Description

Welcome to the RAG (Retrieval-Augmented Generation) Repository as Personal-API, an AI project that leverages the OpenAI API for generating responses and integrates PostgreSQL for robust long-term data storage. With the addition of Qdrant for high-performance vector similarity search, this repository is designed to provide highly relevant and context-aware AI responses.

Features - OpenAI API Integration: Harness the power of GPT-4 for state-of-the-art natural language processing and text generation.

• PostgreSQL Database: Ensure reliable data persistence with a robust and scalable database solution for storing conversational contexts and metadata.
• Qdrant Vector Search: Implement efficient vector similarity searches to retrieve the most relevant data for AI responses.
• TypeScript: Benefit from strong typing and object-oriented programming for maintainable and scalable codebase.
• Langchain Library: Utilize this library to bridge language models with various applications, enhancing the capabilities of our RAG system.

Abilities

Skill	Name	State	Description
talk	Chat	Working	Ability to ask for knowledge
learn	Learn	In-progress	Ability to learn new skills
memory	Memories	Working	Ability to find to look over stored memories

Installation

copy env and add your own OPENAI key to have application be fully operational

$ cp .env.example .env

$ npm install

Running the app

# development
$ npm run start

# watch mode
$ npm run start:dev

# production mode
$ npm run start:prod

Test

# unit tests
$ npm run test

# e2e tests
$ npm run test:e2e

# test coverage
$ npm run test:cov

Databases

I'm using Qdrant as Vector Database and Postgres as storage for data. You can run it locally using Docker:

# Pull docker image and run it
docker pull qdrant/qdrant
docker run -p 6333:6333 -v $(pwd)/qdrant_storage:/qdrant/storage qdrant/qdrant

or

# Pull docker image and run it
docker pull postgres:latest
docker run -p 5433:5433 -v $(pwd)/postgres:/data/postgres postgres:latest

or just run all services locally via docker compose

# Pull all images locally and run it in docker compose network
docker compose up

Resources

• Prompts examples when working with dates