Merge branch 'main' into devin/1745784489-fix-crewstructuredtool-task-compatibility

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

docs/concepts/agents.mdx

@@ -255,11 +255,7 @@ custom_agent = Agent(
 - `response_template`: Formats agent responses
 
 <Note>
-When using custom templates, ensure that both `system_template` and `prompt_template` are defined. The `response_template` is optional but recommended for consistent output formatting.
-</Note>  
-
-<Note>
-When using custom templates, you can use variables like `{role}`, `{goal}`, and `{backstory}` in your templates. These will be automatically populated during execution.
+When using custom templates, you can use variables like `{role}`, `{goal}`, and `{input}` in your templates. These will be automatically populated during execution.
 </Note>
 
 ## Agent Tools

docs/concepts/tasks.mdx

@@ -322,10 +322,6 @@ 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")`
 
-### TaskGuardrail
-
-The `TaskGuardrail` class offers a robust mechanism for validating task outputs
-
 ### Error Handling Best Practices
 
 1. **Structured Error Responses**:
@@ -754,8 +750,6 @@ 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
@@ -775,57 +769,6 @@ 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"
-)
-```
-
-#### Using YAML
-
-```yaml
-research_task:
-  ...
-  guardrail: make sure each bullet contains a minimum of 100 words
-  ...
-```
-
-```python Code
-@CrewBase
-class InternalCrew:
-    agents_config = "config/agents.yaml"
-    tasks_config = "config/tasks.yaml"
-
-    ...
-    @task
-    def research_task(self):
-        return Task(config=self.tasks_config["research_task"])  # type: ignore[index]
-    ...
-```
-
-
-#### 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=TaskGuardrail(
-        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.

docs/concepts/tools.mdx

@@ -190,6 +190,48 @@ def my_tool(question: str) -> str:
     return "Result from your custom tool"
 ```
 
+### Structured Tools
+
+The `StructuredTool` class wraps functions as tools, providing flexibility and validation while reducing boilerplate. It supports custom schemas and dynamic logic for seamless integration of complex functionalities.
+
+#### Example:
+Using `StructuredTool.from_function`, you can wrap a function that interacts with an external API or system, providing a structured interface. This enables robust validation and consistent execution, making it easier to integrate complex functionalities into your applications as demonstrated in the following example:
+
+```python
+from crewai.tools.structured_tool import CrewStructuredTool
+from pydantic import BaseModel
+
+# Define the schema for the tool's input using Pydantic
+class APICallInput(BaseModel):
+    endpoint: str
+    parameters: dict
+
+# Wrapper function to execute the API call
+def tool_wrapper(*args, **kwargs):
+    # Here, you would typically call the API using the parameters
+    # For demonstration, we'll return a placeholder string
+    return f"Call the API at {kwargs['endpoint']} with parameters {kwargs['parameters']}"
+
+# Create and return the structured tool
+def create_structured_tool():
+    return CrewStructuredTool.from_function(
+        name='Wrapper API',
+        description="A tool to wrap API calls with structured input.",
+        args_schema=APICallInput,
+        func=tool_wrapper,
+    )
+
+# Example usage
+structured_tool = create_structured_tool()
+
+# Execute the tool with structured input
+result = structured_tool._run(**{
+    "endpoint": "https://example.com/api",
+    "parameters": {"key1": "value1", "key2": "value2"}
+})
+print(result)  # Output: Call the API at https://example.com/api with parameters {'key1': 'value1', 'key2': 'value2'}
+```
+
 ### Custom Caching Mechanism
 
 <Tip>

pyproject.toml

@@ -11,7 +11,7 @@ dependencies = [
     # Core Dependencies
     "pydantic>=2.4.2",
     "openai>=1.13.3",
-    "litellm==1.67.1",
+    "litellm==1.67.2",
     "instructor>=1.3.3",
     # Text Processing
     "pdfplumber>=0.11.4",
@@ -45,7 +45,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools~=0.42.2"]
+tools = ["crewai-tools~=0.42.0"]
 embeddings = [
     "tiktoken~=0.7.0"
 ]
@@ -60,7 +60,7 @@ pandas = [
 openpyxl = [
     "openpyxl>=3.1.5",
 ]
-mem0 = ["mem0ai>=0.1.94"]
+mem0 = ["mem0ai>=0.1.29"]
 docling = [
     "docling>=2.12.0",
 ]

src/crewai/agent.py

@@ -17,6 +17,7 @@ from crewai.security import Fingerprint
 from crewai.task import Task
 from crewai.tools import BaseTool
 from crewai.tools.agent_tools.agent_tools import AgentTools
+from crewai.tools.structured_tool import CrewStructuredTool
 from crewai.utilities import Converter, Prompts
 from crewai.utilities.agent_utils import (
     get_tool_names,
@@ -185,7 +186,7 @@ class Agent(BaseAgent):
         self,
         task: Task,
         context: Optional[str] = None,
-        tools: Optional[List[BaseTool]] = None
+        tools: Optional[List[Union[BaseTool, CrewStructuredTool]]] = None
     ) -> str:
         """Execute a task with the agent.
