allowed_parameters
+from api.utils.memory_utils import format_ret_data_from_memory, get_memory_type_human
+from api.constants import MEMORY_NAME_LIMIT, MEMORY_SIZE_LIMIT
+from common.constants import MemoryType, RetCode, ForgettingPolicy
+
+
+@manager.route("", methods=["POST"])  # noqa: F821
+@login_required
+@validate_request("name", "memory_type", "embd_id", "llm_id")
+async def create_memory():
+    req = await get_request_json()
+    # check name length
+    name = req["name"]
+    memory_name = name.strip()
+    if len(memory_name) == 0:
+        return get_error_argument_result("Memory name cannot be empty or whitespace.")
+    if len(memory_name) > MEMORY_NAME_LIMIT:
+        return get_error_argument_result(f"Memory name '{memory_name}' exceeds limit of {MEMORY_NAME_LIMIT}.")
+    # check memory_type valid
+    memory_type = set(req["memory_type"])
+    invalid_type = memory_type - {e.name.lower() for e in MemoryType}
+    if invalid_type:
+        return get_error_argument_result(f"Memory type '{invalid_type}' is not supported.")
+    memory_type = list(memory_type)
+
+    try:
+        res, memory = MemoryService.create_memory(
+            tenant_id=current_user.id,
+            name=memory_name,
+            memory_type=memory_type,
+            embd_id=req["embd_id"],
+            llm_id=req["llm_id"]
+        )
+
+        if res:
+            return get_json_result(message=True, data=format_ret_data_from_memory(memory))
+
+        else:
+            return get_json_result(message=memory, code=RetCode.SERVER_ERROR)
+
+    except Exception as e:
+        return get_json_result(message=str(e), code=RetCode.SERVER_ERROR)
+
+
+@manager.route("/<memory_id>", methods=["PUT"])  # noqa: F821
+@login_required
+@not_allowed_parameters("id", "tenant_id", "memory_type", "storage_type", "embd_id")
+async def update_memory(memory_id):
+    req = await get_request_json()
+    update_dict = {}
+    # check name length
+    if "name" in req:
+        name = req["name"]
+        memory_name = name.strip()
+        if len(memory_name) == 0:
+            return get_error_argument_result("Memory name cannot be empty or whitespace.")
+        if len(memory_name) > MEMORY_NAME_LIMIT:
+            return get_error_argument_result(f"Memory name '{memory_name}' exceeds limit of {MEMORY_NAME_LIMIT}.")
+        update_dict["name"] = memory_name
+    # check permissions valid
+    if req.get("permissions"):
+        if req["permissions"] not in [e.value for e in TenantPermission]:
+            return get_error_argument_result(f"Unknown permission '{req['permissions']}'.")
+        update_dict["permissions"] = req["permissions"]
+    if req.get("llm_id"):
+        update_dict["llm_id"] = req["llm_id"]
+    # check memory_size valid
+    if req.get("memory_size"):
+        if not 0 < int(req["memory_size"]) <= MEMORY_SIZE_LIMIT:
+            return get_error_argument_result(f"Memory size should be in range (0, {MEMORY_SIZE_LIMIT}] Bytes.")
+        update_dict["memory_size"] = req["memory_size"]
+    # check forgetting_policy valid
+    if req.get("forgetting_policy"):
+        if req["forgetting_policy"] not in [e.value for e in ForgettingPolicy]:
+            return get_error_argument_result(f"Forgetting policy '{req['forgetting_policy']}' is not supported.")
+        update_dict["forgetting_policy"] = req["forgetting_policy"]
+    # check temperature valid
+    if "temperature" in req:
+        temperature = float(req["temperature"])
+        if not 0 <= temperature <= 1:
+            return get_error_argument_result("Temperature should be in range [0, 1].")
+        update_dict["temperature"] = temperature
+    # allow update to empty fields
+    for field in ["avatar", "description", "system_prompt", "user_prompt"]:
+        if field in req:
+            update_dict[field] = req[field]
+    current_memory = MemoryService.get_by_memory_id(memory_id)
+    if not current_memory:
+        return get_json_result(code=RetCode.NOT_FOUND, message=f"Memory '{memory_id}' not found.")
+
+    memory_dict = current_memory.to_dict()
+    memory_dict.update({"memory_type": get_memory_type_human(current_memory.memory_type)})
+    to_update = {}
+    for k, v in update_dict.items():
+        if isinstance(v, list) and set(memory_dict[k]) != set(v):
+            to_update[k] = v
+        elif memory_dict[k] != v:
+            to_update[k] = v
+
+    if not to_update:
+        return get_json_result(message=True, data=memory_dict)
+
+    try:
+        MemoryService.update_memory(memory_id, to_update)
+        updated_memory = MemoryService.get_by_memory_id(memory_id)
+        return get_json_result(message=True, data=format_ret_data_from_memory(updated_memory))
+
+    except Exception as e:
+        logging.error(e)
+        return get_json_result(message=str(e), code=RetCode.SERVER_ERROR)
+
+
+@manager.route("/<memory_id>", methods=["DELETE"]) # noqa: F821
+@login_required
+async def delete_memory(memory_id):
+    memory = MemoryService.get_by_memory_id(memory_id)
+    if not memory:
+        return get_json_result(message=True, code=RetCode.NOT_FOUND)
+    try:
+        MemoryService.delete_memory(memory_id)
+        return get_json_result(message=True)
+    except Exception as e:
+        logging.error(e)
+        return get_json_result(message=str(e), code=RetCode.SERVER_ERROR)
+
+
+@manager.route("", methods=["GET"]) # noqa: F821
+@login_required
+async def list_memory():
+    args = request.args
+    try:
+        tenant_ids = args.getlist("tenant_id")
+        memory_types = args.getlist("memory_type")
+        storage_type = args.get("storage_type")
+        keywords = args.get("keywords", "")
+        page = int(args.get("page", 1))
+        page_size = int(args.get("page_size", 50))
+        # make filter dict
+        filter_dict = {"memory_type": memory_types, "storage_type": storage_type}
+        if not tenant_ids:
+            # restrict to current user's tenants
+            user_tenants = UserTenantService.get_user_tenant_relation_by_user_id(current_user.id)
+            filter_dict["tenant_id"] = [tenant["tenant_id"] for tenant in user_tenants]
+        else:
+            filter_dict["tenant_id"] = tenant_ids
+
+        memory_list, count = MemoryService.get_by_filter(filter_dict, keywords, page, page_size)
+        [memory.update({"memory_type": get_memory_type_human(memory["memory_type"])}) for memory in memory_list]
+        return get_json_result(message=True, data={"memory_list": memory_list, "total_count": count})
+
+    except Exception as e:
+        logging.error(e)
+        return get_json_result(message=str(e), code=RetCode.SERVER_ERROR)
+
+
+@manager.route("/<memory_id>/config", methods=["GET"])  # noqa: F821
+@login_required
+async def get_memory_config(memory_id):
+    memory = MemoryService.get_with_owner_name_by_id(memory_id)
+    if not memory:
+        return get_json_result(code=RetCode.NOT_FOUND, message=f"Memory '{memory_id}' not found.")
+    return get_json_result(message=True, data=format_ret_data_from_memory(memory))

api/apps/sdk/agents.py

@@ -14,20 +14,29 @@
 #  limitations under the License.
 #
 
+import asyncio
+import base64
+import hashlib
+import hmac
+import ipaddress
 import json
 import logging
 import time
 from typing import Any, cast
 
+import jwt
+
 from agent.canvas import Canvas
 from api.db import CanvasCategory
 from api.db.services.canvas_service import UserCanvasService
+from api.db.services.file_service import FileService
 from api.db.services.user_canvas_version import UserCanvasVersionService
 from common.constants import RetCode
 from common.misc_utils import get_uuid
-from api.utils.api_utils import get_data_error_result, get_error_data_result, get_json_result, token_required
+from api.utils.api_utils import get_data_error_result, get_error_data_result, get_json_result, get_request_json, token_required
 from api.utils.api_utils import get_result
 from quart import request, Response
+from rag.utils.redis_conn import REDIS_CONN
 
 
 @manager.route('/agents', methods=['GET'])  # noqa: F821
@@ -53,7 +62,7 @@ def list_agents(tenant_id):
 @manager.route("/agents", methods=["POST"])  # noqa: F821
 @token_required
 async def create_agent(tenant_id: str):
-    req: dict[str, Any] = cast(dict[str, Any], await request.json)
+    req: dict[str, Any] = cast(dict[str, Any], await get_request_json())
     req["user_id"] = tenant_id
 
     if req.get("dsl") is not None:
@@ -90,7 +99,7 @@ async def create_agent(tenant_id: str):
 @manager.route("/agents/<agent_id>", methods=["PUT"])  # noqa: F821
 @token_required
 async def update_agent(tenant_id: str, agent_id: str):
-    req: dict[str, Any] = {k: v for k, v in cast(dict[str, Any], (await request.json)).items() if v is not None}
+    req: dict[str, Any] = {k: v for k, v in cast(dict[str, Any], (await get_request_json())).items() if v is not None}
     req["user_id"] = tenant_id
 
     if req.get("dsl") is not None:
@@ -132,48 +141,776 @@ def delete_agent(tenant_id: str, agent_id: str):
     UserCanvasService.delete_by_id(agent_id)
     return get_json_result(data=True)
 
+@manager.route("/webhook/<agent_id>", methods=["POST", "GET", "PUT", "PATCH", "DELETE", "HEAD"])  # noqa: F821
+@manager.route("/webhook_test/<agent_id>",methods=["POST", "GET", "PUT", "PATCH", "DELETE", "HEAD"],)  # noqa: F821
+async def webhook(agent_id: str):
+    is_test = request.path.startswith("/api/v1/webhook_test")
+    start_ts = time.time()
 
-@manager.route('/webhook/<agent_id>', methods=['POST'])  # noqa: F821
+    # 1. Fetch canvas by agent_id
-@token_required
+    exists, cvs = UserCanvasService.get_by_id(agent_id)
-async def webhook(tenant_id: str, agent_id: str):
+    if not exists:
-    req = await request.json
+        return get_data_error_result(code=RetCode.BAD_REQUEST,message="Canvas not found."),RetCode.BAD_REQUEST
-    if not UserCanvasService.accessible(req["id"], tenant_id):
-        return get_json_result(
-            data=False, message='Only owner of canvas authorized for this operation.',
-            code=RetCode.OPERATING_ERROR)
-
-    e, cvs = UserCanvasService.get_by_id(req["id"])
-    if not e:
-        return get_data_error_result(message="canvas not found.")
-
-    if not isinstance(cvs.dsl, str):
-        cvs.dsl = json.dumps(cvs.dsl, ensure_ascii=False)
 
+    # 2. Check canvas category
     if cvs.canvas_category == CanvasCategory.DataFlow:
-        return get_data_error_result(message="Dataflow can not be triggered by webhook.")
+        return get_data_error_result(code=RetCode.BAD_REQUEST,message="Dataflow can not be triggered by webhook."),RetCode.BAD_REQUEST
+
+    # 3. Load DSL from canvas
+    dsl = getattr(cvs, "dsl", None)
+    if not isinstance(dsl, dict):
+        return get_data_error_result(code=RetCode.BAD_REQUEST,message="Invalid DSL format."),RetCode.BAD_REQUEST
+
+    # 4. Check webhook configuration in DSL
+    components = dsl.get("components", {})
+    for k, _ in components.items():
+        cpn_obj = components[k]["obj"]
+        if cpn_obj["component_name"].lower() == "begin" and cpn_obj["params"]["mode"] == "Webhook":
+            webhook_cfg = cpn_obj["params"]
+
+    if not webhook_cfg:
+        return get_data_error_result(code=RetCode.BAD_REQUEST,message="Webhook not configured for this agent."),RetCode.BAD_REQUEST
+
+    # 5. Validate request method against webhook_cfg.methods
+    allowed_methods = webhook_cfg.get("methods", [])
+    request_method = request.method.upper()
+    if allowed_methods and request_method not in allowed_methods:
+        return get_data_error_result(
+            code=RetCode.BAD_REQUEST,message=f"HTTP method '{request_method}' not allowed for this webhook."
+        ),RetCode.BAD_REQUEST
+
+    # 6. Validate webhook security
+    async def validate_webhook_security(security_cfg: dict):
+        """Validate webhook security rules based on security configuration."""
+
+        if not security_cfg:
+            return  # No security config → allowed by default
+
+        # 1. Validate max body size
+        await _validate_max_body_size(security_cfg)
+
+        # 2. Validate IP whitelist
+        _validate_ip_whitelist(security_cfg)
+
+        # # 3. Validate rate limiting
+        _validate_rate_limit(security_cfg)
+
+        # 4. Validate authentication
+        auth_type = security_cfg.get("auth_type", "none")
+
+        if auth_type == "none":
+            return
+
+        if auth_type == "token":
+            _validate_token_auth(security_cfg)
+
+        elif auth_type == "basic":
+            _validate_basic_auth(security_cfg)
+
+        elif auth_type == "jwt":
+            _validate_jwt_auth(security_cfg)
+
+        else:
+            raise Exception(f"Unsupported auth_type: {auth_type}")
+
+    async def _validate_max_body_size(security_cfg):
+        """Check request size does not exceed max_body_size."""
+        max_size = security_cfg.get("max_body_size")
+        if not max_size:
+            return
+
+        # Convert "10MB" → bytes
+        units = {"kb": 1024, "mb": 1024**2}
+        size_str = max_size.lower()
+
+        for suffix, factor in units.items():
+            if size_str.endswith(suffix):
+                limit = int(size_str.replace(suffix, "")) * factor
+                break
+        else:
+            raise Exception("Invalid max_body_size format")
+        MAX_LIMIT = 10 * 1024 * 1024  # 10MB
+        if limit > MAX_LIMIT:
+            raise Exception("max_body_size exceeds maximum allowed size (10MB)")
+
+        content_length = request.content_length or 0
+        if content_length > limit:
+            raise Exception(f"Request body too large: {content_length} > {limit}")
+
+    def _validate_ip_whitelist(security_cfg):
+        """Allow only IPs listed in ip_whitelist."""
+        whitelist = security_cfg.get("ip_whitelist", [])
+        if not whitelist:
+            return
+
+        client_ip = request.remote_addr
+
+
+        for rule in whitelist:
+            if "/" in rule:
+                # CIDR notation
+                if ipaddress.ip_address(client_ip) in ipaddress.ip_network(rule, strict=False):
+                    return
+            else:
+                # Single IP
+                if client_ip == rule:
+                    return
+
+        raise Exception(f"IP {client_ip} is not allowed by whitelist")
+
+    def _validate_rate_limit(security_cfg):
+        """Simple in-memory rate limiting."""
+        rl = security_cfg.get("rate_limit")
+        if not rl:
+            return
+
+        limit = int(rl.get("limit", 60))
+        if limit <= 0:
+            raise Exception("rate_limit.limit must be > 0")
+        per = rl.get("per", "minute")
+
+        window = {
+            "second": 1,
+            "minute": 60,
+            "hour": 3600,
+            "day": 86400,
+        }.get(per)
+
+        if not window:
+            raise Exception(f"Invalid rate_limit.per: {per}")
+
+        capacity = limit
+        rate = limit / window
+        cost = 1
+
+        key = f"rl:tb:{agent_id}"
+        now = time.time()
 
         try:
-        canvas = Canvas(cvs.dsl, tenant_id, agent_id)
+            res = REDIS_CONN.lua_token_bucket(
+                keys=[key],
+                args=[capacity, rate, now, cost],
+                client=REDIS_CONN.REDIS,
+            )
+
+            allowed = int(res[0])
+            if allowed != 1:
+                raise Exception("Too many requests (rate limit exceeded)")
+
         except Exception as e:
-        return get_json_result(
+            raise Exception(f"Rate limit error: {e}")
-            data=False, message=str(e),
-            code=RetCode.EXCEPTION_ERROR)
 
-    async def sse():
+    def _validate_token_auth(security_cfg):
-        nonlocal canvas
+        """Validate header-based token authentication."""
+        token_cfg = security_cfg.get("token",{})
+        header = token_cfg.get("token_header")
+        token_value = token_cfg.get("token_value")
+
+        provided = request.headers.get(header)
+        if provided != token_value:
+            raise Exception("Invalid token authentication")
+
+    def _validate_basic_auth(security_cfg):
+        """Validate HTTP Basic Auth credentials."""
+        auth_cfg = security_cfg.get("basic_auth", {})
+        username = auth_cfg.get("username")
+        password = auth_cfg.get("password")
+
+        auth = request.authorization
+        if not auth or auth.username != username or auth.password != password:
+            raise Exception("Invalid Basic Auth credentials")
+
+    def _validate_jwt_auth(security_cfg):
+        """Validate JWT token in Authorization header."""
+        jwt_cfg = security_cfg.get("jwt", {})
+        secret = jwt_cfg.get("secret")
+        if not secret:
+            raise Exception("JWT secret not configured")
+        required_claims = jwt_cfg.get("required_claims", [])
+
+        auth_header = request.headers.get("Authorization", "")
+        if not auth_header.startswith("Bearer "):
+            raise Exception("Missing Bearer token")
+
+        token = auth_header[len("Bearer "):].strip()
+        if not token:
+            raise Exception("Empty Bearer token")
+
+        alg = (jwt_cfg.get("algorithm") or "HS256").upper()
+
+        decode_kwargs = {
+            "key": secret,
+            "algorithms": [alg],
+        }
+        options = {}
+        if jwt_cfg.get("audience"):
+            decode_kwargs["audience"] = jwt_cfg["audience"]
+            options["verify_aud"] = True
+        else:
+            options["verify_aud"] = False
+
+        if jwt_cfg.get("issuer"):
+            decode_kwargs["issuer"] = jwt_cfg["issuer"]
+            options["verify_iss"] = True
+        else:
+            options["verify_iss"] = False
         try:
-            async for ans in canvas.run(query=req.get("query", ""), files=req.get("files", []), user_id=req.get("user_id", tenant_id), webhook_payload=req):
+            decoded = jwt.decode(
-                yield "data:" + json.dumps(ans, ensure_ascii=False) + "\n\n"
+                token,
+                options=options,
+                **decode_kwargs,
+            )
+        except Exception as e:
+            raise Exception(f"Invalid JWT: {str(e)}")
+
+        raw_required_claims = jwt_cfg.get("required_claims", [])
+        if isinstance(raw_required_claims, str):
+            required_claims = [raw_required_claims]
+        elif isinstance(raw_required_claims, (list, tuple, set)):
+            required_claims = list(raw_required_claims)
+        else:
+            required_claims = []
+
+        required_claims = [
+            c for c in required_claims
+            if isinstance(c, str) and c.strip()
+        ]
+
+        RESERVED_CLAIMS = {"exp", "sub", "aud", "iss", "nbf", "iat"}
+        for claim in required_claims:
+            if claim in RESERVED_CLAIMS:
+                raise Exception(f"Reserved JWT claim cannot be required: {claim}")
+
+        for claim in required_claims:
+            if claim not in decoded:
+                raise Exception(f"Missing JWT claim: {claim}")
+
+        return decoded
+
+    try:
+        security_config=webhook_cfg.get("security", {})
+        await validate_webhook_security(security_config)
+    except Exception as e:
+        return get_data_error_result(code=RetCode.BAD_REQUEST,message=str(e)),RetCode.BAD_REQUEST
+    if not isinstance(cvs.dsl, str):
+        dsl = json.dumps(cvs.dsl, ensure_ascii=False)
+    try:
+        canvas = Canvas(dsl, cvs.user_id, agent_id)
+    except Exception as e:
+        resp=get_data_error_result(code=RetCode.BAD_REQUEST,message=str(e))
+        resp.status_code = RetCode.BAD_REQUEST
+        return resp
+
+    # 7. Parse request body
+    async def parse_webhook_request(content_type):
+        """Parse request based on content-type and return structured data."""
+
+        # 1. Query
+        query_data = {k: v for k, v in request.args.items()}
+
+        # 2. Headers
+        header_data = {k: v for k, v in request.headers.items()}
+
+        # 3. Body
+        ctype = request.headers.get("Content-Type", "").split(";")[0].strip()
+        if ctype and ctype != content_type:
+            raise ValueError(
+                f"Invalid Content-Type: expect '{content_type}', got '{ctype}'"
+            )
+
+        body_data: dict = {}
+
+        try:
+            if ctype == "application/json":
+                body_data = await request.get_json() or {}
+
+            elif ctype == "multipart/form-data":
+                nonlocal canvas
+                form = await request.form
+                files = await request.files
+
+                body_data = {}
+
+                for key, value in form.items():
+                    body_data[key] = value
+
+                if len(files) > 10:
+                    raise Exception("Too many uploaded files")
+                for key, file in files.items():
+                    desc = FileService.upload_info(
+                        cvs.user_id,           # user
+                        file,              # FileStorage
+                        None                   # url (None for webhook)
+                    )
+                    file_parsed= await canvas.get_files_async([desc])
+                    body_data[key] = file_parsed
+
+            elif ctype == "application/x-www-form-urlencoded":
+                form = await request.form
+                body_data = dict(form)
+
+            else:
+                # text/plain / octet-stream / empty / unknown
+                raw = await request.get_data()
+                if raw:
+                    try:
+                        body_data = json.loads(raw.decode("utf-8"))
+                    except Exception:
+                        body_data = {}
+                else:
+                    body_data = {}
+
+        except Exception:
+            body_data = {}
+
+        return {
+            "query": query_data,
+            "headers": header_data,
+            "body": body_data,
+            "content_type": ctype,
+        }
+
+    def extract_by_schema(data, schema, name="section"):
+        """
+        Extract only fields defined in schema.
+        Required fields must exist.
+        Optional fields default to type-based default values.
+        Type validation included.
+        """
+        props = schema.get("properties", {})
+        required = schema.get("required", [])
+
+        extracted = {}
+
+        for field, field_schema in props.items():
+            field_type = field_schema.get("type")
+
+            # 1. Required field missing
+            if field in required and field not in data:
+                raise Exception(f"{name} missing required field: {field}")
+
+            # 2. Optional → default value
+            if field not in data:
+                extracted[field] = default_for_type(field_type)
+                continue
+
+            raw_value = data[field]
+
+            # 3. Auto convert value
+            try:
+                value = auto_cast_value(raw_value, field_type)
+            except Exception as e:
+                raise Exception(f"{name}.{field} auto-cast failed: {str(e)}")
+
+            # 4. Type validation
+            if not validate_type(value, field_type):
+                raise Exception(
+                    f"{name}.{field} type mismatch: expected {field_type}, got {type(value).__name__}"
+                )
+
+            extracted[field] = value
+
+        return extracted
+
+
+    def default_for_type(t):
+        """Return default value for the given schema type."""
+        if t == "file":
+            return []
+        if t == "object":
+            return {}
+        if t == "boolean":
+            return False
+        if t == "number":
+            return 0
+        if t == "string":
+            return ""
+        if t and t.startswith("array"):
+            return []
+        if t == "null":
+            return None
+        return None
+
+    def auto_cast_value(value, expected_type):
+        """Convert string values into schema type when possible."""
+
+        # Non-string values already good
+        if not isinstance(value, str):
+            return value
+
+        v = value.strip()
+
+        # Boolean
+        if expected_type == "boolean":
+            if v.lower() in ["true", "1"]:
+                return True
+            if v.lower() in ["false", "0"]:
+                return False
+            raise Exception(f"Cannot convert '{value}' to boolean")
+
+        # Number
+        if expected_type == "number":
+            # integer
+            if v.isdigit() or (v.startswith("-") and v[1:].isdigit()):
+                return int(v)
+
+            # float
+            try:
+                return float(v)
+            except Exception:
+                raise Exception(f"Cannot convert '{value}' to number")
+
+        # Object
+        if expected_type == "object":
+            try:
+                parsed = json.loads(v)
+                if isinstance(parsed, dict):
+                    return parsed
+                else:
+                    raise Exception("JSON is not an object")
+            except Exception:
+                raise Exception(f"Cannot convert '{value}' to object")
+
+        # Array <T>
+        if expected_type.startswith("array"):
+            try:
+                parsed = json.loads(v)
+                if isinstance(parsed, list):
+                    return parsed
+                else:
+                    raise Exception("JSON is not an array")
+            except Exception:
+                raise Exception(f"Cannot convert '{value}' to array")
+
+        # String (accept original)
+        if expected_type == "string":
+            return value
+
+        # File
+        if expected_type == "file":
+            return value
+        # Default: do nothing
+        return value
+
+
+    def validate_type(value, t):
+        """Validate value type against schema type t."""
+        if t == "file":
+            return isinstance(value, list)
+
+        if t == "string":
+            return isinstance(value, str)
+
+        if t == "number":
+            return isinstance(value, (int, float))
+
+        if t == "boolean":
+            return isinstance(value, bool)
+
+        if t == "object":
+            return isinstance(value, dict)
+
+        # array<string> / array<number> / array<object>
+        if t.startswith("array"):
+            if not isinstance(value, list):
+                return False
+
+            if "<" in t and ">" in t:
+                inner = t[t.find("<") + 1 : t.find(">")]
+
+                # Check each element type
+                for item in value:
+                    if not validate_type(item, inner):
+                        return False
+
+            return True
+
+        return True
+    parsed = await parse_webhook_request(webhook_cfg.get("content_types"))
+    SCHEMA = webhook_cfg.get("schema", {"query": {}, "headers": {}, "body": {}})
+
+    # Extract strictly by schema
+    try:
+        query_clean  = extract_by_schema(parsed["query"],   SCHEMA.get("query", {}),  name="query")
+        header_clean = extract_by_schema(parsed["headers"], SCHEMA.get("headers", {}), name="headers")
+        body_clean   = extract_by_schema(parsed["body"],    SCHEMA.get("body", {}),    name="body")
+    except Exception as e:
+        return get_data_error_result(code=RetCode.BAD_REQUEST,message=str(e)),RetCode.BAD_REQUEST
+
+    clean_request = {
+        "query": query_clean,
+        "headers": header_clean,
+        "body": body_clean,
+        "input": parsed
+    }
+
+    execution_mode = webhook_cfg.get("execution_mode", "Immediately")
+    response_cfg = webhook_cfg.get("response", {})
+
+    def append_webhook_trace(agent_id: str, start_ts: float,event: dict, ttl=600):
+        key = f"webhook-trace-{agent_id}-logs"
+
+        raw = REDIS_CONN.get(key)
+        obj = json.loads(raw) if raw else {"webhooks": {}}
+
+        ws = obj["webhooks"].setdefault(
+            str(start_ts),
+            {"start_ts": start_ts, "events": []}
+        )
+
+        ws["events"].append({
+            "ts": time.time(),
+            **event
+        })
+
+        REDIS_CONN.set_obj(key, obj, ttl)
+
+    if execution_mode == "Immediately":
+        status = response_cfg.get("status", 200)
+        try:
+            status = int(status)
+        except (TypeError, ValueError):
+            return get_data_error_result(code=RetCode.BAD_REQUEST,message=str(f"Invalid response status code: {status}")),RetCode.BAD_REQUEST
+
+        if not (200 <= status <= 399):
+            return get_data_error_result(code=RetCode.BAD_REQUEST,message=str(f"Invalid response status code: {status}, must be between 200 and 399")),RetCode.BAD_REQUEST
+
+        body_tpl = response_cfg.get("body_template", "")
+
+        def parse_body(body: str):
+            if not body:
+                return None, "application/json"
+
+            try:
+                parsed = json.loads(body)
+                return parsed, "application/json"
+            except (json.JSONDecodeError, TypeError):
+                return body, "text/plain"
+
+
+        body, content_type = parse_body(body_tpl)
+        resp = Response(
+            json.dumps(body, ensure_ascii=False) if content_type == "application/json" else body,
+            status=status,
+            content_type=content_type,
+        )
+
+        async def background_run():
+            try:
+                async for ans in canvas.run(
+                    query="",
+                    user_id=cvs.user_id,
+                    webhook_payload=clean_request
+                ):
+                    if is_test:
+                        append_webhook_trace(agent_id, start_ts, ans)
+
+                if is_test:
+                    append_webhook_trace(
+                        agent_id,
+                        start_ts,
+                        {
+                            "event": "finished",
+                            "elapsed_time": time.time() - start_ts,
+                            "success": True,
+                        }
+                    )
 
                 cvs.dsl = json.loads(str(canvas))
-            UserCanvasService.update_by_id(req["id"], cvs.to_dict())
+                UserCanvasService.update_by_id(cvs.user_id, cvs.to_dict())
-        except Exception as e:
-            logging.exception(e)
-            yield "data:" + json.dumps({"code": 500, "message": str(e), "data": False}, ensure_ascii=False) + "\n\n"
 
