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Jarvis TR/backup/tts.py

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+import io
+import threading
+import asyncio
+import sounddevice as sd
+import soundfile as sf
+import edge_tts
+
+VOICE = "tr-TR-AhmetNeural"  
+
+RATE = "+0%"     
+VOLUME = "+0%"   
+PITCH = "+0Hz"   
+
+stop_speaking_flag = threading.Event()
+
+def edge_speak(text: str, ui=None, blocking=False):
+    if not text or not text.strip():
+        return
+
+    finished_event = threading.Event()
+
+    def _thread():
+        if ui:
+            ui.start_speaking()
+
+        stop_speaking_flag.clear()
+
+        try:
+            asyncio.run(_speak_async(text))
+        except Exception as e:
+            print("EDGE TTS ERROR:", e)
+        finally:
+            if ui:
+                ui.stop_speaking()
+            finished_event.set()
+
+    threading.Thread(target=_thread, daemon=True).start()
+
+    if blocking:
+        finished_event.wait()
+
+async def _speak_async(text: str):
+    communicate = edge_tts.Communicate(
+        text=text.strip(),
+        voice=VOICE,
+        rate=RATE,
+        volume=VOLUME,
+        pitch=PITCH,
+    )
+
+    audio_bytes = io.BytesIO()
+
+    async for chunk in communicate.stream():
+        if stop_speaking_flag.is_set():
+            return
+
+        if chunk["type"] == "audio":
+            audio_bytes.write(chunk["data"])
+
+    audio_bytes.seek(0)
+
+    data, samplerate = sf.read(audio_bytes, dtype="float32")
+
+    channels = data.shape[1] if len(data.shape) > 1 else 1
+
+    with sd.OutputStream(
+        samplerate=samplerate,
+        channels=channels,
+        dtype="float32",
+    ) as stream:
+        block_size = 1024
+        for start in range(0, len(data), block_size):
+            if stop_speaking_flag.is_set():
+                break
+            stream.write(data[start:start + block_size])
+
+def stop_speaking():
+    stop_speaking_flag.set()