docs: add missing docs about LLMGuardrail events

Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>

docs/concepts/agents.mdx

@@ -295,6 +295,11 @@ multimodal_agent = Agent(
   - `"safe"`: Uses Docker (recommended for production)
   - `"unsafe"`: Direct execution (use only in trusted environments)
 
+<Note>
+  This runs a default Docker image. If you want to configure the docker image, the checkout the Code Interpreter Tool in the tools section.
+  Add the code interpreter tool as a tool in the agent as a tool parameter.
+  </Note>
+
 #### Advanced Features
 - `multimodal`: Enable multimodal capabilities for processing text and visual content
 - `reasoning`: Enable agent to reflect and create plans before executing tasks

docs/concepts/event-listener.mdx

@@ -233,6 +233,11 @@ CrewAI provides a wide range of events that you can listen for:
 - **KnowledgeQueryFailedEvent**: Emitted when a knowledge query fails
 - **KnowledgeSearchQueryFailedEvent**: Emitted when a knowledge search query fails
 
+### LLM Guardrail Events
+
+- **LLMGuardrailStartedEvent**: Emitted when a guardrail validation starts. Contains details about the guardrail being applied and retry count.
+- **LLMGuardrailCompletedEvent**: Emitted when a guardrail validation completes. Contains details about validation success/failure, results, and error messages if any.
+
 ### Flow Events
 
 - **FlowCreatedEvent**: Emitted when a Flow is created

docs/enterprise/features/integrations.mdx

@@ -96,7 +96,7 @@ email_agent = Agent(
     role="Email Manager",
     goal="Manage and organize email communications",
     backstory="An AI assistant specialized in email management and communication.",
-    tools=[enterprise_tools]
+    tools=enterprise_tools
 )
 
 # Task to send an email

docs/installation.mdx

@@ -22,7 +22,7 @@ Watch this video tutorial for a step-by-step demonstration of the installation p
 <Note>
   **Python Version Requirements**
 
-  CrewAI requires `Python >=3.10 and <=3.13`. Here's how to check your version:
+  CrewAI requires `Python >=3.10 and <3.14`. Here's how to check your version:
   ```bash
   python3 --version
   ```

docs/quickstart.mdx

@@ -212,7 +212,7 @@ Follow the steps below to get Crewing! 🚣‍♂️
 
   1. Log in to your CrewAI Enterprise account (create a free account at [app.crewai.com](https://app.crewai.com))
   2. Open Crew Studio
-  3. Type what is the automation you're tryign to build
+  3. Type what is the automation you're trying to build
   4. Create your tasks visually and connect them in sequence
   5. Configure your inputs and click "Download Code" or "Deploy"
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "crewai"
-version = "0.126.0"
+version = "0.130.0"
 description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
 readme = "README.md"
 requires-python = ">=3.10,<3.14"
@@ -47,7 +47,7 @@ Documentation = "https://docs.crewai.com"
 Repository = "https://github.com/crewAIInc/crewAI"
 
 [project.optional-dependencies]
-tools = ["crewai-tools~=0.46.0"]
+tools = ["crewai-tools~=0.47.1"]
 embeddings = [
     "tiktoken~=0.8.0"
 ]

src/crewai/__init__.py

@@ -18,7 +18,7 @@ warnings.filterwarnings(
     category=UserWarning,
     module="pydantic.main",
 )
-__version__ = "0.126.0"
+__version__ = "0.130.0"
 __all__ = [
     "Agent",
     "Crew",

src/crewai/agent.py

@@ -1,6 +1,6 @@
 import shutil
 import subprocess
-from typing import Any, Dict, List, Literal, Optional, Sequence, Type, Union
+from typing import Any, Callable, Dict, List, Literal, Optional, Sequence, Tuple, Type, Union
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
@@ -155,6 +155,13 @@ class Agent(BaseAgent):
         default=None,
         description="The Agent's role to be used from your repository.",
     )
+    guardrail: Optional[Union[Callable[[Any], Tuple[bool, Any]], str]] = Field(
+        default=None,
+        description="Function or string description of a guardrail to validate agent output"
+    )
+    guardrail_max_retries: int = Field(
+        default=3, description="Maximum number of retries when guardrail fails"
+    )
 
     @model_validator(mode="before")
     def validate_from_repository(cls, v):
@@ -780,6 +787,8 @@ class Agent(BaseAgent):
             response_format=response_format,
             i18n=self.i18n,
             original_agent=self,
+            guardrail=self.guardrail,
+            guardrail_max_retries=self.guardrail_max_retries,
         )
 
         return lite_agent.kickoff(messages)

src/crewai/agents/agent_builder/base_agent_executor_mixin.py

@@ -7,6 +7,7 @@ from crewai.utilities import I18N
 from crewai.utilities.converter import ConverterError
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
 from crewai.utilities.printer import Printer
+from crewai.utilities.events.event_listener import event_listener
 
 if TYPE_CHECKING:
     from crewai.agents.agent_builder.base_agent import BaseAgent
@@ -125,33 +126,38 @@ class CrewAgentExecutorMixin:
 
     def _ask_human_input(self, final_answer: str) -> str:
         """Prompt human input with mode-appropriate messaging."""
-        self._printer.print(
-            content=f"\033[1m\033[95m ## Final Result:\033[00m \033[92m{final_answer}\033[00m"
-        )
-
-        # Training mode prompt (single iteration)
-        if self.crew and getattr(self.crew, "_train", False):
-            prompt = (
-                "\n\n=====\n"
-                "## TRAINING MODE: Provide feedback to improve the agent's performance.\n"
-                "This will be used to train better versions of the agent.\n"
-                "Please provide detailed feedback about the result quality and reasoning process.\n"
-                "=====\n"
-            )
-        # Regular human-in-the-loop prompt (multiple iterations)
-        else:
-            prompt = (
-                "\n\n=====\n"
-                "## HUMAN FEEDBACK: Provide feedback on the Final Result and Agent's actions.\n"
-                "Please follow these guidelines:\n"
-                " - If you are happy with the result, simply hit Enter without typing anything.\n"
-                " - Otherwise, provide specific improvement requests.\n"
-                " - You can provide multiple rounds of feedback until satisfied.\n"
-                "=====\n"
+        event_listener.formatter.pause_live_updates()
+        
+        try:
+            self._printer.print(
+                content=f"\033[1m\033[95m ## Final Result:\033[00m \033[92m{final_answer}\033[00m"
             )
 
-        self._printer.print(content=prompt, color="bold_yellow")
-        response = input()
-        if response.strip() != "":
-            self._printer.print(content="\nProcessing your feedback...", color="cyan")
-        return response
+            # Training mode prompt (single iteration)
+            if self.crew and getattr(self.crew, "_train", False):
+                prompt = (
+                    "\n\n=====\n"
+                    "## TRAINING MODE: Provide feedback to improve the agent's performance.\n"
+                    "This will be used to train better versions of the agent.\n"
+                    "Please provide detailed feedback about the result quality and reasoning process.\n"
+                    "=====\n"
+                )
+            # Regular human-in-the-loop prompt (multiple iterations)
+            else:
+                prompt = (
+                    "\n\n=====\n"
+                    "## HUMAN FEEDBACK: Provide feedback on the Final Result and Agent's actions.\n"
+                    "Please follow these guidelines:\n"
+                    " - If you are happy with the result, simply hit Enter without typing anything.\n"
+                    " - Otherwise, provide specific improvement requests.\n"
+                    " - You can provide multiple rounds of feedback until satisfied.\n"
+                    "=====\n"
+                )
+
+            self._printer.print(content=prompt, color="bold_yellow")
+            response = input()
+            if response.strip() != "":
+                self._printer.print(content="\nProcessing your feedback...", color="cyan")
+            return response
+        finally:
+            event_listener.formatter.resume_live_updates()

src/crewai/agents/crew_agent_executor.py

@@ -25,12 +25,16 @@ from crewai.utilities.agent_utils import (
     has_reached_max_iterations,
     is_context_length_exceeded,
     process_llm_response,
-    show_agent_logs,
 )
 from crewai.utilities.constants import MAX_LLM_RETRY, TRAINING_DATA_FILE
 from crewai.utilities.logger import Logger
 from crewai.utilities.tool_utils import execute_tool_and_check_finality
 from crewai.utilities.training_handler import CrewTrainingHandler
+from crewai.utilities.events.agent_events import (
+    AgentLogsStartedEvent,
+    AgentLogsExecutionEvent,
+)
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 
 
 class CrewAgentExecutor(CrewAgentExecutorMixin):
@@ -263,26 +267,32 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         """Show logs for the start of agent execution."""
         if self.agent is None:
             raise ValueError("Agent cannot be None")
-        show_agent_logs(
-            printer=self._printer,
-            agent_role=self.agent.role,
-            task_description=(
-                getattr(self.task, "description") if self.task else "Not Found"
+
+        crewai_event_bus.emit(
+            self.agent,
+            AgentLogsStartedEvent(
+                agent_role=self.agent.role,
+                task_description=(
+                    getattr(self.task, "description") if self.task else "Not Found"
+                ),
+                verbose=self.agent.verbose
+                or (hasattr(self, "crew") and getattr(self.crew, "verbose", False)),
             ),
-            verbose=self.agent.verbose
-            or (hasattr(self, "crew") and getattr(self.crew, "verbose", False)),
         )
 
     def _show_logs(self, formatted_answer: Union[AgentAction, AgentFinish]):
         """Show logs for the agent's execution."""
         if self.agent is None:
             raise ValueError("Agent cannot be None")
-        show_agent_logs(
-            printer=self._printer,
-            agent_role=self.agent.role,
-            formatted_answer=formatted_answer,
-            verbose=self.agent.verbose
-            or (hasattr(self, "crew") and getattr(self.crew, "verbose", False)),
+
+        crewai_event_bus.emit(
+            self.agent,
+            AgentLogsExecutionEvent(
+                agent_role=self.agent.role,
+                formatted_answer=formatted_answer,
+                verbose=self.agent.verbose
+                or (hasattr(self, "crew") and getattr(self.crew, "verbose", False)),
+            ),
         )
 
     def _summarize_messages(self) -> None:

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,<3.14"
 dependencies = [
-    "crewai[tools]>=0.126.0,<1.0.0"
+    "crewai[tools]>=0.130.0,<1.0.0"
 ]
 
 [project.scripts]

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,<3.14"
 dependencies = [
-    "crewai[tools]>=0.126.0,<1.0.0",
+    "crewai[tools]>=0.130.0,<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,<3.14"
 dependencies = [
-    "crewai[tools]>=0.126.0"
+    "crewai[tools]>=0.130.0"
 ]
 
 [tool.crewai]

src/crewai/lite_agent.py

@@ -1,9 +1,33 @@
 import asyncio
+import inspect
 import uuid
-from datetime import datetime
-from typing import Any, Callable, Dict, List, Optional, Type, Union, cast
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    List,
+    Optional,
+    Tuple,
+    Type,
+    Union,
+    cast,
+    get_args,
+    get_origin,
+)
 
-from pydantic import BaseModel, Field, InstanceOf, PrivateAttr, model_validator
+try:
+    from typing import Self
+except ImportError:
+    from typing_extensions import Self
+
+from pydantic import (
+    BaseModel,
+    Field,
+    InstanceOf,
+    PrivateAttr,
+    model_validator,
+    field_validator,
+)
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
@@ -18,6 +42,7 @@ from crewai.llm import LLM
 from crewai.tools.base_tool import BaseTool
 from crewai.tools.structured_tool import CrewStructuredTool
 from crewai.utilities import I18N
+from crewai.utilities.guardrail import process_guardrail
 from crewai.utilities.agent_utils import (
     enforce_rpm_limit,
     format_message_for_llm,
@@ -33,10 +58,10 @@ from crewai.utilities.agent_utils import (
     parse_tools,
     process_llm_response,
     render_text_description_and_args,
-    show_agent_logs,
 )
-from crewai.utilities.converter import convert_to_model, generate_model_description
+from crewai.utilities.converter import generate_model_description
 from crewai.utilities.events.agent_events import (
+    AgentLogsExecutionEvent,
     LiteAgentExecutionCompletedEvent,
     LiteAgentExecutionErrorEvent,
     LiteAgentExecutionStartedEvent,
@@ -146,6 +171,17 @@ class LiteAgent(FlowTrackable, BaseModel):
         default=[], description="Callbacks to be used for the agent"
     )
 
