README.md

metadata

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 — single entrypoint, serves both the API and the built React app.
• React — built to static files at image-build time, served by FastAPI.
• Embedded Qdrant — local path, no separate server. Rebuilt on each boot.
• SQLite — file-based, no Postgres server.
• Imaging models — loaded lazily on the T4 GPU on first request.
• LLM agents — call a hosted API; keys come from Space secrets.

Configuration

Set these under Settings → Variables & secrets:

• LLM_API_KEY — your hosted LLM provider key
• ELEVENLABS_API_KEY — 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.