Ayurveda GraphRAG Clinical Orchestrator

This system provides evidence-based clinical reasoning by integrating classical Ayurvedic knowledge (GRAYU) with modern medical ontologies (BODHI) using a Knowledge Graph.

Core Components

• Clinical Agent: Orchestrates diagnostic workflows using LLM-powered tools.
• Similarity Engine: Aligns Ayurvedic and medical concepts across different domains.
• Knowledge Graph: Unified Neo4j instance containing GRAYU and BODHI data.
• Embedding Sidecar: GPU-accelerated service for dense and sparse embeddings.

Requirements

• Python 3.12+
• Neo4j Database
• Docker (optional for sidecar deployment)

Setup

1. Clone the repository.
2. Install dependencies:

   pip install -r requirements.txt
   

3. Configure environment variables in .env (use .env.example as a template).
4. Initialize the graph database:

   python main.py --load
   

Usage

Launch the interactive clinical CLI:

python main.py --cli

Other options:

• --audit: Run graph inventory and audit.
• --verify: Check data integrity in the database.
• --wipe: Clear the Neo4j database.