QueryCraft-API

This repository contains an API that leverages a Large Language Model (LLM) to provide relevant answers to user queries based on text data stored in a vector database.

Setup

1. Create a virtual environment: python -m venv venv
2. Activate the virtual environment: source venv/bin/activate (Linux/Mac) or venv\Scripts\activate (Windows)
3. Install dependencies: pip install -r requirements.txt
4. Load your environment variables: cp .env.example .env (Linux/Mac) or copy .env.example .env (Windows)

Usage

1. Fill in the required API keys in the code.
2. Add your txt file in '/Data' folder.
3. Run the FastAPI application: uvicorn main:app --reload
4. Visit http://127.0.0.1:8000/docs in your browser to interact with the API using Swagger documentation.

Environment Variables

Create a .env file and add the following:

PINECONE_API_KEY=your_pinecone_api_key
OPENAI_API_KEY=your_openai_api_key