import os
from huggingface_hub import InferenceClient

class SummarizationService:
    """Service for summarizing text and extracting action items."""
    
    def __init__(self):
        self.summarization_model = "facebook/bart-large-cnn"
        self.client = InferenceClient(
            provider="hf-inference",
            token=os.getenv("HF_TOKEN") or os.getenv("HUGGINGFACE_TOKEN")
        )
    
    def _load_prompt(self, prompt_name: str) -> str:
        """Load prompt template from file."""
        try:
            with open(f"prompts/{prompt_name}.txt", "r") as f:
                return f.read().strip()
        except FileNotFoundError:
            if prompt_name == "summary":
                return "Summarize the following meeting transcript in a concise manner:\n\n{transcript}"
            elif prompt_name == "action_items":
                return "Extract action items from the following meeting transcript. List each action item clearly:\n\n{transcript}"
            return "{transcript}"
    
    def summarize(self, transcript: str) -> str:
        """Generate a summary of the transcript."""
        try:
            if not transcript.strip():
                return "No transcript available to summarize"
            
            result = self.client.summarization(
                transcript,
                model=self.summarization_model
            )
            
            return result if result else "Failed to generate summary"
            
        except Exception as e:
            print(f"Summarization error: {e}")
            return f"Error generating summary: {str(e)}"
    
    def extract_action_items(self, transcript: str) -> str:
        """Extract action items from the transcript."""
        try:
            if not transcript.strip():
                return "No transcript available to extract action items"
            
            # Use summarization with action-item focused input
            prompt_template = self._load_prompt("action_items")
            prompt = prompt_template.format(transcript=transcript)
            
            result = self.client.summarization(
                prompt,
                model=self.summarization_model
            )
            
            return result if result else "No action items found"
            
        except Exception as e:
            print(f"Action items extraction error: {e}")
            return f"Error extracting action items: {str(e)}"