Merge branch 'main' into bugfix/fix-type-error-in-token-counter

- Modify `Agent` class to add `set_knowledge` method
- Allow setting embedder from crew-level configuration
- Remove `_set_knowledge` method from initialization
- Update `Crew` class to set agent knowledge during agent setup
- Add default implementation in `BaseAgent` for compatibility

.gitignore

@@ -21,4 +21,5 @@ crew_tasks_output.json
 .mypy_cache
 .ruff_cache
 .venv
-agentops.log
+agentops.log
+test_flow.html

docs/concepts/memory.mdx

@@ -506,7 +506,7 @@ my_crew = Crew(
 )
 ```
 
-### Resetting Memory
+### Resetting Memory via cli
 
 ```shell
 crewai reset-memories [OPTIONS]
@@ -520,8 +520,46 @@ crewai reset-memories [OPTIONS]
 | `-s`, `--short`    | Reset SHORT TERM memory.         | Flag (boolean) | False   |
 | `-e`, `--entities` | Reset ENTITIES memory.           | Flag (boolean) | False   |
 | `-k`, `--kickoff-outputs` | Reset LATEST KICKOFF TASK OUTPUTS. | Flag (boolean) | False   |
+| `-kn`, `--knowledge` | Reset KNOWLEDEGE storage | Flag (boolean) | False   |
 | `-a`, `--all`      | Reset ALL memories.              | Flag (boolean) | False   |
 
+Note: To use the cli command you need to have your crew in a file called crew.py in the same directory.
+
+
+
+
+### Resetting Memory via crew object
+
+```python
+
+my_crew = Crew(
+    agents=[...],
+    tasks=[...],
+    process=Process.sequential,
+    memory=True,
+    verbose=True,
+    embedder={
+        "provider": "custom",
+        "config": {
+            "embedder": CustomEmbedder()
+        }
+    }
+)
+
+my_crew.reset_memories(command_type = 'all') # Resets all the memory
+```
+
+#### Resetting Memory Options
+
+| Command Type       | Description                      |
+| :----------------- | :------------------------------- |
+| `long`             | Reset LONG TERM memory.          | 
+| `short`            | Reset SHORT TERM memory.         | 
+| `entities`         | Reset ENTITIES memory.           | 
+| `kickoff_outputs`  | Reset LATEST KICKOFF TASK OUTPUTS. |
+| `knowledge`        | Reset KNOWLEDGE memory.          |
+| `all`              | Reset ALL memories.              |
+
 
 ## Benefits of Using CrewAI's Memory System
 

docs/how-to/kickoff-async.mdx

@@ -54,7 +54,8 @@ coding_agent = Agent(
 # Create a task that requires code execution
 data_analysis_task = Task(
     description="Analyze the given dataset and calculate the average age of participants. Ages: {ages}",
-    agent=coding_agent
+    agent=coding_agent,
+    expected_output="The average age of the participants."
 )
 
 # Create a crew and add the task
@@ -116,4 +117,4 @@ async def async_multiple_crews():
 
 # Run the async function
 asyncio.run(async_multiple_crews())
-```
+```

docs/how-to/langfuse-observability.mdx

@@ -10,6 +10,8 @@ This notebook demonstrates how to integrate **Langfuse** with **CrewAI** using O
 
 > **What is Langfuse?** [Langfuse](https://langfuse.com) is an open-source LLM engineering platform. It provides tracing and monitoring capabilities for LLM applications, helping developers debug, analyze, and optimize their AI systems. Langfuse integrates with various tools and frameworks via native integrations, OpenTelemetry, and APIs/SDKs.
 
+[![Langfuse Overview Video](https://github.com/user-attachments/assets/3926b288-ff61-4b95-8aa1-45d041c70866)](https://langfuse.com/watch-demo)
+
 ## Get Started
 
 We'll walk through a simple example of using CrewAI and integrating it with Langfuse via OpenTelemetry using OpenLit.

src/crewai/agent.py

@@ -19,25 +19,17 @@ from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.utilities import Converter, Prompts
 from crewai.utilities.constants import TRAINED_AGENTS_DATA_FILE, TRAINING_DATA_FILE
 from crewai.utilities.converter import generate_model_description
+from crewai.utilities.events.agent_events import (
+    AgentExecutionCompletedEvent,
+    AgentExecutionErrorEvent,
+    AgentExecutionStartedEvent,
+)
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 from crewai.utilities.llm_utils import create_llm
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 from crewai.utilities.training_handler import CrewTrainingHandler
 
-agentops = None
 
-try:
-    import agentops  # type: ignore # Name "agentops" is already defined
-    from agentops import track_agent  # type: ignore
-except ImportError:
-
-    def track_agent():
-        def noop(f):
-            return f
-
-        return noop
-
-
-@track_agent()
 class Agent(BaseAgent):
     """Represents an agent in a system.
 
@@ -122,7 +114,6 @@ class Agent(BaseAgent):
 
     @model_validator(mode="after")
     def post_init_setup(self):
-        self._set_knowledge()
         self.agent_ops_agent_name = self.role
 
         self.llm = create_llm(self.llm)
@@ -142,8 +133,11 @@ class Agent(BaseAgent):
             self.cache_handler = CacheHandler()
         self.set_cache_handler(self.cache_handler)
 
-    def _set_knowledge(self):
+    def set_knowledge(self, crew_embedder: Optional[Dict[str, Any]] = None):
         try:
+            if self.embedder is None and crew_embedder:
+                self.embedder = crew_embedder
+
             if self.knowledge_sources:
                 full_pattern = re.compile(r"[^a-zA-Z0-9\-_\r\n]|(\.\.)")
                 knowledge_agent_name = f"{re.sub(full_pattern, '_', self.role)}"
@@ -240,6 +234,15 @@ class Agent(BaseAgent):
             task_prompt = self._use_trained_data(task_prompt=task_prompt)
 
         try:
+            crewai_event_bus.emit(
+                self,
+                event=AgentExecutionStartedEvent(
+                    agent=self,
+                    tools=self.tools,
+                    task_prompt=task_prompt,
+                    task=task,
+                ),
+            )
             result = self.agent_executor.invoke(
                 {
                     "input": task_prompt,
@@ -251,9 +254,25 @@ class Agent(BaseAgent):
         except Exception as e:
             if e.__class__.__module__.startswith("litellm"):
                 # Do not retry on litellm errors
+                crewai_event_bus.emit(
+                    self,
+                    event=AgentExecutionErrorEvent(
+                        agent=self,
+                        task=task,
+                        error=str(e),
+                    ),
+                )
                 raise e
             self._times_executed += 1
             if self._times_executed > self.max_retry_limit:
+                crewai_event_bus.emit(
+                    self,
+                    event=AgentExecutionErrorEvent(
+                        agent=self,
+                        task=task,
+                        error=str(e),
+                    ),
+                )
                 raise e
             result = self.execute_task(task, context, tools)
 
@@ -266,7 +285,10 @@ class Agent(BaseAgent):
         for tool_result in self.tools_results:  # type: ignore # Item "None" of "list[Any] | None" has no attribute "__iter__" (not iterable)
             if tool_result.get("result_as_answer", False):
                 result = tool_result["result"]
-
+        crewai_event_bus.emit(
+            self,
+            event=AgentExecutionCompletedEvent(agent=self, task=task, output=result),
+        )
         return result
 
     def create_agent_executor(

src/crewai/agents/agent_builder/base_agent.py

@@ -20,8 +20,7 @@ from crewai.agents.cache.cache_handler import CacheHandler
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.knowledge.knowledge import Knowledge
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
-from crewai.tools import BaseTool
-from crewai.tools.base_tool import Tool
+from crewai.tools.base_tool import BaseTool, Tool
 from crewai.utilities import I18N, Logger, RPMController
 from crewai.utilities.config import process_config
 from crewai.utilities.converter import Converter
@@ -112,7 +111,7 @@ class BaseAgent(ABC, BaseModel):
         default=False,
         description="Enable agent to delegate and ask questions among each other.",
     )
-    tools: Optional[List[Any]] = Field(
+    tools: Optional[List[BaseTool]] = Field(
         default_factory=list, description="Tools at agents' disposal"
     )
     max_iter: int = Field(
@@ -352,3 +351,6 @@ class BaseAgent(ABC, BaseModel):
         if not self._rpm_controller:
             self._rpm_controller = rpm_controller
             self.create_agent_executor()
+
+    def set_knowledge(self, crew_embedder: Optional[Dict[str, Any]] = None):
+        pass

src/crewai/agents/agent_builder/base_agent_executor_mixin.py

@@ -114,10 +114,15 @@ class CrewAgentExecutorMixin:
             prompt = (
                 "\n\n=====\n"
                 "## HUMAN FEEDBACK: Provide feedback on the Final Result and Agent's actions.\n"
-                "Respond with 'looks good' to accept or provide specific improvement requests.\n"
-                "You can provide multiple rounds of feedback until satisfied.\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")
-        return input()
+        response = input()
+        if response.strip() != "":
+            self._printer.print(content="\nProcessing your feedback...", color="cyan")
+        return response

src/crewai/agents/agent_builder/utilities/base_output_converter.py

@@ -31,11 +31,11 @@ class OutputConverter(BaseModel, ABC):
     )
 
     @abstractmethod
-    def to_pydantic(self, current_attempt=1):
+    def to_pydantic(self, current_attempt=1) -> BaseModel:
         """Convert text to pydantic."""
         pass
 
     @abstractmethod
-    def to_json(self, current_attempt=1):
+    def to_json(self, current_attempt=1) -> dict:
         """Convert text to json."""
         pass

src/crewai/agents/crew_agent_executor.py

@@ -18,6 +18,12 @@ from crewai.tools.base_tool import BaseTool
 from crewai.tools.tool_usage import ToolUsage, ToolUsageErrorException
 from crewai.utilities import I18N, Printer
 from crewai.utilities.constants import MAX_LLM_RETRY, TRAINING_DATA_FILE
+from crewai.utilities.events import (
+    ToolUsageErrorEvent,
+    ToolUsageStartedEvent,
+    crewai_event_bus,
+)
+from crewai.utilities.events.tool_usage_events import ToolUsageStartedEvent
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
@@ -107,11 +113,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             )
             raise
         except Exception as e:
+            self._handle_unknown_error(e)
             if e.__class__.__module__.startswith("litellm"):
                 # Do not retry on litellm errors
                 raise e
             else:
-                self._handle_unknown_error(e)
                 raise e
 
         if self.ask_for_human_input:
@@ -349,40 +355,68 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                 )
 
     def _execute_tool_and_check_finality(self, agent_action: AgentAction) -> ToolResult:
-        tool_usage = ToolUsage(
-            tools_handler=self.tools_handler,
-            tools=self.tools,
-            original_tools=self.original_tools,
-            tools_description=self.tools_description,
-            tools_names=self.tools_names,
-            function_calling_llm=self.function_calling_llm,
-            task=self.task,  # type: ignore[arg-type]
-            agent=self.agent,
-            action=agent_action,
-        )
-        tool_calling = tool_usage.parse_tool_calling(agent_action.text)
-
-        if isinstance(tool_calling, ToolUsageErrorException):
-            tool_result = tool_calling.message
-            return ToolResult(result=tool_result, result_as_answer=False)
-        else:
-            if tool_calling.tool_name.casefold().strip() in [
-                name.casefold().strip() for name in self.tool_name_to_tool_map
-            ] or tool_calling.tool_name.casefold().replace("_", " ") in [
-                name.casefold().strip() for name in self.tool_name_to_tool_map
-            ]:
-                tool_result = tool_usage.use(tool_calling, agent_action.text)
-                tool = self.tool_name_to_tool_map.get(tool_calling.tool_name)
-                if tool:
-                    return ToolResult(
-                        result=tool_result, result_as_answer=tool.result_as_answer
-                    )
-            else:
-                tool_result = self._i18n.errors("wrong_tool_name").format(
-                    tool=tool_calling.tool_name,
-                    tools=", ".join([tool.name.casefold() for tool in self.tools]),
+        try:
+            if self.agent:
+                crewai_event_bus.emit(
+                    self,
+                    event=ToolUsageStartedEvent(
+                        agent_key=self.agent.key,
+                        agent_role=self.agent.role,
+                        tool_name=agent_action.tool,
+                        tool_args=agent_action.tool_input,
+                        tool_class=agent_action.tool,
+                    ),
                 )
-        return ToolResult(result=tool_result, result_as_answer=False)
+            tool_usage = ToolUsage(
+                tools_handler=self.tools_handler,
+                tools=self.tools,
+                original_tools=self.original_tools,
+                tools_description=self.tools_description,
+                tools_names=self.tools_names,
+                function_calling_llm=self.function_calling_llm,
+                task=self.task,  # type: ignore[arg-type]
+                agent=self.agent,
+                action=agent_action,
+            )
+            tool_calling = tool_usage.parse_tool_calling(agent_action.text)
+
+            if isinstance(tool_calling, ToolUsageErrorException):
+                tool_result = tool_calling.message
+                return ToolResult(result=tool_result, result_as_answer=False)
+            else:
+                if tool_calling.tool_name.casefold().strip() in [
+                    name.casefold().strip() for name in self.tool_name_to_tool_map
+                ] or tool_calling.tool_name.casefold().replace("_", " ") in [
+                    name.casefold().strip() for name in self.tool_name_to_tool_map
+                ]:
+                    tool_result = tool_usage.use(tool_calling, agent_action.text)
+                    tool = self.tool_name_to_tool_map.get(tool_calling.tool_name)
+                    if tool:
+                        return ToolResult(
+                            result=tool_result, result_as_answer=tool.result_as_answer
+                        )
+                else:
+                    tool_result = self._i18n.errors("wrong_tool_name").format(
+                        tool=tool_calling.tool_name,
+                        tools=", ".join([tool.name.casefold() for tool in self.tools]),
+                    )
+                return ToolResult(result=tool_result, result_as_answer=False)
+
+        except Exception as e:
+            # TODO: drop
+            if self.agent:
+                crewai_event_bus.emit(
+                    self,
+                    event=ToolUsageErrorEvent(  # validation error
+                        agent_key=self.agent.key,
+                        agent_role=self.agent.role,
+                        tool_name=agent_action.tool,
+                        tool_args=agent_action.tool_input,
+                        tool_class=agent_action.tool,
+                        error=str(e),
+                    ),
+                )
+            raise e
 
     def _summarize_messages(self) -> None:
         messages_groups = []
@@ -514,10 +548,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         self, initial_answer: AgentFinish, feedback: str
     ) -> AgentFinish:
         """Process feedback for training scenarios with single iteration."""
-        self._printer.print(
-            content="\nProcessing training feedback.\n",
-            color="yellow",
-        )
         self._handle_crew_training_output(initial_answer, feedback)
         self.messages.append(
             self._format_msg(
@@ -537,9 +567,8 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         answer = current_answer
 
