feat: support to define a guardrail task no-code

docs/concepts/tasks.mdx

@@ -322,6 +322,14 @@ blog_task = Task(
    - On success: it returns a tuple of `(bool, Any)`. For example: `(True, validated_result)` 
    - On Failure: it returns a tuple of `(bool, str)`. For example: `(False, "Error message explain the failure")`
 
+### GuardrailTask
+
+The `GuardrailTask` class provides a sophisticated way to generate and execute validation code for task outputs. Here's how it works:
+
+#### Code Execution
+
+The generated code can be executed in two ways: Docker container (Default, Recommended) or current environment (unsafe mode)
+
 ### Error Handling Best Practices
 
 1. **Structured Error Responses**:
@@ -750,6 +758,8 @@ Task guardrails provide a powerful way to validate, transform, or filter task ou
 
 ### Basic Usage
 
+#### Define your own logic to validate
+
 ```python Code
 from typing import Tuple, Union
 from crewai import Task
@@ -769,6 +779,34 @@ task = Task(
 )
 ```
 
+#### Leverage a no-code approach for validation
+
+```python Code
+from crewai import Task
+
+task = Task(
+    description="Generate JSON data",
+    expected_output="Valid JSON object",
+    guardrail="Ensure the response is a valid JSON object"
+)
+```
+
+#### Use custom models for code generation
+
+```python Code
+from crewai import Task
+from crewai.llm import LLM
+
+task = Task(
+    description="Generate JSON data",
+    expected_output="Valid JSON object",
+    guardrail=GuardrailTask(
+        description="Ensure the response is a valid JSON object",
+        llm=LLM(model="gpt-4o-mini"),
+    )
+)
+```
+
 ### How Guardrails Work
 
 1. **Optional Attribute**: Guardrails are an optional attribute at the task level, allowing you to add validation only where needed.

src/crewai/task.py

@@ -140,7 +140,7 @@ class Task(BaseModel):
         default=None,
     )
     processed_by_agents: Set[str] = Field(default_factory=set)
-    guardrail: Optional[Callable[[TaskOutput], Tuple[bool, Any]]] = Field(
+    guardrail: Optional[Union[Callable[[TaskOutput], Tuple[bool, Any]], str]] = Field(
         default=None,
         description="Function to validate task output before proceeding to next task",
     )
@@ -157,8 +157,12 @@ class Task(BaseModel):
 
     @field_validator("guardrail")
     @classmethod
-    def validate_guardrail_function(cls, v: Optional[Callable]) -> Optional[Callable]:
+    def validate_guardrail_function(
-        """Validate that the guardrail function has the correct signature and behavior.
+        cls, v: Optional[str | Callable]
+    ) -> Optional[str | Callable]:
+        """
+        If v is a callable, validate that the guardrail function has the correct signature and behavior.
+        If v is a string, return it as is.
 
         While type hints provide static checking, this validator ensures runtime safety by:
         1. Verifying the function accepts exactly one parameter (the TaskOutput)
@@ -171,16 +175,16 @@ class Task(BaseModel):
         - Clear error messages help users debug guardrail implementation issues
 
         Args:
-            v: The guardrail function to validate
+            v: The guardrail function to validate or a string describing the guardrail task
 
         Returns:
-            The validated guardrail function
+            The validated guardrail function or a string describing the guardrail task
 
         Raises:
             ValueError: If the function signature is invalid or return annotation
                        doesn't match Tuple[bool, Any]
         """
-        if v is not None:
+        if v is not None and callable(v):
             sig = inspect.signature(v)
             positional_args = [
                 param
@@ -408,9 +412,7 @@ class Task(BaseModel):
             )
 
             if self.guardrail:
-                guardrail_result = GuardrailResult.from_tuple(
+                guardrail_result = self._process_guardrail(task_output)
-                    self.guardrail(task_output)
-                )
                 if not guardrail_result.success:
                     if self.retry_count >= self.max_retries:
                         raise Exception(
@@ -464,13 +466,52 @@ class Task(BaseModel):
                     )
                 )
                 self._save_file(content)
-            crewai_event_bus.emit(self, TaskCompletedEvent(output=task_output, task=self))
+            crewai_event_bus.emit(
+                self, TaskCompletedEvent(output=task_output, task=self)
+            )
             return task_output
         except Exception as e:
             self.end_time = datetime.datetime.now()
             crewai_event_bus.emit(self, TaskFailedEvent(error=str(e), task=self))
             raise e  # Re-raise the exception after emitting the event
 