 
@@ -406,14 +407,14 @@ class Agent(BaseAgent):
         )["output"]
 
     def create_agent_executor(
-        self, tools: Optional[List[BaseTool]] = None, task=None
+        self, tools: Optional[List[Union[BaseTool, CrewStructuredTool]]] = None, task=None
     ) -> None:
         """Create an agent executor for the agent.
 
         Returns:
             An instance of the CrewAgentExecutor class.
         """
-        raw_tools: List[BaseTool] = tools or self.tools or []
+        raw_tools: List[Union[BaseTool, CrewStructuredTool]] = tools or self.tools or []
         parsed_tools = parse_tools(raw_tools)
 
         prompt = Prompts(

src/crewai/agents/agent_adapters/langgraph/__init__.py

@@ -1 +0,0 @@
-"""LangGraph adapter for crewAI."""

src/crewai/agents/agent_adapters/openai_agents/__init__.py

@@ -1 +0,0 @@
-"""OpenAI agent adapters for crewAI."""

src/crewai/cli/templates/crew/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.117.1,<1.0.0"
+    "crewai[tools]>=0.117.0,<1.0.0"
 ]
 
 [project.scripts]

src/crewai/cli/templates/flow/crews/poem_crew/__init__.py

@@ -1 +0,0 @@
-"""Poem crew template."""

src/crewai/cli/templates/flow/pyproject.toml

@@ -5,7 +5,7 @@ description = "{{name}} using crewAI"
 authors = [{ name = "Your Name", email = "you@example.com" }]
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.117.1,<1.0.0",
+    "crewai[tools]>=0.117.0,<1.0.0",
 ]
 
 [project.scripts]

src/crewai/cli/templates/tool/pyproject.toml

@@ -5,7 +5,7 @@ description = "Power up your crews with {{folder_name}}"
 readme = "README.md"
 requires-python = ">=3.10,<3.13"
 dependencies = [
-    "crewai[tools]>=0.117.1"
+    "crewai[tools]>=0.117.0"
 ]
 
 [tool.crewai]

src/crewai/knowledge/utils/__init__.py

@@ -1 +0,0 @@
-"""Knowledge utilities for crewAI."""

src/crewai/llm.py

@@ -483,7 +483,6 @@ class LLM(BaseLLM):
                     full_response += chunk_content
 
                     # Emit the chunk event
-                    assert hasattr(crewai_event_bus, "emit")
                     crewai_event_bus.emit(
                         self,
                         event=LLMStreamChunkEvent(chunk=chunk_content),
@@ -612,7 +611,6 @@ class LLM(BaseLLM):
                 return full_response
 
             # Emit failed event and re-raise the exception
-            assert hasattr(crewai_event_bus, "emit")
             crewai_event_bus.emit(
                 self,
                 event=LLMCallFailedEvent(error=str(e)),
@@ -635,7 +633,7 @@ class LLM(BaseLLM):
                 current_tool_accumulator.function.arguments += (
                     tool_call.function.arguments
                 )
-            assert hasattr(crewai_event_bus, "emit")
+
             crewai_event_bus.emit(
                 self,
                 event=LLMStreamChunkEvent(
@@ -808,7 +806,6 @@ class LLM(BaseLLM):
                     function_name, lambda: None
                 )  # Ensure fn is always a callable
                 logging.error(f"Error executing function '{function_name}': {e}")
-                assert hasattr(crewai_event_bus, "emit")
                 crewai_event_bus.emit(
                     self,
                     event=LLMCallFailedEvent(error=f"Tool execution error: {str(e)}"),
@@ -846,7 +843,6 @@ class LLM(BaseLLM):
             LLMContextLengthExceededException: If input exceeds model's context limit
         """
         # --- 1) Emit call started event
-        assert hasattr(crewai_event_bus, "emit")
         crewai_event_bus.emit(
             self,
             event=LLMCallStartedEvent(
@@ -895,7 +891,6 @@ class LLM(BaseLLM):
                 # whether to summarize the content or abort based on the respect_context_window flag
                 raise
             except Exception as e:
-                assert hasattr(crewai_event_bus, "emit")
                 crewai_event_bus.emit(
                     self,
                     event=LLMCallFailedEvent(error=str(e)),
@@ -910,7 +905,6 @@ class LLM(BaseLLM):
             response (str): The response from the LLM call.
             call_type (str): The type of call, either "tool_call" or "llm_call".
         """
-        assert hasattr(crewai_event_bus, "emit")
         crewai_event_bus.emit(
             self,
             event=LLMCallCompletedEvent(response=response, call_type=call_type),

src/crewai/llms/__init__.py

@@ -1 +0,0 @@
-"""LLM implementations for crewAI."""