+    # Guardrail Properties
+    guardrail: Optional[Union[Callable[[LiteAgentOutput], Tuple[bool, Any]], str]] = (
+        Field(
+            default=None,
+            description="Function or string description of a guardrail to validate agent output",
+        )
+    )
+    guardrail_max_retries: int = Field(
+        default=3, description="Maximum number of retries when guardrail fails"
+    )
+
     # State and Results
     tools_results: List[Dict[str, Any]] = Field(
         default=[], description="Results of the tools used by the agent."
@@ -163,6 +199,8 @@ class LiteAgent(FlowTrackable, BaseModel):
     _messages: List[Dict[str, str]] = PrivateAttr(default_factory=list)
     _iterations: int = PrivateAttr(default=0)
     _printer: Printer = PrivateAttr(default_factory=Printer)
+    _guardrail: Optional[Callable] = PrivateAttr(default=None)
+    _guardrail_retry_count: int = PrivateAttr(default=0)
 
     @model_validator(mode="after")
     def setup_llm(self):
@@ -184,6 +222,61 @@ class LiteAgent(FlowTrackable, BaseModel):
 
         return self
 
+    @model_validator(mode="after")
+    def ensure_guardrail_is_callable(self) -> Self:
+        if callable(self.guardrail):
+            self._guardrail = self.guardrail
+        elif isinstance(self.guardrail, str):
+            from crewai.tasks.llm_guardrail import LLMGuardrail
+
+            assert isinstance(self.llm, LLM)
+
+            self._guardrail = LLMGuardrail(description=self.guardrail, llm=self.llm)
+
+        return self
+
+    @field_validator("guardrail", mode="before")
+    @classmethod
+    def validate_guardrail_function(
+        cls, v: Optional[Union[Callable, str]]
+    ) -> Optional[Union[Callable, str]]:
+        """Validate that the guardrail function has the correct signature.
+
+        If v is a callable, validate that it has the correct signature.
+        If v is a string, return it as is.
+
+        Args:
+            v: The guardrail function to validate or a string describing the guardrail task
+
+        Returns:
+            The validated guardrail function or a string describing the guardrail task
+        """
+        if v is None or isinstance(v, str):
+            return v
+
+        # Check function signature
+        sig = inspect.signature(v)
+        if len(sig.parameters) != 1:
+            raise ValueError(
+                f"Guardrail function must accept exactly 1 parameter (LiteAgentOutput), "
+                f"but it accepts {len(sig.parameters)}"
+            )
+
+        # Check return annotation if present
+        if sig.return_annotation is not sig.empty:
+            if sig.return_annotation == Tuple[bool, Any]:
+                return v
+
+            origin = get_origin(sig.return_annotation)
+            args = get_args(sig.return_annotation)
+
+            if origin is not tuple or len(args) != 2 or args[0] is not bool:
+                raise ValueError(
+                    "If return type is annotated, it must be Tuple[bool, Any]"
+                )
+
+        return v
+
     @property
     def key(self) -> str:
         """Get the unique key for this agent instance."""
@@ -223,54 +316,7 @@ class LiteAgent(FlowTrackable, BaseModel):
             # Format messages for the LLM
             self._messages = self._format_messages(messages)
 
-            # Emit event for agent execution start
-            crewai_event_bus.emit(
-                self,
-                event=LiteAgentExecutionStartedEvent(
-                    agent_info=agent_info,
-                    tools=self._parsed_tools,
-                    messages=messages,
-                ),
-            )
-
-            # Execute the agent using invoke loop
-            agent_finish = self._invoke_loop()
-            formatted_result: Optional[BaseModel] = None
-            if self.response_format:
-                try:
-                    # Cast to BaseModel to ensure type safety
-                    result = self.response_format.model_validate_json(
-                        agent_finish.output
-                    )
-                    if isinstance(result, BaseModel):
-                        formatted_result = result
-                except Exception as e:
-                    self._printer.print(
-                        content=f"Failed to parse output into response format: {str(e)}",
-                        color="yellow",
-                    )
-
-            # Calculate token usage metrics
-            usage_metrics = self._token_process.get_summary()
-
-            # Create output
-            output = LiteAgentOutput(
-                raw=agent_finish.output,
-                pydantic=formatted_result,
-                agent_role=self.role,
-                usage_metrics=usage_metrics.model_dump() if usage_metrics else None,
-            )
-
-            # Emit completion event
-            crewai_event_bus.emit(
-                self,
-                event=LiteAgentExecutionCompletedEvent(
-                    agent_info=agent_info,
-                    output=agent_finish.output,
-                ),
-            )
-
-            return output
+            return self._execute_core(agent_info=agent_info)
 
         except Exception as e:
             self._printer.print(
@@ -288,6 +334,95 @@ class LiteAgent(FlowTrackable, BaseModel):
             )
             raise e
 
+    def _execute_core(self, agent_info: Dict[str, Any]) -> LiteAgentOutput:
+        # Emit event for agent execution start
+        crewai_event_bus.emit(
+            self,
+            event=LiteAgentExecutionStartedEvent(
+                agent_info=agent_info,
+                tools=self._parsed_tools,
+                messages=self._messages,
+            ),
+        )
+
+        # Execute the agent using invoke loop
+        agent_finish = self._invoke_loop()
+        formatted_result: Optional[BaseModel] = None
+        if self.response_format:
+            try:
+                # Cast to BaseModel to ensure type safety
+                result = self.response_format.model_validate_json(agent_finish.output)
+                if isinstance(result, BaseModel):
+                    formatted_result = result
+            except Exception as e:
+                self._printer.print(
+                    content=f"Failed to parse output into response format: {str(e)}",
+                    color="yellow",
+                )
+
+        # Calculate token usage metrics
+        usage_metrics = self._token_process.get_summary()
+
+        # Create output
+        output = LiteAgentOutput(
+            raw=agent_finish.output,
+            pydantic=formatted_result,
+            agent_role=self.role,
+            usage_metrics=usage_metrics.model_dump() if usage_metrics else None,
+        )
+
+        # Process guardrail if set
+        if self._guardrail is not None:
+            guardrail_result = process_guardrail(
+                output=output,
+                guardrail=self._guardrail,
+                retry_count=self._guardrail_retry_count,
+            )
+
+            if not guardrail_result.success:
+                if self._guardrail_retry_count >= self.guardrail_max_retries:
+                    raise Exception(
+                        f"Agent's guardrail failed validation after {self.guardrail_max_retries} retries. "
+                        f"Last error: {guardrail_result.error}"
+                    )
+                self._guardrail_retry_count += 1
+                if self.verbose:
+                    self._printer.print(
+                        f"Guardrail failed. Retrying ({self._guardrail_retry_count}/{self.guardrail_max_retries})..."
+                        f"\n{guardrail_result.error}"
+                    )
+
+                self._messages.append(
+                    {
+                        "role": "user",
+                        "content": guardrail_result.error
+                        or "Guardrail validation failed",
+                    }
+                )
+
+                return self._execute_core(agent_info=agent_info)
+
+            # Apply guardrail result if available
+            if guardrail_result.result is not None:
+                if isinstance(guardrail_result.result, str):
+                    output.raw = guardrail_result.result
+                elif isinstance(guardrail_result.result, BaseModel):
+                    output.pydantic = guardrail_result.result
+
+            usage_metrics = self._token_process.get_summary()
+            output.usage_metrics = usage_metrics.model_dump() if usage_metrics else None
+
+        # Emit completion event
+        crewai_event_bus.emit(
+            self,
+            event=LiteAgentExecutionCompletedEvent(
+                agent_info=agent_info,
+                output=agent_finish.output,
+            ),
+        )
+
+        return output
+
     async def kickoff_async(
         self, messages: Union[str, List[Dict[str, str]]]
     ) -> LiteAgentOutput:
@@ -467,11 +602,13 @@ class LiteAgent(FlowTrackable, BaseModel):
 
     def _show_logs(self, formatted_answer: Union[AgentAction, AgentFinish]):
         """Show logs for the agent's execution."""
-        show_agent_logs(
-            printer=self._printer,
-            agent_role=self.role,
-            formatted_answer=formatted_answer,
-            verbose=self.verbose,
+        crewai_event_bus.emit(
+            self,
+            AgentLogsExecutionEvent(
+                agent_role=self.role,
+                formatted_answer=formatted_answer,
+                verbose=self.verbose,
+            ),
         )
 
     def _append_message(self, text: str, role: str = "assistant") -> None:

src/crewai/memory/storage/mem0_storage.py

@@ -4,6 +4,9 @@ from typing import Any, Dict, List
 from mem0 import Memory, MemoryClient
 
 from crewai.memory.storage.interface import Storage
+from crewai.utilities.chromadb import sanitize_collection_name
+
+MAX_AGENT_ID_LENGTH_MEM0 = 255
 
 
 class Mem0Storage(Storage):
@@ -134,7 +137,7 @@ class Mem0Storage(Storage):
         agents = self.crew.agents
         agents = [self._sanitize_role(agent.role) for agent in agents]
         agents = "_".join(agents)
-        return agents
+        return sanitize_collection_name(name=agents,max_collection_length=MAX_AGENT_ID_LENGTH_MEM0)
 
     def _get_config(self) -> Dict[str, Any]:
         return self.config or getattr(self, "memory_config", {}).get("config", {}) or {}

src/crewai/task.py

@@ -35,12 +35,12 @@ from pydantic_core import PydanticCustomError
 
 from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.security import Fingerprint, SecurityConfig
-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.utilities.config import process_config
 from crewai.utilities.constants import NOT_SPECIFIED
+from crewai.utilities.guardrail import process_guardrail, GuardrailResult
 from crewai.utilities.converter import Converter, convert_to_model
 from crewai.utilities.events import (
     TaskCompletedEvent,
@@ -431,7 +431,11 @@ class Task(BaseModel):
             )
 
             if self._guardrail:
-                guardrail_result = self._process_guardrail(task_output)
+                guardrail_result = process_guardrail(
+                    output=task_output,
+                    guardrail=self._guardrail,
+                    retry_count=self.retry_count
+                )
                 if not guardrail_result.success:
                     if self.retry_count >= self.max_retries:
                         raise Exception(
@@ -527,10 +531,10 @@ class Task(BaseModel):
 
     def prompt(self) -> str:
         """Generates the task prompt with optional markdown formatting.
-        
+
         When the markdown attribute is True, instructions for formatting the
         response in Markdown syntax will be added to the prompt.
-        
+
         Returns:
             str: The formatted prompt string containing the task description,
                  expected output, and optional markdown formatting instructions.
@@ -541,7 +545,7 @@ class Task(BaseModel):
             expected_output=self.expected_output
         )
         tasks_slices = [self.description, output]
-        
+
         if self.markdown:
             markdown_instruction = """Your final answer MUST be formatted in Markdown syntax.
 Follow these guidelines:

src/crewai/telemetry/telemetry.py

@@ -8,7 +8,7 @@ import platform
 import warnings
 from contextlib import contextmanager
 from importlib.metadata import version
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any, Callable, Optional
 import threading
 
 from opentelemetry import trace
@@ -73,11 +73,16 @@ class Telemetry:
             with cls._lock:
                 if cls._instance is None:
                     cls._instance = super(Telemetry, cls).__new__(cls)
+                    cls._instance._initialized = False
         return cls._instance
 
     def __init__(self) -> None:
+        if hasattr(self, '_initialized') and self._initialized:
+            return
+        
         self.ready: bool = False
         self.trace_set: bool = False
+        self._initialized: bool = True
 
         if self._is_telemetry_disabled():
             return
@@ -113,6 +118,10 @@ class Telemetry:
             or os.getenv("CREWAI_DISABLE_TELEMETRY", "false").lower() == "true"
         )
 