+    def _process_guardrail(self, task_output: TaskOutput) -> GuardrailResult:
+        if self.guardrail is None:
+            raise ValueError("Guardrail is not set")
+
+        from crewai.utilities.events import (
+            GuardrailTaskCompletedEvent,
+            GuardrailTaskStartedEvent,
+        )
+        from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+
+        crewai_event_bus.emit(
+            self,
+            GuardrailTaskStartedEvent(
+                guardrail=self.guardrail, retry_count=self.retry_count
+            ),
+        )
+
+        if isinstance(self.guardrail, str):
+            from crewai.tasks.guardrail_task import GuardrailTask
+
+            result = GuardrailTask(description=self.guardrail, task=self)(task_output)
+        else:
+            result = self.guardrail(task_output)
+
+        guardrail_result = GuardrailResult.from_tuple(result)
+
+        crewai_event_bus.emit(
+            self,
+            GuardrailTaskCompletedEvent(
+                success=guardrail_result.success,
+                result=guardrail_result.result,
+                error=guardrail_result.error,
+                retry_count=self.retry_count,
+            ),
+        )
+        return guardrail_result
+
     def prompt(self) -> str:
         """Prompt the task.
 

src/crewai/tasks/guardrail_task.py

@@ -0,0 +1,154 @@
+from typing import Any, Tuple
+
+from crewai.llm import LLM
+from crewai.task import Task
+from crewai.tasks.task_output import TaskOutput
+from crewai.utilities.printer import Printer
+
+
+class GuardrailTask:
+    """A task that validates the output of another task using generated Python code.
+
+    This class generates and executes Python code to validate task outputs based on
+    specified criteria. It uses an LLM to generate the validation code and provides
+    safety guardrails for code execution.
+
+    Args:
+        description (str): The description of the validation criteria.
+        task (Task, optional): The task whose output needs validation.
+        llm (LLM, optional): The language model to use for code generation.
+        additional_instructions (str, optional): Additional instructions for the guardrail task.
+
+    Raises:
+        ValueError: If no valid LLM is provided.
+    """
+
+    def __init__(
+        self,
+        description: str,
+        task: Task | None = None,
+        llm: LLM | None = None,
+        unsafe_mode: bool = False,
+        additional_instructions: str = "",
+    ):
+        self.description = description
+        self.unsafe_mode: bool = unsafe_mode
+
+        fallback_llm: LLM | None = (
+            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
+
+        self.additional_instructions = additional_instructions
+
+    @property
+    def system_instructions(self) -> str:
+        """System instructions for the LLM code generation.
+
+        Returns:
+            str: Complete system instructions including security constraints.
+        """
+        security_instructions = (
+            "- DO NOT wrap the output in markdown or use triple backticks. Return only raw Python code."
+            "- DO NOT use `exec`, `eval`, `compile`, `open`, `os`, `subprocess`, `socket`, `shutil`, or any other system-level modules.\n"
+            "- Your code must not perform any file I/O, shell access, or dynamic code execution."
+        )
+        return (
+            "You are a expert Python developer"
+            "You **must strictly** follow the task description, use the provided raw output as the input in your code. "
+            "Your code must:\n"
+            "- Return results with: print((True, data)) on success, or print((False, 'very detailed error message')) on failure. Make sure the final output is beign assined to 'result' variable.\n"
+            "- Use the literal string of the task output (already included in your input) if needed.\n"
+            "- Generate the code **following strictly** the task description.\n"
+            "- Be valid Python 3 — executable as-is.\n"
+            f"{security_instructions}\n"
+            "Additional instructions (do not override the previous instructions):\n"
+            f"{self.additional_instructions}"
+        )
+
+    def user_instructions(self, task_output: TaskOutput) -> str:
+        """Generates user instructions for the LLM code generation.
+
+        Args:
+            task_output (TaskOutput): The output to be validated.
+
+        Returns:
+            str: Instructions for generating validation code.
+        """
+        return (
+            "Based on the task description below, generate Python 3 code that validates the task output. \n"
+            "Task description:\n"
+            f"{self.description}\n"
+            "Here is the raw output from the task: \n"
+            f"'{task_output.raw}' \n"
+            "Use this exact string literal inside your generated code (do not reference variables like task_output.raw)."
+            "Now generate Python code that follows the instructions above."
+        )
+
+    def generate_code(self, task_output: TaskOutput) -> str:
+        """Generates Python code for validating the task output.
+
+        Args:
+            task_output (TaskOutput): The output to be validated.
+
+        Returns:
+            str: Generated Python code for validation.
+        """
+        if self.llm is None:
+            raise ValueError("Provide a valid LLM to the GuardrailTask")
+
+        response = self.llm.call(
+            messages=[
+                {
+                    "role": "system",
+                    "content": self.system_instructions,
+                },
+                {
+                    "role": "user",
+                    "content": self.user_instructions(task_output=task_output),
+                },
+            ]
+        )
+
+        printer = Printer()
+        printer.print(
+            content=f"The following code was generated for the guardrail task:\n{response}\n",
+            color="cyan",
+        )
+        return response
+
+    def __call__(self, task_output: TaskOutput) -> Tuple[bool, Any]:
+        """Executes the validation code on the task output.
+
+        Args:
+            task_output (TaskOutput): The output to be validated.
+
+        Returns:
+            Tuple[bool, Any]: A tuple containing:
+                - bool: True if validation passed, False otherwise
+                - Any: The validation result or error message
+        """
+        import ast
+
+        from crewai_tools import CodeInterpreterTool
+
+        code = self.generate_code(task_output)
+        result = CodeInterpreterTool(code=code, unsafe_mode=self.unsafe_mode).run()
+
+        error_messages = [
+            "Something went wrong while running the code",
+            "No result variable found",  # when running in unsafe mode, the final output should be stored in the result variable
+        ]
+
+        if any(msg in result for msg in error_messages):
+            return False, result
+
+        if isinstance(result, str):
+            result = ast.literal_eval(result)
+
+        return result

