Update app.py

app.py

@@ -1,61 +1,46 @@
+import whisper
 from pytube import YouTube
 from transformers import pipeline
-import streamlit as st
+import gradio as gr
 import os
 
 model = whisper.load_model("base")
 summarizer = pipeline("summarization")
 
-def get_audio_from_video(file_path):
-    # You can use a library like moviepy or ffmpeg to extract audio from the video
-    # For simplicity, I'm assuming the video is already in a format that the model can transcribe
-    return file_path
-
 def get_audio(url):
-    yt = YouTube(url)
-    video = yt.streams.filter(only_audio=True).first()
-    out_file = video.download(output_path=".")
-    base, ext = os.path.splitext(out_file)
-    new_file = base + '.mp3'
-    os.rename(out_file, new_file)
-    return new_file
-
-def get_text(url=None, file_path=None):
-    if url:
-        result = model.transcribe(get_audio(url))
-    elif file_path:
-        result = model.transcribe(get_audio_from_video(file_path))
-    return result['text']
-
-def get_summary(url=None, file_path=None):
-    article = get_text(url, file_path)
-    b = summarizer(article)
-    b = b[0]['summary_text']
-    return b
-
-st.title("Youtube video transcription with OpenAI's Whisper")
-st.write("Enter the link of any youtube video or upload a video file to get the transcription and a summary in the form of text.")
-
-option = st.radio('Choose an option', ['Get the transcription of any Youtube video', 'Summary of Youtube video', 'Upload a video file'])
-
-if option == 'Get the transcription of any Youtube video':
-    url1 = st.text_input('Enter the Youtube video URL')
-    if st.button('Get Transcription'):
-        transcription = get_text(url1)
-        st.text_area('Transcription of the video', transcription)
-
-elif option == 'Summary of Youtube video':
-    url2 = st.text_input('Enter the Youtube video URL')
-    if st.button('Get Summary'):
-        summary = get_summary(url2)
-        st.text_area('Summary text of the Youtube Video', summary)
-
-elif option == 'Upload a video file':
-    uploaded_file = st.file_uploader("Choose a video file", type=["mp4"])
-    if uploaded_file:
-        video_path = "temp_video_file.mp4"
-        with open(video_path, "wb") as f:
-            f.write(uploaded_file.getvalue())
-        if st.button('Transcribe Uploaded Video'):
-            transcription = get_text(file_path=video_path)
-            st.text_area('Transcription of the uploaded video file', transcription)
+  yt = YouTube(url)
+  video = yt.streams.filter(only_audio=True).first()
+  out_file=video.download(output_path=".")
+  base, ext = os.path.splitext(out_file)
+  new_file = base+'.mp3'
+  os.rename(out_file, new_file)
+  a = new_file
+  return a
+
+def get_text(url):
+  result = model.transcribe(get_audio(url))
+  return result['text']
+
+def get_summary(url):
+  article = get_text(url)
+  b = summarizer(article)
+  b = b[0]['summary_text']
+  return b
+  
+with gr.Blocks() as demo:
+  gr.Markdown("<h1><center>Youtube video transcription with OpenAI's Whisper</center></h1>")
+  gr.Markdown("<center>Enter the link of any youtube video to get the transcription of the video and a summary of the video in the form of text.</center>")
+  with gr.Tab('Get the transcription of any Youtube video'):
+    with gr.Row():
+      input_text_1 = gr.Textbox(placeholder='Enter the Youtube video URL', label='URL')
+      output_text_1 = gr.Textbox(placeholder='Transcription of the video', label='Transcription')
+    result_button_1 = gr.Button('Get Transcription')
+  with gr.Tab('Summary of Youtube video'):
+    with gr.Row():
+      input_text = gr.Textbox(placeholder='Enter the Youtube video URL', label='URL')
+      output_text = gr.Textbox(placeholder='Summary text of the Youtube Video', label='Summary')
+    result_button = gr.Button('Get Summary')
+
+  result_button.click(get_summary, inputs = input_text, outputs = output_text)
+  result_button_1.click(get_text, inputs = input_text_1, outputs = output_text_1)
+demo.launch(debug=True)