create tabbed interface for video and audio

app.py

@@ -5,17 +5,33 @@ def main():
     with gr.Blocks(title='multilang-asr-transcriber', delete_cache=(86400, 86400), theme=gr.themes.Base()) as demo:
         gr.Markdown('## Multilang ASR Transcriber')
         gr.Markdown('An automatic speech recognition tool using [faster-whisper](https://github.com/SYSTRAN/faster-whisper). Supports multilingual video transcription and translation to english. Users may set the max words per line.')
-        file = gr.File(file_types=["video", "audio"],type="filepath", label="Upload video or audio")
-        max_words_per_line = gr.Number(value=6, label="Max words per line")
-        task = gr.Radio(choices=["transcribe", "translate"], value="transcribe", label="Select Task")
-        model_version = gr.Radio(choices=["deepdml/faster-whisper-large-v3-turbo-ct2", "large-v3"], value="deepdml/faster-whisper-large-v3-turbo-ct2", label="Select Model")
-        text_output = gr.Textbox(label="SRT Text transcription", show_copy_button=True)
-        srt_file = gr.File(file_count="single", type="filepath", file_types=[".srt"], label="SRT file")
-        text_clean_output = gr.Textbox(label="Text transcription", show_copy_button=True)
-        gr.Interface(transcriber,
-                    inputs=[file, max_words_per_line, task, model_version],
-                    outputs=[text_output, srt_file, text_clean_output],
-                    allow_flagging="never")
+
+        with gr.Tab("Video"):
+            file = gr.File(file_types=["video"],type="filepath", label="Upload a video")
+            video = True
+            max_words_per_line = gr.Number(value=6, label="Max words per line")
+            task = gr.Radio(choices=["transcribe", "translate"], value="transcribe", label="Select Task")
+            model_version = gr.Radio(choices=["deepdml/faster-whisper-large-v3-turbo-ct2", "large-v3"], value="deepdml/faster-whisper-large-v3-turbo-ct2", label="Select Model")
+            text_output = gr.Textbox(label="SRT Text transcription", show_copy_button=True)
+            srt_file = gr.File(file_count="single", type="filepath", file_types=[".srt"], label="SRT file")
+            text_clean_output = gr.Textbox(label="Text transcription", show_copy_button=True)
+            gr.Interface(transcriber,
+                        inputs=[file, video, max_words_per_line, task, model_version],
+                        outputs=[text_output, srt_file, text_clean_output],
+                        allow_flagging="never")
+        
+        with gr.Tab("Audio"):
+            file = gr.File(file_types=["audio"],type="filepath", label="Upload an audio file")
+            max_words_per_line = gr.Number(value=6, label="Max words per line")
+            task = gr.Radio(choices=["transcribe", "translate"], value="transcribe", label="Select Task")
+            model_version = gr.Radio(choices=["deepdml/faster-whisper-large-v3-turbo-ct2", "large-v3"], value="deepdml/faster-whisper-large-v3-turbo-ct2", label="Select Model")
+            text_output = gr.Textbox(label="SRT Text transcription", show_copy_button=True)
+            srt_file = gr.File(file_count="single", type="filepath", file_types=[".srt"], label="SRT file")
+            text_clean_output = gr.Textbox(label="Text transcription", show_copy_button=True)
+            gr.Interface(transcriber,
+                        inputs=[file, video, max_words_per_line, task, model_version],
+                        outputs=[text_output, srt_file, text_clean_output],
+                        allow_flagging="never")
     demo.launch()
 
 if __name__ == '__main__':