https://github.com/ramsunvtech/my-first-rag-with-openai
Retrieval-Augmented Generation (RAG) application built using OpenAI's API.
https://github.com/ramsunvtech/my-first-rag-with-openai
Last synced: 4 months ago
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Retrieval-Augmented Generation (RAG) application built using OpenAI's API.
- Host: GitHub
- URL: https://github.com/ramsunvtech/my-first-rag-with-openai
- Owner: ramsunvtech
- License: mit
- Created: 2024-12-06T18:04:41.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-12-06T18:08:15.000Z (over 1 year ago)
- Last Synced: 2025-08-06T15:44:59.790Z (11 months ago)
- Language: Python
- Size: 5.86 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# my-first-RAG-with-OpenAI
Retrieval-Augmented Generation (RAG) application built using OpenAI's API.
### FastAPI RAG Learning App with OpenAI Integration
This project implements a simple FastAPI application that answers questions based on a knowledge base stored in a text file. The app integrates with OpenAI's GPT-3.5 model to provide context-based answers using a RAG (Retrieval-Augmented Generation) approach.
## Features
- **FastAPI-based**: Provides an API to query and retrieve answers.
- **OpenAI Integration**: Uses OpenAI's API to generate responses based on a knowledge base.
- **Simple Knowledge Base**: Stores data in a plain text file for easy editing.
## Requirements
Before running the application, make sure you have the following dependencies installed:
- Python 3.7+
- FastAPI
- Uvicorn
- OpenAI Python SDK
You can install the necessary dependencies using pip:
```bash
pip install fastapi uvicorn openai