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---
title: Medical RAG with Meditron-7B-LLM
emoji: π
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
[](https://opensource.org/licenses/Apache-2.0)
[](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
## π 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()) |