Fix type annotations in guardrail classes to accept BaseLLM

- Update LLMGuardrail to accept BaseLLM instead of LLM in constructor
- Update HallucinationGuardrail to accept BaseLLM instead of LLM in constructor
- Add BaseLLM imports to both guardrail classes
- Fixes type-checker CI failure: 'Argument llm to LLMGuardrail has incompatible type BaseLLM; expected LLM'

Co-Authored-By: João <joao@crewai.com>

src/crewai/tasks/hallucination_guardrail.py

@@ -9,6 +9,7 @@ Classes:
 from typing import Any, Optional, Tuple
 
 from crewai.llm import LLM
+from crewai.llms.base_llm import BaseLLM
 from crewai.tasks.task_output import TaskOutput
 from crewai.utilities.logger import Logger
 
@@ -47,7 +48,7 @@ class HallucinationGuardrail:
     def __init__(
         self,
         context: str,
-        llm: LLM,
+        llm: BaseLLM,
         threshold: Optional[float] = None,
         tool_response: str = "",
     ):
@@ -60,7 +61,7 @@ class HallucinationGuardrail:
             tool_response: Optional tool response information that would be used in evaluation.
         """
         self.context = context
-        self.llm: LLM = llm
+        self.llm: BaseLLM = llm
         self.threshold = threshold
         self.tool_response = tool_response
         self._logger = Logger(verbose=True)

src/crewai/tasks/llm_guardrail.py

@@ -4,6 +4,7 @@ from pydantic import BaseModel, Field
 
 from crewai.agent import Agent, LiteAgentOutput
 from crewai.llm import LLM
+from crewai.llms.base_llm import BaseLLM
 from crewai.task import Task
 from crewai.tasks.task_output import TaskOutput
 
@@ -32,11 +33,11 @@ class LLMGuardrail:
     def __init__(
         self,
         description: str,
-        llm: LLM,
+        llm: BaseLLM,
     ):
         self.description = description
 
-        self.llm: LLM = llm
+        self.llm: BaseLLM = llm
 
     def _validate_output(self, task_output: TaskOutput) -> LiteAgentOutput:
         agent = Agent(