%%writefile app.py
from IPython.display import Javascript
from IPython import display
from google.colab import output
from base64 import b64decode
import datetime
import whisper
import openai
import os
import base64
from Crypto.Cipher import AES
from streamlit_bokeh_events import streamlit_bokeh_events
import streamlit as st
from bokeh.models.widgets import Button
from bokeh.models.widgets.buttons import Button
from bokeh.models import CustomJS
from streamlit_bokeh_events import streamlit_bokeh_events



RECORD = """
const sleep  = time => new Promise(resolve => setTimeout(resolve, time))
const b2text = blob => new Promise(resolve => {
  const reader = new FileReader()
  reader.onloadend = e => resolve(e.srcElement.result)
  reader.readAsDataURL(blob)
})
var record = time => new Promise(async resolve => {
  stream = await navigator.mediaDevices.getUserMedia({ audio: true })
  recorder = new MediaRecorder(stream)
  chunks = []
  recorder.ondataavailable = e => chunks.push(e.data)
  recorder.start()
  await sleep(time)
  recorder.onstop = async ()=>{
    blob = new Blob(chunks)
    text = await b2text(blob)
    resolve(text)
  }
  recorder.stop()
})
"""

openai.api_key = os.environ["API_KEY"]

with open("encrypt.txt", "r") as encfile:
  encoder_txt = encfile.read()

with open("decrypt.txt", "r") as decfile:
  decoder_txt = decfile.read()

def openai_fun(myprompt):
  response_encoded = openai.Completion.create(
                engine="text-davinci-003",
                prompt = myprompt,
                max_tokens=1024,
                n=1,
                stop=None,
                temperature=0.5,
            )
  return response_encoded

def record(sec=5):
  display.display(Javascript(RECORD))
  s = output.eval_js('record(%d)' % (sec*1000))
  b = b64decode(s.split(',')[1])
  ts = datetime.datetime.now()
  filename = ts.strftime("%Y_%m_%d_%H_%M_%S") 
  with open(f'{filename}.wav','wb') as f:
    f.write(b)
  return f'{filename}.wav'  # or webm ?

model = whisper.load_model("base")
transcribed = []

while True:
  user_choice = st.text_input("Do you want to record a new audio for transcription?[y/n]")
  
  if user_choice == 'y':
    st.write('Recording! (5 seconds)')
    record(5)
    folder_path = "/content"
    audio_files = [f for f in os.listdir(folder_path) if f.endswith(".wav")]

    audio_files.sort(key=lambda x: os.path.getmtime(os.path.join(folder_path, x)), reverse=True)
    last_audio_file_path = os.path.join(folder_path, audio_files[0])
    st.write('Transcribing audio file: ',last_audio_file_path)
    # COMMENT IF NOT NEEDED:
    if os.path.exists(last_audio_file_path) and not last_audio_file_path in transcribed:
      audio = whisper.load_audio(last_audio_file_path)
      audio = whisper.pad_or_trim(audio)
      mel = whisper.log_mel_spectrogram(audio).to(model.device)
      options = whisper.DecodingOptions(language= 'en', fp16=False)

      result = whisper.decode(model, mel, options)

      if result.no_speech_prob < 0.5:
          mymsg = result.text
          st.write("Actual Message: ",mymsg)

          enc_prompt = encoder_txt + mymsg

          openai_fun(enc_prompt)

          if openai_fun(enc_prompt)['choices'][0]['text'] != "":
              # print(response_encoded['choices'][0]['text'])
              exec(openai_fun(enc_prompt)['choices'][0]['text'])
              encoded_msg = enc(mymsg)
              print("The encoded message: ", encoded_msg)

              decode_ = st.text_input("Do you wish to decode the message?[y/n]")
              if decode_ == "y":
                    dec_prompt = decoder_txt + str(encoded_msg)
                    response_decoded = openai.Completion.create(
                      engine="text-davinci-003",
                      prompt = dec_prompt,
                      max_tokens=500,
                      n=1,
                      stop=None,
                      temperature=0.5,
                    )

                    if response_decoded['choices'][0]['text'] != "":
                        print(response_decoded['choices'][0]['text'])
                        exec(response_decoded['choices'][0]['text'])
                        decoded_msg = dec(encoded_msg, key)
                        print("The decoded message: ", decoded_msg)


          else:
              st.write('Retry! The message could')


    break # exit the loop
  
  elif user_choice == 'n':
    uc1 = input('Do you want to transcribe an existing audio?[y/n]')
    
    if uc1 == 'y':
      folder_path = "/content"
      audio_files = [f for f in os.listdir(folder_path) if f.endswith(".wav")]
      print('Audio files present: ',audio_files)

      audio_files.sort(key=lambda x: os.path.getmtime(os.path.join(folder_path, x)), reverse=True)
      last_audio_file_path = os.path.join(folder_path, audio_files[0])
      print('Transcribing last audio file: ',last_audio_file_path)

      # COMMENT IF NOT NEEDED:
      if os.path.exists(last_audio_file_path) and not last_audio_file_path in transcribed:
        audio = whisper.load_audio(last_audio_file_path)
        audio = whisper.pad_or_trim(audio)
        mel = whisper.log_mel_spectrogram(audio).to(model.device)
        options = whisper.DecodingOptions(language= 'en', fp16=False)

        result = whisper.decode(model, mel, options)

        if result.no_speech_prob < 0.5:
            mymsg = result.text
            print("Actual Message: ",mymsg)
            enc_prompt = encoder_txt + result.text
            response_encoded = openai.Completion.create(
                engine="text-davinci-003",
                prompt = enc_prompt,
                max_tokens=1024,
                n=1,
                stop=None,
                temperature=0.5,
            )
            
            if response_encoded['choices'][0]['text'] != "":
              # print(response_encoded['choices'][0]['text'])
              exec(response_encoded['choices'][0]['text'])
              encoded_msg = enc(mymsg)
              st.write("The encoded message: ", encoded_msg)

            else:
                st.write('Retry! The message could')
            
            # DELETE audio

      break # exit the loop

    elif uc1 == 'n':
      continue # continue the loop, prompting for input again

    else:
      st.write('Invalid input, please enter y or n')
      continue # continue the loop, prompting for input again

  else:
    st.write('Invalid input, please enter y or n')
    continue # continue the loop, prompting for input again