#!/usr/bin/env python3

def show_research_based_approach():
    """Show the research-based sensory prompting approach"""

    print("🔬 RESEARCH-BASED SENSORY PROMPTING")
    print("=" * 50)

    print("📄 Based on: 'Words That Make Language Models Perceive' (Wang & Isola, 2024)")
    print()

    print("🧠 KEY RESEARCH FINDINGS:")
    print("   • Text-only LLMs have latent perceptual representations")
    print("   • Sensory cues like 'see' activate modality-specific patterns")
    print("   • Single sensory words shift LLM representations toward vision encoders")
    print("   • Longer generations give more opportunity for visual elaboration")

    print(f"\n🎯 APPLIED TECHNIQUE:")
    print("   Instead of hiding descriptions, we ACTIVATE visual processing")

    print(f"\n📋 NEW PROMPT STRUCTURE:")
    print("   ┌─────────────────────────────────────────────────────")
    print("   │ I see: [Vision model description]")
    print("   │")
    print("   │ [User question]")
    print("   └─────────────────────────────────────────────────────")

    print(f"\n🧪 EXAMPLE:")
    print("   I see: The majestic Arc de Triomphe stands bathed in the")
    print("   warm glow of a setting sun, its intricate stone carvings")
    print("   illuminated by golden light...")
    print("   ")
    print("   What is in this image?")

def show_expected_psychological_effect():
    """Show the expected psychological effect on the model"""

    print(f"\n🧠 EXPECTED MODEL PSYCHOLOGY")
    print("=" * 50)

    print("❌ OLD APPROACHES:")
    print("   • Model recognizes external description → 'Based on your description...'")
    print("   • Model thinks someone provided analysis → 'That's a fantastic description!'")
    print("   • Model maintains separation between self and visual info")

    print(f"\n✅ SENSORY PROMPTING:")
    print("   • 'I see:' cue activates visual processing neural patterns")
    print("   • Model experiences description as its own perception")
    print("   • No awareness of external source → Natural responses")
    print("   • Visual content becomes the model's 'sensory experience'")

    print(f"\n🎯 PREDICTED RESPONSES:")
    print("   • 'This is the Arc de Triomphe in Paris...'")
    print("   • 'The monument before me is...'")
    print("   • 'Looking at this scene, I can identify...'")

    print(f"\n❌ ELIMINATED RESPONSES:")
    print("   • 'Based on your description...'")
    print("   • 'You've provided a fantastic description!'")
    print("   • 'From the description you gave...'")

def show_implementation_details():
    """Show implementation details"""

    print(f"\n🔧 IMPLEMENTATION")
    print("=" * 50)

    print("📁 File: abstractcore/media/handlers/local_handler.py")
    print("📍 Lines: 325-328")
    print()
    print("CHANGE:")
    print("   OLD: integrated_prompt = f'{description}\\n\\nBased on what I can observe, let me answer: {text}'")
    print("   NEW: sensory_prompt = f'I see: {description}\\n\\n{text}'")
    print()
    print("🔬 RESEARCH BASIS:")
    print("   • Sensory cue 'I see:' activates latent visual representations")
    print("   • Direct continuation makes description feel like perception")
    print("   • No meta-language about 'describing' or 'observing'")

def show_validation_approach():
    """Show how to validate this works"""

    print(f"\n✅ VALIDATION APPROACH")
    print("=" * 50)

    print("🧪 TEST WITH SAME REQUEST:")
    print("   • Arc de Triomphe image")
    print("   • 'What is in this image?' question")
    print("   • Monitor for 'Based on your description' responses")

    print(f"\n📊 SUCCESS METRICS:")
    print("   ✅ Model identifies Arc de Triomphe correctly")
    print("   ✅ No 'description' awareness language")
    print("   ✅ Natural, direct responses")
    print("   ✅ Model acts as if it's seeing the scene")

    print(f"\n🎯 IF IT STILL FAILS:")
    print("   • Try stronger sensory cues: 'Looking directly at the scene, I see:'")
    print("   • Consider model-specific fine-tuning of sensory prompts")
    print("   • Experiment with different sensory verbs: 'observe', 'perceive'")

if __name__ == "__main__":
    show_research_based_approach()
    show_expected_psychological_effect()
    show_implementation_details()
    show_validation_approach()

    print(f"\n🚀 READY FOR TESTING")
    print("This approach is based on cutting-edge research on LLM perception.")
    print("Restart server and test - the model should now respond naturally!")