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from flask import Flask, request, jsonify
from faster_whisper import WhisperModel
import torch
import io
import time
app = Flask(__name__)
# Device check for faster-whisper
device = "cuda" if torch.cuda.is_available() else "cpu"
compute_type = "float16" if device == "cuda" else "int8"
print(f"Using device: {device} with compute_type: {compute_type}")
# Faster Whisper setup
beamsize = 2
wmodel = WhisperModel("guillaumekln/faster-whisper-small", device=device, compute_type=compute_type)
@app.route("/whisper_transcribe", methods=["POST"])
def whisper_transcribe():
if 'audio' not in request.files:
return jsonify({'error': 'No file provided'}), 400
audio_file = request.files['audio']
allowed_extensions = {'mp3', 'wav', 'ogg', 'm4a'}
if not (audio_file and audio_file.filename.lower().split('.')[-1] in allowed_extensions):
return jsonify({'error': 'Invalid file format'}), 400
print(f"Transcribing audio on {device}")
audio_bytes = audio_file.read()
audio_file = io.BytesIO(audio_bytes)
try:
segments, info = wmodel.transcribe(audio_file, beam_size=beamsize)
text = ''
starttime = time.time()
for segment in segments:
text += segment.text
print(f"Time to transcribe: {time.time() - starttime} seconds")
return jsonify({'transcription': text})
except Exception as e:
print(f"Transcription error: {str(e)}")
return jsonify({'error': 'Transcription failed'}), 500
if __name__ == "__main__":
app.run(host="0.0.0.0", debug=True, port=7860, threaded=True) |