import os
import time
from sqlalchemy.orm import Session
from models import Evidence
import google.generativeai as genai
from database import SessionLocal

def process_transcription(evidence_id: int):
    """
    Background task to transcribe audio.
    In a real scenario, this would call a local model runner like Ollama (Whisper)
    or an external API like Gemini.
    """
    db = SessionLocal()
    try:
        evidence = db.query(Evidence).filter(Evidence.id == evidence_id).first()
        if not evidence:
            return

        evidence.transcription_status = "processing"
        db.commit()

        # Simulate local processing or call a local model
        # For now, we'll try to use Gemini if available, or a mock
        
        file_path = evidence.file_path
        if not os.path.exists(file_path):
            evidence.transcription_status = "error"
            evidence.transcription = "Error: File not found"
            db.commit()
            return

        api_key = os.getenv("GOOGLE_API_KEY")
        if api_key:
            try:
                genai.configure(api_key=api_key)
                
                # Upload to Gemini (Media Service)
                audio_file = genai.upload_file(path=file_path, mime_type=evidence.media_type or "audio/wav")
                
                # Use Gemini 1.5 Flash for audio-to-text
                model = genai.GenerativeModel("gemini-2.5-flash-lite")
                response = model.generate_content([
                    "Por favor, transcribe exactamente lo que se dice en este audio. Solo devuelve el texto transcrito.",
                    audio_file
                ])
                
                evidence.transcription = response.text
                evidence.transcription_status = "completed"
            except Exception as e:
                evidence.transcription_status = "error"
                evidence.transcription = f"Error: {str(e)}"
        else:
            # Mock transcription if no API key (Local Model Simulation)
            time.sleep(5) # Simulate work
            evidence.transcription = f"[LOCAL MOCK TRANSCRIPTION] Transcripción asíncrona completada para {os.path.basename(file_path)}"
            evidence.transcription_status = "completed"

        db.commit()
    except Exception as e:
        print(f"Transcription error: {e}")
        try:
            evidence = db.query(Evidence).filter(Evidence.id == evidence_id).first()
            if evidence:
                evidence.transcription_status = "error"
                evidence.transcription = f"Unexpected error: {str(e)}"
                db.commit()
        except:
            pass
    finally:
        db.close()