Update app.py

app.py

@@ -2,6 +2,10 @@ import gradio as gr
 import edge_tts
 import tempfile
 import asyncio
+import hashlib
+import os
+from pathlib import Path
+from functools import lru_cache
 
 # Voice Mapping
 VOICE_MAP = {
@@ -13,8 +17,37 @@ VOICE_MAP = {
     "English (US) F": "en-US-AriaNeural"
 }
 
+# معالجة 2 طلبات فقط في نفس الوقت (لـ 2 vCPUs)
+TTS_SEMAPHORE = asyncio.Semaphore(2)
+
+# Cache directory
+CACHE_DIR = Path("./tts_cache")
+CACHE_DIR.mkdir(exist_ok=True)
+
+# تنظيف الكاش القديم عند البداية
+def cleanup_old_cache(max_files=100):
+    """حذف أقدم ملفات الكاش إذا تجاوز العدد الحد المسموح"""
+    cache_files = sorted(CACHE_DIR.glob("*.mp3"), key=os.path.getmtime)
+    if len(cache_files) > max_files:
+        for f in cache_files[:len(cache_files) - max_files]:
+            try:
+                f.unlink()
+            except:
+                pass
+
+cleanup_old_cache(max_files=100)
+
+def generate_cache_key(text, voice, rate, pitch):
+    """توليد مفتاح فريد للكاش"""
+    content = f"{text[:500]}{voice}{rate}{pitch}"  # أول 500 حرف فقط
+    return hashlib.md5(content.encode('utf-8')).hexdigest()
+
 async def generate_speech(text, voice, emotion, is_symbol, rate, pitch):
-    if not text or not text.strip(): return None
+    if not text or not text.strip(): 
+        return None
+    
+    # تقليم النص الطويل جداً (حماية من الإساءة)
+    text = text[:5000]
     
     # Defaults
     final_rate = rate if rate and isinstance(rate, str) and len(rate.strip()) > 0 else "+0%"
@@ -22,25 +55,53 @@ async def generate_speech(text, voice, emotion, is_symbol, rate, pitch):
     
     # Voice Selection
     selected_voice = "ar-SA-HamedNeural"
-    if voice in VOICE_MAP: selected_voice = VOICE_MAP[voice]
-    elif voice in VOICE_MAP.values(): selected_voice = voice
-    
-    print(f"Generating: {len(text)} chars | {selected_voice} | {final_rate} | {final_pitch}")
-
-    try:
-        output_file = tempfile.NamedTemporaryFile(suffix=".mp3", delete=False)
-        output_path = output_file.name
-        output_file.close()
-        
-        communicate = edge_tts.Communicate(text, selected_voice, rate=final_rate, pitch=final_pitch)
-        await communicate.save(output_path)
-        return output_path
-    except Exception as e:
-        print(f"ERROR: {str(e)}")
-        raise gr.Error(f"TTS Error: {str(e)}")
-
-# UI Definition using Blocks (Fixes TypeError)
-with gr.Blocks(title="Natiq Pro API") as demo:
+    if voice in VOICE_MAP: 
+        selected_voice = VOICE_MAP[voice]
+    elif voice in VOICE_MAP.values(): 
+        selected_voice = voice
+    
+    # Check cache
+    cache_key = generate_cache_key(text, selected_voice, final_rate, final_pitch)
+    cache_path = CACHE_DIR / f"{cache_key}.mp3"
+    
+    if cache_path.exists():
+        print(f"✓ Cache hit: {len(text)} chars")
+        return str(cache_path)
+    
+    print(f"⚙ Generating: {len(text)} chars | {selected_voice}")
+
+    # Semaphore للتحكم في التزامن
+    async with TTS_SEMAPHORE:
+        try:
+            # استخدام cache path مباشرة بدلاً من tempfile
+            communicate = edge_tts.Communicate(
+                text, 
+                selected_voice, 
+                rate=final_rate, 
+                pitch=final_pitch
+            )
+            
+            # حفظ مباشرة في الكاش
+            await asyncio.wait_for(
+                communicate.save(str(cache_path)),
+                timeout=45.0  # timeout 45 ثانية
+            )
+            
+            return str(cache_path)
+            
+        except asyncio.TimeoutError:
+            print(f"✗ Timeout for {len(text)} chars")
+            if cache_path.exists():
+                cache_path.unlink()
+            raise gr.Error("Request timeout - try shorter text")
+        except Exception as e:
+            print(f"✗ ERROR: {str(e)}")
+            if cache_path.exists():
+                cache_path.unlink()
+            raise gr.Error(f"TTS Error: {str(e)[:100]}")
+
+# UI Definition
+with gr.Blocks(title="Natiq Pro API", css=".gradio-container {max-width: 100%}") as demo:
     with gr.Row(visible=False):
         t = gr.Textbox(label="Text")
         v = gr.Textbox(label="Voice")
@@ -52,8 +113,19 @@ with gr.Blocks(title="Natiq Pro API") as demo:
     o = gr.Audio(label="Output", type="filepath")
     b = gr.Button("Generate", visible=False)
     
-    # Explicit API Name
-    b.click(generate_speech, inputs=[t,v,e,s,r,p], outputs=[o], api_name="text_to_speech_edge")
+    b.click(
+        generate_speech, 
+        inputs=[t, v, e, s, r, p], 
+        outputs=[o], 
+        api_name="text_to_speech_edge",
+        concurrency_limit=3  # 3 طلبات متزامنة كحد أقصى
+    )
 
 if __name__ == "__main__":
-    demo.queue().launch()
+    demo.queue(
+        default_concurrency_limit=3,
+        max_size=30  # قائمة انتظار 30 طلب ف��ط
+    ).launch(
+        max_threads=6,  # threads محدودة
+        show_error=True
+    )