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README.md
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这是一个基于FastAPI的聊天API服务，使用OpenAI格式的请求来调用pipeline.invoke方法进行聊天。 这是一个基于FastAPI的聊天API服务，使用OpenAI格式的请求来调用pipeline.invoke方法进行聊天。
## Docker Installation
For production deployment using Docker, see the [Installation Guide](README_INSTALL.md).
## 安装依赖 ## 安装依赖
```bash ```bash
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### Start the `front_apis` server ### Start the `front_apis` server
The frontend talks to the `front_apis` FastAPI service, which by default listens on `http://127.0.0.1:8001`. The frontend talks to the `front_apis` FastAPI service, which by default listens on `http://127.0.0.1:8500`.
From the project root: From the project root:
```bash ```bash
uvicorn fastapi_server.front_apis:app --reload --host 0.0.0.0 --port 8001 uvicorn fastapi_server.front_apis:app --reload --host 0.0.0.0 --port 8500
``` ```
You can change the URL by setting `VITE_FRONT_API_BASE_URL` in `frontend/.env` (defaults to `http://127.0.0.1:8001`). Or run directly:
```bash
python fastapi_server/front_apis.py
```
### Backend run modes
Run whichever backend mode you need from the project root:
```bash
# admin/control plane only (/v1/... frontend APIs)
uvicorn fastapi_server.front_apis:app --reload --host 0.0.0.0 --port 8500
# DashScope chat runtime only (/apps/... and /v1/apps/... APIs)
uvicorn fastapi_server.server_dashscope:app --reload --host 0.0.0.0 --port 8588
# combined mode: one process serves both front_apis + DashScope endpoints
uvicorn fastapi_server.combined:app --reload --host 0.0.0.0 --port 8500
```
You can change the URL by setting `VITE_FRONT_API_BASE_URL` in `frontend/.env` (defaults to `http://127.0.0.1:8500`).
### Start the development server ### Start the development server

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# Installation Guide
This guide explains how to install and run the LangChain Agent application using Docker.
## Prerequisites
- Docker (version 20.10 or later)
- Docker Compose (version 2.0 or later, or use `docker compose` command)
## Quick Start
1. **Run the installation script:**
```bash
./scripts/shell_scripts/install.sh
```
This script will:
- Check for required tools (Docker, docker-compose)
- Create a `.env` file with default configuration
- Build Docker images (or use pre-loaded images)
- Start all services (PostgreSQL, Backend API, Nginx)
2. **Access the application:**
- Frontend: http://localhost (or http://localhost:80)
- Backend API: http://localhost:8500
- Database: localhost:5432
## Installation for China / Offline Use
If Docker Hub is slow or inaccessible in your region:
### Option 1: Use Chinese Docker Mirrors
Configure Docker to use Chinese registry mirrors:
```bash
sudo tee /etc/docker/daemon.json <<EOF
{
"registry-mirrors": [
"https://registry.docker-cn.com",
"https://mirror.ccsogou.com",
"https://docker.1ms.run"
]
}
EOF
sudo systemctl daemon-reload
sudo systemctl restart docker
```
Then run `./scripts/shell_scripts/install.sh`
### Option 2: Pre-load Docker Images Offline
1. On a machine with good Docker Hub access, run:
```bash
./scripts/shell_scripts/download_images.sh
```
This creates `images.tar` with all required images.
