F3: connect Prompt tools and web task controls to native Jobs

backend/services/brains/prompt_brain.py

@@ -72,6 +72,7 @@ class PromptBrain(BaseBrain):
         self._action_stages = ActionStageRunner(self._actions)
         self._message_stages = MessageStageRunner()
         self._tool_by_id = {tool.id: tool for tool in cfg.tools}
+        self._task_bridge = None
         self._runtime: BrainRuntime | None = None
         self._realtime_controller: PromptRealtimeToolController | None = None
         self._output: FixedSpeechOutput | None = None
@@ -100,7 +101,11 @@ class PromptBrain(BaseBrain):
         )
 
     def system_prompt(self, cfg: AssistantConfig) -> str:
-        return self._store.render(cfg.prompt) if self._dynamic_enabled else cfg.prompt
+        prompt = self._store.render(cfg.prompt) if self._dynamic_enabled else cfg.prompt
+        if cfg.runtimeMode == "pipeline" and any(tool.type == "task" for tool in cfg.tools):
+            from services.brains.prompt_tasks import TASK_HINT
+            prompt += "\n" + TASK_HINT
+        return prompt
 
     def build_llm(self, cfg: AssistantConfig, context: LLMContext) -> FrameProcessor:
         from services.pipecat.service_factory import create_llm
@@ -153,6 +158,20 @@ class PromptBrain(BaseBrain):
             ):
                 logger.warning(f"跳过客户端未上报的工具: {tool.function_name}")
                 continue
+            if tool.type == "task":
+                if cfg.runtimeMode != "pipeline":
+                    raise ValueError("后台任务工具仅支持提示词 Pipeline")
+                from services.brains.prompt_tasks import PromptTaskBridge
+                if self._task_bridge is not None:
+                    raise ValueError("最多绑定一个后台任务工具")
+                self._task_bridge = PromptTaskBridge(cfg, runtime, self._tools)
+                for schema, handler in self._task_bridge.functions(tool, binding_by_id[tool.id]):
+                    if schema.name in registered_names:
+                        raise ValueError("后台任务函数名与已有工具冲突")
+                    schemas.append(schema)
+                    registered_names.add(schema.name)
+                    runtime.llm.register_function(schema.name, handler, cancel_on_interruption=False)
+                continue
             if tool.type == "system":
                 schema, handler = self._make_system_tool(tool, runtime)
             elif tool.type in {"http", "mcp", "client"}:
@@ -178,6 +197,11 @@ class PromptBrain(BaseBrain):
             )
         runtime.set_tools(schemas)
 
+    async def close(self):
+        if self._task_bridge:
+            self._task_bridge.close()
+            self._task_bridge = None
+
     def restore_text_state(self, snapshot: dict[str, Any]) -> None:
         """Restore Prompt startup progress for a later Responses API turn."""
         if snapshot.get("type") != "prompt":
@@ -596,7 +620,7 @@ class PromptBrain(BaseBrain):
 
     def _refresh_prompt(self) -> None:
         if self._dynamic_enabled and self._runtime is not None:
-            self._runtime.set_system_prompt(self._store.render(self._cfg.prompt))
+            self._runtime.set_system_prompt(self.system_prompt(self._cfg))
 
     def _make_remote_tool(self, tool, runtime: BrainRuntime, binding):
         properties, required = self._tools.schema_parts(tool, binding)