AI Coding Agent - LangChain with SQLite Checkpoint

A LangChain-based AI coding assistant with SQLite persistent conversation history. This example demonstrates how to use LangChain agents with AG-Kit tools and SQLite checkpoint for conversation persistence.

Features

- 🤖 LangChain Integration - Built on LangChain with AG-Kit tool conversion
- 💾 SQLite Persistence - Conversation history stored in SQLite database
- 🔧 AG-Kit Tools - Full access to AG-Kit's React coding tools
- 📝 Interactive CLI - Simple command-line interface for testing
- 🔄 Memory Management - Persistent conversation state across sessions

Prerequisites

- Node.js 18+
- OpenAI API key

Quick Start

1. Install and run:
``bash
npm install
npm run interactive
`

Environment Variables

Create a .env file with:

`bash


OpenAI Configuration


OPENAI_API_KEY=your_openai_api_key
OPENAI_MODEL=gpt-4o-mini
OPENAI_BASE_URL=https://api.openai.com/v1
`

Usage

$3

Start the interactive CLI:

`bash
npm run interactive
`

Example conversation:
`
💬 You: Create a React component for a todo list

🤖 Assistant:
I'll help you create a React todo list component. Let me create a new component file...

💬 You: Add TypeScript support to this component

🤖 Assistant:
I'll convert the component to TypeScript with proper type definitions...
`

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`typescript
import { createAgent } from '@cloudbase/agent-examples-langchain-ai-coding';

const agent = createAgent({
baseProjectPath: '/path/to/projects',
projectName: 'my-react-app',
autoInstallDependencies: true,
});

const response = await agent.invoke({
messages: [{ role: 'user', content: 'Create a React component' }]
});

console.log(response.content);
`

Architecture

This example demonstrates:

1. LangChain Agent Creation - Using the existing agent.ts implementation
2. AG-Kit Tool Integration - Converting AG-Kit tools to LangChain format
3. SQLite Checkpoint - Persistent conversation storage using LangChain's SQLite checkpoint
4. Interactive CLI - Simple readline-based interface for testing

`
┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐
│ User Input │───▶│ LangChain Agent │───▶│ AG-Kit Tools │
└─────────────────┘ └──────────────────┘ └─────────────────┘
│ │
▼ ▼
┌──────────────────┐ ┌─────────────────┐
│ SQLite Checkpoint│ │ React Coding │
└──────────────────┘ └─────────────────┘
`

Project Structure

`
src/
├── agent.ts # LangChain agent implementation
└── index.ts # Main exports

examples/
└── full-workflow.ts # Interactive CLI example
`

Available Commands

- npm run build - Build the project
- npm run interactive - Start interactive CLI

Troubleshooting

$3

- Verify your API key is correct
- Check you have sufficient credits
- Ensure the model name is supported

$3

The SQLite database (checkpoints.db`) will be created automatically in the project directory when you first run the agent.

Contributing

This example is part of the AG-Kit project. Please refer to the main project's contributing guidelines.

License

MIT License - see the main AG-Kit project for details.