File size: 1,180 Bytes
1a75907 13593ef 1a75907 13593ef 1a75907 49f69f0 13593ef 1a75907 0b0e86f 1a75907 0b0e86f 1a75907 0b0e86f 1a75907 49f69f0 0b0e86f 1a75907 0b0e86f 1a75907 0b0e86f 1a75907 0b0e86f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | from flask import Flask, request, jsonify
from flask_cors import CORS
from faster_whisper import WhisperModel
import tempfile
import os
app = Flask(__name__)
CORS(app)
# Load model (same as your working Gradio code)
model_size = "tiny"
device = "cpu"
compute_type = "int8"
model = WhisperModel(model_size, device=device, compute_type=compute_type)
@app.route('/transcribe', methods=['POST'])
def transcribe():
if 'audio' not in request.files:
return jsonify({'error': 'No audio file'}), 400
file = request.files['audio']
# Save temp file
temp = tempfile.NamedTemporaryFile(delete=False, suffix='.wav')
file.save(temp.name)
temp.close()
try:
# Same transcribe function that worked
segments, _ = model.transcribe(temp.name, beam_size=5)
text = "".join([segment.text for segment in segments])
return jsonify({'text': text})
except Exception as e:
return jsonify({'error': str(e)}), 500
finally:
os.unlink(temp.name)
@app.route('/health', methods=['GET'])
def health():
return jsonify({'status': 'ok'})
if __name__ == '__main__':
app.run(host='0.0.0.0', port=7860) |