src/crewai/llms/third_party/__init__.py

@@ -1 +0,0 @@
-"""Third-party LLM implementations for crewAI."""

src/crewai/memory/storage/__init__.py

@@ -1 +0,0 @@
-"""Memory storage implementations for crewAI."""

src/crewai/memory/storage/mem0_storage.py

@@ -88,9 +88,7 @@ class Mem0Storage(Storage):
             }
 
         if params:
-            if isinstance(self.memory, MemoryClient):
-                params["output_format"] = "v1.1"
-            self.memory.add(value, **params)
+            self.memory.add(value, **params | {"output_format": "v1.1"})
 
     def search(
         self,
@@ -98,7 +96,7 @@ class Mem0Storage(Storage):
         limit: int = 3,
         score_threshold: float = 0.35,
     ) -> List[Any]:
-        params = {"query": query, "limit": limit, "output_format": "v1.1"}
+        params = {"query": query, "limit": limit}
         if user_id := self._get_user_id():
             params["user_id"] = user_id
 
@@ -118,11 +116,8 @@ class Mem0Storage(Storage):
 
         # Discard the filters for now since we create the filters
         # automatically when the crew is created.
-        if isinstance(self.memory, Memory):
-            del params["metadata"], params["output_format"]
-            
         results = self.memory.search(**params)
-        return [r for r in results["results"] if r["score"] >= score_threshold]
+        return [r for r in results if r["score"] >= score_threshold]
 
     def _get_user_id(self) -> str:
         return self._get_config().get("user_id", "")

src/crewai/project/crew_base.py

@@ -8,6 +8,8 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
+logging.basicConfig(level=logging.WARNING)
+
 T = TypeVar("T", bound=type)
 
 """Base decorator for creating crew classes with configuration and function management."""
@@ -246,9 +248,6 @@ def CrewBase(cls: T) -> T:
                     callback_functions[callback]() for callback in callbacks
                 ]
 
-            if guardrail := task_info.get("guardrail"):
-                self.tasks_config[task_name]["guardrail"] = guardrail
-
     # Include base class (qual)name in the wrapper class (qual)name.
     WrappedClass.__name__ = CrewBase.__name__ + "(" + cls.__name__ + ")"
     WrappedClass.__qualname__ = CrewBase.__qualname__ + "(" + cls.__name__ + ")"

src/crewai/task.py

@@ -40,6 +40,7 @@ from crewai.tasks.guardrail_result import GuardrailResult
 from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
 from crewai.tools.base_tool import BaseTool
+from crewai.tools.structured_tool import CrewStructuredTool
 from crewai.utilities.config import process_config
 from crewai.utilities.converter import Converter, convert_to_model
 from crewai.utilities.events import (
@@ -72,7 +73,11 @@ class Task(BaseModel):
         security_config: Security configuration including fingerprinting.
         tools: List of tools/resources limited for task execution.
     """
-
+    
+    model_config = {
+        "arbitrary_types_allowed": True,
+    }
+    
     __hash__ = object.__hash__  # type: ignore
     logger: ClassVar[logging.Logger] = logging.getLogger(__name__)
     used_tools: int = 0
@@ -118,7 +123,7 @@ class Task(BaseModel):
     output: Optional[TaskOutput] = Field(
         description="Task output, it's final result after being executed", default=None
     )
-    tools: Optional[List[BaseTool]] = Field(
+    tools: Optional[List[Union[BaseTool, CrewStructuredTool]]] = Field(
         default_factory=list,
         description="Tools the agent is limited to use for this task.",
     )
@@ -140,9 +145,9 @@ class Task(BaseModel):
         default=None,
     )
     processed_by_agents: Set[str] = Field(default_factory=set)
-    guardrail: Optional[Union[Callable[[TaskOutput], Tuple[bool, Any]], str]] = Field(
+    guardrail: Optional[Callable[[TaskOutput], Tuple[bool, Any]]] = Field(
         default=None,
-        description="Function or string description of a guardrail to validate task output before proceeding to next task",
+        description="Function to validate task output before proceeding to next task",
     )
     max_retries: int = Field(
         default=3, description="Maximum number of retries when guardrail fails"
@@ -157,12 +162,8 @@ class Task(BaseModel):
 
     @field_validator("guardrail")
     @classmethod
-    def validate_guardrail_function(
-        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.
+    def validate_guardrail_function(cls, v: Optional[Callable]) -> Optional[Callable]:
+        """Validate that the guardrail function has the correct signature and behavior.
