docs: update Python version requirement from <=3.13 to <3.14

This correctly reflects support for all 3.13.x patch version

src/crewai/agent.py

@@ -1,6 +1,6 @@
 import shutil
 import subprocess
-from typing import Any, Callable, Dict, List, Literal, Optional, Sequence, Tuple, Type, Union
+from typing import Any, Dict, List, Literal, Optional, Sequence, Type, Union
 
 from pydantic import Field, InstanceOf, PrivateAttr, model_validator
 
@@ -155,13 +155,6 @@ 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):
@@ -787,8 +780,6 @@ 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

@@ -7,7 +7,6 @@ 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
@@ -126,9 +125,6 @@ class CrewAgentExecutorMixin:
 
     def _ask_human_input(self, final_answer: str) -> str:
         """Prompt human input with mode-appropriate messaging."""
-        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"
         )
@@ -159,5 +155,3 @@ class CrewAgentExecutorMixin:
         if response.strip() != "":
             self._printer.print(content="\nProcessing your feedback...", color="cyan")
         return response
-        finally:
-            event_listener.formatter.resume_live_updates()

src/crewai/lite_agent.py

@@ -1,14 +1,9 @@
 import asyncio
-import inspect
 import uuid
-from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union, cast, get_args, get_origin
+from datetime import datetime
+from typing import Any, Callable, Dict, List, Optional, Type, Union, cast
 
-try:
+from pydantic import BaseModel, Field, InstanceOf, PrivateAttr, model_validator
-    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
@@ -23,7 +18,6 @@ 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,
@@ -41,7 +35,7 @@ from crewai.utilities.agent_utils import (
     render_text_description_and_args,
     show_agent_logs,
 )
-from crewai.utilities.converter import generate_model_description
+from crewai.utilities.converter import convert_to_model, generate_model_description
 from crewai.utilities.events.agent_events import (
     LiteAgentExecutionCompletedEvent,
     LiteAgentExecutionErrorEvent,
@@ -152,15 +146,6 @@ 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."
@@ -178,9 +163,6 @@ 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):
@@ -202,60 +184,6 @@ 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."""
@@ -295,32 +223,13 @@ class LiteAgent(FlowTrackable, BaseModel):
             # Format messages for the LLM
             self._messages = self._format_messages(messages)
 
-            return self._execute_core(agent_info=agent_info)
-
-        except Exception as e:
-            self._printer.print(
-                content="Agent failed to reach a final answer. This is likely a bug - please report it.",
-                color="red",
-            )
-            handle_unknown_error(self._printer, e)
-            # Emit error event
-            crewai_event_bus.emit(
-                self,
-                event=LiteAgentExecutionErrorEvent(
-                    agent_info=agent_info,
-                    error=str(e),
-                ),
-            )
-            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,
+                    messages=messages,
                 ),
             )
 
@@ -352,44 +261,6 @@ class LiteAgent(FlowTrackable, BaseModel):
                 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,
@@ -401,6 +272,22 @@ class LiteAgent(FlowTrackable, BaseModel):
 
             return output
 
+        except Exception as e:
+            self._printer.print(
+                content="Agent failed to reach a final answer. This is likely a bug - please report it.",
+                color="red",
+            )
+            handle_unknown_error(self._printer, e)
+            # Emit error event
+            crewai_event_bus.emit(
+                self,
+                event=LiteAgentExecutionErrorEvent(
+                    agent_info=agent_info,
+                    error=str(e),
+                ),
+            )
+            raise e
+
     async def kickoff_async(
         self, messages: Union[str, List[Dict[str, str]]]
     ) -> LiteAgentOutput:

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,
@@ -431,11 +431,7 @@ class Task(BaseModel):
             )
 
             if self._guardrail:
-                guardrail_result = process_guardrail(
+                guardrail_result = self._process_guardrail(task_output)
-                    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(

src/crewai/tasks/guardrail_result.py

@@ -1,7 +1,15 @@
-from typing import Any, Callable, Optional, Tuple, Union
+"""
+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 pydantic import BaseModel, field_validator
 
+
 class GuardrailResult(BaseModel):
     """Result from a task guardrail execution.
 
@@ -46,48 +54,3 @@ 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

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, Callable, Optional
+from typing import TYPE_CHECKING, Any, Optional
 import threading
 
 from opentelemetry import trace
@@ -73,16 +73,11 @@ 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
@@ -118,10 +113,6 @@ 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:
@@ -132,9 +123,8 @@ class Telemetry:
                 self.ready = False
                 self.trace_set = False
 
-    def _safe_telemetry_operation(self, operation: Callable[[], None]) -> None:
+    def _safe_telemetry_operation(self, operation):
-        """Execute telemetry operation safely, checking both readiness and environment variables."""
+        if not self.ready:
-        if not self._should_execute_telemetry():
             return
         try:
             operation()
@@ -433,8 +423,7 @@ class Telemetry:
 
             return span
 
-        self._safe_telemetry_operation(operation)
+        return 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.
@@ -784,8 +773,7 @@ class Telemetry:
             return span
 
         if crew.share_crew:
-            self._safe_telemetry_operation(operation)
+            return self._safe_telemetry_operation(operation)
-            return operation()
         return None
 
     def end_crew(self, crew, final_string_output):

src/crewai/utilities/events/event_listener.py

@@ -326,14 +326,10 @@ class EventListener(BaseEventListener):
 
