"""
Complete workflow test for Science Storyteller
Tests the full pipeline: Search -> Analyze -> Script -> Audio
"""
import asyncio
import logging
from agents.research_agent import ResearchAgent
from agents.analysis_agent import AnalysisAgent
from agents.audio_agent import AudioAgent

logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)

async def test_full_workflow():
    """Test complete Science Storyteller workflow"""
    print("\n" + "="*60)
    print("🎬 SCIENCE STORYTELLER - FULL WORKFLOW TEST")
    print("="*60 + "\n")
    
    topic = "AlphaFold protein structure prediction"
    print(f"📚 Topic: {topic}\n")
    
    # Step 1: Search for papers
    print("🔍 STEP 1: Searching for research papers...")
    research_agent = ResearchAgent()
    papers = await research_agent.search(topic, max_results=3)
    
    if not papers:
        print("❌ No papers found!")
        return False
    
    print(f"✅ Found {len(papers)} papers")
    best_paper = papers[0]
    print(f"   📄 Selected: {best_paper.get('title', 'Unknown')[:80]}...")
    print()
    
    # Step 2: Analyze and generate summary
    print("🤖 STEP 2: Analyzing with Claude AI...")
    analysis_agent = AnalysisAgent()
    summary = await analysis_agent.summarize(best_paper)
    
    if not summary:
        print("❌ Failed to generate summary!")
        return False
    
    print(f"✅ Summary generated ({len(summary)} chars)")
    print(f"   Preview: {summary[:150]}...")
    print()
    
    # Step 3: Generate podcast script
    print("📝 STEP 3: Creating podcast script...")
    script = await analysis_agent.create_script(summary, best_paper)
    
    if not script:
        print("❌ Failed to generate script!")
        return False
    
    print(f"✅ Script created ({len(script)} chars)")
    print(f"   Preview: {script[:150]}...")
    print()
    
    # Step 4: Generate audio with Kokoro-82M
    print("🎤 STEP 4: Generating audio with Kokoro-82M...")
    audio_agent = AudioAgent()
    
    # Use a short excerpt for testing (full script would be too long/expensive)
    test_excerpt = script[:500] + "... And that's just the beginning of this fascinating research."
    
    audio_path = await audio_agent.text_to_speech(
        test_excerpt, 
        f"test_workflow_{int(asyncio.get_event_loop().time())}.wav"
    )
    
    if not audio_path:
        print("❌ Failed to generate audio!")
        return False
    
    print(f"✅ Audio generated: {audio_path}")
    
    # Check file size
    from pathlib import Path
    file_size = Path(audio_path).stat().st_size / 1024  # KB
    print(f"   📦 File size: {file_size:.2f} KB")
    print()
    
    # Summary
    print("="*60)
    print("🎉 WORKFLOW COMPLETE - ALL STEPS SUCCESSFUL!")
    print("="*60)
    print("\nResults:")
    print(f"  • Papers found: {len(papers)}")
    print(f"  • Summary length: {len(summary)} chars")
    print(f"  • Script length: {len(script)} chars")
    print(f"  • Audio file: {audio_path}")
    print(f"  • Audio size: {file_size:.2f} KB")
    print("\n✅ Ready for production deployment!\n")
    
    return True

if __name__ == "__main__":
    try:
        success = asyncio.run(test_full_workflow())
        exit(0 if success else 1)
    except KeyboardInterrupt:
        print("\n\n⚠️ Test interrupted by user")
        exit(1)
    except Exception as e:
        print(f"\n\n❌ Test failed with error: {e}")
        import traceback
        traceback.print_exc()
        exit(1)