Update app.py

app.py

@@ -20,46 +20,60 @@ pipelines['a'].g2p.lexicon.golds['kokoro'] = 'kˈOkəɹO'
 
 def text_to_audio(text, speed=1.0):
     """Convert text to audio using Kokoro model.
+    
     Args:
         text: The text to convert to speech
         speed: Speech speed multiplier (0.5-2.0, where 1.0 is normal speed)
-            Returns:
+        
+    Returns:
         Audio data as a tuple of (sample_rate, audio_array)
     """
     if not text:
         return None
+    
     pipeline = pipelines['a']  # Use English pipeline
     voice = "af_heart"  # Default voice (US English, female, Heart)
+    
     # Process the text
     pack = pipeline.load_voice(voice)
+    
     for _, ps, _ in pipeline(text, voice, speed):
         ref_s = pack[len(ps)-1]
+        
         # Generate audio
         try:
             audio = model(ps, ref_s, speed)
         except Exception as e:
             raise gr.Error(f"Error generating audio: {str(e)}")
+        
         # Return the audio with 24kHz sample rate
         return 24000, audio.numpy()
+    
     return None
 
 def text_to_audio_b64(text, speed=1.0):
     """Convert text to audio and return as base64 encoded WAV file.
+    
     Args:
         text: The text to convert to speech
         speed: Speech speed multiplier (0.5-2.0, where 1.0 is normal speed)
+        
     Returns:
         Base64 encoded WAV file as a string
     """
     import soundfile as sf
+    
     result = text_to_audio(text, speed)
     if result is None:
         return None
+    
     sample_rate, audio_data = result
+    
     # Save to BytesIO object
     wav_io = io.BytesIO()
     sf.write(wav_io, audio_data, sample_rate, format='WAV')
     wav_io.seek(0)
+    
     # Convert to base64
     wav_b64 = base64.b64encode(wav_io.read()).decode('utf-8')
     return wav_b64
@@ -68,64 +82,60 @@ def text_to_audio_b64(text, speed=1.0):
 with gr.Blocks(title="Kokoro Text-to-Audio MCP") as app:
     gr.Markdown("# 🎵 Kokoro Text-to-Audio MCP")
     gr.Markdown("Convert text to speech using the Kokoro-82M model")
-    # Tab for Kokoro Text-to-Audio
-    with gr.Tab("Kokoro Text-to-Audio"):
-        with gr.Row():
-            with gr.Column():
-                text_input = gr.Textbox(
-                    label="Enter your text",
-                    placeholder="Type something to convert to audio...",
-                    lines=5
-                )
-                speed_slider = gr.Slider(
-                    minimum=0.5,
-                    maximum=2.0,
-                    value=1.0,
-                    step=0.1,
-                    label="Speech Speed"
-                )
-                submit_btn = gr.Button("Generate Audio")
-            with gr.Column():
-                audio_output = gr.Audio(label="Generated Audio", type="numpy")
-        submit_btn.click(
-            fn=text_to_audio,
-            inputs=[text_input, speed_slider],
-            outputs=[audio_output]
-        )
-        gr.Markdown("---") # Horizontal line for separation
-        gr.Markdown("### Usage Tips")
-        gr.Markdown("- Adjust the speed slider to modify the pace of speech")
-        # Add section about MCP support
-        with gr.Accordion("MCP Support (for LLMs)", open=False):
-            gr.Markdown("""
-            ### MCP Support
-            This app supports the Model Context Protocol (MCP), allowing Large Language Models like Claude Desktop to use it as a tool.
-            To use this app with an MCP client, add the following configuration:
-            ```json
-            {
-              "mcpServers": {
-                "kokoroTTS": {
-                  "url": "[https://fdaudens-kokoro-mcp.hf.space/gradio_api/mcp/sse](https://fdaudens-kokoro-mcp.hf.space/gradio_api/mcp/sse)"
-                }
-              }
+    
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(
+                label="Enter your text",
+                placeholder="Type something to convert to audio...",
+                lines=5
+            )
+            speed_slider = gr.Slider(
+                minimum=0.5,
+                maximum=2.0,
+                value=1.0,
+                step=0.1,
+                label="Speech Speed"
+            )
+            submit_btn = gr.Button("Generate Audio")
+        
+        with gr.Column():
+            audio_output = gr.Audio(label="Generated Audio", type="numpy")
+    
+    submit_btn.click(
+        fn=text_to_audio,
+        inputs=[text_input, speed_slider],
+        outputs=[audio_output]
+    )
+    
+    gr.Markdown("### Usage Tips")
+    gr.Markdown("- Adjust the speed slider to modify the pace of speech")
+    
+    # Add section about MCP support
+    with gr.Accordion("MCP Support (for LLMs)", open=False):
+        gr.Markdown("""
+        ### MCP Support
+        
+        This app supports the Model Context Protocol (MCP), allowing Large Language Models like Claude Desktop to use it as a tool.
+        
+        To use this app with an MCP client, add the following configuration:
+        
+        ```json
+        {
+          "mcpServers": {
+            "kokoroTTS": {
+              "url": "https://fdaudens-kokoro-mcp.hf.space/gradio_api/mcp/sse"
             }
-            ```
-            Replace `your-app-url.hf.space` with your actual Hugging Face Space URL.
-            """)
-    # Tab for AIxCel Space using an iframe, now pointing to localhost
-    with gr.Tab("AIxCel"):
-        # *** CRUCIAL CHANGE HERE: iframe src points to localhost:8080 ***
-        gr.HTML(
-            '<iframe src="http://localhost:8080/" ' # Assuming AIxCel serves from root '/'
-            'style="width: 100%; height: 800px; border: none;" '
-            'allow="accelerometer; ambient-light-sensor; camera; encrypted-media; geolocation; gyroscope; hid; microphone; midi; clipboard-read; clipboard-write; web-share" '
-            'sandbox="allow-forms allow-modals allow-popups allow-presentation allow-same-origin allow-scripts">'
-            '</iframe>'
-        )
-        gr.Markdown("If the AIxCel app does not load, please visit it directly: [AIxCel Space](https://huggingface.co/spaces/YoussefSharawy91/AIxCel)")
+          }
+        }
+        ```
+        
+        Replace `your-app-url.hf.space` with your actual Hugging Face Space URL.
+        """)
 
 # Launch the app with MCP support
 if __name__ == "__main__":
     # Check for environment variable to enable MCP
     enable_mcp = os.environ.get('GRADIO_MCP_SERVER', 'True').lower() in ('true', '1', 't')
-    app.launch(mcp_server=enable_mcp)
+    
+    app.launch(mcp_server=True)