app.py

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

model = whisper.load_model("large-v2")

app = Flask(__name__)
app.config['TIMEOUT'] = 60 * 10 # 10 mins

@app.route("/")
def indexApi():
    return jsonify({"output": "okay"})

@app.route("/run", methods=['POST'])
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"

    audio = whisper.load_audio(audio)
    audio = whisper.pad_or_trim(audio)
    
    mel = whisper.log_mel_spectrogram(audio).to(model.device)
    
    _, probs = model.detect_language(mel)
    
    options = whisper.DecodingOptions(fp16 = False)
    result = whisper.decode(model, mel, options)


    end_time = time.time()
    total_time = end_time - start_time

    return jsonify({
        "audio_url": audio_url,
        # "model": model,
        "result": result.text,
        "exec_time_sec": total_time
    })

if __name__ == "__main__":
    options = {
        'gateway_timeout': 600
    }
    app.run(host="0.0.0.0", port=7860, options=options)
        
# def inference(audio):
#     audio = whisper.load_audio(audio)
#     audio = whisper.pad_or_trim(audio)
    
#     mel = whisper.log_mel_spectrogram(audio).to(model.device)
    
#     _, probs = model.detect_language(mel)
    
#     options = whisper.DecodingOptions(fp16 = False)
#     result = whisper.decode(model, mel, options)
    
#     # print(result.text)
#     return result.text, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)