---
title: Medical RAG with Meditron-7B-LLM
emoji: 📚
colorFrom: blue
colorTo: indigo
sdk: docker
sdk_version: 20.10.17
app_file: app.py
pinned: false
license: apache-2.0
short_description: A specialized AI assistant for medical information retrieval
---

# Medical RAG QA System

A Retrieval-Augmented Generation (RAG) system for medical question answering using:
- Meditron-7B LLM
- Qdrant Vector Database
- PubMedBERT Embeddings

[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![Model Card](https://img.shields.io/badge/🤗%20Model-MedITRON--7B--GGUF-blue)](https://huggingface.co/joshnader/meditron-7b-Q4_K_M-GGUF)

## Features
- PDF document ingestion
- Semantic search with medical embeddings
- LLM-powered question answering
- Source document citation

## 🚀 Usage

1. **Query Interface**:
```python
import requests

response = requests.post("https://d221/Qdrant_Backend.hf.space/get_response", 
                         data={"query": "What are the symptoms of diabetes?"})
print(response.json())