Update app.py

app.py

@@ -1,86 +1,30 @@
 import streamlit as st
-import gradio as gr
-import os
-from gradio_client import Client
+from transformers import pipeline
 
+# Initialize the transcription pipeline
+transcribe = pipeline(model="openai/whisper-large-v2")
 
-with st.sidebar: 
-    st.image("https://www.onepointltd.com/wp-content/uploads/2020/03/inno2.png")
-    st.title("Campus Comrade Assistant")
-    choice = st.radio("Navigation", ["Home/about","Meal Suggester","Accomodation available", "Assignment assist", "Events", "Transcribe, audio to Text"])
-    st.info("This project application helps you accomplish both major and minor tasks efficiently.")
+# Streamlit page configuration
+st.title("Transcription Service")
+st.write("Upload a YouTube URL or an audio file to transcribe.")
 
-if choice == "Home/about":
-    st.title("Welcome to Campus Comrade Assitant")
-    
-if choice == "Meal Suggester": 
-    st.title("Time to Eat")
+# Input: YouTube URL or Audio File
+url = st.text_input("Enter YouTube URL:")
+audio_file = st.file_uploader("Or upload an audio file (mp3, wav):")
 
-if choice == "Accomodation available":
-    st.title("Ready to Move in?")
+if url:
+    # Process the YouTube URL and extract audio for transcription
+    # Note: You'll need to implement the extraction of audio from YouTube URL
+    st.write("Transcribing from YouTube URL...")
+    # audio_data = extract_audio_from_url(url) # Placeholder for actual extraction function
+    # transcription = transcribe(audio_data)
+    # st.write(transcription)
+    st.write("YouTube URL transcription is not implemented yet.")
+elif audio_file:
+    # Process the uploaded audio file for transcription
+    st.write("Transcribing from uploaded audio file...")
+    transcription = transcribe(audio_file.getvalue())
+    st.write(transcription)
 
-if choice == "Assignment assist": 
-    st.title("Let's complete that assignment")
-    
-if choice == "Events": 
-    st.title("Collaborate and Jazz. Events around You")
+st.write("Thank you for using our service!")
 
-if choice == "Transcribe, audio to Text": 
-    st.title("Tired of listening long audio? convert to Text")
-    
-    def transcribe_audio(youtube_url: str, task: str = "transcribe", return_timestamps: bool = False, api_name: str = "/predict_2") -> dict:
-        """
-        Transcribe audio from a given YouTube URL using a specified model.
-        Parameters:
-        - youtube_url (str): The YouTube URL to transcribe.
-        - task (str, optional): The task to perform. Default is "transcribe".
-        - return_timestamps (bool, optional): Whether to return timestamps. Default is True.
-        - api_name (str, optional): The API endpoint to use. Default is "/predict_2".
-        Returns:
-        - dict: The transcription result.
-        """
-        client = Client("https://sanchit-gandhi-whisper-jax.hf.space/")
-        result = client.predict(youtube_url, task, return_timestamps, fn_index=7)
-        return result
-    
-    
-    
-    MODEL_NAME = "openai/whisper-large-v2"
-    
-    
-    demo = gr.Blocks()
-    
-    EXAMPLES = [
-        ["https://www.youtube.com/watch?v=H1YoNlz2LxA", "translate",False],
-    ]
-    
-    
-    yt_transcribe = gr.Interface(
-        fn=transcribe_audio,
-        inputs=[
-            gr.inputs.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL"),
-            gr.inputs.Radio(["transcribe", "translate"], label="Task", default="transcribe"),
-            gr.inputs.Checkbox(label="Return timestamps")
-        ],
-        outputs=[gr.outputs.HTML(label="Video"),
-            gr.outputs.Textbox(label="Transcription").style(show_copy_button=True)],
-        layout="horizontal",
-        theme=gr.themes.Base(),
-        title="Whisper Large V2: Transcribe YouTube",
-        description=(
-            "Transcribe long-form YouTube videos with the click of a button! Demo uses the checkpoint"
-            f" [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe video files of"
-            " arbitrary length."
-        ),
-        allow_flagging="never",
-        examples=EXAMPLES,
-        cache_examples=False
-    )
-    
-    with demo:
-        gr.DuplicateButton()
-        gr.TabbedInterface([yt_transcribe], [ "YouTube"])
-    
-    demo.launch(enable_queue=True)
-    
-