Spaces:
Sleeping
Sleeping
| title: RAG | |
| emoji: 🔍 | |
| colorFrom: yellow | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 5.30.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: Retrieval-Augmented Generation (RAG) | |
| models: | |
| - bert-base-uncased | |
| - google/flan-t5-base | |
| # 📄🔍 Retrieval-Augmented Generation (RAG) Demo | |
| A simple yet powerful RAG application that lets you upload documents and ask questions about them. | |
| ## Features | |
| - 📄 Upload multiple .txt files | |
| - 🔍 Automatic document processing and indexing | |
| - 💡 Query your documents using natural language | |
| - 🤖 Get AI-generated answers based on your content | |
| ## How It Works | |
| 1. **Upload** - Add your text files to the system | |
| 2. **Index** - Documents are embedded using `bert-base-uncased` | |
| 3. **Query** - Ask a question about the documents | |
| 4. **Retrieve** - The system finds the most relevant content using cosine similarity | |
| 5. **Generate** - `flan-t5-base` creates a natural language answer | |
| ## Technical Details | |
| - Built with Hugging Face's Transformers | |
| - Uses cosine similarity for matching | |
| - No GPU required (ZeroGPU compatible) | |
| - Runs completely in-memory | |
| ## Usage | |
| Simply upload your text files, ask a question, and get an answer within seconds! | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |