60 lines
1.8 KiB
Python
60 lines
1.8 KiB
Python
from flask import Flask, request, jsonify
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import os
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import subprocess
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from werkzeug.utils import secure_filename
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app = Flask(__name__)
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# Configure upload folder (adjust as needed)
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UPLOAD_FOLDER = "./uploads"
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
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# Path to whisper.cpp executable & model (update paths as needed)
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WHISPER_CPP_PATH = "./whisper.cpp/main" # Path to compiled whisper.cpp binary
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MODEL_PATH = "./whisper.cpp/models/ggml-small.en.bin" # Path to model
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@app.route('/transcribe', methods=['POST'])
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def transcribe_audio():
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if 'audio' not in request.files:
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return jsonify({"error": "No audio file provided"}), 400
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audio_file = request.files['audio']
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if audio_file.filename == '':
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return jsonify({"error": "Empty filename"}), 400
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# Save the uploaded file
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filename = secure_filename(audio_file.filename)
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filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
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audio_file.save(filepath)
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try:
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# Run whisper.cpp to transcribe
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command = [
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WHISPER_CPP_PATH,
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"-m", MODEL_PATH,
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"-f", filepath,
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"--output-txt" # Output as text
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]
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result = subprocess.run(command, capture_output=True, text=True)
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if result.returncode != 0:
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return jsonify({"error": "Transcription failed", "details": result.stderr}), 500
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# Read the transcription
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output_txt = filepath + ".txt"
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with open(output_txt, 'r') as f:
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transcription = f.read()
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# Clean up files
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os.remove(filepath)
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os.remove(output_txt)
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return jsonify({"text": transcription.strip()})
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=4002, debug=True)
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