Create main.py

main.py

@@ -0,0 +1,57 @@
+from flask import Flask, request, jsonify
+import whisper
+import os
+
+app = Flask(__name__)
+
+# Load the Whisper model
+model = whisper.load_model("small")
+
+def transcribe(audio_path):
+    # Load audio and pad/trim it to fit 30 seconds
+    audio = whisper.load_audio(audio_path)
+    audio = whisper.pad_or_trim(audio)
+
+    # Make log-Mel spectrogram and move to the same device as the model
+    mel = whisper.log_mel_spectrogram(audio).to(model.device)
+
+    # Detect the spoken language
+    _, probs = model.detect_language(mel)
+    language = max(probs, key=probs.get)
+    
+    # Decode the audio
+    options = whisper.DecodingOptions(fp16=False)
+    result = whisper.decode(model, mel, options)
+    
+    return result.text, language
+
+@app.route('/transcribe', methods=['POST'])
+def transcribe_audio():
+    if 'audio' not in request.files:
+        return jsonify({"error": "No audio file provided"}), 400
+    
+    audio_file = request.files['audio']
+    
+    # Save the uploaded audio file
+    audio_path = os.path.join("temp_audio", audio_file.filename)
+    os.makedirs("temp_audio", exist_ok=True)
+    audio_file.save(audio_path)
+    
+    # Transcribe the audio
+    try:
+        transcription, language = transcribe(audio_path)
+    except Exception as e:
+        return jsonify({"error": f"An error occurred: {str(e)}"}), 500
+    
+    # Clean up the saved file
+    os.remove(audio_path)
+    
+    # Return the transcription and detected language
+    return jsonify({"transcription": transcription, "language": language}), 200
+
+@app.route('/healthcheck', methods=['GET'])
+def healthcheck():
+    return jsonify({"status": "API is running"}), 200
+
+if __name__ == '__main__':
+    app.run(host="0.0.0.0", port=5000)