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| title: RAG Question Answering System | |
| emoji: 🤖 | |
| colorFrom: blue | |
| colorTo: purple | |
| sdk: docker | |
| pinned: false | |
| license: apache-2.0 | |
| # RAG Question Answering System | |
| This application allows users to upload documents (PDF or TXT) and ask questions about their content. It uses a Retrieval-Augmented Generation (RAG) approach to provide accurate answers based on the document content. | |
| ## Features | |
| - Upload PDF or TXT documents | |
| - Ask questions about the document content | |
| - View the context used to generate answers | |
| - Modern, responsive user interface | |
| ## How to Use | |
| 1. Upload a document (PDF or TXT) using the file upload interface | |
| 2. Wait for the document to be processed | |
| 3. Ask questions about the document content in the chat interface | |
| 4. View the answers and the context used to generate them | |
| ## Technical Details | |
| The application consists of two main components: | |
| 1. **FastAPI Backend**: Handles file uploads, document processing, and question answering | |
| 2. **React Frontend**: Provides a user-friendly interface for uploading documents and asking questions | |
| ## Environment Variables | |
| - `OPENAI_API_KEY`: Your OpenAI API key (required) | |
| ## License | |
| This project is licensed under the Apache 2.0 License. |