 
         While type hints provide static checking, this validator ensures runtime safety by:
         1. Verifying the function accepts exactly one parameter (the TaskOutput)
@@ -175,16 +176,16 @@ class Task(BaseModel):
         - Clear error messages help users debug guardrail implementation issues
 
         Args:
-            v: The guardrail function to validate or a string describing the guardrail task
+            v: The guardrail function to validate
 
         Returns:
-            The validated guardrail function or a string describing the guardrail task
+            The validated guardrail function
 
         Raises:
             ValueError: If the function signature is invalid or return annotation
                        doesn't match Tuple[bool, Any]
         """
-        if v is not None and callable(v):
+        if v is not None:
             sig = inspect.signature(v)
             positional_args = [
                 param
@@ -215,7 +216,6 @@ class Task(BaseModel):
                     )
         return v
 
-    _guardrail: Optional[Callable] = PrivateAttr(default=None)
     _original_description: Optional[str] = PrivateAttr(default=None)
     _original_expected_output: Optional[str] = PrivateAttr(default=None)
     _original_output_file: Optional[str] = PrivateAttr(default=None)
@@ -236,20 +236,6 @@ class Task(BaseModel):
                 )
         return self
 
-    @model_validator(mode="after")
-    def ensure_guardrail_is_callable(self) -> "Task":
-        if callable(self.guardrail):
-            self._guardrail = self.guardrail
-        elif isinstance(self.guardrail, str):
-            from crewai.tasks.task_guardrail import TaskGuardrail
-
-            assert self.agent is not None
-            self._guardrail = TaskGuardrail(
-                description=self.guardrail, llm=self.agent.llm
-            )
-
-        return self
-
     @field_validator("id", mode="before")
     @classmethod
     def _deny_user_set_id(cls, v: Optional[UUID4]) -> None:
@@ -426,8 +412,10 @@ class Task(BaseModel):
                 output_format=self._get_output_format(),
             )
 
-            if self._guardrail:
-                guardrail_result = self._process_guardrail(task_output)
+            if self.guardrail:
+                guardrail_result = GuardrailResult.from_tuple(
+                    self.guardrail(task_output)
+                )
                 if not guardrail_result.success:
                     if self.retry_count >= self.max_retries:
                         raise Exception(
@@ -481,46 +469,13 @@ 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:
-        assert self._guardrail is not None
-
-        from crewai.utilities.events import (
-            TaskGuardrailCompletedEvent,
-            TaskGuardrailStartedEvent,
-        )
-        from crewai.utilities.events.crewai_event_bus import crewai_event_bus
-
-        result = self._guardrail(task_output)
-
-        crewai_event_bus.emit(
-            self,
-            TaskGuardrailStartedEvent(
-                guardrail=self._guardrail, retry_count=self.retry_count
-            ),
-        )
-
-        guardrail_result = GuardrailResult.from_tuple(result)
-
-        crewai_event_bus.emit(
-            self,
-            TaskGuardrailCompletedEvent(
-                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/task_guardrail.py

@@ -1,92 +0,0 @@
-from typing import Any, Optional, Tuple
-
-from pydantic import BaseModel, Field
-
-from crewai.agent import Agent, LiteAgentOutput
-from crewai.llm import LLM
-from crewai.task import Task
-from crewai.tasks.task_output import TaskOutput
-
-
-class TaskGuardrailResult(BaseModel):
-    valid: bool = Field(
-        description="Whether the task output complies with the guardrail"
-    )
-    feedback: str | None = Field(
-        description="A feedback about the task output if it is not valid",
-        default=None,
-    )
-
-
-class TaskGuardrail:
-    """It validates the output of another task using an LLM.
-
-    This class is used to validate the output from a Task based on specified criteria.
-    It uses an LLM to validate the output and provides a feedback if the output is not valid.
-
-    Args:
-        description (str): The description of the validation criteria.
-        llm (LLM, optional): The language model to use for code generation.
-    """
-
-    def __init__(
-        self,
-        description: str,
-        llm: LLM,
-    ):
-        self.description = description
-
-        self.llm: LLM = llm
-
-    def _validate_output(self, task_output: TaskOutput) -> LiteAgentOutput:
-        agent = Agent(
-            role="Guardrail Agent",
-            goal="Validate the output of the task",
-            backstory="You are a expert at validating the output of a task. By providing effective feedback if the output is not valid.",
-            llm=self.llm,
-        )
-
-        query = f"""
-        Ensure the following task result complies with the given guardrail.
-
-        Task result:
-        {task_output.raw}
-
-        Guardrail:
-        {self.description}
-        
-        Your task:
-        - Confirm if the Task result complies with the guardrail.
-        - If not, provide clear feedback explaining what is wrong (e.g., by how much it violates the rule, or what specific part fails).
-        - Focus only on identifying issues — do not propose corrections.
-        - If the Task result complies with the guardrail, saying that is valid
-        """
-
-        result = agent.kickoff(query, response_format=TaskGuardrailResult)
-
-        return result
-
-    def __call__(self, task_output: TaskOutput) -> Tuple[bool, Any]:
-        """Validates the output of a task based on specified criteria.