-    resp = Response(sse(), mimetype="text/event-stream")
+            except Exception as e:
-    resp.headers.add_header("Cache-control", "no-cache")
+                logging.exception("Webhook background run failed")
-    resp.headers.add_header("Connection", "keep-alive")
+                if is_test:
-    resp.headers.add_header("X-Accel-Buffering", "no")
+                    try:
-    resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
+                        append_webhook_trace(
+                            agent_id,
+                            start_ts,
+                            {
+                                "event": "error",
+                                "message": str(e),
+                                "error_type": type(e).__name__,
+                            }
+                        )
+                        append_webhook_trace(
+                            agent_id,
+                            start_ts,
+                            {
+                                "event": "finished",
+                                "elapsed_time": time.time() - start_ts,
+                                "success": False,
+                            }
+                        )
+                    except Exception:
+                        logging.exception("Failed to append webhook trace")
+
+        asyncio.create_task(background_run())
         return resp
+    else:
+        async def sse():
+            nonlocal canvas
+            contents: list[str] = []
+
+            try:
+                async for ans in canvas.run(
+                    query="",
+                    user_id=cvs.user_id,
+                    webhook_payload=clean_request,
+                ):
+                    if ans["event"] == "message":
+                        content = ans["data"]["content"]
+                        if ans["data"].get("start_to_think", False):
+                            content = "<think>"
+                        elif ans["data"].get("end_to_think", False):
+                            content = "</think>"
+                        if content:
+                            contents.append(content)
+                    if is_test:
+                        append_webhook_trace(
+                            agent_id,
+                            start_ts,
+                            ans
+                        )
+                if is_test:
+                    append_webhook_trace(
+                        agent_id,
+                        start_ts,
+                        {
+                            "event": "finished",
+                            "elapsed_time": time.time() - start_ts,
+                            "success": True,
+                        }
+                    )
+                final_content = "".join(contents)
+                yield json.dumps(final_content, ensure_ascii=False)
+
+            except Exception as e:
+                if is_test:
+                    append_webhook_trace(
+                        agent_id,
+                        start_ts,
+                        {
+                            "event": "error",
+                            "message": str(e),
+                            "error_type": type(e).__name__,
+                        }
+                    )
+                    append_webhook_trace(
+                        agent_id,
+                        start_ts,
+                        {
+                            "event": "finished",
+                            "elapsed_time": time.time() - start_ts,
+                            "success": False,
+                        }
+                    )
+                yield json.dumps({"code": 500, "message": str(e)}, ensure_ascii=False)
+
+        resp = Response(sse(), mimetype="application/json")
+        return resp
+
+
+@manager.route("/webhook_trace/<agent_id>", methods=["GET"])  # noqa: F821
+async def webhook_trace(agent_id: str):
+    def encode_webhook_id(start_ts: str) -> str:
+        WEBHOOK_ID_SECRET = "webhook_id_secret"
+        sig = hmac.new(
+            WEBHOOK_ID_SECRET.encode("utf-8"),
+            start_ts.encode("utf-8"),
+            hashlib.sha256,
+        ).digest()
+        return base64.urlsafe_b64encode(sig).decode("utf-8").rstrip("=")
+
+    def decode_webhook_id(enc_id: str, webhooks: dict) -> str | None:
+        for ts in webhooks.keys():
+            if encode_webhook_id(ts) == enc_id:
+                return ts
+        return None
+    since_ts = request.args.get("since_ts", type=float)
+    webhook_id = request.args.get("webhook_id")
+
+    key = f"webhook-trace-{agent_id}-logs"
+    raw = REDIS_CONN.get(key)
+
+    if since_ts is None:
+        now = time.time()
+        return get_json_result(
+            data={
+                "webhook_id": None,
+                "events": [],
+                "next_since_ts": now,
+                "finished": False,
+            }
+        )
+
+    if not raw:
+        return get_json_result(
+            data={
+                "webhook_id": None,
+                "events": [],
+                "next_since_ts": since_ts,
+                "finished": False,
+            }
+        )
+
+    obj = json.loads(raw)
+    webhooks = obj.get("webhooks", {})
+
+    if webhook_id is None:
+        candidates = [
+            float(k) for k in webhooks.keys() if float(k) > since_ts
+        ]
+
+        if not candidates:
+            return get_json_result(
+                data={
+                    "webhook_id": None,
+                    "events": [],
+                    "next_since_ts": since_ts,
+                    "finished": False,
+                }
+            )
+
+        start_ts = min(candidates)
+        real_id = str(start_ts)
+        webhook_id = encode_webhook_id(real_id)
+
+        return get_json_result(
+            data={
+                "webhook_id": webhook_id,
+                "events": [],
+                "next_since_ts": start_ts,
+                "finished": False,
+            }
+        )
+
+    real_id = decode_webhook_id(webhook_id, webhooks)
+
+    if not real_id:
+        return get_json_result(
+            data={
+                "webhook_id": webhook_id,
+                "events": [],
+                "next_since_ts": since_ts,
+                "finished": True,
+            }
+        )
+
+    ws = webhooks.get(str(real_id))
+    events = ws.get("events", [])
+    new_events = [e for e in events if e.get("ts", 0) > since_ts]
+
+    next_ts = since_ts
+    for e in new_events:
+        next_ts = max(next_ts, e["ts"])
+
+    finished = any(e.get("event") == "finished" for e in new_events)
+
+    return get_json_result(
+        data={
+            "webhook_id": webhook_id,
+            "events": new_events,
+            "next_since_ts": next_ts,
+            "finished": finished,
+        }
+    )

api/apps/sdk/chat.py

@@ -21,13 +21,13 @@ from api.db.services.tenant_llm_service import TenantLLMService
 from api.db.services.user_service import TenantService
 from common.misc_utils import get_uuid
 from common.constants import RetCode, StatusEnum
-from api.utils.api_utils import check_duplicate_ids, get_error_data_result, get_result, token_required, request_json
+from api.utils.api_utils import check_duplicate_ids, get_error_data_result, get_result, token_required, get_request_json
 
 
 @manager.route("/chats", methods=["POST"])  # noqa: F821
 @token_required
 async def create(tenant_id):
-    req = await request_json()
+    req = await get_request_json()
     ids = [i for i in req.get("dataset_ids", []) if i]
     for kb_id in ids:
         kbs = KnowledgebaseService.accessible(kb_id=kb_id, user_id=tenant_id)
@@ -92,7 +92,7 @@ async def create(tenant_id):
     req["tenant_id"] = tenant_id
     # prompt more parameter
     default_prompt = {
-        "system": """You are an intelligent assistant. Please summarize the content of the knowledge base to answer the question. Please list the data in the knowledge base and answer in detail. When all knowledge base content is irrelevant to the question, your answer must include the sentence "The answer you are looking for is not found in the knowledge base!" Answers need to consider chat history.
+        "system": """You are an intelligent assistant. Please summarize the content of the dataset to answer the question. Please list the data in the dataset and answer in detail. When all dataset content is irrelevant to the question, your answer must include the sentence "The answer you are looking for is not found in the dataset!" Answers need to consider chat history.
       Here is the knowledge base:
       {knowledge}
       The above is the knowledge base.""",
@@ -146,7 +146,7 @@ async def create(tenant_id):
 async def update(tenant_id, chat_id):
     if not DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value):
         return get_error_data_result(message="You do not own the chat")
-    req = await request_json()
+    req = await get_request_json()
     ids = req.get("dataset_ids", [])
     if "show_quotation" in req:
         req["do_refer"] = req.pop("show_quotation")
@@ -174,7 +174,9 @@ async def update(tenant_id, chat_id):
             req["llm_id"] = llm.pop("model_name")
             if req.get("llm_id") is not None:
                 llm_name, llm_factory = TenantLLMService.split_model_name_and_factory(req["llm_id"])
-                if not TenantLLMService.query(tenant_id=tenant_id, llm_name=llm_name, llm_factory=llm_factory, model_type="chat"):
+                model_type = llm.pop("model_type")
+                model_type = model_type if model_type in ["chat", "image2text"] else "chat"
+                if not TenantLLMService.query(tenant_id=tenant_id, llm_name=llm_name, llm_factory=llm_factory, model_type=model_type):
                     return get_error_data_result(f"`model_name` {req.get('llm_id')} doesn't exist")
         req["llm_setting"] = req.pop("llm")
     e, tenant = TenantService.get_by_id(tenant_id)
@@ -229,7 +231,7 @@ async def update(tenant_id, chat_id):
 async def delete_chats(tenant_id):
     errors = []
     success_count = 0
-    req = await request_json()
+    req = await get_request_json()
     if not req:
         ids = None
     else:
@@ -250,7 +252,6 @@ async def delete_chats(tenant_id):
             continue
         temp_dict = {"status": StatusEnum.INVALID.value}
         success_count += DialogService.update_by_id(id, temp_dict)
-        print(success_count, "$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$", flush=True)
 
     if errors:
         if success_count > 0:

api/apps/sdk/dify_retrieval.py

@@ -15,14 +15,14 @@
 #
 import logging
 
-from quart import request, jsonify
+from quart import jsonify
 
 from api.db.services.document_service import DocumentService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMBundle
-from api.utils.api_utils import validate_request, build_error_result, apikey_required
+from common.metadata_utils import meta_filter, convert_conditions
+from api.utils.api_utils import apikey_required, build_error_result, get_request_json, validate_request
 from rag.app.tag import label_question
-from api.db.services.dialog_service import meta_filter, convert_conditions
 from common.constants import RetCode, LLMType
 from common import settings
 
@@ -113,7 +113,7 @@ async def retrieval(tenant_id):
       404:
         description: Knowledge base or document not found
     """
-    req = await request.json
+    req = await get_request_json()
     question = req["query"]
     kb_id = req["knowledge_id"]
     use_kg = req.get("use_kg", False)

api/apps/sdk/doc.py

@@ -14,6 +14,7 @@
 #  limitations under the License.
 #
 import datetime
+import json
 import logging
 import pathlib
 import re
@@ -33,10 +34,10 @@ from api.db.services.file_service import FileService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMBundle
 from api.db.services.tenant_llm_service import TenantLLMService
-from api.db.services.task_service import TaskService, queue_tasks
+from api.db.services.task_service import TaskService, queue_tasks, cancel_all_task_of
-from api.db.services.dialog_service import meta_filter, convert_conditions
+from common.metadata_utils import meta_filter, convert_conditions
 from api.utils.api_utils import check_duplicate_ids, construct_json_result, get_error_data_result, get_parser_config, get_result, server_error_response, token_required, \
-    request_json
+    get_request_json
 from rag.app.qa import beAdoc, rmPrefix
 from rag.app.tag import label_question
 from rag.nlp import rag_tokenizer, search
@@ -231,12 +232,12 @@ async def update_doc(tenant_id, dataset_id, document_id):
         schema:
           type: object
     """
-    req = await request_json()
+    req = await get_request_json()
     if not KnowledgebaseService.query(id=dataset_id, tenant_id=tenant_id):
         return get_error_data_result(message="You don't own the dataset.")
     e, kb = KnowledgebaseService.get_by_id(dataset_id)
     if not e:
-        return get_error_data_result(message="Can't find this knowledgebase!")
+        return get_error_data_result(message="Can't find this dataset!")
     doc = DocumentService.query(kb_id=dataset_id, id=document_id)
     if not doc:
         return get_error_data_result(message="The dataset doesn't own the document.")
@@ -321,9 +322,7 @@ async def update_doc(tenant_id, dataset_id, document_id):
             try:
                 if not DocumentService.update_by_id(doc.id, {"status": str(status)}):
                     return get_error_data_result(message="Database error (Document update)!")
-
                 settings.docStoreConn.update({"doc_id": doc.id}, {"available_int": status}, search.index_name(kb.tenant_id), doc.kb_id)
-                return get_result(data=True)
             except Exception as e:
                 return server_error_response(e)
 
@@ -350,12 +349,10 @@ async def update_doc(tenant_id, dataset_id, document_id):
     }
     renamed_doc = {}
     for key, value in doc.to_dict().items():
-        if key == "run":
-            renamed_doc["run"] = run_mapping.get(str(value))
         new_key = key_mapping.get(key, key)
         renamed_doc[new_key] = value
         if key == "run":
-            renamed_doc["run"] = run_mapping.get(value)
+            renamed_doc["run"] = run_mapping.get(str(value))
 
     return get_result(data=renamed_doc)
 
@@ -555,13 +552,29 @@ def list_docs(dataset_id, tenant_id):
     run_status           = q.getlist("run")
     create_time_from     = int(q.get("create_time_from", 0))
     create_time_to       = int(q.get("create_time_to", 0))
+    metadata_condition_raw = q.get("metadata_condition")
+    metadata_condition = {}
+    if metadata_condition_raw:
+        try:
+            metadata_condition = json.loads(metadata_condition_raw)
+        except Exception:
+            return get_error_data_result(message="metadata_condition must be valid JSON.")
+    if metadata_condition and not isinstance(metadata_condition, dict):
+        return get_error_data_result(message="metadata_condition must be an object.")
 
-    # map run status (accept text or numeric) - align with API parameter
+    # map run status (text or numeric) - align with API parameter
     run_status_text_to_numeric = {"UNSTART": "0", "RUNNING": "1", "CANCEL": "2", "DONE": "3", "FAIL": "4"}
     run_status_converted = [run_status_text_to_numeric.get(v, v) for v in run_status]
 
+    doc_ids_filter = None
+    if metadata_condition:
+        metas = DocumentService.get_flatted_meta_by_kbs([dataset_id])
+        doc_ids_filter = meta_filter(metas, convert_conditions(metadata_condition), metadata_condition.get("logic", "and"))
+        if metadata_condition.get("conditions") and not doc_ids_filter:
+            return get_result(data={"total": 0, "docs": []})
+
     docs, total = DocumentService.get_list(
-        dataset_id, page, page_size, orderby, desc, keywords, document_id, name, suffix, run_status_converted
+        dataset_id, page, page_size, orderby, desc, keywords, document_id, name, suffix, run_status_converted, doc_ids_filter
     )
 
     # time range filter (0 means no bound)
@@ -590,6 +603,70 @@ def list_docs(dataset_id, tenant_id):
 
     return get_result(data={"total": total, "docs": output_docs})
 
+
+@manager.route("/datasets/<dataset_id>/metadata/summary", methods=["GET"])  # noqa: F821
+@token_required
+def metadata_summary(dataset_id, tenant_id):
+    if not KnowledgebaseService.accessible(kb_id=dataset_id, user_id=tenant_id):
+        return get_error_data_result(message=f"You don't own the dataset {dataset_id}. ")
+
+    try:
+        summary = DocumentService.get_metadata_summary(dataset_id)
+        return get_result(data={"summary": summary})
+    except Exception as e:
+        return server_error_response(e)
+
+
+@manager.route("/datasets/<dataset_id>/metadata/update", methods=["POST"])  # noqa: F821
+@token_required
+async def metadata_batch_update(dataset_id, tenant_id):
+    if not KnowledgebaseService.accessible(kb_id=dataset_id, user_id=tenant_id):
+        return get_error_data_result(message=f"You don't own the dataset {dataset_id}. ")
+
+    req = await get_request_json()
+    selector = req.get("selector", {}) or {}
+    updates = req.get("updates", []) or []
+    deletes = req.get("deletes", []) or []
+
+    if not isinstance(selector, dict):
+        return get_error_data_result(message="selector must be an object.")
+    if not isinstance(updates, list) or not isinstance(deletes, list):
+        return get_error_data_result(message="updates and deletes must be lists.")
+
+    metadata_condition = selector.get("metadata_condition", {}) or {}
+    if metadata_condition and not isinstance(metadata_condition, dict):
+        return get_error_data_result(message="metadata_condition must be an object.")
+
+    document_ids = selector.get("document_ids", []) or []
+    if document_ids and not isinstance(document_ids, list):
+        return get_error_data_result(message="document_ids must be a list.")
+
+    for upd in updates:
+        if not isinstance(upd, dict) or not upd.get("key") or "value" not in upd:
+            return get_error_data_result(message="Each update requires key and value.")
+    for d in deletes:
+        if not isinstance(d, dict) or not d.get("key"):
+            return get_error_data_result(message="Each delete requires key.")
+
+    kb_doc_ids = KnowledgebaseService.list_documents_by_ids([dataset_id])
+    target_doc_ids = set(kb_doc_ids)
+    if document_ids:
+        invalid_ids = set(document_ids) - set(kb_doc_ids)
+        if invalid_ids:
+            return get_error_data_result(message=f"These documents do not belong to dataset {dataset_id}: {', '.join(invalid_ids)}")
+        target_doc_ids = set(document_ids)
+
+    if metadata_condition:
+        metas = DocumentService.get_flatted_meta_by_kbs([dataset_id])
+        filtered_ids = set(meta_filter(metas, convert_conditions(metadata_condition), metadata_condition.get("logic", "and")))
+        target_doc_ids = target_doc_ids & filtered_ids
+        if metadata_condition.get("conditions") and not target_doc_ids:
+            return get_result(data={"updated": 0, "matched_docs": 0})
+
+    target_doc_ids = list(target_doc_ids)
+    updated = DocumentService.batch_update_metadata(dataset_id, target_doc_ids, updates, deletes)
+    return get_result(data={"updated": updated, "matched_docs": len(target_doc_ids)})
+
 @manager.route("/datasets/<dataset_id>/documents", methods=["DELETE"])  # noqa: F821
 @token_required
 async def delete(tenant_id, dataset_id):
@@ -631,7 +708,7 @@ async def delete(tenant_id, dataset_id):
     """
     if not KnowledgebaseService.accessible(kb_id=dataset_id, user_id=tenant_id):
         return get_error_data_result(message=f"You don't own the dataset {dataset_id}. ")
-    req = await request_json()
+    req = await get_request_json()
     if not req:
         doc_ids = None
     else:
@@ -741,7 +818,7 @@ async def parse(tenant_id, dataset_id):
     """
     if not KnowledgebaseService.accessible(kb_id=dataset_id, user_id=tenant_id):
         return get_error_data_result(message=f"You don't own the dataset {dataset_id}.")
-    req = await request_json()
+    req = await get_request_json()
     if not req.get("document_ids"):
         return get_error_data_result("`document_ids` is required")
     doc_list = req.get("document_ids")
@@ -824,7 +901,7 @@ async def stop_parsing(tenant_id, dataset_id):
     """
     if not KnowledgebaseService.accessible(kb_id=dataset_id, user_id=tenant_id):
         return get_error_data_result(message=f"You don't own the dataset {dataset_id}.")
-    req = await request_json()
+    req = await get_request_json()
 
     if not req.get("document_ids"):
         return get_error_data_result("`document_ids` is required")
@@ -839,6 +916,8 @@ async def stop_parsing(tenant_id, dataset_id):
             return get_error_data_result(message=f"You don't own the document {id}.")
         if int(doc[0].progress) == 1 or doc[0].progress == 0:
             return get_error_data_result("Can't stop parsing document with progress at 0 or 1")
+        # Send cancellation signal via Redis to stop background task
+        cancel_all_task_of(id)
         info = {"run": "2", "progress": 0, "chunk_num": 0}
         DocumentService.update_by_id(id, info)
         settings.docStoreConn.delete({"doc_id": doc[0].id}, search.index_name(tenant_id), dataset_id)
@@ -892,7 +971,7 @@ def list_chunks(tenant_id, dataset_id, document_id):
         type: string
         required: false
         default: ""
-        description: Chunk Id.
+        description: Chunk id.
       - in: header
         name: Authorization
         type: string
@@ -1096,7 +1175,7 @@ async def add_chunk(tenant_id, dataset_id, document_id):
     if not doc:
         return get_error_data_result(message=f"You don't own the document {document_id}.")
     doc = doc[0]
-    req = await request_json()
+    req = await get_request_json()
     if not str(req.get("content", "")).strip():
         return get_error_data_result(message="`content` is required")
     if "important_keywords" in req:
@@ -1202,7 +1281,7 @@ async def rm_chunk(tenant_id, dataset_id, document_id):
     docs = DocumentService.get_by_ids([document_id])
     if not docs:
         raise LookupError(f"Can't find the document with ID {document_id}!")
-    req = await request_json()
+    req = await get_request_json()
     condition = {"doc_id": document_id}
     if "chunk_ids" in req:
         unique_chunk_ids, duplicate_messages = check_duplicate_ids(req["chunk_ids"], "chunk")
@@ -1288,7 +1367,7 @@ async def update_chunk(tenant_id, dataset_id, document_id, chunk_id):
     if not doc:
         return get_error_data_result(message=f"You don't own the document {document_id}.")
     doc = doc[0]
-    req = await request_json()
+    req = await get_request_json()
     if "content" in req and req["content"] is not None:
         content = req["content"]
     else:
@@ -1411,7 +1490,7 @@ async def retrieval_test(tenant_id):
                     format: float
                     description: Similarity score.
     """
-    req = await request_json()
+    req = await get_request_json()
     if not req.get("dataset_ids"):
         return get_error_data_result("`dataset_ids` is required.")
     kb_ids = req["dataset_ids"]
@@ -1446,6 +1525,9 @@ async def retrieval_test(tenant_id):
         metadata_condition = req.get("metadata_condition", {}) or {}
         metas = DocumentService.get_meta_by_kbs(kb_ids)
         doc_ids = meta_filter(metas, convert_conditions(metadata_condition), metadata_condition.get("logic", "and"))
+        # If metadata_condition has conditions but no docs match, return empty result
+        if not doc_ids and metadata_condition.get("conditions"):
+            return get_result(data={"total": 0, "chunks": [], "doc_aggs": {}})
         if metadata_condition and not doc_ids:
             doc_ids = ["-999"]
     similarity_threshold = float(req.get("similarity_threshold", 0.2))
@@ -1467,11 +1549,11 @@ async def retrieval_test(tenant_id):
             rerank_mdl = LLMBundle(kb.tenant_id, LLMType.RERANK, llm_name=req["rerank_id"])
 
         if langs:
-            question = cross_languages(kb.tenant_id, None, question, langs)
+            question = await cross_languages(kb.tenant_id, None, question, langs)
 
         if req.get("keyword", False):
             chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
-            question += keyword_extraction(chat_mdl, question)
+            question += await keyword_extraction(chat_mdl, question)
 
         ranks = settings.retriever.retrieval(
             question,

api/apps/sdk/files.py

@@ -14,7 +14,7 @@
 #  limitations under the License.
 #
 
-
+import asyncio
 import pathlib
 import re
 from quart import request, make_response
@@ -23,14 +23,15 @@ from pathlib import Path
 from api.db.services.document_service import DocumentService
 from api.db.services.file2document_service import File2DocumentService
 from api.db.services.knowledgebase_service import KnowledgebaseService
-from api.utils.api_utils import server_error_response, token_required
+from api.utils.api_utils import get_json_result, get_request_json, server_error_response, token_required
 from common.misc_utils import get_uuid
 from api.db import FileType
 from api.db.services import duplicate_name
 from api.db.services.file_service import FileService
-from api.utils.api_utils import get_json_result
 from api.utils.file_utils import filename_type
+from api.utils.web_utils import CONTENT_TYPE_MAP
 from common import settings
+from common.constants import RetCode
 
 
 @manager.route('/file/upload', methods=['POST'])  # noqa: F821
@@ -40,7 +41,7 @@ async def upload(tenant_id):
     Upload a file to the system.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     parameters:
@@ -86,19 +87,19 @@ async def upload(tenant_id):
         pf_id = root_folder["id"]
 
     if 'file' not in files:
-        return get_json_result(data=False, message='No file part!', code=400)
+        return get_json_result(data=False, message='No file part!', code=RetCode.BAD_REQUEST)
     file_objs = files.getlist('file')
 
     for file_obj in file_objs:
         if file_obj.filename == '':
-            return get_json_result(data=False, message='No selected file!', code=400)
+            return get_json_result(data=False, message='No selected file!', code=RetCode.BAD_REQUEST)
 
     file_res = []
 
     try:
         e, pf_folder = FileService.get_by_id(pf_id)
         if not e:
-            return get_json_result(data=False, message="Can't find this folder!", code=404)
+            return get_json_result(data=False, message="Can't find this folder!", code=RetCode.NOT_FOUND)
 
         for file_obj in file_objs:
             # Handle file path
@@ -114,13 +115,13 @@ async def upload(tenant_id):
             if file_len != len_id_list:
                 e, file = FileService.get_by_id(file_id_list[len_id_list - 1])
                 if not e:
-                    return get_json_result(data=False, message="Folder not found!", code=404)
+                    return get_json_result(data=False, message="Folder not found!", code=RetCode.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_json_result(data=False, message="Folder not found!", code=404)
+                    return get_json_result(data=False, message="Folder not found!", code=RetCode.NOT_FOUND)
                 last_folder = FileService.create_folder(file, file_id_list[len_id_list - 2], file_obj_names,
                                                         len_id_list)
 
@@ -156,7 +157,7 @@ async def create(tenant_id):
     Create a new file or folder.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     parameters:
@@ -193,16 +194,16 @@ async def create(tenant_id):
                 type:
                   type: string
     """
-    req = await request.json
+    req = await get_request_json()
-    pf_id = await request.json.get("parent_id")
+    pf_id = req.get("parent_id")
-    input_file_type = await request.json.get("type")
+    input_file_type = req.get("type")
     if not pf_id:
         root_folder = FileService.get_root_folder(tenant_id)
         pf_id = root_folder["id"]
 
     try:
         if not FileService.is_parent_folder_exist(pf_id):
-            return get_json_result(data=False, message="Parent Folder Doesn't Exist!", code=400)
+            return get_json_result(data=False, message="Parent Folder Doesn't Exist!", code=RetCode.BAD_REQUEST)
         if FileService.query(name=req["name"], parent_id=pf_id):
             return get_json_result(data=False, message="Duplicated folder name in the same folder.", code=409)
 
@@ -229,12 +230,12 @@ async def create(tenant_id):
 
 @manager.route('/file/list', methods=['GET'])  # noqa: F821
 @token_required
-def list_files(tenant_id):
+async def list_files(tenant_id):
     """
     List files under a specific folder.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     parameters:
@@ -306,13 +307,13 @@ def list_files(tenant_id):
     try:
         e, file = FileService.get_by_id(pf_id)
         if not e:
-            return get_json_result(message="Folder not found!", code=404)
+            return get_json_result(message="Folder not found!", code=RetCode.NOT_FOUND)
 
         files, total = FileService.get_by_pf_id(tenant_id, pf_id, page_number, items_per_page, orderby, desc, keywords)
 
         parent_folder = FileService.get_parent_folder(pf_id)
         if not parent_folder:
-            return get_json_result(message="File not found!", code=404)
+            return get_json_result(message="File not found!", code=RetCode.NOT_FOUND)
 
         return get_json_result(data={"total": total, "files": files, "parent_folder": parent_folder.to_json()})
     except Exception as e:
@@ -321,12 +322,12 @@ def list_files(tenant_id):
 
 @manager.route('/file/root_folder', methods=['GET'])  # noqa: F821
 @token_required
-def get_root_folder(tenant_id):
+async def get_root_folder(tenant_id):
     """
     Get user's root folder.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     responses:
@@ -357,12 +358,12 @@ def get_root_folder(tenant_id):
 
 @manager.route('/file/parent_folder', methods=['GET'])  # noqa: F821
 @token_required
-def get_parent_folder():
+async def get_parent_folder():
     """
     Get parent folder info of a file.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     parameters:
@@ -392,7 +393,7 @@ def get_parent_folder():
     try:
         e, file = FileService.get_by_id(file_id)
         if not e:
-            return get_json_result(message="Folder not found!", code=404)
+            return get_json_result(message="Folder not found!", code=RetCode.NOT_FOUND)
 
         parent_folder = FileService.get_parent_folder(file_id)
         return get_json_result(data={"parent_folder": parent_folder.to_json()})
@@ -402,12 +403,12 @@ def get_parent_folder():
 
 @manager.route('/file/all_parent_folder', methods=['GET'])  # noqa: F821
 @token_required
-def get_all_parent_folders(tenant_id):
+async def get_all_parent_folders(tenant_id):
     """
     Get all parent folders of a file.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     parameters:
@@ -439,7 +440,7 @@ def get_all_parent_folders(tenant_id):
     try:
         e, file = FileService.get_by_id(file_id)
         if not e:
-            return get_json_result(message="Folder not found!", code=404)
+            return get_json_result(message="Folder not found!", code=RetCode.NOT_FOUND)
 
         parent_folders = FileService.get_all_parent_folders(file_id)
         parent_folders_res = [folder.to_json() for folder in parent_folders]
@@ -455,7 +456,7 @@ async def rm(tenant_id):
     Delete one or multiple files/folders.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     parameters:
@@ -481,40 +482,40 @@ async def rm(tenant_id):
               type: boolean
               example: true
     """
-    req = await request.json
+    req = await get_request_json()
     file_ids = req["file_ids"]
     try:
         for file_id in file_ids:
             e, file = FileService.get_by_id(file_id)
             if not e:
-                return get_json_result(message="File or Folder not found!", code=404)
+                return get_json_result(message="File or Folder not found!", code=RetCode.NOT_FOUND)
             if not file.tenant_id:
-                return get_json_result(message="Tenant not found!", code=404)
+                return get_json_result(message="Tenant not found!", code=RetCode.NOT_FOUND)
 
             if file.type == FileType.FOLDER.value:
                 file_id_list = FileService.get_all_innermost_file_ids(file_id, [])
                 for inner_file_id in file_id_list:
                     e, file = FileService.get_by_id(inner_file_id)
                     if not e:
-                        return get_json_result(message="File not found!", code=404)
+                        return get_json_result(message="File not found!", code=RetCode.NOT_FOUND)
                     settings.STORAGE_IMPL.rm(file.parent_id, file.location)
                 FileService.delete_folder_by_pf_id(tenant_id, file_id)
             else:
                 settings.STORAGE_IMPL.rm(file.parent_id, file.location)
                 if not FileService.delete(file):
-                    return get_json_result(message="Database error (File removal)!", code=500)
+                    return get_json_result(message="Database error (File removal)!", code=RetCode.SERVER_ERROR)
 
             informs = File2DocumentService.get_by_file_id(file_id)
             for inform in informs:
                 doc_id = inform.document_id
                 e, doc = DocumentService.get_by_id(doc_id)
                 if not e:
-                    return get_json_result(message="Document not found!", code=404)
+                    return get_json_result(message="Document not found!", code=RetCode.NOT_FOUND)
                 tenant_id = DocumentService.get_tenant_id(doc_id)
                 if not tenant_id:
-                    return get_json_result(message="Tenant not found!", code=404)
+                    return get_json_result(message="Tenant not found!", code=RetCode.NOT_FOUND)
                 if not DocumentService.remove_document(doc, tenant_id):
-                    return get_json_result(message="Database error (Document removal)!", code=500)
+                    return get_json_result(message="Database error (Document removal)!", code=RetCode.SERVER_ERROR)
             File2DocumentService.delete_by_file_id(file_id)
 
         return get_json_result(data=True)
@@ -529,7 +530,7 @@ async def rename(tenant_id):
     Rename a file.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     parameters:
@@ -556,27 +557,27 @@ async def rename(tenant_id):
               type: boolean
               example: true
     """
-    req = await request.json
+    req = await get_request_json()
     try:
         e, file = FileService.get_by_id(req["file_id"])
         if not e:
-            return get_json_result(message="File not found!", code=404)
+            return get_json_result(message="File not found!", code=RetCode.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, message="The extension of file can't be changed", code=400)
+            return get_json_result(data=False, message="The extension of file can't be changed", code=RetCode.BAD_REQUEST)
 
         for existing_file in FileService.query(name=req["name"], pf_id=file.parent_id):
             if existing_file.name == req["name"]:
                 return get_json_result(data=False, message="Duplicated file name in the same folder.", code=409)
 
         if not FileService.update_by_id(req["file_id"], {"name": req["name"]}):
-            return get_json_result(message="Database error (File rename)!", code=500)
+            return get_json_result(message="Database error (File rename)!", code=RetCode.SERVER_ERROR)
 