         while self.ask_for_human_input:
-            response = self._get_llm_feedback_response(feedback)
-
-            if not self._feedback_requires_changes(response):
+            # If the user provides a blank response, assume they are happy with the result
+            if feedback.strip() == "":
                 self.ask_for_human_input = False
             else:
                 answer = self._process_feedback_iteration(feedback)
@@ -547,27 +576,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
 
         return answer
 
-    def _get_llm_feedback_response(self, feedback: str) -> Optional[str]:
-        """Get LLM classification of whether feedback requires changes."""
-        prompt = self._i18n.slice("human_feedback_classification").format(
-            feedback=feedback
-        )
-        message = self._format_msg(prompt, role="system")
-
-        for retry in range(MAX_LLM_RETRY):
-            try:
-                response = self.llm.call([message], callbacks=self.callbacks)
-                return response.strip().lower() if response else None
-            except Exception as error:
-                self._log_feedback_error(retry, error)
-
-        self._log_max_retries_exceeded()
-        return None
-
-    def _feedback_requires_changes(self, response: Optional[str]) -> bool:
-        """Determine if feedback response indicates need for changes."""
-        return response == "true" if response else False
-
     def _process_feedback_iteration(self, feedback: str) -> AgentFinish:
         """Process a single feedback iteration."""
         self.messages.append(

src/crewai/cli/constants.py

@@ -216,10 +216,43 @@ MODELS = {
         "watsonx/ibm/granite-3-8b-instruct",
     ],
     "bedrock": [
+        "bedrock/us.amazon.nova-pro-v1:0",
+        "bedrock/us.amazon.nova-micro-v1:0",
+        "bedrock/us.amazon.nova-lite-v1:0",
+        "bedrock/us.anthropic.claude-3-5-sonnet-20240620-v1:0",
+        "bedrock/us.anthropic.claude-3-5-haiku-20241022-v1:0",
+        "bedrock/us.anthropic.claude-3-5-sonnet-20241022-v2:0",
+        "bedrock/us.anthropic.claude-3-7-sonnet-20250219-v1:0",
+        "bedrock/us.anthropic.claude-3-sonnet-20240229-v1:0",
+        "bedrock/us.anthropic.claude-3-opus-20240229-v1:0",
+        "bedrock/us.anthropic.claude-3-haiku-20240307-v1:0",
+        "bedrock/us.meta.llama3-2-11b-instruct-v1:0",
+        "bedrock/us.meta.llama3-2-3b-instruct-v1:0",
+        "bedrock/us.meta.llama3-2-90b-instruct-v1:0",
+        "bedrock/us.meta.llama3-2-1b-instruct-v1:0",
+        "bedrock/us.meta.llama3-1-8b-instruct-v1:0",
+        "bedrock/us.meta.llama3-1-70b-instruct-v1:0",
+        "bedrock/us.meta.llama3-3-70b-instruct-v1:0",
+        "bedrock/us.meta.llama3-1-405b-instruct-v1:0",
+        "bedrock/eu.anthropic.claude-3-5-sonnet-20240620-v1:0",
+        "bedrock/eu.anthropic.claude-3-sonnet-20240229-v1:0",
+        "bedrock/eu.anthropic.claude-3-haiku-20240307-v1:0",
+        "bedrock/eu.meta.llama3-2-3b-instruct-v1:0",
+        "bedrock/eu.meta.llama3-2-1b-instruct-v1:0",
+        "bedrock/apac.anthropic.claude-3-5-sonnet-20240620-v1:0",
+        "bedrock/apac.anthropic.claude-3-5-sonnet-20241022-v2:0",
+        "bedrock/apac.anthropic.claude-3-sonnet-20240229-v1:0",
+        "bedrock/apac.anthropic.claude-3-haiku-20240307-v1:0",
+        "bedrock/amazon.nova-pro-v1:0",
+        "bedrock/amazon.nova-micro-v1:0",
+        "bedrock/amazon.nova-lite-v1:0",
         "bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0",
+        "bedrock/anthropic.claude-3-5-haiku-20241022-v1:0",
+        "bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0",
+        "bedrock/anthropic.claude-3-7-sonnet-20250219-v1:0",
         "bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
-        "bedrock/anthropic.claude-3-haiku-20240307-v1:0",
         "bedrock/anthropic.claude-3-opus-20240229-v1:0",
+        "bedrock/anthropic.claude-3-haiku-20240307-v1:0",
         "bedrock/anthropic.claude-v2:1",
         "bedrock/anthropic.claude-v2",
         "bedrock/anthropic.claude-instant-v1",
@@ -234,8 +267,6 @@ MODELS = {
         "bedrock/ai21.j2-mid-v1",
         "bedrock/ai21.j2-ultra-v1",
         "bedrock/ai21.jamba-instruct-v1:0",
-        "bedrock/meta.llama2-13b-chat-v1",
-        "bedrock/meta.llama2-70b-chat-v1",
         "bedrock/mistral.mistral-7b-instruct-v0:2",
         "bedrock/mistral.mixtral-8x7b-instruct-v0:1",
     ],

src/crewai/cli/utils.py

@@ -257,11 +257,11 @@ def get_crew(crew_path: str = "crew.py", require: bool = False) -> Crew | None:
         import os
 
         for root, _, files in os.walk("."):
-            if "crew.py" in files:
-                crew_path = os.path.join(root, "crew.py")
+            if crew_path in files:
+                crew_os_path = os.path.join(root, crew_path)
                 try:
                     spec = importlib.util.spec_from_file_location(
-                        "crew_module", crew_path
+                        "crew_module", crew_os_path
                     )
                     if not spec or not spec.loader:
                         continue
@@ -273,9 +273,11 @@ def get_crew(crew_path: str = "crew.py", require: bool = False) -> Crew | None:
                         for attr_name in dir(module):
                             attr = getattr(module, attr_name)
                             try:
-                                if callable(attr) and hasattr(attr, "crew"):
-                                    crew_instance = attr().crew()
-                                    return crew_instance
+                                if isinstance(attr, Crew) and hasattr(attr, "kickoff"):
+                                    print(
+                                        f"Found valid crew object in attribute '{attr_name}' at {crew_os_path}."
+                                    )
+                                    return attr
 
                             except Exception as e:
                                 print(f"Error processing attribute {attr_name}: {e}")

src/crewai/crew.py

@@ -35,7 +35,6 @@ from crewai.process import Process
 from crewai.task import Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.task_output import TaskOutput
-from crewai.telemetry import Telemetry
 from crewai.tools.agent_tools.agent_tools import AgentTools
 from crewai.tools.base_tool import Tool
 from crewai.types.usage_metrics import UsageMetrics
@@ -43,6 +42,18 @@ from crewai.utilities import I18N, FileHandler, Logger, RPMController
 from crewai.utilities.constants import TRAINING_DATA_FILE
 from crewai.utilities.evaluators.crew_evaluator_handler import CrewEvaluator
 from crewai.utilities.evaluators.task_evaluator import TaskEvaluator
+from crewai.utilities.events.crew_events import (
+    CrewKickoffCompletedEvent,
+    CrewKickoffFailedEvent,
+    CrewKickoffStartedEvent,
+    CrewTestCompletedEvent,
+    CrewTestFailedEvent,
+    CrewTestStartedEvent,
+    CrewTrainCompletedEvent,
+    CrewTrainFailedEvent,
+    CrewTrainStartedEvent,
+)
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 from crewai.utilities.formatter import (
     aggregate_raw_outputs_from_task_outputs,
     aggregate_raw_outputs_from_tasks,
@@ -52,12 +63,6 @@ from crewai.utilities.planning_handler import CrewPlanner
 from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
 from crewai.utilities.training_handler import CrewTrainingHandler
 
-try:
-    import agentops  # type: ignore
-except ImportError:
-    agentops = None
-
-
 warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
 
 
@@ -251,8 +256,6 @@ class Crew(BaseModel):
         if self.function_calling_llm and not isinstance(self.function_calling_llm, LLM):
             self.function_calling_llm = create_llm(self.function_calling_llm)
 
-        self._telemetry = Telemetry()
-        self._telemetry.set_tracer()
         return self
 
     @model_validator(mode="after")
@@ -521,10 +524,19 @@ class Crew(BaseModel):
         self, n_iterations: int, filename: str, inputs: Optional[Dict[str, Any]] = {}
     ) -> None:
         """Trains the crew for a given number of iterations."""
-        train_crew = self.copy()
-        train_crew._setup_for_training(filename)
-
         try:
+            crewai_event_bus.emit(
+                self,
+                CrewTrainStartedEvent(
+                    crew_name=self.name or "crew",
+                    n_iterations=n_iterations,
+                    filename=filename,
+                    inputs=inputs,
+                ),
+            )
+            train_crew = self.copy()
+            train_crew._setup_for_training(filename)
+
             for n_iteration in range(n_iterations):
                 train_crew._train_iteration = n_iteration
                 train_crew.kickoff(inputs=inputs)
@@ -539,7 +551,20 @@ class Crew(BaseModel):
                     CrewTrainingHandler(filename).save_trained_data(
                         agent_id=str(agent.role), trained_data=result.model_dump()
                     )
+
+            crewai_event_bus.emit(
+                self,
+                CrewTrainCompletedEvent(
+                    crew_name=self.name or "crew",
+                    n_iterations=n_iterations,
+                    filename=filename,
+                ),
+            )
         except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                CrewTrainFailedEvent(error=str(e), crew_name=self.name or "crew"),
+            )
             self._logger.log("error", f"Training failed: {e}", color="red")
             CrewTrainingHandler(TRAINING_DATA_FILE).clear()
             CrewTrainingHandler(filename).clear()
@@ -549,60 +574,71 @@ class Crew(BaseModel):
         self,
         inputs: Optional[Dict[str, Any]] = None,
     ) -> CrewOutput:
-        for before_callback in self.before_kickoff_callbacks:
-            if inputs is None:
-                inputs = {}
-            inputs = before_callback(inputs)
+        try:
+            for before_callback in self.before_kickoff_callbacks:
+                if inputs is None:
+                    inputs = {}
+                inputs = before_callback(inputs)
 
-        """Starts the crew to work on its assigned tasks."""
-        self._execution_span = self._telemetry.crew_execution_span(self, inputs)
-        self._task_output_handler.reset()
-        self._logging_color = "bold_purple"
-
-        if inputs is not None:
-            self._inputs = inputs
-            self._interpolate_inputs(inputs)
-        self._set_tasks_callbacks()
-
-        i18n = I18N(prompt_file=self.prompt_file)
-
-        for agent in self.agents:
-            agent.i18n = i18n
-            # type: ignore[attr-defined] # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
-            agent.crew = self  # type: ignore[attr-defined]
-            # TODO: Create an AgentFunctionCalling protocol for future refactoring
-            if not agent.function_calling_llm:  # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
-                agent.function_calling_llm = self.function_calling_llm  # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
-
-            if not agent.step_callback:  # type: ignore # "BaseAgent" has no attribute "step_callback"
-                agent.step_callback = self.step_callback  # type: ignore # "BaseAgent" has no attribute "step_callback"
-
-            agent.create_agent_executor()
-
-        if self.planning:
-            self._handle_crew_planning()
-
-        metrics: List[UsageMetrics] = []
-
-        if self.process == Process.sequential:
-            result = self._run_sequential_process()
-        elif self.process == Process.hierarchical:
-            result = self._run_hierarchical_process()
-        else:
-            raise NotImplementedError(
-                f"The process '{self.process}' is not implemented yet."
+            crewai_event_bus.emit(
+                self,
+                CrewKickoffStartedEvent(crew_name=self.name or "crew", inputs=inputs),
             )
 
-        for after_callback in self.after_kickoff_callbacks:
-            result = after_callback(result)
+            # Starts the crew to work on its assigned tasks.
+            self._task_output_handler.reset()
+            self._logging_color = "bold_purple"
 
-        metrics += [agent._token_process.get_summary() for agent in self.agents]
+            if inputs is not None:
+                self._inputs = inputs
+                self._interpolate_inputs(inputs)
+            self._set_tasks_callbacks()
 
-        self.usage_metrics = UsageMetrics()
-        for metric in metrics:
-            self.usage_metrics.add_usage_metrics(metric)
+            i18n = I18N(prompt_file=self.prompt_file)
 
-        return result
+            for agent in self.agents:
+                agent.i18n = i18n
+                # type: ignore[attr-defined] # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
+                agent.crew = self  # type: ignore[attr-defined]
+                agent.set_knowledge(crew_embedder=self.embedder)
+                # TODO: Create an AgentFunctionCalling protocol for future refactoring
+                if not agent.function_calling_llm:  # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
+                    agent.function_calling_llm = self.function_calling_llm  # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
+
+                if not agent.step_callback:  # type: ignore # "BaseAgent" has no attribute "step_callback"
+                    agent.step_callback = self.step_callback  # type: ignore # "BaseAgent" has no attribute "step_callback"
+
+                agent.create_agent_executor()
+
+            if self.planning:
+                self._handle_crew_planning()
+
+            metrics: List[UsageMetrics] = []
+
+            if self.process == Process.sequential:
+                result = self._run_sequential_process()
+            elif self.process == Process.hierarchical:
+                result = self._run_hierarchical_process()
+            else:
+                raise NotImplementedError(
+                    f"The process '{self.process}' is not implemented yet."
+                )
+
+            for after_callback in self.after_kickoff_callbacks:
+                result = after_callback(result)
+
+            metrics += [agent._token_process.get_summary() for agent in self.agents]
+
+            self.usage_metrics = UsageMetrics()
+            for metric in metrics:
+                self.usage_metrics.add_usage_metrics(metric)
+            return result
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                CrewKickoffFailedEvent(error=str(e), crew_name=self.name or "crew"),
+            )
+            raise
 
     def kickoff_for_each(self, inputs: List[Dict[str, Any]]) -> List[CrewOutput]:
         """Executes the Crew's workflow for each input in the list and aggregates results."""
@@ -950,7 +986,12 @@ class Crew(BaseModel):
         final_string_output = final_task_output.raw
         self._finish_execution(final_string_output)
         token_usage = self.calculate_usage_metrics()
-
+        crewai_event_bus.emit(
+            self,
+            CrewKickoffCompletedEvent(
+                crew_name=self.name or "crew", output=final_task_output
+            ),
+        )
         return CrewOutput(
             raw=final_task_output.raw,
             pydantic=final_task_output.pydantic,
@@ -1070,7 +1111,6 @@ class Crew(BaseModel):
             "_short_term_memory",
             "_long_term_memory",
             "_entity_memory",
-            "_telemetry",
             "agents",
             "tasks",
             "knowledge_sources",
@@ -1136,13 +1176,6 @@ class Crew(BaseModel):
     def _finish_execution(self, final_string_output: str) -> None:
         if self.max_rpm:
             self._rpm_controller.stop_rpm_counter()
-        if agentops:
-            agentops.end_session(
-                end_state="Success",
-                end_state_reason="Finished Execution",
-                is_auto_end=True,
-            )
-        self._telemetry.end_crew(self, final_string_output)
 
     def calculate_usage_metrics(self) -> UsageMetrics:
         """Calculates and returns the usage metrics."""
@@ -1164,26 +1197,41 @@ class Crew(BaseModel):
         inputs: Optional[Dict[str, Any]] = None,
     ) -> None:
         """Test and evaluate the Crew with the given inputs for n iterations concurrently using concurrent.futures."""
-        test_crew = self.copy()
+        try:
+            eval_llm = create_llm(eval_llm)
+            if not eval_llm:
+                raise ValueError("Failed to create LLM instance.")
 
