RAG PROJECT INTAKE

Developed a Retrieval-Augmented Generation (RAG) application using Streamlit and Hugging Face models. The project enables users to upload documents, convert text into embeddings, store them in a vector database, retrieve relevant information based on user queries, and generate accurate responses using an AI model. Implemented document processing, embedding generation, similarity search, and an interactive Streamlit user interface to improve information retrieval and question-answering capabilities.