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| title: Rag | |
| emoji: 🚀 | |
| colorFrom: red | |
| colorTo: red | |
| sdk: docker | |
| app_port: 8501 | |
| tags: | |
| - streamlit | |
| pinned: false | |
| short_description: Streamlit template space | |
| Agentic PDF RAG System | |
| 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. | |
| Features | |
| PDF Upload and Ingestion: Upload multiple PDF files, extract text, and store embeddings in a ChromaDB vector store. | |
| Question Answering: Query the knowledge base with natural language questions and get answers powered by Google Gemini 2.5 Flash. | |
| Source Attribution: Optionally display source document snippets for answers. | |
| Query History: View past queries and export them as JSON or CSV. | |
| Knowledge Base Management: Clear the knowledge base and view statistics (e.g., number of documents and chunks). | |
| Prerequisites | |
| A Hugging Face account to deploy the application on Hugging Face Spaces. | |
| A Google Gemini API key for embeddings and language model inference. Obtain one from Google AI Studio. | |
| Python 3.8+ installed locally for testing (optional). | |
| Setup Instructions for Hugging Face Spaces | |
| 1. Create a New Hugging Face Space | |
| Log in to Hugging Face and navigate to Spaces. | |
| Click Create new Space. | |
| Choose a name for your Space (e.g., agentic-pdf-rag). | |
| Select Streamlit as the framework. | |
| Set visibility (e.g., Public or Private). | |
| Create the Space. | |
| 2. Clone or Upload the Repository | |
| Clone this repository or upload the following files to your Hugging Face Space: | |
| main.py: The main Streamlit application. | |
| rag_system.py: The RAG system implementation. | |
| pdf_processor.py: PDF text extraction and metadata creation. | |
| export_utils.py: Placeholder for export utilities. | |
| requirements.txt: Dependency list. | |
| README.md: This file (optional for documentation). | |
| Alternatively, fork this repository or upload files manually via the Hugging Face Spaces interface. | |
| 3. File Contents | |
| Ensure the following files are in the root directory of your Space: | |
| main.py | |
| The main Streamlit application (use the code from your first message). It provides the user interface for uploading PDFs, querying, and viewing history. | |
| rag_system.py | |
| The RAG system implementation (use the code from your second message). It handles document ingestion, embedding, and querying using Google Gemini and ChromaDB. | |
| pdf_processor.py |