feat: add project fork async job service with cli prune/clear commands and shared container image build target

devplacepy/services/devii/agentic/controller.py

@@ -10,7 +10,14 @@ from ..config import Settings
 from ..errors import ToolInputError
 from .lessons import LessonStore
 from .loop import TraceCallback, react_loop
-from .state import AgentState, get_state
+from .state import (
+    MAX_EVAL_DEPTH,
+    AgentState,
+    get_eval_depth,
+    get_state,
+    reset_eval_depth,
+    set_eval_depth,
+)
 
 logger = logging.getLogger("devii.agentic.controller")
 
@@ -58,6 +65,7 @@ class AgenticController:
             "forget_lessons": self._forget,
             "verify": self._verify,
             "delegate": self._delegate,
+            "eval": self._eval,
         }
         handler = handlers.get(name)
         if handler is None:
@@ -147,12 +155,53 @@ class AgenticController:
             {"status": "success", "verified": bool(confirmed), "summary": summary}, ensure_ascii=False
         )
 
+    async def _spawn(
+        self, prompt: str, tools: list[dict[str, Any]], system_prompt: str = SUB_AGENT_SYSTEM_PROMPT
+    ) -> tuple[str, AgentState]:
+        if self._llm is None or self._dispatcher is None:
+            raise ToolInputError("Sub-agent execution is not available in this context.")
+        depth = get_eval_depth()
+        if depth >= MAX_EVAL_DEPTH:
+            raise ToolInputError(
+                "Nested self-evaluation limit reached; a tool or eval cannot keep calling itself."
+            )
+        messages = [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": prompt},
+        ]
+        sub_state = AgentState()
+        token = set_eval_depth(depth + 1)
+        try:
+            result = await react_loop(
+                llm=self._llm,
+                dispatcher=self._dispatcher,
+                messages=messages,
+                tools=tools,
+                state=sub_state,
+                settings=self._settings,
+                max_iterations=self._settings.delegate_max_iterations,
+                plan_required=self._settings.plan_required,
+                verify_required=self._settings.verify_required,
+                on_trace=self._on_trace,
+                cost_tracker=self._cost_tracker,
+                chunk_store=self._chunk_store,
+            )
+        finally:
+            reset_eval_depth(token)
+        return result, sub_state
+
+    async def run_subagent(self, prompt: str) -> str:
+        prompt = str(prompt or "").strip()
+        if not prompt:
+            raise ToolInputError("A non-empty prompt is required.")
+        tools = [tool for tool in self._tools if tool["function"]["name"] != NO_DELEGATE]
+        result, _ = await self._spawn(prompt, tools)
+        return result
+
     async def _delegate(self, arguments: dict[str, Any]) -> str:
         task = str(arguments.get("task", "")).strip()
         if not task:
             raise ToolInputError("delegate requires a task description.")
-        if self._llm is None or self._dispatcher is None:
-            raise ToolInputError("Delegation is not available in this context.")
         allowed = arguments.get("allowed_tools")
         if allowed:
             allowed_set = {str(name) for name in allowed}
@@ -163,26 +212,7 @@ class AgenticController:
             ]
         else:
             tools = [tool for tool in self._tools if tool["function"]["name"] != NO_DELEGATE]
-
-        messages = [
-            {"role": "system", "content": SUB_AGENT_SYSTEM_PROMPT},
-            {"role": "user", "content": task},
-        ]
-        sub_state = AgentState()
-        result = await react_loop(
-            llm=self._llm,
-            dispatcher=self._dispatcher,
-            messages=messages,
-            tools=tools,
-            state=sub_state,
-            settings=self._settings,
-            max_iterations=self._settings.delegate_max_iterations,
-            plan_required=self._settings.plan_required,
-            verify_required=self._settings.verify_required,
-            on_trace=self._on_trace,
-            cost_tracker=self._cost_tracker,
-            chunk_store=self._chunk_store,
-        )
+        result, sub_state = await self._spawn(task, tools)
         return json.dumps(
             {
                 "status": "success",
@@ -193,3 +223,10 @@ class AgenticController:
             },
             ensure_ascii=False,
         )
+
+    async def _eval(self, arguments: dict[str, Any]) -> str:
+        prompt = str(arguments.get("prompt", "")).strip()
+        if not prompt:
+            raise ToolInputError("eval requires a non-empty prompt.")
+        result = await self.run_subagent(prompt)
+        return json.dumps({"status": "success", "result": result}, ensure_ascii=False)