Merge remote-tracking branch 'origin/main'

# Conflicts:
#	frontend/components.d.ts

Author: ziyujiahao

.dockerignore

@@ -0,0 +1,12 @@
+# Python
+backend/__pycache__
+backend/app.egg-info
+backend/*.pyc
+backend/.mypy_cache
+backend/.coverage
+backend/htmlcov
+backend/.venv
+backend/.gitignore
+backend/README.md
+backend/scripts
+backend/.DS_Store

.github/workflows/build_docker.yml

@@ -48,7 +48,7 @@ jobs:
     - name: Build and push Docker image
       uses: docker/build-push-action@v4
       with:
-        context: ./backend
+        context: .
         push: true
         tags: |
           ${{ secrets.DOCKERHUB_REGISTRY }}/dataease-v2/sqlbot:latest

.gitignore

@@ -184,4 +184,6 @@ cython_debug/
 .pypirc
 
 .DS_Store
-test.py
+test.py
+
+

Dockerfile

@@ -0,0 +1,63 @@
+# Build stage
+FROM registry.cn-qingdao.aliyuncs.com/dataease/python:3.11-slim-bookworm AS builder
+
+# Set build environment variables
+ENV PYTHONUNBUFFERED=1
+ENV SQLBOT_HOME=/opt/sqlbot
+ENV APP_HOME=${SQLBOT_HOME}/app
+ENV UI_HOME=${SQLBOT_HOME}/frontend
+ENV PYTHONPATH=${SQLBOT_HOME}/app
+ENV PATH="${APP_HOME}/.venv/bin:$PATH"
+ENV UV_COMPILE_BYTECODE=1
+ENV UV_LINK_MODE=copy
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Create necessary directories
+RUN mkdir -p ${APP_HOME} ${UI_HOME}
+
+WORKDIR ${APP_HOME}
+
+# Install uv tool
+COPY --from=ghcr.io/astral-sh/uv:0.7.8 /uv /uvx /bin/
+
+# COPY ../frontend/dist /opt/sqlbot/frontend/dist
+COPY frontend/dist ${UI_HOME}/dist
+
+# Install dependencies
+RUN test -f "./uv.lock" && \
+    --mount=type=cache,target=/root/.cache/uv \
+    --mount=type=bind,source=backend/uv.lock,target=uv.lock \
+    --mount=type=bind,source=backend/pyproject.toml,target=pyproject.toml \
+    uv sync --frozen --no-install-project || echo "uv.lock file not found, skipping intermediate-layers"
+
+COPY ./backend ${APP_HOME}
+
+# Final sync to ensure all dependencies are installed
+RUN --mount=type=cache,target=/root/.cache/uv \
+   uv sync
+
+# Runtime stage
+FROM registry.cn-qingdao.aliyuncs.com/dataease/python:3.11-slim-bookworm
+
+# Set runtime environment variables
+ENV PYTHONUNBUFFERED=1
+ENV SQLBOT_HOME=/opt/sqlbot
+ENV PYTHONPATH=${SQLBOT_HOME}/app
+ENV PATH="${SQLBOT_HOME}/app/.venv/bin:$PATH"
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    curl \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy necessary files from builder
+COPY --from=builder ${SQLBOT_HOME} ${SQLBOT_HOME}
+
+WORKDIR ${SQLBOT_HOME}/app
+
+# Add health check
+HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
+    CMD curl -f http://localhost:8000 || exit 1
+
+# Run with uvicorn
+CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "4", "--proxy-headers"]

backend/.dockerignore

@@ -0,0 +1,64 @@
+"""009_modify_chat
+
+Revision ID: 1f077c30e476
+Revises: 35d925df4568
+Create Date: 2025-05-30 16:11:08.020715
+
+"""
+from alembic import op
+import sqlalchemy as sa
+import sqlmodel.sql.sqltypes
+from sqlalchemy.dialects import postgresql
+
+# revision identifiers, used by Alembic.
+revision = '1f077c30e476'
+down_revision = '35d925df4568'
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table('chat_record')
+    op.create_table('chat_record',
+    sa.Column('id', sa.Integer(), sa.Identity(always=True), nullable=False),
+    sa.Column('chat_id', sa.Integer(), nullable=True),
+    sa.Column('create_time', sa.DateTime(timezone=True), nullable=True),
+    sa.Column('finish_time', sa.DateTime(timezone=True), nullable=True),
+    sa.Column('create_by', sa.BigInteger(), nullable=True),
+    sa.Column('datasource', sa.Integer(), nullable=False),
+    sa.Column('engine_type', sqlmodel.sql.sqltypes.AutoString(length=64), nullable=False),
+    sa.Column('question', sa.Text(), nullable=True),
+    sa.Column('sql_answer', sa.Text(), nullable=True),
+    sa.Column('sql', sa.Text(), nullable=True),
+    sa.Column('sql_exec_result', sa.Text(), nullable=True),
+    sa.Column('data', sa.Text(), nullable=True),
+    sa.Column('chart_answer', sa.Text(), nullable=True),
+    sa.Column('chart', sa.Text(), nullable=True),
+    sa.Column('full_sql_message', sa.Text(), nullable=True),
+    sa.Column('full_chart_message', sa.Text(), nullable=True),
+    sa.Column('finish', sa.Boolean(), nullable=True),
+    sa.Column('error', sa.Text(), nullable=True),
+    sa.Column('run_time', sa.Float(), nullable=False),
+    sa.PrimaryKeyConstraint('id')
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade():
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table('chat_record')
+    op.create_table('chat_record',
+    sa.Column('id', sa.Integer(), sa.Identity(always=True), nullable=False),
+    sa.Column('chat_id', sa.Integer(), nullable=True),
+    sa.Column('create_time', sa.DateTime(timezone=True), nullable=True),
+    sa.Column('create_by', sa.BigInteger(), nullable=True),
+    sa.Column('datasource', sa.Integer(), nullable=False),
+    sa.Column('engine_type', sqlmodel.sql.sqltypes.AutoString(length=64), nullable=False),
+    sa.Column('question', sa.Text(), nullable=True),
+    sa.Column('full_question', sa.Text(), nullable=True),
+    sa.Column('answer', sa.Text(), nullable=True),
+    sa.Column('run_time', sa.Float(), nullable=False),
+    sa.PrimaryKeyConstraint('id')
+                    )
+    # ### end Alembic commands ###

backend/Dockerfile

@@ -0,0 +1 @@
+# todo

backend/alembic/versions/1f077c30e476_009_modify_chat.py

@@ -3,6 +3,10 @@
 from abc import ABC, abstractmethod
 from langchain_core.language_models import BaseLLM as LangchainBaseLLM
 from langchain_openai import ChatOpenAI
+
+from apps.system.models.system_model import AiModelDetail
+
+
 # from langchain_community.llms import Tongyi, VLLM
 
 class LLMConfig(BaseModel):
@@ -84,4 +88,16 @@ def create_llm(cls, config: LLMConfig) -> BaseLLM:
     @classmethod
     def register_llm(cls, model_type: str, llm_class: Type[BaseLLM]):
         """Register new model type"""
-        cls._llm_types[model_type] = llm_class
+        cls._llm_types[model_type] = llm_class
+
+
+#  todo
+def get_llm_config(aimodel: AiModelDetail) -> LLMConfig:
+    config = LLMConfig(
+        model_type="openai",
+        model_name=aimodel.name,
+        api_key=aimodel.api_key,
+        api_base_url=aimodel.endpoint,
+        additional_params={"temperature": aimodel.temperature}
+    )
+    return config