Create app.py

app.py

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+import base64
+import os
+from flask import Flask, request, jsonify
+from pydub import AudioSegment
+import whisper
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+# Load the Whisper model
+whisper_model = whisper.load_model("base")
+
+# Load the translation model and tokenizer
+tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
+translation_model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
+
+def preprocess_audio(audio_path):
+    """Convert audio to 16kHz mono WAV format."""
+    audio = AudioSegment.from_file(audio_path)
+    audio = audio.set_frame_rate(16000).set_channels(1)  # Set to 16kHz and mono
+    processed_path = f"{audio_path}_processed.wav"
+    audio.export(processed_path, format="wav")
+    return processed_path
+
+def transcribe_audio(audio_path, source_language=None):
+    """Transcribe audio using Whisper with an optional source language."""
+    options = {"language": source_language} if source_language else {}
+    result = whisper_model.transcribe(audio_path, **options)
+    return result['text']
+
+def translate_text(text, source_lang="en", target_lang="hi"):
+    """Translate text using Facebook's M2M100 model."""
+    tokenizer.src_lang = source_lang
+    inputs = tokenizer(text, return_tensors="pt")
+    translated_tokens = translation_model.generate(
+        **inputs,
+        forced_bos_token_id=tokenizer.get_lang_id(target_lang)
+    )
+    return tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
+
+def handle_request(audio_base64, source_lang, target_lang):
+    """Handle audio translation request."""
+    audio_file_path = "temp_audio.wav"
+    # Decode the base64 audio
+    with open(audio_file_path, "wb") as audio_file:
+        audio_file.write(base64.b64decode(audio_base64))
+
+    # Process the audio file
+    processed_audio_file_name = preprocess_audio(audio_file_path)
+    spoken_text = transcribe_audio(processed_audio_file_name, source_lang)
+    translated_text = translate_text(spoken_text, source_lang, target_lang)
+
+    # Clean up temporary files
+    os.remove(processed_audio_file_name)
+    os.remove(audio_file_path)
+
+    return {"transcribed_text": spoken_text, "translated_text": translated_text}
+
+# Flask for handling external POST requests
+app = Flask(__name__)
+
+@app.route('/translate', methods=['POST'])
+def translate():
+    """API endpoint for handling audio translation."""
+    data = request.json
+    if 'audio' not in data or 'source_lang' not in data or 'target_lang' not in data:
+        return jsonify({"error": "Invalid request format"}), 400
+    
+    audio_base64 = data['audio']
+    source_lang = data['source_lang']
+    target_lang = data['target_lang']
+
+    # Call the handle_request function to process the request
+    response = handle_request(audio_base64, source_lang, target_lang)
+    return jsonify(response)
+
+if __name__ == "__main__":
+    app.run(host='0.0.0.0', port=7860)