This is an Express service written in TypeScript that provides authorization functionality and includes gen-AI features, using RAG concepts, vector database and implements AI memory history with Redis DB.

🌱 This project is under development.

• LangChain for handling LLM and RAG functionality.
• Express and Node for creating backend service.
• Qdrant as vector store database.
• JWT for handling authentication
• GoogleGenAI langchain plugin.
• Google Gemini - API
• Docker Containers for setting up environment.
• Redis database for storing AI messages.
• ZOD as body parameters validation.

common: common code and utilities for all modules
di: dependency injection container
modules: application features
  module_name:
    adapters: class adapters for external resources
      dataproviders:
      services:

    application: application layer for controllers and routes
      controllers:
      routes:

    core: application core logic
      entities:
      usecases:
      utils: class and constant utilities for this module

Before running the application, make sure you have the following installed:

• NodeJS (v20.12.1)
• PNPM (v9.7.0)
• Docker (v27.2.0)

1. Clone this repository

git clone https://github.com/WillACosta/genai-langchain-api

Copy the .env.example file to .env and fill it with your own credentials

cp .env.example .env

2. You'll need Docker to setup and running the application services

From the app's root directory, run the following command to build and running docker containers:

docker compose up --build

The application will be available at http://localhost:3000.