+    def _should_execute_telemetry(self) -> bool:
+        """Check if telemetry operations should be executed."""
+        return self.ready and not self._is_telemetry_disabled()
+
     def set_tracer(self):
         if self.ready and not self.trace_set:
             try:
@@ -123,8 +132,9 @@ class Telemetry:
                 self.ready = False
                 self.trace_set = False
 
-    def _safe_telemetry_operation(self, operation):
-        if not self.ready:
+    def _safe_telemetry_operation(self, operation: Callable[[], None]) -> None:
+        """Execute telemetry operation safely, checking both readiness and environment variables."""
+        if not self._should_execute_telemetry():
             return
         try:
             operation()
@@ -423,7 +433,8 @@ class Telemetry:
 
             return span
 
-        return self._safe_telemetry_operation(operation)
+        self._safe_telemetry_operation(operation)
+        return None
 
     def task_ended(self, span: Span, task: Task, crew: Crew):
         """Records the completion of a task execution in a crew.
@@ -773,7 +784,8 @@ class Telemetry:
             return span
 
         if crew.share_crew:
-            return self._safe_telemetry_operation(operation)
+            self._safe_telemetry_operation(operation)
+            return operation()
         return None
 
     def end_crew(self, crew, final_string_output):

src/crewai/tools/base_tool.py

@@ -64,7 +64,7 @@ class BaseTool(BaseModel, ABC):
                 },
             },
         )
-        
+
     @field_validator("max_usage_count", mode="before")
     @classmethod
     def validate_max_usage_count(cls, v: int | None) -> int | None:
@@ -88,11 +88,11 @@ class BaseTool(BaseModel, ABC):
         # If _run is async, we safely run it
         if asyncio.iscoroutine(result):
             result = asyncio.run(result)
-            
+
         self.current_usage_count += 1
-        
+
         return result
-        
+
     def reset_usage_count(self) -> None:
         """Reset the current usage count to zero."""
         self.current_usage_count = 0
@@ -279,7 +279,7 @@ def to_langchain(
 def tool(*args, result_as_answer: bool = False, max_usage_count: int | None = None) -> Callable:
     """
     Decorator to create a tool from a function.
-    
+
     Args:
         *args: Positional arguments, either the function to decorate or the tool name.
         result_as_answer: Flag to indicate if the tool result should be used as the final agent answer.

src/crewai/utilities/chromadb.py

@@ -23,7 +23,7 @@ def is_ipv4_pattern(name: str) -> bool:
     return bool(IPV4_PATTERN.match(name))
 
 
-def sanitize_collection_name(name: Optional[str]) -> str:
+def sanitize_collection_name(name: Optional[str], max_collection_length: int = MAX_COLLECTION_LENGTH) -> str:
     """
     Sanitize a collection name to meet ChromaDB requirements:
     1. 3-63 characters long
@@ -54,8 +54,8 @@ def sanitize_collection_name(name: Optional[str]) -> str:
 
     if len(sanitized) < MIN_COLLECTION_LENGTH:
         sanitized = sanitized + "x" * (MIN_COLLECTION_LENGTH - len(sanitized))
-    if len(sanitized) > MAX_COLLECTION_LENGTH:
-        sanitized = sanitized[:MAX_COLLECTION_LENGTH]
+    if len(sanitized) > max_collection_length:
+        sanitized = sanitized[:max_collection_length]
         if not sanitized[-1].isalnum():
             sanitized = sanitized[:-1] + "z"
 

src/crewai/utilities/events/agent_events.py

@@ -102,3 +102,24 @@ class LiteAgentExecutionErrorEvent(BaseEvent):
     agent_info: Dict[str, Any]
     error: str
     type: str = "lite_agent_execution_error"
+
+
+# New logging events
+class AgentLogsStartedEvent(BaseEvent):
+    """Event emitted when agent logs should be shown at start"""
+
+    agent_role: str
+    task_description: Optional[str] = None
+    verbose: bool = False
+    type: str = "agent_logs_started"
+
+
+class AgentLogsExecutionEvent(BaseEvent):
+    """Event emitted when agent logs should be shown during execution"""
+
+    agent_role: str
+    formatted_answer: Any
+    verbose: bool = False
+    type: str = "agent_logs_execution"
+
+    model_config = {"arbitrary_types_allowed": True}

src/crewai/utilities/events/event_listener.py

@@ -27,6 +27,8 @@ from crewai.utilities.events.utils.console_formatter import ConsoleFormatter
 from .agent_events import (
     AgentExecutionCompletedEvent,
     AgentExecutionStartedEvent,
+    AgentLogsStartedEvent,
+    AgentLogsExecutionEvent,
     LiteAgentExecutionCompletedEvent,
     LiteAgentExecutionErrorEvent,
     LiteAgentExecutionStartedEvent,
@@ -108,6 +110,7 @@ class EventListener(BaseEventListener):
                 event.crew_name or "Crew",
                 source.id,
                 "completed",
+                final_string_output,
             )
 
         @crewai_event_bus.on(CrewKickoffFailedEvent)
@@ -286,13 +289,14 @@ class EventListener(BaseEventListener):
             if isinstance(source, LLM):
                 self.formatter.handle_llm_tool_usage_started(
                     event.tool_name,
+                    event.tool_args,
                 )
             else:
                 self.formatter.handle_tool_usage_started(
                     self.formatter.current_agent_branch,
                     event.tool_name,
-                self.formatter.current_crew_tree,
-            )
+                    self.formatter.current_crew_tree,
+                )
 
         @crewai_event_bus.on(ToolUsageFinishedEvent)
         def on_tool_usage_finished(source, event: ToolUsageFinishedEvent):
@@ -320,16 +324,20 @@ class EventListener(BaseEventListener):
                     event.tool_name,
                     event.error,
                     self.formatter.current_crew_tree,
-            )
+                )
 
         # ----------- LLM EVENTS -----------
 
         @crewai_event_bus.on(LLMCallStartedEvent)
         def on_llm_call_started(source, event: LLMCallStartedEvent):
-            self.formatter.handle_llm_call_started(
+            # Capture the returned tool branch and update the current_tool_branch reference
+            thinking_branch = self.formatter.handle_llm_call_started(
                 self.formatter.current_agent_branch,
                 self.formatter.current_crew_tree,
             )
+            # Update the formatter's current_tool_branch to ensure proper cleanup
+            if thinking_branch is not None:
+                self.formatter.current_tool_branch = thinking_branch
 
         @crewai_event_bus.on(LLMCallCompletedEvent)
         def on_llm_call_completed(source, event: LLMCallCompletedEvent):
@@ -462,5 +470,23 @@ class EventListener(BaseEventListener):
                 self.formatter.current_crew_tree,
             )
 
+        # ----------- AGENT LOGGING EVENTS -----------
+
+        @crewai_event_bus.on(AgentLogsStartedEvent)
+        def on_agent_logs_started(source, event: AgentLogsStartedEvent):
+            self.formatter.handle_agent_logs_started(
+                event.agent_role,
+                event.task_description,
+                event.verbose,
+            )
+
+        @crewai_event_bus.on(AgentLogsExecutionEvent)
+        def on_agent_logs_execution(source, event: AgentLogsExecutionEvent):
+            self.formatter.handle_agent_logs_execution(
+                event.agent_role,
+                event.formatted_answer,
+                event.verbose,
+            )
+
 
 event_listener = EventListener()

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

@@ -5,6 +5,7 @@ from rich.panel import Panel
 from rich.text import Text
 from rich.tree import Tree
 from rich.live import Live
+from rich.syntax import Syntax
 
 
 class ConsoleFormatter:
@@ -17,6 +18,7 @@ class ConsoleFormatter:
     current_lite_agent_branch: Optional[Tree] = None
     tool_usage_counts: Dict[str, int] = {}
     current_reasoning_branch: Optional[Tree] = None  # Track reasoning status
+    _live_paused: bool = False
     current_llm_tool_tree: Optional[Tree] = None
 
     def __init__(self, verbose: bool = False):
@@ -39,7 +41,12 @@ class ConsoleFormatter:
         )
 
     def create_status_content(
-        self, title: str, name: str, status_style: str = "blue", **fields
+        self,
+        title: str,
+        name: str,
+        status_style: str = "blue",
+        tool_args: Dict[str, Any] | str = "",
+        **fields,
     ) -> Text:
         """Create standardized status content with consistent formatting."""
         content = Text()
@@ -52,6 +59,8 @@ class ConsoleFormatter:
             content.append(
                 f"{value}\n", style=fields.get(f"{label}_style", status_style)
             )
+        content.append("Tool Args: ", style="white")
+        content.append(f"{tool_args}\n", style=status_style)
 
         return content
 
@@ -119,6 +128,19 @@ class ConsoleFormatter:
         # Finally, pass through to the regular Console.print implementation
         self.console.print(*args, **kwargs)
 
+    def pause_live_updates(self) -> None:
+        """Pause Live session updates to allow for human input without interference."""
+        if not self._live_paused:
+            if self._live:
+                self._live.stop()
+                self._live = None
+            self._live_paused = True
+
+    def resume_live_updates(self) -> None:
+        """Resume Live session updates after human input is complete."""
+        if self._live_paused:
+            self._live_paused = False
+
     def print_panel(
         self, content: Text, title: str, style: str = "blue", is_flow: bool = False
     ) -> None:
@@ -138,6 +160,7 @@ class ConsoleFormatter:
         crew_name: str,
         source_id: str,
         status: str = "completed",
+        final_string_output: str = "",
     ) -> None:
         """Handle crew tree updates with consistent formatting."""
         if not self.verbose or tree is None:
@@ -169,6 +192,7 @@ class ConsoleFormatter:
             style,
             ID=source_id,
         )
+        content.append(f"Final Output: {final_string_output}\n", style="white")
 
         self.print_panel(content, title, style)
 
@@ -441,12 +465,19 @@ class ConsoleFormatter:
     def handle_llm_tool_usage_started(
         self,
         tool_name: str,
+        tool_args: Dict[str, Any] | str,
     ):
-        tree = self.get_llm_tree(tool_name)
-        self.add_tree_node(tree, "🔄 Tool Usage Started", "green")
-        self.print(tree)
+        # Create status content for the tool usage
+        content = self.create_status_content(
+            "Tool Usage Started", tool_name, Status="In Progress", tool_args=tool_args
+        )
+
+        # Create and print the panel
+        self.print_panel(content, "Tool Usage", "green")
         self.print()
-        return tree
+
+        # Still return the tree for compatibility with existing code
+        return self.get_llm_tree(tool_name)
 
     def handle_llm_tool_usage_finished(
         self,
@@ -477,6 +508,7 @@ class ConsoleFormatter:
         agent_branch: Optional[Tree],
         tool_name: str,
         crew_tree: Optional[Tree],
+        tool_args: Dict[str, Any] | str = "",
     ) -> Optional[Tree]:
         """Handle tool usage started event."""
         if not self.verbose:
@@ -484,9 +516,7 @@ class ConsoleFormatter:
 
