Multi-Agent-Medical-Assistant
GenAI powered multi-agentic medical diagnostics and healthcare research assistance chatbot
GraphCanon updated 1mo · GitHub synced 1mo · 30 views this month
Decision brief
A chatbot designed to assist in medical diagnostics using generative AI technologies.
Good fit when
- When precise disease detection through genAI is needed for patient care
- For researchers requiring AI-powered insights into complex medical images
Avoid when
- If real-time interaction speed is critical due to potential latency in responses
- For tasks outside of its specialized healthcare and research focus areas
Observed Jul 12, 2026 · Source: enrich:decision_facts
Verify the decision
Maintenance and security
Full trust report- Maintenance
- Dormant (445d since push)
- As of 1mo
- Provenance
- Not a fork · Personal account
- As of 1mo
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install Multi-Agent-Medical-AssistantHow it fits your stack(6)
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Integrates
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Relationship graph
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Similar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
A chatbot designed to assist in medical diagnostics and healthcare research for professionals, researchers, and patients using generative AI technologies.
Capability facts
- Deploy
- Self-host
Source: dockerfile:Dockerfile · Jul 22, 2026
- Docker
- Dockerfile present
Source: dockerfile:Dockerfile · Jul 22, 2026
- Languages
- python
Source: github.language · Jul 22, 2026
Categories
Graph entities
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 22, 2026)
docker exec medical-assistant-app python ingest_rag_data.py --file ./data/raw/brain_tumors_ucni.pdfSource link
Tags
README
🚀 Installation & Setup
📌 Option 1: Using Docker
3️⃣ Build the Docker Image
docker build -t medical-assistant .
4️⃣ Run the Docker Container
docker run -d --name medical-assistant-app -p 8000:8000 --env-file .env medical-assistant
The application will be available at: http://localhost:8000
5️⃣ Ingest Data into Vector DB from Docker Container
- To ingest a single document:
docker exec medical-assistant-app python ingest_rag_data.py --file ./data/raw/brain_tumors_ucni.pdf
- To ingest multiple documents from a directory:
docker exec medical-assistant-app python ingest_rag_data.py --dir ./data/raw
📌 Option 2: Without Using Docker
3️⃣ Install Dependencies
[!IMPORTANT]
ffmpeg is required for speech service to work.
- If using conda:
conda install -c conda-forge ffmpeg
pip install -r requirements.txt
- If using python venv:
winget install ffmpeg
pip install -r requirements.txt
⚖️ License
This project is licensed under the Apache-2.0 License. See the LICENSE file for details.
For agents
This page has a .md twin and JSON over the API.