         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_json_result(message="Database error (Document rename)!", code=500)
+                return get_json_result(message="Database error (Document rename)!", code=RetCode.SERVER_ERROR)
 
         return get_json_result(data=True)
     except Exception as e:
@@ -590,7 +591,7 @@ async def get(tenant_id, file_id):
     Download a file.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     produces:
@@ -606,13 +607,13 @@ async def get(tenant_id, file_id):
         description: File stream
         schema:
           type: file
-      404:
+      RetCode.NOT_FOUND:
         description: File not found
     """
     try:
         e, file = FileService.get_by_id(file_id)
         if not e:
-            return get_json_result(message="Document not found!", code=404)
+            return get_json_result(message="Document not found!", code=RetCode.NOT_FOUND)
 
         blob = settings.STORAGE_IMPL.get(file.parent_id, file.location)
         if not blob:
@@ -630,6 +631,19 @@ async def get(tenant_id, file_id):
     except Exception as e:
         return server_error_response(e)
 
+@manager.route("/file/download/<attachment_id>", methods=["GET"])  # noqa: F821
+@token_required
+async def download_attachment(tenant_id,attachment_id):
+    try:
+        ext = request.args.get("ext", "markdown")
+        data = await asyncio.to_thread(settings.STORAGE_IMPL.get, tenant_id, attachment_id)
+        response = await make_response(data)
+        response.headers.set("Content-Type", CONTENT_TYPE_MAP.get(ext, f"application/{ext}"))
+
+        return response
+
+    except Exception as e:
+        return server_error_response(e)
 
 @manager.route('/file/mv', methods=['POST'])  # noqa: F821
 @token_required
@@ -638,7 +652,7 @@ async def move(tenant_id):
     Move one or multiple files to another folder.
     ---
     tags:
-      - File Management
+      - File
     security:
       - ApiKeyAuth: []
     parameters:
@@ -667,7 +681,7 @@ async def move(tenant_id):
               type: boolean
               example: true
     """
-    req = await request.json
+    req = await get_request_json()
     try:
         file_ids = req["src_file_ids"]
         parent_id = req["dest_file_id"]
@@ -677,13 +691,13 @@ async def move(tenant_id):
         for file_id in file_ids:
             file = files_dict[file_id]
             if not file:
-                return get_json_result(message="File or Folder not found!", code=404)
+                return get_json_result(message="File or Folder not found!", code=RetCode.NOT_FOUND)
             if not file.tenant_id:
-                return get_json_result(message="Tenant not found!", code=404)
+                return get_json_result(message="Tenant not found!", code=RetCode.NOT_FOUND)
 
         fe, _ = FileService.get_by_id(parent_id)
         if not fe:
-            return get_json_result(message="Parent Folder not found!", code=404)
+            return get_json_result(message="Parent Folder not found!", code=RetCode.NOT_FOUND)
 
         FileService.move_file(file_ids, parent_id)
         return get_json_result(data=True)
@@ -694,7 +708,7 @@ async def move(tenant_id):
 @manager.route('/file/convert', methods=['POST'])  # noqa: F821
 @token_required
 async def convert(tenant_id):
-    req = await request.json
+    req = await get_request_json()
     kb_ids = req["kb_ids"]
     file_ids = req["file_ids"]
     file2documents = []
@@ -705,7 +719,7 @@ async def convert(tenant_id):
         for file_id in file_ids:
             file = files_set[file_id]
             if not file:
-                return get_json_result(message="File not found!", code=404)
+                return get_json_result(message="File not found!", code=RetCode.NOT_FOUND)
             file_ids_list = [file_id]
             if file.type == FileType.FOLDER.value:
                 file_ids_list = FileService.get_all_innermost_file_ids(file_id, [])
@@ -716,13 +730,13 @@ async def convert(tenant_id):
                     doc_id = inform.document_id
                     e, doc = DocumentService.get_by_id(doc_id)
                     if not e:
-                        return get_json_result(message="Document not found!", code=404)
+                        return get_json_result(message="Document not found!", code=RetCode.NOT_FOUND)
                     tenant_id = DocumentService.get_tenant_id(doc_id)
                     if not tenant_id:
-                        return get_json_result(message="Tenant not found!", code=404)
+                        return get_json_result(message="Tenant not found!", code=RetCode.NOT_FOUND)
                     if not DocumentService.remove_document(doc, tenant_id):
                         return get_json_result(
-                            message="Database error (Document removal)!", code=404)
+                            message="Database error (Document removal)!", code=RetCode.NOT_FOUND)
                 File2DocumentService.delete_by_file_id(id)
 
                 # insert
@@ -730,11 +744,11 @@ async def convert(tenant_id):
                     e, kb = KnowledgebaseService.get_by_id(kb_id)
                     if not e:
                         return get_json_result(
-                            message="Can't find this knowledgebase!", code=404)
+                            message="Can't find this dataset!", code=RetCode.NOT_FOUND)
                     e, file = FileService.get_by_id(id)
                     if not e:
                         return get_json_result(
-                            message="Can't find this file!", code=404)
+                            message="Can't find this file!", code=RetCode.NOT_FOUND)
 
                     doc = DocumentService.insert({
                         "id": get_uuid(),

api/apps/sdk/session.py

@@ -14,6 +14,7 @@
 #  limitations under the License.
 #
 import json
+import copy
 import re
 import time
 
@@ -25,27 +26,30 @@ from api.db.db_models import APIToken
 from api.db.services.api_service import API4ConversationService
 from api.db.services.canvas_service import UserCanvasService, completion_openai
 from api.db.services.canvas_service import completion as agent_completion
-from api.db.services.conversation_service import ConversationService, iframe_completion
+from api.db.services.conversation_service import ConversationService
-from api.db.services.conversation_service import completion as rag_completion
+from api.db.services.conversation_service import async_iframe_completion as iframe_completion
-from api.db.services.dialog_service import DialogService, ask, chat, gen_mindmap, meta_filter
+from api.db.services.conversation_service import async_completion as rag_completion
+from api.db.services.dialog_service import DialogService, async_ask, async_chat, gen_mindmap
 from api.db.services.document_service import DocumentService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.llm_service import LLMBundle
+from common.metadata_utils import apply_meta_data_filter, convert_conditions, meta_filter
 from api.db.services.search_service import SearchService
 from api.db.services.user_service import UserTenantService
 from common.misc_utils import get_uuid
 from api.utils.api_utils import check_duplicate_ids, get_data_openai, get_error_data_result, get_json_result, \
-    get_result, server_error_response, token_required, validate_request
+    get_result, get_request_json, server_error_response, token_required, validate_request
 from rag.app.tag import label_question
 from rag.prompts.template import load_prompt
-from rag.prompts.generator import cross_languages, gen_meta_filter, keyword_extraction, chunks_format
+from rag.prompts.generator import cross_languages, keyword_extraction, chunks_format
 from common.constants import RetCode, LLMType, StatusEnum
 from common import settings
 
+
 @manager.route("/chats/<chat_id>/sessions", methods=["POST"])  # noqa: F821
 @token_required
 async def create(tenant_id, chat_id):
-    req = await request.json
+    req = await get_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:
@@ -73,7 +77,7 @@ async def create(tenant_id, chat_id):
 
 @manager.route("/agents/<agent_id>/sessions", methods=["POST"])  # noqa: F821
 @token_required
-def create_agent_session(tenant_id, agent_id):
+async def create_agent_session(tenant_id, agent_id):
     user_id = request.args.get("user_id", tenant_id)
     e, cvs = UserCanvasService.get_by_id(agent_id)
     if not e:
@@ -98,7 +102,7 @@ def create_agent_session(tenant_id, agent_id):
 @manager.route("/chats/<chat_id>/sessions/<session_id>", methods=["PUT"])  # noqa: F821
 @token_required
 async def update(tenant_id, chat_id, session_id):
-    req = await request.json
+    req = await get_request_json()
     req["dialog_id"] = chat_id
     conv_id = session_id
     conv = ConversationService.query(id=conv_id, dialog_id=chat_id)
@@ -120,16 +124,38 @@ async def update(tenant_id, chat_id, session_id):
 @manager.route("/chats/<chat_id>/completions", methods=["POST"])  # noqa: F821
 @token_required
 async def chat_completion(tenant_id, chat_id):
-    req = await request.json
+    req = await get_request_json()
     if not req:
         req = {"question": ""}
     if not req.get("session_id"):
         req["question"] = ""
-    if not DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value):
+    dia = DialogService.query(tenant_id=tenant_id, id=chat_id, status=StatusEnum.VALID.value)
+    if not dia:
         return get_error_data_result(f"You don't own the chat {chat_id}")
+    dia = dia[0]
     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']}")
+
+    metadata_condition = req.get("metadata_condition") or {}
+    if metadata_condition and not isinstance(metadata_condition, dict):
+        return get_error_data_result(message="metadata_condition must be an object.")
+
+    if metadata_condition and req.get("question"):
+        metas = DocumentService.get_meta_by_kbs(dia.kb_ids or [])
+        filtered_doc_ids = meta_filter(
+            metas,
+            convert_conditions(metadata_condition),
+            metadata_condition.get("logic", "and"),
+        )
+        if metadata_condition.get("conditions") and not filtered_doc_ids:
+            filtered_doc_ids = ["-999"]
+
+        if filtered_doc_ids:
+            req["doc_ids"] = ",".join(filtered_doc_ids)
+        else:
+            req.pop("doc_ids", None)
+
     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")
@@ -140,7 +166,7 @@ async def chat_completion(tenant_id, chat_id):
         return resp
     else:
         answer = None
-        for ans in rag_completion(tenant_id, chat_id, **req):
+        async for ans in rag_completion(tenant_id, chat_id, **req):
             answer = ans
             break
         return get_result(data=answer)
@@ -192,7 +218,19 @@ async def chat_completion_openai_like(tenant_id, chat_id):
             {"role": "user", "content": "Can you tell me how to install neovim"},
         ],
         stream=stream,
-        extra_body={"reference": reference}
+        extra_body={
+            "reference": reference,
+            "metadata_condition": {
+                "logic": "and",
+                "conditions": [
+                    {
+                        "name": "author",
+                        "comparison_operator": "is",
+                        "value": "bob"
+                    }
+                ]
+            }
+        }
     )
 
     if stream:
@@ -206,9 +244,13 @@ async def chat_completion_openai_like(tenant_id, chat_id):
         if reference:
             print(completion.choices[0].message.reference)
     """
-    req = await request.get_json()
+    req = await get_request_json()
 
-    need_reference = bool(req.get("reference", False))
+    extra_body = req.get("extra_body") or {}
+    if extra_body and not isinstance(extra_body, dict):
+        return get_error_data_result("extra_body must be an object.")
+
+    need_reference = bool(extra_body.get("reference", False))
 
     messages = req.get("messages", [])
     # To prevent empty [] input
@@ -226,6 +268,22 @@ async def chat_completion_openai_like(tenant_id, chat_id):
         return get_error_data_result(f"You don't own the chat {chat_id}")
     dia = dia[0]
 
+    metadata_condition = extra_body.get("metadata_condition") or {}
+    if metadata_condition and not isinstance(metadata_condition, dict):
+        return get_error_data_result(message="metadata_condition must be an object.")
+
+    doc_ids_str = None
+    if metadata_condition:
+        metas = DocumentService.get_meta_by_kbs(dia.kb_ids or [])
+        filtered_doc_ids = meta_filter(
+            metas,
+            convert_conditions(metadata_condition),
+            metadata_condition.get("logic", "and"),
+        )
+        if metadata_condition.get("conditions") and not filtered_doc_ids:
+            filtered_doc_ids = ["-999"]
+        doc_ids_str = ",".join(filtered_doc_ids) if filtered_doc_ids else None
+
     # Filter system and non-sense assistant messages
     msg = []
     for m in messages:
@@ -244,7 +302,7 @@ async def chat_completion_openai_like(tenant_id, chat_id):
         # The value for the usage field on all chunks except for the last one will be null.
         # The usage field on the last chunk contains token usage statistics for the entire request.
         # The choices field on the last chunk will always be an empty array [].
-        def streamed_response_generator(chat_id, dia, msg):
+        async def streamed_response_generator(chat_id, dia, msg):
             token_used = 0
             answer_cache = ""
             reasoning_cache = ""
@@ -273,7 +331,10 @@ async def chat_completion_openai_like(tenant_id, chat_id):
             }
 
             try:
-                for ans in chat(dia, msg, True, toolcall_session=toolcall_session, tools=tools, quote=need_reference):
+                chat_kwargs = {"toolcall_session": toolcall_session, "tools": tools, "quote": need_reference}
+                if doc_ids_str:
+                    chat_kwargs["doc_ids"] = doc_ids_str
+                async for ans in async_chat(dia, msg, True, **chat_kwargs):
                     last_ans = ans
                     answer = ans["answer"]
 
@@ -325,8 +386,7 @@ async def chat_completion_openai_like(tenant_id, chat_id):
             response["choices"][0]["delta"]["content"] = None
             response["choices"][0]["delta"]["reasoning_content"] = None
             response["choices"][0]["finish_reason"] = "stop"
-            response["usage"] = {"prompt_tokens": len(prompt), "completion_tokens": token_used,
+            response["usage"] = {"prompt_tokens": len(prompt), "completion_tokens": token_used, "total_tokens": len(prompt) + token_used}
-                                 "total_tokens": len(prompt) + token_used}
             if need_reference:
                 response["choices"][0]["delta"]["reference"] = chunks_format(last_ans.get("reference", []))
                 response["choices"][0]["delta"]["final_content"] = last_ans.get("answer", "")
@@ -341,7 +401,10 @@ async def chat_completion_openai_like(tenant_id, chat_id):
         return resp
     else:
         answer = None
-        for ans in chat(dia, msg, False, toolcall_session=toolcall_session, tools=tools, quote=need_reference):
+        chat_kwargs = {"toolcall_session": toolcall_session, "tools": tools, "quote": need_reference}
+        if doc_ids_str:
+            chat_kwargs["doc_ids"] = doc_ids_str
+        async for ans in async_chat(dia, msg, False, **chat_kwargs):
             # focus answer content only
             answer = ans
             break
@@ -384,7 +447,7 @@ async def chat_completion_openai_like(tenant_id, chat_id):
 @validate_request("model", "messages")  # noqa: F821
 @token_required
 async def agents_completion_openai_compatibility(tenant_id, agent_id):
-    req = await request.json
+    req = await get_request_json()
     tiktokenenc = tiktoken.get_encoding("cl100k_base")
     messages = req.get("messages", [])
     if not messages:
@@ -442,11 +505,13 @@ async def agents_completion_openai_compatibility(tenant_id, agent_id):
 @manager.route("/agents/<agent_id>/completions", methods=["POST"])  # noqa: F821
 @token_required
 async def agent_completions(tenant_id, agent_id):
-    req = await request.json
+    req = await get_request_json()
+    return_trace = bool(req.get("return_trace", False))
 
     if req.get("stream", True):
 
         async def generate():
+            trace_items = []
             async for answer in agent_completion(tenant_id=tenant_id, agent_id=agent_id, **req):
                 if isinstance(answer, str):
                     try:
@@ -454,7 +519,21 @@ async def agent_completions(tenant_id, agent_id):
                     except Exception:
                         continue
 
-                if ans.get("event") not in ["message", "message_end"]:
+                event = ans.get("event")
+                if event == "node_finished":
+                    if return_trace:
+                        data = ans.get("data", {})
+                        trace_items.append(
+                            {
+                                "component_id": data.get("component_id"),
+                                "trace": [copy.deepcopy(data)],
+                            }
+                        )
+                        ans.setdefault("data", {})["trace"] = trace_items
+                        answer = "data:" + json.dumps(ans, ensure_ascii=False) + "\n\n"
+                    yield answer
+
+                if event not in ["message", "message_end"]:
                     continue
 
                 yield answer
@@ -471,6 +550,7 @@ async def agent_completions(tenant_id, agent_id):
     full_content = ""
     reference = {}
     final_ans = ""
+    trace_items = []
     async for answer in agent_completion(tenant_id=tenant_id, agent_id=agent_id, **req):
         try:
             ans = json.loads(answer[5:])
@@ -481,17 +561,28 @@ async def agent_completions(tenant_id, agent_id):
             if ans.get("data", {}).get("reference", None):
                 reference.update(ans["data"]["reference"])
 
+            if return_trace and ans.get("event") == "node_finished":
+                data = ans.get("data", {})
+                trace_items.append(
+                    {
+                        "component_id": data.get("component_id"),
+                        "trace": [copy.deepcopy(data)],
+                    }
+                )
+
             final_ans = ans
         except Exception as e:
             return get_result(data=f"**ERROR**: {str(e)}")
     final_ans["data"]["content"] = full_content
     final_ans["data"]["reference"] = reference
+    if return_trace and final_ans:
+        final_ans["data"]["trace"] = trace_items
     return get_result(data=final_ans)
 
 
 @manager.route("/chats/<chat_id>/sessions", methods=["GET"])  # noqa: F821
 @token_required
-def list_session(tenant_id, chat_id):
+async 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")
@@ -545,7 +636,7 @@ def list_session(tenant_id, chat_id):
 
 @manager.route("/agents/<agent_id>/sessions", methods=["GET"])  # noqa: F821
 @token_required
-def list_agent_session(tenant_id, agent_id):
+async 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")
@@ -614,7 +705,7 @@ async def delete(tenant_id, chat_id):
 
     errors = []
     success_count = 0
-    req = await request.json
+    req = await get_request_json()
     convs = ConversationService.query(dialog_id=chat_id)
     if not req:
         ids = None
@@ -662,7 +753,7 @@ async def delete(tenant_id, chat_id):
 async def delete_agent_session(tenant_id, agent_id):
     errors = []
     success_count = 0
-    req = await request.json
+    req = await get_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}")
@@ -715,7 +806,7 @@ async def delete_agent_session(tenant_id, agent_id):
 @manager.route("/sessions/ask", methods=["POST"])  # noqa: F821
 @token_required
 async def ask_about(tenant_id):
-    req = await request.json
+    req = await get_request_json()
     if not req.get("question"):
         return get_error_data_result("`question` is required.")
     if not req.get("dataset_ids"):
@@ -732,10 +823,10 @@ async def ask_about(tenant_id):
             return get_error_data_result(f"The dataset {kb_id} doesn't own parsed file")
     uid = tenant_id
 
-    def stream():
+    async def stream():
         nonlocal req, uid
         try:
-            for ans in ask(req["question"], req["kb_ids"], uid):
+            async for ans in async_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(
@@ -754,7 +845,7 @@ async def ask_about(tenant_id):
 @manager.route("/sessions/related_questions", methods=["POST"])  # noqa: F821
 @token_required
 async def related_questions(tenant_id):
-    req = await request.json
+    req = await get_request_json()
     if not req.get("question"):
         return get_error_data_result("`question` is required.")
     question = req["question"]
@@ -787,7 +878,7 @@ Reason:
  - 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(
+    ans = await chat_mdl.async_chat(
         prompt,
         [
             {
@@ -805,7 +896,7 @@ Related search terms:
 
 @manager.route("/chatbots/<dialog_id>/completions", methods=["POST"])  # noqa: F821
 async def chatbot_completions(dialog_id):
-    req = await request.json
+    req = await get_request_json()
 
     token = request.headers.get("Authorization").split()
     if len(token) != 2:
@@ -826,12 +917,12 @@ async def chatbot_completions(dialog_id):
         resp.headers.add_header("Content-Type", "text/event-stream; charset=utf-8")
         return resp
 
-    for answer in iframe_completion(dialog_id, **req):
+    async for answer in iframe_completion(dialog_id, **req):
         return get_result(data=answer)
 
 
 @manager.route("/chatbots/<dialog_id>/info", methods=["GET"])  # noqa: F821
-def chatbots_inputs(dialog_id):
+async def chatbots_inputs(dialog_id):
     token = request.headers.get("Authorization").split()
     if len(token) != 2:
         return get_error_data_result(message='Authorization is not valid!"')
@@ -855,7 +946,7 @@ def chatbots_inputs(dialog_id):
 
 @manager.route("/agentbots/<agent_id>/completions", methods=["POST"])  # noqa: F821
 async def agent_bot_completions(agent_id):
-    req = await request.json
+    req = await get_request_json()
 
     token = request.headers.get("Authorization").split()
     if len(token) != 2:
@@ -878,7 +969,7 @@ async def agent_bot_completions(agent_id):
 
 
 @manager.route("/agentbots/<agent_id>/inputs", methods=["GET"])  # noqa: F821
-def begin_inputs(agent_id):
+async def begin_inputs(agent_id):
     token = request.headers.get("Authorization").split()
     if len(token) != 2:
         return get_error_data_result(message='Authorization is not valid!"')
@@ -908,7 +999,7 @@ async def ask_about_embedded():
     if not objs:
         return get_error_data_result(message='Authentication error: API key is invalid!"')
 
-    req = await request.json
+    req = await get_request_json()
     uid = objs[0].tenant_id
 
     search_id = req.get("search_id", "")
@@ -917,10 +1008,10 @@ async def ask_about_embedded():
         if search_app := SearchService.get_detail(search_id):
             search_config = search_app.get("search_config", {})
 
-    def stream():
+    async def stream():
         nonlocal req, uid
         try:
-            for ans in ask(req["question"], req["kb_ids"], uid, search_config=search_config):
+            async for ans in async_ask(req["question"], req["kb_ids"], uid, search_config=search_config):
                 yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
         except Exception as e:
             yield "data:" + json.dumps(
@@ -947,7 +1038,7 @@ async def retrieval_test_embedded():
     if not objs:
         return get_error_data_result(message='Authentication error: API key is invalid!"')
 
-    req = await request.json
+    req = await get_request_json()
     page = int(req.get("page", 1))
     size = int(req.get("size", 30))
     question = req["question"]
@@ -963,28 +1054,31 @@ async def retrieval_test_embedded():
     use_kg = req.get("use_kg", False)
     top = int(req.get("top_k", 1024))
     langs = req.get("cross_languages", [])
-    tenant_ids = []
-
     tenant_id = objs[0].tenant_id
     if not tenant_id:
         return get_error_data_result(message="permission denined.")
 
+    async def _retrieval():
+        local_doc_ids = list(doc_ids) if doc_ids else []
+        tenant_ids = []
+        _question = question
+
+        meta_data_filter = {}
+        chat_mdl = None
         if req.get("search_id", ""):
             search_config = SearchService.get_detail(req.get("search_id", "")).get("search_config", {})
             meta_data_filter = search_config.get("meta_data_filter", {})
-        metas = DocumentService.get_meta_by_kbs(kb_ids)
+            if meta_data_filter.get("method") in ["auto", "semi_auto"]:
-        if meta_data_filter.get("method") == "auto":
                 chat_mdl = LLMBundle(tenant_id, LLMType.CHAT, llm_name=search_config.get("chat_id", ""))
-            filters: dict = gen_meta_filter(chat_mdl, metas, question)
+        else:
-            doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
+            meta_data_filter = req.get("meta_data_filter") or {}
-            if not doc_ids:
+            if meta_data_filter.get("method") in ["auto", "semi_auto"]:
-                doc_ids = None
+                chat_mdl = LLMBundle(tenant_id, LLMType.CHAT)
-        elif meta_data_filter.get("method") == "manual":
+
-            doc_ids.extend(meta_filter(metas, meta_data_filter["manual"], meta_data_filter.get("logic", "and")))
+        if meta_data_filter:
-            if meta_data_filter["manual"] and not doc_ids:
+            metas = DocumentService.get_meta_by_kbs(kb_ids)
-                doc_ids = ["-999"]
+            local_doc_ids = await apply_meta_data_filter(meta_data_filter, metas, _question, chat_mdl, local_doc_ids)
 
-    try:
         tenants = UserTenantService.query(user_id=tenant_id)
         for kb_id in kb_ids:
             for tenant in tenants:
@@ -992,7 +1086,7 @@ async def retrieval_test_embedded():
                     tenant_ids.append(tenant.tenant_id)
                     break
             else:
-                return get_json_result(data=False, message="Only owner of knowledgebase authorized for this operation.",
+                return get_json_result(data=False, message="Only owner of dataset authorized for this operation.",
                                        code=RetCode.OPERATING_ERROR)
 
         e, kb = KnowledgebaseService.get_by_id(kb_ids[0])
@@ -1000,7 +1094,7 @@ async def retrieval_test_embedded():
             return get_error_data_result(message="Knowledgebase not found!")
 
         if langs:
-            question = cross_languages(kb.tenant_id, None, question, langs)
+            _question = await cross_languages(kb.tenant_id, None, _question, langs)
 
         embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
 
@@ -1010,15 +1104,15 @@ async def retrieval_test_embedded():
 
         if req.get("keyword", False):
             chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
-            question += keyword_extraction(chat_mdl, question)
+            _question += await keyword_extraction(chat_mdl, _question)
 
-        labels = label_question(question, [kb])
+        labels = label_question(_question, [kb])
         ranks = settings.retriever.retrieval(
-            question, embd_mdl, tenant_ids, kb_ids, page, size, similarity_threshold, vector_similarity_weight, top,
+            _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"), rank_feature=labels
+            local_doc_ids, rerank_mdl=rerank_mdl, highlight=req.get("highlight"), rank_feature=labels
         )
         if use_kg:
-            ck = settings.kg_retriever.retrieval(question, tenant_ids, kb_ids, embd_mdl,
+            ck = settings.kg_retriever.retrieval(_question, tenant_ids, kb_ids, embd_mdl,
                                                  LLMBundle(kb.tenant_id, LLMType.CHAT))
             if ck["content_with_weight"]:
                 ranks["chunks"].insert(0, ck)
@@ -1028,6 +1122,9 @@ async def retrieval_test_embedded():
         ranks["labels"] = labels
 
         return get_json_result(data=ranks)
+
+    try:
+        return await _retrieval()
     except Exception as e:
         if str(e).find("not_found") > 0:
             return get_json_result(data=False, message="No chunk found! Check the chunk status please!",
@@ -1046,7 +1143,7 @@ async def related_questions_embedded():
     if not objs:
         return get_error_data_result(message='Authentication error: API key is invalid!"')
 
-    req = await request.json
+    req = await get_request_json()
     tenant_id = objs[0].tenant_id
     if not tenant_id:
         return get_error_data_result(message="permission denined.")
@@ -1064,7 +1161,7 @@ async def related_questions_embedded():
 
     gen_conf = search_config.get("llm_setting", {"temperature": 0.9})
     prompt = load_prompt("related_question")
-    ans = chat_mdl.chat(
+    ans = await chat_mdl.async_chat(
         prompt,
         [
             {
@@ -1081,7 +1178,7 @@ Related search terms:
 
 
 @manager.route("/searchbots/detail", methods=["GET"])  # noqa: F821
-def detail_share_embedded():
+async def detail_share_embedded():
     token = request.headers.get("Authorization").split()
     if len(token) != 2:
         return get_error_data_result(message='Authorization is not valid!"')
@@ -1123,12 +1220,12 @@ async def mindmap():
         return get_error_data_result(message='Authentication error: API key is invalid!"')
 
     tenant_id = objs[0].tenant_id
-    req = await request.json
+    req = await get_request_json()
 
     search_id = req.get("search_id", "")
     search_app = SearchService.get_detail(search_id) if search_id else {}
 
-    mind_map = gen_mindmap(req["question"], req["kb_ids"], tenant_id, search_app.get("search_config", {}))
+    mind_map =await gen_mindmap(req["question"], req["kb_ids"], tenant_id, search_app.get("search_config", {}))
     if "error" in mind_map:
         return server_error_response(Exception(mind_map["error"]))
     return get_json_result(data=mind_map)

api/apps/search_app.py

@@ -24,14 +24,14 @@ from api.db.services.search_service import SearchService
 from api.db.services.user_service import TenantService, UserTenantService
 from common.misc_utils import get_uuid
 from common.constants import RetCode, StatusEnum
-from api.utils.api_utils import get_data_error_result, get_json_result, not_allowed_parameters, server_error_response, validate_request
+from api.utils.api_utils import get_data_error_result, get_json_result, not_allowed_parameters, get_request_json, server_error_response, validate_request
 
 
 @manager.route("/create", methods=["post"])  # noqa: F821
 @login_required
 @validate_request("name")
 async def create():
-    req = await request.get_json()
+    req = await get_request_json()
     search_name = req["name"]
     description = req.get("description", "")
     if not isinstance(search_name, str):
@@ -66,7 +66,7 @@ async def create():
 @validate_request("search_id", "name", "search_config", "tenant_id")
 @not_allowed_parameters("id", "created_by", "create_time", "update_time", "create_date", "update_date", "created_by")
 async def update():
-    req = await request.get_json()
+    req = await get_request_json()
     if not isinstance(req["name"], str):
         return get_data_error_result(message="Search name must be string.")
     if req["name"].strip() == "":
@@ -150,7 +150,7 @@ async def list_search_app():
     else:
         desc = True
 
-    req = await request.get_json()
+    req = await get_request_json()
     owner_ids = req.get("owner_ids", [])
     try:
         if not owner_ids:
@@ -174,7 +174,7 @@ async def list_search_app():
 @login_required
 @validate_request("search_id")
 async def rm():
-    req = await request.get_json()
+    req = await get_request_json()
     search_id = req["search_id"]
     if not SearchService.accessible4deletion(search_id, current_user.id):
         return get_json_result(data=False, message="No authorization.", code=RetCode.AUTHENTICATION_ERROR)

api/apps/tenant_app.py

@@ -13,8 +13,8 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
-
+import logging
-from quart import request
+import asyncio
 from api.db import UserTenantRole
 from api.db.db_models import UserTenant
 from api.db.services.user_service import UserTenantService, UserService
@@ -22,10 +22,10 @@ from api.db.services.user_service import UserTenantService, UserService
 from common.constants import RetCode, StatusEnum
 from common.misc_utils import get_uuid
 from common.time_utils import delta_seconds
-from api.utils.api_utils import get_json_result, validate_request, server_error_response, get_data_error_result
+from api.utils.api_utils import get_data_error_result, get_json_result, get_request_json, server_error_response, validate_request
 from api.utils.web_utils import send_invite_email
 from common import settings
-from api.apps import smtp_mail_server, login_required, current_user
+from api.apps import login_required, current_user
 
 
 @manager.route("/<tenant_id>/user/list", methods=["GET"])  # noqa: F821
@@ -56,7 +56,7 @@ async def create(tenant_id):
             message='No authorization.',
             code=RetCode.AUTHENTICATION_ERROR)
 
-    req = await request.json
+    req = await get_request_json()
     invite_user_email = req["email"]
     invite_users = UserService.query(email=invite_user_email)
     if not invite_users:
@@ -81,20 +81,24 @@ async def create(tenant_id):
         role=UserTenantRole.INVITE,
         status=StatusEnum.VALID.value)
 
-    if smtp_mail_server and settings.SMTP_CONF:
+    try:
-        from threading import Thread
 
         user_name = ""
         _, user = UserService.get_by_id(current_user.id)
         if user:
             user_name = user.nickname
 
-        Thread(
+        asyncio.create_task(
-            target=send_invite_email,
+            send_invite_email(
-            args=(invite_user_email, settings.MAIL_FRONTEND_URL, tenant_id, user_name or current_user.email),
+                to_email=invite_user_email,
-            daemon=True
+                invite_url=settings.MAIL_FRONTEND_URL,
-        ).start()
+                tenant_id=tenant_id,
-
+                inviter=user_name or current_user.email
+            )
+        )
+    except Exception as e:
+        logging.exception(f"Failed to send invite email to {invite_user_email}: {e}")
+        return get_json_result(data=False, message="Failed to send invite email.", code=RetCode.SERVER_ERROR)
     usr = invite_users[0].to_dict()
     usr = {k: v for k, v in usr.items() if k in ["id", "avatar", "email", "nickname"]}
 

api/apps/user_app.py

@@ -21,8 +21,9 @@ import re
 import secrets
 import time
 from datetime import datetime
+import base64
 
-from quart import redirect, request, session, make_response
+from quart import make_response, redirect, request, session
 from werkzeug.security import check_password_hash, generate_password_hash
 
 from api.apps.auth import get_auth_client
@@ -39,12 +40,13 @@ from common.connection_utils import construct_response
 from api.utils.api_utils import (
     get_data_error_result,
     get_json_result,
+    get_request_json,
     server_error_response,
     validate_request,
 )
 from api.utils.crypt import decrypt
 from rag.utils.redis_conn import REDIS_CONN
-from api.apps import smtp_mail_server, login_required, current_user, login_user, logout_user
+from api.apps import login_required, current_user, login_user, logout_user
 from api.utils.web_utils import (
     send_email_html,
     OTP_LENGTH,
@@ -57,6 +59,7 @@ from api.utils.web_utils import (
     captcha_key,
 )
 from common import settings
+from common.http_client import async_request
 
 
 @manager.route("/login", methods=["POST", "GET"])  # noqa: F821
@@ -90,11 +93,14 @@ async def login():
         schema:
           type: object
     """
-    json_body = await request.json
+    json_body = await get_request_json()
     if not json_body:
         return get_json_result(data=False, code=RetCode.AUTHENTICATION_ERROR, message="Unauthorized!")
 
     email = json_body.get("email", "")
+    if email == "admin@ragflow.io":
+        return get_json_result(data=False, code=RetCode.AUTHENTICATION_ERROR, message="Default admin account cannot be used to login normal services!")
+    
     users = UserService.query(email=email)
     if not users:
         return get_json_result(
@@ -121,8 +127,8 @@ async def login():
         response_data = user.to_json()
         user.access_token = get_uuid()
         login_user(user)
-        user.update_time = (current_timestamp(),)
+        user.update_time = current_timestamp()
-        user.update_date = (datetime_format(datetime.now()),)
+        user.update_date = datetime_format(datetime.now())
         user.save()
         msg = "Welcome back!"
 
