"""
Hugging Face Inference API endpoint for mbaza-model
This file exposes the model for API calls via HF Inference API.
"""
from typing import Dict, List, Any
from assistant import get_assistant

# Initialize the assistant once
assistant = get_assistant()


def model(inputs: List[str]) -> Dict[str, Any]:
    """
    Main inference function called by Hugging Face Inference API.
    
    Args:
        inputs: List of input strings (prompts/queries)
        
    Returns:
        Dict with model response
    """
    if not inputs or not isinstance(inputs, list):
        return {"error": "Invalid input format. Expected list of strings."}
    
    prompt = inputs[0]
    user_id = inputs[1] if len(inputs) > 1 else "api_user"
    
    try:
        result = assistant.handle_query(user_id, prompt)
        return result
    except Exception as e:
        return {
            "error": f"Processing failed: {str(e)}",
            "text": "An error occurred while processing your request."
        }


def predict(prompt: str, user_id: str = "api_user") -> Dict[str, Any]:
    """
    Alternative prediction function with explicit parameters.
    
    Args:
        prompt: User query or greeting
        user_id: Optional user identifier for context tracking
        
    Returns:
        Dict with response, intent, and any matched data
    """
    try:
        result = assistant.handle_query(user_id, prompt)
        return result
    except Exception as e:
        return {
            "error": f"Processing failed: {str(e)}",
            "text": "An error occurred while processing your request."
        }


# For testing locally
if __name__ == "__main__":
    test_queries = [
        "Mwaramutse neza",
        "Ibihano by'ubujura ni ibihe?",
        "Kwinjira aho umuntu atuye bitemewe namategeko",
        "What are the laws about corruption?"
    ]
    
    print("Testing inference.py locally...\n")
    for query in test_queries:
        print(f"Query: {query}")
        response = model([query])
        print(f"Response: {response.get('text', response)}")
        print("-" * 80)