         # Parent for tool usage: LiteAgent > Agent > Task
         branch_to_use = (
-            self.current_lite_agent_branch
-            or agent_branch
-            or self.current_task_branch
+            self.current_lite_agent_branch or agent_branch or self.current_task_branch
         )
 
         # Render full crew tree when available for consistent live updates
@@ -595,9 +625,7 @@ class ConsoleFormatter:
 
         # Parent for tool usage: LiteAgent > Agent > Task
         branch_to_use = (
-            self.current_lite_agent_branch
-            or agent_branch
-            or self.current_task_branch
+            self.current_lite_agent_branch or agent_branch or self.current_task_branch
         )
 
         # Render full crew tree when available for consistent live updates
@@ -611,14 +639,21 @@ class ConsoleFormatter:
                 return None
 
         # Only add thinking status if we don't have a current tool branch
-        if self.current_tool_branch is None:
+        # or if the current tool branch is not a thinking node
+        should_add_thinking = self.current_tool_branch is None or "Thinking" not in str(
+            self.current_tool_branch.label
+        )
+
+        if should_add_thinking:
             tool_branch = branch_to_use.add("")
             self.update_tree_label(tool_branch, "🧠", "Thinking...", "blue")
             self.current_tool_branch = tool_branch
             self.print(tree_to_use)
             self.print()
             return tool_branch
-        return None
+
+        # Return the existing tool branch if it's already a thinking node
+        return self.current_tool_branch
 
     def handle_llm_call_completed(
         self,
@@ -627,7 +662,7 @@ class ConsoleFormatter:
         crew_tree: Optional[Tree],
     ) -> None:
         """Handle LLM call completed event."""
-        if not self.verbose or tool_branch is None:
+        if not self.verbose:
             return
 
         # Decide which tree to render: prefer full crew tree, else parent branch
@@ -635,23 +670,50 @@ class ConsoleFormatter:
         if tree_to_use is None:
             return
 
-        # Remove the thinking status node when complete
-        if "Thinking" in str(tool_branch.label):
+        # Try to remove the thinking status node - first try the provided tool_branch
+        thinking_branch_to_remove = None
+        removed = False
+
+        # Method 1: Use the provided tool_branch if it's a thinking node
+        if tool_branch is not None and "Thinking" in str(tool_branch.label):
+            thinking_branch_to_remove = tool_branch
+
+        # Method 2: Fallback - search for any thinking node if tool_branch is None or not thinking
+        if thinking_branch_to_remove is None:
             parents = [
                 self.current_lite_agent_branch,
                 self.current_agent_branch,
                 self.current_task_branch,
                 tree_to_use,
             ]
-            removed = False
             for parent in parents:
-                if isinstance(parent, Tree) and tool_branch in parent.children:
-                    parent.children.remove(tool_branch)
+                if isinstance(parent, Tree):
+                    for child in parent.children:
+                        if "Thinking" in str(child.label):
+                            thinking_branch_to_remove = child
+                            break
+                    if thinking_branch_to_remove:
+                        break
+
+        # Remove the thinking node if found
+        if thinking_branch_to_remove:
+            parents = [
+                self.current_lite_agent_branch,
+                self.current_agent_branch,
+                self.current_task_branch,
+                tree_to_use,
+            ]
+            for parent in parents:
+                if (
+                    isinstance(parent, Tree)
+                    and thinking_branch_to_remove in parent.children
+                ):
+                    parent.children.remove(thinking_branch_to_remove)
                     removed = True
                     break
 
             # Clear pointer if we just removed the current_tool_branch
-            if self.current_tool_branch is tool_branch:
+            if self.current_tool_branch is thinking_branch_to_remove:
                 self.current_tool_branch = None
 
             if removed:
@@ -668,9 +730,36 @@ class ConsoleFormatter:
         # Decide which tree to render: prefer full crew tree, else parent branch
         tree_to_use = self.current_crew_tree or crew_tree or self.current_task_branch
 
-        # Update tool branch if it exists
-        if tool_branch:
-            tool_branch.label = Text("❌ LLM Failed", style="red bold")
+        # Find the thinking branch to update (similar to completion logic)
+        thinking_branch_to_update = None
+
+        # Method 1: Use the provided tool_branch if it's a thinking node
+        if tool_branch is not None and "Thinking" in str(tool_branch.label):
+            thinking_branch_to_update = tool_branch
+
+        # Method 2: Fallback - search for any thinking node if tool_branch is None or not thinking
+        if thinking_branch_to_update is None:
+            parents = [
+                self.current_lite_agent_branch,
+                self.current_agent_branch,
+                self.current_task_branch,
+                tree_to_use,
+            ]
+            for parent in parents:
+                if isinstance(parent, Tree):
+                    for child in parent.children:
+                        if "Thinking" in str(child.label):
+                            thinking_branch_to_update = child
+                            break
+                    if thinking_branch_to_update:
+                        break
+
+        # Update the thinking branch to show failure
+        if thinking_branch_to_update:
+            thinking_branch_to_update.label = Text("❌ LLM Failed", style="red bold")
+            # Clear the current_tool_branch reference
+            if self.current_tool_branch is thinking_branch_to_update:
+                self.current_tool_branch = None
             if tree_to_use:
                 self.print(tree_to_use)
                 self.print()
@@ -1113,9 +1202,7 @@ class ConsoleFormatter:
 
         # Prefer LiteAgent > Agent > Task branch as the parent for reasoning
         branch_to_use = (
-            self.current_lite_agent_branch
-            or agent_branch
-            or self.current_task_branch
+            self.current_lite_agent_branch or agent_branch or self.current_task_branch
         )
 
         # We always want to render the full crew tree when possible so the
@@ -1162,7 +1249,9 @@ class ConsoleFormatter:
         )
 
         style = "green" if ready else "yellow"
-        status_text = "Reasoning Completed" if ready else "Reasoning Completed (Not Ready)"
+        status_text = (
+            "Reasoning Completed" if ready else "Reasoning Completed (Not Ready)"
+        )
 
         if reasoning_branch is not None:
             self.update_tree_label(reasoning_branch, "✅", status_text, style)
@@ -1219,3 +1308,149 @@ class ConsoleFormatter:
 
         # Clear stored branch after failure
         self.current_reasoning_branch = None
+
+    # ----------- AGENT LOGGING EVENTS -----------
+
+    def handle_agent_logs_started(
+        self,
+        agent_role: str,
+        task_description: Optional[str] = None,
+        verbose: bool = False,
+    ) -> None:
+        """Handle agent logs started event."""
+        if not verbose:
+            return
+
+        agent_role = agent_role.split("\n")[0]
+
+        # Create panel content
+        content = Text()
+        content.append("Agent: ", style="white")
+        content.append(f"{agent_role}", style="bright_green bold")
+
+        if task_description:
+            content.append("\n\nTask: ", style="white")
+            content.append(f"{task_description}", style="bright_green")
+
+        # Create and display the panel
+        agent_panel = Panel(
+            content,
+            title="🤖 Agent Started",
+            border_style="magenta",
+            padding=(1, 2),
+        )
+        self.print(agent_panel)
+        self.print()
+
+    def handle_agent_logs_execution(
+        self,
+        agent_role: str,
+        formatted_answer: Any,
+        verbose: bool = False,
+    ) -> None:
+        """Handle agent logs execution event."""
+        if not verbose:
+            return
+
+        from crewai.agents.parser import AgentAction, AgentFinish
+        import json
+        import re
+
+        agent_role = agent_role.split("\n")[0]
+
+        if isinstance(formatted_answer, AgentAction):
+            thought = re.sub(r"\n+", "\n", formatted_answer.thought)
+            formatted_json = json.dumps(
+                formatted_answer.tool_input,
+                indent=2,
+                ensure_ascii=False,
+            )
+
+            # Create content for the action panel
+            content = Text()
+            content.append("Agent: ", style="white")
+            content.append(f"{agent_role}\n\n", style="bright_green bold")
+
+            if thought and thought != "":
+                content.append("Thought: ", style="white")
+                content.append(f"{thought}\n\n", style="bright_green")
+
+            content.append("Using Tool: ", style="white")
+            content.append(f"{formatted_answer.tool}\n\n", style="bright_green bold")
+
+            content.append("Tool Input:\n", style="white")
+
+            # Create a syntax-highlighted JSON code block
+            json_syntax = Syntax(
+                formatted_json,
+                "json",
+                theme="monokai",
+                line_numbers=False,
+                background_color="default",
+            )
+
+            content.append("\n")
+
+            # Create separate panels for better organization
+            main_content = Text()
+            main_content.append("Agent: ", style="white")
+            main_content.append(f"{agent_role}\n\n", style="bright_green bold")
+
+            if thought and thought != "":
+                main_content.append("Thought: ", style="white")
+                main_content.append(f"{thought}\n\n", style="bright_green")
+
+            main_content.append("Using Tool: ", style="white")
+            main_content.append(f"{formatted_answer.tool}", style="bright_green bold")
+
+            # Create the main action panel
+            action_panel = Panel(
+                main_content,
+                title="🔧 Agent Tool Execution",
+                border_style="magenta",
+                padding=(1, 2),
+            )
+
+            # Create the JSON input panel
+            input_panel = Panel(
+                json_syntax,
+                title="Tool Input",
+                border_style="blue",
+                padding=(1, 2),
+            )
+
+            # Create tool output content with better formatting
+            output_text = str(formatted_answer.result)
+            if len(output_text) > 2000:
+                output_text = output_text[:1997] + "..."
+
+            output_panel = Panel(
+                Text(output_text, style="bright_green"),
+                title="Tool Output",
+                border_style="green",
+                padding=(1, 2),
+            )
+
+            # Print all panels
+            self.print(action_panel)
+            self.print(input_panel)
+            self.print(output_panel)
+            self.print()
+
+        elif isinstance(formatted_answer, AgentFinish):
+            # Create content for the finish panel
+            content = Text()
+            content.append("Agent: ", style="white")
+            content.append(f"{agent_role}\n\n", style="bright_green bold")
+            content.append("Final Answer:\n", style="white")
+            content.append(f"{formatted_answer.output}", style="bright_green")
+
+            # Create and display the finish panel
+            finish_panel = Panel(
+                content,
+                title="✅ Agent Final Answer",
+                border_style="green",
+                padding=(1, 2),
+            )
+            self.print(finish_panel)
+            self.print()

src/crewai/utilities/guardrail.py

@@ -1,15 +1,7 @@
-"""
-Module for handling task guardrail validation results.
-
-This module provides the GuardrailResult class which standardizes
-the way task guardrails return their validation results.
-"""
-
-from typing import Any, Optional, Tuple, Union
+from typing import Any, Callable, Optional, Tuple, Union
 
 from pydantic import BaseModel, field_validator
 
-
 class GuardrailResult(BaseModel):
     """Result from a task guardrail execution.
 