-        eval_llm = create_llm(eval_llm)
+            crewai_event_bus.emit(
+                self,
+                CrewTestStartedEvent(
+                    crew_name=self.name or "crew",
+                    n_iterations=n_iterations,
+                    eval_llm=eval_llm,
+                    inputs=inputs,
+                ),
+            )
+            test_crew = self.copy()
+            evaluator = CrewEvaluator(test_crew, eval_llm)  # type: ignore[arg-type]
 
-        if not eval_llm:
-            raise ValueError("Failed to create LLM instance.")
+            for i in range(1, n_iterations + 1):
+                evaluator.set_iteration(i)
+                test_crew.kickoff(inputs=inputs)
 
-        self._test_execution_span = test_crew._telemetry.test_execution_span(
-            test_crew,
-            n_iterations,
-            inputs,
-            eval_llm.model,  # type: ignore[arg-type]
-        )  # type: ignore[arg-type]
-        evaluator = CrewEvaluator(test_crew, eval_llm)  # type: ignore[arg-type]
+            evaluator.print_crew_evaluation_result()
 
-        for i in range(1, n_iterations + 1):
-            evaluator.set_iteration(i)
-            test_crew.kickoff(inputs=inputs)
-
-        evaluator.print_crew_evaluation_result()
+            crewai_event_bus.emit(
+                self,
+                CrewTestCompletedEvent(
+                    crew_name=self.name or "crew",
+                ),
+            )
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                CrewTestFailedEvent(error=str(e), crew_name=self.name or "crew"),
+            )
+            raise
 
     def __repr__(self):
         return f"Crew(id={self.id}, process={self.process}, number_of_agents={len(self.agents)}, number_of_tasks={len(self.tasks)})"
@@ -1225,11 +1273,11 @@ class Crew(BaseModel):
     def _reset_all_memories(self) -> None:
         """Reset all available memory systems."""
         memory_systems = [
-            ("short term", self._short_term_memory),
-            ("entity", self._entity_memory),
-            ("long term", self._long_term_memory),
-            ("task output", self._task_output_handler),
-            ("knowledge", self.knowledge),
+            ("short term", getattr(self, "_short_term_memory", None)),
+            ("entity", getattr(self, "_entity_memory", None)),
+            ("long term", getattr(self, "_long_term_memory", None)),
+            ("task output", getattr(self, "_task_output_handler", None)),
+            ("knowledge", getattr(self, "knowledge", None)),
         ]
 
         for name, system in memory_systems:

src/crewai/flow/flow.py

@@ -17,19 +17,21 @@ from typing import (
 )
 from uuid import uuid4
 
-from blinker import Signal
 from pydantic import BaseModel, Field, ValidationError
 
-from crewai.flow.flow_events import (
-    FlowFinishedEvent,
-    FlowStartedEvent,
-    MethodExecutionFinishedEvent,
-    MethodExecutionStartedEvent,
-)
 from crewai.flow.flow_visualizer import plot_flow
 from crewai.flow.persistence.base import FlowPersistence
 from crewai.flow.utils import get_possible_return_constants
-from crewai.telemetry import Telemetry
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+from crewai.utilities.events.flow_events import (
+    FlowCreatedEvent,
+    FlowFinishedEvent,
+    FlowPlotEvent,
+    FlowStartedEvent,
+    MethodExecutionFailedEvent,
+    MethodExecutionFinishedEvent,
+    MethodExecutionStartedEvent,
+)
 from crewai.utilities.printer import Printer
 
 logger = logging.getLogger(__name__)
@@ -427,7 +429,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
 
     Type parameter T must be either Dict[str, Any] or a subclass of BaseModel."""
 
-    _telemetry = Telemetry()
     _printer = Printer()
 
     _start_methods: List[str] = []
@@ -435,7 +436,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
     _routers: Set[str] = set()
     _router_paths: Dict[str, List[str]] = {}
     initial_state: Union[Type[T], T, None] = None
-    event_emitter = Signal("event_emitter")
 
     def __class_getitem__(cls: Type["Flow"], item: Type[T]) -> Type["Flow"]:
         class _FlowGeneric(cls):  # type: ignore
@@ -469,7 +469,13 @@ class Flow(Generic[T], metaclass=FlowMeta):
         if kwargs:
             self._initialize_state(kwargs)
 
-        self._telemetry.flow_creation_span(self.__class__.__name__)
+        crewai_event_bus.emit(
+            self,
+            FlowCreatedEvent(
+                type="flow_created",
+                flow_name=self.__class__.__name__,
+            ),
+        )
 
         # Register all flow-related methods
         for method_name in dir(self):
@@ -703,16 +709,34 @@ class Flow(Generic[T], metaclass=FlowMeta):
             raise TypeError(f"State must be dict or BaseModel, got {type(self._state)}")
 
     def kickoff(self, inputs: Optional[Dict[str, Any]] = None) -> Any:
-        """Start the flow execution.
+        """
+        Start the flow execution in a synchronous context.
+
+        This method wraps kickoff_async so that all state initialization and event
+        emission is handled in the asynchronous method.
+        """
+
+        async def run_flow():
+            return await self.kickoff_async(inputs)
+
+        return asyncio.run(run_flow())
+
+    async def kickoff_async(self, inputs: Optional[Dict[str, Any]] = None) -> Any:
+        """
+        Start the flow execution asynchronously.
+
+        This method performs state restoration (if an 'id' is provided and persistence is available)
+        and updates the flow state with any additional inputs. It then emits the FlowStartedEvent,
+        logs the flow startup, and executes all start methods. Once completed, it emits the
+        FlowFinishedEvent and returns the final output.
 
         Args:
-            inputs: Optional dictionary containing input values and potentially a state ID to restore
-        """
-        # Handle state restoration if ID is provided in inputs
-        if inputs and "id" in inputs and self._persistence is not None:
-            restore_uuid = inputs["id"]
-            stored_state = self._persistence.load_state(restore_uuid)
+            inputs: Optional dictionary containing input values and/or a state ID for restoration.
 
+        Returns:
+            The final output from the flow, which is the result of the last executed method.
+        """
+        if inputs:
             # Override the id in the state if it exists in inputs
             if "id" in inputs:
                 if isinstance(self._state, dict):
@@ -720,27 +744,30 @@ class Flow(Generic[T], metaclass=FlowMeta):
                 elif isinstance(self._state, BaseModel):
                     setattr(self._state, "id", inputs["id"])
 
-            if stored_state:
-                self._log_flow_event(
-                    f"Loading flow state from memory for UUID: {restore_uuid}",
-                    color="yellow",
-                )
-                # Restore the state
-                self._restore_state(stored_state)
-            else:
-                self._log_flow_event(
-                    f"No flow state found for UUID: {restore_uuid}", color="red"
-                )
+            # If persistence is enabled, attempt to restore the stored state using the provided id.
+            if "id" in inputs and self._persistence is not None:
+                restore_uuid = inputs["id"]
+                stored_state = self._persistence.load_state(restore_uuid)
+                if stored_state:
+                    self._log_flow_event(
+                        f"Loading flow state from memory for UUID: {restore_uuid}",
+                        color="yellow",
+                    )
+                    self._restore_state(stored_state)
+                else:
+                    self._log_flow_event(
+                        f"No flow state found for UUID: {restore_uuid}", color="red"
+                    )
 
-            # Apply any additional inputs after restoration
+            # Update state with any additional inputs (ignoring the 'id' key)
             filtered_inputs = {k: v for k, v in inputs.items() if k != "id"}
             if filtered_inputs:
                 self._initialize_state(filtered_inputs)
 
-        # Start flow execution
-        self.event_emitter.send(
+        # Emit FlowStartedEvent and log the start of the flow.
+        crewai_event_bus.emit(
             self,
-            event=FlowStartedEvent(
+            FlowStartedEvent(
                 type="flow_started",
                 flow_name=self.__class__.__name__,
                 inputs=inputs,
@@ -753,16 +780,6 @@ class Flow(Generic[T], metaclass=FlowMeta):
         if inputs is not None and "id" not in inputs:
             self._initialize_state(inputs)
 
-        return asyncio.run(self.kickoff_async())
-
-    async def kickoff_async(self, inputs: Optional[Dict[str, Any]] = None) -> Any:
-        if not self._start_methods:
-            raise ValueError("No start method defined")
-
-        self._telemetry.flow_execution_span(
-            self.__class__.__name__, list(self._methods.keys())
-        )
-
         tasks = [
             self._execute_start_method(start_method)
             for start_method in self._start_methods
@@ -771,14 +788,15 @@ class Flow(Generic[T], metaclass=FlowMeta):
 
         final_output = self._method_outputs[-1] if self._method_outputs else None
 
-        self.event_emitter.send(
+        crewai_event_bus.emit(
             self,
-            event=FlowFinishedEvent(
+            FlowFinishedEvent(
                 type="flow_finished",
                 flow_name=self.__class__.__name__,
                 result=final_output,
             ),
         )
+
         return final_output
 
     async def _execute_start_method(self, start_method_name: str) -> None:
@@ -807,40 +825,55 @@ class Flow(Generic[T], metaclass=FlowMeta):
     async def _execute_method(
         self, method_name: str, method: Callable, *args: Any, **kwargs: Any
     ) -> Any:
-        dumped_params = {f"_{i}": arg for i, arg in enumerate(args)} | (kwargs or {})
-        self.event_emitter.send(
-            self,
-            event=MethodExecutionStartedEvent(
-                type="method_execution_started",
-                method_name=method_name,
-                flow_name=self.__class__.__name__,
-                params=dumped_params,
-                state=self._copy_state(),
-            ),
-        )
+        try:
+            dumped_params = {f"_{i}": arg for i, arg in enumerate(args)} | (
+                kwargs or {}
+            )
+            crewai_event_bus.emit(
+                self,
+                MethodExecutionStartedEvent(
+                    type="method_execution_started",
+                    method_name=method_name,
+                    flow_name=self.__class__.__name__,
+                    params=dumped_params,
+                    state=self._copy_state(),
+                ),
+            )
 
-        result = (
-            await method(*args, **kwargs)
-            if asyncio.iscoroutinefunction(method)
-            else method(*args, **kwargs)
-        )
-        self._method_outputs.append(result)
-        self._method_execution_counts[method_name] = (
-            self._method_execution_counts.get(method_name, 0) + 1
-        )
+            result = (
+                await method(*args, **kwargs)
+                if asyncio.iscoroutinefunction(method)
+                else method(*args, **kwargs)
+            )
 
-        self.event_emitter.send(
-            self,
-            event=MethodExecutionFinishedEvent(
-                type="method_execution_finished",
-                method_name=method_name,
-                flow_name=self.__class__.__name__,
-                state=self._copy_state(),
-                result=result,
-            ),
-        )
+            self._method_outputs.append(result)
+            self._method_execution_counts[method_name] = (
+                self._method_execution_counts.get(method_name, 0) + 1
+            )
 
-        return result
+            crewai_event_bus.emit(
+                self,
+                MethodExecutionFinishedEvent(
+                    type="method_execution_finished",
+                    method_name=method_name,
+                    flow_name=self.__class__.__name__,
+                    state=self._copy_state(),
+                    result=result,
+                ),
+            )
+
+            return result
+        except Exception as e:
+            crewai_event_bus.emit(
+                self,
+                MethodExecutionFailedEvent(
+                    type="method_execution_failed",
+                    method_name=method_name,
+                    flow_name=self.__class__.__name__,
+                    error=e,
+                ),
+            )
+            raise e
 
     async def _execute_listeners(self, trigger_method: str, result: Any) -> None:
         """
@@ -978,6 +1011,7 @@ class Flow(Generic[T], metaclass=FlowMeta):
         """
         try:
             method = self._methods[listener_name]
+
             sig = inspect.signature(method)
             params = list(sig.parameters.values())
             method_params = [p for p in params if p.name != "self"]
@@ -1027,7 +1061,11 @@ class Flow(Generic[T], metaclass=FlowMeta):
             logger.warning(message)
 
     def plot(self, filename: str = "crewai_flow") -> None:
-        self._telemetry.flow_plotting_span(
-            self.__class__.__name__, list(self._methods.keys())
+        crewai_event_bus.emit(
+            self,
+            FlowPlotEvent(
+                type="flow_plot",
+                flow_name=self.__class__.__name__,
+            ),
         )
         plot_flow(self, filename)

src/crewai/flow/flow_events.py

@@ -1,39 +0,0 @@
-from dataclasses import dataclass, field
-from datetime import datetime
-from typing import Any, Dict, Optional, Union
-
-from pydantic import BaseModel
-
-
-@dataclass
-class Event:
-    type: str
-    flow_name: str
-    timestamp: datetime = field(init=False)
-
-    def __post_init__(self):
-        self.timestamp = datetime.now()
-
-
-@dataclass
-class FlowStartedEvent(Event):
-    inputs: Optional[Dict[str, Any]] = None
-
-
-@dataclass
-class MethodExecutionStartedEvent(Event):
-    method_name: str
-    state: Union[Dict[str, Any], BaseModel]
-    params: Optional[Dict[str, Any]] = None
-
-
-@dataclass
-class MethodExecutionFinishedEvent(Event):
-    method_name: str
-    state: Union[Dict[str, Any], BaseModel]
-    result: Any = None
-
-
-@dataclass
-class FlowFinishedEvent(Event):
-    result: Optional[Any] = None

src/crewai/flow/persistence/decorators.py

@@ -58,7 +58,7 @@ class PersistenceDecorator:
     _printer = Printer()  # Class-level printer instance
 
     @classmethod
-    def persist_state(cls, flow_instance: Any, method_name: str, persistence_instance: FlowPersistence) -> None:
+    def persist_state(cls, flow_instance: Any, method_name: str, persistence_instance: FlowPersistence, verbose: bool = False) -> None:
         """Persist flow state with proper error handling and logging.
 
         This method handles the persistence of flow state data, including proper
@@ -68,6 +68,7 @@ class PersistenceDecorator:
             flow_instance: The flow instance whose state to persist
             method_name: Name of the method that triggered persistence
             persistence_instance: The persistence backend to use
+            verbose: Whether to log persistence operations
 
         Raises:
             ValueError: If flow has no state or state lacks an ID
@@ -88,9 +89,10 @@ class PersistenceDecorator:
             if not flow_uuid:
                 raise ValueError("Flow state must have an 'id' field for persistence")
 
-            # Log state saving with consistent message
-            cls._printer.print(LOG_MESSAGES["save_state"].format(flow_uuid), color="cyan")
-            logger.info(LOG_MESSAGES["save_state"].format(flow_uuid))
+            # Log state saving only if verbose is True
+            if verbose:
+                cls._printer.print(LOG_MESSAGES["save_state"].format(flow_uuid), color="cyan")
+                logger.info(LOG_MESSAGES["save_state"].format(flow_uuid))
 
             try:
                 persistence_instance.save_state(
@@ -115,7 +117,7 @@ class PersistenceDecorator:
             raise ValueError(error_msg) from e
 
 
-def persist(persistence: Optional[FlowPersistence] = None):
+def persist(persistence: Optional[FlowPersistence] = None, verbose: bool = False):
     """Decorator to persist flow state.
 
