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import os | |
os.system("pip install git+https://github.com/openai/whisper.git") | |
import whisper | |
from flask import Flask, jsonify, request | |
import requests | |
import time | |
from transformers import pipeline | |
model = whisper.load_model("small") | |
pipe = pipeline( | |
"automatic-speech-recognition", | |
model="openai/whisper-small.en", | |
chunk_length_s=15, | |
device=model.device, | |
) | |
app = Flask(__name__) | |
app.config['TIMEOUT'] = 60 * 10 # 10 mins | |
def indexApi(): | |
return jsonify({"output": "okay"}) | |
def runApi(): | |
start_time = time.time() | |
audio_url = request.form.get("audio_url") | |
response = requests.get(audio_url) | |
if response.status_code == requests.codes.ok: | |
with open("audio.mp3", "wb") as f: | |
f.write(response.content) | |
else: | |
return jsonify({ | |
"result": "Unable to save file, status code: {response.status_code}" , | |
}), 400 | |
audio = "audio.mp3" | |
audioOri = whisper.load_audio(audio) | |
prediction = pipe(audioOri)["text"] | |
end_time = time.time() | |
total_time = end_time - start_time | |
return jsonify({ | |
"audio_url": audio_url, | |
"result": prediction, | |
"exec_time_sec": total_time | |
}) | |
if __name__ == "__main__": | |
app.run(host="0.0.0.0", port=7860) | |