Video Translation API Guide

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from openai import OpenAI
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client = OpenAI()
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# Extract audio from video first (using ffmpeg or similar)
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audio_file = open("original-audio.wav", "rb")
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transcript = client.audio.transcriptions.create(
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    model="whisper-1",
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    file=audio_file,
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    response_format="verbose_json",
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    timestamp_granularities=["segment"],
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)
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print(transcript.text)
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# Save segments with timestamps for alignment
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for segment in transcript.segments:
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    print(f"[{segment['start']:.1f}s - {segment['end']:.1f}s] {segment['text']}")

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from openai import OpenAI
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client = OpenAI()
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original_text = "Welcome to our platform. Today we'll walk through the new features."
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target_language = "Spanish"
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response = client.chat.completions.create(
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    model="gpt-4o",
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    messages=[
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        {
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            "role": "system",
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            "content": f"Translate the following text to {target_language}. "
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                       f"Keep the tone natural and conversational. "
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                       f"Return only the translated text.",
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        },
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        {"role": "user", "content": original_text},
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    ],
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)
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translated_text = response.choices[0].message.content
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print(translated_text)
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# "Bienvenidos a nuestra plataforma. Hoy repasaremos las nuevas funciones."

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import requests
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ELEVENLABS_API_KEY = "your-elevenlabs-key"
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VOICE_ID = "EXAVITQu4vr4xnSDxMaL"  # Or a cloned voice ID
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response = requests.post(
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    f"https://api.elevenlabs.io/v1/text-to-speech/{VOICE_ID}",
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    headers={
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        "xi-api-key": ELEVENLABS_API_KEY,
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        "Content-Type": "application/json",
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    },
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    json={
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        "text": "Bienvenidos a nuestra plataforma. Hoy repasaremos las nuevas funciones.",
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        "model_id": "eleven_multilingual_v2",
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        "voice_settings": {
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            "stability": 0.5,
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            "similarity_boost": 0.75,
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        },
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    },
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)
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with open("translated-audio.mp3", "wb") as f:
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    f.write(response.content)