LangConnect

LangConnect is a RAG (Retrieval-Augmented Generation) service built with FastAPI and LangChain. It provides a REST API for managing collections and documents, with PostgreSQL and pgvector for vector storage.

Features

• FastAPI-based REST API
• PostgreSQL with pgvector for document storage and vector embeddings
• Docker support for easy deployment

Getting Started

Prerequisites

• Docker and Docker Compose
• Python 3.11 or higher

Running with Docker

1. Clone the repository:

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

2. Start the services:

   docker-compose up -d
   

   This will:

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

3. Access the API:

   • API documentation: http://localhost:8080/docs
   • Health check: http://localhost:8080/health

Development

To run the services in development mode with live reload:

docker-compose up

API Documentation

The API documentation is available at http://localhost:8080/docs when the service is running.

Environment Variables

The following environment variables can be configured in the docker-compose.yml file:

Variable	Description	Default
POSTGRES_HOST	PostgreSQL host	postgres
POSTGRES_PORT	PostgreSQL port	5432
POSTGRES_USER	PostgreSQL username	postgres
POSTGRES_PASSWORD	PostgreSQL password	postgres
POSTGRES_DB	PostgreSQL database name	postgres

License

This project is licensed under the terms of the license included in the repository.

Endpoints

Collections

/collections (GET)

List all collections.

/collections (POST)

Create a new collection.

/collections/{collection_id} (GET)

Get a specific collection by ID.

/collections/{collection_id} (DELETE)

Delete a specific collection by ID.

Documents

/collections/{collection_id}/documents (GET)

List all documents in a specific collection.

/collections/{collection_id}/documents (POST)

Create a new document in a specific collection.

/collections/{collection_id}/documents/{document_id} (DELETE)

Delete a specific document by ID.

/collections/{collection_id}/documents/search (POST)

Search for documents using semantic search.