# services/chatbot_service.py (CONFIRMED WORKING VERSION)
from transformers import pipeline
import logging

logger = logging.getLogger(__name__)

# Global chatbot pipeline
chatbot_pipeline = None

def load_chatbot_model():
    """Load the free chatbot model"""
    global chatbot_pipeline
    try:
        logger.info("Loading DialoGPT chatbot model...")
        
        chatbot_pipeline = pipeline(
            "text-generation",
            model="microsoft/DialoGPT-small",
            device="cpu"
        )
        logger.info("✓ Chatbot model loaded successfully")
    except Exception as e:
        logger.error(f"✗ Failed to load chatbot model: {str(e)}")
        chatbot_pipeline = None

async def get_chatbot_response(user_text: str, user_id: str = "default") -> str:
    """
    Generate chatbot response using free model.
    """
    global chatbot_pipeline
    
    try:
        if chatbot_pipeline is None:
            load_chatbot_model()
            if chatbot_pipeline is None:
                return get_fallback_response(user_text)
        
        logger.info(f"Generating chatbot response for: '{user_text}'")
        
        # Prepare prompt
        prompt = f"User: {user_text}\nAssistant:"
        
        # Generate response
        response = chatbot_pipeline(
            prompt,
            max_new_tokens=100,
            do_sample=True,
            temperature=0.7,
            top_p=0.9,
            pad_token_id=chatbot_pipeline.tokenizer.eos_token_id
        )
        
        # Extract the response
        generated_text = response[0]['generated_text']
        
        # Extract only the assistant's response
        if "Assistant:" in generated_text:
            bot_response = generated_text.split("Assistant:")[-1].strip()
        else:
            bot_response = generated_text.replace(prompt, "").strip()
        
        # Clean up the response
        if not bot_response:
            bot_response = get_fallback_response(user_text)
        
        logger.info(f"✓ Response generated: '{bot_response}'")
        return bot_response
        
    except Exception as e:
        logger.error(f"✗ Chatbot response failed: {str(e)}")
        return get_fallback_response(user_text)

def get_fallback_response(user_text: str) -> str:
    """Provide fallback responses"""
    fallback_responses = [
        f"I understand you said: '{user_text}'. How can I help you with that?",
        f"That's interesting! Regarding '{user_text}', what would you like to know?",
        f"Thanks for your message about '{user_text}'. How can I assist you further?"
    ]
    
    import random
    return random.choice(fallback_responses)