@@ -136,7 +142,7 @@ async def login():
 
 
 @manager.route("/login/channels", methods=["GET"])  # noqa: F821
-def get_login_channels():
+async def get_login_channels():
     """
     Get all supported authentication channels.
     """
@@ -157,7 +163,7 @@ def get_login_channels():
 
 
 @manager.route("/login/<channel>", methods=["GET"])  # noqa: F821
-def oauth_login(channel):
+async def oauth_login(channel):
     channel_config = settings.OAUTH_CONFIG.get(channel)
     if not channel_config:
         raise ValueError(f"Invalid channel name: {channel}")
@@ -170,7 +176,7 @@ def oauth_login(channel):
 
 
 @manager.route("/oauth/callback/<channel>", methods=["GET"])  # noqa: F821
-def oauth_callback(channel):
+async def oauth_callback(channel):
     """
     Handle the OAuth/OIDC callback for various channels dynamically.
     """
@@ -192,6 +198,9 @@ def oauth_callback(channel):
             return redirect("/?error=missing_code")
 
         # Exchange authorization code for access token
+        if hasattr(auth_cli, "async_exchange_code_for_token"):
+            token_info = await auth_cli.async_exchange_code_for_token(code)
+        else:
             token_info = auth_cli.exchange_code_for_token(code)
         access_token = token_info.get("access_token")
         if not access_token:
@@ -200,6 +209,9 @@ def oauth_callback(channel):
         id_token = token_info.get("id_token")
 
         # Fetch user info
+        if hasattr(auth_cli, "async_fetch_user_info"):
+            user_info = await auth_cli.async_fetch_user_info(access_token, id_token=id_token)
+        else:
             user_info = auth_cli.fetch_user_info(access_token, id_token=id_token)
         if not user_info.email:
             return redirect("/?error=email_missing")
@@ -259,7 +271,7 @@ def oauth_callback(channel):
 
 
 @manager.route("/github_callback", methods=["GET"])  # noqa: F821
-def github_callback():
+async def github_callback():
     """
     **Deprecated**, Use `/oauth/callback/<channel>` instead.
 
@@ -279,9 +291,8 @@ def github_callback():
         schema:
           type: object
     """
-    import requests
+    res = await async_request(
-
+        "POST",
-    res = requests.post(
         settings.GITHUB_OAUTH.get("url"),
         data={
             "client_id": settings.GITHUB_OAUTH.get("client_id"),
@@ -299,7 +310,7 @@ def github_callback():
 
     session["access_token"] = res["access_token"]
     session["access_token_from"] = "github"
-    user_info = user_info_from_github(session["access_token"])
+    user_info = await user_info_from_github(session["access_token"])
     email_address = user_info["email"]
     users = UserService.query(email=email_address)
     user_id = get_uuid()
@@ -348,7 +359,7 @@ def github_callback():
 
 
 @manager.route("/feishu_callback", methods=["GET"])  # noqa: F821
-def feishu_callback():
+async def feishu_callback():
     """
     Feishu OAuth callback endpoint.
     ---
@@ -366,9 +377,8 @@ def feishu_callback():
         schema:
           type: object
     """
-    import requests
+    app_access_token_res = await async_request(
-
+        "POST",
-    app_access_token_res = requests.post(
         settings.FEISHU_OAUTH.get("app_access_token_url"),
         data=json.dumps(
             {
@@ -382,7 +392,8 @@ def feishu_callback():
     if app_access_token_res["code"] != 0:
         return redirect("/?error=%s" % app_access_token_res)
 
-    res = requests.post(
+    res = await async_request(
+        "POST",
         settings.FEISHU_OAUTH.get("user_access_token_url"),
         data=json.dumps(
             {
@@ -403,7 +414,7 @@ def feishu_callback():
         return redirect("/?error=contact:user.email:readonly not in scope")
     session["access_token"] = res["data"]["access_token"]
     session["access_token_from"] = "feishu"
-    user_info = user_info_from_feishu(session["access_token"])
+    user_info = await user_info_from_feishu(session["access_token"])
     email_address = user_info["email"]
     users = UserService.query(email=email_address)
     user_id = get_uuid()
@@ -451,36 +462,34 @@ def feishu_callback():
     return redirect("/?auth=%s" % user.get_id())
 
 
-def user_info_from_feishu(access_token):
+async def user_info_from_feishu(access_token):
-    import requests
-
     headers = {
         "Content-Type": "application/json; charset=utf-8",
         "Authorization": f"Bearer {access_token}",
     }
-    res = requests.get("https://open.feishu.cn/open-apis/authen/v1/user_info", headers=headers)
+    res = await async_request("GET", "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
 
 
-def user_info_from_github(access_token):
+async def user_info_from_github(access_token):
-    import requests
-
     headers = {"Accept": "application/json", "Authorization": f"token {access_token}"}
-    res = requests.get(f"https://api.github.com/user?access_token={access_token}", headers=headers)
+    res = await async_request("GET", f"https://api.github.com/user?access_token={access_token}", headers=headers)
     user_info = res.json()
-    email_info = requests.get(
+    email_info_response = await async_request(
+        "GET",
         f"https://api.github.com/user/emails?access_token={access_token}",
         headers=headers,
-    ).json()
+    )
+    email_info = email_info_response.json()
     user_info["email"] = next((email for email in email_info if email["primary"]), None)["email"]
     return user_info
 
 
 @manager.route("/logout", methods=["GET"])  # noqa: F821
 @login_required
-def log_out():
+async def log_out():
     """
     User logout endpoint.
     ---
@@ -531,7 +540,7 @@ async def setting_user():
           type: object
     """
     update_dict = {}
-    request_data = await request.json
+    request_data = await get_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"])):
@@ -570,7 +579,7 @@ async def setting_user():
 
 @manager.route("/info", methods=["GET"])  # noqa: F821
 @login_required
-def user_profile():
+async def user_profile():
     """
     Get user profile information.
     ---
@@ -698,7 +707,7 @@ async def user_add():
             code=RetCode.OPERATING_ERROR,
         )
 
-    req = await request.json
+    req = await get_request_json()
     email_address = req["email"]
 
     # Validate the email address
@@ -755,7 +764,7 @@ async def user_add():
 
 @manager.route("/tenant_info", methods=["GET"])  # noqa: F821
 @login_required
-def tenant_info():
+async def tenant_info():
     """
     Get tenant information.
     ---
@@ -831,7 +840,7 @@ async def set_tenant_info():
         schema:
           type: object
     """
-    req = await request.json
+    req = await get_request_json()
     try:
         tid = req.pop("tenant_id")
         TenantService.update_by_id(tid, req)
@@ -875,7 +884,7 @@ async def forget_send_otp():
     - Verify the image captcha stored at captcha:{email} (case-insensitive).
     - On success, generate an email OTP (A–Z with length = OTP_LENGTH), store hash + salt (and timestamp) in Redis with TTL, reset attempts and cooldown, and send the OTP via email.
     """
-    req = await request.get_json()
+    req = await get_request_json()
     email = req.get("email") or ""
     captcha = (req.get("captcha") or "").strip()
 
@@ -918,47 +927,45 @@ async def forget_send_otp():
 
     ttl_min = OTP_TTL_SECONDS // 60
 
-    if not smtp_mail_server:
-        logging.warning("SMTP mail server not initialized; skip sending email.")
-    else:
     try:
-            send_email_html(
+        await send_email_html(
             subject="Your Password Reset Code",
             to_email=email,
             template_key="reset_code",
             code=otp,
             ttl_min=ttl_min,
         )
-        except Exception:
+
+    except Exception as e:
+        logging.exception(e)
         return get_json_result(data=False, code=RetCode.SERVER_ERROR, message="failed to send email")
 
     return get_json_result(data=True, code=RetCode.SUCCESS, message="verification passed, email sent")
 
 
-@manager.route("/forget", methods=["POST"])  # noqa: F821
+def _verified_key(email: str) -> str:
-async def forget():
+    return f"otp:verified:{email}"
+
+
+@manager.route("/forget/verify-otp", methods=["POST"])  # noqa: F821
+async def forget_verify_otp():
     """
-    POST: Verify email + OTP and reset password, then log the user in.
+    Verify email + OTP only. On success:
-    Request JSON: { email, otp, new_password, confirm_new_password }
+    - consume the OTP and attempt counters
+    - set a short-lived verified flag in Redis for the email
+    Request JSON: { email, otp }
     """
-    req = await request.get_json()
+    req = await get_request_json()
     email = req.get("email") or ""
     otp = (req.get("otp") or "").strip()
-    new_pwd = req.get("new_password")
-    new_pwd2 = req.get("confirm_new_password")
 
-    if not all([email, otp, new_pwd, new_pwd2]):
+    if not all([email, otp]):
-        return get_json_result(data=False, code=RetCode.ARGUMENT_ERROR, message="email, otp and passwords are required")
+        return get_json_result(data=False, code=RetCode.ARGUMENT_ERROR, message="email and otp are required")
-
-    # For reset, passwords are provided as-is (no decrypt needed)
-    if new_pwd != new_pwd2:
-        return get_json_result(data=False, code=RetCode.ARGUMENT_ERROR, message="passwords do not match")
 
     users = UserService.query(email=email)
     if not users:
         return get_json_result(data=False, code=RetCode.DATA_ERROR, message="invalid email")
 
-    user = users[0]
     # Verify OTP from Redis
     k_code, k_attempts, k_last, k_lock = otp_keys(email)
     if REDIS_CONN.get(k_lock):
@@ -974,7 +981,6 @@ async def forget():
     except Exception:
         return get_json_result(data=False, code=RetCode.EXCEPTION_ERROR, message="otp storage corrupted")
 
-    # Case-insensitive verification: OTP generated uppercase
     calc = hash_code(otp.upper(), salt)
     if calc != stored_hash:
         # bump attempts
@@ -987,23 +993,70 @@ async def forget():
             REDIS_CONN.set(k_lock, int(time.time()), ATTEMPT_LOCK_SECONDS)
         return get_json_result(data=False, code=RetCode.AUTHENTICATION_ERROR, message="expired otp")
 
-    # Success: consume OTP and reset password
+    # Success: consume OTP and attempts; mark verified
     REDIS_CONN.delete(k_code)
     REDIS_CONN.delete(k_attempts)
     REDIS_CONN.delete(k_last)
     REDIS_CONN.delete(k_lock)
 
+    # set verified flag with limited TTL, reuse OTP_TTL_SECONDS or smaller window
     try:
-        UserService.update_user_password(user.id, new_pwd)
+        REDIS_CONN.set(_verified_key(email), "1", OTP_TTL_SECONDS)
+    except Exception:
+        return get_json_result(data=False, code=RetCode.SERVER_ERROR, message="failed to set verification state")
+
+    return get_json_result(data=True, code=RetCode.SUCCESS, message="otp verified")
+
+
+@manager.route("/forget/reset-password", methods=["POST"])  # noqa: F821
+async def forget_reset_password():
+    """
+    Reset password after successful OTP verification.
+    Requires: { email, new_password, confirm_new_password }
+    Steps:
+    - check verified flag in Redis
+    - update user password
+    - auto login
+    - clear verified flag
+    """
+    
+    req = await get_request_json()
+    email = req.get("email") or ""
+    new_pwd = req.get("new_password")
+    new_pwd2 = req.get("confirm_new_password")
+
+    new_pwd_base64 = decrypt(new_pwd)
+    new_pwd_string = base64.b64decode(new_pwd_base64).decode('utf-8')
+    new_pwd2_string = base64.b64decode(decrypt(new_pwd2)).decode('utf-8')
+
+    REDIS_CONN.get(_verified_key(email))
+    if not REDIS_CONN.get(_verified_key(email)):
+        return get_json_result(data=False, code=RetCode.AUTHENTICATION_ERROR, message="email not verified")
+
+    if not all([email, new_pwd, new_pwd2]):
+        return get_json_result(data=False, code=RetCode.ARGUMENT_ERROR, message="email and passwords are required")
+
+    if new_pwd_string != new_pwd2_string:
+        return get_json_result(data=False, code=RetCode.ARGUMENT_ERROR, message="passwords do not match")
+
+    users = UserService.query_user_by_email(email=email)
+    if not users:
+        return get_json_result(data=False, code=RetCode.DATA_ERROR, message="invalid email")
+    
+    user = users[0]
+    try:
+        UserService.update_user_password(user.id, new_pwd_base64)
     except Exception as e:
         logging.exception(e)
         return get_json_result(data=False, code=RetCode.EXCEPTION_ERROR, message="failed to reset password")
 
-    # Auto login (reuse login flow)
+    # clear verified flag
-    user.access_token = get_uuid()
+    try:
-    login_user(user)
+        REDIS_CONN.delete(_verified_key(email))
-    user.update_time = (current_timestamp(),)
+    except Exception:
-    user.update_date = (datetime_format(datetime.now()),)
+        pass
-    user.save()
+
     msg = "Password reset successful. Logged in."
-    return construct_response(data=user.to_json(), auth=user.get_id(), message=msg)
+    return await construct_response(data=user.to_json(), auth=user.get_id(), message=msg)
+
+

api/constants.py

@@ -24,3 +24,5 @@ REQUEST_MAX_WAIT_SEC = 300
 
 DATASET_NAME_LIMIT = 128
 FILE_NAME_LEN_LIMIT = 255
+MEMORY_NAME_LIMIT = 128
+MEMORY_SIZE_LIMIT = 10*1024*1024 # Byte

api/db/db_models.py

@@ -749,7 +749,7 @@ class Knowledgebase(DataBaseModel):
 
     parser_id = CharField(max_length=32, null=False, help_text="default parser ID", default=ParserType.NAIVE.value, index=True)
     pipeline_id = CharField(max_length=32, null=True, help_text="Pipeline ID", index=True)
-    parser_config = JSONField(null=False, default={"pages": [[1, 1000000]]})
+    parser_config = JSONField(null=False, default={"pages": [[1, 1000000]], "table_context_size": 0, "image_context_size": 0})
     pagerank = IntegerField(default=0, index=False)
 
     graphrag_task_id = CharField(max_length=32, null=True, help_text="Graph RAG task ID", index=True)
@@ -774,7 +774,7 @@ class Document(DataBaseModel):
     kb_id = CharField(max_length=256, null=False, index=True)
     parser_id = CharField(max_length=32, null=False, help_text="default parser ID", index=True)
     pipeline_id = CharField(max_length=32, null=True, help_text="pipeline ID", index=True)
-    parser_config = JSONField(null=False, default={"pages": [[1, 1000000]]})
+    parser_config = JSONField(null=False, default={"pages": [[1, 1000000]], "table_context_size": 0, "image_context_size": 0})
     source_type = CharField(max_length=128, null=False, default="local", help_text="where dose this document come from", index=True)
     type = CharField(max_length=32, null=False, help_text="file extension", index=True)
     created_by = CharField(max_length=32, null=False, help_text="who created it", index=True)
@@ -1113,6 +1113,91 @@ class SyncLogs(DataBaseModel):
         db_table = "sync_logs"
 
 
+class EvaluationDataset(DataBaseModel):
+    """Ground truth dataset for RAG evaluation"""
+    id = CharField(max_length=32, primary_key=True)
+    tenant_id = CharField(max_length=32, null=False, index=True, help_text="tenant ID")
+    name = CharField(max_length=255, null=False, index=True, help_text="dataset name")
+    description = TextField(null=True, help_text="dataset description")
+    kb_ids = JSONField(null=False, help_text="knowledge base IDs to evaluate against")
+    created_by = CharField(max_length=32, null=False, index=True, help_text="creator user ID")
+    create_time = BigIntegerField(null=False, index=True, help_text="creation timestamp")
+    update_time = BigIntegerField(null=False, help_text="last update timestamp")
+    status = IntegerField(null=False, default=1, help_text="1=valid, 0=invalid")
+
+    class Meta:
+        db_table = "evaluation_datasets"
+
+
+class EvaluationCase(DataBaseModel):
+    """Individual test case in an evaluation dataset"""
+    id = CharField(max_length=32, primary_key=True)
+    dataset_id = CharField(max_length=32, null=False, index=True, help_text="FK to evaluation_datasets")
+    question = TextField(null=False, help_text="test question")
+    reference_answer = TextField(null=True, help_text="optional ground truth answer")
+    relevant_doc_ids = JSONField(null=True, help_text="expected relevant document IDs")
+    relevant_chunk_ids = JSONField(null=True, help_text="expected relevant chunk IDs")
+    metadata = JSONField(null=True, help_text="additional context/tags")
+    create_time = BigIntegerField(null=False, help_text="creation timestamp")
+
+    class Meta:
+        db_table = "evaluation_cases"
+
+
+class EvaluationRun(DataBaseModel):
+    """A single evaluation run"""
+    id = CharField(max_length=32, primary_key=True)
+    dataset_id = CharField(max_length=32, null=False, index=True, help_text="FK to evaluation_datasets")
+    dialog_id = CharField(max_length=32, null=False, index=True, help_text="dialog configuration being evaluated")
+    name = CharField(max_length=255, null=False, help_text="run name")
+    config_snapshot = JSONField(null=False, help_text="dialog config at time of evaluation")
+    metrics_summary = JSONField(null=True, help_text="aggregated metrics")
+    status = CharField(max_length=32, null=False, default="PENDING", help_text="PENDING/RUNNING/COMPLETED/FAILED")
+    created_by = CharField(max_length=32, null=False, index=True, help_text="user who started the run")
+    create_time = BigIntegerField(null=False, index=True, help_text="creation timestamp")
+    complete_time = BigIntegerField(null=True, help_text="completion timestamp")
+
+    class Meta:
+        db_table = "evaluation_runs"
+
+
+class EvaluationResult(DataBaseModel):
+    """Result for a single test case in an evaluation run"""
+    id = CharField(max_length=32, primary_key=True)
+    run_id = CharField(max_length=32, null=False, index=True, help_text="FK to evaluation_runs")
+    case_id = CharField(max_length=32, null=False, index=True, help_text="FK to evaluation_cases")
+    generated_answer = TextField(null=False, help_text="generated answer")
+    retrieved_chunks = JSONField(null=False, help_text="chunks that were retrieved")
+    metrics = JSONField(null=False, help_text="all computed metrics")
+    execution_time = FloatField(null=False, help_text="response time in seconds")
+    token_usage = JSONField(null=True, help_text="prompt/completion tokens")
+    create_time = BigIntegerField(null=False, help_text="creation timestamp")
+
+    class Meta:
+        db_table = "evaluation_results"
+
+
+class Memory(DataBaseModel):
+    id = CharField(max_length=32, primary_key=True)
+    name = CharField(max_length=128, null=False, index=False, help_text="Memory name")
+    avatar = TextField(null=True, help_text="avatar base64 string")
+    tenant_id = CharField(max_length=32, null=False, index=True)
+    memory_type = IntegerField(null=False, default=1, index=True, help_text="Bit flags (LSB->MSB): 1=raw, 2=semantic, 4=episodic, 8=procedural. E.g., 5 enables raw + episodic.")
+    storage_type = CharField(max_length=32, default='table', null=False, index=True, help_text="table|graph")
+    embd_id = CharField(max_length=128, null=False, index=False, help_text="embedding model ID")
+    llm_id = CharField(max_length=128, null=False, index=False, help_text="chat model ID")
+    permissions = CharField(max_length=16, null=False, index=True, help_text="me|team", default="me")
+    description = TextField(null=True, help_text="description")
+    memory_size = IntegerField(default=5242880, null=False, index=False)
+    forgetting_policy = CharField(max_length=32, null=False, default="fifo", index=False, help_text="lru|fifo")
+    temperature = FloatField(default=0.5, index=False)
+    system_prompt = TextField(null=True, help_text="system prompt", index=False)
+    user_prompt = TextField(null=True, help_text="user prompt", index=False)
+
+    class Meta:
+        db_table = "memory"
+
+
 def migrate_db():
     logging.disable(logging.ERROR)
     migrator = DatabaseMigrator[settings.DATABASE_TYPE.upper()].value(DB)
@@ -1293,4 +1378,43 @@ def migrate_db():
         migrate(migrator.add_column("llm_factories", "rank", IntegerField(default=0, index=False)))
     except Exception:
         pass
+
+    # RAG Evaluation tables
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "id", CharField(max_length=32, primary_key=True)))
+    except Exception:
+        pass
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "tenant_id", CharField(max_length=32, null=False, index=True)))
+    except Exception:
+        pass
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "name", CharField(max_length=255, null=False, index=True)))
+    except Exception:
+        pass
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "description", TextField(null=True)))
+    except Exception:
+        pass
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "kb_ids", JSONField(null=False)))
+    except Exception:
+        pass
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "created_by", CharField(max_length=32, null=False, index=True)))
+    except Exception:
+        pass
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "create_time", BigIntegerField(null=False, index=True)))
+    except Exception:
+        pass
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "update_time", BigIntegerField(null=False)))
+    except Exception:
+        pass
+    try:
+        migrate(migrator.add_column("evaluation_datasets", "status", IntegerField(null=False, default=1)))
+    except Exception:
+        pass
+
     logging.disable(logging.NOTSET)

api/db/init_data.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
 import logging
 import json
 import os
@@ -73,11 +74,10 @@ def init_superuser(nickname=DEFAULT_SUPERUSER_NICKNAME, email=DEFAULT_SUPERUSER_
     UserTenantService.insert(**usr_tenant)
     TenantLLMService.insert_many(tenant_llm)
     logging.info(
-        f"Super user initialized. email: {email}, password: {password}. Changing the password after login is strongly recommended.")
+        f"Super user initialized. email: {email},A default password has been set; changing the password after login is strongly recommended.")
 
     chat_mdl = LLMBundle(tenant["id"], LLMType.CHAT, tenant["llm_id"])
-    msg = chat_mdl.chat(system="", history=[
+    msg = asyncio.run(chat_mdl.async_chat(system="", history=[{"role": "user", "content": "Hello!"}], gen_conf={}))
-        {"role": "user", "content": "Hello!"}], gen_conf={})
     if msg.find("ERROR: ") == 0:
         logging.error(
             "'{}' doesn't work. {}".format(

api/db/joint_services/user_account_service.py

@@ -153,7 +153,7 @@ def delete_user_data(user_id: str) -> dict:
             done_msg += "Start to delete owned tenant.\n"
             tenant_id = owned_tenant[0]["tenant_id"]
             kb_ids = KnowledgebaseService.get_kb_ids(usr.id)
-            # step1.1 delete knowledgebase related file and info
+            # step1.1 delete dataset related file and info
             if kb_ids:
                 # step1.1.1 delete files in storage, remove bucket
                 for kb_id in kb_ids:
@@ -182,7 +182,7 @@ def delete_user_data(user_id: str) -> dict:
                                          search.index_name(tenant_id), kb_ids)
                 done_msg += f"- Deleted {r} chunk records.\n"
                 kb_delete_res = KnowledgebaseService.delete_by_ids(kb_ids)
-                done_msg += f"- Deleted {kb_delete_res} knowledgebase records.\n"
+                done_msg += f"- Deleted {kb_delete_res} dataset records.\n"
                 # step1.1.4 delete agents
                 agent_delete_res = delete_user_agents(usr.id)
                 done_msg += f"- Deleted {agent_delete_res['agents_deleted_count']} agent, {agent_delete_res['version_deleted_count']} versions records.\n"
@@ -258,7 +258,7 @@ def delete_user_data(user_id: str) -> dict:
                     # step2.1.5 delete document record
                     doc_delete_res = DocumentService.delete_by_ids([d['id'] for d in created_documents])
                     done_msg += f"- Deleted {doc_delete_res} documents.\n"
-                    # step2.1.6 update knowledge base doc&chunk&token cnt
+                    # step2.1.6 update dataset doc&chunk&token cnt
                     for kb_id, doc_num in kb_doc_info.items():
                         KnowledgebaseService.decrease_document_num_in_delete(kb_id, doc_num)
 
@@ -273,7 +273,7 @@ def delete_user_data(user_id: str) -> dict:
 
     except Exception as e:
         logging.exception(e)
-        return {"success": False, "message": f"Error: {str(e)}. Already done:\n{done_msg}"}
+        return {"success": False, "message": "An internal error occurred during user deletion. Some operations may have completed.","details": done_msg}
 
 
 def delete_user_agents(user_id: str) -> dict:

api/db/services/common_service.py

@@ -169,10 +169,12 @@ class CommonService:
         """
         if "id" not in kwargs:
             kwargs["id"] = get_uuid()
-        kwargs["create_time"] = current_timestamp()
+        timestamp = current_timestamp()
-        kwargs["create_date"] = datetime_format(datetime.now())
+        cur_datetime = datetime_format(datetime.now())
-        kwargs["update_time"] = current_timestamp()
+        kwargs["create_time"] = timestamp
-        kwargs["update_date"] = datetime_format(datetime.now())
+        kwargs["create_date"] = cur_datetime
+        kwargs["update_time"] = timestamp
+        kwargs["update_date"] = cur_datetime
         sample_obj = cls.model(**kwargs).save(force_insert=True)
         return sample_obj
 
@@ -207,10 +209,14 @@ class CommonService:
             data_list (list): List of dictionaries containing record data to update.
                              Each dictionary must include an 'id' field.
         """
+
+        timestamp = current_timestamp()
+        cur_datetime = datetime_format(datetime.now())
+        for data in data_list:
+            data["update_time"] = timestamp
+            data["update_date"] = cur_datetime
         with DB.atomic():
             for data in data_list:
-                data["update_time"] = current_timestamp()
-                data["update_date"] = datetime_format(datetime.now())
                 cls.model.update(data).where(cls.model.id == data["id"]).execute()
 
     @classmethod

api/db/services/conversation_service.py

@@ -19,7 +19,7 @@ from common.constants 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.db.services.dialog_service import DialogService, async_chat
 from common.misc_utils import get_uuid
 import json
 
@@ -89,8 +89,7 @@ def structure_answer(conv, ans, message_id, session_id):
         conv.reference[-1] = reference
     return ans
 
-
+async def async_completion(tenant_id, chat_id, question, name="New session", session_id=None, stream=True, **kwargs):
-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."
@@ -148,7 +147,7 @@ def completion(tenant_id, chat_id, question, name="New session", session_id=None
 
     if stream:
         try:
-            for ans in chat(dia, msg, True, **kwargs):
+            async for ans in async_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())
@@ -160,14 +159,13 @@ def completion(tenant_id, chat_id, question, name="New session", session_id=None
 
     else:
         answer = None
-        for ans in chat(dia, msg, False, **kwargs):
+        async for ans in async_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
 
