📂 RAG Q&A with Gemini (Streamlit + LangChain + Chroma)

A Retrieval-Augmented Generation (RAG) application built with Streamlit, LangChain, Google Gemini 1.5 Flash, and Chroma as the vector store.
This app lets you upload documents (PDF, DOCX, TXT) and ask natural-language questions, with answers generated by Gemini grounded in your file contents.

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✨ Features

• 📑 Upload and process .pdf, .docx, .txt files
• 🔍 Text chunking with RecursiveCharacterTextSplitter
• 🧠 Embedding generation via GoogleGenerativeAIEmbeddings
• 📦 Persistent vector store with ChromaDB
• 🤖 Q&A powered by RetrievalQA + Gemini 1.5 Flash
• ⚡ Streamlit UI for interactive querying
• 📎 Displays both the answer and the source snippets