lang-agent/README_INSTALL.md

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:

   ./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:

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

configuring '.env' and 'frontend/.env'

ALI_API_KEY="API_KEY_FOR_ALI_QWEN"
ALI_BASE_URL="https://dashscope.aliyuncs.com/compatible-mode/v1"
POSTGRES_ROOT_PASSWORD="ROOT_PASSOWRD_FOR_DB_IN_CONN_STR - required for installation"
POSTGRES_PASSWORD="USER_PASSWORD_FOR_DB_CONN_STR - required for installation" - need to be same in POSTGRES_PASSWORD
CONN_STR="CONNECTION_STRING_TO_DATABASE" # DOCKER PASSWORD
FAST_AUTH_KEYS="API_KEY_FOR_OTHER_APPLICATIONS_TO_USE_BUILT_PIPELINE"
DAYTONA_API_KEY="DAYTONA_CONFIG - NOT REQUIRED"

Option 2: Pre-load Docker Images Offline

1. On a machine with good Docker Hub access, run:

   ./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:

   docker load < images.tar
   

4. Run the install script:

   ./scripts/shell_scripts/install.sh
   

Manual Installation

If you prefer to set up manually:

1. Create environment file:

   cp .env.example .env  # Edit as needed
   

2. Build and start services:

   cd docker
   docker compose -f docker-compose.prod.yml up -d --build
   

3. Check service status:

   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:

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:

cd docker
docker compose -f docker-compose.prod.yml down

Restart services:

cd docker
docker compose -f docker-compose.prod.yml restart

Rebuild after code changes:

cd docker
docker compose -f docker-compose.prod.yml up -d --build

Reset database (delete all data):

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:

   docker compose -f docker-compose.prod.yml ps postgres
   

2. Verify the connection string in .env matches the database configuration

3. Check backend logs:

   docker compose -f docker-compose.prod.yml logs backend
   

Frontend not loading / NetworkError

1. Check nginx logs:

   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:

# Example: use port 5433 for PostgreSQL
POSTGRES_PORT=5433

Development

For development, you may want to run services separately:

1. Start only PostgreSQL:

   cd docker
   docker compose -f docker-compose.prod.yml up -d postgres
   

2. Run backend locally:

   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:

   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