<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> This Python project develops specialized LLM-based AI agents designed to analyze complex medical cases. It aims to integrate insights from various medical specialists, offering comprehensive assessments and personalized treatment recommendations, thereby demonstrating AI's potential in multidisciplinary medicine for research and educational purposes.

How It Works

The system employs three parallel AI agents, powered by GPT-5, each focusing on a distinct medical specialty: Cardiology, Psychology, and Pulmonology. A medical report is simultaneously fed to these agents via threading. Their individual findings are then aggregated and summarized to present up to three potential health issues, complete with supporting reasoning, showcasing a multidisciplinary AI diagnostic approach.

Quick Start & Requirements

• Installation: Clone the repository, create a Python virtual environment (e.g., python -m venv venv), activate it, and install dependencies using pip install -r requirements.txt.
• API Credentials: Configure your LLM provider API key by creating an apikey.env file in the project root with the format OPENAI_API_KEY=your_api_key_here.
• Execution: Run the main application script via python main.py.
• Prerequisites: Python 3.x environment, an API key for an LLM provider (e.g., OpenAI).
• Documentation: Links to official quick-start guides, comprehensive documentation, or live demos are not provided within the README.

Highlighted Details

• Employs specialized LLM agents for Cardiology, Psychology, and Pulmonology.
• Utilizes parallel processing (threading) for concurrent agent analysis of medical reports.
• Integrates multi-specialist insights into a unified diagnostic summary.

Maintenance & Community

No specific details regarding contributors, sponsorships, community channels (Discord, Slack), or roadmap are present in the provided README.

Licensing & Compatibility

Licensed under the MIT License, permitting broad use, modification, and distribution, including commercial applications. The software is provided "as is" without warranty.

Limitations & Caveats

This project is strictly for research and educational purposes and is not intended for clinical use. The current implementation relies on GPT-5, and future enhancements aim to support local LLMs and multimodal analysis.