2. Transfer `images.tar` to your target machine.
3. Load the images:
```bash
docker load < images.tar
```
4. Run the install script:
```bash
./scripts/shell_scripts/install.sh
```
## Manual Installation
If you prefer to set up manually:
1. **Create environment file:**
```bash
cp .env.example .env # Edit as needed
```
2. **Build and start services:**
```bash
cd docker
docker compose -f docker-compose.prod.yml up -d --build
```
3. **Check service status:**
```bash
cd docker
docker compose -f docker-compose.prod.yml ps
```
## Configuration
Edit the `.env` file to customize:
- `POSTGRES_DB`: Database name (default: `ai_conversations`)
- `POSTGRES_USER`: Database user (default: `myapp_user`)
- `POSTGRES_PASSWORD`: Database password (default: `secure_password_123`)
- `POSTGRES_PORT`: PostgreSQL port (default: `5432`)
- `BACKEND_PORT`: Backend API port (default: `8500`)
- `FRONTEND_PORT`: Frontend web server port (default: `80`)
## Database Initialization
The database is automatically initialized when the PostgreSQL container starts for the first time. The following SQL scripts are executed in order:
1. `scripts/init_database/00_init_user.sh` - Creates database user and database
2. `scripts/init_database/create_conv_store.sql` - Creates conversation storage tables
3. `scripts/init_database/create_prompt_config.sql` - Creates prompt configuration tables
## Service Management
All commands run from the `docker/` directory:
### View logs:
```bash
cd docker
docker compose -f docker-compose.prod.yml logs -f
# Specific service
docker compose -f docker-compose.prod.yml logs -f backend
docker compose -f docker-compose.prod.yml logs -f postgres
docker compose -f docker-compose.prod.yml logs -f nginx
```
### Stop services:
```bash
cd docker
docker compose -f docker-compose.prod.yml down
```
### Restart services:
```bash
cd docker
docker compose -f docker-compose.prod.yml restart
```
### Rebuild after code changes:
```bash
cd docker
docker compose -f docker-compose.prod.yml up -d --build
```
### Reset database (delete all data):
```bash
cd docker
docker compose -f docker-compose.prod.yml down -v
docker compose -f docker-compose.prod.yml up -d
```
## Architecture
The application consists of three main services:
1. **PostgreSQL** (`postgres`): Database server
- Stores conversations and prompt configurations
- Automatically initializes schema on first run
2. **Backend** (`backend`): FastAPI application
- Serves API endpoints at port 8500
- Handles agent management and chat endpoints
- Connects to PostgreSQL database
3. **Nginx** (`nginx`): Web server
- Serves the React frontend (port 80)
- Proxies API requests to the backend
- Handles static file serving
## Project Structure
```
langchain-agent/
├── docker/
│ ├── docker-compose.prod.yml # Production compose file
│ └── Dockerfile.prod # Backend Docker image
├── scripts/
│ ├── shell_scripts/
│ │ ├── install.sh # Main installation script
│ │ └── download_images.sh # For offline image download
│ └── init_database/ # Database initialization scripts
├── frontend/ # React frontend
├── configs/ # Pipeline configurations
├── nginx.conf # Nginx configuration
└── .env # Environment variables
```
## Troubleshooting
### Database connection issues
If the backend can't connect to the database:
1. Check that PostgreSQL is running:
```bash
docker compose -f docker-compose.prod.yml ps postgres
```
2. Verify the connection string in `.env` matches the database configuration
3. Check backend logs:
```bash
docker compose -f docker-compose.prod.yml logs backend
```
### Frontend not loading / NetworkError
1. Check nginx logs:
```bash
docker compose -f docker-compose.prod.yml logs nginx
```
2. Ensure frontend is built with correct API base URL. The `frontend/.env` file should contain:
```
VITE_FRONT_API_BASE_URL=/
```
Then rebuild: `docker compose -f docker-compose.prod.yml build backend`
### Port conflicts
If ports are already in use, update the port mappings in `.env`:
```bash
# Example: use port 5433 for PostgreSQL
POSTGRES_PORT=5433
```
## Development
For development, you may want to run services separately:
1. Start only PostgreSQL:
```bash
cd docker
docker compose -f docker-compose.prod.yml up -d postgres
```
2. Run backend locally:
```bash
export CONN_STR="postgresql://myapp_user:secure_password_123@localhost:5432/ai_conversations"
python -m uvicorn lang_agent.fastapi_server.combined:app --reload --host 0.0.0.0 --port 8500
```
3. Run frontend locally:
```bash
cd frontend
npm install
npm run dev
```
Note: For local frontend development, create a `.env` file in `frontend/` with:
```
VITE_FRONT_API_BASE_URL=http://localhost:8500
```