-
-        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
-        """
-
-        try:
-            result = self._validate_output(task_output)
-            assert isinstance(
-                result.pydantic, TaskGuardrailResult
-            ), "The guardrail result is not a valid pydantic model"
-
-            if result.pydantic.valid:
-                return True, task_output.raw
-            else:
-                return False, result.pydantic.feedback
-        except Exception as e:
-            return False, f"Error while validating the task output: {str(e)}"

src/crewai/tools/agent_tools/__init__.py

@@ -1 +0,0 @@
-"""Agent tools for crewAI."""

src/crewai/utilities/agent_utils.py

@@ -21,15 +21,17 @@ from crewai.utilities.exceptions.context_window_exceeding_exception import (
 )
 
 
-def parse_tools(tools: List[BaseTool]) -> List[CrewStructuredTool]:
+def parse_tools(tools: List[Union[BaseTool, CrewStructuredTool]]) -> List[CrewStructuredTool]:
     """Parse tools to be used for the task."""
     tools_list = []
 
     for tool in tools:
         if isinstance(tool, CrewAITool):
             tools_list.append(tool.to_structured_tool())
+        elif isinstance(tool, CrewStructuredTool):
+            tools_list.append(tool)
         else:
-            raise ValueError("Tool is not a CrewStructuredTool or BaseTool")
+            raise ValueError("Tool must be an instance of BaseTool or CrewStructuredTool")
 
     return tools_list
 

src/crewai/utilities/evaluators/__init__.py

@@ -1 +0,0 @@
-"""Evaluators for crewAI."""

src/crewai/utilities/events/__init__.py

@@ -9,10 +9,6 @@ from .crew_events import (
     CrewTestCompletedEvent,
     CrewTestFailedEvent,
 )
-from .task_guardrail_events import (
-    TaskGuardrailCompletedEvent,
-    TaskGuardrailStartedEvent,
-)
 from .agent_events import (
     AgentExecutionStartedEvent,
     AgentExecutionCompletedEvent,

src/crewai/utilities/events/event_types.py

@@ -34,10 +34,6 @@ from .task_events import (
     TaskFailedEvent,
     TaskStartedEvent,
 )
-from .task_guardrail_events import (
-    TaskGuardrailCompletedEvent,
-    TaskGuardrailStartedEvent,
-)
 from .tool_usage_events import (
     ToolUsageErrorEvent,
     ToolUsageFinishedEvent,
@@ -72,6 +68,4 @@ EventTypes = Union[
     LLMCallCompletedEvent,
     LLMCallFailedEvent,
     LLMStreamChunkEvent,
-    TaskGuardrailStartedEvent,
-    TaskGuardrailCompletedEvent,
 ]

src/crewai/utilities/events/task_guardrail_events.py

@@ -1,38 +0,0 @@
-from typing import Any, Callable, Optional, Union
-
-from crewai.utilities.events.base_events import BaseEvent
-
-
-class TaskGuardrailStartedEvent(BaseEvent):
-    """Event emitted when a guardrail task starts
-
-    Attributes:
-        guardrail: The guardrail callable or TaskGuardrail instance
-        retry_count: The number of times the guardrail has been retried
-    """
-
-    type: str = "task_guardrail_started"
-    guardrail: Union[str, Callable]
-    retry_count: int
-
-    def __init__(self, **data):
-        from inspect import getsource
-
-        from crewai.tasks.task_guardrail import TaskGuardrail
-
-        super().__init__(**data)
-
-        if isinstance(self.guardrail, TaskGuardrail):
-            self.guardrail = self.guardrail.description.strip()
-        elif isinstance(self.guardrail, Callable):
-            self.guardrail = getsource(self.guardrail).strip()
-
-
-class TaskGuardrailCompletedEvent(BaseEvent):
-    """Event emitted when a guardrail task completes"""
-
-    type: str = "task_guardrail_completed"
-    success: bool
-    result: Any
-    error: Optional[str] = None
-    retry_count: int

src/crewai/utilities/events/utils/__init__.py

@@ -1 +0,0 @@
-"""Event utilities for crewAI."""

src/crewai/utilities/exceptions/__init__.py

@@ -1 +0,0 @@
-"""Exceptions for crewAI."""

src/crewai/utilities/prompts.py

@@ -54,12 +54,10 @@ class Prompts(BaseModel):
         response_template=None,
     ) -> str:
         """Constructs a prompt string from specified components."""
-        if not system_template or not prompt_template:
-            # If any of the required templates are missing, fall back to the default format
+        if not system_template and not prompt_template:
             prompt_parts = [self.i18n.slice(component) for component in components]
             prompt = "".join(prompt_parts)
         else:
-            # All templates are provided, use them
             prompt_parts = [
                 self.i18n.slice(component)
                 for component in components
@@ -69,12 +67,8 @@ class Prompts(BaseModel):
             prompt = prompt_template.replace(
                 "{{ .Prompt }}", "".join(self.i18n.slice("task"))
             )
-            # Handle missing response_template
-            if response_template:
-                response = response_template.split("{{ .Response }}")[0]
-                prompt = f"{system}\n{prompt}\n{response}"
-            else:
-                prompt = f"{system}\n{prompt}"
+            response = response_template.split("{{ .Response }}")[0]
+            prompt = f"{system}\n{prompt}\n{response}"
 
         prompt = (
             prompt.replace("{goal}", self.agent.goal)

tests/agent_test.py

@@ -72,54 +72,9 @@ def test_agent_creation():
     assert agent.role == "test role"
     assert agent.goal == "test goal"
     assert agent.backstory == "test backstory"
-
-def test_agent_with_only_system_template():
-    """Test that an agent with only system_template works without errors."""