@@ -54,3 +46,48 @@ class GuardrailResult(BaseModel):
             result=data if success else None,
             error=data if not success else None
         )
+
+
+def process_guardrail(output: Any, guardrail: Callable, retry_count: int) -> GuardrailResult:
+    """Process the guardrail for the agent output.
+
+    Args:
+        output: The output to validate with the guardrail
+
+    Returns:
+        GuardrailResult: The result of the guardrail validation
+    """
+    from crewai.task import TaskOutput
+    from crewai.lite_agent import LiteAgentOutput
+
+    assert isinstance(output, TaskOutput) or isinstance(output, LiteAgentOutput), "Output must be a TaskOutput or LiteAgentOutput"
+
+    assert guardrail is not None
+
+    from crewai.utilities.events import (
+        LLMGuardrailCompletedEvent,
+        LLMGuardrailStartedEvent,
+    )
+    from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+
+    crewai_event_bus.emit(
+        None,
+        LLMGuardrailStartedEvent(
+            guardrail=guardrail, retry_count=retry_count
+        ),
+    )
+
+    result = guardrail(output)
+    guardrail_result = GuardrailResult.from_tuple(result)
+
+    crewai_event_bus.emit(
+        None,
+        LLMGuardrailCompletedEvent(
+            success=guardrail_result.success,
+            result=guardrail_result.result,
+            error=guardrail_result.error,
+            retry_count=retry_count,
+        ),
+    )
+
+    return guardrail_result

tests/agent_test.py

@@ -501,8 +501,7 @@ def test_agent_custom_max_iterations():
 def test_agent_repeated_tool_usage(capsys):
     @tool
     def get_final_answer() -> float:
-        """Get the final answer but don't give it yet, just re-use this
-        tool non-stop."""
+        """Get the final answer but don't give it yet, just re-use this tool non-stop."""
         return 42
 
     agent = Agent(
@@ -527,12 +526,42 @@ def test_agent_repeated_tool_usage(capsys):
     )
 
     captured = capsys.readouterr()
-
-    assert (
-        "I tried reusing the same input, I must stop using this action input. I'll try something else instead."
-        in captured.out
+    output = (
+        captured.out.replace("\n", " ")
+        .replace("  ", " ")
+        .strip()
+        .replace("╭", "")
+        .replace("╮", "")
+        .replace("╯", "")
+        .replace("╰", "")
+        .replace("│", "")
+        .replace("─", "")
+        .replace("[", "")
+        .replace("]", "")
+        .replace("bold", "")
+        .replace("blue", "")
+        .replace("yellow", "")
+        .replace("green", "")
+        .replace("red", "")
+        .replace("dim", "")
+        .replace("🤖", "")
+        .replace("🔧", "")
+        .replace("✅", "")
+        .replace("\x1b[93m", "")
+        .replace("\x1b[00m", "")
+        .replace("\\", "")
+        .replace('"', "")
+        .replace("'", "")
     )
 
+    # Look for the message in the normalized output, handling the apostrophe difference
+    expected_message = (
+        "I tried reusing the same input, I must stop using this action input."
+    )
+    assert (
+        expected_message in output
+    ), f"Expected message not found in output. Output was: {output}"
+
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_agent_repeated_tool_usage_check_even_with_disabled_cache(capsys):
@@ -564,11 +593,43 @@ def test_agent_repeated_tool_usage_check_even_with_disabled_cache(capsys):
     )
 
     captured = capsys.readouterr()
-    assert (
-        "I tried reusing the same input, I must stop using this action input. I'll try something else instead."
-        in captured.out
+    output = (
+        captured.out.replace("\n", " ")
+        .replace("  ", " ")
+        .strip()
+        .replace("╭", "")
+        .replace("╮", "")
+        .replace("╯", "")
+        .replace("╰", "")
+        .replace("│", "")
+        .replace("─", "")
+        .replace("[", "")
+        .replace("]", "")
+        .replace("bold", "")
+        .replace("blue", "")
+        .replace("yellow", "")
+        .replace("green", "")
+        .replace("red", "")
+        .replace("dim", "")
+        .replace("🤖", "")
+        .replace("🔧", "")
+        .replace("✅", "")
+        .replace("\x1b[93m", "")
+        .replace("\x1b[00m", "")
+        .replace("\\", "")
+        .replace('"', "")
+        .replace("'", "")
     )
 
+    # Look for the message in the normalized output, handling the apostrophe difference
+    expected_message = (
+        "I tried reusing the same input, I must stop using this action input"
+    )
+
+    assert (
+        expected_message in output
+    ), f"Expected message not found in output. Output was: {output}"
+
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_agent_moved_on_after_max_iterations():
@@ -2092,7 +2153,12 @@ def test_agent_from_repository_with_invalid_tools(mock_get_agent, mock_get_auth_
         "role": "test role",
         "goal": "test goal",
         "backstory": "test backstory",
-        "tools": [{"name": "DoesNotExist", "module": "crewai_tools",}],
+        "tools": [
+            {
+                "name": "DoesNotExist",
+                "module": "crewai_tools",
+            }
+        ],
     }
     mock_get_agent.return_value = mock_get_response
     with pytest.raises(
@@ -2131,7 +2197,9 @@ def test_agent_from_repository_agent_not_found(mock_get_agent, mock_get_auth_tok
 @patch("crewai.cli.plus_api.PlusAPI.get_agent")
 @patch("crewai.utilities.agent_utils.Settings")
 @patch("crewai.utilities.agent_utils.console")
-def test_agent_from_repository_displays_org_info(mock_console, mock_settings, mock_get_agent, mock_get_auth_token):
+def test_agent_from_repository_displays_org_info(
+    mock_console, mock_settings, mock_get_agent, mock_get_auth_token
+):
     mock_settings_instance = MagicMock()
     mock_settings_instance.org_uuid = "test-org-uuid"
     mock_settings_instance.org_name = "Test Organization"
@@ -2143,7 +2211,7 @@ def test_agent_from_repository_displays_org_info(mock_console, mock_settings, mo
         "role": "test role",
         "goal": "test goal",
         "backstory": "test backstory",
-        "tools": []
+        "tools": [],
     }
     mock_get_agent.return_value = mock_get_response
 
@@ -2151,7 +2219,7 @@ def test_agent_from_repository_displays_org_info(mock_console, mock_settings, mo
 
     mock_console.print.assert_any_call(
         "Fetching agent from organization: Test Organization (test-org-uuid)",
-        style="bold blue"
+        style="bold blue",
     )
 
     assert agent.role == "test role"
@@ -2162,7 +2230,9 @@ def test_agent_from_repository_displays_org_info(mock_console, mock_settings, mo
 @patch("crewai.cli.plus_api.PlusAPI.get_agent")
 @patch("crewai.utilities.agent_utils.Settings")
 @patch("crewai.utilities.agent_utils.console")
-def test_agent_from_repository_without_org_set(mock_console, mock_settings, mock_get_agent, mock_get_auth_token):
+def test_agent_from_repository_without_org_set(
+    mock_console, mock_settings, mock_get_agent, mock_get_auth_token
+):
     mock_settings_instance = MagicMock()
     mock_settings_instance.org_uuid = None
     mock_settings_instance.org_name = None
@@ -2175,11 +2245,11 @@ def test_agent_from_repository_without_org_set(mock_console, mock_settings, mock
 
     with pytest.raises(
         AgentRepositoryError,
-        match="Agent test_agent could not be loaded: Unauthorized access"
+        match="Agent test_agent could not be loaded: Unauthorized access",
     ):
         Agent(from_repository="test_agent")
 
     mock_console.print.assert_any_call(
         "No organization currently set. We recommend setting one before using: `crewai org switch <org_id>` command.",
-        style="yellow"
+        style="yellow",
     )

tests/cassettes/test_agent_output_when_guardrail_returns_base_model.yaml

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+      information about the best soccer players\n\nTo give my best complete final
+      answer to the task respond using the exact following format:\n\nThought: I now
+      can give a great answer\nFinal Answer: Your final answer must be the great and
+      the most complete as possible, it must be outcome described.\n\nI MUST use these
+      formats, my job depends on it!"}, {"role": "user", "content": "Top 10 best players
+      in the world?"}], "model": "gpt-4o-mini", "stop": ["\nObservation:"]}'
+    headers:
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tests/cassettes/test_guardrail_is_called_using_callable.yaml

@@ -0,0 +1,130 @@
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+- request:
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+      are an expert at gathering and organizing information. You carefully collect
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+      information about the best soccer players\n\nTo give my best complete final
+      answer to the task respond using the exact following format:\n\nThought: I now
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tests/cassettes/test_guardrail_is_called_using_string.yaml

@@ -0,0 +1,643 @@
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+- request:
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+      are an expert at gathering and organizing information. You carefully collect
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+      answer to the task respond using the exact following format:\n\nThought: I now
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+      information about the best soccer players\n\nTo give my best complete final
+      answer to the task respond using the exact following format:\n\nThought: I now
+      can give a great answer\nFinal Answer: Your final answer must be the great and
+      the most complete as possible, it must be outcome described.\n\nI MUST use these
+      formats, my job depends on it!"}, {"role": "user", "content": "Top 10 best players
+      in the world?"}, {"role": "assistant", "content": "Thought: I now can give a
+      great answer  \nFinal Answer: The top 10 best soccer players in the world, as
+      of October 2023, can be identified based on their recent performances, skills,
+      impact on games, and overall contributions to their teams. Here is the structured
+      list:\n\n1. **Lionel Messi (Inter Miami CF)**\n   - Position: Forward\n   -
+      Key Attributes: Dribbling, vision, goal-scoring ability.\n   - Achievements:
+      Multiple Ballon d''Or winner, Copa America champion, World Cup champion (2022).\n\n2.
+      **Kylian Mbapp\u00e9 (Paris Saint-Germain)**\n   - Position: Forward\n   - Key
+      Attributes: Speed, technique, finishing.\n   - Achievements: FIFA World Cup
+      champion (2018), Ligue 1 titles, multiple domestic cups.\n\n3. **Erling Haaland
+      (Manchester City)**\n   - Position: Forward\n   - Key Attributes: Power, speed,
+      goal-scoring instinct.\n   - Achievements: Bundesliga top scorer, UEFA Champions
+      League winner (2023), Premier League titles.\n\n4. **Kevin De Bruyne (Manchester
+      City)**\n   - Position: Midfielder\n   - Key Attributes: Passing, vision, creativity.\n   -
+      Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League
+      winner (2023).\n\n5. **Karim Benzema (Al-Ittihad)**\n   - Position: Forward\n   -
+      Key Attributes: Goal-scoring, playmaking, tactical intelligence.\n   - Achievements:
+      2022 Ballon d''Or winner, multiple Champions Leagues with Real Madrid.\n\n6.
+      **Neymar Jr. (Al Hilal)**\n   - Position: Forward\n   - Key Attributes: Flair,
+      dribbling, creativity.\n   - Achievements: Multiple domestic league titles,
+      Champions League runner-up.\n\n7. **Robert Lewandowski (FC Barcelona)**\n   -
+      Position: Forward\n   - Key Attributes: Finishing, positioning, aerial ability.\n   -
+      Achievements: FIFA Best Men''s Player, multiple Bundesliga titles, La Liga champion
+      (2023).\n\n8. **Mohamed Salah (Liverpool)**\n   - Position: Forward\n   - Key
+      Attributes: Speed, finishing, dribbling.\n   - Achievements: Premier League
+      champion, FA Cup, UEFA Champions League winner.\n\n9. **Vin\u00edcius J\u00fanior
+      (Real Madrid)**\n   - Position: Forward\n   - Key Attributes: Speed, dribbling,
+      creativity.\n   - Achievements: UEFA Champions League winner (2022), La Liga
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+      Achievements: Multiple Champions League titles, Ballon d''Or winner (2018).\n\nThis
+      list is compiled based on their current form, past performances, and contributions
+      to their respective teams in both domestic and international competitions. Player
+      rankings can vary based on personal opinion and specific criteria used for evaluation,
+      but these players have consistently been regarded as some of the best in the
+      world as of October 2023."}, {"role": "user", "content": "You are not allowed
+      to include Brazilian players"}, {"role": "assistant", "content": "Thought: I
+      now can give a great answer  \nFinal Answer: Here is an updated list of the
+      top 10 best soccer players in the world as of October 2023, excluding Brazilian
+      players:\n\n1. **Lionel Messi (Inter Miami CF)**\n   - Position: Forward\n   -
+      Key Attributes: Dribbling, vision, goal-scoring ability.\n   - Achievements:
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+      Achievements: Multiple Premier League titles, FA Cups, UEFA Champions League
+      winner (2023).\n\n5. **Karim Benzema (Al-Ittihad)**\n   - Position: Forward\n   -
+      Key Attributes: Goal-scoring, playmaking, tactical intelligence.\n   - Achievements:
+      2022 Ballon d''Or winner, multiple Champions Leagues with Real Madrid.\n\n6.
+      **Robert Lewandowski (FC Barcelona)**\n   - Position: Forward\n   - Key Attributes:
+      Finishing, positioning, aerial ability.\n   - Achievements: FIFA Best Men''s
+      Player, multiple Bundesliga titles, La Liga champion (2023).\n\n7. **Mohamed
+      Salah (Liverpool)**\n   - Position: Forward\n   - Key Attributes: Speed, finishing,
+      dribbling.\n   - Achievements: Premier League champion, FA Cup, UEFA Champions
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+      Forward\n   - Key Attributes: Speed, dribbling, creativity.\n   - Achievements:
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+      Golden Boot winner, Premier League titles, UEFA European Championship runner-up.\n\nThis
+      list has been adjusted to exclude Brazilian players and focuses on those who
+      have made significant impacts in their clubs and on the international stage
+      as of October 2023. Each player is recognized for their exceptional skills,
+      performances, and achievements."}, {"role": "user", "content": "You are not
+      allowed to include Brazilian players"}, {"role": "assistant", "content": "Thought:
+      I now can give a great answer  \nFinal Answer: Here is the revised list of the
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+      **Kylian Mbapp\u00e9 (Paris Saint-Germain)**\n   - Position: Forward\n   - Key
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+      to the restriction of excluding Brazilian players. Each player included has
+      demonstrated exceptional skills and remarkable performances, solidifying their
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+      message: OK
 version: 1

