Update app.py

app.py

@@ -1,23 +1,27 @@
 import gradio as gr
 import whisper
-import subprocess
-import os
 from pytube import YouTube
 from fastapi import FastAPI, Response, Request
 import yt_dlp
+import uvicorn
+
+CUSTOM_PATH = "/"
+
+app = FastAPI()
 
 langs = ["None"] + sorted(list(whisper.tokenizer.LANGUAGES.values()))
 model_size = list(whisper._MODELS.keys())
 
 
-@app.get("/subtitle")
-async def get_subtitle(url: str):
+
+#async def get_subtitle(url: str):
     # Download the subtitle with download_subtitle()
-    subtitle_url = download_subtitle(url)
+    #subtitle_url = download_subtitle(url)
     # Stream the subtitle as a response
-    return StreamingResponse(requests.get(subtitle_url, stream=True).iter_content(chunk_size=1024))
+    #return StreamingResponse(requests.get(subtitle_url, stream=True).iter_content(chunk_size=1024))
 
-def get_subtitle(url, lang='en'):
+@app.get("/subtitle")
+async def get_subtitle(url, lang='en'):
     # Download subtitles if available
     ydl_opts = {
         'writesubtitles': True,
@@ -98,29 +102,33 @@ def format_timestamp(t):
     mi = (t - int(t))*1000
     return f"{int(hh):02d}:{int(mm):02d}:{int(ss):02d},{int(mi):03d}"
 
+def gradio_interface():
+    with gr.Blocks() as demo:
+    
+        with gr.Row():
+    
+            with gr.Column():
+    
+                with gr.Row():
+                    url = gr.Textbox(placeholder='Youtube video URL', label='URL')
+    
+                with gr.Row():
+    
+                    model_size = gr.Dropdown(choices=model_size, value='tiny', label="Model")
+                    lang = gr.Dropdown(choices=langs, value="None", label="Language (Optional)")
+                    format = gr.Dropdown(choices=["None", ".srt"], value="None", label="Timestamps? (Optional)")
+    
+                with gr.Row():
+                    gr.Markdown("Larger models are more accurate, but slower. For 1min video, it'll take ~30s (tiny), ~1min (base), ~3min (small), ~5min (medium), etc.")
+                    transcribe_btn = gr.Button('Transcribe')
+    
+            with gr.Column():
+                outputs = gr.Textbox(placeholder='Transcription of the video', label='Transcription')
+    
+        transcribe_btn.click(get_transcript, inputs=[url, model_size, lang, format], outputs=outputs)
 
-with gr.Blocks() as demo:
-
-    with gr.Row():
-
-        with gr.Column():
-
-            with gr.Row():
-                url = gr.Textbox(placeholder='Youtube video URL', label='URL')
-
-            with gr.Row():
-
-                model_size = gr.Dropdown(choices=model_size, value='tiny', label="Model")
-                lang = gr.Dropdown(choices=langs, value="None", label="Language (Optional)")
-                format = gr.Dropdown(choices=["None", ".srt"], value="None", label="Timestamps? (Optional)")
-
-            with gr.Row():
-                gr.Markdown("Larger models are more accurate, but slower. For 1min video, it'll take ~30s (tiny), ~1min (base), ~3min (small), ~5min (medium), etc.")
-                transcribe_btn = gr.Button('Transcribe')
-
-        with gr.Column():
-            outputs = gr.Textbox(placeholder='Transcription of the video', label='Transcription')
-
-    transcribe_btn.click(get_transcript, inputs=[url, model_size, lang, format], outputs=outputs)
+#demo.launch(debug=True)
+io = gr.Interface(gradio_interface)
 
-demo.launch(debug=True)
+app = gr.mount_gradio_app(app, io, path=CUSTOM_PATH)
+uvicorn.run(app, host="0.0.0.0", port=7860)