     This decorator can be applied at either the class level or method level.
@@ -126,6 +128,7 @@ def persist(persistence: Optional[FlowPersistence] = None):
     Args:
         persistence: Optional FlowPersistence implementation to use.
                     If not provided, uses SQLiteFlowPersistence.
+        verbose: Whether to log persistence operations. Defaults to False.
 
     Returns:
         A decorator that can be applied to either a class or method
@@ -135,13 +138,12 @@ def persist(persistence: Optional[FlowPersistence] = None):
         RuntimeError: If state persistence fails
 
     Example:
-        @persist  # Class-level persistence with default SQLite
+        @persist(verbose=True)  # Class-level persistence with logging
         class MyFlow(Flow[MyState]):
             @start()
             def begin(self):
                 pass
     """
-
     def decorator(target: Union[Type, Callable[..., T]]) -> Union[Type, Callable[..., T]]:
         """Decorator that handles both class and method decoration."""
         actual_persistence = persistence or SQLiteFlowPersistence()
@@ -179,7 +181,7 @@ def persist(persistence: Optional[FlowPersistence] = None):
                         @functools.wraps(original_method)
                         async def method_wrapper(self: Any, *args: Any, **kwargs: Any) -> Any:
                             result = await original_method(self, *args, **kwargs)
-                            PersistenceDecorator.persist_state(self, method_name, actual_persistence)
+                            PersistenceDecorator.persist_state(self, method_name, actual_persistence, verbose)
                             return result
                         return method_wrapper
 
@@ -199,7 +201,7 @@ def persist(persistence: Optional[FlowPersistence] = None):
                         @functools.wraps(original_method)
                         def method_wrapper(self: Any, *args: Any, **kwargs: Any) -> Any:
                             result = original_method(self, *args, **kwargs)
-                            PersistenceDecorator.persist_state(self, method_name, actual_persistence)
+                            PersistenceDecorator.persist_state(self, method_name, actual_persistence, verbose)
                             return result
                         return method_wrapper
 
@@ -228,7 +230,7 @@ def persist(persistence: Optional[FlowPersistence] = None):
                         result = await method_coro
                     else:
                         result = method_coro
-                    PersistenceDecorator.persist_state(flow_instance, method.__name__, actual_persistence)
+                    PersistenceDecorator.persist_state(flow_instance, method.__name__, actual_persistence, verbose)
                     return result
 
                 for attr in ["__is_start_method__", "__trigger_methods__", "__condition_type__", "__is_router__"]:
@@ -240,7 +242,7 @@ def persist(persistence: Optional[FlowPersistence] = None):
                 @functools.wraps(method)
                 def method_sync_wrapper(flow_instance: Any, *args: Any, **kwargs: Any) -> T:
                     result = method(flow_instance, *args, **kwargs)
-                    PersistenceDecorator.persist_state(flow_instance, method.__name__, actual_persistence)
+                    PersistenceDecorator.persist_state(flow_instance, method.__name__, actual_persistence, verbose)
                     return result
 
                 for attr in ["__is_start_method__", "__trigger_methods__", "__condition_type__", "__is_router__"]:

src/crewai/flow/persistence/sqlite.py

@@ -4,7 +4,7 @@ SQLite-based implementation of flow state persistence.
 
 import json
 import sqlite3
-from datetime import datetime
+from datetime import datetime, timezone
 from pathlib import Path
 from typing import Any, Dict, Optional, Union
 
@@ -34,6 +34,7 @@ class SQLiteFlowPersistence(FlowPersistence):
             ValueError: If db_path is invalid
         """
         from crewai.utilities.paths import db_storage_path
+
         # Get path from argument or default location
         path = db_path or str(Path(db_storage_path()) / "flow_states.db")
 
@@ -46,7 +47,8 @@ class SQLiteFlowPersistence(FlowPersistence):
     def init_db(self) -> None:
         """Create the necessary tables if they don't exist."""
         with sqlite3.connect(self.db_path) as conn:
-            conn.execute("""
+            conn.execute(
+                """
             CREATE TABLE IF NOT EXISTS flow_states (
                 id INTEGER PRIMARY KEY AUTOINCREMENT,
                 flow_uuid TEXT NOT NULL,
@@ -54,12 +56,15 @@ class SQLiteFlowPersistence(FlowPersistence):
                 timestamp DATETIME NOT NULL,
                 state_json TEXT NOT NULL
             )
-            """)
+            """
+            )
             # Add index for faster UUID lookups
-            conn.execute("""
+            conn.execute(
+                """
             CREATE INDEX IF NOT EXISTS idx_flow_states_uuid
             ON flow_states(flow_uuid)
-            """)
+            """
+            )
 
     def save_state(
         self,
@@ -85,19 +90,22 @@ class SQLiteFlowPersistence(FlowPersistence):
             )
 
         with sqlite3.connect(self.db_path) as conn:
-            conn.execute("""
+            conn.execute(
+                """
             INSERT INTO flow_states (
                 flow_uuid,
                 method_name,
                 timestamp,
                 state_json
             ) VALUES (?, ?, ?, ?)
-            """, (
-                flow_uuid,
-                method_name,
-                datetime.utcnow().isoformat(),
-                json.dumps(state_dict),
-            ))
+            """,
+                (
+                    flow_uuid,
+                    method_name,
+                    datetime.now(timezone.utc).isoformat(),
+                    json.dumps(state_dict),
+                ),
+            )
 
     def load_state(self, flow_uuid: str) -> Optional[Dict[str, Any]]:
         """Load the most recent state for a given flow UUID.
@@ -109,13 +117,16 @@ class SQLiteFlowPersistence(FlowPersistence):
             The most recent state as a dictionary, or None if no state exists
         """
         with sqlite3.connect(self.db_path) as conn:
-            cursor = conn.execute("""
+            cursor = conn.execute(
+                """
             SELECT state_json
             FROM flow_states
             WHERE flow_uuid = ?
             ORDER BY id DESC
             LIMIT 1
-            """, (flow_uuid,))
+            """,
+                (flow_uuid,),
+            )
             row = cursor.fetchone()
 
         if row:

src/crewai/flow/state_utils.py

@@ -1,12 +1,18 @@
+import json
 from datetime import date, datetime
-from typing import Any
+from typing import Any, Dict, List, Union
 
 from pydantic import BaseModel
 
 from crewai.flow import Flow
 
+SerializablePrimitive = Union[str, int, float, bool, None]
+Serializable = Union[
+    SerializablePrimitive, List["Serializable"], Dict[str, "Serializable"]
+]
 
-def export_state(flow: Flow) -> dict[str, Any]:
+
+def export_state(flow: Flow) -> dict[str, Serializable]:
     """Exports the Flow's internal state as JSON-compatible data structures.
 
     Performs a one-way transformation of a Flow's state into basic Python types
@@ -20,10 +26,27 @@ def export_state(flow: Flow) -> dict[str, Any]:
         dict[str, Any]: The transformed state using JSON-compatible Python
             types.
     """
-    return _to_serializable(flow._state)
+    result = to_serializable(flow._state)
+    assert isinstance(result, dict)
+    return result
 
 
-def _to_serializable(obj: Any, max_depth: int = 5, _current_depth: int = 0) -> Any:
+def to_serializable(
+    obj: Any, max_depth: int = 5, _current_depth: int = 0
+) -> Serializable:
+    """Converts a Python object into a JSON-compatible representation.
+
+    Supports primitives, datetime objects, collections, dictionaries, and
+    Pydantic models. Recursion depth is limited to prevent infinite nesting.
+    Non-convertible objects default to their string representations.
+
+    Args:
+        obj (Any): Object to transform.
+        max_depth (int, optional): Maximum recursion depth. Defaults to 5.
+
+    Returns:
+        Serializable: A JSON-compatible structure.
+    """
     if _current_depth >= max_depth:
         return repr(obj)
 
@@ -32,16 +55,16 @@ def _to_serializable(obj: Any, max_depth: int = 5, _current_depth: int = 0) -> A
     elif isinstance(obj, (date, datetime)):
         return obj.isoformat()
     elif isinstance(obj, (list, tuple, set)):
-        return [_to_serializable(item, max_depth, _current_depth + 1) for item in obj]
+        return [to_serializable(item, max_depth, _current_depth + 1) for item in obj]
     elif isinstance(obj, dict):
         return {
-            _to_serializable_key(key): _to_serializable(
+            _to_serializable_key(key): to_serializable(
                 value, max_depth, _current_depth + 1
             )
             for key, value in obj.items()
         }
     elif isinstance(obj, BaseModel):
-        return _to_serializable(obj.model_dump(), max_depth, _current_depth + 1)
+        return to_serializable(obj.model_dump(), max_depth, _current_depth + 1)
     else:
         return repr(obj)
 
@@ -50,3 +73,19 @@ def _to_serializable_key(key: Any) -> str:
     if isinstance(key, (str, int)):
         return str(key)
     return f"key_{id(key)}_{repr(key)}"
+
+
+def to_string(obj: Any) -> str | None:
+    """Serializes an object into a JSON string.
+
+    Args:
+        obj (Any): Object to serialize.
+
+    Returns:
+        str | None: A JSON-formatted string or `None` if empty.
+    """
+    serializable = to_serializable(obj)
+    if serializable is None:
+        return None
+    else:
+        return json.dumps(serializable)

src/crewai/flow/utils.py

@@ -16,7 +16,8 @@ Example
 import ast
 import inspect
 import textwrap
-from typing import Any, Dict, List, Optional, Set, Union
+from collections import defaultdict, deque
+from typing import Any, Deque, Dict, List, Optional, Set, Union
 
 
 def get_possible_return_constants(function: Any) -> Optional[List[str]]:
@@ -118,7 +119,7 @@ def calculate_node_levels(flow: Any) -> Dict[str, int]:
     - Processes router paths separately
     """
     levels: Dict[str, int] = {}
-    queue: List[str] = []
+    queue: Deque[str] = deque()
     visited: Set[str] = set()
     pending_and_listeners: Dict[str, Set[str]] = {}
 
@@ -128,28 +129,35 @@ def calculate_node_levels(flow: Any) -> Dict[str, int]:
             levels[method_name] = 0
             queue.append(method_name)
 
+    # Precompute listener dependencies
+    or_listeners = defaultdict(list)
+    and_listeners = defaultdict(set)
+    for listener_name, (condition_type, trigger_methods) in flow._listeners.items():
+        if condition_type == "OR":
+            for method in trigger_methods:
+                or_listeners[method].append(listener_name)
+        elif condition_type == "AND":
+            and_listeners[listener_name] = set(trigger_methods)
+
     # Breadth-first traversal to assign levels
     while queue:
-        current = queue.pop(0)
+        current = queue.popleft()
         current_level = levels[current]
         visited.add(current)
 
-        for listener_name, (condition_type, trigger_methods) in flow._listeners.items():
-            if condition_type == "OR":
-                if current in trigger_methods:
-                    if (
-                        listener_name not in levels
-                        or levels[listener_name] > current_level + 1
-                    ):
-                        levels[listener_name] = current_level + 1
-                        if listener_name not in visited:
-                            queue.append(listener_name)
-            elif condition_type == "AND":
+        for listener_name in or_listeners[current]:
+            if listener_name not in levels or levels[listener_name] > current_level + 1:
+                levels[listener_name] = current_level + 1
+                if listener_name not in visited:
+                    queue.append(listener_name)
+
+        for listener_name, required_methods in and_listeners.items():
+            if current in required_methods:
                 if listener_name not in pending_and_listeners:
                     pending_and_listeners[listener_name] = set()
-                if current in trigger_methods:
-                    pending_and_listeners[listener_name].add(current)
-                if set(trigger_methods) == pending_and_listeners[listener_name]:
+                pending_and_listeners[listener_name].add(current)
+
+                if required_methods == pending_and_listeners[listener_name]:
                     if (
                         listener_name not in levels
                         or levels[listener_name] > current_level + 1
@@ -159,22 +167,7 @@ def calculate_node_levels(flow: Any) -> Dict[str, int]:
                             queue.append(listener_name)
 
         # Handle router connections
-        if current in flow._routers:
-            router_method_name = current
-            paths = flow._router_paths.get(router_method_name, [])
-            for path in paths:
-                for listener_name, (
-                    condition_type,
-                    trigger_methods,
-                ) in flow._listeners.items():
-                    if path in trigger_methods:
-                        if (
-                            listener_name not in levels
-                            or levels[listener_name] > current_level + 1
-                        ):
-                            levels[listener_name] = current_level + 1
-                            if listener_name not in visited:
-                                queue.append(listener_name)
+        process_router_paths(flow, current, current_level, levels, queue)
 
     return levels
 
@@ -227,10 +220,7 @@ def build_ancestor_dict(flow: Any) -> Dict[str, Set[str]]:
 
 
 def dfs_ancestors(
-    node: str,
-    ancestors: Dict[str, Set[str]],
-    visited: Set[str],
-    flow: Any
+    node: str, ancestors: Dict[str, Set[str]], visited: Set[str], flow: Any
 ) -> None:
     """
     Perform depth-first search to build ancestor relationships.
@@ -274,7 +264,9 @@ def dfs_ancestors(
                     dfs_ancestors(listener_name, ancestors, visited, flow)
 
 
-def is_ancestor(node: str, ancestor_candidate: str, ancestors: Dict[str, Set[str]]) -> bool:
+def is_ancestor(
+    node: str, ancestor_candidate: str, ancestors: Dict[str, Set[str]]
+) -> bool:
     """
     Check if one node is an ancestor of another.
 
@@ -339,7 +331,9 @@ def build_parent_children_dict(flow: Any) -> Dict[str, List[str]]:
     return parent_children
 
 
-def get_child_index(parent: str, child: str, parent_children: Dict[str, List[str]]) -> int:
+def get_child_index(
+    parent: str, child: str, parent_children: Dict[str, List[str]]
+) -> int:
     """
     Get the index of a child node in its parent's sorted children list.
 
