Introduction to LangConnect

LangConnect is an innovative Retrieval-Augmented Generation (RAG) service that leverages the capabilities of FastAPI and LangChain. This project aims to streamline the management of collections and documents through a robust REST API, utilizing PostgreSQL and pgvector for efficient vector storage.

Key Features of LangConnect

• FastAPI-based REST API: Provides a high-performance interface for document management.
• PostgreSQL with pgvector: Ensures efficient document storage and vector embeddings.
• Docker Support: Simplifies deployment and management of services.

Technical Architecture and Implementation

LangConnect is built on a solid architecture that integrates FastAPI for the API layer and PostgreSQL for data storage. The use of pgvector allows for advanced vector operations, making it suitable for applications requiring semantic search capabilities.

Getting Started with LangConnect

To begin using LangConnect, follow these simple steps:

Prerequisites

• Docker and Docker Compose
• Python 3.11 or higher

Installation Steps

git clone https://github.com/langchain-ai/langconnect.git
cd langconnect

Next, start the services using Docker:

docker-compose up -d

This command will:

• Start a PostgreSQL database with the pgvector extension.
• Build and start the LangConnect API service.

Once the services are running, you can access the API documentation at http://localhost:8080/docs and perform a health check at http://localhost:8080/health.

Using LangConnect: API Overview

LangConnect provides a variety of endpoints for managing collections and documents:

Collections Endpoints

• GET /collections: List all collections.
• POST /collections: Create a new collection.
• GET /collections/{collection_id}: Retrieve a specific collection by ID.
• DELETE /collections/{collection_id}: Delete a specific collection by ID.

Documents Endpoints

• GET /collections/{collection_id}/documents: List all documents in a specific collection.
• POST /collections/{collection_id}/documents: Create a new document in a specific collection.
• DELETE /collections/{collection_id}/documents/{document_id}: Delete a specific document by ID.
• POST /collections/{collection_id}/documents/search: Search for documents using semantic search.

Community and Contribution

LangConnect is an open-source project, and contributions are welcome! Developers can participate by submitting issues, feature requests, or pull requests. Engaging with the community helps improve the project and fosters collaboration.

License and Legal Considerations

LangConnect is licensed under the MIT License, allowing for free use, modification, and distribution. However, it is essential to include the original copyright notice and license in all copies or substantial portions of the software.

Conclusion

LangConnect is a powerful tool for developers looking to implement RAG services efficiently. With its robust architecture, easy setup, and comprehensive API, it stands out as a valuable resource in the open-source community.

For more information, visit the official repository: LangConnect on GitHub.

Frequently Asked Questions (FAQ)