Modernizing the transcribe to new version of Open AI
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@ -2,7 +2,7 @@ import os
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import json
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import json
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import logging
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import logging
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import openai
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from openai import OpenAI
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from telegram import Update, Bot
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from telegram import Update, Bot
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from django.http import JsonResponse
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from django.http import JsonResponse
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from django.views.decorators.csrf import csrf_exempt
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from django.views.decorators.csrf import csrf_exempt
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@ -19,9 +19,8 @@ from .handlers import (
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logger = logging.getLogger(__name__)
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logger = logging.getLogger(__name__)
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# Configura tu API Key de OpenAI
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# Configura tu cliente de OpenAI
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openai.api_key = os.getenv("OPENAI_API_KEY")
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client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
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# -------------------------------
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# -------------------------------
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# 🛠 Modular local handlers inside views.py
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# 🛠 Modular local handlers inside views.py
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@ -91,29 +90,25 @@ async def dispatch_private_commands(update, text):
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# -------------------------------
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# -------------------------------
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# 🛠 Voice transcription helper
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# 🛠 Voice transcription helper (Whisper via OpenAI client)
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# -------------------------------
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# -------------------------------
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async def transcribe_with_whisper(update, bot):
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async def transcribe_with_whisper(update, bot):
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# 1. Descarga el archivo de voz desde Telegram
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# 1. Descarga el archivo de voz desde Telegram
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tg_file = await bot.get_file(update.message.voice.file_id)
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tg_file = await bot.get_file(update.message.voice.file_id)
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download_path = f"/tmp/{update.message.voice.file_id}.ogg"
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download_path = f"/tmp/{update.message.voice.file_id}.ogg"
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# En python-telegram-bot v21: download_to_drive es coroutine
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await tg_file.download_to_drive(download_path)
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await tg_file.download_to_drive(download_path)
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# 2. Envía el audio a la API Whisper de OpenAI
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# 2. Envía el audio a la API de OpenAI para transcripción
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with open(download_path, "rb") as audio:
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with open(download_path, "rb") as audio_file:
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transcript = openai.Audio.transcribe(
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transcript = client.audio.transcriptions.create(
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model="whisper-1",
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model="gpt-4o-transcribe", # o "whisper-1"
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file=audio,
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file=audio_file,
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response_format="text",
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response_format="text",
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language="es"
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language="es"
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)
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)
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return transcript.strip()
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return transcript.text if hasattr(transcript, 'text') else transcript
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# -------------------------------
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# 🌐 Main webhook
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# -------------------------------
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# -------------------------------
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@csrf_exempt
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@csrf_exempt
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