@@ -360,3 +354,23 @@ def get_child_index(parent: str, child: str, parent_children: Dict[str, List[str
     children = parent_children.get(parent, [])
     children.sort()
     return children.index(child)
+
+
+def process_router_paths(flow, current, current_level, levels, queue):
+    """
+    Handle the router connections for the current node.
+    """
+    if current in flow._routers:
+        paths = flow._router_paths.get(current, [])
+        for path in paths:
+            for listener_name, (
+                condition_type,
+                trigger_methods,
+            ) in flow._listeners.items():
+                if path in trigger_methods:
+                    if (
+                        listener_name not in levels
+                        or levels[listener_name] > current_level + 1
+                    ):
+                        levels[listener_name] = current_level + 1
+                        queue.append(listener_name)

src/crewai/knowledge/storage/knowledge_storage.py

@@ -76,7 +76,7 @@ class KnowledgeStorage(BaseKnowledgeStorage):
                         "context": fetched["documents"][0][i],  # type: ignore
                         "score": fetched["distances"][0][i],  # type: ignore
                     }
-                    if result["score"] >= score_threshold:  # type: ignore
+                    if result["score"] >= score_threshold:
                         results.append(result)
                 return results
             else:

src/crewai/llm.py

@@ -10,14 +10,23 @@ from typing import Any, Dict, List, Literal, Optional, Type, Union, cast
 from dotenv import load_dotenv
 from pydantic import BaseModel
 
+from crewai.utilities.events.llm_events import (
+    LLMCallCompletedEvent,
+    LLMCallFailedEvent,
+    LLMCallStartedEvent,
+    LLMCallType,
+)
+from crewai.utilities.events.tool_usage_events import ToolExecutionErrorEvent
+
 with warnings.catch_warnings():
     warnings.simplefilter("ignore", UserWarning)
     import litellm
-    from litellm import Choices, get_supported_openai_params
+    from litellm import Choices
     from litellm.types.utils import ModelResponse
-    from litellm.utils import supports_response_schema
+    from litellm.utils import get_supported_openai_params, supports_response_schema
 
 
+from crewai.utilities.events import crewai_event_bus
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
@@ -55,6 +64,7 @@ LLM_CONTEXT_WINDOW_SIZES = {
     "gpt-4-turbo": 128000,
     "o1-preview": 128000,
     "o1-mini": 128000,
+    "o3-mini": 200000,  # Based on official o3-mini specifications
     # gemini
     "gemini-2.0-flash": 1048576,
     "gemini-1.5-pro": 2097152,
@@ -181,14 +191,14 @@ class LLM:
 
     def _is_anthropic_model(self, model: str) -> bool:
         """Determine if the model is from Anthropic provider.
-        
+
         Args:
             model: The model identifier string.
-            
+
         Returns:
             bool: True if the model is from Anthropic, False otherwise.
         """
-        ANTHROPIC_PREFIXES = ('anthropic/', 'claude-', 'claude/')
+        ANTHROPIC_PREFIXES = ("anthropic/", "claude-", "claude/")
         return any(prefix in model.lower() for prefix in ANTHROPIC_PREFIXES)
 
     def call(
@@ -199,7 +209,7 @@ class LLM:
         available_functions: Optional[Dict[str, Any]] = None,
     ) -> Union[str, Any]:
         """High-level LLM call method.
-        
+
         Args:
             messages: Input messages for the LLM.
                      Can be a string or list of message dictionaries.
@@ -211,22 +221,22 @@ class LLM:
                       during and after the LLM call.
             available_functions: Optional dict mapping function names to callables
                                that can be invoked by the LLM.
-        
+
         Returns:
             Union[str, Any]: Either a text response from the LLM (str) or
                            the result of a tool function call (Any).
-        
+
         Raises:
             TypeError: If messages format is invalid
             ValueError: If response format is not supported
             LLMContextLengthExceededException: If input exceeds model's context limit
-        
+
         Examples:
             # Example 1: Simple string input
             >>> response = llm.call("Return the name of a random city.")
             >>> print(response)
             "Paris"
-            
+
             # Example 2: Message list with system and user messages
             >>> messages = [
             ...     {"role": "system", "content": "You are a geography expert"},
@@ -236,6 +246,15 @@ class LLM:
             >>> print(response)
             "The capital of France is Paris."
         """
+        crewai_event_bus.emit(
+            self,
+            event=LLMCallStartedEvent(
+                messages=messages,
+                tools=tools,
+                callbacks=callbacks,
+                available_functions=available_functions,
+            ),
+        )
         # Validate parameters before proceeding with the call.
         self._validate_call_params()
 
@@ -310,6 +329,7 @@ class LLM:
 
                 # --- 4) If no tool calls, return the text response
                 if not tool_calls or not available_functions:
+                    self._handle_emit_call_events(text_response, LLMCallType.LLM_CALL)
                     return text_response
 
                 # --- 5) Handle the tool call
@@ -327,12 +347,28 @@ class LLM:
                     try:
                         # Call the actual tool function
                         result = fn(**function_args)
+                        self._handle_emit_call_events(result, LLMCallType.TOOL_CALL)
                         return result
 
                     except Exception as e:
                         logging.error(
                             f"Error executing function '{function_name}': {e}"
                         )
+                        crewai_event_bus.emit(
+                            self,
+                            event=ToolExecutionErrorEvent(
+                                tool_name=function_name,
+                                tool_args=function_args,
+                                tool_class=fn,
+                                error=str(e),
+                            ),
+                        )
+                        crewai_event_bus.emit(
+                            self,
+                            event=LLMCallFailedEvent(
+                                error=f"Tool execution error: {str(e)}"
+                            ),
+                        )
                         return text_response
 
                 else:
@@ -342,42 +378,62 @@ class LLM:
                     return text_response
 
             except Exception as e:
+                crewai_event_bus.emit(
+                    self,
+                    event=LLMCallFailedEvent(error=str(e)),
+                )
                 if not LLMContextLengthExceededException(
                     str(e)
                 )._is_context_limit_error(str(e)):
                     logging.error(f"LiteLLM call failed: {str(e)}")
                 raise
 
-    def _format_messages_for_provider(self, messages: List[Dict[str, str]]) -> List[Dict[str, str]]:
+    def _handle_emit_call_events(self, response: Any, call_type: LLMCallType):
+        """Handle the events for the LLM call.
+
+        Args:
+            response (str): The response from the LLM call.
+            call_type (str): The type of call, either "tool_call" or "llm_call".
+        """
+        crewai_event_bus.emit(
+            self,
+            event=LLMCallCompletedEvent(response=response, call_type=call_type),
+        )
+
+    def _format_messages_for_provider(
+        self, messages: List[Dict[str, str]]
+    ) -> List[Dict[str, str]]:
         """Format messages according to provider requirements.
-        
+
         Args:
             messages: List of message dictionaries with 'role' and 'content' keys.
                      Can be empty or None.
-        
+
         Returns:
             List of formatted messages according to provider requirements.
             For Anthropic models, ensures first message has 'user' role.
-        
+
         Raises:
             TypeError: If messages is None or contains invalid message format.
         """
         if messages is None:
             raise TypeError("Messages cannot be None")
-            
+
         # Validate message format first
         for msg in messages:
             if not isinstance(msg, dict) or "role" not in msg or "content" not in msg:
-                raise TypeError("Invalid message format. Each message must be a dict with 'role' and 'content' keys")
-            
+                raise TypeError(
+                    "Invalid message format. Each message must be a dict with 'role' and 'content' keys"
+                )
+
         if not self.is_anthropic:
             return messages
-            
+
         # Anthropic requires messages to start with 'user' role
         if not messages or messages[0]["role"] == "system":
             # If first message is system or empty, add a placeholder user message
             return [{"role": "user", "content": "."}, *messages]
-                
+
         return messages
 
     def _get_custom_llm_provider(self) -> str:
@@ -413,7 +469,7 @@ class LLM:
     def supports_function_calling(self) -> bool:
         try:
             params = get_supported_openai_params(model=self.model)
-            return "response_format" in params
+            return params is not None and "tools" in params
         except Exception as e:
             logging.error(f"Failed to get supported params: {str(e)}")
             return False
@@ -421,7 +477,7 @@ class LLM:
     def supports_stop_words(self) -> bool:
         try:
             params = get_supported_openai_params(model=self.model)
-            return "stop" in params
+            return params is not None and "stop" in params
         except Exception as e:
             logging.error(f"Failed to get supported params: {str(e)}")
             return False
@@ -430,10 +486,23 @@ class LLM:
         """
         Returns the context window size, using 75% of the maximum to avoid
         cutting off messages mid-thread.
+
+        Raises:
+            ValueError: If a model's context window size is outside valid bounds (1024-2097152)
         """
         if self.context_window_size != 0:
             return self.context_window_size
 
+        MIN_CONTEXT = 1024
+        MAX_CONTEXT = 2097152  # Current max from gemini-1.5-pro
+
+        # Validate all context window sizes
+        for key, value in LLM_CONTEXT_WINDOW_SIZES.items():
+            if value < MIN_CONTEXT or value > MAX_CONTEXT:
+                raise ValueError(
+                    f"Context window for {key} must be between {MIN_CONTEXT} and {MAX_CONTEXT}"
+                )
+
         self.context_window_size = int(
             DEFAULT_CONTEXT_WINDOW_SIZE * CONTEXT_WINDOW_USAGE_RATIO
         )

src/crewai/task.py

@@ -21,7 +21,6 @@ from typing import (
     Union,
 )
 
-from opentelemetry.trace import Span
 from pydantic import (
     UUID4,
     BaseModel,
@@ -36,10 +35,15 @@ from crewai.agents.agent_builder.base_agent import BaseAgent
 from crewai.tasks.guardrail_result import GuardrailResult
 from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
-from crewai.telemetry.telemetry import Telemetry
 from crewai.tools.base_tool import BaseTool
 from crewai.utilities.config import process_config
 from crewai.utilities.converter import Converter, convert_to_model
+from crewai.utilities.events import (
+    TaskCompletedEvent,
+    TaskFailedEvent,
+    TaskStartedEvent,
+)
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 from crewai.utilities.i18n import I18N
 from crewai.utilities.printer import Printer
 
@@ -183,8 +187,6 @@ class Task(BaseModel):
                     )
         return v
 
-    _telemetry: Telemetry = PrivateAttr(default_factory=Telemetry)
-    _execution_span: Optional[Span] = PrivateAttr(default=None)
     _original_description: Optional[str] = PrivateAttr(default=None)
     _original_expected_output: Optional[str] = PrivateAttr(default=None)
     _original_output_file: Optional[str] = PrivateAttr(default=None)
@@ -348,100 +350,102 @@ class Task(BaseModel):
         tools: Optional[List[Any]],
     ) -> TaskOutput:
         """Run the core execution logic of the task."""
-        agent = agent or self.agent
-        self.agent = agent
-        if not agent:
-            raise Exception(
-                f"The task '{self.description}' has no agent assigned, therefore it can't be executed directly and should be executed in a Crew using a specific process that support that, like hierarchical."
+        try:
+            agent = agent or self.agent
+            self.agent = agent
+            if not agent:
+                raise Exception(
+                    f"The task '{self.description}' has no agent assigned, therefore it can't be executed directly and should be executed in a Crew using a specific process that support that, like hierarchical."
+                )
+
+            self.start_time = datetime.datetime.now()
+
+            self.prompt_context = context
+            tools = tools or self.tools or []
+
+            self.processed_by_agents.add(agent.role)
+            crewai_event_bus.emit(self, TaskStartedEvent(context=context))
+            result = agent.execute_task(
+                task=self,
+                context=context,
+                tools=tools,
             )
 
-        self.start_time = datetime.datetime.now()
-        self._execution_span = self._telemetry.task_started(crew=agent.crew, task=self)
+            pydantic_output, json_output = self._export_output(result)
+            task_output = TaskOutput(
+                name=self.name,
+                description=self.description,
+                expected_output=self.expected_output,
+                raw=result,
+                pydantic=pydantic_output,
+                json_dict=json_output,
+                agent=agent.role,
+                output_format=self._get_output_format(),
+            )
 
-        self.prompt_context = context
-        tools = tools or self.tools or []
+            if self.guardrail:
+                guardrail_result = GuardrailResult.from_tuple(
+                    self.guardrail(task_output)
+                )
+                if not guardrail_result.success:
+                    if self.retry_count >= self.max_retries:
+                        raise Exception(
+                            f"Task failed guardrail validation after {self.max_retries} retries. "
+                            f"Last error: {guardrail_result.error}"
+                        )
 
-        self.processed_by_agents.add(agent.role)
+                    self.retry_count += 1
+                    context = self.i18n.errors("validation_error").format(
+                        guardrail_result_error=guardrail_result.error,
+                        task_output=task_output.raw,
+                    )
+                    printer = Printer()
+                    printer.print(
+                        content=f"Guardrail blocked, retrying, due to: {guardrail_result.error}\n",
+                        color="yellow",
+                    )
+                    return self._execute_core(agent, context, tools)
 
-        result = agent.execute_task(
-            task=self,
-            context=context,
-            tools=tools,
-        )
-
-        pydantic_output, json_output = self._export_output(result)
-        task_output = TaskOutput(
-            name=self.name,
-            description=self.description,
-            expected_output=self.expected_output,
-            raw=result,
-            pydantic=pydantic_output,
-            json_dict=json_output,
-            agent=agent.role,
-            output_format=self._get_output_format(),
-        )
-
-        if self.guardrail:
-            guardrail_result = GuardrailResult.from_tuple(self.guardrail(task_output))
-            if not guardrail_result.success:
-                if self.retry_count >= self.max_retries:
+                if guardrail_result.result is None:
                     raise Exception(
-                        f"Task failed guardrail validation after {self.max_retries} retries. "
-                        f"Last error: {guardrail_result.error}"
+                        "Task guardrail returned None as result. This is not allowed."
                     )
 