-
+async def async_iframe_completion(dialog_id, question, session_id=None, stream=True, **kwargs):
-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:
@@ -222,7 +220,7 @@ def iframe_completion(dialog_id, question, session_id=None, stream=True, **kwarg
 
     if stream:
         try:
-            for ans in chat(dia, msg, True, **kwargs):
+            async for ans in async_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"
@@ -235,7 +233,7 @@ def iframe_completion(dialog_id, question, session_id=None, stream=True, **kwarg
 
     else:
         answer = None
-        for ans in chat(dia, msg, False, **kwargs):
+        async for ans in async_chat(dia, msg, False, **kwargs):
             answer = structure_answer(conv, ans, message_id, session_id)
             API4ConversationService.append_message(conv.id, conv.to_dict())
             break

api/db/services/dialog_service.py

@@ -21,10 +21,10 @@ from copy import deepcopy
 from datetime import datetime
 from functools import partial
 from timeit import default_timer as timer
-import trio
 from langfuse import Langfuse
 from peewee import fn
 from agentic_reasoning import DeepResearcher
+from api.db.services.file_service import FileService
 from common.constants import LLMType, ParserType, StatusEnum
 from api.db.db_models import DB, Dialog
 from api.db.services.common_service import CommonService
@@ -32,6 +32,7 @@ from api.db.services.document_service import DocumentService
 from api.db.services.knowledgebase_service import KnowledgebaseService
 from api.db.services.langfuse_service import TenantLangfuseService
 from api.db.services.llm_service import LLMBundle
+from common.metadata_utils import apply_meta_data_filter
 from api.db.services.tenant_llm_service import TenantLLMService
 from common.time_utils import current_timestamp, datetime_format
 from graphrag.general.mind_map_extractor import MindMapExtractor
@@ -39,7 +40,7 @@ from rag.app.resume import forbidden_select_fields4resume
 from rag.app.tag import label_question
 from rag.nlp.search import index_name
 from rag.prompts.generator import chunks_format, citation_prompt, cross_languages, full_question, kb_prompt, keyword_extraction, message_fit_in, \
-    gen_meta_filter, PROMPT_JINJA_ENV, ASK_SUMMARY
+    PROMPT_JINJA_ENV, ASK_SUMMARY
 from common.token_utils import num_tokens_from_string
 from rag.utils.tavily_conn import Tavily
 from common.string_utils import remove_redundant_spaces
@@ -177,7 +178,11 @@ class DialogService(CommonService):
             offset += limit
         return res
 
-def chat_solo(dialog, messages, stream=True):
+
+async def async_chat_solo(dialog, messages, stream=True):
+    attachments = ""
+    if "files" in messages[-1]:
+        attachments = "\n\n".join(FileService.get_files(messages[-1]["files"]))
     if TenantLLMService.llm_id2llm_type(dialog.llm_id) == "image2text":
         chat_mdl = LLMBundle(dialog.tenant_id, LLMType.IMAGE2TEXT, dialog.llm_id)
     else:
@@ -188,10 +193,13 @@ def chat_solo(dialog, messages, stream=True):
     if prompt_config.get("tts"):
         tts_mdl = LLMBundle(dialog.tenant_id, LLMType.TTS)
     msg = [{"role": m["role"], "content": re.sub(r"##\d+\$\$", "", m["content"])} for m in messages if m["role"] != "system"]
+    if attachments and msg:
+        msg[-1]["content"] += attachments
     if stream:
         last_ans = ""
         delta_ans = ""
-        for ans in chat_mdl.chat_streamly(prompt_config.get("system", ""), msg, dialog.llm_setting):
+        answer = ""
+        async for ans in chat_mdl.async_chat_streamly(prompt_config.get("system", ""), msg, dialog.llm_setting):
             answer = ans
             delta_ans = ans[len(last_ans):]
             if num_tokens_from_string(delta_ans) < 16:
@@ -202,7 +210,7 @@ def chat_solo(dialog, messages, stream=True):
         if delta_ans:
             yield {"answer": answer, "reference": {}, "audio_binary": tts(tts_mdl, delta_ans), "prompt": "", "created_at": time.time()}
     else:
-        answer = chat_mdl.chat(prompt_config.get("system", ""), msg, dialog.llm_setting)
+        answer = await chat_mdl.async_chat(prompt_config.get("system", ""), msg, dialog.llm_setting)
         user_content = msg[-1].get("content", "[content not available]")
         logging.debug("User: {}|Assistant: {}".format(user_content, answer))
         yield {"answer": answer, "reference": {}, "audio_binary": tts(tts_mdl, answer), "prompt": "", "created_at": time.time()}
@@ -270,84 +278,12 @@ def repair_bad_citation_formats(answer: str, kbinfos: dict, idx: set):
     return answer, idx
 
 
-def convert_conditions(metadata_condition):
+async def async_chat(dialog, messages, stream=True, **kwargs):
-    if metadata_condition is None:
-        metadata_condition = {}
-    op_mapping = {
-        "is": "=",
-        "not is": "≠"
-    }
-    return [
-        {
-            "op": op_mapping.get(cond["comparison_operator"], cond["comparison_operator"]),
-            "key": cond["name"],
-            "value": cond["value"]
-        }
-        for cond in metadata_condition.get("conditions", [])
-    ]
-
-
-def meta_filter(metas: dict, filters: list[dict], logic: str = "and"):
-    doc_ids = set([])
-
-    def filter_out(v2docs, operator, value):
-        ids = []
-        for input, docids in v2docs.items():
-            if operator in ["=", "≠", ">", "<", "≥", "≤"]:
-                try:
-                    input = float(input)
-                    value = float(value)
-                except Exception:
-                    input = str(input)
-                    value = str(value)
-
-            for conds in [
-                (operator == "contains", str(value).lower() in str(input).lower()),
-                (operator == "not contains", str(value).lower() not in str(input).lower()),
-                (operator == "in", str(input).lower() in str(value).lower()),
-                (operator == "not in", str(input).lower() not in str(value).lower()),
-                (operator == "start with", str(input).lower().startswith(str(value).lower())),
-                (operator == "end with", str(input).lower().endswith(str(value).lower())),
-                (operator == "empty", not input),
-                (operator == "not empty", input),
-                (operator == "=", input == value),
-                (operator == "≠", input != value),
-                (operator == ">", input > value),
-                (operator == "<", input < value),
-                (operator == "≥", input >= value),
-                (operator == "≤", input <= value),
-            ]:
-                try:
-                    if all(conds):
-                        ids.extend(docids)
-                        break
-                except Exception:
-                    pass
-        return ids
-
-    for k, v2docs in metas.items():
-        for f in filters:
-            if k != f["key"]:
-                continue
-            ids = filter_out(v2docs, f["op"], f["value"])
-            if not doc_ids:
-                doc_ids = set(ids)
-            else:
-                if logic == "and":
-                    doc_ids = doc_ids & set(ids)
-                else:
-                    doc_ids = doc_ids | set(ids)
-            if not doc_ids:
-                return []
-    return list(doc_ids)
-
-
-def chat(dialog, messages, stream=True, **kwargs):
     assert messages[-1]["role"] == "user", "The last content of this conversation is not from user."
     if not dialog.kb_ids and not dialog.prompt_config.get("tavily_api_key"):
-        for ans in chat_solo(dialog, messages, stream):
+        async for ans in async_chat_solo(dialog, messages, stream):
             yield ans
-        return None
+        return
 
     chat_start_ts = timer()
 
@@ -380,18 +316,21 @@ def chat(dialog, messages, stream=True, **kwargs):
     retriever = settings.retriever
     questions = [m["content"] for m in messages if m["role"] == "user"][-3:]
     attachments = kwargs["doc_ids"].split(",") if "doc_ids" in kwargs else []
+    attachments_= ""
     if "doc_ids" in messages[-1]:
         attachments = messages[-1]["doc_ids"]
+    if "files" in messages[-1]:
+        attachments_ = "\n\n".join(FileService.get_files(messages[-1]["files"]))
 
     prompt_config = dialog.prompt_config
     field_map = KnowledgebaseService.get_field_map(dialog.kb_ids)
     # try to use sql if field mapping is good to go
     if field_map:
         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), dialog.kb_ids)
+        ans = await use_sql(questions[-1], field_map, dialog.tenant_id, chat_mdl, prompt_config.get("quote", True), dialog.kb_ids)
         if ans:
             yield ans
-            return None
+            return
 
     for p in prompt_config["parameters"]:
         if p["key"] == "knowledge":
@@ -402,28 +341,25 @@ def chat(dialog, messages, stream=True, **kwargs):
             prompt_config["system"] = prompt_config["system"].replace("{%s}" % p["key"], " ")
 
     if len(questions) > 1 and prompt_config.get("refine_multiturn"):
-        questions = [full_question(dialog.tenant_id, dialog.llm_id, messages)]
+        questions = [await full_question(dialog.tenant_id, dialog.llm_id, messages)]
     else:
         questions = questions[-1:]
 
     if prompt_config.get("cross_languages"):
-        questions = [cross_languages(dialog.tenant_id, dialog.llm_id, questions[0], prompt_config["cross_languages"])]
+        questions = [await cross_languages(dialog.tenant_id, dialog.llm_id, questions[0], prompt_config["cross_languages"])]
 
     if dialog.meta_data_filter:
         metas = DocumentService.get_meta_by_kbs(dialog.kb_ids)
-        if dialog.meta_data_filter.get("method") == "auto":
+        attachments = await apply_meta_data_filter(
-            filters: dict = gen_meta_filter(chat_mdl, metas, questions[-1])
+            dialog.meta_data_filter,
-            attachments.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
+            metas,
-            if not attachments:
+            questions[-1],
-                attachments = None
+            chat_mdl,
-        elif dialog.meta_data_filter.get("method") == "manual":
+            attachments,
-            conds = dialog.meta_data_filter["manual"]
+        )
-            attachments.extend(meta_filter(metas, conds, dialog.meta_data_filter.get("logic", "and")))
-            if conds and not attachments:
-                attachments = ["-999"]
 
     if prompt_config.get("keyword", False):
-        questions[-1] += keyword_extraction(chat_mdl, questions[-1])
+        questions[-1] += await keyword_extraction(chat_mdl, questions[-1])
 
     refine_question_ts = timer()
 
@@ -451,7 +387,7 @@ def chat(dialog, messages, stream=True, **kwargs):
                 ),
             )
 
-            for think in reasoner.thinking(kbinfos, " ".join(questions)):
+            async for think in reasoner.thinking(kbinfos, attachments_ + " ".join(questions)):
                 if isinstance(think, str):
                     thought = think
                     knowledges = [t for t in think.split("\n") if t]
@@ -478,6 +414,7 @@ def chat(dialog, messages, stream=True, **kwargs):
                     cks = retriever.retrieval_by_toc(" ".join(questions), kbinfos["chunks"], tenant_ids, chat_mdl, dialog.top_n)
                     if cks:
                         kbinfos["chunks"] = cks
+                kbinfos["chunks"] = retriever.retrieval_by_children(kbinfos["chunks"], tenant_ids)
             if prompt_config.get("tavily_api_key"):
                 tav = Tavily(prompt_config["tavily_api_key"])
                 tav_res = tav.retrieve_chunks(" ".join(questions))
@@ -498,12 +435,13 @@ def chat(dialog, messages, stream=True, **kwargs):
         empty_res = prompt_config["empty_response"]
         yield {"answer": empty_res, "reference": kbinfos, "prompt": "\n\n### Query:\n%s" % " ".join(questions),
                "audio_binary": tts(tts_mdl, empty_res)}
-        return {"answer": prompt_config["empty_response"], "reference": kbinfos}
+        yield {"answer": prompt_config["empty_response"], "reference": kbinfos}
+        return
 
     kwargs["knowledge"] = "\n------\n" + "\n\n------\n\n".join(knowledges)
     gen_conf = dialog.llm_setting
 
-    msg = [{"role": "system", "content": prompt_config["system"].format(**kwargs)}]
+    msg = [{"role": "system", "content": prompt_config["system"].format(**kwargs)+attachments_}]
     prompt4citation = ""
     if knowledges and (prompt_config.get("quote", True) and kwargs.get("quote", True)):
         prompt4citation = citation_prompt()
@@ -602,7 +540,7 @@ def chat(dialog, messages, stream=True, **kwargs):
     if stream:
         last_ans = ""
         answer = ""
-        for ans in chat_mdl.chat_streamly(prompt + prompt4citation, msg[1:], gen_conf):
+        async for ans in chat_mdl.async_chat_streamly(prompt + prompt4citation, msg[1:], gen_conf):
             if thought:
                 ans = re.sub(r"^.*</think>", "", ans, flags=re.DOTALL)
             answer = ans
@@ -616,17 +554,17 @@ def chat(dialog, messages, stream=True, **kwargs):
             yield {"answer": thought + answer, "reference": {}, "audio_binary": tts(tts_mdl, delta_ans)}
         yield decorate_answer(thought + answer)
     else:
-        answer = chat_mdl.chat(prompt + prompt4citation, msg[1:], gen_conf)
+        answer = await chat_mdl.async_chat(prompt + prompt4citation, msg[1:], gen_conf)
         user_content = msg[-1].get("content", "[content not available]")
         logging.debug("User: {}|Assistant: {}".format(user_content, answer))
         res = decorate_answer(answer)
         res["audio_binary"] = tts(tts_mdl, answer)
         yield res
 
-    return None
+    return
 
 
-def use_sql(question, field_map, tenant_id, chat_mdl, quota=True, kb_ids=None):
+async def use_sql(question, field_map, tenant_id, chat_mdl, quota=True, kb_ids=None):
     sys_prompt = """
 You are a Database Administrator. You need to check the fields of the following tables based on the user's list of questions and write the SQL corresponding to the last question.
 Ensure that:
@@ -644,9 +582,9 @@ Please write the SQL, only SQL, without any other explanations or text.
 """.format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question)
     tried_times = 0
 
-    def get_table():
+    async def get_table():
         nonlocal sys_prompt, user_prompt, question, tried_times
-        sql = chat_mdl.chat(sys_prompt, [{"role": "user", "content": user_prompt}], {"temperature": 0.06})
+        sql = await chat_mdl.async_chat(sys_prompt, [{"role": "user", "content": user_prompt}], {"temperature": 0.06})
         sql = re.sub(r"^.*</think>", "", sql, flags=re.DOTALL)
         logging.debug(f"{question} ==> {user_prompt} get SQL: {sql}")
         sql = re.sub(r"[\r\n]+", " ", sql.lower())
@@ -672,6 +610,10 @@ Please write the SQL, only SQL, without any other explanations or text.
         if kb_ids:
             kb_filter = "(" + " OR ".join([f"kb_id = '{kb_id}'" for kb_id in kb_ids]) + ")"
             if "where" not in sql.lower():
+                o = sql.lower().split("order by")
+                if len(o) > 1:
+                    sql = o[0] + f" WHERE {kb_filter}  order by " + o[1]
+                else:
                     sql += f" WHERE {kb_filter}"
             else:
                 sql += f" AND {kb_filter}"
@@ -680,10 +622,9 @@ Please write the SQL, only SQL, without any other explanations or text.
         tried_times += 1
         return settings.retriever.sql_retrieval(sql, format="json"), sql
 
-    tbl, sql = get_table()
+    try:
-    if tbl is None:
+        tbl, sql = await get_table()
-        return None
+    except Exception as e:
-    if tbl.get("error") and tried_times <= 2:
         user_prompt = """
         Table name: {};
         Table of database fields are as follows:
@@ -697,16 +638,14 @@ Please write the SQL, only SQL, without any other explanations or text.
         The SQL error you provided last time is as follows:
         {}
 
-        Error issued by database as follows:
-        {}
-
         Please correct the error and write SQL again, only SQL, without any other explanations or text.
-        """.format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question, sql, tbl["error"])
+        """.format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question, e)
-        tbl, sql = get_table()
+        try:
-        logging.debug("TRY it again: {}".format(sql))
+            tbl, sql = await get_table()
+        except Exception:
+            return
 
-    logging.debug("GET table: {}".format(tbl))
+    if len(tbl["rows"]) == 0:
-    if tbl.get("error") or len(tbl["rows"]) == 0:
         return None
 
     docid_idx = set([ii for ii, c in enumerate(tbl["columns"]) if c["name"] == "doc_id"])
@@ -750,17 +689,51 @@ Please write the SQL, only SQL, without any other explanations or text.
         "prompt": sys_prompt,
     }
 
+def clean_tts_text(text: str) -> str:
+    if not text:
+        return ""
+
+    text = text.encode("utf-8", "ignore").decode("utf-8", "ignore")
+
+    text = re.sub(r"[\x00-\x08\x0B-\x0C\x0E-\x1F\x7F]", "", text)
+
+    emoji_pattern = re.compile(
+        "[\U0001F600-\U0001F64F"
+        "\U0001F300-\U0001F5FF"
+        "\U0001F680-\U0001F6FF"
+        "\U0001F1E0-\U0001F1FF"
+        "\U00002700-\U000027BF"
+        "\U0001F900-\U0001F9FF"
+        "\U0001FA70-\U0001FAFF"
+        "\U0001FAD0-\U0001FAFF]+",
+        flags=re.UNICODE
+    )
+    text = emoji_pattern.sub("", text)
+
+    text = re.sub(r"\s+", " ", text).strip()
+
+    MAX_LEN = 500
+    if len(text) > MAX_LEN:
+        text = text[:MAX_LEN]
+
+    return text
 
 def tts(tts_mdl, text):
     if not tts_mdl or not text:
         return None
+    text = clean_tts_text(text)
+    if not text:
+        return None
     bin = b""
+    try:
         for chunk in tts_mdl.tts(text):
             bin += chunk
+    except Exception as e:
+        logging.error(f"TTS failed: {e}, text={text!r}")
+        return None
     return binascii.hexlify(bin).decode("utf-8")
 
-
+async def async_ask(question, kb_ids, tenant_id, chat_llm_name=None, search_config={}):
-def ask(question, kb_ids, tenant_id, chat_llm_name=None, search_config={}):
     doc_ids = search_config.get("doc_ids", [])
     rerank_mdl = None
     kb_ids = search_config.get("kb_ids", kb_ids)
@@ -783,15 +756,7 @@ def ask(question, kb_ids, tenant_id, chat_llm_name=None, search_config={}):
 
     if meta_data_filter:
         metas = DocumentService.get_meta_by_kbs(kb_ids)
-        if meta_data_filter.get("method") == "auto":
+        doc_ids = await apply_meta_data_filter(meta_data_filter, metas, question, chat_mdl, doc_ids)
-            filters: dict = gen_meta_filter(chat_mdl, metas, question)
-            doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
-            if not doc_ids:
-                doc_ids = None
-        elif meta_data_filter.get("method") == "manual":
-            doc_ids.extend(meta_filter(metas, meta_data_filter["manual"], meta_data_filter.get("logic", "and")))
-            if meta_data_filter["manual"] and not doc_ids:
-                doc_ids = ["-999"]
 
     kbinfos = retriever.retrieval(
         question=question,
@@ -834,13 +799,13 @@ def ask(question, kb_ids, tenant_id, chat_llm_name=None, search_config={}):
         return {"answer": answer, "reference": refs}
 
     answer = ""
-    for ans in chat_mdl.chat_streamly(sys_prompt, msg, {"temperature": 0.1}):
+    async for ans in chat_mdl.async_chat_streamly(sys_prompt, msg, {"temperature": 0.1}):
         answer = ans
         yield {"answer": answer, "reference": {}}
     yield decorate_answer(answer)
 
 
-def gen_mindmap(question, kb_ids, tenant_id, search_config={}):
+async def gen_mindmap(question, kb_ids, tenant_id, search_config={}):
     meta_data_filter = search_config.get("meta_data_filter", {})
     doc_ids = search_config.get("doc_ids", [])
     rerank_id = search_config.get("rerank_id", "")
@@ -858,15 +823,7 @@ def gen_mindmap(question, kb_ids, tenant_id, search_config={}):
 
     if meta_data_filter:
         metas = DocumentService.get_meta_by_kbs(kb_ids)
-        if meta_data_filter.get("method") == "auto":
+        doc_ids = await apply_meta_data_filter(meta_data_filter, metas, question, chat_mdl, doc_ids)
-            filters: dict = gen_meta_filter(chat_mdl, metas, question)
-            doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
-            if not doc_ids:
-                doc_ids = None
-        elif meta_data_filter.get("method") == "manual":
-            doc_ids.extend(meta_filter(metas, meta_data_filter["manual"], meta_data_filter.get("logic", "and")))
-            if meta_data_filter["manual"] and not doc_ids:
-                doc_ids = ["-999"]
 
     ranks = settings.retriever.retrieval(
         question=question,
@@ -884,5 +841,5 @@ def gen_mindmap(question, kb_ids, tenant_id, search_config={}):
         rank_feature=label_question(question, kbs),
     )
     mindmap = MindMapExtractor(chat_mdl)
-    mind_map = trio.run(mindmap, [c["content_with_weight"] for c in ranks["chunks"]])
+    mind_map = await mindmap([c["content_with_weight"] for c in ranks["chunks"]])
     return mind_map.output

api/db/services/document_service.py

@@ -13,6 +13,7 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
 import json
 import logging
 import random
@@ -22,7 +23,6 @@ from copy import deepcopy
 from datetime import datetime
 from io import BytesIO
 
-import trio
 import xxhash
 from peewee import fn, Case, JOIN
 
@@ -79,7 +79,7 @@ class DocumentService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_list(cls, kb_id, page_number, items_per_page,
-                 orderby, desc, keywords, id, name, suffix=None, run = None):
+                 orderby, desc, keywords, id, name, suffix=None, run = None, doc_ids=None):
         fields = cls.get_cls_model_fields()
         docs = cls.model.select(*[*fields, UserCanvas.title]).join(File2Document, on = (File2Document.document_id == cls.model.id))\
             .join(File, on = (File.id == File2Document.file_id))\
@@ -96,6 +96,8 @@ class DocumentService(CommonService):
             docs = docs.where(
                 fn.LOWER(cls.model.name).contains(keywords.lower())
             )
+        if doc_ids:
+            docs = docs.where(cls.model.id.in_(doc_ids))
         if suffix:
             docs = docs.where(cls.model.suffix.in_(suffix))
         if run:
@@ -123,7 +125,7 @@ class DocumentService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_by_kb_id(cls, kb_id, page_number, items_per_page,
-                     orderby, desc, keywords, run_status, types, suffix):
+                     orderby, desc, keywords, run_status, types, suffix, doc_ids=None):
         fields = cls.get_cls_model_fields()
         if keywords:
             docs = cls.model.select(*[*fields, UserCanvas.title.alias("pipeline_name"), User.nickname])\
@@ -143,6 +145,8 @@ class DocumentService(CommonService):
                 .join(User, on=(cls.model.created_by == User.id), join_type=JOIN.LEFT_OUTER)\
                 .where(cls.model.kb_id == kb_id)
 
+        if doc_ids:
+            docs = docs.where(cls.model.id.in_(doc_ids))
         if run_status:
             docs = docs.where(cls.model.run.in_(run_status))
         if types:
@@ -644,6 +648,13 @@ class DocumentService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_meta_by_kbs(cls, kb_ids):
+        """
+        Legacy metadata aggregator (backward-compatible).
+        - Does NOT expand list values and a list is kept as one string key.
+          Example: {"tags": ["foo","bar"]} -> meta["tags"]["['foo', 'bar']"] = [doc_id]
+        - Expects meta_fields is a dict.
+        Use when existing callers rely on the old list-as-string semantics.
+        """
         fields = [
             cls.model.id,
             cls.model.meta_fields,
@@ -660,6 +671,171 @@ class DocumentService(CommonService):
                 meta[k][v].append(doc_id)
         return meta
 
+    @classmethod
+    @DB.connection_context()
+    def get_flatted_meta_by_kbs(cls, kb_ids):
+        """
+        - Parses stringified JSON meta_fields when possible and skips non-dict or unparsable values.
+        - Expands list values into individual entries.
+          Example: {"tags": ["foo","bar"], "author": "alice"} ->
+            meta["tags"]["foo"] = [doc_id], meta["tags"]["bar"] = [doc_id], meta["author"]["alice"] = [doc_id]
+        Prefer for metadata_condition filtering and scenarios that must respect list semantics.
+        """
+        fields = [
+            cls.model.id,
+            cls.model.meta_fields,
+        ]
+        meta = {}
+        for r in cls.model.select(*fields).where(cls.model.kb_id.in_(kb_ids)):
+            doc_id = r.id
+            meta_fields = r.meta_fields or {}
+            if isinstance(meta_fields, str):
+                try:
+                    meta_fields = json.loads(meta_fields)
+                except Exception:
+                    continue
+            if not isinstance(meta_fields, dict):
+                continue
+            for k, v in meta_fields.items():
+                if k not in meta:
+                    meta[k] = {}
+                values = v if isinstance(v, list) else [v]
+                for vv in values:
+                    if vv is None:
+                        continue
+                    sv = str(vv)
+                    if sv not in meta[k]:
+                        meta[k][sv] = []
+                    meta[k][sv].append(doc_id)
+        return meta
+
+    @classmethod
+    @DB.connection_context()
+    def get_metadata_summary(cls, kb_id):
+        fields = [cls.model.id, cls.model.meta_fields]
+        summary = {}
+        for r in cls.model.select(*fields).where(cls.model.kb_id == kb_id):
+            meta_fields = r.meta_fields or {}
+            if isinstance(meta_fields, str):
+                try:
+                    meta_fields = json.loads(meta_fields)
+                except Exception:
+                    continue
+            if not isinstance(meta_fields, dict):
+                continue
+            for k, v in meta_fields.items():
+                values = v if isinstance(v, list) else [v]
+                for vv in values:
+                    if not vv:
+                        continue
+                    sv = str(vv)
+                    if k not in summary:
+                        summary[k] = {}
+                    summary[k][sv] = summary[k].get(sv, 0) + 1
+        return {k: sorted([(val, cnt) for val, cnt in v.items()], key=lambda x: x[1], reverse=True) for k, v in summary.items()}
+
+    @classmethod
+    @DB.connection_context()
+    def batch_update_metadata(cls, kb_id, doc_ids, updates=None, deletes=None):
+        updates = updates or []
+        deletes = deletes or []
+        if not doc_ids:
+            return 0
+
+        def _normalize_meta(meta):
+            if isinstance(meta, str):
+                try:
+                    meta = json.loads(meta)
+                except Exception:
+                    return {}
+            if not isinstance(meta, dict):
+                return {}
+            return deepcopy(meta)
+
+        def _str_equal(a, b):
+            return str(a) == str(b)
+
+        def _apply_updates(meta):
+            changed = False
+            for upd in updates:
+                key = upd.get("key")
+                if not key or key not in meta:
+                    continue
+
+                new_value = upd.get("value")
+                match_provided = "match" in upd
+                if isinstance(meta[key], list):
+                    if not match_provided:
+                        meta[key] = new_value
+                        changed = True
+                    else:
+                        match_value = upd.get("match")
+                        replaced = False
+                        new_list = []
+                        for item in meta[key]:
+                            if _str_equal(item, match_value):
+                                new_list.append(new_value)
+                                replaced = True
+                            else:
+                                new_list.append(item)
+                        if replaced:
+                            meta[key] = new_list
+                            changed = True
+                else:
+                    if not match_provided:
+                        meta[key] = new_value
+                        changed = True
+                    else:
+                        match_value = upd.get("match")
+                        if _str_equal(meta[key], match_value):
+                            meta[key] = new_value
+                            changed = True
+            return changed
+
+        def _apply_deletes(meta):
+            changed = False
+            for d in deletes:
+                key = d.get("key")
+                if not key or key not in meta:
+                    continue
+                value = d.get("value", None)
+                if isinstance(meta[key], list):
+                    if value is None:
+                        del meta[key]
+                        changed = True
+                        continue
+                    new_list = [item for item in meta[key] if not _str_equal(item, value)]
+                    if len(new_list) != len(meta[key]):
+                        if new_list:
+                            meta[key] = new_list
+                        else:
+                            del meta[key]
+                        changed = True
+                else:
+                    if value is None or _str_equal(meta[key], value):
+                        del meta[key]
+                        changed = True
+            return changed
+
+        updated_docs = 0
+        with DB.atomic():
+            rows = cls.model.select(cls.model.id, cls.model.meta_fields).where(
+                (cls.model.id.in_(doc_ids)) & (cls.model.kb_id == kb_id)
+            )
+            for r in rows:
+                meta = _normalize_meta(r.meta_fields or {})
+                original_meta = deepcopy(meta)
+                changed = _apply_updates(meta)
+                changed = _apply_deletes(meta) or changed
+                if changed and meta != original_meta:
+                    cls.model.update(
+                        meta_fields=meta,
+                        update_time=current_timestamp(),
+                        update_date=get_format_time()
+                    ).where(cls.model.id == r.id).execute()
+                    updated_docs += 1
+        return updated_docs
+
     @classmethod
     @DB.connection_context()
     def update_progress(cls):
@@ -719,10 +895,14 @@ class DocumentService(CommonService):
                 # only for special task and parsed docs and unfinished
                 freeze_progress = special_task_running and doc_progress >= 1 and not finished
                 msg = "\n".join(sorted(msg))
+                begin_at = d.get("process_begin_at")
+                if not begin_at:
+                    begin_at = datetime.now()
+                    # fallback
+                    cls.update_by_id(d["id"], {"process_begin_at": begin_at})
+
                 info = {
-                    "process_duration": datetime.timestamp(
+                    "process_duration": max(datetime.timestamp(datetime.now()) - begin_at.timestamp(), 0),
-                        datetime.now()) -
-                                       d["process_begin_at"].timestamp(),
                     "run": status}
                 if prg != 0 and not freeze_progress:
                     info["progress"] = prg
@@ -902,12 +1082,12 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
 
     e, dia = DialogService.get_by_id(conv.dialog_id)
     if not dia.kb_ids:
-        raise LookupError("No knowledge base associated with this conversation. "
+        raise LookupError("No dataset associated with this conversation. "
-                          "Please add a knowledge base before uploading documents")
+                          "Please add a dataset before uploading documents")
     kb_id = dia.kb_ids[0]
     e, kb = KnowledgebaseService.get_by_id(kb_id)
     if not e:
-        raise LookupError("Can't find this knowledgebase!")
+        raise LookupError("Can't find this dataset!")
 
     embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING, llm_name=kb.embd_id, lang=kb.language)
 
