This project implements a Retrieval Augmented Generation (RAG) system using the AutoGen framework. The system leverages multiple agents capable of interacting with one another to execute tasks that require specific document knowledge, focusing on large unstructured textual data in medical education.
- Utilizes the latest AutoGen capabilities with the
retrievechat
feature package. - Implements OpenAI's powerful embedding functions.
- Integrates LangChain for optimal text splitting.
- Employs ChromaDB for efficient vector storage and retrieval.
Clone this repository:
git clone <repository-url>
cd AutoGenRAG
pip install -r requirements.txt