The RAG_ChatBot provides responses based on data extracted from documents related to risk factors in financial trade. It uses Retrieval-Augmented Generation (RAG) to enhance responses with relevant information from the provided documents.
Features:
* Data-Driven Responses: Answers based on data extracted from provided documents.
* Retrieval-Augmented Generation: Combines information retrieval with generation for accurate and relevant responses.
* Interactive Interface: Built with Streamlit for a user-friendly experience.
Demonstration:
The RAG-chatbot is thinking
Negative prompt (test out of context request)
Response based on knoweldge in documents
Note: This project is for a client who contacted me on LinkedIn.
