Update app.py

app.py

@@ -1,10 +1,9 @@
 import torch
 import gradio as gr
-import pytube as pt
 from transformers import pipeline
 
 MODEL_NAME = "BlueRaccoon/whisper-small-kab"  # this always needs to stay in line 8 :D sorry for the hackiness
-lang = "uz"
+lang = "kab"  # Language updated to Kabyle
 
 device = 0 if torch.cuda.is_available() else "cpu"
 pipe = pipeline(
@@ -17,77 +16,30 @@ pipe = pipeline(
 pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(language=lang, task="transcribe")
 
 
-def transcribe(microphone, file_upload):
-    warn_output = ""
-    if (microphone is not None) and (file_upload is not None):
-        warn_output = (
-            "WARNING: You've uploaded an audio file and used the microphone. "
-            "The recorded file from the microphone will be used and the uploaded audio will be discarded.\n"
-        )
-
-    elif (microphone is None) and (file_upload is None):
-        return "ERROR: You have to either use the microphone or upload an audio file"
-
-    file = microphone if microphone is not None else file_upload
-
-    text = pipe(file)["text"]
-
-    return warn_output + text
-
-
-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)
-    stream = yt.streams.filter(only_audio=True)[0]
-    stream.download(filename="audio.mp3")
+def transcribe(microphone):
+    if microphone is None:
+        return "ERROR: You need to record or upload an audio file."
 
-    text = pipe("audio.mp3")["text"]
-
-    return html_embed_str, text
+    text = pipe(microphone)["text"]
+    return text
 
 
 with gr.Blocks() as demo:
-    with gr.Tab("Transcribe Audio"):
+    with gr.Tab("Transcribe Kabyle Audio"):
         gr.Markdown(
             f"""
-            # Whisper Demo: Transcribe Audio
-            Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the fine-tuned
-            checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files
-            of arbitrary length.
+            # Kabyle Whisper Demo: Transcribe Audio
+            Transcribe Kabyle audio recorded from the microphone or uploaded as a file. This demo uses the fine-tuned
+            checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe Kabyle audio
+            files of arbitrary length.
             """
         )
-        # Inputs for microphone recording or file upload
-        microphone_input = gr.Audio(type="filepath", label="Record or Upload Audio")
-        file_upload_input = gr.Audio(type="filepath", label="Upload Audio File (Optional)")
+        # Input for microphone recording only
+        microphone_input = gr.Audio(type="filepath", label="Record or Upload Kabyle Audio")
         gr.Interface(
             fn=transcribe,
-            inputs=[microphone_input, file_upload_input],
+            inputs=[microphone_input],
             outputs=gr.Textbox(label="Transcription"),
         )
 
-    with gr.Tab("Transcribe YouTube"):
-        gr.Markdown(
-            f"""
-            # Whisper Demo: Transcribe YouTube
-            Transcribe long-form YouTube videos with the click of a button! Demo uses the fine-tuned checkpoint
-            [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files of
-            arbitrary length.
-            """
-        )
-        yt_url_input = gr.Textbox(lines=1, placeholder="Paste the URL to a YouTube video here", label="YouTube URL")
-        gr.Interface(
-            fn=yt_transcribe,
-            inputs=[yt_url_input],
-            outputs=[gr.HTML(label="YouTube Video"), gr.Textbox(label="Transcription")],
-        )
-
 demo.launch()