src/audioProcessing.py

import os
import tempfile
import requests
import json
import uuid
from typing import Tuple, Optional, Dict, Any

def transcribe_audio(audio_file, api_key, model_id="scribe_v1"):
    if not api_key:
        return {"error": "Please provide an API key"}
    url = "https://api.elevenlabs.io/v1/speech-to-text"
    headers = {
        "xi-api-key": api_key
    }
    files = {
        "file": open(audio_file, "rb"),
        "model_id": (None, model_id)
    }
    try:
        response = requests.post(url, headers=headers, files=files)
        response.raise_for_status()
        result = response.json()
        return result
    except requests.exceptions.RequestException as e:
        return {"error": f"API request failed: {str(e)}"}
    except json.JSONDecodeError:
        return {"error": "Failed to parse API response"}
    finally:
        files["file"].close()

def save_transcription(transcription):
    if "error" in transcription:
        return None, transcription["error"]
    transcript_filename = f"transcription_{uuid.uuid4().hex[:8]}.txt"
    try:
        with open(transcript_filename, "w", encoding="utf-8") as f:
            f.write(transcription.get('text', 'No text found'))
        return transcript_filename, "Transcription saved as text file"
    except Exception as e:
        return None, f"Error saving transcription: {str(e)}"

def process_audio_file(audio_file, elevenlabs_api_key, model_id="scribe_v1") -> Tuple[str, str, str]:
    if not elevenlabs_api_key:
        return None, "ElevenLabs API key is required for transcription", None
    
    transcription_result = transcribe_audio(audio_file, elevenlabs_api_key, model_id)
    
    if "error" in transcription_result:
        return None, transcription_result["error"], None
    
    transcript_text = transcription_result.get('text', '')
    transcript_path = tempfile.mktemp(suffix='.txt')
    
    with open(transcript_path, 'w', encoding='utf-8') as transcript_file:
        transcript_file.write(transcript_text)
    
    return transcript_path, f"Transcription completed successfully. Length: {len(transcript_text)} characters.", transcript_text