Update main.py

main.py

@@ -1,51 +1,130 @@
 import whisper
 import yt_dlp
 import gradio as gr
+import os
 
-def yt_download(link):
+def youtube_(link):
     if not link.strip():
         gr.Info("You need to provide a download link.")
         print("You need to provide a download link")
         return None
-    ydl_opts = {
-        'format': 'bestaudio',
-        'outtmpl': '%(title)s',
-        'nocheckcertificate': True,
-        'ignoreerrors': True,
-        'no_warnings': True,
-        'quiet': True,
-        'extractaudio': True,
-        'postprocessors': [{'key': 'FFmpegExtractAudio', 'preferredcodec': 'wav'}],
-        'postprocessor_args': [
-            '-acodec', 'pcm_f32le'
-        ],
-    }
-    with yt_dlp.YoutubeDL(ydl_opts) as ydl:
-        result = ydl.extract_info(link, download=True)
-        download_path = ydl.prepare_filename(result, outtmpl='%(title)s.wav')
-        
-    return download_path
-
+    
+    try:
+        ydl_opts = {
+            'format': 'bestaudio/best',
+            'outtmpl': '%(title)s.%(ext)s',
+            'nocheckcertificate': True,
+            'ignoreerrors': True,
+            'no_warnings': True,
+            'quiet': True,
+            'extractaudio': True,
+            'postprocessors': [{
+                'key': 'FFmpegExtractAudio',
+                'preferredcodec': 'wav',
+                'preferredquality': '192',
+            }],
+        }
+        with yt_dlp.YoutubeDL(ydl_opts) as ydl:
+            result = ydl.extract_info(link, download=True)
+            download_path = ydl.prepare_filename(result, outtmpl='%(title)s.wav')
+            
+        return download_path
+    
+    except Exception as e:
+        gr.Error(f"Error downloading video: {str(e)}")
+        print(f"Error: {e}")
+        return None
 
 def whisper_(input_audio):
-    model = whisper.load_model("medium")
+    try:
+        model = whisper.load_model("base")  # Using base for faster demo, change to "medium" if needed
+        
+        # Transcribe the audio
+        result = model.transcribe(input_audio)
+        
+        text_result = result["text"]
+        language = result["language"]
+        
+        print(f"Detected language: {language}")
+        print(f"Transcription: {text_result}")
+        
+        return text_result
     
-    # load audio and pad/trim it to fit 30 seconds
-    audio = whisper.load_audio(input_audio)
-    audio = whisper.pad_or_trim(audio)
-    # make log-Mel spectrogram and move to the same device as the model
-    mel = whisper.log_mel_spectrogram(audio, n_mels=model.dims.n_mels).to(model.device)
+    except Exception as e:
+        gr.Error(f"Error during transcription: {str(e)}")
+        print(f"Error: {e}")
+        return None
+
+def transcribe(url_audio):
+    # Download audio from YouTube
+    audio_path = youtube_(url_audio)
+    
+    if audio_path is None:
+        return "Failed to download audio. Please check the URL and try again."
     
-    # detect the spoken language
-    _, probs = model.detect_language(mel)
-    print(f"Detected language: {max(probs, key=probs.get)}")
+    # Transcribe the audio
+    result = whisper_(audio_path)
     
-    # decode the audio
-    options = whisper.DecodingOptions()
-    result = whisper.decode(model, mel, options)
-    # print the recognized text
+    # Clean up downloaded file
+    try:
+        if os.path.exists(audio_path):
+            os.remove(audio_path)
+    except:
+        pass
     
-    text_result = result.text
-    return text_result
+    if result is None:
+        return "Failed to transcribe audio. Please try again."
     
-    
+    return result
+
+# Gradio interface
+with gr.Blocks(title="YouTube Audio Transcriber") as demo:
+    gr.Markdown("""
+    # 🎙️ YouTube Audio Transcriber
+    Enter a YouTube URL and get the audio transcribed using Whisper AI.
+    """)
+    
+    with gr.Row():
+        with gr.Column(scale=4):
+            url_input = gr.Textbox(
+                label="YouTube URL",
+                placeholder="https://www.youtube.com/watch?v=...",
+                lines=2
+            )
+            transcribe_btn = gr.Button("Transcribe", variant="primary", size="lg")
+        
+        with gr.Column(scale=5):
+            output_text = gr.Textbox(
+                label="Transcription",
+                lines=10,
+                placeholder="The transcribed text will appear here...",
+                interactive=False
+            )
+    
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("""
+            ### ⚡ Tips:
+            - Works with most YouTube videos
+            - Supports multiple languages
+            - Audio is automatically downloaded and processed
+            - Processing may take a few seconds depending on video length
+            """)
+    
+    # Wire up the function
+    transcribe_btn.click(
+        fn=transcribe,
+        inputs=url_input,
+        outputs=output_text
+    )
+    
+    # Also support Enter key
+    url_input.submit(
+        fn=transcribe,
+        inputs=url_input,
+        outputs=output_text
+    )
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch(share=True)