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---
title: Multi-Agent Medical Assistant
emoji: 🩺
colorFrom: blue
colorTo: indigo
sdk: docker
app_port: 7860
suggested_hardware: t4-small
short_description: Multi-agent clinical assistant with RAG and imaging analysis
---
# Multi-Agent Medical Assistant
Multi-agent clinical assistant: diagnosis, retrieval, reasoning, and imaging
agents behind a FastAPI backend with a React frontend, deployed as a single
Docker Space.
## Architecture on Spaces
Everything runs in one container on port 7860:
- **FastAPI** β€” single entrypoint, serves both the API and the built React app.
- **React** β€” built to static files at image-build time, served by FastAPI.
- **Embedded Qdrant** β€” local path, no separate server. Rebuilt on each boot.
- **SQLite** β€” file-based, no Postgres server.
- **Imaging models** β€” loaded lazily on the T4 GPU on first request.
- **LLM agents** β€” call a hosted API; keys come from Space secrets.
## Configuration
Set these under **Settings β†’ Variables & secrets**:
- `LLM_API_KEY` β€” your hosted LLM provider key
- `ELEVENLABS_API_KEY` β€” for voice output (optional)
## Notes
- Free tier disk is ephemeral: the vector store is rebuilt from seed docs on
every restart. User uploads do not persist across restarts.
- Requires a paid GPU tier (t4-small) for imaging inference. Pause the Space
when not in use to control cost.