# Your app.py goes here
# Program title: ______________


# import part
import streamlit as st
from transformers import pipeline


# function part - FOUR functions


# function part
# img2text
def img2text(url):
    image_to_text_model = pipeline("image-to-text", model="Salesforce/blip-image-captioning-base")
    text = image_to_text_model(url)[0]["generated_text"]
    return text

# text2story
def text2story(text):
    pipe = pipeline("text-generation", model="pranavpsv/genre-story-generator-v2")
    story_text = pipe(text)[0]['generated_text']
    return story_text

# text2audio
def text2audio(story_text):
    pipe = pipeline("text-to-audio", model="Matthijs/mms-tts-eng")
    audio_data = pipe(story_text)
    return audio_data

def main():
  st.set_page_config(page_title="Your Image to Audio Story",
                   page_icon="🦜")
  st.header("Turn Your Image to Audio Story")
  uploaded_file = st.file_uploader("Select an Image...")

  if uploaded_file is not None:
      print(uploaded_file)
      bytes_data = uploaded_file.getvalue()
      with open(uploaded_file.name, "wb") as file:
          file.write(bytes_data)
      st.image(uploaded_file, caption="Uploaded Image",
              use_column_width=True)

      #Stage 1: Image to Text
      st.text('Processing img2text...')
      scenario = img2text(uploaded_file.name)
      st.write(scenario)

      #Stage 2: Text to Story
      st.text('Generating a story...')
      story = text2story(scenario)
      st.write(story)

      #Stage 3: Story to Audio data
      st.text('Generating audio data...')
      audio_data =text2audio(story)

      # Play button
      if st.button("Play Audio"):
          st.audio(audio_data['audio'],
                      format="audio/wav",
                      start_time=0,
                      sample_rate = audio_data['sampling_rate'])

# main program part
if __name__ == "__main__":
    main()