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import gradio as gr |
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import whisper |
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from translate import Translator |
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from dotenv import dotenv_values |
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from elevenlabs.client import ElevenLabs |
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from elevenlabs import VoiceSettings |
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# requirements.txt |
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""" |
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gradio |
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openai-whisper |
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translate |
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python-dotenv |
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elevenlabs |
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""" |
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# Configuración .env |
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# config = dotenv_values(".env") |
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# ELEVENLABS_API_KEY = config["ELEVENLABS_API_KEY"] |
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ELEVENLABS_API_KEY = "MY_API_KEY" |
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def translator(audio_file): |
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# 1. Transcribir texto |
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# Usamos Whisper: https://github.com/openai/whisper |
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# Alternativa API online: https://www.assemblyai.com |
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try: |
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model = whisper.load_model("base") |
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result = model.transcribe(audio_file, language="Spanish", fp16=False) |
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transcription = result["text"] |
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except Exception as e: |
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raise gr.Error( |
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f"Se ha producido un error transcribiendo el texto: {str(e)}") |
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print(f"Texto original: {transcription}") |
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# 2. Traducir texto |
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# Usamos Translate: https://github.com/terryyin/translate-python |
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try: |
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en_transcription = Translator( |
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from_lang="es", to_lang="en").translate(transcription) |
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it_transcription = Translator( |
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from_lang="es", to_lang="it").translate(transcription) |
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fr_transcription = Translator( |
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from_lang="es", to_lang="fr").translate(transcription) |
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ja_transcription = Translator( |
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from_lang="es", to_lang="ja").translate(transcription) |
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except Exception as e: |
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raise gr.Error( |
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f"Se ha producido un error traduciendo el texto: {str(e)}") |
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print(f"Texto traducido a Inglés: {en_transcription}") |
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print(f"Texto traducido a Italiano: {it_transcription}") |
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print(f"Texto traducido a Francés: {fr_transcription}") |
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print(f"Texto traducido a Japonés: {ja_transcription}") |
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# 3. Generar audio traducido |
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# Usamos Elevenlabs IO: https://elevenlabs.io/docs/api-reference/getting-started |
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en_save_file_path = text_to_speach(en_transcription, "en") |
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it_save_file_path = text_to_speach(it_transcription, "it") |
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fr_save_file_path = text_to_speach(fr_transcription, "fr") |
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ja_save_file_path = text_to_speach(ja_transcription, "ja") |
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return en_save_file_path, it_save_file_path, fr_save_file_path, ja_save_file_path |
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def text_to_speach(text: str, language: str) -> str: |
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try: |
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client = ElevenLabs(api_key=ELEVENLABS_API_KEY) |
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response = client.text_to_speech.convert( |
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voice_id="pNInz6obpgDQGcFmaJgB", # Adam |
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optimize_streaming_latency="0", |
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output_format="mp3_22050_32", |
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text=text, |
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model_id="eleven_turbo_v2", |
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voice_settings=VoiceSettings( |
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stability=0.0, |
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similarity_boost=0.0, |
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style=0.0, |
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use_speaker_boost=True, |
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), |
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) |
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save_file_path = f"audios/{language}.mp3" |
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with open(save_file_path, "wb") as f: |
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for chunk in response: |
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if chunk: |
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f.write(chunk) |
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except Exception as e: |
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raise gr.Error( |
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f"Se ha producido un error creando el audio: {str(e)}") |
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return save_file_path |
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web = gr.Interface( |
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fn=translator, |
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inputs=gr.Audio( |
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sources=["microphone"], |
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type="filepath", |
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label="Español" |
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), |
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outputs=[ |
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gr.Audio(label="Inglés"), |
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gr.Audio(label="Italiano"), |
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gr.Audio(label="Francés"), |
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gr.Audio(label="Japonés") |
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], |
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title="Traductor de voz", |
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description="Traductor de voz con IA a varios idiomas" |
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) |
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web.launch() |
mouredev revised this gist