tests/crew_test.py

@@ -856,18 +856,22 @@ def test_crew_verbose_output(researcher, writer, capsys):
     )
 
     expected_strings = [
-        "\x1b[1m\x1b[95m# Agent:\x1b[00m \x1b[1m\x1b[92mResearcher",
-        "\x1b[00m\n\x1b[95m## Task:\x1b[00m \x1b[92mResearch AI advancements.",
-        "\x1b[1m\x1b[95m# Agent:\x1b[00m \x1b[1m\x1b[92mSenior Writer",
-        "\x1b[95m## Task:\x1b[00m \x1b[92mWrite about AI in healthcare.",
-        "\n\n\x1b[1m\x1b[95m# Agent:\x1b[00m \x1b[1m\x1b[92mResearcher",
-        "\x1b[00m\n\x1b[95m## Final Answer:",
-        "\n\n\x1b[1m\x1b[95m# Agent:\x1b[00m \x1b[1m\x1b[92mSenior Writer",
-        "\x1b[00m\n\x1b[95m## Final Answer:",
+        "🤖 Agent Started",
+        "Agent: Researcher",
+        "Task: Research AI advancements.",
+        "✅ Agent Final Answer",
+        "Agent: Researcher",
+        "🤖 Agent Started",
+        "Agent: Senior Writer",
+        "Task: Write about AI in healthcare.",
+        "✅ Agent Final Answer",
+        "Agent: Senior Writer",
     ]
 
     for expected_string in expected_strings:
-        assert expected_string in filtered_output
+        assert (
+            expected_string in filtered_output
+        ), f"Expected '{expected_string}' in output, but it was not found."
 
     # Now test with verbose set to False
     crew.verbose = False
@@ -1783,12 +1787,20 @@ def test_hierarchical_kickoff_usage_metrics_include_manager(researcher):
     )
 
     # ── 2.  Stub out each agent’s _token_process.get_summary() ───────────────────
-    researcher_metrics = UsageMetrics(total_tokens=120, prompt_tokens=80, completion_tokens=40, successful_requests=2)
-    manager_metrics = UsageMetrics(total_tokens=30, prompt_tokens=20, completion_tokens=10, successful_requests=1)
+    researcher_metrics = UsageMetrics(
+        total_tokens=120, prompt_tokens=80, completion_tokens=40, successful_requests=2
+    )
+    manager_metrics = UsageMetrics(
+        total_tokens=30, prompt_tokens=20, completion_tokens=10, successful_requests=1
+    )
 
     # Replace the internal _token_process objects with simple mocks
-    researcher._token_process = MagicMock(get_summary=MagicMock(return_value=researcher_metrics))
-    manager._token_process = MagicMock(get_summary=MagicMock(return_value=manager_metrics))
+    researcher._token_process = MagicMock(
+        get_summary=MagicMock(return_value=researcher_metrics)
+    )
+    manager._token_process = MagicMock(
+        get_summary=MagicMock(return_value=manager_metrics)
+    )
 
     # ── 3.  Create the crew (hierarchical!) and kick it off ──────────────────────
     crew = Crew(
@@ -1799,14 +1811,32 @@ def test_hierarchical_kickoff_usage_metrics_include_manager(researcher):
     )
 
     # We don’t care about LLM output here; patch execute_sync to avoid network
-    with patch.object(Task, "execute_sync", return_value=TaskOutput(description="dummy", raw="Hello", agent=researcher.role)):
+    with patch.object(
+        Task,
+        "execute_sync",
+        return_value=TaskOutput(
+            description="dummy", raw="Hello", agent=researcher.role
+        ),
+    ):
         crew.kickoff()
 
     # ── 4.  Assert the aggregated numbers are the *sum* of both agents ───────────
-    assert crew.usage_metrics.total_tokens == researcher_metrics.total_tokens + manager_metrics.total_tokens
-    assert crew.usage_metrics.prompt_tokens == researcher_metrics.prompt_tokens + manager_metrics.prompt_tokens
-    assert crew.usage_metrics.completion_tokens == researcher_metrics.completion_tokens + manager_metrics.completion_tokens
-    assert crew.usage_metrics.successful_requests == researcher_metrics.successful_requests + manager_metrics.successful_requests
+    assert (
+        crew.usage_metrics.total_tokens
+        == researcher_metrics.total_tokens + manager_metrics.total_tokens
+    )
+    assert (
+        crew.usage_metrics.prompt_tokens
+        == researcher_metrics.prompt_tokens + manager_metrics.prompt_tokens
+    )
+    assert (
+        crew.usage_metrics.completion_tokens
+        == researcher_metrics.completion_tokens + manager_metrics.completion_tokens
+    )
+    assert (
+        crew.usage_metrics.successful_requests
+        == researcher_metrics.successful_requests + manager_metrics.successful_requests
+    )
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -4450,27 +4480,29 @@ def test_sets_parent_flow_when_inside_flow(researcher, writer):
     assert result.parent_flow is flow
 
 
-def test_reset_knowledge_with_no_crew_knowledge(researcher,writer):
+def test_reset_knowledge_with_no_crew_knowledge(researcher, writer):
     crew = Crew(
         agents=[researcher, writer],
         process=Process.sequential,
         tasks=[
             Task(description="Task 1", expected_output="output", agent=researcher),
             Task(description="Task 2", expected_output="output", agent=writer),
-        ]
+        ],
     )
 
     with pytest.raises(RuntimeError) as excinfo:
-        crew.reset_memories(command_type='knowledge')
-        
+        crew.reset_memories(command_type="knowledge")
+
         # Optionally, you can also check the error message
-    assert "Crew Knowledge and Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message
+    assert "Crew Knowledge and Agent Knowledge memory system is not initialized" in str(
+        excinfo.value
+    )  # Replace with the expected message
 
 
-def test_reset_knowledge_with_only_crew_knowledge(researcher,writer):
+def test_reset_knowledge_with_only_crew_knowledge(researcher, writer):
     mock_ks = MagicMock(spec=Knowledge)
 
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
+    with patch.object(Crew, "reset_knowledge") as mock_reset_agent_knowledge:
         crew = Crew(
             agents=[researcher, writer],
             process=Process.sequential,
@@ -4478,14 +4510,14 @@ def test_reset_knowledge_with_only_crew_knowledge(researcher,writer):
                 Task(description="Task 1", expected_output="output", agent=researcher),
                 Task(description="Task 2", expected_output="output", agent=writer),
             ],
-            knowledge=mock_ks
+            knowledge=mock_ks,
         )
 
-        crew.reset_memories(command_type='knowledge')
+        crew.reset_memories(command_type="knowledge")
         mock_reset_agent_knowledge.assert_called_once_with([mock_ks])
 
 
-def test_reset_knowledge_with_crew_and_agent_knowledge(researcher,writer):
+def test_reset_knowledge_with_crew_and_agent_knowledge(researcher, writer):
     mock_ks_crew = MagicMock(spec=Knowledge)
     mock_ks_research = MagicMock(spec=Knowledge)
     mock_ks_writer = MagicMock(spec=Knowledge)
@@ -4493,7 +4525,7 @@ def test_reset_knowledge_with_crew_and_agent_knowledge(researcher,writer):
     researcher.knowledge = mock_ks_research
     writer.knowledge = mock_ks_writer
 
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
+    with patch.object(Crew, "reset_knowledge") as mock_reset_agent_knowledge:
         crew = Crew(
             agents=[researcher, writer],
             process=Process.sequential,
@@ -4501,21 +4533,23 @@ def test_reset_knowledge_with_crew_and_agent_knowledge(researcher,writer):
                 Task(description="Task 1", expected_output="output", agent=researcher),
                 Task(description="Task 2", expected_output="output", agent=writer),
             ],
-            knowledge=mock_ks_crew
+            knowledge=mock_ks_crew,
         )
 
-        crew.reset_memories(command_type='knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks_crew,mock_ks_research,mock_ks_writer])
+        crew.reset_memories(command_type="knowledge")
+        mock_reset_agent_knowledge.assert_called_once_with(
+            [mock_ks_crew, mock_ks_research, mock_ks_writer]
+        )
 
 
-def test_reset_knowledge_with_only_agent_knowledge(researcher,writer):
+def test_reset_knowledge_with_only_agent_knowledge(researcher, writer):
     mock_ks_research = MagicMock(spec=Knowledge)
     mock_ks_writer = MagicMock(spec=Knowledge)
 
     researcher.knowledge = mock_ks_research
     writer.knowledge = mock_ks_writer
 
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
+    with patch.object(Crew, "reset_knowledge") as mock_reset_agent_knowledge:
         crew = Crew(
             agents=[researcher, writer],
             process=Process.sequential,
@@ -4525,11 +4559,13 @@ def test_reset_knowledge_with_only_agent_knowledge(researcher,writer):
             ],
         )
 
-        crew.reset_memories(command_type='knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks_research,mock_ks_writer])
+        crew.reset_memories(command_type="knowledge")
+        mock_reset_agent_knowledge.assert_called_once_with(
+            [mock_ks_research, mock_ks_writer]
+        )
 
 
-def test_reset_agent_knowledge_with_no_agent_knowledge(researcher,writer):
+def test_reset_agent_knowledge_with_no_agent_knowledge(researcher, writer):
     crew = Crew(
         agents=[researcher, writer],
         process=Process.sequential,
@@ -4540,13 +4576,15 @@ def test_reset_agent_knowledge_with_no_agent_knowledge(researcher,writer):
     )
 
     with pytest.raises(RuntimeError) as excinfo:
-        crew.reset_memories(command_type='agent_knowledge')
-    
+        crew.reset_memories(command_type="agent_knowledge")
+
     # Optionally, you can also check the error message
-    assert "Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message
+    assert "Agent Knowledge memory system is not initialized" in str(
+        excinfo.value
+    )  # Replace with the expected message
 