         @crewai_event_bus.on(LLMCallStartedEvent)
         def on_llm_call_started(source, event: LLMCallStartedEvent):
-            # Capture the returned tool branch and update the current_tool_branch reference
+            self.formatter.handle_llm_call_started(
-            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):

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

@@ -17,7 +17,6 @@ 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):
@@ -120,19 +119,6 @@ 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:
@@ -625,22 +611,14 @@ class ConsoleFormatter:
                 return None
 
         # Only add thinking status if we don't have a current tool branch
-        # or if the current tool branch is not a thinking node
+        if self.current_tool_branch is None:
-        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,
@@ -649,7 +627,7 @@ class ConsoleFormatter:
         crew_tree: Optional[Tree],
     ) -> None:
         """Handle LLM call completed event."""
-        if not self.verbose:
+        if not self.verbose or tool_branch is None:
             return
 
         # Decide which tree to render: prefer full crew tree, else parent branch
@@ -657,47 +635,23 @@ class ConsoleFormatter:
         if tree_to_use is None:
             return
 
-        # Try to remove the thinking status node - first try the provided tool_branch
+        # Remove the thinking status node when complete
-        thinking_branch_to_remove = None
+        if "Thinking" in str(tool_branch.label):
+            parents = [
+                self.current_lite_agent_branch,
+                self.current_agent_branch,
+                self.current_task_branch,
+                tree_to_use,
+            ]
             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,
-            ]
             for parent in parents:
-                if isinstance(parent, Tree):
+                if isinstance(parent, Tree) and tool_branch in parent.children:
-                    for child in parent.children:
+                    parent.children.remove(tool_branch)
-                        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 thinking_branch_to_remove:
+            if self.current_tool_branch is tool_branch:
                 self.current_tool_branch = None
 
             if removed:
@@ -714,36 +668,9 @@ 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
 
-        # Find the thinking branch to update (similar to completion logic)
+        # Update tool branch if it exists
-        thinking_branch_to_update = None
+        if tool_branch:
-
+            tool_branch.label = Text("❌ LLM Failed", style="red bold")
-        # 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()

tests/cassettes/test_agent_output_when_guardrail_returns_base_model.yaml

@@ -1,137 +0,0 @@
-interactions:
-- request:
-    body: '{"messages": [{"role": "system", "content": "You are Sports Analyst. You
-      are an expert at gathering and organizing information. You carefully collect
-      details and present them in a structured way.\nYour personal goal is: Gather
-      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:
-      accept:
-      - application/json
-      accept-encoding:
-      - gzip, deflate, zstd
-      connection:
-      - keep-alive
-      content-length:
-      - '694'
-      content-type:
-      - application/json
-      host:
-      - api.openai.com
-      user-agent:
-      - OpenAI/Python 1.78.0
-      x-stainless-arch:
-      - arm64
-      x-stainless-async:
-      - 'false'
-      x-stainless-lang:
-      - python
-      x-stainless-os:
-      - MacOS
-      x-stainless-package-version:
-      - 1.78.0
-      x-stainless-raw-response:
-      - 'true'
-      x-stainless-read-timeout:
-      - '600.0'
-      x-stainless-retry-count:
-      - '0'
-      x-stainless-runtime:
-      - CPython
-      x-stainless-runtime-version:
-      - 3.12.9
-    method: POST
-    uri: https://api.openai.com/v1/chat/completions
-  response:
-    body:
-      string: !!binary |
-        H4sIAAAAAAAAAwAAAP//nFfNchtHDr7rKVBz0a6KVJGUZMm6SVrJcSw6Ktmb7NY6pQJ7wBlEPd1T
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-      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. **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 League winner.\n\n8. **Luka Modri\u0107 (Real Madrid)**\n   -
-      Position: Midfielder\n   - Key Attributes: Passing, vision, tactical intelligence.\n   -
-      Achievements: Multiple Champions League titles, Ballon d''Or winner (2018).\n\n9.
-      **Harry Kane (Bayern Munich)**\n   - Position: Forward\n   - Key Attributes:
-      Goal-scoring, technique, playmaking.\n   - Achievements: Golden Boot winner,
-      Premier League titles, UEFA European Championship runner-up.\n\n10. **Rodri
-      (Manchester City)**\n    - Position: Midfielder\n    - Key Attributes: Defensive
-      skills, passing, positional awareness.\n    - Achievements: Premier League titles,
-      UEFA Champions League winner (2023).\n\nThis list is curated while adhering
-      to the restriction of excluding Brazilian players. Each player included has
-      demonstrated exceptional skills and remarkable performances, solidifying their
-      status as some of the best in the world as of October 2023."}, {"role": "user",
-      "content": "You are not allowed to include Brazilian players"}], "model": "gpt-4o-mini",
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tests/telemetry/test_telemetry.py

@@ -9,14 +9,6 @@ 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

@@ -1,19 +1,11 @@
 import os
-from unittest.mock import patch, MagicMock
+from unittest.mock import patch
 
 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),
@@ -36,59 +28,3 @@ 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

@@ -1,167 +0,0 @@
-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 @@
-from collections import defaultdict
+import asyncio
 from typing import cast
 from unittest.mock import Mock
 
@@ -313,108 +313,5 @@ def test_sets_parent_flow_when_inside_flow():
             nonlocal captured_agent
             captured_agent = source
 
-        flow.kickoff()
+        result = 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

@@ -1,116 +0,0 @@
-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