-    agent = Agent(
-        role="Test Role",
-        goal="Test Goal",
-        backstory="Test Backstory",
-        allow_delegation=False,
-        system_template="You are a test agent...",
-        # prompt_template is intentionally missing
-    )
-
-    assert agent.role == "Test Role"
-    assert agent.goal == "Test Goal"
-    assert agent.backstory == "Test Backstory"
-
-def test_agent_with_only_prompt_template():
-    """Test that an agent with only system_template works without errors."""
-    agent = Agent(
-        role="Test Role",
-        goal="Test Goal",
-        backstory="Test Backstory",
-        allow_delegation=False,
-        prompt_template="You are a test agent...",
-        # prompt_template is intentionally missing
-    )
-
-    assert agent.role == "Test Role"
-    assert agent.goal == "Test Goal"
-    assert agent.backstory == "Test Backstory"
+    assert agent.tools == []
 
 
-def test_agent_with_missing_response_template():
-    """Test that an agent with system_template and prompt_template but no response_template works without errors."""
-    agent = Agent(
-        role="Test Role",
-        goal="Test Goal",
-        backstory="Test Backstory",
-        allow_delegation=False,
-        system_template="You are a test agent...",
-        prompt_template="This is a test prompt...",
-        # response_template is intentionally missing
-    )
-
-    assert agent.role == "Test Role"
-    assert agent.goal == "Test Goal"
-    assert agent.backstory == "Test Backstory"
-    
 def test_agent_default_values():
     agent = Agent(role="test role", goal="test goal", backstory="test backstory")
     assert agent.llm.model == "gpt-4o-mini"

tests/agents/agent_adapters/__init__.py

@@ -1 +0,0 @@
-"""Tests for agent adapters."""

tests/agents/agent_builder/__init__.py

@@ -1 +0,0 @@
-"""Tests for agent builder."""

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tests/cli/deploy/__init__.py

@@ -1 +0,0 @@
-"""Tests for CLI deploy."""

tests/config/tasks.yaml

@@ -6,7 +6,6 @@ research_task:
   expected_output: >
     A list with 10 bullet points of the most relevant information about {topic}
   agent: researcher
-  guardrail: ensure each bullet contains its source
 
 reporting_task:
   description: >

tests/memory/__init__.py

@@ -1 +0,0 @@
-"""Tests for memory."""

tests/memory/user_memory_test.py

@@ -1,3 +1,4 @@
+
 from unittest.mock import MagicMock, patch
 
 import pytest
@@ -64,4 +65,4 @@ def test_save_and_search(user_memory):
     with patch.object(UserMemory, 'search', return_value=expected_result) as mock_search:
         find = UserMemory.search("test value", score_threshold=0.01)[0]
         mock_search.assert_called_once_with("test value", score_threshold=0.01)
-        assert find == expected_result[0]
+        assert find == expected_result[0]

tests/project_test.py

@@ -1,5 +1,4 @@
 from typing import List
-from unittest.mock import patch
 
 import pytest
 
@@ -143,15 +142,6 @@ def test_agent_function_calling_llm():
     ), "agent's function_calling_llm is incorrect"
 
 
-def test_task_guardrail():
-    crew = InternalCrew()
-    research_task = crew.research_task()
-    assert research_task.guardrail == "ensure each bullet contains its source"
-
-    reporting_task = crew.reporting_task()
-    assert reporting_task.guardrail is None
-
-
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_before_kickoff_modification():
     crew = InternalCrew()

tests/storage/__init__.py

@@ -1 +0,0 @@
-"""Tests for storage."""

