Use FastGPT app opener for greetings

engine/config.py

@@ -147,7 +147,6 @@ class LLMConfig:
     variables: dict[str, str] = field(default_factory=dict)
     detail: bool = False
     timeout_sec: float = 60.0
-    send_system_prompt: bool = False
 
     @property
     def is_fastgpt(self) -> bool:
@@ -160,7 +159,7 @@ class LLMConfig:
     @property
     def uses_local_context_history(self) -> bool:
         """Whether the pipeline should seed and maintain local LLM context history."""
-        return not self.is_fastgpt or self.send_system_prompt
+        return not self.is_fastgpt
 
 
 @dataclass(frozen=True)
@@ -233,9 +232,11 @@ def config_from_dict(data: dict) -> EngineConfig:
     agent = _dict(data.get("agent"))
     if agent.get("greeting") == "":
         agent["greeting"] = None
-    if agent.get("greeting_mode") not in (None, "generated", "fixed", "off"):
-        raise ValueError("agent.greeting_mode must be one of: generated, fixed, off")
-    response_state = ResponseStateConfig(**_dict(agent.pop("response_state")))
+    if agent.get("greeting_mode") not in (None, "generated", "fixed", "off", "fastgpt_opener"):
+        raise ValueError(
+            "agent.greeting_mode must be one of: generated, fixed, off, fastgpt_opener"
+        )
+    response_state = ResponseStateConfig(**_dict(agent.pop("response_state", None)))
     if response_state.max_prefix_chars < 1:
         raise ValueError("agent.response_state.max_prefix_chars must be greater than 0")
     if not response_state.tag:
@@ -255,6 +256,10 @@ def config_from_dict(data: dict) -> EngineConfig:
         llm["app_id"] = None
     if not isinstance(llm.get("variables"), dict):
         llm["variables"] = {}
+    if agent.get("greeting_mode") == "fastgpt_opener" and llm["provider"] != "fastgpt":
+        raise ValueError(
+            "agent.greeting_mode='fastgpt_opener' requires services.llm.provider='fastgpt'"
+        )
 
     turn = _dict(data.get("turn"))
     vad = _dict(turn.get("vad"))

engine/fastgpt_llm.py

@@ -170,7 +170,6 @@ class FastGPTLLMService(LLMService):
         base_url: str,
         chat_id: str | None = None,
         app_id: str | None = None,
-        send_system_prompt: bool = False,
         greeting_prompt: str | None = None,
         timeout: float = 60.0,
         settings: FastGPTLLMSettings | None = None,
@@ -183,7 +182,6 @@ class FastGPTLLMService(LLMService):
 
         self._chat_id = chat_id or f"voice_{uuid.uuid4().hex[:16]}"
         self._app_id = (app_id or "").strip()
-        self._send_system_prompt = send_system_prompt
         self._greeting_prompt = (greeting_prompt or "你好").strip() or "你好"
         self._client = AsyncChatClient(
             api_key=api_key,
@@ -246,6 +244,8 @@ class FastGPTLLMService(LLMService):
         return _first_nonempty_text(
             chat_config.get("welcomeText"),
             app_payload.get("welcomeText"),
+            app_payload.get("opener"),
+            app_payload.get("intro"),
         )
 
     async def fetch_welcome_text(self) -> str | None:
@@ -261,7 +261,7 @@ class FastGPTLLMService(LLMService):
             response.raise_for_status()
             text = self._welcome_text_from_init_payload(response.json())
             if text:
-                logger.info(f"FastGPT welcomeText loaded for appId={self._app_id}")
+                logger.info(f"FastGPT app opener loaded for appId={self._app_id}")
             return text or None
         except FastGPTError as exc:
             logger.warning(f"FastGPT chat init failed: {exc}")
@@ -279,26 +279,15 @@ class FastGPTLLMService(LLMService):
 
     def _build_fastgpt_messages(self, context: LLMContext) -> list[dict[str, str]]:
         raw_messages = context.get_messages()
-        messages: list[dict[str, str]] = []
-
-        if self._send_system_prompt:
-            for message in raw_messages:
-                if not isinstance(message, dict) or message.get("role") != "system":
-                    continue
-                text = _message_text(message)
-                if text:
-                    messages.append({"role": "system", "content": text})
 
         for message in reversed(raw_messages):
             if not isinstance(message, dict) or message.get("role") != "user":
                 continue
             text = _message_text(message)
             if text:
-                messages.append({"role": "user", "content": text})
-                return messages
+                return [{"role": "user", "content": text}]
 
-        messages.append({"role": "user", "content": self._greeting_prompt})
-        return messages
+        return [{"role": "user", "content": self._greeting_prompt}]
 
     async def _process_context(self, context: LLMContext) -> None:
         messages = self._build_fastgpt_messages(context)

engine/pipeline.py

@@ -196,15 +196,17 @@ async def run_pipeline_with_serializer(
         logger.info(f"{client_label} websocket client connected")
         if config.agent.greeting_mode == "fixed" and config.agent.greeting:
             await task.queue_frames([TTSSpeakFrame(config.agent.greeting)])
-        elif config.agent.greeting_mode == "generated":
+        elif config.agent.greeting_mode == "fastgpt_opener":
             if isinstance(llm, FastGPTLLMService):
                 welcome = await llm.fetch_welcome_text()
                 if welcome:
                     await task.queue_frames([TTSSpeakFrame(welcome)])
                 else:
-                    await task.queue_frames([LLMRunFrame()])
+                    logger.warning("FastGPT opener requested but no opener text was returned")
             else:
-                await task.queue_frames([LLMRunFrame()])
+                raise RuntimeError("agent.greeting_mode='fastgpt_opener' requires FastGPT LLM service")
+        elif config.agent.greeting_mode == "generated":
+            await task.queue_frames([LLMRunFrame()])
 
     @transport.event_handler("on_client_disconnected")
     async def on_client_disconnected(_transport, _client):

engine/services.py

@@ -63,7 +63,6 @@ def create_llm_service(
             base_url=config.base_url or "http://localhost:3000",
             chat_id=chat_id or config.chat_id,
             app_id=config.app_id,
-            send_system_prompt=config.send_system_prompt,
             greeting_prompt=greeting_prompt,
             timeout=config.timeout_sec,
             settings=FastGPTLLMSettings(