Update README.md

README.md

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 short_description: Streamlit template space
 ---
 
-# Welcome to Streamlit!
+Agentic PDF RAG System
 
-Edit `/src/streamlit_app.py` to customize this app to your heart's desire. :heart:
+This is a Streamlit-based Retrieval-Augmented Generation (RAG) system that allows users to upload PDF documents, build a knowledge base, and ask questions to retrieve AI-powered answers using Google Gemini and ChromaDB. The system supports document ingestion, querying with source references, and exporting query history as JSON or CSV.
 
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
+Features
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+PDF Upload and Ingestion: Upload multiple PDF files, extract text, and store embeddings in a ChromaDB vector store.
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+Question Answering: Query the knowledge base with natural language questions and get answers powered by Google Gemini 2.5 Flash.
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+Source Attribution: Optionally display source document snippets for answers.
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+Query History: View past queries and export them as JSON or CSV.
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+Knowledge Base Management: Clear the knowledge base and view statistics (e.g., number of documents and chunks).
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+Prerequisites
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+A Hugging Face account to deploy the application on Hugging Face Spaces.
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+A Google Gemini API key for embeddings and language model inference. Obtain one from Google AI Studio.
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+Python 3.8+ installed locally for testing (optional).
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+Setup Instructions for Hugging Face Spaces
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+1. Create a New Hugging Face Space
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+Log in to Hugging Face and navigate to Spaces.
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+Click Create new Space.
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+Choose a name for your Space (e.g., agentic-pdf-rag).
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+Select Streamlit as the framework.
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+Set visibility (e.g., Public or Private).
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+Create the Space.
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+2. Clone or Upload the Repository
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+Clone this repository or upload the following files to your Hugging Face Space:
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+main.py: The main Streamlit application.
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+rag_system.py: The RAG system implementation.
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+pdf_processor.py: PDF text extraction and metadata creation.
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+export_utils.py: Placeholder for export utilities.
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+requirements.txt: Dependency list.
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+README.md: This file (optional for documentation).
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+Alternatively, fork this repository or upload files manually via the Hugging Face Spaces interface.
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+3. File Contents
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+Ensure the following files are in the root directory of your Space:
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+main.py
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+The main Streamlit application (use the code from your first message). It provides the user interface for uploading PDFs, querying, and viewing history.
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+rag_system.py
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+The RAG system implementation (use the code from your second message). It handles document ingestion, embedding, and querying using Google Gemini and ChromaDB.
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+pdf_processor.py