This project integrates a Retrieval Augmented Generation (RAG) approach to build a sophisticated Question Answering (QA) Bot. It combines the capabilities of OpenAI's language models with ChromaDB for efficient data retrieval, offering insightful and contextually relevant answers to various queries.
The RAG QA Bot is designed to fetch pertinent information from a structured dataset using ChromaDB and then leverage the advanced language processing power of OpenAI's models to generate accurate and relevant answers. This project specifically demonstrates the bot's capabilities using a dataset related to the Bhagavad Gita.
- Python 3.6+
- Access to OpenAI API (API Key required)
- Clone the repository:
git clone <repository-url> cd <repository-directory>