youtube links

app.py

@@ -1,14 +1,47 @@
 from transformers import pipeline
 import gradio as gr
+from youtube_dl import YoutubeDL
 
-model = pipeline(model="SofiaK/checkpoints")
 
-iface = gr.Interface(
-    fn=lambda audio: model(audio)["text"],
-    inputs=gr.Audio(sources=["upload", "microphone"], type="filepath"),
+# Function to download audio from YouTube link
+def download_audio(youtube_link, output_path):
+    ydl_opts = {
+        "format": "bestaudio/best",
+        "outtmpl": output_path,
+        "postprocessors": [
+            {
+                "key": "FFmpegExtractAudio",
+                "preferredcodec": "mp3",
+                "preferredquality": "192",
+            }
+        ],
+    }
+    with YoutubeDL(ydl_opts) as ydl:
+        ydl.download([youtube_link])
+
+
+# Function to transcribe audio
+def transcribe_audio(audio_path):
+    model = pipeline(model="SofiaK/checkpoints")
+    return model(audio_path)["text"]
+
+
+interface = gr.Interface(
+    fn=lambda input_type, audio_or_link: transcribe_audio(audio_or_link)
+    if input_type == "audio"
+    else transcribe_audio(download_audio(audio_or_link, "temp.mp3")),
+    inputs=[
+        gr.Radio(["audio", "youtube"], label="Select Input Type"),
+        gr.Audio(
+            sources=["upload", "microphone"],
+            type="filepath",
+            label="Upload Audio, or speak in the microphone",
+        ),
+        gr.Textbox(default="https://www.youtube.com/", label="Youtube Link"),
+    ],
     outputs=gr.Text(label="Model output"),
     title="Whisper-RU",
     description="Fine-tuned Whisper for Russian language",
 )
 
-iface.launch()
+interface.launch(share=True)