-                self.retry_count += 1
-                context = self.i18n.errors("validation_error").format(
-                    guardrail_result_error=guardrail_result.error,
-                    task_output=task_output.raw,
+                if isinstance(guardrail_result.result, str):
+                    task_output.raw = guardrail_result.result
+                    pydantic_output, json_output = self._export_output(
+                        guardrail_result.result
+                    )
+                    task_output.pydantic = pydantic_output
+                    task_output.json_dict = json_output
+                elif isinstance(guardrail_result.result, TaskOutput):
+                    task_output = guardrail_result.result
+
+            self.output = task_output
+            self.end_time = datetime.datetime.now()
+
+            if self.callback:
+                self.callback(self.output)
+
+            crew = self.agent.crew  # type: ignore[union-attr]
+            if crew and crew.task_callback and crew.task_callback != self.callback:
+                crew.task_callback(self.output)
+
+            if self.output_file:
+                content = (
+                    json_output
+                    if json_output
+                    else pydantic_output.model_dump_json()
+                    if pydantic_output
+                    else result
                 )
-                printer = Printer()
-                printer.print(
-                    content=f"Guardrail blocked, retrying, due to: {guardrail_result.error}\n",
-                    color="yellow",
-                )
-                return self._execute_core(agent, context, tools)
-
-            if guardrail_result.result is None:
-                raise Exception(
-                    "Task guardrail returned None as result. This is not allowed."
-                )
-
-            if isinstance(guardrail_result.result, str):
-                task_output.raw = guardrail_result.result
-                pydantic_output, json_output = self._export_output(
-                    guardrail_result.result
-                )
-                task_output.pydantic = pydantic_output
-                task_output.json_dict = json_output
-            elif isinstance(guardrail_result.result, TaskOutput):
-                task_output = guardrail_result.result
-
-        self.output = task_output
-        self.end_time = datetime.datetime.now()
-
-        if self.callback:
-            self.callback(self.output)
-
-        crew = self.agent.crew  # type: ignore[union-attr]
-        if crew and crew.task_callback and crew.task_callback != self.callback:
-            crew.task_callback(self.output)
-
-        if self._execution_span:
-            self._telemetry.task_ended(self._execution_span, self, agent.crew)
-            self._execution_span = None
-
-        if self.output_file:
-            content = (
-                json_output
-                if json_output
-                else pydantic_output.model_dump_json()
-                if pydantic_output
-                else result
-            )
-            self._save_file(content)
-
-        return task_output
+                self._save_file(content)
+            crewai_event_bus.emit(self, TaskCompletedEvent(output=task_output))
+            return task_output
+        except Exception as e:
+            self.end_time = datetime.datetime.now()
+            crewai_event_bus.emit(self, TaskFailedEvent(error=str(e)))
+            raise e  # Re-raise the exception after emitting the event
 
     def prompt(self) -> str:
         """Prompt the task.
@@ -716,10 +720,9 @@ class Task(BaseModel):
                     file.write(str(result))
         except (OSError, IOError) as e:
             raise RuntimeError(
-                "\n".join([
-                    f"Failed to save output file: {e}",
-                    FILEWRITER_RECOMMENDATION
-                ])
+                "\n".join(
+                    [f"Failed to save output file: {e}", FILEWRITER_RECOMMENDATION]
+                )
             )
         return None
 

src/crewai/tools/tool_usage.py

@@ -10,20 +10,21 @@ from typing import Any, Dict, List, Optional, Union
 import json5
 from json_repair import repair_json
 
-import crewai.utilities.events as events
 from crewai.agents.tools_handler import ToolsHandler
 from crewai.task import Task
 from crewai.telemetry import Telemetry
 from crewai.tools import BaseTool
 from crewai.tools.structured_tool import CrewStructuredTool
 from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
-from crewai.tools.tool_usage_events import ToolUsageError, ToolUsageFinished
 from crewai.utilities import I18N, Converter, ConverterError, Printer
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+from crewai.utilities.events.tool_usage_events import (
+    ToolSelectionErrorEvent,
+    ToolUsageErrorEvent,
+    ToolUsageFinishedEvent,
+    ToolValidateInputErrorEvent,
+)
 
-try:
-    import agentops  # type: ignore
-except ImportError:
-    agentops = None
 OPENAI_BIGGER_MODELS = [
     "gpt-4",
     "gpt-4o",
@@ -136,7 +137,6 @@ class ToolUsage:
         tool: Any,
         calling: Union[ToolCalling, InstructorToolCalling],
     ) -> str:  # TODO: Fix this return type
-        tool_event = agentops.ToolEvent(name=calling.tool_name) if agentops else None  # type: ignore
         if self._check_tool_repeated_usage(calling=calling):  # type: ignore # _check_tool_repeated_usage of "ToolUsage" does not return a value (it only ever returns None)
             try:
                 result = self._i18n.errors("task_repeated_usage").format(
@@ -212,10 +212,6 @@ class ToolUsage:
                     return error  # type: ignore # No return value expected
 
                 self.task.increment_tools_errors()
-                if agentops:
-                    agentops.record(
-                        agentops.ErrorEvent(exception=e, trigger_event=tool_event)
-                    )
                 return self.use(calling=calling, tool_string=tool_string)  # type: ignore # No return value expected
 
             if self.tools_handler:
@@ -231,9 +227,6 @@ class ToolUsage:
                 self.tools_handler.on_tool_use(
                     calling=calling, output=result, should_cache=should_cache
                 )
-
-        if agentops:
-            agentops.record(tool_event)
         self._telemetry.tool_usage(
             llm=self.function_calling_llm,
             tool_name=tool.name,
@@ -308,14 +301,33 @@ class ToolUsage:
             ):
                 return tool
         self.task.increment_tools_errors()
+        tool_selection_data = {
+            "agent_key": self.agent.key,
+            "agent_role": self.agent.role,
+            "tool_name": tool_name,
+            "tool_args": {},
+            "tool_class": self.tools_description,
+        }
         if tool_name and tool_name != "":
-            raise Exception(
-                f"Action '{tool_name}' don't exist, these are the only available Actions:\n{self.tools_description}"
+            error = f"Action '{tool_name}' don't exist, these are the only available Actions:\n{self.tools_description}"
+            crewai_event_bus.emit(
+                self,
+                ToolSelectionErrorEvent(
+                    **tool_selection_data,
+                    error=error,
+                ),
             )
+            raise Exception(error)
         else:
-            raise Exception(
-                f"I forgot the Action name, these are the only available Actions: {self.tools_description}"
+            error = f"I forgot the Action name, these are the only available Actions: {self.tools_description}"
+            crewai_event_bus.emit(
+                self,
+                ToolSelectionErrorEvent(
+                    **tool_selection_data,
+                    error=error,
+                ),
             )
+            raise Exception(error)
 
     def _render(self) -> str:
         """Render the tool name and description in plain text."""
@@ -451,18 +463,33 @@ class ToolUsage:
             if isinstance(arguments, dict):
                 return arguments
         except Exception as e:
-            self._printer.print(content=f"Failed to repair JSON: {e}", color="red")
+            error = f"Failed to repair JSON: {e}"
+            self._printer.print(content=error, color="red")
 
-        # If all parsing attempts fail, raise an error
-        raise Exception(
+        error_message = (
             "Tool input must be a valid dictionary in JSON or Python literal format"
         )
+        self._emit_validate_input_error(error_message)
+        # If all parsing attempts fail, raise an error
+        raise Exception(error_message)
+
+    def _emit_validate_input_error(self, final_error: str):
+        tool_selection_data = {
+            "agent_key": self.agent.key,
+            "agent_role": self.agent.role,
+            "tool_name": self.action.tool,
+            "tool_args": str(self.action.tool_input),
+            "tool_class": self.__class__.__name__,
+        }
+
+        crewai_event_bus.emit(
+            self,
+            ToolValidateInputErrorEvent(**tool_selection_data, error=final_error),
+        )
 
     def on_tool_error(self, tool: Any, tool_calling: ToolCalling, e: Exception) -> None:
         event_data = self._prepare_event_data(tool, tool_calling)
-        events.emit(
-            source=self, event=ToolUsageError(**{**event_data, "error": str(e)})
-        )
+        crewai_event_bus.emit(self, ToolUsageErrorEvent(**{**event_data, "error": e}))
 
     def on_tool_use_finished(
         self, tool: Any, tool_calling: ToolCalling, from_cache: bool, started_at: float
@@ -476,7 +503,7 @@ class ToolUsage:
                 "from_cache": from_cache,
             }
         )
-        events.emit(source=self, event=ToolUsageFinished(**event_data))
+        crewai_event_bus.emit(self, ToolUsageFinishedEvent(**event_data))
 
     def _prepare_event_data(self, tool: Any, tool_calling: ToolCalling) -> dict:
         return {

src/crewai/tools/tool_usage_events.py

@@ -1,24 +0,0 @@
-from datetime import datetime
-from typing import Any, Dict
-
-from pydantic import BaseModel
-
-
-class ToolUsageEvent(BaseModel):
-    agent_key: str
-    agent_role: str
-    tool_name: str
-    tool_args: Dict[str, Any]
-    tool_class: str
-    run_attempts: int | None = None
-    delegations: int | None = None
-
-
-class ToolUsageFinished(ToolUsageEvent):
-    started_at: datetime
-    finished_at: datetime
-    from_cache: bool = False
-
-
-class ToolUsageError(ToolUsageEvent):
-    error: str

src/crewai/translations/en.json

@@ -23,7 +23,6 @@
     "summary": "This is a summary of our conversation so far:\n{merged_summary}",
     "manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
     "formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python.",
-    "human_feedback_classification": "Determine if the following feedback indicates that the user is satisfied or if further changes are needed. Respond with 'True' if further changes are needed, or 'False' if the user is satisfied. **Important** Do not include any additional commentary outside of your 'True' or 'False' response.\n\nFeedback: \"{feedback}\"",
     "conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals.",
     "feedback_instructions": "User feedback: {feedback}\nInstructions: Use this feedback to enhance the next output iteration.\nNote: Do not respond or add commentary."
   },
@@ -40,8 +39,8 @@
     "validation_error": "### Previous attempt failed validation: {guardrail_result_error}\n\n\n### Previous result:\n{task_output}\n\n\nTry again, making sure to address the validation error."
   },
   "tools": {
-    "delegate_work": "Delegate a specific task to one of the following coworkers: {coworkers}\nThe input to this tool should be the coworker, the task you want them to do, and ALL necessary context to execute the task, they know nothing about the task, so share absolute everything you know, don't reference things but instead explain them.",
-    "ask_question": "Ask a specific question to one of the following coworkers: {coworkers}\nThe input to this tool should be the coworker, the question you have for them, and ALL necessary context to ask the question properly, they know nothing about the question, so share absolute everything you know, don't reference things but instead explain them.",
+    "delegate_work": "Delegate a specific task to one of the following coworkers: {coworkers}\nThe input to this tool should be the coworker, the task you want them to do, and ALL necessary context to execute the task, they know nothing about the task, so share absolutely everything you know, don't reference things but instead explain them.",
+    "ask_question": "Ask a specific question to one of the following coworkers: {coworkers}\nThe input to this tool should be the coworker, the question you have for them, and ALL necessary context to ask the question properly, they know nothing about the question, so share absolutely everything you know, don't reference things but instead explain them.",
     "add_image": {
       "name": "Add image to content",
       "description": "See image to understand its content, you can optionally ask a question about the image",

src/crewai/utilities/constants.py

@@ -4,3 +4,4 @@ DEFAULT_SCORE_THRESHOLD = 0.35
 KNOWLEDGE_DIRECTORY = "knowledge"
 MAX_LLM_RETRY = 3
 MAX_FILE_NAME_LENGTH = 255
+EMITTER_COLOR = "bold_blue"

src/crewai/utilities/converter.py

@@ -20,11 +20,11 @@ class ConverterError(Exception):
 class Converter(OutputConverter):
     """Class that converts text into either pydantic or json."""
 
-    def to_pydantic(self, current_attempt=1):
+    def to_pydantic(self, current_attempt=1) -> BaseModel:
         """Convert text to pydantic."""
         try:
             if self.llm.supports_function_calling():
-                return self._create_instructor().to_pydantic()
+                result = self._create_instructor().to_pydantic()
             else:
                 response = self.llm.call(
                     [
@@ -32,18 +32,40 @@ class Converter(OutputConverter):
                         {"role": "user", "content": self.text},
                     ]
                 )
-                return self.model.model_validate_json(response)
+                try:
+                    # Try to directly validate the response JSON
+                    result = self.model.model_validate_json(response)
+                except ValidationError:
+                    # If direct validation fails, attempt to extract valid JSON
+                    result = handle_partial_json(response, self.model, False, None)
+                    # Ensure result is a BaseModel instance
+                    if not isinstance(result, BaseModel):
+                        if isinstance(result, dict):
+                            result = self.model.parse_obj(result)
+                        elif isinstance(result, str):
+                            try:
+                                parsed = json.loads(result)
+                                result = self.model.parse_obj(parsed)
+                            except Exception as parse_err:
+                                raise ConverterError(
+                                    f"Failed to convert partial JSON result into Pydantic: {parse_err}"
+                                )
+                        else:
+                            raise ConverterError(
+                                "handle_partial_json returned an unexpected type."
+                            )
+            return result
         except ValidationError as e:
             if current_attempt < self.max_attempts:
                 return self.to_pydantic(current_attempt + 1)
             raise ConverterError(
-                f"Failed to convert text into a Pydantic model due to the following validation error: {e}"
+                f"Failed to convert text into a Pydantic model due to validation error: {e}"
             )
         except Exception as e:
             if current_attempt < self.max_attempts:
                 return self.to_pydantic(current_attempt + 1)
             raise ConverterError(
-                f"Failed to convert text into a Pydantic model due to the following error: {e}"
+                f"Failed to convert text into a Pydantic model due to error: {e}"
             )
 
     def to_json(self, current_attempt=1):
@@ -197,11 +219,15 @@ def get_conversion_instructions(model: Type[BaseModel], llm: Any) -> str:
     if llm.supports_function_calling():
         model_schema = PydanticSchemaParser(model=model).get_schema()
         instructions += (
-            f"\n\nThe JSON should follow this schema:\n```json\n{model_schema}\n```"
+            f"\n\nOutput ONLY the valid JSON and nothing else.\n\n"
+            f"The JSON must follow this schema exactly:\n```json\n{model_schema}\n```"
         )
     else:
         model_description = generate_model_description(model)
-        instructions += f"\n\nThe JSON should follow this format:\n{model_description}"
+        instructions += (
+            f"\n\nOutput ONLY the valid JSON and nothing else.\n\n"
+            f"The JSON must follow this format exactly:\n{model_description}"
+        )
     return instructions
 
 

src/crewai/utilities/evaluators/task_evaluator.py

@@ -3,19 +3,9 @@ from typing import List
 from pydantic import BaseModel, Field
 
 from crewai.utilities import Converter
+from crewai.utilities.events import TaskEvaluationEvent, crewai_event_bus
 from crewai.utilities.pydantic_schema_parser import PydanticSchemaParser
 
-agentops = None
-try:
-    from agentops import track_agent  # type: ignore
-except ImportError:
-
-    def track_agent(name):
-        def noop(f):
-            return f
-
-        return noop
-
 
 class Entity(BaseModel):
     name: str = Field(description="The name of the entity.")
@@ -48,12 +38,15 @@ class TrainingTaskEvaluation(BaseModel):
     )
 
