app.py

import pandas as pd
from pyannote.audio import Pipeline
pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization",use_auth_token="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")
def diarization():
    diarization = pipeline("result.wav")
    speakertime=[]
# print the result
    for turn, _, speaker in diarization.itertracks(yield_label=True):
        details=[turn.start,turn.end,speaker]
        speakertime.append(details)
        #print(turn.start)
        #print(speaker)
        print(f"start={turn.start:.1f}s stop={turn.end:.1f}s speaker_{speaker}")
    #print(speakertime)
    df = pd.DataFrame(speakertime,columns=['start', 'end','speaker'])
    text=[]
    for i in range (df.start.count()):
        text.append(generatetext("result.wav",df.start[i], df.end[i]))
    df['text']=text
    with open('my_file.txt', 'w') as my_file:
      for i in range (df.start.count()):
          my_file.write(df.speaker[i]+": " +df.text[i] + '\n')
    print(open("my_file.txt","r").read())


def generatetext(filename,starttime,endtime):
  
  t1 = starttime * 1000 # works in milliseconds
  t2 = endtime * 1000

  newAudio = AudioSegment.from_wav(filename)
  a = newAudio[t1:t2]
  a.export('audio.wav', format="wav") 
  text1 = whisper('audio.wav')
  return text1.get("text")

block = gr.Blocks()
with block:
    with gr.Group():
        with gr.Box(): 
            with gr.Row().style():
               
                inp_audio = gr.Audio(
                    label="Input Audio",
                    type="filepath",
                    mirror_webcam = False
                )
                outputdialogs = gr.Textbox()
            btn = gr.Button("Generate Text")
        btn.click(diarisation, inputs=[inp_audio], outputdialogs=[op],api_name="view_api")
block.launch(enable_queue = True,debug=True)