RAG-based Chatbot using Gemini API and DSPy

This project implements a Retrieval-Augmented Generation (RAG) chatbot that utilizes the Gemini API for natural language processing tasks. The chatbot is designed to answer questions based on the HotPotQA dataset, leveraging both retrieval and generative capabilities.

Features

• Retrieval-Augmented Generation: Combines retrieval of relevant context with generative responses.
• Custom Gemini Model Integration: Utilizes the Gemini API for generating answers.
• Local Dataset Handling: Downloads and caches the HotPotQA dataset locally for efficient access.
• Multi-hop Querying: Supports complex queries through a multi-hop retrieval mechanism.

Requirements

• Python 3.11 or higher
• dspy library
• google-generativeai library
• datasets library
• Other dependencies are managed via requirements.txt.

Installation

1. Clone this repository:

   https://github.com/Sagor0078/building-RAG-using-DSPy-and-Gemini-API.git

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