Update app.py

app.py

@@ -1,4 +1,7 @@
 import streamlit as st
+import gradio as gr
+import os
+from gradio_client import Client
 
 
 with st.sidebar: 
@@ -24,3 +27,60 @@ if choice == "Events":
 
 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)
+    
+