Create app.py

app.py

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+import gradio as gr
+import edge_tts
+import tempfile
+import asyncio
+
+# Map frontend voice labels to Edge TTS internal IDs
+VOICES = {
+    "رجل (مصري)": "ar-EG-ShakirNeural",
+    "سيدة (مصرية)": "ar-EG-SalmaNeural",
+    "رجل (سعودي)": "ar-SA-HamedNeural",
+    "سيدة (سعودية)": "ar-SA-ZariyahNeural"
+}
+
+async def generate_audio(text, voice_label, emotion_ignored, advanced_ignored, rate_ignored, pitch_ignored):
+    """
+    Generates audio. 
+    Note: We ignore rate/pitch arguments because Natiq Pro handles 
+    speed and pitch shifting on the Frontend (Web Audio API) for zero-latency adjustments.
+    """
+    if not text or not text.strip():
+        return None
+
+    # Default to Saudi Male if voice not found
+    voice_id = VOICES.get(voice_label, "ar-SA-HamedNeural")
+    
+    communicate = edge_tts.Communicate(text, voice_id)
+    
+    # Create a temporary file
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
+        tmp_path = tmp_file.name
+
+    await communicate.save(tmp_path)
+    return tmp_path
+
+# Build the Interface
+with gr.Blocks() as demo:
+    # Inputs match the order sent by your frontend
+    with gr.Row():
+        text_input = gr.Textbox(label="Text")
+        voice_input = gr.Textbox(label="Voice")
+        emotion_input = gr.Textbox(label="Emotion")
+        advanced_input = gr.Checkbox(label="Is Advanced")
+        rate_input = gr.Number(label="Rate")
+        pitch_input = gr.Textbox(label="Pitch")
+    
+    audio_output = gr.Audio(label="Generated Audio", type="filepath")
+    
+    generate_btn = gr.Button("Generate")
+
+    # The API name must match what is in audioService.ts
+    generate_btn.click(
+        fn=generate_audio,
+        inputs=[text_input, voice_input, emotion_input, advanced_input, rate_input, pitch_input],
+        outputs=audio_output,
+        api_name="text_to_speech_edge"
+    )
+
+# CRITICAL: This enables parallel processing. 
+# The frontend sends 10 requests at once; this allows the backend to accept 20 at once.
+demo.queue(max_size=40, default_concurrency_limit=20).launch()