Refactor project structure and enhance backend integration

- Expanded package inclusion in `pyproject.toml` to support new modules.
- Introduced new `adapters` and `protocol` packages for better organization.
- Added backend adapter implementations for control plane integration.
- Updated main application imports to reflect new package structure.
- Removed deprecated core components and adjusted documentation accordingly.
- Enhanced architecture documentation to clarify the new runtime and integration layers.

engine/providers/tts/streaming_adapter.py

@@ -0,0 +1,95 @@
+"""Backend-agnostic streaming adapter from LLM text to TTS audio."""
+
+import asyncio
+
+from loguru import logger
+
+from providers.common.base import BaseTTSService
+from providers.common.streaming_text import extract_tts_sentence, has_spoken_content
+
+
+class StreamingTTSAdapter:
+    """
+    Adapter for streaming LLM text to TTS with sentence-level chunking.
+
+    This reduces latency by starting TTS as soon as a complete sentence
+    is received from the LLM, rather than waiting for the full response.
+    """
+
+    SENTENCE_ENDS = {"。", "！", "？", ".", "!", "?", "\n"}
+    SENTENCE_CLOSERS = frozenset()
+
+    def __init__(self, tts_service: BaseTTSService, transport, session_id: str):
+        self.tts_service = tts_service
+        self.transport = transport
+        self.session_id = session_id
+        self._buffer = ""
+        self._cancel_event = asyncio.Event()
+        self._is_speaking = False
+
+    async def process_text_chunk(self, text_chunk: str) -> None:
+        """
+        Process a text chunk from LLM and trigger TTS when sentence is complete.
+
+        Args:
+            text_chunk: Text chunk from LLM streaming
+        """
+        if self._cancel_event.is_set():
+            return
+
+        self._buffer += text_chunk
+
+        # Check for sentence completion
+        while True:
+            split_result = extract_tts_sentence(
+                self._buffer,
+                end_chars=frozenset(self.SENTENCE_ENDS),
+                trailing_chars=frozenset(self.SENTENCE_ENDS),
+                closers=self.SENTENCE_CLOSERS,
+                force=False,
+            )
+            if not split_result:
+                break
+
+            sentence, self._buffer = split_result
+            if sentence and has_spoken_content(sentence):
+                await self._speak_sentence(sentence)
+
+    async def flush(self) -> None:
+        """Flush remaining buffer."""
+        if self._buffer.strip() and not self._cancel_event.is_set():
+            await self._speak_sentence(self._buffer.strip())
+        self._buffer = ""
+
+    async def _speak_sentence(self, text: str) -> None:
+        """Synthesize and send a sentence."""
+        if not text or self._cancel_event.is_set():
+            return
+
+        self._is_speaking = True
+
+        try:
+            async for chunk in self.tts_service.synthesize_stream(text):
+                if self._cancel_event.is_set():
+                    break
+                await self.transport.send_audio(chunk.audio)
+                await asyncio.sleep(0.01)  # Prevent flooding
+        except Exception as e:
+            logger.error(f"TTS speak error: {e}")
+        finally:
+            self._is_speaking = False
+
+    def cancel(self) -> None:
+        """Cancel ongoing speech."""
+        self._cancel_event.set()
+        self._buffer = ""
+
+    def reset(self) -> None:
+        """Reset for new turn."""
+        self._cancel_event.clear()
+        self._buffer = ""
+        self._is_speaking = False
+
+    @property
+    def is_speaking(self) -> bool:
+        return self._is_speaking