 
-def test_reset_agent_knowledge_with_only_crew_knowledge(researcher,writer):
+def test_reset_agent_knowledge_with_only_crew_knowledge(researcher, writer):
     mock_ks = MagicMock(spec=Knowledge)
 
     crew = Crew(
@@ -4556,17 +4594,19 @@ def test_reset_agent_knowledge_with_only_crew_knowledge(researcher,writer):
             Task(description="Task 1", expected_output="output", agent=researcher),
             Task(description="Task 2", expected_output="output", agent=writer),
         ],
-        knowledge=mock_ks
+        knowledge=mock_ks,
     )
 
     with pytest.raises(RuntimeError) as excinfo:
-        crew.reset_memories(command_type='agent_knowledge')
-    
+        crew.reset_memories(command_type="agent_knowledge")
+
     # Optionally, you can also check the error message
-    assert "Agent Knowledge memory system is not initialized" in str(excinfo.value)  # Replace with the expected message
+    assert "Agent Knowledge memory system is not initialized" in str(
+        excinfo.value
+    )  # Replace with the expected message
 
 
-def test_reset_agent_knowledge_with_crew_and_agent_knowledge(researcher,writer):
+def test_reset_agent_knowledge_with_crew_and_agent_knowledge(researcher, writer):
     mock_ks_crew = MagicMock(spec=Knowledge)
     mock_ks_research = MagicMock(spec=Knowledge)
     mock_ks_writer = MagicMock(spec=Knowledge)
@@ -4574,7 +4614,7 @@ def test_reset_agent_knowledge_with_crew_and_agent_knowledge(researcher,writer):
     researcher.knowledge = mock_ks_research
     writer.knowledge = mock_ks_writer
 
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
+    with patch.object(Crew, "reset_knowledge") as mock_reset_agent_knowledge:
         crew = Crew(
             agents=[researcher, writer],
             process=Process.sequential,
@@ -4582,21 +4622,23 @@ def test_reset_agent_knowledge_with_crew_and_agent_knowledge(researcher,writer):
                 Task(description="Task 1", expected_output="output", agent=researcher),
                 Task(description="Task 2", expected_output="output", agent=writer),
             ],
-            knowledge=mock_ks_crew
+            knowledge=mock_ks_crew,
         )
 
-        crew.reset_memories(command_type='agent_knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks_research,mock_ks_writer])
+        crew.reset_memories(command_type="agent_knowledge")
+        mock_reset_agent_knowledge.assert_called_once_with(
+            [mock_ks_research, mock_ks_writer]
+        )
 
 
-def test_reset_agent_knowledge_with_only_agent_knowledge(researcher,writer):
+def test_reset_agent_knowledge_with_only_agent_knowledge(researcher, writer):
     mock_ks_research = MagicMock(spec=Knowledge)
     mock_ks_writer = MagicMock(spec=Knowledge)
 
     researcher.knowledge = mock_ks_research
     writer.knowledge = mock_ks_writer
 
-    with patch.object(Crew,'reset_knowledge') as mock_reset_agent_knowledge:
+    with patch.object(Crew, "reset_knowledge") as mock_reset_agent_knowledge:
         crew = Crew(
             agents=[researcher, writer],
             process=Process.sequential,
@@ -4606,5 +4648,7 @@ def test_reset_agent_knowledge_with_only_agent_knowledge(researcher,writer):
             ],
         )
 
-        crew.reset_memories(command_type='agent_knowledge')
-        mock_reset_agent_knowledge.assert_called_once_with([mock_ks_research,mock_ks_writer])
+        crew.reset_memories(command_type="agent_knowledge")
+        mock_reset_agent_knowledge.assert_called_once_with(
+            [mock_ks_research, mock_ks_writer]
+        )

tests/telemetry/test_telemetry.py

@@ -9,6 +9,14 @@ from crewai.telemetry import Telemetry
 from opentelemetry import trace
 
 
+@pytest.fixture(autouse=True)
+def cleanup_telemetry():
+    """Automatically clean up Telemetry singleton between tests."""
+    Telemetry._instance = None
+    yield
+    Telemetry._instance = None
+
+
 @pytest.mark.parametrize(
     "env_var,value,expected_ready",
     [

tests/telemetry/test_telemetry_disable.py

@@ -1,11 +1,19 @@
 import os
-from unittest.mock import patch
+from unittest.mock import patch, MagicMock
 
 import pytest
 
 from crewai.telemetry import Telemetry
 
 
+@pytest.fixture(autouse=True)
+def cleanup_telemetry():
+    """Automatically clean up Telemetry singleton between tests."""
+    Telemetry._instance = None
+    yield
+    Telemetry._instance = None
+
+
 @pytest.mark.parametrize("env_var,value,expected_ready", [
     ("OTEL_SDK_DISABLED", "true", False),
     ("OTEL_SDK_DISABLED", "TRUE", False),
@@ -28,3 +36,59 @@ def test_telemetry_enabled_by_default():
         with patch("crewai.telemetry.telemetry.TracerProvider"):
             telemetry = Telemetry()
             assert telemetry.ready is True
+
+
+def test_telemetry_disable_after_singleton_creation():
+    """Test that telemetry operations are disabled when env var is set after singleton creation."""
+    with patch.dict(os.environ, {}, clear=True):
+        with patch("crewai.telemetry.telemetry.TracerProvider"):
+            telemetry = Telemetry()
+            assert telemetry.ready is True
+            
+            mock_operation = MagicMock()
+            telemetry._safe_telemetry_operation(mock_operation)
+            mock_operation.assert_called_once()
+            
+            mock_operation.reset_mock()
+            
+            os.environ['CREWAI_DISABLE_TELEMETRY'] = 'true'
+            
+            telemetry._safe_telemetry_operation(mock_operation)
+            mock_operation.assert_not_called()
+
+
+def test_telemetry_disable_with_multiple_instances():
+    """Test that multiple telemetry instances respect dynamically changed env vars."""
+    with patch.dict(os.environ, {}, clear=True):
+        with patch("crewai.telemetry.telemetry.TracerProvider"):
+            telemetry1 = Telemetry()
+            assert telemetry1.ready is True
+            
+            os.environ['CREWAI_DISABLE_TELEMETRY'] = 'true'
+            
+            telemetry2 = Telemetry()
+            assert telemetry2 is telemetry1
+            assert telemetry2.ready is True
+            
+            mock_operation = MagicMock()
+            telemetry2._safe_telemetry_operation(mock_operation)
+            mock_operation.assert_not_called()
+
+
+def test_telemetry_otel_sdk_disabled_after_creation():
+    """Test that OTEL_SDK_DISABLED also works when set after singleton creation."""
+    with patch.dict(os.environ, {}, clear=True):
+        with patch("crewai.telemetry.telemetry.TracerProvider"):
+            telemetry = Telemetry()
+            assert telemetry.ready is True
+            
+            mock_operation = MagicMock()
+            telemetry._safe_telemetry_operation(mock_operation)
+            mock_operation.assert_called_once()
+            
+            mock_operation.reset_mock()
+            
+            os.environ['OTEL_SDK_DISABLED'] = 'true'
+            
+            telemetry._safe_telemetry_operation(mock_operation)
+            mock_operation.assert_not_called()

tests/test_flow_human_input_integration.py

@@ -0,0 +1,167 @@
+import pytest
+from unittest.mock import patch, MagicMock
+from crewai.utilities.events.event_listener import event_listener
+
+
+class TestFlowHumanInputIntegration:
+    """Test integration between Flow execution and human input functionality."""
+
+    def test_console_formatter_pause_resume_methods(self):
+        """Test that ConsoleFormatter pause/resume methods work correctly."""
+        formatter = event_listener.formatter
+        
+        original_paused_state = formatter._live_paused
+        
+        try:
+            formatter._live_paused = False
+            
+            formatter.pause_live_updates()
+            assert formatter._live_paused
+            
+            formatter.resume_live_updates()
+            assert not formatter._live_paused
+        finally:
+            formatter._live_paused = original_paused_state
+
+    @patch('builtins.input', return_value='')
+    def test_human_input_pauses_flow_updates(self, mock_input):
+        """Test that human input pauses Flow status updates."""
+        from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
+        
+        executor = CrewAgentExecutorMixin()
+        executor.crew = MagicMock()
+        executor.crew._train = False
+        executor._printer = MagicMock()
+        
+        formatter = event_listener.formatter
+        
+        original_paused_state = formatter._live_paused
+        
+        try:
+            formatter._live_paused = False
+            
+            with patch.object(formatter, 'pause_live_updates') as mock_pause, \
+                 patch.object(formatter, 'resume_live_updates') as mock_resume:
+                
+                result = executor._ask_human_input("Test result")
+                
+                mock_pause.assert_called_once()
+                mock_resume.assert_called_once()
+                mock_input.assert_called_once()
+                assert result == ''
+        finally:
+            formatter._live_paused = original_paused_state
+
+    @patch('builtins.input', side_effect=['feedback', ''])
+    def test_multiple_human_input_rounds(self, mock_input):
+        """Test multiple rounds of human input with Flow status management."""
+        from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
+        
+        executor = CrewAgentExecutorMixin()
+        executor.crew = MagicMock()
+        executor.crew._train = False
+        executor._printer = MagicMock()
+        
+        formatter = event_listener.formatter
+        
+        original_paused_state = formatter._live_paused
+        
+        try:
+            pause_calls = []
+            resume_calls = []
+            
+            def track_pause():
+                pause_calls.append(True)
+                
+            def track_resume():
+                resume_calls.append(True)
+            
+            with patch.object(formatter, 'pause_live_updates', side_effect=track_pause), \
+                 patch.object(formatter, 'resume_live_updates', side_effect=track_resume):
+                
+                result1 = executor._ask_human_input("Test result 1")
+                assert result1 == 'feedback'
+                
+                result2 = executor._ask_human_input("Test result 2")
+                assert result2 == ''
+                
+                assert len(pause_calls) == 2
+                assert len(resume_calls) == 2
+        finally:
+            formatter._live_paused = original_paused_state
+
+    def test_pause_resume_with_no_live_session(self):
+        """Test pause/resume methods handle case when no Live session exists."""
+        formatter = event_listener.formatter
+        
+        original_live = formatter._live
+        original_paused_state = formatter._live_paused
+        
+        try:
+            formatter._live = None
+            formatter._live_paused = False
+            
+            formatter.pause_live_updates()
+            formatter.resume_live_updates()
+            
+            assert not formatter._live_paused
+        finally:
+            formatter._live = original_live
+            formatter._live_paused = original_paused_state
+
+    def test_pause_resume_exception_handling(self):
+        """Test that resume is called even if exception occurs during human input."""
+        from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
+        
+        executor = CrewAgentExecutorMixin()
+        executor.crew = MagicMock()
+        executor.crew._train = False
+        executor._printer = MagicMock()
+        
+        formatter = event_listener.formatter
+        
+        original_paused_state = formatter._live_paused
+        
+        try:
+            with patch.object(formatter, 'pause_live_updates') as mock_pause, \
+                 patch.object(formatter, 'resume_live_updates') as mock_resume, \
+                 patch('builtins.input', side_effect=KeyboardInterrupt("Test exception")):
+                
+                with pytest.raises(KeyboardInterrupt):
+                    executor._ask_human_input("Test result")
+                
+                mock_pause.assert_called_once()
+                mock_resume.assert_called_once()
+        finally:
+            formatter._live_paused = original_paused_state
+
+    def test_training_mode_human_input(self):
+        """Test human input in training mode."""
+        from crewai.agents.agent_builder.base_agent_executor_mixin import CrewAgentExecutorMixin
+        
+        executor = CrewAgentExecutorMixin()
+        executor.crew = MagicMock()
+        executor.crew._train = True
+        executor._printer = MagicMock()
+        
+        formatter = event_listener.formatter
+        
+        original_paused_state = formatter._live_paused
+        
+        try:
+            with patch.object(formatter, 'pause_live_updates') as mock_pause, \
+                 patch.object(formatter, 'resume_live_updates') as mock_resume, \
+                 patch('builtins.input', return_value='training feedback'):
+                
+                result = executor._ask_human_input("Test result")
+                
+                mock_pause.assert_called_once()
+                mock_resume.assert_called_once()
+                assert result == 'training feedback'
+                
+                executor._printer.print.assert_called()
+                call_args = [call[1]['content'] for call in executor._printer.print.call_args_list]
+                training_prompt_found = any('TRAINING MODE' in content for content in call_args)
+                assert training_prompt_found
+        finally:
+            formatter._live_paused = original_paused_state

tests/test_lite_agent.py

@@ -1,4 +1,4 @@
-import asyncio
+from collections import defaultdict
 from typing import cast
 from unittest.mock import Mock
 