tests/storage/test_mem0_storage.py

@@ -15,7 +15,6 @@ from crewai.task import Task
 class MockCrew:
     def __init__(self, memory_config):
         self.memory_config = memory_config
-        self.agents = [MagicMock(role="Test Agent")]
 
 
 @pytest.fixture
@@ -108,13 +107,11 @@ def mem0_storage_with_memory_client_using_config_from_crew(mock_mem0_memory_clie
 
 
 @pytest.fixture
-def mem0_storage_with_memory_client_using_explictly_config(mock_mem0_memory_client, mock_mem0_memory):
+def mem0_storage_with_memory_client_using_explictly_config(mock_mem0_memory_client):
     """Fixture to create a Mem0Storage instance with mocked dependencies"""
 
-    # We need to patch both MemoryClient and Memory to prevent actual initialization
-    with patch.object(MemoryClient, "__new__", return_value=mock_mem0_memory_client), \
-         patch.object(Memory, "__new__", return_value=mock_mem0_memory):
-
+    # We need to patch the MemoryClient before it's instantiated
+    with patch.object(MemoryClient, "__new__", return_value=mock_mem0_memory_client):
         crew = MockCrew(
             memory_config={
                 "provider": "mem0",
@@ -158,82 +155,3 @@ def test_mem0_storage_with_explict_config(
         mem0_storage_with_memory_client_using_explictly_config.memory_config
         == expected_config
     )
-
-
-def test_save_method_with_memory_oss(mem0_storage_with_mocked_config):
-    """Test save method for different memory types"""
-    mem0_storage, _, _ = mem0_storage_with_mocked_config
-    mem0_storage.memory.add = MagicMock()
-    
-    # Test short_term memory type (already set in fixture)
-    test_value = "This is a test memory"
-    test_metadata = {"key": "value"}
-    
-    mem0_storage.save(test_value, test_metadata)
-    
-    mem0_storage.memory.add.assert_called_once_with(
-        test_value,
-        agent_id="Test_Agent",
-        infer=False,
-        metadata={"type": "short_term", "key": "value"},
-    )
-
-
-def test_save_method_with_memory_client(mem0_storage_with_memory_client_using_config_from_crew):
-    """Test save method for different memory types"""
-    mem0_storage = mem0_storage_with_memory_client_using_config_from_crew
-    mem0_storage.memory.add = MagicMock()
-    
-    # Test short_term memory type (already set in fixture)
-    test_value = "This is a test memory"
-    test_metadata = {"key": "value"}
-    
-    mem0_storage.save(test_value, test_metadata)
-    
-    mem0_storage.memory.add.assert_called_once_with(
-        test_value,
-        agent_id="Test_Agent",
-        infer=False,
-        metadata={"type": "short_term", "key": "value"},
-        output_format="v1.1"
-    )
-
-
-def test_search_method_with_memory_oss(mem0_storage_with_mocked_config):
-    """Test search method for different memory types"""
-    mem0_storage, _, _ = mem0_storage_with_mocked_config
-    mock_results = {"results": [{"score": 0.9, "content": "Result 1"}, {"score": 0.4, "content": "Result 2"}]}
-    mem0_storage.memory.search = MagicMock(return_value=mock_results)
-
-    results = mem0_storage.search("test query", limit=5, score_threshold=0.5)
-
-    mem0_storage.memory.search.assert_called_once_with(
-        query="test query", 
-        limit=5, 
-        agent_id="Test_Agent",
-        user_id="test_user"
-    )
-
-    assert len(results) == 1
-    assert results[0]["content"] == "Result 1"
-
-
-def test_search_method_with_memory_client(mem0_storage_with_memory_client_using_config_from_crew):
-    """Test search method for different memory types"""
-    mem0_storage = mem0_storage_with_memory_client_using_config_from_crew
-    mock_results = {"results": [{"score": 0.9, "content": "Result 1"}, {"score": 0.4, "content": "Result 2"}]}
-    mem0_storage.memory.search = MagicMock(return_value=mock_results)
-
-    results = mem0_storage.search("test query", limit=5, score_threshold=0.5)
-
-    mem0_storage.memory.search.assert_called_once_with(
-        query="test query", 
-        limit=5, 
-        agent_id="Test_Agent", 
-        metadata={"type": "short_term"},
-        user_id="test_user",
-        output_format='v1.1'
-    )
-
-    assert len(results) == 1
-    assert results[0]["content"] == "Result 1"

tests/test_task_guardrails.py

@@ -1,16 +1,11 @@
-from unittest.mock import ANY, Mock, patch
+"""Tests for task guardrails functionality."""
+
+from unittest.mock import Mock
 
 import pytest
 
-from crewai import Agent, Task
-from crewai.llm import LLM
-from crewai.tasks.task_guardrail import TaskGuardrail
+from crewai.task import Task
 from crewai.tasks.task_output import TaskOutput
-from crewai.utilities.events import (
-    TaskGuardrailCompletedEvent,
-    TaskGuardrailStartedEvent,
-)
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 
 
 def test_task_without_guardrail():
@@ -27,7 +22,7 @@ def test_task_without_guardrail():
     assert result.raw == "test result"
 
 
-def test_task_with_successful_guardrail_func():
+def test_task_with_successful_guardrail():
     """Test that successful guardrail validation passes transformed result."""