@@ -923,7 +1103,7 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
         ParserType.AUDIO.value: audio,
         ParserType.EMAIL.value: email
     }
-    parser_config = {"chunk_token_num": 4096, "delimiter": "\n!?;。；！？", "layout_recognize": "Plain Text"}
+    parser_config = {"chunk_token_num": 4096, "delimiter": "\n!?;。；！？", "layout_recognize": "Plain Text", "table_context_size": 0, "image_context_size": 0}
     exe = ThreadPoolExecutor(max_workers=12)
     threads = []
     doc_nm = {}
@@ -995,7 +1175,7 @@ def doc_upload_and_parse(conversation_id, file_objs, user_id):
             from graphrag.general.mind_map_extractor import MindMapExtractor
             mindmap = MindMapExtractor(llm_bdl)
             try:
-                mind_map = trio.run(mindmap, [c["content_with_weight"] for c in docs if c["doc_id"] == doc_id])
+                mind_map = asyncio.run(mindmap([c["content_with_weight"] for c in docs if c["doc_id"] == doc_id]))
                 mind_map = json.dumps(mind_map.output, ensure_ascii=False, indent=2)
                 if len(mind_map) < 32:
                     raise Exception("Few content: " + mind_map)

api/db/services/evaluation_service.py

@@ -0,0 +1,637 @@
+#
+#  Copyright 2025 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.
+#
+
+"""
+RAG Evaluation Service
+
+Provides functionality for evaluating RAG system performance including:
+- Dataset management
+- Test case management
+- Evaluation execution
+- Metrics computation
+- Configuration recommendations
+"""
+
+import asyncio
+import logging
+import queue
+import threading
+from typing import List, Dict, Any, Optional, Tuple
+from datetime import datetime
+from timeit import default_timer as timer
+
+from api.db.db_models import EvaluationDataset, EvaluationCase, EvaluationRun, EvaluationResult
+from api.db.services.common_service import CommonService
+from api.db.services.dialog_service import DialogService
+from common.misc_utils import get_uuid
+from common.time_utils import current_timestamp
+from common.constants import StatusEnum
+
+
+class EvaluationService(CommonService):
+    """Service for managing RAG evaluations"""
+
+    model = EvaluationDataset
+
+    # ==================== Dataset Management ====================
+
+    @classmethod
+    def create_dataset(cls, name: str, description: str, kb_ids: List[str],
+                      tenant_id: str, user_id: str) -> Tuple[bool, str]:
+        """
+        Create a new evaluation dataset.
+
+        Args:
+            name: Dataset name
+            description: Dataset description
+            kb_ids: List of knowledge base IDs to evaluate against
+            tenant_id: Tenant ID
+            user_id: User ID who creates the dataset
+
+        Returns:
+            (success, dataset_id or error_message)
+        """
+        try:
+            dataset_id = get_uuid()
+            dataset = {
+                "id": dataset_id,
+                "tenant_id": tenant_id,
+                "name": name,
+                "description": description,
+                "kb_ids": kb_ids,
+                "created_by": user_id,
+                "create_time": current_timestamp(),
+                "update_time": current_timestamp(),
+                "status": StatusEnum.VALID.value
+            }
+
+            if not EvaluationDataset.create(**dataset):
+                return False, "Failed to create dataset"
+
+            return True, dataset_id
+        except Exception as e:
+            logging.error(f"Error creating evaluation dataset: {e}")
+            return False, str(e)
+
+    @classmethod
+    def get_dataset(cls, dataset_id: str) -> Optional[Dict[str, Any]]:
+        """Get dataset by ID"""
+        try:
+            dataset = EvaluationDataset.get_by_id(dataset_id)
+            if dataset:
+                return dataset.to_dict()
+            return None
+        except Exception as e:
+            logging.error(f"Error getting dataset {dataset_id}: {e}")
+            return None
+
+    @classmethod
+    def list_datasets(cls, tenant_id: str, user_id: str,
+                     page: int = 1, page_size: int = 20) -> Dict[str, Any]:
+        """List datasets for a tenant"""
+        try:
+            query = EvaluationDataset.select().where(
+                (EvaluationDataset.tenant_id == tenant_id) &
+                (EvaluationDataset.status == StatusEnum.VALID.value)
+            ).order_by(EvaluationDataset.create_time.desc())
+
+            total = query.count()
+            datasets = query.paginate(page, page_size)
+
+            return {
+                "total": total,
+                "datasets": [d.to_dict() for d in datasets]
+            }
+        except Exception as e:
+            logging.error(f"Error listing datasets: {e}")
+            return {"total": 0, "datasets": []}
+
+    @classmethod
+    def update_dataset(cls, dataset_id: str, **kwargs) -> bool:
+        """Update dataset"""
+        try:
+            kwargs["update_time"] = current_timestamp()
+            return EvaluationDataset.update(**kwargs).where(
+                EvaluationDataset.id == dataset_id
+            ).execute() > 0
+        except Exception as e:
+            logging.error(f"Error updating dataset {dataset_id}: {e}")
+            return False
+
+    @classmethod
+    def delete_dataset(cls, dataset_id: str) -> bool:
+        """Soft delete dataset"""
+        try:
+            return EvaluationDataset.update(
+                status=StatusEnum.INVALID.value,
+                update_time=current_timestamp()
+            ).where(EvaluationDataset.id == dataset_id).execute() > 0
+        except Exception as e:
+            logging.error(f"Error deleting dataset {dataset_id}: {e}")
+            return False
+
+    # ==================== Test Case Management ====================
+
+    @classmethod
+    def add_test_case(cls, dataset_id: str, question: str,
+                     reference_answer: Optional[str] = None,
+                     relevant_doc_ids: Optional[List[str]] = None,
+                     relevant_chunk_ids: Optional[List[str]] = None,
+                     metadata: Optional[Dict[str, Any]] = None) -> Tuple[bool, str]:
+        """
+        Add a test case to a dataset.
+
+        Args:
+            dataset_id: Dataset ID
+            question: Test question
+            reference_answer: Optional ground truth answer
+            relevant_doc_ids: Optional list of relevant document IDs
+            relevant_chunk_ids: Optional list of relevant chunk IDs
+            metadata: Optional additional metadata
+
+        Returns:
+            (success, case_id or error_message)
+        """
+        try:
+            case_id = get_uuid()
+            case = {
+                "id": case_id,
+                "dataset_id": dataset_id,
+                "question": question,
+                "reference_answer": reference_answer,
+                "relevant_doc_ids": relevant_doc_ids,
+                "relevant_chunk_ids": relevant_chunk_ids,
+                "metadata": metadata,
+                "create_time": current_timestamp()
+            }
+
+            if not EvaluationCase.create(**case):
+                return False, "Failed to create test case"
+
+            return True, case_id
+        except Exception as e:
+            logging.error(f"Error adding test case: {e}")
+            return False, str(e)
+
+    @classmethod
+    def get_test_cases(cls, dataset_id: str) -> List[Dict[str, Any]]:
+        """Get all test cases for a dataset"""
+        try:
+            cases = EvaluationCase.select().where(
+                EvaluationCase.dataset_id == dataset_id
+            ).order_by(EvaluationCase.create_time)
+
+            return [c.to_dict() for c in cases]
+        except Exception as e:
+            logging.error(f"Error getting test cases for dataset {dataset_id}: {e}")
+            return []
+
+    @classmethod
+    def delete_test_case(cls, case_id: str) -> bool:
+        """Delete a test case"""
+        try:
+            return EvaluationCase.delete().where(
+                EvaluationCase.id == case_id
+            ).execute() > 0
+        except Exception as e:
+            logging.error(f"Error deleting test case {case_id}: {e}")
+            return False
+
+    @classmethod
+    def import_test_cases(cls, dataset_id: str, cases: List[Dict[str, Any]]) -> Tuple[int, int]:
+        """
+        Bulk import test cases from a list.
+
+        Args:
+            dataset_id: Dataset ID
+            cases: List of test case dictionaries
+
+        Returns:
+            (success_count, failure_count)
+        """
+        success_count = 0
+        failure_count = 0
+
+        for case_data in cases:
+            success, _ = cls.add_test_case(
+                dataset_id=dataset_id,
+                question=case_data.get("question", ""),
+                reference_answer=case_data.get("reference_answer"),
+                relevant_doc_ids=case_data.get("relevant_doc_ids"),
+                relevant_chunk_ids=case_data.get("relevant_chunk_ids"),
+                metadata=case_data.get("metadata")
+            )
+
+            if success:
+                success_count += 1
+            else:
+                failure_count += 1
+
+        return success_count, failure_count
+
+    # ==================== Evaluation Execution ====================
+
+    @classmethod
+    def start_evaluation(cls, dataset_id: str, dialog_id: str,
+                        user_id: str, name: Optional[str] = None) -> Tuple[bool, str]:
+        """
+        Start an evaluation run.
+
+        Args:
+            dataset_id: Dataset ID
+            dialog_id: Dialog configuration to evaluate
+            user_id: User ID who starts the run
+            name: Optional run name
+
+        Returns:
+            (success, run_id or error_message)
+        """
+        try:
+            # Get dialog configuration
+            success, dialog = DialogService.get_by_id(dialog_id)
+            if not success:
+                return False, "Dialog not found"
+
+            # Create evaluation run
+            run_id = get_uuid()
+            if not name:
+                name = f"Evaluation Run {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
+
+            run = {
+                "id": run_id,
+                "dataset_id": dataset_id,
+                "dialog_id": dialog_id,
+                "name": name,
+                "config_snapshot": dialog.to_dict(),
+                "metrics_summary": None,
+                "status": "RUNNING",
+                "created_by": user_id,
+                "create_time": current_timestamp(),
+                "complete_time": None
+            }
+
+            if not EvaluationRun.create(**run):
+                return False, "Failed to create evaluation run"
+
+            # Execute evaluation asynchronously (in production, use task queue)
+            # For now, we'll execute synchronously
+            cls._execute_evaluation(run_id, dataset_id, dialog)
+
+            return True, run_id
+        except Exception as e:
+            logging.error(f"Error starting evaluation: {e}")
+            return False, str(e)
+
+    @classmethod
+    def _execute_evaluation(cls, run_id: str, dataset_id: str, dialog: Any):
+        """
+        Execute evaluation for all test cases.
+
+        This method runs the RAG pipeline for each test case and computes metrics.
+        """
+        try:
+            # Get all test cases
+            test_cases = cls.get_test_cases(dataset_id)
+
+            if not test_cases:
+                EvaluationRun.update(
+                    status="FAILED",
+                    complete_time=current_timestamp()
+                ).where(EvaluationRun.id == run_id).execute()
+                return
+
+            # Execute each test case
+            results = []
+            for case in test_cases:
+                result = cls._evaluate_single_case(run_id, case, dialog)
+                if result:
+                    results.append(result)
+
+            # Compute summary metrics
+            metrics_summary = cls._compute_summary_metrics(results)
+
+            # Update run status
+            EvaluationRun.update(
+                status="COMPLETED",
+                metrics_summary=metrics_summary,
+                complete_time=current_timestamp()
+            ).where(EvaluationRun.id == run_id).execute()
+
+        except Exception as e:
+            logging.error(f"Error executing evaluation {run_id}: {e}")
+            EvaluationRun.update(
+                status="FAILED",
+                complete_time=current_timestamp()
+            ).where(EvaluationRun.id == run_id).execute()
+
+    @classmethod
+    def _evaluate_single_case(cls, run_id: str, case: Dict[str, Any],
+                             dialog: Any) -> Optional[Dict[str, Any]]:
+        """
+        Evaluate a single test case.
+
+        Args:
+            run_id: Evaluation run ID
+            case: Test case dictionary
+            dialog: Dialog configuration
+
+        Returns:
+            Result dictionary or None if failed
+        """
+        try:
+            # Prepare messages
+            messages = [{"role": "user", "content": case["question"]}]
+
+            # Execute RAG pipeline
+            start_time = timer()
+            answer = ""
+            retrieved_chunks = []
+
+
+            def _sync_from_async_gen(async_gen):
+                result_queue: queue.Queue = queue.Queue()
+
+                def runner():
+                    loop = asyncio.new_event_loop()
+                    asyncio.set_event_loop(loop)
+
+                    async def consume():
+                        try:
+                            async for item in async_gen:
+                                result_queue.put(item)
+                        except Exception as e:
+                            result_queue.put(e)
+                        finally:
+                            result_queue.put(StopIteration)
+
+                    loop.run_until_complete(consume())
+                    loop.close()
+
+                threading.Thread(target=runner, daemon=True).start()
+
+                while True:
+                    item = result_queue.get()
+                    if item is StopIteration:
+                        break
+                    if isinstance(item, Exception):
+                        raise item
+                    yield item
+
+
+            def chat(dialog, messages, stream=True, **kwargs):
+                from api.db.services.dialog_service import async_chat
+
+                return _sync_from_async_gen(async_chat(dialog, messages, stream=stream, **kwargs))
+
+            for ans in chat(dialog, messages, stream=False):
+                if isinstance(ans, dict):
+                    answer = ans.get("answer", "")
+                    retrieved_chunks = ans.get("reference", {}).get("chunks", [])
+                    break
+
+            execution_time = timer() - start_time
+
+            # Compute metrics
+            metrics = cls._compute_metrics(
+                question=case["question"],
+                generated_answer=answer,
+                reference_answer=case.get("reference_answer"),
+                retrieved_chunks=retrieved_chunks,
+                relevant_chunk_ids=case.get("relevant_chunk_ids"),
+                dialog=dialog
+            )
+
+            # Save result
+            result_id = get_uuid()
+            result = {
+                "id": result_id,
+                "run_id": run_id,
+                "case_id": case["id"],
+                "generated_answer": answer,
+                "retrieved_chunks": retrieved_chunks,
+                "metrics": metrics,
+                "execution_time": execution_time,
+                "token_usage": None,  # TODO: Track token usage
+                "create_time": current_timestamp()
+            }
+
+            EvaluationResult.create(**result)
+
+            return result
+        except Exception as e:
+            logging.error(f"Error evaluating case {case.get('id')}: {e}")
+            return None
+
+    @classmethod
+    def _compute_metrics(cls, question: str, generated_answer: str,
+                        reference_answer: Optional[str],
+                        retrieved_chunks: List[Dict[str, Any]],
+                        relevant_chunk_ids: Optional[List[str]],
+                        dialog: Any) -> Dict[str, float]:
+        """
+        Compute evaluation metrics for a single test case.
+
+        Returns:
+            Dictionary of metric names to values
+        """
+        metrics = {}
+
+        # Retrieval metrics (if ground truth chunks provided)
+        if relevant_chunk_ids:
+            retrieved_ids = [c.get("chunk_id") for c in retrieved_chunks]
+            metrics.update(cls._compute_retrieval_metrics(retrieved_ids, relevant_chunk_ids))
+
+        # Generation metrics
+        if generated_answer:
+            # Basic metrics
+            metrics["answer_length"] = len(generated_answer)
+            metrics["has_answer"] = 1.0 if generated_answer.strip() else 0.0
+
+            # TODO: Implement advanced metrics using LLM-as-judge
+            # - Faithfulness (hallucination detection)
+            # - Answer relevance
+            # - Context relevance
+            # - Semantic similarity (if reference answer provided)
+
+        return metrics
+
+    @classmethod
+    def _compute_retrieval_metrics(cls, retrieved_ids: List[str],
+                                   relevant_ids: List[str]) -> Dict[str, float]:
+        """
+        Compute retrieval metrics.
+
+        Args:
+            retrieved_ids: List of retrieved chunk IDs
+            relevant_ids: List of relevant chunk IDs (ground truth)
+
+        Returns:
+            Dictionary of retrieval metrics
+        """
+        if not relevant_ids:
+            return {}
+
+        retrieved_set = set(retrieved_ids)
+        relevant_set = set(relevant_ids)
+
+        # Precision: proportion of retrieved that are relevant
+        precision = len(retrieved_set & relevant_set) / len(retrieved_set) if retrieved_set else 0.0
+
+        # Recall: proportion of relevant that were retrieved
+        recall = len(retrieved_set & relevant_set) / len(relevant_set) if relevant_set else 0.0
+
+        # F1 score
+        f1 = 2 * (precision * recall) / (precision + recall) if (precision + recall) > 0 else 0.0
+
+        # Hit rate: whether any relevant chunk was retrieved
+        hit_rate = 1.0 if (retrieved_set & relevant_set) else 0.0
+
+        # MRR (Mean Reciprocal Rank): position of first relevant chunk
+        mrr = 0.0
+        for i, chunk_id in enumerate(retrieved_ids, 1):
+            if chunk_id in relevant_set:
+                mrr = 1.0 / i
+                break
+
+        return {
+            "precision": precision,
+            "recall": recall,
+            "f1_score": f1,
+            "hit_rate": hit_rate,
+            "mrr": mrr
+        }
+
+    @classmethod
+    def _compute_summary_metrics(cls, results: List[Dict[str, Any]]) -> Dict[str, Any]:
+        """
+        Compute summary metrics across all test cases.
+
+        Args:
+            results: List of result dictionaries
+
+        Returns:
+            Summary metrics dictionary
+        """
+        if not results:
+            return {}
+
+        # Aggregate metrics
+        metric_sums = {}
+        metric_counts = {}
+
+        for result in results:
+            metrics = result.get("metrics", {})
+            for key, value in metrics.items():
+                if isinstance(value, (int, float)):
+                    metric_sums[key] = metric_sums.get(key, 0) + value
+                    metric_counts[key] = metric_counts.get(key, 0) + 1
+
+        # Compute averages
+        summary = {
+            "total_cases": len(results),
+            "avg_execution_time": sum(r.get("execution_time", 0) for r in results) / len(results)
+        }
+
+        for key in metric_sums:
+            summary[f"avg_{key}"] = metric_sums[key] / metric_counts[key]
+
+        return summary
+
+    # ==================== Results & Analysis ====================
+
+    @classmethod
+    def get_run_results(cls, run_id: str) -> Dict[str, Any]:
+        """Get results for an evaluation run"""
+        try:
+            run = EvaluationRun.get_by_id(run_id)
+            if not run:
+                return {}
+
+            results = EvaluationResult.select().where(
+                EvaluationResult.run_id == run_id
+            ).order_by(EvaluationResult.create_time)
+
+            return {
+                "run": run.to_dict(),
+                "results": [r.to_dict() for r in results]
+            }
+        except Exception as e:
+            logging.error(f"Error getting run results {run_id}: {e}")
+            return {}
+
+    @classmethod
+    def get_recommendations(cls, run_id: str) -> List[Dict[str, Any]]:
+        """
+        Analyze evaluation results and provide configuration recommendations.
+
+        Args:
+            run_id: Evaluation run ID
+
+        Returns:
+            List of recommendation dictionaries
+        """
+        try:
+            run = EvaluationRun.get_by_id(run_id)
+            if not run or not run.metrics_summary:
+                return []
+
+            metrics = run.metrics_summary
+            recommendations = []
+
+            # Low precision: retrieving irrelevant chunks
+            if metrics.get("avg_precision", 1.0) < 0.7:
+                recommendations.append({
+                    "issue": "Low Precision",
+                    "severity": "high",
+                    "description": "System is retrieving many irrelevant chunks",
+                    "suggestions": [
+                        "Increase similarity_threshold to filter out less relevant chunks",
+                        "Enable reranking to improve chunk ordering",
+                        "Reduce top_k to return fewer chunks"
+                    ]
+                })
+
+            # Low recall: missing relevant chunks
+            if metrics.get("avg_recall", 1.0) < 0.7:
+                recommendations.append({
+                    "issue": "Low Recall",
+                    "severity": "high",
+                    "description": "System is missing relevant chunks",
+                    "suggestions": [
+                        "Increase top_k to retrieve more chunks",
+                        "Lower similarity_threshold to be more inclusive",
+                        "Enable hybrid search (keyword + semantic)",
+                        "Check chunk size - may be too large or too small"
+                    ]
+                })
+
+            # Slow response time
+            if metrics.get("avg_execution_time", 0) > 5.0:
+                recommendations.append({
+                    "issue": "Slow Response Time",
+                    "severity": "medium",
+                    "description": f"Average response time is {metrics['avg_execution_time']:.2f}s",
+                    "suggestions": [
+                        "Reduce top_k to retrieve fewer chunks",
+                        "Optimize embedding model selection",
+                        "Consider caching frequently asked questions"
+                    ]
+                })
+
+            return recommendations
+        except Exception as e:
+            logging.error(f"Error generating recommendations for run {run_id}: {e}")
+            return []

api/db/services/file_service.py

@@ -13,10 +13,15 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
+import base64
 import logging
 import re
+import sys
+import time
 from concurrent.futures import ThreadPoolExecutor
 from pathlib import Path
+from typing import Union
 
 from peewee import fn
 
@@ -89,13 +94,13 @@ class FileService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_kb_id_by_file_id(cls, file_id):
-        # Get knowledge base IDs associated with a file
+        # Get dataset IDs associated with a file
         # Args:
         #     file_id: File ID
         # Returns:
-        #     List of dictionaries containing knowledge base IDs and names
+        #     List of dictionaries containing dataset IDs and names
         kbs = (
-            cls.model.select(*[Knowledgebase.id, Knowledgebase.name])
+            cls.model.select(*[Knowledgebase.id, Knowledgebase.name, File2Document.document_id])
             .join(File2Document, on=(File2Document.file_id == file_id))
             .join(Document, on=(File2Document.document_id == Document.id))
             .join(Knowledgebase, on=(Knowledgebase.id == Document.kb_id))
@@ -105,7 +110,7 @@ class FileService(CommonService):
             return []
         kbs_info_list = []
         for kb in list(kbs.dicts()):
-            kbs_info_list.append({"kb_id": kb["id"], "kb_name": kb["name"]})
+            kbs_info_list.append({"kb_id": kb["id"], "kb_name": kb["name"], "document_id": kb["document_id"]})
         return kbs_info_list
 
     @classmethod
@@ -242,7 +247,7 @@ class FileService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_kb_folder(cls, tenant_id):
-        # Get knowledge base folder for tenant
+        # Get dataset folder for tenant
         # Args:
         #     tenant_id: Tenant ID
         # Returns:
@@ -258,7 +263,7 @@ class FileService(CommonService):
     @classmethod
     @DB.connection_context()
     def new_a_file_from_kb(cls, tenant_id, name, parent_id, ty=FileType.FOLDER.value, size=0, location=""):
-        # Create a new file from knowledge base
+        # Create a new file from dataset
         # Args:
         #     tenant_id: Tenant ID
         #     name: File name
@@ -287,7 +292,7 @@ class FileService(CommonService):
     @classmethod
     @DB.connection_context()
     def init_knowledgebase_docs(cls, root_id, tenant_id):
-        # Initialize knowledge base documents
+        # Initialize dataset documents
         # Args:
         #     root_id: Root folder ID
         #     tenant_id: Tenant ID
@@ -520,7 +525,7 @@ class FileService(CommonService):
         if img_base64 and file_type == FileType.VISUAL.value:
             return GptV4.image2base64(blob)
         cks = FACTORY.get(FileService.get_parser(filename_type(filename), filename, ""), naive).chunk(filename, blob, **kwargs)
-        return "\n".join([ck["content_with_weight"] for ck in cks])
+        return f"\n -----------------\nFile: {filename}\nContent as following: \n" + "\n".join([ck["content_with_weight"] for ck in cks])
 
     @staticmethod
     def get_parser(doc_type, filename, default):
@@ -588,3 +593,80 @@ class FileService(CommonService):
                 errors += str(e)
 
         return errors
+
+    @staticmethod
+    def upload_info(user_id, file, url: str|None=None):
+        def structured(filename, filetype, blob, content_type):
+            nonlocal user_id
+            if filetype == FileType.PDF.value:
+                blob = read_potential_broken_pdf(blob)
+
+            location = get_uuid()
+            FileService.put_blob(user_id, location, blob)
+
+            return {
+                "id": location,
+                "name": filename,
+                "size": sys.getsizeof(blob),
+                "extension": filename.split(".")[-1].lower(),
+                "mime_type": content_type,
+                "created_by": user_id,
+                "created_at": time.time(),
+                "preview_url": None
+            }
+
+        if url:
+            from crawl4ai import (
+                AsyncWebCrawler,
+                BrowserConfig,
+                CrawlerRunConfig,
+                DefaultMarkdownGenerator,
+                PruningContentFilter,
+                CrawlResult
+            )
+            filename = re.sub(r"\?.*", "", url.split("/")[-1])
+            async def adownload():
+                browser_config = BrowserConfig(
+                    headless=True,
+                    verbose=False,
+                )
+                async with AsyncWebCrawler(config=browser_config) as crawler:
+                    crawler_config = CrawlerRunConfig(
+                        markdown_generator=DefaultMarkdownGenerator(
+                            content_filter=PruningContentFilter()
+                        ),
+                        pdf=True,
+                        screenshot=False
+                    )
+                    result: CrawlResult = await crawler.arun(
+                        url=url,
+                        config=crawler_config
+                    )
+                    return result
+            page = asyncio.run(adownload())
+            if page.pdf:
+                if filename.split(".")[-1].lower() != "pdf":
+                    filename += ".pdf"
+                return structured(filename, "pdf", page.pdf, page.response_headers["content-type"])
+
+            return structured(filename, "html", str(page.markdown).encode("utf-8"), page.response_headers["content-type"], user_id)
+
+        DocumentService.check_doc_health(user_id, file.filename)
+        return structured(file.filename, filename_type(file.filename), file.read(), file.content_type)
+
+    @staticmethod
+    def get_files(files: Union[None, list[dict]]) -> list[str]:
+        if not files:
+            return  []
+        def image_to_base64(file):
+            return "data:{};base64,{}".format(file["mime_type"],
+                                        base64.b64encode(FileService.get_blob(file["created_by"], file["id"])).decode("utf-8"))
+        exe = ThreadPoolExecutor(max_workers=5)
+        threads = []
+        for file in files:
+            if file["mime_type"].find("image") >=0:
+                threads.append(exe.submit(image_to_base64, file))
+                continue
+            threads.append(exe.submit(FileService.parse, file["name"], FileService.get_blob(file["created_by"], file["id"]), True, file["created_by"]))
+        return [th.result() for th in threads]
+

api/db/services/knowledgebase_service.py

@@ -30,9 +30,9 @@ from api.utils.api_utils import get_parser_config, get_data_error_result
 
 
 class KnowledgebaseService(CommonService):
-    """Service class for managing knowledge base operations.
+    """Service class for managing dataset operations.
 
-    This class extends CommonService to provide specialized functionality for knowledge base
+    This class extends CommonService to provide specialized functionality for dataset
     management, including document parsing status tracking, access control, and configuration
     management. It handles operations such as listing, creating, updating, and deleting
     knowledge bases, as well as managing their associated documents and permissions.
@@ -41,7 +41,7 @@ class KnowledgebaseService(CommonService):
     - Document parsing status verification
     - Knowledge base access control
     - Parser configuration management
-    - Tenant-based knowledge base organization
+    - Tenant-based dataset organization
 
     Attributes:
         model: The Knowledgebase model class for database operations.
@@ -51,18 +51,18 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def accessible4deletion(cls, kb_id, user_id):
-        """Check if a knowledge base can be deleted by a specific user.
+        """Check if a dataset can be deleted by a specific user.
 
-        This method verifies whether a user has permission to delete a knowledge base
+        This method verifies whether a user has permission to delete a dataset
-        by checking if they are the creator of that knowledge base.
+        by checking if they are the creator of that dataset.
 
         Args:
-            kb_id (str): The unique identifier of the knowledge base to check.
+            kb_id (str): The unique identifier of the dataset to check.
             user_id (str): The unique identifier of the user attempting the deletion.
 
         Returns:
-            bool: True if the user has permission to delete the knowledge base,
+            bool: True if the user has permission to delete the dataset,
-                  False if the user doesn't have permission or the knowledge base doesn't exist.
+                  False if the user doesn't have permission or the dataset doesn't exist.
 
