Update app.py

app.py

@@ -1,80 +1,77 @@
-import gradio as gr
-from transformers import pipeline
-
-# Load the audio classification model
-pipe = pipeline("audio-classification", model="dima806/english_accents_classification")
-
-# Define the inference function with styled, color-coded output
-def classify_accent(audio):
-    try:
-        result = pipe(audio)
-        if not result:
-            return "<p style='color: red; font-weight: bold;'>⚠️ No prediction returned. Please try a different audio file.</p>"
-        
-        # Start HTML table with styling
-        table = """
-        <table style="
-            width: 100%; 
-            border-collapse: collapse; 
-            font-family: Arial, sans-serif; 
-            margin-top: 1em;
-        ">
-            <thead>
-                <tr style="border-bottom: 2px solid #4CAF50; background-color: #f2f2f2;">
-                    <th style="text-align:left; padding: 8px; font-size: 1.1em; color: #333;">Accent</th>
-                    <th style="text-align:left; padding: 8px; font-size: 1.1em; color: #333;">Confidence</th>
-                </tr>
-            </thead>
-            <tbody>
-        """
-
-        for i, r in enumerate(result):
-            label = r['label'].capitalize()
-            score = f"{r['score'] * 100:.2f}%"
-            
-            if i == 0:
-                # Highlight top accent with green background and bold text
-                row = f"""
-                <tr style="background-color:#d4edda; font-weight: bold; color: #155724;">
-                    <td style="padding: 8px; border-bottom: 1px solid #c3e6cb;">{label}</td>
-                    <td style="padding: 8px; border-bottom: 1px solid #c3e6cb;">{score}</td>
-                </tr>
-                """
-            else:
-                row = f"""
-                <tr style="color: #333;">
-                    <td style="padding: 8px; border-bottom: 1px solid #ddd;">{label}</td>
-                    <td style="padding: 8px; border-bottom: 1px solid #ddd;">{score}</td>
-                </tr>
-                """
-            table += row
-        
-        table += "</tbody></table>"
-
-        top_result = result[0]
-        return f"""
-        <h3 style='color: #2E7D32; font-family: Arial, sans-serif;'>
-            🎤 Predicted Accent: <span style='font-weight:bold'>{top_result['label'].capitalize()}</span>
-        </h3>
-        {table}
-        """
-    
-    except Exception as e:
-        return f"<p style='color: red; font-weight: bold;'>⚠️ Error: {str(e)}<br>Please upload a valid English audio file (e.g., .wav, .mp3).</p>"
-
-# Create and launch the Gradio app
-gr.Interface(
-    fn=classify_accent,
-    inputs=gr.Audio(type="filepath", label="🎙 Record or Upload English Audio"),
-    outputs=gr.HTML(),  # Important: Use HTML output here to render the table properly
-    title="🌍 English Accent Classifier",
-    description=(
-        "Upload or record an English audio sample to detect the speaker's accent.\n\n"
-        "**Supported accents:** American, British, Indian, African, Australian.\n"
-        "Audio Classification Model:\n" 
-        "[dima806/english_accents_classification](https://huggingface.co/dima806/english_accents_classification)\n"
-        "Dataset: https://www.kaggle.com/code/dima806/common-voice-accent-classification\n"
-    ),
-    flagging_mode="never",
-    theme="default"
-).launch(share=True)
+import gradio as gr
+from transformers import pipeline
+import os
+
+# Load the model
+pipe = pipeline("audio-classification", model="dima806/english_accents_classification")
+
+def classify_accent(audio):
+    try:
+        result = pipe(audio)
+        if not result:
+            return "<p style='color: red; font-weight: bold;'>⚠️ No prediction returned. Please try a different audio file.</p>"
+
+        table = """
+        <table style='width: 100%; border-collapse: collapse; font-family: Arial, sans-serif; margin-top: 1em;'>
+            <thead>
+                <tr style='border-bottom: 2px solid #4CAF50; background-color: #f2f2f2;'>
+                    <th style='text-align:left; padding: 8px; font-size: 1.1em; color: #333;'>Accent</th>
+                    <th style='text-align:left; padding: 8px; font-size: 1.1em; color: #333;'>Confidence</th>
+                </tr>
+            </thead>
+            <tbody>
+        """
+
+        for i, r in enumerate(result):
+            label = r['label'].capitalize()
+            score = f"{r['score'] * 100:.2f}%"
+            if i == 0:
+                row = f"""
+                <tr style='background-color:#d4edda; font-weight: bold; color: #155724;'>
+                    <td style='padding: 8px; border-bottom: 1px solid #c3e6cb;'>{label}</td>
+                    <td style='padding: 8px; border-bottom: 1px solid #c3e6cb;'>{score}</td>
+                </tr>
+                """
+            else:
+                row = f"""
+                <tr style='color: #333;'>
+                    <td style='padding: 8px; border-bottom: 1px solid #ddd;'>{label}</td>
+                    <td style='padding: 8px; border-bottom: 1px solid #ddd;'>{score}</td>
+                </tr>
+                """
+            table += row
+
+        table += "</tbody></table>"
+
+        top_result = result[0]
+        return f"""
+        <h3 style='color: #2E7D32; font-family: Arial, sans-serif;'>
+            🎤 Predicted Accent: <span style='font-weight:bold'>{top_result['label'].capitalize()}</span>
+        </h3>
+        {table}
+        """
+
+    except Exception as e:
+        return f"<p style='color: red; font-weight: bold;'>⚠️ Error: {str(e)}<br>Please upload a valid English audio file (e.g., .wav, .mp3).</p>"
+
+# Determine if it's safe to enable the submit button
+def enable_submit(audio_path):
+    if audio_path is None:
+        return gr.update(interactive=False)
+    # If file name contains "microphone", assume it’s from mic input and delay submission
+    if "microphone" in os.path.basename(audio_path).lower():
+        return gr.update(interactive=True)  # Enable only when recording finishes
+    return gr.update(interactive=True)  # File upload: enable immediately
+
+# Build UI
+with gr.Blocks(theme="default") as demo:
+    gr.Markdown("## 🌍 English Accent Classifier\nRecord or upload English audio to detect accent.")
+    audio_input = gr.Audio(type="filepath", label="🎙 Record or Upload English Audio")
+    submit_button = gr.Button("Submit", interactive=False)
+    result_output = gr.HTML()
+
+    # Reactively enable submit only after audio is uploaded or recording stops
+    audio_input.change(enable_submit, inputs=audio_input, outputs=submit_button)
+    submit_button.click(classify_accent, inputs=audio_input, outputs=result_output)
+
+demo.launch(share=True)