refactor: drop task paramenter from TaskGuardrail

This parameter was used to get the model from the `task.agent` which is a quite bit redudant since we could propagate the llm directly

src/crewai/task.py

@@ -243,7 +243,10 @@ class Task(BaseModel):
         elif isinstance(self.guardrail, str):
             from crewai.tasks.task_guardrail import TaskGuardrail
 
-            self._guardrail = TaskGuardrail(description=self.guardrail, task=self)
+            assert self.agent is not None
+            self._guardrail = TaskGuardrail(
+                description=self.guardrail, llm=self.agent.llm
+            )
 
         return self
 

src/crewai/tasks/task_guardrail.py

@@ -33,20 +33,11 @@ class TaskGuardrail:
     def __init__(
         self,
         description: str,
-        task: Task | None = None,
+        llm: LLM,
-        llm: LLM | None = None,
     ):
         self.description = description
 
-        fallback_llm: LLM | None = (
+        self.llm: LLM = llm
-            task.agent.llm
-            if task is not None
-            and hasattr(task, "agent")
-            and task.agent is not None
-            and hasattr(task.agent, "llm")
-            else None
-        )
-        self.llm: LLM | None = llm or fallback_llm
 
     def _validate_output(self, task_output: TaskOutput) -> LiteAgentOutput:
         agent = Agent(

tests/test_task_guardrails.py

@@ -153,14 +153,18 @@ def task_output():
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_task_guardrail_process_output(task_output):
-    guardrail = TaskGuardrail(description="Ensure the result has less than 10 words")
+    guardrail = TaskGuardrail(
+        description="Ensure the result has less than 10 words", llm=LLM(model="gpt-4o")
+    )
 
     result = guardrail(task_output)
     assert result[0] is False
 
     assert "exceeding the guardrail limit of fewer than" in result[1].lower()
 
-    guardrail = TaskGuardrail(description="Ensure the result has less than 500 words")
+    guardrail = TaskGuardrail(
+        description="Ensure the result has less than 500 words", llm=LLM(model="gpt-4o")
+    )
 
     result = guardrail(task_output)
     assert result[0] is True