更新 Dockerfile

Dockerfile

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+FROM python:3.11-slim
+
+# 设置 pip 全局使用国内源
+ENV PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple/
+ENV PIP_TRUSTED_HOST=pypi.tuna.tsinghua.edu.cn
+
+WORKDIR /app
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir --upgrade pip && \
+    pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 8000
+
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

README.md

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+# Unified LLM Gateway & Data Import Analysis Service
+
+This project exposes a FastAPI-based microservice that provides:
+
+- A unified chat completions gateway supporting multiple LLM providers (OpenAI, Anthropic, OpenRouter, Gemini, Qwen, DeepSeek, etc.)
+- An asynchronous data import analysis pipeline that orchestrates LLM calls to produce structured metadata and processing recommendations
+
+The following instructions cover environment setup, dependency installation, and running the backend service.
+
+## Prerequisites
+
+- Python 3.11 (recommended) or newer
+- Git
+- [uv](https://github.com/astral-sh/uv) package manager (used for Python dependency management)
+
+## Install uv
+
+```bash
+# Linux / macOS
+curl -LsSf https://astral.sh/uv/install.sh | sh
+
+# Windows (PowerShell)
+powershell -c "irm https://astral.sh/uv/install.ps1 | iex"
+```
+
+After installation, ensure `uv` is on your `PATH`:
+
+```bash
+uv --version
+```
+
+## Install Python Dependencies
+
+Create (or activate) a virtual environment, then install project dependencies with `uv`:
+
+```bash
+# Create a virtualenv named .venv if it doesn't exist
+uv venv .venv
+
+# Activate the virtualenv (Linux/macOS)
+source .venv/bin/activate
+
+# On Windows PowerShell:
+# .\.venv\Scripts\Activate.ps1
+
+# Install dependencies from requirements.txt
+uv pip install -r requirements.txt
+```
+
+If you prefer native `pip`, replace the last command with `pip install -r requirements.txt`.
+
+## Environment Variables
+
+Copy `.env.example` to `.env` (if provided) or edit `.env` to supply API keys and configuration values:
+
+- `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, `OPENROUTER_API_KEY`, etc.
+- `HTTP_CLIENT_TIMEOUT`, `IMPORT_CHAT_TIMEOUT_SECONDS`
+- `LOG_LEVEL`, `LOG_FORMAT` for logging
+
+
+## Run the Backend Service
+
+Start the FastAPI application using uvicorn:
+
+```bash
+uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
+```
+
+- `--reload` enables auto-restart during development.
+- Access the interactive API docs at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs).
+
+To keep it running in the background (Unix-like systems):
+
+```bash
+nohup uvicorn app.main:app --host 0.0.0.0 --port 8000 > server.log 2>&1 &
+```
+
+Or use a process manager such as `pm2`, `supervisor`, or systemd for production deployments.
+
+## API List
+1. 导入分析schema接口 http://localhost:8000/v1/import/analyze
+
+## Additional Commands
+
+- Run the data import analysis example: `python test/data_import_analysis_example.py`
+- Test the OpenRouter demo: `python test/openrouter_chat_example.py`
+- Send a DeepSeek chat request script: `python scripts/deepseek_request.py`

docker-compose.yml

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+services:
+  app:
+    build: .
+    ports:
+      - "8060:8000"
+    volumes:
+      - .:/app
+    environment:
+      - PYTHONUNBUFFERED=1
+    # 开发模式：启用 --reload
+    command: uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
+    # 生产模式：注释上面 command，取消注释下面这行
+    # command: uvicorn app.main:app --host 0.0.0.0 --port 8000 --workers 4