 
-@track_agent(name="Task Evaluator")
 class TaskEvaluator:
     def __init__(self, original_agent):
         self.llm = original_agent.llm
+        self.original_agent = original_agent
 
     def evaluate(self, task, output) -> TaskEvaluation:
+        crewai_event_bus.emit(
+            self, TaskEvaluationEvent(evaluation_type="task_evaluation")
+        )
         evaluation_query = (
             f"Assess the quality of the task completed based on the description, expected output, and actual results.\n\n"
             f"Task Description:\n{task.description}\n\n"
@@ -90,6 +83,9 @@ class TaskEvaluator:
             - training_data (dict): The training data to be evaluated.
             - agent_id (str): The ID of the agent.
         """
+        crewai_event_bus.emit(
+            self, TaskEvaluationEvent(evaluation_type="training_data_evaluation")
+        )
 
         output_training_data = training_data[agent_id]
         final_aggregated_data = ""

src/crewai/utilities/events.py

@@ -1,44 +0,0 @@
-from functools import wraps
-from typing import Any, Callable, Dict, Generic, List, Type, TypeVar
-
-from pydantic import BaseModel
-
-T = TypeVar("T")
-EVT = TypeVar("EVT", bound=BaseModel)
-
-
-class Emitter(Generic[T, EVT]):
-    _listeners: Dict[Type[EVT], List[Callable]] = {}
-
-    def on(self, event_type: Type[EVT]):
-        def decorator(func: Callable):
-            @wraps(func)
-            def wrapper(*args, **kwargs):
-                return func(*args, **kwargs)
-
-            self._listeners.setdefault(event_type, []).append(wrapper)
-            return wrapper
-
-        return decorator
-
-    def emit(self, source: T, event: EVT) -> None:
-        event_type = type(event)
-        for func in self._listeners.get(event_type, []):
-            func(source, event)
-
-
-default_emitter = Emitter[Any, BaseModel]()
-
-
-def emit(source: Any, event: BaseModel, raise_on_error: bool = False) -> None:
-    try:
-        default_emitter.emit(source, event)
-    except Exception as e:
-        if raise_on_error:
-            raise e
-        else:
-            print(f"Error emitting event: {e}")
-
-
-def on(event_type: Type[BaseModel]) -> Callable:
-    return default_emitter.on(event_type)

src/crewai/utilities/events/__init__.py

@@ -0,0 +1,41 @@
+from .crew_events import (
+    CrewKickoffStartedEvent,
+    CrewKickoffCompletedEvent,
+    CrewKickoffFailedEvent,
+    CrewTrainStartedEvent,
+    CrewTrainCompletedEvent,
+    CrewTrainFailedEvent,
+    CrewTestStartedEvent,
+    CrewTestCompletedEvent,
+    CrewTestFailedEvent,
+)
+from .agent_events import (
+    AgentExecutionStartedEvent,
+    AgentExecutionCompletedEvent,
+    AgentExecutionErrorEvent,
+)
+from .task_events import TaskStartedEvent, TaskCompletedEvent, TaskFailedEvent, TaskEvaluationEvent
+from .flow_events import (
+    FlowCreatedEvent,
+    FlowStartedEvent,
+    FlowFinishedEvent,
+    FlowPlotEvent,
+    MethodExecutionStartedEvent,
+    MethodExecutionFinishedEvent,
+    MethodExecutionFailedEvent,
+)
+from .crewai_event_bus import CrewAIEventsBus, crewai_event_bus
+from .tool_usage_events import (
+    ToolUsageFinishedEvent,
+    ToolUsageErrorEvent,
+    ToolUsageStartedEvent,
+    ToolExecutionErrorEvent,
+    ToolSelectionErrorEvent,
+    ToolUsageEvent,
+    ToolValidateInputErrorEvent,
+)
+from .llm_events import LLMCallCompletedEvent, LLMCallFailedEvent, LLMCallStartedEvent
+
+# events
+from .event_listener import EventListener
+from .third_party.agentops_listener import agentops_listener

src/crewai/utilities/events/agent_events.py

@@ -0,0 +1,40 @@
+from typing import TYPE_CHECKING, Any, Dict, Optional, Sequence, Union
+
+from crewai.agents.agent_builder.base_agent import BaseAgent
+from crewai.tools.base_tool import BaseTool
+from crewai.tools.structured_tool import CrewStructuredTool
+
+from .base_events import CrewEvent
+
+if TYPE_CHECKING:
+    from crewai.agents.agent_builder.base_agent import BaseAgent
+
+
+class AgentExecutionStartedEvent(CrewEvent):
+    """Event emitted when an agent starts executing a task"""
+
+    agent: BaseAgent
+    task: Any
+    tools: Optional[Sequence[Union[BaseTool, CrewStructuredTool]]]
+    task_prompt: str
+    type: str = "agent_execution_started"
+
+    model_config = {"arbitrary_types_allowed": True}
+
+
+class AgentExecutionCompletedEvent(CrewEvent):
+    """Event emitted when an agent completes executing a task"""
+
+    agent: BaseAgent
+    task: Any
+    output: str
+    type: str = "agent_execution_completed"
+
+
+class AgentExecutionErrorEvent(CrewEvent):
+    """Event emitted when an agent encounters an error during execution"""
+
+    agent: BaseAgent
+    task: Any
+    error: str
+    type: str = "agent_execution_error"

src/crewai/utilities/events/base_event_listener.py

@@ -0,0 +1,14 @@
+from abc import ABC, abstractmethod
+from logging import Logger
+
+from crewai.utilities.events.crewai_event_bus import CrewAIEventsBus, crewai_event_bus
+
+
+class BaseEventListener(ABC):
+    def __init__(self):
+        super().__init__()
+        self.setup_listeners(crewai_event_bus)
+
+    @abstractmethod
+    def setup_listeners(self, crewai_event_bus: CrewAIEventsBus):
+        pass

src/crewai/utilities/events/base_events.py

@@ -0,0 +1,10 @@
+from datetime import datetime
+
+from pydantic import BaseModel, Field
+
+
+class CrewEvent(BaseModel):
+    """Base class for all crew events"""
+
+    timestamp: datetime = Field(default_factory=datetime.now)
+    type: str

src/crewai/utilities/events/crew_events.py

@@ -0,0 +1,81 @@
+from typing import Any, Dict, Optional, Union
+
+from pydantic import InstanceOf
+
+from crewai.utilities.events.base_events import CrewEvent
+
+
+class CrewKickoffStartedEvent(CrewEvent):
+    """Event emitted when a crew starts execution"""
+
+    crew_name: Optional[str]
+    inputs: Optional[Dict[str, Any]]
+    type: str = "crew_kickoff_started"
+
+
+class CrewKickoffCompletedEvent(CrewEvent):
+    """Event emitted when a crew completes execution"""
+
+    crew_name: Optional[str]
+    output: Any
+    type: str = "crew_kickoff_completed"
+
+
+class CrewKickoffFailedEvent(CrewEvent):
+    """Event emitted when a crew fails to complete execution"""
+
+    error: str
+    crew_name: Optional[str]
+    type: str = "crew_kickoff_failed"
+
+
+class CrewTrainStartedEvent(CrewEvent):
+    """Event emitted when a crew starts training"""
+
+    crew_name: Optional[str]
+    n_iterations: int
+    filename: str
+    inputs: Optional[Dict[str, Any]]
+    type: str = "crew_train_started"
+
+
+class CrewTrainCompletedEvent(CrewEvent):
+    """Event emitted when a crew completes training"""
+
+    crew_name: Optional[str]
+    n_iterations: int
+    filename: str
+    type: str = "crew_train_completed"
+
+
+class CrewTrainFailedEvent(CrewEvent):
+    """Event emitted when a crew fails to complete training"""
+
+    error: str
+    crew_name: Optional[str]
+    type: str = "crew_train_failed"
+
+
+class CrewTestStartedEvent(CrewEvent):
+    """Event emitted when a crew starts testing"""
+
+    crew_name: Optional[str]
+    n_iterations: int
+    eval_llm: Optional[Union[str, Any]]
+    inputs: Optional[Dict[str, Any]]
+    type: str = "crew_test_started"
+
+
+class CrewTestCompletedEvent(CrewEvent):
+    """Event emitted when a crew completes testing"""
+
+    crew_name: Optional[str]
+    type: str = "crew_test_completed"
+
+
+class CrewTestFailedEvent(CrewEvent):
+    """Event emitted when a crew fails to complete testing"""
+
+    error: str
+    crew_name: Optional[str]
+    type: str = "crew_test_failed"

src/crewai/utilities/events/crewai_event_bus.py

@@ -0,0 +1,113 @@
+import threading
+from contextlib import contextmanager
+from typing import Any, Callable, Dict, List, Type, TypeVar, cast
+
+from blinker import Signal
+
+from crewai.utilities.events.base_events import CrewEvent
+from crewai.utilities.events.event_types import EventTypes
+
+EventT = TypeVar("EventT", bound=CrewEvent)
+
+
+class CrewAIEventsBus:
+    """
+    A singleton event bus that uses blinker signals for event handling.
+    Allows both internal (Flow/Crew) and external event handling.
+    """
+
+    _instance = None
+    _lock = threading.Lock()
+
+    def __new__(cls):
+        if cls._instance is None:
+            with cls._lock:
+                if cls._instance is None:  # prevent race condition
+                    cls._instance = super(CrewAIEventsBus, cls).__new__(cls)
+                    cls._instance._initialize()
+        return cls._instance
+
+    def _initialize(self) -> None:
+        """Initialize the event bus internal state"""
+        self._signal = Signal("crewai_event_bus")
+        self._handlers: Dict[Type[CrewEvent], List[Callable]] = {}
+
+    def on(
+        self, event_type: Type[EventT]
+    ) -> Callable[[Callable[[Any, EventT], None]], Callable[[Any, EventT], None]]:
+        """
+        Decorator to register an event handler for a specific event type.
+
+        Usage:
+            @crewai_event_bus.on(AgentExecutionCompletedEvent)
+            def on_agent_execution_completed(
+                source: Any, event: AgentExecutionCompletedEvent
+            ):
+                print(f"👍 Agent '{event.agent}' completed task")
+                print(f"   Output: {event.output}")
+        """
+
+        def decorator(
+            handler: Callable[[Any, EventT], None],
+        ) -> Callable[[Any, EventT], None]:
+            if event_type not in self._handlers:
+                self._handlers[event_type] = []
+            self._handlers[event_type].append(
+                cast(Callable[[Any, EventT], None], handler)
+            )
+            return handler
+
+        return decorator
+
+    def emit(self, source: Any, event: CrewEvent) -> None:
+        """
+        Emit an event to all registered handlers
+
+        Args:
+            source: The object emitting the event
+            event: The event instance to emit
+        """
+        event_type = type(event)
+        if event_type in self._handlers:
+            for handler in self._handlers[event_type]:
+                handler(source, event)
+        self._signal.send(source, event=event)
+
+    def clear_handlers(self) -> None:
+        """Clear all registered event handlers - useful for testing"""
+        self._handlers.clear()
+
+    def register_handler(
+        self, event_type: Type[EventTypes], handler: Callable[[Any, EventTypes], None]
+    ) -> None:
+        """Register an event handler for a specific event type"""
+        if event_type not in self._handlers:
+            self._handlers[event_type] = []
+        self._handlers[event_type].append(
+            cast(Callable[[Any, EventTypes], None], handler)
+        )
+
+    @contextmanager
+    def scoped_handlers(self):
+        """
+        Context manager for temporary event handling scope.
+        Useful for testing or temporary event handling.
+
+        Usage:
+            with crewai_event_bus.scoped_handlers():
+                @crewai_event_bus.on(CrewKickoffStarted)
+                def temp_handler(source, event):
+                    print("Temporary handler")
+                # Do stuff...
+            # Handlers are cleared after the context
+        """
+        previous_handlers = self._handlers.copy()
+        self._handlers.clear()
+        try:
+            yield
+        finally:
+            self._handlers = previous_handlers
+
+
+# Global instance
+crewai_event_bus = CrewAIEventsBus()