src/crewai/utilities/events/__init__.py

@@ -9,6 +9,10 @@ from .crew_events import (
     CrewTestCompletedEvent,
     CrewTestFailedEvent,
 )
+from .guardrail_task_events import (
+    GuardrailTaskCompletedEvent,
+    GuardrailTaskStartedEvent,
+)
 from .agent_events import (
     AgentExecutionStartedEvent,
     AgentExecutionCompletedEvent,

src/crewai/utilities/events/event_types.py

@@ -23,6 +23,10 @@ from .flow_events import (
     MethodExecutionFinishedEvent,
     MethodExecutionStartedEvent,
 )
+from .guardrail_task_events import (
+    GuardrailTaskCompletedEvent,
+    GuardrailTaskStartedEvent,
+)
 from .llm_events import (
     LLMCallCompletedEvent,
     LLMCallFailedEvent,
@@ -68,4 +72,6 @@ EventTypes = Union[
     LLMCallCompletedEvent,
     LLMCallFailedEvent,
     LLMStreamChunkEvent,
+    GuardrailTaskStartedEvent,
+    GuardrailTaskCompletedEvent,
 ]

src/crewai/utilities/events/guardrail_task_events.py

@@ -0,0 +1,28 @@
+from typing import Any, Callable, Optional, Union
+
+from pydantic import BaseModel
+
+from crewai.utilities.events.base_events import BaseEvent
+
+
+class GuardrailTaskStartedEvent(BaseEvent):
+    """Event emitted when a guardrail task starts
+
+    Attributes:
+        messages: Content can be either a string or a list of dictionaries that support
+            multimodal content (text, images, etc.)
+    """
+
+    type: str = "guardrail_task_started"
+    guardrail: Union[str, Callable]
+    retry_count: int
+
+
+class GuardrailTaskCompletedEvent(BaseEvent):
+    """Event emitted when a guardrail task completes"""
+
+    type: str = "guardrail_task_completed"
+    success: bool
+    result: Any
+    error: Optional[str] = None
+    retry_count: int

tests/cassettes/test_guardrail_emits_events.yaml

@@ -0,0 +1,307 @@
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tests/test_task_guardrails.py

@@ -1,11 +1,16 @@
-"""Tests for task guardrails functionality."""
+from unittest.mock import Mock, patch
-
-from unittest.mock import Mock
 
 import pytest
 
-from crewai.task import Task
+from crewai import Agent, Task
+from crewai.llm import LLM
+from crewai.tasks.guardrail_task import GuardrailTask
 from crewai.tasks.task_output import TaskOutput
+from crewai.utilities.events import (
+    GuardrailTaskCompletedEvent,
+    GuardrailTaskStartedEvent,
+)
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 
 
 def test_task_without_guardrail():
@@ -22,7 +27,7 @@ def test_task_without_guardrail():
     assert result.raw == "test result"
 
 
-def test_task_with_successful_guardrail():
+def test_task_with_successful_guardrail_func():
     """Test that successful guardrail validation passes transformed result."""
 
     def guardrail(result: TaskOutput):
@@ -127,3 +132,190 @@ def test_guardrail_error_in_context():
 