@@ -313,5 +313,108 @@ def test_sets_parent_flow_when_inside_flow():
             nonlocal captured_agent
             captured_agent = source
 
-        result = flow.kickoff()
+        flow.kickoff()
         assert captured_agent.parent_flow is flow
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_guardrail_is_called_using_string():
+    guardrail_events = defaultdict(list)
+    from crewai.utilities.events import LLMGuardrailCompletedEvent, LLMGuardrailStartedEvent
+    with crewai_event_bus.scoped_handlers():
+        @crewai_event_bus.on(LLMGuardrailStartedEvent)
+        def capture_guardrail_started(source, event):
+            guardrail_events["started"].append(event)
+
+        @crewai_event_bus.on(LLMGuardrailCompletedEvent)
+        def capture_guardrail_completed(source, event):
+            guardrail_events["completed"].append(event)
+
+        agent = Agent(
+            role="Sports Analyst",
+            goal="Gather information about the best soccer players",
+            backstory="""You are an expert at gathering and organizing information. You carefully collect details and present them in a structured way.""",
+            guardrail="""Only include Brazilian players, both women and men""",
+        )
+
+        result = agent.kickoff(messages="Top 10 best players in the world?")
+
+        assert len(guardrail_events['started']) == 2
+        assert len(guardrail_events['completed']) == 2
+        assert not guardrail_events['completed'][0].success
+        assert guardrail_events['completed'][1].success
+        assert "Here are the top 10 best soccer players in the world, focusing exclusively on Brazilian players" in result.raw
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_guardrail_is_called_using_callable():
+    guardrail_events = defaultdict(list)
+    from crewai.utilities.events import LLMGuardrailCompletedEvent, LLMGuardrailStartedEvent
+    with crewai_event_bus.scoped_handlers():
+        @crewai_event_bus.on(LLMGuardrailStartedEvent)
+        def capture_guardrail_started(source, event):
+            guardrail_events["started"].append(event)
+
+        @crewai_event_bus.on(LLMGuardrailCompletedEvent)
+        def capture_guardrail_completed(source, event):
+            guardrail_events["completed"].append(event)
+
+        agent = Agent(
+            role="Sports Analyst",
+            goal="Gather information about the best soccer players",
+            backstory="""You are an expert at gathering and organizing information. You carefully collect details and present them in a structured way.""",
+            guardrail=lambda output: (True, "Pelé - Santos, 1958"),
+        )
+
+        result = agent.kickoff(messages="Top 1 best players in the world?")
+
+        assert len(guardrail_events['started']) == 1
+        assert len(guardrail_events['completed']) == 1
+        assert guardrail_events['completed'][0].success
+        assert "Pelé - Santos, 1958" in result.raw
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_guardrail_reached_attempt_limit():
+    guardrail_events = defaultdict(list)
+    from crewai.utilities.events import LLMGuardrailCompletedEvent, LLMGuardrailStartedEvent
+    with crewai_event_bus.scoped_handlers():
+        @crewai_event_bus.on(LLMGuardrailStartedEvent)
+        def capture_guardrail_started(source, event):
+            guardrail_events["started"].append(event)
+
+        @crewai_event_bus.on(LLMGuardrailCompletedEvent)
+        def capture_guardrail_completed(source, event):
+            guardrail_events["completed"].append(event)
+
+        agent = Agent(
+            role="Sports Analyst",
+            goal="Gather information about the best soccer players",
+            backstory="""You are an expert at gathering and organizing information. You carefully collect details and present them in a structured way.""",
+            guardrail=lambda output: (False, "You are not allowed to include Brazilian players"),
+            guardrail_max_retries=2,
+        )
+
+        with pytest.raises(Exception, match="Agent's guardrail failed validation after 2 retries"):
+            agent.kickoff(messages="Top 10 best players in the world?")
+
+        assert len(guardrail_events['started']) == 3 # 2 retries + 1 initial call
+        assert len(guardrail_events['completed']) == 3 # 2 retries + 1 initial call
+        assert not guardrail_events['completed'][0].success
+        assert not guardrail_events['completed'][1].success
+        assert not guardrail_events['completed'][2].success
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_output_when_guardrail_returns_base_model():
+    class Player(BaseModel):
+        name: str
+        country: str
+
+    agent = Agent(
+        role="Sports Analyst",
+        goal="Gather information about the best soccer players",
+        backstory="""You are an expert at gathering and organizing information. You carefully collect details and present them in a structured way.""",
+        guardrail=lambda output: (True, Player(name="Lionel Messi", country="Argentina")),
+    )
+
+    result = agent.kickoff(messages="Top 10 best players in the world?")
+
+    assert result.pydantic == Player(name="Lionel Messi", country="Argentina")

tests/utilities/test_console_formatter_pause_resume.py

@@ -0,0 +1,116 @@
+from unittest.mock import MagicMock, patch
+from rich.tree import Tree
+from rich.live import Live
+from crewai.utilities.events.utils.console_formatter import ConsoleFormatter
+
+
+class TestConsoleFormatterPauseResume:
+    """Test ConsoleFormatter pause/resume functionality."""
+
+    def test_pause_live_updates_with_active_session(self):
+        """Test pausing when Live session is active."""
+        formatter = ConsoleFormatter()
+        
+        mock_live = MagicMock(spec=Live)
+        formatter._live = mock_live
+        formatter._live_paused = False
+        
+        formatter.pause_live_updates()
+        
+        mock_live.stop.assert_called_once()
+        assert formatter._live_paused
+
+    def test_pause_live_updates_when_already_paused(self):
+        """Test pausing when already paused does nothing."""
+        formatter = ConsoleFormatter()
+        
+        mock_live = MagicMock(spec=Live)
+        formatter._live = mock_live
+        formatter._live_paused = True
+        
+        formatter.pause_live_updates()
+        
+        mock_live.stop.assert_not_called()
+        assert formatter._live_paused
+
+    def test_pause_live_updates_with_no_session(self):
+        """Test pausing when no Live session exists."""
+        formatter = ConsoleFormatter()
+        
+        formatter._live = None
+        formatter._live_paused = False
+        
+        formatter.pause_live_updates()
+        
+        assert formatter._live_paused
+
+    def test_resume_live_updates_when_paused(self):
+        """Test resuming when paused."""
+        formatter = ConsoleFormatter()
+        
+        formatter._live_paused = True
+        
+        formatter.resume_live_updates()
+        
+        assert not formatter._live_paused
+
+    def test_resume_live_updates_when_not_paused(self):
+        """Test resuming when not paused does nothing."""
+        formatter = ConsoleFormatter()
+        
+        formatter._live_paused = False
+        
+        formatter.resume_live_updates()
+        
+        assert not formatter._live_paused
+
+    def test_print_after_resume_restarts_live_session(self):
+        """Test that printing a Tree after resume creates new Live session."""
+        formatter = ConsoleFormatter()
+        
+        formatter._live_paused = True
+        formatter._live = None
+        
+        formatter.resume_live_updates()
+        assert not formatter._live_paused
+        
+        tree = Tree("Test")
+        
+        with patch('crewai.utilities.events.utils.console_formatter.Live') as mock_live_class:
+            mock_live_instance = MagicMock()
+            mock_live_class.return_value = mock_live_instance
+            
+            formatter.print(tree)
+            
+            mock_live_class.assert_called_once()
+            mock_live_instance.start.assert_called_once()
+            assert formatter._live == mock_live_instance
+
+    def test_multiple_pause_resume_cycles(self):
+        """Test multiple pause/resume cycles work correctly."""
+        formatter = ConsoleFormatter()
+        
+        mock_live = MagicMock(spec=Live)
+        formatter._live = mock_live
+        formatter._live_paused = False
+        
+        formatter.pause_live_updates()
+        assert formatter._live_paused
+        mock_live.stop.assert_called_once()
+        assert formatter._live is None  # Live session should be cleared
+        
+        formatter.resume_live_updates()
+        assert not formatter._live_paused
+        
+        formatter.pause_live_updates()
+        assert formatter._live_paused
+        
+        formatter.resume_live_updates()
+        assert not formatter._live_paused
+
+    def test_pause_resume_state_initialization(self):
+        """Test that _live_paused is properly initialized."""
+        formatter = ConsoleFormatter()
+        
+        assert hasattr(formatter, '_live_paused')
+        assert not formatter._live_paused

uv.lock

@@ -725,7 +725,7 @@ wheels = [
 
 [[package]]
 name = "crewai"
-version = "0.126.0"
+version = "0.130.0"
 source = { editable = "." }
 dependencies = [
     { name = "appdirs" },
@@ -814,7 +814,7 @@ requires-dist = [
     { name = "blinker", specifier = ">=1.9.0" },
     { name = "chromadb", specifier = ">=0.5.23" },
     { name = "click", specifier = ">=8.1.7" },
-    { name = "crewai-tools", marker = "extra == 'tools'", specifier = "~=0.46.0" },
+    { name = "crewai-tools", marker = "extra == 'tools'", specifier = "~=0.47.1" },
     { name = "docling", marker = "extra == 'docling'", specifier = ">=2.12.0" },
     { name = "instructor", specifier = ">=1.3.3" },
     { name = "json-repair", specifier = ">=0.25.2" },
@@ -866,7 +866,7 @@ dev = [
 
 [[package]]
 name = "crewai-tools"
-version = "0.46.0"
+version = "0.47.1"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "chromadb" },
@@ -880,10 +880,11 @@ dependencies = [
     { name = "pyright" },
     { name = "pytube" },
     { name = "requests" },
+    { name = "tiktoken" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/0d/9e/69109f5d5b398b2edeccec1055e93cdceac3becd04407bcce97de6557180/crewai_tools-0.46.0.tar.gz", hash = "sha256:c8f89247199d528c77db4b450a1ca781b5d32405982467baf516ede4b2045bd1", size = 913715 }
+sdist = { url = "https://files.pythonhosted.org/packages/0e/cd/fc5a96be8c108febcc2c767714e3ec9b70cca9be8e6b29bba7c1874fb6d2/crewai_tools-0.47.1.tar.gz", hash = "sha256:4de5ebf320aeae317ffabe2e4704b98b5d791f663196871fb5ad2e7bbea14a82", size = 921418 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ab/62/0b68637ce820fbb0385495bd6d75ceb27de53f060df5417f293419826481/crewai_tools-0.46.0-py3-none-any.whl", hash = "sha256:f8e60723869ca36ede7b43dcc1491ebefc93410a972d97b7b0ce59c4bd7a826b", size = 606190 },
+    { url = "https://files.pythonhosted.org/packages/e3/2c/05d9fa584d9d814c0c8c4c3793df572222417695fe3d716f14bc274376d6/crewai_tools-0.47.1-py3-none-any.whl", hash = "sha256:4dc9bb0a08e3afa33c6b9efb163e47181801a7906be7241977426e6d3dec0a05", size = 606305 },
 ]
 
 [[package]]