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---
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
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