         Example:
             >>> KnowledgebaseService.accessible4deletion("kb123", "user456")
@@ -71,10 +71,10 @@ class KnowledgebaseService(CommonService):
         Note:
             - This method only checks creator permissions
             - A return value of False can mean either:
-                1. The knowledge base doesn't exist
+                1. The dataset doesn't exist
-                2. The user is not the creator of the knowledge base
+                2. The user is not the creator of the dataset
         """
-        # Check if a knowledge base can be deleted by a user
+        # Check if a dataset can be deleted by a user
         docs = cls.model.select(
             cls.model.id).where(cls.model.id == kb_id, cls.model.created_by == user_id).paginate(0, 1)
         docs = docs.dicts()
@@ -85,7 +85,7 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def is_parsed_done(cls, kb_id):
-        # Check if all documents in the knowledge base have completed parsing
+        # Check if all documents in the dataset have completed parsing
         #
         # Args:
         #     kb_id: Knowledge base ID
@@ -96,13 +96,13 @@ class KnowledgebaseService(CommonService):
         from common.constants import TaskStatus
         from api.db.services.document_service import DocumentService
 
-        # Get knowledge base information
+        # Get dataset information
         kbs = cls.query(id=kb_id)
         if not kbs:
             return False, "Knowledge base not found"
         kb = kbs[0]
 
-        # Get all documents in the knowledge base
+        # Get all documents in the dataset
         docs, _ = DocumentService.get_by_kb_id(kb_id, 1, 1000, "create_time", True, "", [], [])
 
         # Check parsing status of each document
@@ -119,9 +119,9 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def list_documents_by_ids(cls, kb_ids):
-        # Get document IDs associated with given knowledge base IDs
+        # Get document IDs associated with given dataset IDs
         # Args:
-        #     kb_ids: List of knowledge base IDs
+        #     kb_ids: List of dataset IDs
         # Returns:
         #     List of document IDs
         doc_ids = cls.model.select(Document.id.alias("document_id")).join(Document, on=(cls.model.id == Document.kb_id)).where(
@@ -235,11 +235,11 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_kb_ids(cls, tenant_id):
-        # Get all knowledge base IDs for a tenant
+        # Get all dataset IDs for a tenant
         # Args:
         #     tenant_id: Tenant ID
         # Returns:
-        #     List of knowledge base IDs
+        #     List of dataset IDs
         fields = [
             cls.model.id,
         ]
@@ -250,11 +250,11 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_detail(cls, kb_id):
-        # Get detailed information about a knowledge base
+        # Get detailed information about a dataset
         # Args:
         #     kb_id: Knowledge base ID
         # Returns:
-        #     Dictionary containing knowledge base details
+        #     Dictionary containing dataset details
         fields = [
             cls.model.id,
             cls.model.embd_id,
@@ -294,13 +294,13 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def update_parser_config(cls, id, config):
-        # Update parser configuration for a knowledge base
+        # Update parser configuration for a dataset
         # Args:
         #     id: Knowledge base ID
         #     config: New parser configuration
         e, m = cls.get_by_id(id)
         if not e:
-            raise LookupError(f"knowledgebase({id}) not found.")
+            raise LookupError(f"dataset({id}) not found.")
 
         def dfs_update(old, new):
             # Deep update of nested configuration
@@ -325,7 +325,7 @@ class KnowledgebaseService(CommonService):
     def delete_field_map(cls, id):
         e, m = cls.get_by_id(id)
         if not e:
-            raise LookupError(f"knowledgebase({id}) not found.")
+            raise LookupError(f"dataset({id}) not found.")
 
         m.parser_config.pop("field_map", None)
         cls.update_by_id(id, {"parser_config": m.parser_config})
@@ -335,7 +335,7 @@ class KnowledgebaseService(CommonService):
     def get_field_map(cls, ids):
         # Get field mappings for knowledge bases
         # Args:
-        #     ids: List of knowledge base IDs
+        #     ids: List of dataset IDs
         # Returns:
         #     Dictionary of field mappings
         conf = {}
@@ -347,7 +347,7 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_by_name(cls, kb_name, tenant_id):
-        # Get knowledge base by name and tenant ID
+        # Get dataset by name and tenant ID
         # Args:
         #     kb_name: Knowledge base name
         #     tenant_id: Tenant ID
@@ -365,9 +365,9 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_all_ids(cls):
-        # Get all knowledge base IDs
+        # Get all dataset IDs
         # Returns:
-        #     List of all knowledge base IDs
+        #     List of all dataset IDs
         return [m["id"] for m in cls.model.select(cls.model.id).dicts()]
 
 
@@ -471,7 +471,7 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def accessible(cls, kb_id, user_id):
-        # Check if a knowledge base is accessible by a user
+        # Check if a dataset is accessible by a user
         # Args:
         #     kb_id: Knowledge base ID
         #     user_id: User ID
@@ -488,12 +488,12 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_kb_by_id(cls, kb_id, user_id):
-        # Get knowledge base by ID and user ID
+        # Get dataset by ID and user ID
         # Args:
         #     kb_id: Knowledge base ID
         #     user_id: User ID
         # Returns:
-        #     List containing knowledge base information
+        #     List containing dataset information
         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()
@@ -502,12 +502,12 @@ class KnowledgebaseService(CommonService):
     @classmethod
     @DB.connection_context()
     def get_kb_by_name(cls, kb_name, user_id):
-        # Get knowledge base by name and user ID
+        # Get dataset by name and user ID
         # Args:
         #     kb_name: Knowledge base name
         #     user_id: User ID
         # Returns:
-        #     List containing knowledge base information
+        #     List containing dataset information
         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()

api/db/services/llm_service.py

@@ -13,16 +13,20 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 #
+import asyncio
 import inspect
 import logging
+import queue
 import re
-from common.token_utils import num_tokens_from_string
+import threading
 from functools import partial
 from typing import Generator
-from common.constants import LLMType
+
 from api.db.db_models import LLM
 from api.db.services.common_service import CommonService
 from api.db.services.tenant_llm_service import LLM4Tenant, TenantLLMService
+from common.constants import LLMType
+from common.token_utils import num_tokens_from_string
 
 
 class LLMService(CommonService):
@@ -31,6 +35,7 @@ class LLMService(CommonService):
 
 def get_init_tenant_llm(user_id):
     from common import settings
+
     tenant_llm = []
 
     model_configs = {
@@ -104,7 +109,7 @@ class LLMBundle(LLM4Tenant):
 
         llm_name = getattr(self, "llm_name", None)
         if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens, llm_name):
-            logging.error("LLMBundle.encode can't update token usage for {}/EMBEDDING used_tokens: {}".format(self.tenant_id, used_tokens))
+            logging.error("LLMBundle.encode can't update token usage for <tenant redacted>/EMBEDDING used_tokens: {}".format(used_tokens))
 
         if self.langfuse:
             generation.update(usage_details={"total_tokens": used_tokens})
@@ -119,7 +124,7 @@ class LLMBundle(LLM4Tenant):
         emd, used_tokens = self.mdl.encode_queries(query)
         llm_name = getattr(self, "llm_name", None)
         if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens, llm_name):
-            logging.error("LLMBundle.encode_queries 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 <tenant redacted>/EMBEDDING used_tokens: {}".format(used_tokens))
 
         if self.langfuse:
             generation.update(usage_details={"total_tokens": used_tokens})
@@ -183,6 +188,68 @@ class LLMBundle(LLM4Tenant):
 
         return txt
 
+    def stream_transcription(self, audio):
+        mdl = self.mdl
+        supports_stream = hasattr(mdl, "stream_transcription") and callable(getattr(mdl, "stream_transcription"))
+        if supports_stream:
+            if self.langfuse:
+                generation = self.langfuse.start_generation(
+                    trace_context=self.trace_context,
+                    name="stream_transcription",
+                    metadata={"model": self.llm_name},
+                )
+            final_text = ""
+            used_tokens = 0
+
+            try:
+                for evt in mdl.stream_transcription(audio):
+                    if evt.get("event") == "final":
+                        final_text = evt.get("text", "")
+
+                    yield evt
+
+            except Exception as e:
+                err = {"event": "error", "text": str(e)}
+                yield err
+                final_text = final_text or ""
+            finally:
+                if final_text:
+                    used_tokens = num_tokens_from_string(final_text)
+                    TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens)
+
+                if self.langfuse:
+                    generation.update(
+                        output={"output": final_text},
+                        usage_details={"total_tokens": used_tokens},
+                    )
+                    generation.end()
+
+            return
+
+        if self.langfuse:
+            generation = self.langfuse.start_generation(
+                trace_context=self.trace_context,
+                name="stream_transcription",
+                metadata={"model": self.llm_name},
+            )
+
+        full_text, used_tokens = mdl.transcription(audio)
+        if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens):
+            logging.error(f"LLMBundle.stream_transcription can't update token usage for {self.tenant_id}/SEQUENCE2TXT used_tokens: {used_tokens}")
+
+        if self.langfuse:
+            generation.update(
+                output={"output": full_text},
+                usage_details={"total_tokens": used_tokens},
+            )
+            generation.end()
+
+        yield {
+            "event": "final",
+            "text": full_text,
+            "streaming": False,
+        }
+
     def tts(self, text: str) -> Generator[bytes, None, None]:
         if self.langfuse:
             generation = self.langfuse.start_generation(trace_context=self.trace_context, name="tts", input={"text": text})
@@ -227,46 +294,132 @@ class LLMBundle(LLM4Tenant):
             return kwargs
         else:
             return {k: v for k, v in kwargs.items() if k in allowed_params}
-    def chat(self, system: str, history: list, gen_conf: dict = {}, **kwargs) -> str:
+
+    def _run_coroutine_sync(self, coro):
+        try:
+            asyncio.get_running_loop()
+        except RuntimeError:
+            return asyncio.run(coro)
+
+        result_queue: queue.Queue = queue.Queue()
+
+        def runner():
+            try:
+                result_queue.put((True, asyncio.run(coro)))
+            except Exception as e:
+                result_queue.put((False, e))
+
+        thread = threading.Thread(target=runner, daemon=True)
+        thread.start()
+        thread.join()
+
+        success, value = result_queue.get_nowait()
+        if success:
+            return value
+        raise value
+
+    def _sync_from_async_stream(self, async_gen_fn, *args, **kwargs):
+        result_queue: queue.Queue = queue.Queue()
+
+        def runner():
+            loop = asyncio.new_event_loop()
+            asyncio.set_event_loop(loop)
+
+            async def consume():
+                try:
+                    async for item in async_gen_fn(*args, **kwargs):
+                        result_queue.put(item)
+                except Exception as e:
+                    result_queue.put(e)
+                finally:
+                    result_queue.put(StopIteration)
+
+            loop.run_until_complete(consume())
+            loop.close()
+
+        threading.Thread(target=runner, daemon=True).start()
+
+        while True:
+            item = result_queue.get()
+            if item is StopIteration:
+                break
+            if isinstance(item, Exception):
+                raise item
+            yield item
+
+    def _bridge_sync_stream(self, gen):
+        loop = asyncio.get_running_loop()
+        queue: asyncio.Queue = asyncio.Queue()
+
+        def worker():
+            try:
+                for item in gen:
+                    loop.call_soon_threadsafe(queue.put_nowait, item)
+            except Exception as e:
+                loop.call_soon_threadsafe(queue.put_nowait, e)
+            finally:
+                loop.call_soon_threadsafe(queue.put_nowait, StopAsyncIteration)
+
+        threading.Thread(target=worker, daemon=True).start()
+        return queue
+
+    async def async_chat(self, system: str, history: list, gen_conf: dict = {}, **kwargs):
+        if self.is_tools and getattr(self.mdl, "is_tools", False) and hasattr(self.mdl, "async_chat_with_tools"):
+            base_fn = self.mdl.async_chat_with_tools
+        elif hasattr(self.mdl, "async_chat"):
+            base_fn = self.mdl.async_chat
+        else:
+            raise RuntimeError(f"Model {self.mdl} does not implement async_chat or async_chat_with_tools")
+
+        generation = None
         if self.langfuse:
             generation = self.langfuse.start_generation(trace_context=self.trace_context, name="chat", model=self.llm_name, input={"system": system, "history": history})
 
-        chat_partial = partial(self.mdl.chat, system, history, gen_conf, **kwargs)
+        chat_partial = partial(base_fn, system, history, gen_conf)
-        if self.is_tools and self.mdl.is_tools:
-            chat_partial = partial(self.mdl.chat_with_tools, system, history, gen_conf, **kwargs)
-
         use_kwargs = self._clean_param(chat_partial, **kwargs)
-        txt, used_tokens = chat_partial(**use_kwargs)
-        txt = self._remove_reasoning_content(txt)
 
+        try:
+            txt, used_tokens = await chat_partial(**use_kwargs)
+        except Exception as e:
+            if generation:
+                generation.update(output={"error": str(e)})
+                generation.end()
+            raise
+
+        txt = self._remove_reasoning_content(txt)
         if not self.verbose_tool_use:
             txt = re.sub(r"<tool_call>.*?</tool_call>", "", txt, flags=re.DOTALL)
 
-        if isinstance(txt, int) and not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens, self.llm_name):
+        if used_tokens and not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, used_tokens, self.llm_name):
-            logging.error("LLMBundle.chat can't update token usage for {}/CHAT llm_name: {}, used_tokens: {}".format(self.tenant_id, self.llm_name, used_tokens))
+            logging.error("LLMBundle.async_chat can't update token usage for {}/CHAT llm_name: {}, used_tokens: {}".format(self.tenant_id, self.llm_name, used_tokens))
 
-        if self.langfuse:
+        if generation:
             generation.update(output={"output": txt}, usage_details={"total_tokens": used_tokens})
             generation.end()
 
         return txt
 
-    def chat_streamly(self, system: str, history: list, gen_conf: dict = {}, **kwargs):
+    async def async_chat_streamly(self, system: str, history: list, gen_conf: dict = {}, **kwargs):
+        total_tokens = 0
+        ans = ""
+        if self.is_tools and getattr(self.mdl, "is_tools", False) and hasattr(self.mdl, "async_chat_streamly_with_tools"):
+            stream_fn = getattr(self.mdl, "async_chat_streamly_with_tools", None)
+        elif hasattr(self.mdl, "async_chat_streamly"):
+            stream_fn = getattr(self.mdl, "async_chat_streamly", None)
+        else:
+            raise RuntimeError(f"Model {self.mdl} does not implement async_chat or async_chat_with_tools")
+
+        generation = None
         if self.langfuse:
             generation = self.langfuse.start_generation(trace_context=self.trace_context, name="chat_streamly", model=self.llm_name, input={"system": system, "history": history})
 
-        ans = ""
+        if stream_fn:
-        chat_partial = partial(self.mdl.chat_streamly, system, history, gen_conf)
+            chat_partial = partial(stream_fn, system, history, gen_conf)
-        total_tokens = 0
-        if self.is_tools and self.mdl.is_tools:
-            chat_partial = partial(self.mdl.chat_streamly_with_tools, system, history, gen_conf)
             use_kwargs = self._clean_param(chat_partial, **kwargs)
-        for txt in chat_partial(**use_kwargs):
+            try:
+                async for txt in chat_partial(**use_kwargs):
                     if isinstance(txt, int):
                         total_tokens = txt
-                if self.langfuse:
-                    generation.update(output={"output": ans})
-                    generation.end()
                         break
 
                     if txt.endswith("</think>"):
@@ -277,7 +430,14 @@ class LLMBundle(LLM4Tenant):
 
                     ans += txt
                     yield ans
-
+            except Exception as e:
-        if total_tokens > 0:
+                if generation:
-            if not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, txt, self.llm_name):
+                    generation.update(output={"error": str(e)})
-                logging.error("LLMBundle.chat_streamly can't update token usage for {}/CHAT llm_name: {}, content: {}".format(self.tenant_id, self.llm_name, txt))
+                    generation.end()
+                raise
+            if total_tokens and not TenantLLMService.increase_usage(self.tenant_id, self.llm_type, total_tokens, self.llm_name):
+                logging.error("LLMBundle.async_chat_streamly can't update token usage for {}/CHAT llm_name: {}, used_tokens: {}".format(self.tenant_id, self.llm_name, total_tokens))
+            if generation:
+                generation.update(output={"output": ans}, usage_details={"total_tokens": total_tokens})
+                generation.end()
+            return

api/db/services/memory_service.py

@@ -0,0 +1,150 @@
+#
+#  Copyright 2025 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 typing import List
+
+from api.apps import current_user
+from api.db.db_models import DB, Memory, User
+from api.db.services import duplicate_name
+from api.db.services.common_service import CommonService
+from api.utils.memory_utils import calculate_memory_type
+from api.constants import MEMORY_NAME_LIMIT
+from common.misc_utils import get_uuid
+from common.time_utils import get_format_time, current_timestamp
+
+
+class MemoryService(CommonService):
+    # Service class for manage memory operations
+    model = Memory
+
+    @classmethod
+    @DB.connection_context()
+    def get_by_memory_id(cls, memory_id: str):
+        return cls.model.select().where(cls.model.id == memory_id).first()
+
+    @classmethod
+    @DB.connection_context()
+    def get_with_owner_name_by_id(cls, memory_id: str):
+        fields = [
+            cls.model.id,
+            cls.model.name,
+            cls.model.avatar,
+            cls.model.tenant_id,
+            User.nickname.alias("owner_name"),
+            cls.model.memory_type,
+            cls.model.storage_type,
+            cls.model.embd_id,
+            cls.model.llm_id,
+            cls.model.permissions,
+            cls.model.description,
+            cls.model.memory_size,
+            cls.model.forgetting_policy,
+            cls.model.temperature,
+            cls.model.system_prompt,
+            cls.model.user_prompt
+        ]
+        memory = cls.model.select(*fields).join(User, on=(cls.model.tenant_id == User.id)).where(
+            cls.model.id == memory_id
+        ).first()
+        return memory
+
+    @classmethod
+    @DB.connection_context()
+    def get_by_filter(cls, filter_dict: dict, keywords: str, page: int = 1, page_size: int = 50):
+        fields = [
+            cls.model.id,
+            cls.model.name,
+            cls.model.avatar,
+            cls.model.tenant_id,
+            User.nickname.alias("owner_name"),
+            cls.model.memory_type,
+            cls.model.storage_type,
+            cls.model.permissions,
+            cls.model.description
+        ]
+        memories = cls.model.select(*fields).join(User, on=(cls.model.tenant_id == User.id))
+        if filter_dict.get("tenant_id"):
+            memories = memories.where(cls.model.tenant_id.in_(filter_dict["tenant_id"]))
+        if filter_dict.get("memory_type"):
+            memory_type_int = calculate_memory_type(filter_dict["memory_type"])
+            memories = memories.where(cls.model.memory_type.bin_and(memory_type_int) > 0)
+        if filter_dict.get("storage_type"):
+            memories = memories.where(cls.model.storage_type == filter_dict["storage_type"])
+        if keywords:
+            memories = memories.where(cls.model.name.contains(keywords))
+        count = memories.count()
+        memories = memories.order_by(cls.model.update_time.desc())
+        memories = memories.paginate(page, page_size)
+
+        return list(memories.dicts()), count
+
+    @classmethod
+    @DB.connection_context()
+    def create_memory(cls, tenant_id: str, name: str, memory_type: List[str], embd_id: str, llm_id: str):
+        # Deduplicate name within tenant
+        memory_name = duplicate_name(
+            cls.query,
+            name=name,
+            tenant_id=tenant_id
+        )
+        if len(memory_name) > MEMORY_NAME_LIMIT:
+            return False, f"Memory name {memory_name} exceeds limit of {MEMORY_NAME_LIMIT}."
+
+        # build create dict
+        memory_info = {
+            "id": get_uuid(),
+            "name": memory_name,
+            "memory_type": calculate_memory_type(memory_type),
+            "tenant_id": tenant_id,
+            "embd_id": embd_id,
+            "llm_id": llm_id,
+            "create_time": current_timestamp(),
+            "create_date": get_format_time(),
+            "update_time": current_timestamp(),
+            "update_date": get_format_time(),
+        }
+        obj = cls.model(**memory_info).save(force_insert=True)
+
+        if not obj:
+            return False, "Could not create new memory."
+
+        db_row = cls.model.select().where(cls.model.id == memory_info["id"]).first()
+
+        return obj, db_row
+
+    @classmethod
+    @DB.connection_context()
+    def update_memory(cls, memory_id: str, update_dict: dict):
+        if not update_dict:
+            return 0
+        if "temperature" in update_dict and isinstance(update_dict["temperature"], str):
+            update_dict["temperature"] = float(update_dict["temperature"])
+        if "name" in update_dict:
+            update_dict["name"] = duplicate_name(
+                cls.query,
+                name=update_dict["name"],
+                tenant_id=current_user.id
+            )
+        update_dict.update({
+            "update_time": current_timestamp(),
+            "update_date": get_format_time()
+        })
+
+        return cls.model.update(update_dict).where(cls.model.id == memory_id).execute()
+
+    @classmethod
+    @DB.connection_context()
+    def delete_memory(cls, memory_id: str):
+        return cls.model.delete().where(cls.model.id == memory_id).execute()

api/db/services/pipeline_operation_log_service.py

@@ -121,7 +121,7 @@ class PipelineOperationLogService(CommonService):
         else:
             ok, kb_info = KnowledgebaseService.get_by_id(document.kb_id)
             if not ok:
-                raise RuntimeError(f"Cannot find knowledge base {document.kb_id} for referred_document {referred_document_id}")
+                raise RuntimeError(f"Cannot find dataset {document.kb_id} for referred_document {referred_document_id}")
 
             tenant_id = kb_info.tenant_id
             title = document.parser_id

api/db/services/task_service.py

@@ -76,7 +76,7 @@ class TaskService(CommonService):
         """Retrieve detailed task information by task ID.
 
         This method fetches comprehensive task details including associated document,
-        knowledge base, and tenant information. It also handles task retry logic and
+        dataset, and tenant information. It also handles task retry logic and
         progress updates.
 
         Args:
@@ -121,6 +121,13 @@ class TaskService(CommonService):
                 .where(cls.model.id == task_id)
         )
         docs = list(docs.dicts())
+        # Assuming docs = list(docs.dicts())
+        if docs:
+            kb_config = docs[0]['kb_parser_config']  # Dict from Knowledgebase.parser_config
+            mineru_method = kb_config.get('mineru_parse_method', 'auto')
+            mineru_formula = kb_config.get('mineru_formula_enable', True)
+            mineru_table = kb_config.get('mineru_table_enable', True)
+            print(mineru_method, mineru_formula, mineru_table)
         if not docs:
             return None
 

api/db/services/tenant_llm_service.py

@@ -14,15 +14,17 @@
 #  limitations under the License.
 #
 import os
+import json
 import logging
+from peewee import IntegrityError
 from langfuse import Langfuse
 from common import settings
-from common.constants import LLMType
+from common.constants import MINERU_DEFAULT_CONFIG, MINERU_ENV_KEYS, LLMType
 from api.db.db_models import DB, LLMFactories, TenantLLM
 from api.db.services.common_service import CommonService
 from api.db.services.langfuse_service import TenantLangfuseService
 from api.db.services.user_service import TenantService
-from rag.llm import ChatModel, CvModel, EmbeddingModel, RerankModel, Seq2txtModel, TTSModel
+from rag.llm import ChatModel, CvModel, EmbeddingModel, OcrModel, RerankModel, Seq2txtModel, TTSModel
 
 
 class LLMFactoriesService(CommonService):
@@ -104,6 +106,10 @@ class TenantLLMService(CommonService):
             mdlnm = tenant.rerank_id if not llm_name else llm_name
         elif llm_type == LLMType.TTS:
             mdlnm = tenant.tts_id if not llm_name else llm_name
+        elif llm_type == LLMType.OCR:
+            if not llm_name:
+                raise LookupError("OCR model name is required")
+            mdlnm = llm_name
         else:
             assert False, "LLM type error"
 
@@ -137,31 +143,31 @@ class TenantLLMService(CommonService):
             return EmbeddingModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"],
                                                                base_url=model_config["api_base"])
 
-        if llm_type == LLMType.RERANK:
+        elif llm_type == LLMType.RERANK:
             if model_config["llm_factory"] not in RerankModel:
                 return None
             return RerankModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"],
                                                             base_url=model_config["api_base"])
 
-        if llm_type == LLMType.IMAGE2TEXT.value:
+        elif llm_type == LLMType.IMAGE2TEXT.value:
             if model_config["llm_factory"] not in CvModel:
                 return None
             return CvModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"], lang,
                                                         base_url=model_config["api_base"], **kwargs)
 
-        if llm_type == LLMType.CHAT.value:
+        elif llm_type == LLMType.CHAT.value:
             if model_config["llm_factory"] not in ChatModel:
                 return None
             return ChatModel[model_config["llm_factory"]](model_config["api_key"], model_config["llm_name"],
                                                           base_url=model_config["api_base"], **kwargs)
 
-        if llm_type == LLMType.SPEECH2TEXT:
+        elif llm_type == LLMType.SPEECH2TEXT:
             if model_config["llm_factory"] not in Seq2txtModel:
                 return None
             return Seq2txtModel[model_config["llm_factory"]](key=model_config["api_key"],
                                                              model_name=model_config["llm_name"], lang=lang,
                                                              base_url=model_config["api_base"])
-        if llm_type == LLMType.TTS:
+        elif llm_type == LLMType.TTS:
             if model_config["llm_factory"] not in TTSModel:
                 return None
             return TTSModel[model_config["llm_factory"]](
@@ -169,6 +175,17 @@ class TenantLLMService(CommonService):
                 model_config["llm_name"],
                 base_url=model_config["api_base"],
             )
+
+        elif llm_type == LLMType.OCR:
+            if model_config["llm_factory"] not in OcrModel:
+                return None
+            return OcrModel[model_config["llm_factory"]](
+                key=model_config["api_key"],
+                model_name=model_config["llm_name"],
+                base_url=model_config.get("api_base", ""),
+                **kwargs,
+            )
+
         return None
 
     @classmethod
@@ -186,6 +203,7 @@ class TenantLLMService(CommonService):
             LLMType.CHAT.value: tenant.llm_id if not llm_name else llm_name,
             LLMType.RERANK.value: tenant.rerank_id if not llm_name else llm_name,
             LLMType.TTS.value: tenant.tts_id if not llm_name else llm_name,
+            LLMType.OCR.value: llm_name,
         }
 
         mdlnm = llm_map.get(llm_type)
@@ -218,6 +236,68 @@ class TenantLLMService(CommonService):
                                         ~(cls.model.llm_name == "text-embedding-3-large")).dicts()
         return list(objs)
 
+    @classmethod
+    def _collect_mineru_env_config(cls) -> dict | None:
+        cfg = MINERU_DEFAULT_CONFIG
+        found = False
+        for key in MINERU_ENV_KEYS:
+            val = os.environ.get(key)
+            if val:
+                found = True
+                cfg[key] = val
+        return cfg if found else None
+
+    @classmethod
+    @DB.connection_context()
+    def ensure_mineru_from_env(cls, tenant_id: str) -> str | None:
+        """
+        Ensure a MinerU OCR model exists for the tenant if env variables are present.
+        Return the existing or newly created llm_name, or None if env not set.
+        """
+        cfg = cls._collect_mineru_env_config()
+        if not cfg:
+            return None
+
+        saved_mineru_models = cls.query(tenant_id=tenant_id, llm_factory="MinerU", model_type=LLMType.OCR.value)
+
+        def _parse_api_key(raw: str) -> dict:
+            try:
+                return json.loads(raw or "{}")
+            except Exception:
+                return {}
+
+        for item in saved_mineru_models:
+            api_cfg = _parse_api_key(item.api_key)
+            normalized = {k: api_cfg.get(k, MINERU_DEFAULT_CONFIG.get(k)) for k in MINERU_ENV_KEYS}
+            if normalized == cfg:
+                return item.llm_name
+
+        used_names = {item.llm_name for item in saved_mineru_models}
+        idx = 1
+        base_name = "mineru-from-env"
+        while True:
+            candidate = f"{base_name}-{idx}"
+            if candidate in used_names:
+                idx += 1
+                continue
+
+            try:
+                cls.save(
+                    tenant_id=tenant_id,
+                    llm_factory="MinerU",
+                    llm_name=candidate,
+                    model_type=LLMType.OCR.value,
+                    api_key=json.dumps(cfg),
+                    api_base="",
+                    max_tokens=0,
+                )
+                return candidate
+            except IntegrityError:
+                logging.warning("MinerU env model %s already exists for tenant %s, retry with next name", candidate, tenant_id)
+                used_names.add(candidate)
+                idx += 1
+                continue
+
     @classmethod
     @DB.connection_context()
     def delete_by_tenant_id(cls, tenant_id):

api/ragflow_server.py

@@ -25,13 +25,12 @@ import logging
 import os
 import signal
 import sys
-import time
 import traceback
 import threading
 import uuid
 import faulthandler
 
-from api.apps import app, smtp_mail_server
+from api.apps import app
 from api.db.runtime_config import RuntimeConfig
 from api.db.services.document_service import DocumentService
 from common.file_utils import get_project_base_directory
@@ -69,7 +68,7 @@ def signal_handler(sig, frame):
     logging.info("Received interrupt signal, shutting down...")
     shutdown_all_mcp_sessions()
     stop_event.set()
-    time.sleep(1)
+    stop_event.wait(1)
     sys.exit(0)
 
 if __name__ == '__main__':
@@ -144,18 +143,6 @@ if __name__ == '__main__':
     else:
         threading.Timer(1.0, delayed_start_update_progress).start()
 
-    # init smtp server
-    if settings.SMTP_CONF:
-        app.config["MAIL_SERVER"] = settings.MAIL_SERVER
-        app.config["MAIL_PORT"] = settings.MAIL_PORT
-        app.config["MAIL_USE_SSL"] = settings.MAIL_USE_SSL
-        app.config["MAIL_USE_TLS"] = settings.MAIL_USE_TLS
-        app.config["MAIL_USERNAME"] = settings.MAIL_USERNAME
-        app.config["MAIL_PASSWORD"] = settings.MAIL_PASSWORD
-        app.config["MAIL_DEFAULT_SENDER"] = settings.MAIL_DEFAULT_SENDER
-        smtp_mail_server.init_app(app)
-
-
     # start http server
     try:
         logging.info("RAGFlow HTTP server start...")
@@ -163,5 +150,5 @@ if __name__ == '__main__':
     except Exception:
         traceback.print_exc()
         stop_event.set()
-        time.sleep(1)
+        stop_event.wait(1)
         os.kill(os.getpid(), signal.SIGKILL)

api/utils/api_utils.py

@@ -14,6 +14,7 @@
 #  limitations under the License.
 #
 
+import asyncio
 import functools
 import inspect
 import json
@@ -22,9 +23,9 @@ import os
 import time
 from copy import deepcopy
 from functools import wraps
+from typing import Any
 
 import requests
-import trio
 from quart import (
     Response,
     jsonify,
@@ -45,11 +46,40 @@ from common import settings
 requests.models.complexjson.dumps = functools.partial(json.dumps, cls=CustomJSONEncoder)
 
 
-async def request_json():
+async def _coerce_request_data() -> dict:
+    """Fetch JSON body with sane defaults; fallback to form data."""
+    payload: Any = None
+    last_error: Exception | None = None
+
     try:
-        return await request.json
+        payload = await request.get_json(force=True, silent=True)
-    except Exception:
+    except Exception as e:
-        return {}
+        last_error = e
+        payload = None
+
+    if payload is None:
+        try:
+            form = await request.form
+            payload = form.to_dict()
+        except Exception as e:
+            last_error = e
+            payload = None
+
+    if payload is None:
+        if last_error is not None:
+            raise last_error
+        raise ValueError("No JSON body or form data found in request.")
+
+    if isinstance(payload, dict):
+        return payload or {}
+
+    if isinstance(payload, str):
+        raise AttributeError("'str' object has no attribute 'get'")
+
+    raise TypeError(f"Unsupported request payload type: {type(payload)!r}")
+
+async def get_request_json():
+    return await _coerce_request_data()
 
 def serialize_for_json(obj):
     """
@@ -137,7 +167,7 @@ def validate_request(*args, **kwargs):
     def wrapper(func):
         @wraps(func)
         async def decorated_function(*_args, **_kwargs):
-            errs = process_args(await request.json or (await request.form).to_dict())
+            errs = process_args(await _coerce_request_data())
             if errs:
                 return get_json_result(code=RetCode.ARGUMENT_ERROR, message=errs)
             if inspect.iscoroutinefunction(func):
@@ -152,7 +182,7 @@ def validate_request(*args, **kwargs):
 def not_allowed_parameters(*params):
     def decorator(func):
         async def wrapper(*args, **kwargs):
-            input_arguments = await request.json or (await request.form).to_dict()
+            input_arguments = await _coerce_request_data()
             for param in params:
                 if param in input_arguments:
                     return get_json_result(code=RetCode.ARGUMENT_ERROR, message=f"Parameter {param} isn't allowed")
@@ -313,6 +343,10 @@ def get_parser_config(chunk_method, parser_config):
         chunk_method = "naive"
 
     # Define default configurations for each chunking method
+    base_defaults = {
+        "table_context_size": 0,
+        "image_context_size": 0,
+    }
     key_mapping = {
         "naive": {
             "layout_recognize": "DeepDOC",
@@ -365,16 +399,19 @@ def get_parser_config(chunk_method, parser_config):
 
     default_config = key_mapping[chunk_method]
 
-    # If no parser_config provided, return default
+    # If no parser_config provided, return default merged with base defaults
     if not parser_config:
-        return default_config
+        if default_config is None:
+            return deep_merge(base_defaults, {})
+        return deep_merge(base_defaults, default_config)
 
     # If parser_config is provided, merge with defaults to ensure required fields exist
     if default_config is None:
-        return parser_config
+        return deep_merge(base_defaults, parser_config)
 
     # Ensure raptor and graphrag fields have default values if not provided
-    merged_config = deep_merge(default_config, parser_config)
+    merged_config = deep_merge(base_defaults, default_config)
+    merged_config = deep_merge(merged_config, parser_config)
 
     return merged_config
 
@@ -644,18 +681,32 @@ async def is_strong_enough(chat_model, embedding_model):
     async def _is_strong_enough():
         nonlocal chat_model, embedding_model
         if embedding_model:
-            with trio.fail_after(10):
+            await asyncio.wait_for(
-                _ = await trio.to_thread.run_sync(lambda: embedding_model.encode(["Are you strong enough!?"]))
+                asyncio.to_thread(embedding_model.encode, ["Are you strong enough!?"]),
+                timeout=10
+            )
+
         if chat_model:
-            with trio.fail_after(30):
+            res = await asyncio.wait_for(
-                res = await trio.to_thread.run_sync(lambda: chat_model.chat("Nothing special.", [{"role": "user", "content": "Are you strong enough!?"}], {}))
+                chat_model.async_chat("Nothing special.", [{"role": "user", "content": "Are you strong enough!?"}]),
-            if res.find("**ERROR**") >= 0:
+                timeout=30
+            )
+            if "**ERROR**" in res:
                 raise Exception(res)
 
     # Pressure test for GraphRAG task
-    async with trio.open_nursery() as nursery:
+    tasks = [
-        for _ in range(count):
+        asyncio.create_task(_is_strong_enough())
-            nursery.start_soon(_is_strong_enough)
+        for _ in range(count)
+    ]
+    try:
+        await asyncio.gather(*tasks, return_exceptions=False)
+    except Exception as e:
+        logging.error(f"Pressure test failed: {e}")
+        for t in tasks:
+            t.cancel()
+        await asyncio.gather(*tasks, return_exceptions=True)
+        raise
 
 
 def get_allowed_llm_factories() -> list:

api/utils/email_templates.py

@@ -20,18 +20,18 @@ Reusable HTML email templates and registry.
 
