fix(experimental): allow AgentExecutor restore from checkpoint

llm and prompt were declared required with exclude=True, making the
model un-restorable from its own serialized output. Mirror the
CrewAgentExecutor pattern: make them nullable with default None, keep
exclude=True, and re-attach llm on the resume path alongside the other
re-attached fields. Guard the two prompt-deref sites so the runtime
invariant survives the looser type.

lib/crewai/src/crewai/agent/core.py

@@ -1109,9 +1109,14 @@ class Agent(BaseAgent):
         """
         if self.agent_executor is None:
             raise RuntimeError("Agent executor is not initialized.")
+        if not isinstance(self.llm, BaseLLM):
+            raise RuntimeError(
+                "LLM must be resolved before updating agent executor parameters."
+            )
 
         if task is not None:
             self.agent_executor.task = task
+        self.agent_executor.llm = self.llm
         self.agent_executor.tools = tools
         self.agent_executor.original_tools = raw_tools
         self.agent_executor.prompt = prompt
@@ -1411,6 +1416,11 @@ class Agent(BaseAgent):
 
         if _is_resuming_agent_executor(self.agent_executor):
             executor = self.agent_executor
+            if not isinstance(self.llm, BaseLLM):
+                raise RuntimeError(
+                    "LLM must be resolved before resuming agent executor."
+                )
+            executor.llm = self.llm
             executor.tools = parsed_tools
             executor.tools_names = get_tool_names(parsed_tools)
             executor.tools_description = render_text_description_and_args(parsed_tools)

lib/crewai/src/crewai/experimental/agent_executor.py

@@ -173,8 +173,10 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
 
     executor_type: Literal["experimental"] = "experimental"
     suppress_flow_events: bool = True  # always suppress for executor
-    llm: BaseLLM = Field(exclude=True)
-    prompt: SystemPromptResult | StandardPromptResult = Field(exclude=True)
+    llm: BaseLLM | None = Field(default=None, exclude=True)
+    prompt: SystemPromptResult | StandardPromptResult | None = Field(
+        default=None, exclude=True
+    )
     max_iter: int = Field(default=25, exclude=True)
     tools: list[CrewStructuredTool] = Field(default_factory=list, exclude=True)
     tools_names: str = Field(default="", exclude=True)
@@ -2585,6 +2587,11 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
 
             self._kickoff_input = inputs.get("input", "")
 
+            if self.llm is None or self.prompt is None:
+                raise RuntimeError(
+                    "AgentExecutor.llm or .prompt is unset; the executor was "
+                    "not fully restored or initialized before execution."
+                )
             if "system" in self.prompt:
                 from crewai.llms.cache import mark_cache_breakpoint
 
@@ -2686,6 +2693,11 @@ class AgentExecutor(Flow[AgentExecutorState], BaseAgentExecutor):
 
             self._kickoff_input = inputs.get("input", "")
 
+            if self.llm is None or self.prompt is None:
+                raise RuntimeError(
+                    "AgentExecutor.llm or .prompt is unset; the executor was "
+                    "not fully restored or initialized before execution."
+                )
             if "system" in self.prompt:
                 from crewai.llms.cache import mark_cache_breakpoint