Mechanism Flowchart

Generates Mermaid flowchart code and visual representations of medical mechanisms, pathophysiology, and drug action pathways.

Features

• Automatic flowchart generation from text descriptions
• Multiple diagram types (flowchart, sequence, state)
• Customizable styling for publication
• Support for complex branching logic
• Export to multiple formats

Use Cases

• Creating educational diagrams for presentations
• Visualizing drug mechanism of action
• Illustrating disease pathways
• Thesis and publication figure preparation

Input Parameters

Output Format

{
  "mermaid_code": "string",
  "diagram_type": "string",
  "nodes": ["string"],
  "edges": ["string"],
  "rendered_svg": "string (optional)"
}

Example Usage

from mechanism_flowchart import MechanismDiagram

diagram = MechanismDiagram()
result = diagram.generate(
    "Type 2 Diabetes: Insulin resistance leads to hyperglycemia, "
    "causing beta cell dysfunction and further glucose elevation"
)
print(result['mermaid_code'])

Sample Output

flowchart TB
    A[Insulin Resistance] --> B[Hyperglycemia]
    B --> C[Beta Cell Dysfunction]
    C --> D[Worsening Glucose Control]
    B --> D

Limitations

• Requires Mermaid renderer for visualization
• Complex mechanisms may need manual refinement
• Limited to Mermaid-supported diagram types

Risk Assessment

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• Input file paths validated (no ../ traversal)
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no stack traces exposed)
• Dependencies audited

Prerequisites

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:
  • Performance optimization
  • Additional feature support