 # Invitation email template
 INVITE_EMAIL_TMPL = """
-<p>Hi {{email}},</p>
+Hi {{email}},
-<p>{{inviter}} has invited you to join their team (ID: {{tenant_id}}).</p>
+{{inviter}} has invited you to join their team (ID: {{tenant_id}}).
-<p>Click the link below to complete your registration:<br>
+Click the link below to complete your registration:
-<a href="{{invite_url}}">{{invite_url}}</a></p>
+{{invite_url}}
-<p>If you did not request this, please ignore this email.</p>
+If you did not request this, please ignore this email.
 """
 
 # Password reset code template
 RESET_CODE_EMAIL_TMPL = """
-<p>Hello,</p>
+Hello,
-<p>Your password reset code is: <b>{{ code }}</b></p>
+Your password reset code is: {{ code }}
-<p>This code will expire in {{ ttl_min }} minutes.</p>
+This code will expire in {{ ttl_min }} minutes.
 """
 
 # Template registry

api/utils/memory_utils.py

@@ -0,0 +1,54 @@
+#
+#  Copyright 2025 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 typing import List
+from common.constants import MemoryType
+
+def format_ret_data_from_memory(memory):
+    return {
+        "id": memory.id,
+        "name": memory.name,
+        "avatar": memory.avatar,
+        "tenant_id": memory.tenant_id,
+        "owner_name": memory.owner_name if hasattr(memory, "owner_name") else None,
+        "memory_type": get_memory_type_human(memory.memory_type),
+        "storage_type": memory.storage_type,
+        "embd_id": memory.embd_id,
+        "llm_id": memory.llm_id,
+        "permissions": memory.permissions,
+        "description": memory.description,
+        "memory_size": memory.memory_size,
+        "forgetting_policy": memory.forgetting_policy,
+        "temperature": memory.temperature,
+        "system_prompt": memory.system_prompt,
+        "user_prompt": memory.user_prompt,
+        "create_time": memory.create_time,
+        "create_date": memory.create_date,
+        "update_time": memory.update_time,
+        "update_date": memory.update_date
+    }
+
+
+def get_memory_type_human(memory_type: int) -> List[str]:
+    return [mem_type.name.lower() for mem_type in MemoryType if memory_type & mem_type.value]
+
+
+def calculate_memory_type(memory_type_name_list: List[str]) -> int:
+    memory_type = 0
+    type_value_map = {mem_type.name.lower(): mem_type.value for mem_type in MemoryType}
+    for mem_type in memory_type_name_list:
+        if mem_type in type_value_map:
+            memory_type |= type_value_map[mem_type]
+    return memory_type

api/utils/validation_utils.py

@@ -14,6 +14,7 @@
 #  limitations under the License.
 #
 from collections import Counter
+import string
 from typing import Annotated, Any, Literal
 from uuid import UUID
 
@@ -25,6 +26,7 @@ from pydantic import (
     StringConstraints,
     ValidationError,
     field_validator,
+    model_validator,
 )
 from pydantic_core import PydanticCustomError
 from werkzeug.exceptions import BadRequest, UnsupportedMediaType
@@ -329,6 +331,7 @@ class RaptorConfig(Base):
     threshold: Annotated[float, Field(default=0.1, ge=0.0, le=1.0)]
     max_cluster: Annotated[int, Field(default=64, ge=1, le=1024)]
     random_seed: Annotated[int, Field(default=0, ge=0)]
+    auto_disable_for_structured_data: Annotated[bool, Field(default=True)]
 
 
 class GraphragConfig(Base):
@@ -361,10 +364,9 @@ class CreateDatasetReq(Base):
     description: Annotated[str | None, Field(default=None, max_length=65535)]
     embedding_model: Annotated[str | None, Field(default=None, max_length=255, serialization_alias="embd_id")]
     permission: Annotated[Literal["me", "team"], Field(default="me", min_length=1, max_length=16)]
-    chunk_method: Annotated[
+    chunk_method: Annotated[str | None, Field(default=None, serialization_alias="parser_id")]
-        Literal["naive", "book", "email", "laws", "manual", "one", "paper", "picture", "presentation", "qa", "table", "tag"],
+    parse_type: Annotated[int | None, Field(default=None, ge=0, le=64)]
-        Field(default="naive", min_length=1, max_length=32, serialization_alias="parser_id"),
+    pipeline_id: Annotated[str | None, Field(default=None, min_length=32, max_length=32, serialization_alias="pipeline_id")]
-    ]
     parser_config: Annotated[ParserConfig | None, Field(default=None)]
 
     @field_validator("avatar", mode="after")
@@ -525,6 +527,93 @@ class CreateDatasetReq(Base):
             raise PydanticCustomError("string_too_long", "Parser config exceeds size limit (max 65,535 characters). Current size: {actual}", {"actual": len(json_str)})
         return v
 
+    @field_validator("pipeline_id", mode="after")
+    @classmethod
+    def validate_pipeline_id(cls, v: str | None) -> str | None:
+        """Validate pipeline_id as 32-char lowercase hex string if provided.
+
+        Rules:
+        - None or empty string: treat as None (not set)
+        - Must be exactly length 32
+        - Must contain only hex digits (0-9a-fA-F); normalized to lowercase
+        """
+        if v is None:
+            return None
+        if v == "":
+            return None
+        if len(v) != 32:
+            raise PydanticCustomError("format_invalid", "pipeline_id must be 32 hex characters")
+        if any(ch not in string.hexdigits for ch in v):
+            raise PydanticCustomError("format_invalid", "pipeline_id must be hexadecimal")
+        return v.lower()
+
+    @model_validator(mode="after")
+    def validate_parser_dependency(self) -> "CreateDatasetReq":
+        """
+        Mixed conditional validation:
+        - If parser_id is omitted (field not set):
+            * If both parse_type and pipeline_id are omitted → default chunk_method = "naive"
+            * If both parse_type and pipeline_id are provided → allow ingestion pipeline mode
+        - If parser_id is provided (valid enum) → parse_type and pipeline_id must be None (disallow mixed usage)
+
+        Raises:
+            PydanticCustomError with code 'dependency_error' on violation.
+        """
+        # Omitted chunk_method (not in fields) logic
+        if self.chunk_method is None and "chunk_method" not in self.model_fields_set:
+            # All three absent → default naive
+            if self.parse_type is None and self.pipeline_id is None:
+                object.__setattr__(self, "chunk_method", "naive")
+                return self
+            # parser_id omitted: require BOTH parse_type & pipeline_id present (no partial allowed)
+            if self.parse_type is None or self.pipeline_id is None:
+                missing = []
+                if self.parse_type is None:
+                    missing.append("parse_type")
+                if self.pipeline_id is None:
+                    missing.append("pipeline_id")
+                raise PydanticCustomError(
+                    "dependency_error",
+                    "parser_id omitted → required fields missing: {fields}",
+                    {"fields": ", ".join(missing)},
+                )
+            # Both provided → allow pipeline mode
+            return self
+
+        # parser_id provided (valid): MUST NOT have parse_type or pipeline_id
+        if isinstance(self.chunk_method, str):
+            if self.parse_type is not None or self.pipeline_id is not None:
+                invalid = []
+                if self.parse_type is not None:
+                    invalid.append("parse_type")
+                if self.pipeline_id is not None:
+                    invalid.append("pipeline_id")
+                raise PydanticCustomError(
+                    "dependency_error",
+                    "parser_id provided → disallowed fields present: {fields}",
+                    {"fields": ", ".join(invalid)},
+                )
+        return self
+
+    @field_validator("chunk_method", mode="wrap")
+    @classmethod
+    def validate_chunk_method(cls, v: Any, handler) -> Any:
+        """Wrap validation to unify error messages, including type errors (e.g. list)."""
+        allowed = {"naive", "book", "email", "laws", "manual", "one", "paper", "picture", "presentation", "qa", "table", "tag"}
+        error_msg = "Input should be 'naive', 'book', 'email', 'laws', 'manual', 'one', 'paper', 'picture', 'presentation', 'qa', 'table' or 'tag'"
+        # Omitted field: handler won't be invoked (wrap still gets value); None treated as explicit invalid
+        if v is None:
+            raise PydanticCustomError("literal_error", error_msg)
+        try:
+            # Run inner validation (type checking)
+            result = handler(v)
+        except Exception:
+            raise PydanticCustomError("literal_error", error_msg)
+        # After handler, enforce enumeration
+        if not isinstance(result, str) or result == "" or result not in allowed:
+            raise PydanticCustomError("literal_error", error_msg)
+        return result
+
 
 class UpdateDatasetReq(CreateDatasetReq):
     dataset_id: Annotated[str, Field(...)]

api/utils/web_utils.py

@@ -20,9 +20,10 @@ import json
 import re
 import socket
 from urllib.parse import urlparse
-
+import aiosmtplib
-from api.apps import smtp_mail_server
+from email.mime.text import MIMEText
-from flask_mail import Message
+from email.header import Header
+from common import settings
 from quart import render_template_string
 from api.utils.email_templates import EMAIL_TEMPLATES
 from selenium import webdriver
@@ -35,11 +36,11 @@ from selenium.webdriver.support.ui import WebDriverWait
 from webdriver_manager.chrome import ChromeDriverManager
 
 
-OTP_LENGTH = 8
+OTP_LENGTH = 4
-OTP_TTL_SECONDS = 5 * 60
+OTP_TTL_SECONDS = 5 * 60 # valid for 5 minutes
-ATTEMPT_LIMIT = 5
+ATTEMPT_LIMIT = 5 # maximum attempts
-ATTEMPT_LOCK_SECONDS = 30 * 60
+ATTEMPT_LOCK_SECONDS = 30 * 60 # lock for 30 minutes
-RESEND_COOLDOWN_SECONDS = 60
+RESEND_COOLDOWN_SECONDS = 60 # cooldown for 1 minute
 
 
 CONTENT_TYPE_MAP = {
@@ -185,25 +186,32 @@ def get_float(req: dict, key: str, default: float | int = 10.0) -> float:
         return default
     
 
-def send_email_html(subject: str, to_email: str, template_key: str, **context):
+async def send_email_html(to_email: str, subject: str, template_key: str, **context):
-    """Generic HTML email sender using shared templates.
+
-    template_key must exist in EMAIL_TEMPLATES.
+    body = await render_template_string(EMAIL_TEMPLATES.get(template_key), **context)
-    """
+    msg = MIMEText(body, "plain", "utf-8")
-    from api.apps import app
+    msg["Subject"] = Header(subject, "utf-8")
-    tmpl = EMAIL_TEMPLATES.get(template_key)
+    msg["From"] = f"{settings.MAIL_DEFAULT_SENDER[0]} <{settings.MAIL_DEFAULT_SENDER[1]}>"
-    if not tmpl:
+    msg["To"] = to_email
-        raise ValueError(f"Unknown email template: {template_key}")
+
-    with app.app_context():
+    smtp = aiosmtplib.SMTP(
-        msg = Message(subject=subject, recipients=[to_email])
+        hostname=settings.MAIL_SERVER,
-        msg.html = render_template_string(tmpl, **context)
+        port=settings.MAIL_PORT,
-        smtp_mail_server.send(msg)
+        use_tls=True,
+        timeout=10,
+    )
+
+    await smtp.connect()
+    await smtp.login(settings.MAIL_USERNAME, settings.MAIL_PASSWORD)
+    await smtp.send_message(msg)
+    await smtp.quit()
 
 
-def send_invite_email(to_email, invite_url, tenant_id, inviter):
+async def send_invite_email(to_email, invite_url, tenant_id, inviter):
     # Reuse the generic HTML sender with 'invite' template
-    send_email_html(
+    await send_email_html(
-        subject="RAGFlow Invitation",
         to_email=to_email,
+        subject="RAGFlow Invitation",
         template_key="invite",
         email=to_email,
         invite_url=invite_url,

common/connection_utils.py

@@ -19,7 +19,6 @@ import queue
 import threading
 from typing import Any, Callable, Coroutine, Optional, Type, Union
 import asyncio
-import trio
 from functools import wraps
 from quart import make_response, jsonify
 from common.constants import RetCode
@@ -70,11 +69,10 @@ def timeout(seconds: float | int | str = None, attempts: int = 2, *, exception:
             for a in range(attempts):
                 try:
                     if os.environ.get("ENABLE_TIMEOUT_ASSERTION"):
-                        with trio.fail_after(seconds):
+                        return await asyncio.wait_for(func(*args, **kwargs), timeout=seconds)
-                            return await func(*args, **kwargs)
                     else:
                         return await func(*args, **kwargs)
-                except trio.TooSlowError:
+                except asyncio.TimeoutError:
                     if a < attempts - 1:
                         continue
                     if on_timeout is not None:

common/constants.py

@@ -49,6 +49,7 @@ class RetCode(IntEnum, CustomEnum):
     RUNNING = 106
     PERMISSION_ERROR = 108
     AUTHENTICATION_ERROR = 109
+    BAD_REQUEST = 400
     UNAUTHORIZED = 401
     SERVER_ERROR = 500
     FORBIDDEN = 403
@@ -72,6 +73,7 @@ class LLMType(StrEnum):
     IMAGE2TEXT = 'image2text'
     RERANK = 'rerank'
     TTS = 'tts'
+    OCR = 'ocr'
 
 
 class TaskStatus(StrEnum):
@@ -121,7 +123,7 @@ class FileSource(StrEnum):
     WEBDAV = "webdav"
     MOODLE = "moodle"
     DROPBOX = "dropbox"
-
+    BOX = "box"
 
 class PipelineTaskType(StrEnum):
     PARSE = "Parse"
@@ -147,6 +149,24 @@ class Storage(Enum):
     AWS_S3 = 4
     OSS = 5
     OPENDAL = 6
+    GCS = 7
+
+
+class MemoryType(Enum):
+    RAW = 0b0001          # 1 << 0 = 1 (0b00000001)
+    SEMANTIC = 0b0010     # 1 << 1 = 2 (0b00000010)
+    EPISODIC = 0b0100     # 1 << 2 = 4 (0b00000100)
+    PROCEDURAL = 0b1000   # 1 << 3 = 8 (0b00001000)
+
+
+class MemoryStorageType(StrEnum):
+    TABLE = "table"
+    GRAPH = "graph"
+
+
+class ForgettingPolicy(StrEnum):
+    FIFO = "fifo"
+
 
 # environment
 # ENV_STRONG_TEST_COUNT = "STRONG_TEST_COUNT"
@@ -197,3 +217,13 @@ PAGERANK_FLD = "pagerank_fea"
 SVR_QUEUE_NAME = "rag_flow_svr_queue"
 SVR_CONSUMER_GROUP_NAME = "rag_flow_svr_task_broker"
 TAG_FLD = "tag_feas"
+
+
+MINERU_ENV_KEYS = ["MINERU_APISERVER", "MINERU_OUTPUT_DIR", "MINERU_BACKEND", "MINERU_SERVER_URL", "MINERU_DELETE_OUTPUT"]
+MINERU_DEFAULT_CONFIG = {
+    "MINERU_APISERVER": "",
+    "MINERU_OUTPUT_DIR": "",
+    "MINERU_BACKEND": "pipeline",
+    "MINERU_SERVER_URL": "",
+    "MINERU_DELETE_OUTPUT": 1,
+}

common/crypto_utils.py

@@ -0,0 +1,374 @@
+#
+#  Copyright 2025 The InfiniFlow Authors. All Rights Reserved.
+#
+#  Licensed under the Apache License, Version 2.0 (the "License");
+#  you may not use this file except in compliance with the License.
+#  You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+#  Unless required by applicable law or agreed to in writing, software
+#  distributed under the License is distributed on an "AS IS" BASIS,
+#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+#  See the License for the specific language governing permissions and
+#  limitations under the License.
+#
+
+import os
+from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
+from cryptography.hazmat.primitives import padding
+from cryptography.hazmat.backends import default_backend
+from cryptography.hazmat.primitives.kdf.pbkdf2 import PBKDF2HMAC
+from cryptography.hazmat.primitives import hashes
+
+
+class BaseCrypto:
+    """Base class for cryptographic algorithms"""
+    
+    # Magic header to identify encrypted data
+    ENCRYPTED_MAGIC = b'RAGF'
+    
+    def __init__(self, key, iv=None, block_size=16, key_length=32, iv_length=16):
+        """
+        Initialize cryptographic algorithm
+        
+        Args:
+            key: Encryption key
+            iv: Initialization vector, automatically generated if None
+            block_size: Block size
+            key_length: Key length
+            iv_length: Initialization vector length
+        """
+        self.block_size = block_size
+        self.key_length = key_length
+        self.iv_length = iv_length
+        
+        # Normalize key
+        self.key = self._normalize_key(key)
+        self.iv = iv
+    
+    def _normalize_key(self, key):
+        """Normalize key length"""
+        if isinstance(key, str):
+            key = key.encode('utf-8')
+        
+        # Use PBKDF2 for key derivation to ensure correct key length
+        kdf = PBKDF2HMAC(
+            algorithm=hashes.SHA256(),
+            length=self.key_length,
+            salt=b"ragflow_crypto_salt",  # Fixed salt to ensure consistent key derivation results
+            iterations=100000,
+            backend=default_backend()
+        )
+        
+        return kdf.derive(key)
+    
+    def encrypt(self, data):
+        """
+        Encrypt data (template method)
+        
+        Args:
+            data: Data to encrypt (bytes)
+            
+        Returns:
+            Encrypted data (bytes), format: magic_header + iv + encrypted_data
+        """
+        # Generate random IV
+        iv = os.urandom(self.iv_length) if not self.iv else self.iv
+        
+        # Use PKCS7 padding
+        padder = padding.PKCS7(self.block_size * 8).padder()
+        padded_data = padder.update(data) + padder.finalize()
+        
+        # Delegate to subclass for specific encryption
+        ciphertext = self._encrypt(padded_data, iv)
+        
+        # Return Magic Header + IV + encrypted data
+        return self.ENCRYPTED_MAGIC + iv + ciphertext
+    
+    def decrypt(self, encrypted_data):
+        """
+        Decrypt data (template method)
+        
+        Args:
+            encrypted_data: Encrypted data (bytes)
+            
+        Returns:
+            Decrypted data (bytes)
+        """
+        # Check if data is encrypted by magic header
+        if not encrypted_data.startswith(self.ENCRYPTED_MAGIC):
+            # Not encrypted, return as-is
+            return encrypted_data
+        
+        # Remove magic header
+        encrypted_data = encrypted_data[len(self.ENCRYPTED_MAGIC):]
+        
+        # Separate IV and encrypted data
+        iv = encrypted_data[:self.iv_length]
+        ciphertext = encrypted_data[self.iv_length:]
+        
+        # Delegate to subclass for specific decryption
+        padded_data = self._decrypt(ciphertext, iv)
+        
+        # Remove padding
+        unpadder = padding.PKCS7(self.block_size * 8).unpadder()
+        data = unpadder.update(padded_data) + unpadder.finalize()
+        
+        return data
+    
+    def _encrypt(self, padded_data, iv):
+        """
+        Encrypt padded data with specific algorithm
+        
+        Args:
+            padded_data: Padded data to encrypt
+            iv: Initialization vector
+            
+        Returns:
+            Encrypted data
+        """
+        raise NotImplementedError("_encrypt method must be implemented by subclass")
+    
+    def _decrypt(self, ciphertext, iv):
+        """
+        Decrypt ciphertext with specific algorithm
+        
+        Args:
+            ciphertext: Ciphertext to decrypt
+            iv: Initialization vector
+            
+        Returns:
+            Decrypted padded data
+        """
+        raise NotImplementedError("_decrypt method must be implemented by subclass")
+
+
+class AESCrypto(BaseCrypto):
+    """Base class for AES cryptographic algorithm"""
+    
+    def __init__(self, key, iv=None, key_length=32):
+        """
+        Initialize AES cryptographic algorithm
+        
+        Args:
+            key: Encryption key
+            iv: Initialization vector, automatically generated if None
+            key_length: Key length (16 for AES-128, 32 for AES-256)
+        """
+        super().__init__(key, iv, block_size=16, key_length=key_length, iv_length=16)
+
+    def _encrypt(self, padded_data, iv):
+        """AES encryption implementation"""
+        # Create encryptor
+        cipher = Cipher(
+            algorithms.AES(self.key),
+            modes.CBC(iv),
+            backend=default_backend()
+        )
+        encryptor = cipher.encryptor()
+        
+        # Encrypt data
+        return encryptor.update(padded_data) + encryptor.finalize()
+    
+    def _decrypt(self, ciphertext, iv):
+        """AES decryption implementation"""
+        # Create decryptor
+        cipher = Cipher(
+            algorithms.AES(self.key),
+            modes.CBC(iv),
+            backend=default_backend()
+        )
+        decryptor = cipher.decryptor()
+        
+        # Decrypt data
+        return decryptor.update(ciphertext) + decryptor.finalize()
+
+
+class AES128CBC(AESCrypto):
+    """AES-128-CBC cryptographic algorithm"""
+    
+    def __init__(self, key, iv=None):
+        """
+        Initialize AES-128-CBC cryptographic algorithm
+        
+        Args:
+            key: Encryption key
+            iv: Initialization vector, automatically generated if None
+        """
+        super().__init__(key, iv, key_length=16)
+
+
+class AES256CBC(AESCrypto):
+    """AES-256-CBC cryptographic algorithm"""
+    
+    def __init__(self, key, iv=None):
+        """
+        Initialize AES-256-CBC cryptographic algorithm
+        
+        Args:
+            key: Encryption key
+            iv: Initialization vector, automatically generated if None
+        """
+        super().__init__(key, iv, key_length=32)
+
+
+class SM4CBC(BaseCrypto):
+    """SM4-CBC cryptographic algorithm using cryptography library for better performance"""
+    
+    def __init__(self, key, iv=None):
+        """
+        Initialize SM4-CBC cryptographic algorithm
+        
+        Args:
+            key: Encryption key
+            iv: Initialization vector, automatically generated if None
+        """
+        super().__init__(key, iv, block_size=16, key_length=16, iv_length=16)
+
+    def _encrypt(self, padded_data, iv):
+        """SM4 encryption implementation using cryptography library"""
+        # Create encryptor
+        cipher = Cipher(
+            algorithms.SM4(self.key),
+            modes.CBC(iv),
+            backend=default_backend()
+        )
+        encryptor = cipher.encryptor()
+        
+        # Encrypt data
+        return encryptor.update(padded_data) + encryptor.finalize()
+    
+    def _decrypt(self, ciphertext, iv):
+        """SM4 decryption implementation using cryptography library"""
+        # Create decryptor
+        cipher = Cipher(
+            algorithms.SM4(self.key),
+            modes.CBC(iv),
+            backend=default_backend()
+        )
+        decryptor = cipher.decryptor()
+        
+        # Decrypt data
+        return decryptor.update(ciphertext) + decryptor.finalize()
+
+
+class CryptoUtil:
+    """Cryptographic utility class, using factory pattern to create cryptographic algorithm instances"""
+    
+    # Supported cryptographic algorithms mapping
+    SUPPORTED_ALGORITHMS = {
+        "aes-128-cbc": AES128CBC,
+        "aes-256-cbc": AES256CBC,
+        "sm4-cbc": SM4CBC
+    }
+    
+    def __init__(self, algorithm="aes-256-cbc", key=None, iv=None):
+        """
+        Initialize cryptographic utility
+        
+        Args:
+            algorithm: Cryptographic algorithm, default is aes-256-cbc
+            key: Encryption key, uses RAGFLOW_CRYPTO_KEY environment variable if None
+            iv: Initialization vector, automatically generated if None
+        """
+        if algorithm not in self.SUPPORTED_ALGORITHMS:
+            raise ValueError(f"Unsupported algorithm: {algorithm}")
+            
+        if not key:
+            raise ValueError("Encryption key not provided and RAGFLOW_CRYPTO_KEY environment variable not set")
+        
+        # Create cryptographic algorithm instance
+        self.algorithm_name = algorithm
+        self.crypto = self.SUPPORTED_ALGORITHMS[algorithm](key=key, iv=iv)
+    
+    def encrypt(self, data):
+        """
+        Encrypt data
+        
+        Args:
+            data: Data to encrypt (bytes)
+            
+        Returns:
+            Encrypted data (bytes)
+        """
+        # import time
+        # start_time = time.time()
+        encrypted = self.crypto.encrypt(data)
+        # end_time = time.time()
+        # logging.info(f"Encryption completed, data length: {len(data)} bytes, time: {(end_time - start_time)*1000:.2f} ms")
+        return encrypted
+    
+    def decrypt(self, encrypted_data):
+        """
+        Decrypt data
+        
+        Args:
+            encrypted_data: Encrypted data (bytes)
+            
+        Returns:
+            Decrypted data (bytes)
+        """
+        # import time
+        # start_time = time.time()
+        decrypted = self.crypto.decrypt(encrypted_data)
+        # end_time = time.time()
+        # logging.info(f"Decryption completed, data length: {len(encrypted_data)} bytes, time: {(end_time - start_time)*1000:.2f} ms")
+        return decrypted
+
+
+# Test code
+if __name__ == "__main__":
+    # Test AES encryption
+    crypto = CryptoUtil(algorithm="aes-256-cbc", key="test_key_123456")
+    test_data = b"Hello, RAGFlow! This is a test for encryption."
+    
+    encrypted = crypto.encrypt(test_data)
+    decrypted = crypto.decrypt(encrypted)
+    
+    print("AES Test:")
+    print(f"Original: {test_data}")
+    print(f"Encrypted: {encrypted}")
+    print(f"Decrypted: {decrypted}")
+    print(f"Success: {test_data == decrypted}")
+    print()
+    
+    # Test SM4 encryption
+    try:
+        crypto_sm4 = CryptoUtil(algorithm="sm4-cbc", key="test_key_123456")
+        encrypted_sm4 = crypto_sm4.encrypt(test_data)
+        decrypted_sm4 = crypto_sm4.decrypt(encrypted_sm4)
+        
+        print("SM4 Test:")
+        print(f"Original: {test_data}")
+        print(f"Encrypted: {encrypted_sm4}")
+        print(f"Decrypted: {decrypted_sm4}")
+        print(f"Success: {test_data == decrypted_sm4}")
+    except Exception as e:
+        print(f"SM4 Test Failed: {e}")
+        import traceback
+        traceback.print_exc()
+    
+    # Test with specific algorithm classes directly
+    print("\nDirect Algorithm Class Test:")
+    
+    # Test AES-128-CBC
+    aes128 = AES128CBC(key="test_key_123456")
+    encrypted_aes128 = aes128.encrypt(test_data)
+    decrypted_aes128 = aes128.decrypt(encrypted_aes128)
+    print(f"AES-128-CBC test: {'passed' if decrypted_aes128 == test_data else 'failed'}")
+    
+    # Test AES-256-CBC
+    aes256 = AES256CBC(key="test_key_123456")
+    encrypted_aes256 = aes256.encrypt(test_data)
+    decrypted_aes256 = aes256.decrypt(encrypted_aes256)
+    print(f"AES-256-CBC test: {'passed' if decrypted_aes256 == test_data else 'failed'}")
+    
+    # Test SM4-CBC
+    try:
+        sm4 = SM4CBC(key="test_key_123456")
+        encrypted_sm4 = sm4.encrypt(test_data)
+        decrypted_sm4 = sm4.decrypt(encrypted_sm4)
+        print(f"SM4-CBC test: {'passed' if decrypted_sm4 == test_data else 'failed'}")
+    except Exception as e:
+        print(f"SM4-CBC test failed: {e}")

common/data_source/__init__.py

@@ -1,6 +1,26 @@
 
 """
 Thanks to https://github.com/onyx-dot-app/onyx
+
+Content of this directory is under the "MIT Expat" license as defined below.
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
 """
 
 from .blob_connector import BlobStorageConnector