Update app.py

app.py

@@ -1,62 +1,68 @@
 import gradio as gr
 import edge_tts
-import tempfile
 import asyncio
+import tempfile
+import os
 
-# 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",
-    "English (US) F": "en-US-AriaNeural",
-    "English (US) M": "en-US-EricNeural"
-}
-
-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():
+# الدالة الرئيسية التي تستقبل المعاملات الجديدة
+async def text_to_speech_edge(text, voice, emotion, is_symbol, rate, pitch):
+    if 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)
+    # التعامل مع القيم الافتراضية إذا كانت فارغة
+    if not rate: rate = "+0%"
+    if not pitch: pitch = "+0Hz"
     
-    # 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
+    # تحديد اسم الصوت بناءً على المدخل
+    voice_map = {
+        "رجل (مصري)": "ar-EG-ShakirNeural",
+        "سيدة (مصرية)": "ar-EG-SalmaNeural",
+        "رجل (سعودي)": "ar-SA-HamedNeural",
+        "سيدة (سعودية)": "ar-SA-ZariyahNeural",
+        "English (US) M": "en-US-EricNeural",
+        "English (US) F": "en-US-AriaNeural"
+    }
+    
+    # استخدام المفتاح المباشر إذا لم يكن في القاموس
+    selected_voice = voice_map.get(voice, voice)
+    
+    output_file = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False)
+    output_path = output_file.name
+    output_file.close()
+    
+    # توليد الصوت مع المعاملات الإضافية
+    communicate = edge_tts.Communicate(text, selected_voice, rate=rate, pitch=pitch)
+    await communicate.save(output_path)
+    
+    return output_path
 
-# Build the Interface
+# بناء الواجهة
 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")
+        voice_input = gr.Dropdown(
+            ["رجل (مصري)", "سيدة (مصرية)", "رجل (سعودي)", "سيدة (سعودية)", "English (US) M", "English (US) F"], 
+            label="Voice"
+        )
+        
+    # مدخلات إضافية ليتوافق مع طلب التطبيق
+    emotion_input = gr.Textbox(label="Emotion", value="محايد", visible=False)
+    symbol_input = gr.Checkbox(label="Is Symbol", value=True, visible=False)
     
-    audio_output = gr.Audio(label="Generated Audio", type="filepath")
+    # المعاملات الجديدة المهمة
+    rate_input = gr.Textbox(label="Rate", value="+0%")
+    pitch_input = gr.Textbox(label="Pitch", value="+0Hz")
     
-    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"
+    output_audio = gr.Audio(label="Output", type="filepath")
+    
+    submit_btn = gr.Button("Generate")
+    
+    # ربط الدالة بالواجهة - تأكد من الترتيب الصحيح للمدخلات
+    submit_btn.click(
+        text_to_speech_edge, 
+        inputs=[text_input, voice_input, emotion_input, symbol_input, rate_input, pitch_input], 
+        outputs=output_audio
     )
 
-# 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()
+if __name__ == "__main__":
+    demo.queue().launch()