 
     def guardrail(result: TaskOutput):
@@ -132,138 +127,3 @@ 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.fixture
-def task_output():
-    return TaskOutput(
-        raw="""
-        Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry's standard dummy text ever
-        """,
-        description="Test task",
-        expected_output="Output",
-        agent="Test Agent",
-    )
-
-
-@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", 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", llm=LLM(model="gpt-4o")
-    )
-
-    result = guardrail(task_output)
-    assert result[0] is True
-    assert result[1] == task_output.raw
-
-
-@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(TaskGuardrailStartedEvent)
-        def handle_guardrail_started(source, event):
-            started_guardrail.append(
-                {"guardrail": event.guardrail, "retry_count": event.retry_count}
-            )
-
-        @crewai_event_bus.on(TaskGuardrailCompletedEvent)
-        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="Gather information about available books on the First World War",
-            agent=sample_agent,
-            expected_output="A list of available books on the First World War",
-            guardrail="Ensure the authors are from Italy",
-        )
-
-        result = task.execute_sync(agent=sample_agent)
-
-        def custom_guardrail(result: TaskOutput):
-            return (True, "good result from callable function")
-
-        task = Task(
-            description="Test task",
-            expected_output="Output",
-            guardrail=custom_guardrail,
-        )
-
-        task.execute_sync(agent=sample_agent)
-
-        expected_started_events = [
-            {"guardrail": "Ensure the authors are from Italy", "retry_count": 0},
-            {"guardrail": "Ensure the authors are from Italy", "retry_count": 1},
-            {
-                "guardrail": """def custom_guardrail(result: TaskOutput):
-            return (True, "good result from callable function")""",
-                "retry_count": 0,
-            },
-        ]
-
-        expected_completed_events = [
-            {
-                "success": False,
-                "result": None,
-                "error": "The task result does not comply with the guardrail because none of "
-                "the listed authors are from Italy. All authors mentioned are from "
-                "different countries, including Germany, the UK, the USA, and others, "
-                "which violates the requirement that authors must be Italian.",
-                "retry_count": 0,
-            },
-            {"success": True, "result": result.raw, "error": None, "retry_count": 1},
-            {
-                "success": True,
-                "result": "good result from callable function",
-                "error": None,
-                "retry_count": 0,
-            },
-        ]
-        assert started_guardrail == expected_started_events
-        assert completed_guardrail == expected_completed_events
-
-
-@pytest.mark.vcr(filter_headers=["authorization"])
-def test_guardrail_when_an_error_occurs(sample_agent, task_output):
-    with (
-        patch(
-            "crewai.Agent.kickoff",
-            side_effect=Exception("Unexpected error"),
-        ),
-        pytest.raises(
-            Exception,
-            match="Error while validating the task output: Unexpected error",
-        ),
-    ):
-        task = Task(
-            description="Gather information about available books on the First World War",
-            agent=sample_agent,
-            expected_output="A list of available books on the First World War",
-            guardrail="Ensure the authors are from Italy",
-            max_retries=0,
-        )
-        task.execute_sync(agent=sample_agent)

tests/tools/__init__.py

@@ -1 +0,0 @@
-"""Tests for tools."""

tests/tools/test_task_with_structured_tool.py

@@ -0,0 +1,62 @@
+import pytest
+from pydantic import BaseModel, Field
+
+from crewai.task import Task
+from crewai.tools.structured_tool import CrewStructuredTool
+
+
+@pytest.fixture
+def simple_tool_function():
+    def test_func(param1: str, param2: int = 0) -> str:
+        """Test function with basic params."""
+        return f"{param1} {param2}"
+
+    return test_func
+
+
+def test_task_with_structured_tool(simple_tool_function):
+    """Test that CrewStructuredTool can be used directly with Task."""
+    tool = CrewStructuredTool.from_function(
+        func=simple_tool_function,
+        name="test_tool",
+        description="Test tool description"
+    )
+    
+    task = Task(
+        description="Test task description",
+        expected_output="Expected output",
+        tools=[tool]
+    )
+    
+    assert len(task.tools) == 1
+    assert task.tools[0] == tool
+
+
+def test_mixed_tool_types(simple_tool_function):
+    """Test that both BaseTool and CrewStructuredTool can be used together with Task."""
+    from crewai.tools import BaseTool
+    
+    structured_tool = CrewStructuredTool.from_function(
+        func=simple_tool_function,
+        name="structured_tool",
+        description="Structured tool description"
+    )
+    
+    class TestBaseTool(BaseTool):
+        name: str = "base_tool"
+        description: str = "Base tool description"
+        
+        def _run(self, query: str) -> str:
+            return f"Result for {query}"
+    
+    base_tool = TestBaseTool()
+    
+    task = Task(
+        description="Test task description",
+        expected_output="Expected output",
+        tools=[structured_tool, base_tool]
+    )
+    
+    assert len(task.tools) == 2
+    assert task.tools[0] == structured_tool
+    assert isinstance(task.tools[1], BaseTool)

tests/utilities/__init__.py

@@ -1 +0,0 @@
-"""Tests for utilities."""

tests/utilities/evaluators/__init__.py

@@ -1 +0,0 @@
-"""Tests for evaluators."""

tests/utilities/events/__init__.py

@@ -1 +0,0 @@
-"""Tests for events."""