import asyncio
import logging
import spacy
from app.services.llm_service import get_llm_service
from app.services.spacy_medical_nlp import get_spacy_nlp

# Configure Logging
logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
logger = logging.getLogger("FINAL_VERIFY")

async def verify_stack():
    print("\n" + "="*60)
    print("🚀 FINAL SYSTEM STACK VERIFICATION")
    print("="*60)
    
    # --- 1. NLP Verification (SciSpaCy) ---
    print("\n🔬 1. Verifying Medical NLP (SciSpaCy)...")
    try:
        nlp_service = get_spacy_nlp()
        if nlp_service.nlp and "sci" in nlp_service.nlp.meta.get("lang", "") + nlp_service.nlp.meta.get("name", ""):
            print("   ✅ SciSpaCy Model Found: en_core_sci_md")
        else:
             print(f"   ℹ️  Model loaded: {nlp_service.nlp.meta.get('name') if nlp_service.nlp else 'None'}")
        
        text = "Patient prescribed 100mg Aspirin for severe hypertension."
        entities = nlp_service.extract_medical_entities(text)
        
        if entities:
            print(f"   ✅ Extraction Success: {entities}")
        else:
            print("   ⚠️  No entities extracted (Check model type)")
            
    except Exception as e:
        print(f"   ❌ NLP Setup Failed: {e}")

    # --- 2. LLM Verification (TinyLlama) ---
    print("\n🤖 2. Verifying Local LLM (TinyLlama)...")
    try:
        llm = get_llm_service()
        prompt = "Explain fever in one sentence."
        print(f"   📤 Prompt: '{prompt}'")
        
        response = await llm.generate_response(prompt, system_prompt="You are a doctor.")
        
        print(f"   📥 Response: {response.strip()}")
        
        if response and "apologize" not in response.lower():
            print("   ✅ Local Inference Success!")
        else:
            print("   ⚠️  Fallback Triggered (Check LLM logs)")
            
    except Exception as e:
        print(f"   ❌ LLM Inference Failed: {e}")

    print("\n" + "="*60)

if __name__ == "__main__":
    asyncio.run(verify_stack())