     assert "Task failed guardrail validation" in str(exc_info.value)
     assert "Expected JSON, got string" in str(exc_info.value)
+
+
+@pytest.fixture
+def sample_agent():
+    return Agent(role="Test Agent", goal="Test Goal", backstory="Test Backstory")
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_guardrail_using_llm(sample_agent):
+    task = Task(
+        description="Test task",
+        expected_output="Output",
+        guardrail="Ensure the output is equal to 'good result'",
+    )
+
+    with patch(
+        "crewai.tasks.guardrail_task.GuardrailTask.__call__",
+        side_effect=[(False, "bad result"), (True, "good result")],
+    ) as mock_guardrail:
+        task.execute_sync(agent=sample_agent)
+
+    assert mock_guardrail.call_count == 2
+
+    task.guardrail = GuardrailTask(
+        description="Ensure the output is equal to 'good result'",
+        llm=LLM(model="gpt-4o-mini"),
+    )
+
+    with patch(
+        "crewai.tasks.guardrail_task.GuardrailTask.__call__",
+        side_effect=[(False, "bad result"), (True, "good result")],
+    ) as mock_guardrail:
+        task.execute_sync(agent=sample_agent)
+
+    assert mock_guardrail.call_count == 2
+
+
+@pytest.fixture
+def task_output():
+    return TaskOutput(
+        raw="Test output",
+        description="Test task",
+        expected_output="Output",
+        agent="Test Agent",
+    )
+
+
+def test_guardrail_task_initialization_no_llm(task_output):
+    """Test GuardrailTask initialization fails without LLM"""
+    with pytest.raises(ValueError, match="Provide a valid LLM to the GuardrailTask"):
+        GuardrailTask(description="Test")(task_output)
+
+
+@pytest.fixture
+def mock_llm():
+    llm = Mock(spec=LLM)
+    llm.call.return_value = """
+output = 'Sample book data'
+if isinstance(output, str):
+    result = (True, output)
+else:
+    result = (False, 'Invalid output format')
+print(result)
+"""
+    return llm
+
+
+@pytest.mark.parametrize(
+    "tool_run_output",
+    [
+        {
+            "output": "(True, 'Valid output')",
+            "expected_result": True,
+            "expected_output": "Valid output",
+        },
+        {
+            "output": "(False, 'Invalid output format')",
+            "expected_result": False,
+            "expected_output": "Invalid output format",
+        },
+        {
+            "output": "Something went wrong while running the code, Invalid output format",
+            "expected_result": False,
+            "expected_output": "Something went wrong while running the code, Invalid output format",
+        },
+        {
+            "output": "No result variable found",
+            "expected_result": False,
+            "expected_output": "No result variable found",
+        },
+        {
+            "output": (False, "Invalid output format"),
+            "expected_result": False,
+            "expected_output": "Invalid output format",
+        },
+    ],
+)
+@patch("crewai_tools.CodeInterpreterTool.run")
+def test_guardrail_task_execute_code(mock_run, mock_llm, tool_run_output, task_output):
+    mock_run.return_value = tool_run_output["output"]
+
+    guardrail = GuardrailTask(description="Test validation", llm=mock_llm)
+
+    result = guardrail(task_output)
+    assert result[0] == tool_run_output["expected_result"]
+    assert result[1] == tool_run_output["expected_output"]
+
+
+@patch("crewai_tools.CodeInterpreterTool.run")
+def test_guardrail_using_additional_instructions(mock_run, mock_llm, task_output):
+    mock_run.return_value = "(True, 'Valid output')"
+    additional_instructions = (
+        "This is an additional instruction created by the user follow it strictly"
+    )
+    guardrail = GuardrailTask(
+        description="Test validation",
+        llm=mock_llm,
+        additional_instructions=additional_instructions,
+    )
+
+    guardrail(task_output)
+
+    assert additional_instructions in str(mock_llm.call.call_args)
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_guardrail_emits_events(sample_agent):
+    started_guardrail = []
+    completed_guardrail = []
+
+    with crewai_event_bus.scoped_handlers():
+
+        @crewai_event_bus.on(GuardrailTaskStartedEvent)
+        def handle_guardrail_started(source, event):
+            started_guardrail.append(
+                {"guardrail": event.guardrail, "retry_count": event.retry_count}
+            )
+
+        @crewai_event_bus.on(GuardrailTaskCompletedEvent)
+        def handle_guardrail_completed(source, event):
+            completed_guardrail.append(
+                {
+                    "success": event.success,
+                    "result": event.result,
+                    "error": event.error,
+                    "retry_count": event.retry_count,
+                }
+            )
+
+        task = Task(
+            description="Test task",
+            expected_output="Output",
+            guardrail="Ensure the output is equal to 'good result'",
+        )
+
+        with patch(
+            "crewai.tasks.guardrail_task.GuardrailTask.__call__",
+            side_effect=[(False, "bad result"), (True, "good result")],
+        ):
+            task.execute_sync(agent=sample_agent)
+
+        expected_started_events = [
+            {
+                "guardrail": "Ensure the output is equal to 'good result'",
+                "retry_count": 0,
+            },
+            {
+                "guardrail": "Ensure the output is equal to 'good result'",
+                "retry_count": 1,
+            },
+        ]
+        expected_completed_events = [
+            {
+                "success": False,
+                "result": None,
+                "error": "bad result",
+                "retry_count": 0,
+            },
+            {
+                "success": True,
+                "result": "good result",
+                "error": None,
+                "retry_count": 1,
+            },
+        ]
+        assert started_guardrail == expected_started_events
+        assert completed_guardrail == expected_completed_events