main.py

"""
Main Entry Point - LangGraph UI Regression Testing System
Hybrid Approach: Screenshots + HF Vision + CSS Extraction
"""

import os
import sys
import argparse
from datetime import datetime

# Load environment variables from .env file manually
def load_env_file(env_path: str = ".env"):
    """Load environment variables from .env file."""
    if os.path.exists(env_path):
        with open(env_path, 'r') as f:
            for line in f:
                line = line.strip()
                if line and not line.startswith('#') and '=' in line:
                    key, value = line.split('=', 1)
                    os.environ[key.strip()] = value.strip()

load_env_file()

from state_schema import create_initial_state, WorkflowState
from agents.agent_0_super_agent import agent_0_node
from agents.agent_1_design_inspector import agent_1_node
from agents.agent_2_website_inspector import agent_2_node
from agents.agent_3_difference_analyzer import agent_3_node
from screenshot_annotator import annotate_all_screenshots
from report_generator import ReportGenerator


def get_credentials():
    """Get credentials from environment variables."""
    figma_key = os.getenv("FIGMA_FILE_KEY", "")
    figma_token = os.getenv("FIGMA_ACCESS_TOKEN", "")
    website_url = os.getenv("WEBSITE_URL", "")
    hf_token = os.getenv("HUGGINGFACE_API_TOKEN", "")
    
    if not figma_key:
        print("❌ Error: FIGMA_FILE_KEY not set in .env")
        sys.exit(1)
    
    if not figma_token:
        print("❌ Error: FIGMA_ACCESS_TOKEN not set in .env")
        sys.exit(1)
    
    if not website_url:
        print("❌ Error: WEBSITE_URL not set in .env")
        sys.exit(1)
    
    return figma_key, figma_token, website_url, hf_token


def run_workflow(figma_file_key: str, figma_access_token: str, website_url: str, hf_token: str, execution_id: str) -> WorkflowState:
    """Run the complete workflow."""
    # Create initial state
    state = create_initial_state(
        figma_file_key=figma_file_key,
        figma_access_token=figma_access_token,
        website_url=website_url,
        hf_token=hf_token,
        execution_id=execution_id
    )
    
    print("\n" + "="*60)
    print("🚀 Starting UI Regression Testing Workflow")
    print("="*60)
    
    # Agent 0: Super Agent (Test Plan)
    print("\n🤖 Agent 0: Super Agent - Generating Test Plan...")
    agent_0_result = agent_0_node(state)
    state.test_plan = agent_0_result.get("test_plan", {})
    state.test_categories = agent_0_result.get("test_categories", state.test_categories)
    print(f"  ✓ Test plan generated")
    
    # Agent 1: Design Inspector (Figma Screenshots)
    print("\n🎨 Agent 1: Design Inspector - Capturing Figma Screenshots...")
    agent_1_result = agent_1_node(state.__dict__)
    state.design_screenshots = agent_1_result.get("design_screenshots", {})
    state.status = agent_1_result.get("status", state.status)
    
    if state.status == "design_inspection_failed":
        print(f"  ❌ Agent 1 failed")
        return state
    
    # Agent 2: Website Inspector (Website Screenshots)
    print("\n🌐 Agent 2: Website Inspector - Capturing Website Screenshots...")
    agent_2_result = agent_2_node(state.__dict__)
    state.website_screenshots = agent_2_result.get("website_screenshots", {})
    state.status = agent_2_result.get("status", state.status)
    
    if state.status == "website_inspection_failed":
        print(f"  ❌ Agent 2 failed")
        return state
    
    # Agent 3: Difference Analyzer (Screenshot Comparison)
    print("\n🔍 Agent 3: Difference Analyzer - Analyzing Visual Differences...")
    agent_3_result = agent_3_node(state.__dict__)
    state.visual_differences = agent_3_result.get("visual_differences", [])
    state.similarity_score = agent_3_result.get("similarity_score", 0)
    state.status = agent_3_result.get("status", state.status)
    
    if state.status == "analysis_failed":
        print(f"  ❌ Agent 3 failed")
        return state
    
    # Annotate screenshots
    print("\n📸 Annotating Screenshots...")
    state = annotate_all_screenshots(state)
    
    print("\n" + "="*60)
    print("✅ Workflow Completed")
    print("="*60)
    
    return state


def main():
    """Main entry point."""
    parser = argparse.ArgumentParser(description="UI Regression Testing System")
    parser.add_argument("--execution-id", default="", help="Execution ID")
    parser.add_argument("--debug", action="store_true", help="Enable debug mode")
    parser.add_argument("--output-dir", default="reports", help="Output directory for reports")
    
    args = parser.parse_args()
    
    # Print header
    print("\n" + "="*70)
    print("🚀 UI REGRESSION TESTING SYSTEM (Hybrid Approach)")
    print("="*70)
    
    # Get credentials
    print("\n📋 Configuration:")
    figma_key, figma_token, website_url, hf_token = get_credentials()
    
    print(f"  Figma File Key: {figma_key[:20]}...")
    print(f"  Website URL: {website_url}")
    print(f"  Output Directory: {args.output_dir}")
    print(f"  Debug Mode: {args.debug}")
    print(f"  HF Token: {'✓ Enabled' if hf_token else '✗ Disabled'}")
    
    print("\n" + "="*70)
    
    # Generate execution ID if not provided
    execution_id = args.execution_id or f"exec_{datetime.now().strftime('%Y%m%d_%H%M%S')}"
    
    # Run workflow
    try:
        final_state = run_workflow(
            figma_file_key=figma_key,
            figma_access_token=figma_token,
            website_url=website_url,
            hf_token=hf_token,
            execution_id=execution_id
        )
        
        # Generate reports
        if final_state.status == "analysis_complete":
            ReportGenerator.generate_all_reports(final_state, args.output_dir)
            
            # Print summary
            print("\n" + "="*70)
            print("✅ EXECUTION COMPLETED SUCCESSFULLY")
            print("="*70)
            print(f"\n📊 Results:")
            print(f"  Total Differences: {len(final_state.visual_differences)}")
            print(f"  High Severity: {len([d for d in final_state.visual_differences if d.severity == 'High'])}")
            print(f"  Medium Severity: {len([d for d in final_state.visual_differences if d.severity == 'Medium'])}")
            print(f"  Low Severity: {len([d for d in final_state.visual_differences if d.severity == 'Low'])}")
            print(f"  Similarity Score: {final_state.similarity_score:.1f}/100")
            print(f"\n📁 Reports saved to: {args.output_dir}/")
            print("\n" + "="*70)
        else:
            print(f"\n❌ Workflow failed: {final_state.error_message}")
            sys.exit(1)
    
    except Exception as e:
        print(f"\n❌ Error: {str(e)}")
        import traceback
        traceback.print_exc()
        sys.exit(1)


if __name__ == "__main__":
    main()