Update app.py

app.py

@@ -4,16 +4,26 @@ import pytube as pt
 from transformers import pipeline
 from huggingface_hub import model_info
 
+
 transcribe_model_ckpt = "openai/whisper-small"
 lang = "en"
-
+device = 0 if torch.cuda.is_available() else "cpu"
 transcribe_pipe = pipeline(
     task="automatic-speech-recognition",
     model=transcribe_model_ckpt,
     chunk_length_s=30,
+    device=device,
 )
 transcribe_pipe.model.config.forced_decoder_ids = transcribe_pipe.tokenizer.get_decoder_prompt_ids(language=lang, task="transcribe")
 
+def _return_yt_html_embed(yt_url):
+    video_id = yt_url.split("?v=")[-1]
+    HTML_str = (
+        f'<center> <iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"> </iframe>'
+        " </center>"
+    )
+    return HTML_str
+
 def yt_transcribe(yt_url):
     yt = pt.YouTube(yt_url)
     html_embed_str = _return_yt_html_embed(yt_url)
@@ -48,22 +58,15 @@ with gr.Blocks() as demo:
                     D -->E[Answer]
                     """)
     with gr.Column():
-        with gr.Row():
-            in_yt = gr.inputs.Textbox(lines=1, placeholder="Enter Youtube URL", label="YouTube URL")
-        with gr.Row():
-            transcribe_btn = gr.Button("Trascribe")
+        in_yt = gr.inputs.Textbox(lines=1, placeholder="Enter Youtube URL", label="YouTube URL")
+        transcribe_btn = gr.Button("Trascribe")
     with gr.Column():
-        with gr.Row():
-            out_yt_html = gr.outputs.HTML()
-        with gr.Row():
-            out_yt_text = gr.Textbox()
+        out_yt_html = gr.outputs.HTML()
+        out_yt_text = gr.Textbox()
     with gr.Column():
-        with gr.Row():
-            in_query = gr.Textbox(lines=1, placeholder="What's your Question", label="Query")
-        with gr.Row():
-            ans_btn = gr.Button("Answer")
-        with gr.Row():
-            out_query = gr.outputs.Textbox()
+        in_query = gr.Textbox(lines=1, placeholder="What's your Question", label="Query")
+        ans_btn = gr.Button("Answer")
+        out_query = gr.outputs.Textbox()
             
     
     transcribe_btn.click(fn=yt_transcribe, inputs=in_yt, outputs=[out_yt_html,out_yt_text])