src/crewai/utilities/events/event_listener.py

@@ -0,0 +1,288 @@
+from typing import Any, Dict
+
+from pydantic import Field, PrivateAttr
+
+from crewai.task import Task
+from crewai.telemetry.telemetry import Telemetry
+from crewai.utilities import Logger
+from crewai.utilities.constants import EMITTER_COLOR
+from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.utilities.events.llm_events import (
+    LLMCallCompletedEvent,
+    LLMCallFailedEvent,
+    LLMCallStartedEvent,
+)
+
+from .agent_events import AgentExecutionCompletedEvent, AgentExecutionStartedEvent
+from .crew_events import (
+    CrewKickoffCompletedEvent,
+    CrewKickoffFailedEvent,
+    CrewKickoffStartedEvent,
+    CrewTestCompletedEvent,
+    CrewTestFailedEvent,
+    CrewTestStartedEvent,
+    CrewTrainCompletedEvent,
+    CrewTrainFailedEvent,
+    CrewTrainStartedEvent,
+)
+from .flow_events import (
+    FlowCreatedEvent,
+    FlowFinishedEvent,
+    FlowStartedEvent,
+    MethodExecutionFailedEvent,
+    MethodExecutionFinishedEvent,
+    MethodExecutionStartedEvent,
+)
+from .task_events import TaskCompletedEvent, TaskFailedEvent, TaskStartedEvent
+from .tool_usage_events import (
+    ToolUsageErrorEvent,
+    ToolUsageFinishedEvent,
+    ToolUsageStartedEvent,
+)
+
+
+class EventListener(BaseEventListener):
+    _instance = None
+    _telemetry: Telemetry = PrivateAttr(default_factory=lambda: Telemetry())
+    logger = Logger(verbose=True, default_color=EMITTER_COLOR)
+    execution_spans: Dict[Task, Any] = Field(default_factory=dict)
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+            cls._instance._initialized = False
+        return cls._instance
+
+    def __init__(self):
+        if not hasattr(self, "_initialized") or not self._initialized:
+            super().__init__()
+            self._telemetry = Telemetry()
+            self._telemetry.set_tracer()
+            self.execution_spans = {}
+            self._initialized = True
+
+    # ----------- CREW EVENTS -----------
+
+    def setup_listeners(self, crewai_event_bus):
+        @crewai_event_bus.on(CrewKickoffStartedEvent)
+        def on_crew_started(source, event: CrewKickoffStartedEvent):
+            self.logger.log(
+                f"🚀 Crew '{event.crew_name}' started, {source.id}",
+                event.timestamp,
+            )
+            self._telemetry.crew_execution_span(source, event.inputs)
+
+        @crewai_event_bus.on(CrewKickoffCompletedEvent)
+        def on_crew_completed(source, event: CrewKickoffCompletedEvent):
+            final_string_output = event.output.raw
+            self._telemetry.end_crew(source, final_string_output)
+            self.logger.log(
+                f"✅ Crew '{event.crew_name}' completed, {source.id}",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(CrewKickoffFailedEvent)
+        def on_crew_failed(source, event: CrewKickoffFailedEvent):
+            self.logger.log(
+                f"❌ Crew '{event.crew_name}' failed, {source.id}",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(CrewTestStartedEvent)
+        def on_crew_test_started(source, event: CrewTestStartedEvent):
+            cloned_crew = source.copy()
+            self._telemetry.test_execution_span(
+                cloned_crew,
+                event.n_iterations,
+                event.inputs,
+                event.eval_llm or "",
+            )
+            self.logger.log(
+                f"🚀 Crew '{event.crew_name}' started test, {source.id}",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(CrewTestCompletedEvent)
+        def on_crew_test_completed(source, event: CrewTestCompletedEvent):
+            self.logger.log(
+                f"✅ Crew '{event.crew_name}' completed test",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(CrewTestFailedEvent)
+        def on_crew_test_failed(source, event: CrewTestFailedEvent):
+            self.logger.log(
+                f"❌ Crew '{event.crew_name}' failed test",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(CrewTrainStartedEvent)
+        def on_crew_train_started(source, event: CrewTrainStartedEvent):
+            self.logger.log(
+                f"📋 Crew '{event.crew_name}' started train",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(CrewTrainCompletedEvent)
+        def on_crew_train_completed(source, event: CrewTrainCompletedEvent):
+            self.logger.log(
+                f"✅ Crew '{event.crew_name}' completed train",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(CrewTrainFailedEvent)
+        def on_crew_train_failed(source, event: CrewTrainFailedEvent):
+            self.logger.log(
+                f"❌ Crew '{event.crew_name}' failed train",
+                event.timestamp,
+            )
+
+        # ----------- TASK EVENTS -----------
+
+        @crewai_event_bus.on(TaskStartedEvent)
+        def on_task_started(source, event: TaskStartedEvent):
+            span = self._telemetry.task_started(crew=source.agent.crew, task=source)
+            self.execution_spans[source] = span
+
+            self.logger.log(
+                f"📋 Task started: {source.description}",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(TaskCompletedEvent)
+        def on_task_completed(source, event: TaskCompletedEvent):
+            span = self.execution_spans.get(source)
+            if span:
+                self._telemetry.task_ended(span, source, source.agent.crew)
+            self.logger.log(
+                f"✅ Task completed: {source.description}",
+                event.timestamp,
+            )
+            self.execution_spans[source] = None
+
+        @crewai_event_bus.on(TaskFailedEvent)
+        def on_task_failed(source, event: TaskFailedEvent):
+            span = self.execution_spans.get(source)
+            if span:
+                if source.agent and source.agent.crew:
+                    self._telemetry.task_ended(span, source, source.agent.crew)
+                self.execution_spans[source] = None
+            self.logger.log(
+                f"❌ Task failed: {source.description}",
+                event.timestamp,
+            )
+
+        # ----------- AGENT EVENTS -----------
+
+        @crewai_event_bus.on(AgentExecutionStartedEvent)
+        def on_agent_execution_started(source, event: AgentExecutionStartedEvent):
+            self.logger.log(
+                f"🤖 Agent '{event.agent.role}' started task",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(AgentExecutionCompletedEvent)
+        def on_agent_execution_completed(source, event: AgentExecutionCompletedEvent):
+            self.logger.log(
+                f"✅ Agent '{event.agent.role}' completed task",
+                event.timestamp,
+            )
+
+        # ----------- FLOW EVENTS -----------
+
+        @crewai_event_bus.on(FlowCreatedEvent)
+        def on_flow_created(source, event: FlowCreatedEvent):
+            self._telemetry.flow_creation_span(event.flow_name)
+            self.logger.log(
+                f"🌊 Flow Created: '{event.flow_name}'",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(FlowStartedEvent)
+        def on_flow_started(source, event: FlowStartedEvent):
+            self._telemetry.flow_execution_span(
+                event.flow_name, list(source._methods.keys())
+            )
+            self.logger.log(
+                f"🤖 Flow Started: '{event.flow_name}', {source.flow_id}",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(FlowFinishedEvent)
+        def on_flow_finished(source, event: FlowFinishedEvent):
+            self.logger.log(
+                f"👍 Flow Finished: '{event.flow_name}', {source.flow_id}",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(MethodExecutionStartedEvent)
+        def on_method_execution_started(source, event: MethodExecutionStartedEvent):
+            self.logger.log(
+                f"🤖 Flow Method Started: '{event.method_name}'",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(MethodExecutionFailedEvent)
+        def on_method_execution_failed(source, event: MethodExecutionFailedEvent):
+            self.logger.log(
+                f"❌ Flow Method Failed: '{event.method_name}'",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(MethodExecutionFinishedEvent)
+        def on_method_execution_finished(source, event: MethodExecutionFinishedEvent):
+            self.logger.log(
+                f"👍 Flow Method Finished: '{event.method_name}'",
+                event.timestamp,
+            )
+
+        # ----------- TOOL USAGE EVENTS -----------
+
+        @crewai_event_bus.on(ToolUsageStartedEvent)
+        def on_tool_usage_started(source, event: ToolUsageStartedEvent):
+            self.logger.log(
+                f"🤖 Tool Usage Started: '{event.tool_name}'",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(ToolUsageFinishedEvent)
+        def on_tool_usage_finished(source, event: ToolUsageFinishedEvent):
+            self.logger.log(
+                f"✅ Tool Usage Finished: '{event.tool_name}'",
+                event.timestamp,
+                #
+            )
+
+        @crewai_event_bus.on(ToolUsageErrorEvent)
+        def on_tool_usage_error(source, event: ToolUsageErrorEvent):
+            self.logger.log(
+                f"❌ Tool Usage Error: '{event.tool_name}'",
+                event.timestamp,
+                #
+            )
+
+        # ----------- LLM EVENTS -----------
+
+        @crewai_event_bus.on(LLMCallStartedEvent)
+        def on_llm_call_started(source, event: LLMCallStartedEvent):
+            self.logger.log(
+                f"🤖 LLM Call Started",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(LLMCallCompletedEvent)
+        def on_llm_call_completed(source, event: LLMCallCompletedEvent):
+            self.logger.log(
+                f"✅ LLM Call Completed",
+                event.timestamp,
+            )
+
+        @crewai_event_bus.on(LLMCallFailedEvent)
+        def on_llm_call_failed(source, event: LLMCallFailedEvent):
+            self.logger.log(
+                f"❌ LLM Call Failed: '{event.error}'",
+                event.timestamp,
+            )
+
+
+event_listener = EventListener()

src/crewai/utilities/events/event_types.py

@@ -0,0 +1,61 @@
+from typing import Union
+
+from .agent_events import (
+    AgentExecutionCompletedEvent,
+    AgentExecutionErrorEvent,
+    AgentExecutionStartedEvent,
+)
+from .crew_events import (
+    CrewKickoffCompletedEvent,
+    CrewKickoffFailedEvent,
+    CrewKickoffStartedEvent,
+    CrewTestCompletedEvent,
+    CrewTestFailedEvent,
+    CrewTestStartedEvent,
+    CrewTrainCompletedEvent,
+    CrewTrainFailedEvent,
+    CrewTrainStartedEvent,
+)
+from .flow_events import (
+    FlowFinishedEvent,
+    FlowStartedEvent,
+    MethodExecutionFailedEvent,
+    MethodExecutionFinishedEvent,
+    MethodExecutionStartedEvent,
+)
+from .task_events import (
+    TaskCompletedEvent,
+    TaskFailedEvent,
+    TaskStartedEvent,
+)
+from .tool_usage_events import (
+    ToolUsageErrorEvent,
+    ToolUsageFinishedEvent,
+    ToolUsageStartedEvent,
+)
+
+EventTypes = Union[
+    CrewKickoffStartedEvent,
+    CrewKickoffCompletedEvent,
+    CrewKickoffFailedEvent,
+    CrewTestStartedEvent,
+    CrewTestCompletedEvent,
+    CrewTestFailedEvent,
+    CrewTrainStartedEvent,
+    CrewTrainCompletedEvent,
+    CrewTrainFailedEvent,
+    AgentExecutionStartedEvent,
+    AgentExecutionCompletedEvent,
+    TaskStartedEvent,
+    TaskCompletedEvent,
+    TaskFailedEvent,
+    FlowStartedEvent,
+    FlowFinishedEvent,
+    MethodExecutionStartedEvent,
+    MethodExecutionFinishedEvent,
+    MethodExecutionFailedEvent,
+    AgentExecutionErrorEvent,
+    ToolUsageFinishedEvent,
+    ToolUsageErrorEvent,
+    ToolUsageStartedEvent,
+]

src/crewai/utilities/events/flow_events.py

@@ -0,0 +1,71 @@
+from typing import Any, Dict, Optional, Union
+
+from pydantic import BaseModel
+
+from .base_events import CrewEvent
+
+
+class FlowEvent(CrewEvent):
+    """Base class for all flow events"""
+
+    type: str
+    flow_name: str
+
+
+class FlowStartedEvent(FlowEvent):
+    """Event emitted when a flow starts execution"""
+
+    flow_name: str
+    inputs: Optional[Dict[str, Any]] = None
+    type: str = "flow_started"
+
+
+class FlowCreatedEvent(FlowEvent):
+    """Event emitted when a flow is created"""
+
+    flow_name: str
+    type: str = "flow_created"
+
+
+class MethodExecutionStartedEvent(FlowEvent):
+    """Event emitted when a flow method starts execution"""
+
+    flow_name: str
+    method_name: str
+    state: Union[Dict[str, Any], BaseModel]
+    params: Optional[Dict[str, Any]] = None
+    type: str = "method_execution_started"
+
+
+class MethodExecutionFinishedEvent(FlowEvent):
+    """Event emitted when a flow method completes execution"""
+
+    flow_name: str
+    method_name: str
+    result: Any = None
+    state: Union[Dict[str, Any], BaseModel]
+    type: str = "method_execution_finished"
+
+
+class MethodExecutionFailedEvent(FlowEvent):
+    """Event emitted when a flow method fails execution"""
+
+    flow_name: str
+    method_name: str
+    error: Any
+    type: str = "method_execution_failed"
+
+
+class FlowFinishedEvent(FlowEvent):
+    """Event emitted when a flow completes execution"""
+
+    flow_name: str
+    result: Optional[Any] = None
+    type: str = "flow_finished"
+
+
+class FlowPlotEvent(FlowEvent):
+    """Event emitted when a flow plot is created"""
+
+    flow_name: str
+    type: str = "flow_plot"

src/crewai/utilities/events/llm_events.py

@@ -0,0 +1,36 @@
+from enum import Enum
+from typing import Any, Dict, List, Optional, Union
+
+from crewai.utilities.events.base_events import CrewEvent
+
+
+class LLMCallType(Enum):
+    """Type of LLM call being made"""
+
+    TOOL_CALL = "tool_call"
+    LLM_CALL = "llm_call"
+
+
+class LLMCallStartedEvent(CrewEvent):
+    """Event emitted when a LLM call starts"""
+
+    type: str = "llm_call_started"
+    messages: Union[str, List[Dict[str, str]]]
+    tools: Optional[List[dict]] = None
+    callbacks: Optional[List[Any]] = None
+    available_functions: Optional[Dict[str, Any]] = None
+
+
+class LLMCallCompletedEvent(CrewEvent):
+    """Event emitted when a LLM call completes"""
+
+    type: str = "llm_call_completed"
+    response: Any
+    call_type: LLMCallType
+
+
+class LLMCallFailedEvent(CrewEvent):
+    """Event emitted when a LLM call fails"""
+
+    error: str
+    type: str = "llm_call_failed"

src/crewai/utilities/events/task_events.py

@@ -0,0 +1,32 @@
+from typing import Optional
+
+from crewai.tasks.task_output import TaskOutput
+from crewai.utilities.events.base_events import CrewEvent
+
+
+class TaskStartedEvent(CrewEvent):
+    """Event emitted when a task starts"""
+
+    type: str = "task_started"
+    context: Optional[str]
+
+
+class TaskCompletedEvent(CrewEvent):
+    """Event emitted when a task completes"""
+
+    output: TaskOutput
+    type: str = "task_completed"
+
+
+class TaskFailedEvent(CrewEvent):
+    """Event emitted when a task fails"""
+
+    error: str
+    type: str = "task_failed"
+
+
+class TaskEvaluationEvent(CrewEvent):
+    """Event emitted when a task evaluation is completed"""
+
+    type: str = "task_evaluation"
+    evaluation_type: str

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

@@ -0,0 +1 @@
+from .agentops_listener import agentops_listener

src/crewai/utilities/events/third_party/agentops_listener.py

@@ -0,0 +1,67 @@
+from typing import Optional
+
+from crewai.utilities.events import (
+    CrewKickoffCompletedEvent,
+    ToolUsageErrorEvent,
+    ToolUsageStartedEvent,
+)
+from crewai.utilities.events.base_event_listener import BaseEventListener
+from crewai.utilities.events.crew_events import CrewKickoffStartedEvent
+from crewai.utilities.events.task_events import TaskEvaluationEvent
+
+try:
+    import agentops
+
+    AGENTOPS_INSTALLED = True
+except ImportError:
+    AGENTOPS_INSTALLED = False
+
+
+class AgentOpsListener(BaseEventListener):
+    tool_event: Optional["agentops.ToolEvent"] = None
+    session: Optional["agentops.Session"] = None
+
+    def __init__(self):
+        super().__init__()
+
+    def setup_listeners(self, crewai_event_bus):
+        if not AGENTOPS_INSTALLED:
+            return
+
+        @crewai_event_bus.on(CrewKickoffStartedEvent)
+        def on_crew_kickoff_started(source, event: CrewKickoffStartedEvent):
+            self.session = agentops.init()
+            for agent in source.agents:
+                if self.session:
+                    self.session.create_agent(
+                        name=agent.role,
+                        agent_id=str(agent.id),
+                    )
+
+        @crewai_event_bus.on(CrewKickoffCompletedEvent)
+        def on_crew_kickoff_completed(source, event: CrewKickoffCompletedEvent):
+            if self.session:
+                self.session.end_session(
+                    end_state="Success",
+                    end_state_reason="Finished Execution",
+                )
+
+        @crewai_event_bus.on(ToolUsageStartedEvent)
+        def on_tool_usage_started(source, event: ToolUsageStartedEvent):
+            self.tool_event = agentops.ToolEvent(name=event.tool_name)
+            if self.session:
+                self.session.record(self.tool_event)
+
+        @crewai_event_bus.on(ToolUsageErrorEvent)
+        def on_tool_usage_error(source, event: ToolUsageErrorEvent):
+            agentops.ErrorEvent(exception=event.error, trigger_event=self.tool_event)
+
+        @crewai_event_bus.on(TaskEvaluationEvent)
+        def on_task_evaluation(source, event: TaskEvaluationEvent):
+            if self.session:
+                self.session.create_agent(
+                    name="Task Evaluator", agent_id=str(source.original_agent.id)
+                )
+
+
+agentops_listener = AgentOpsListener()

src/crewai/utilities/events/tool_usage_events.py

@@ -0,0 +1,64 @@
+from datetime import datetime
+from typing import Any, Callable, Dict
+
+from .base_events import CrewEvent
+
+
+class ToolUsageEvent(CrewEvent):
+    """Base event for tool usage tracking"""
+
+    agent_key: str
+    agent_role: str
+    tool_name: str
+    tool_args: Dict[str, Any] | str
+    tool_class: str
+    run_attempts: int | None = None
+    delegations: int | None = None
+
+    model_config = {"arbitrary_types_allowed": True}
+
+
+class ToolUsageStartedEvent(ToolUsageEvent):
+    """Event emitted when a tool execution is started"""
+
+    type: str = "tool_usage_started"
+
+
+class ToolUsageFinishedEvent(ToolUsageEvent):
+    """Event emitted when a tool execution is completed"""
+
+    started_at: datetime
+    finished_at: datetime
+    from_cache: bool = False
+    type: str = "tool_usage_finished"
+
+
+class ToolUsageErrorEvent(ToolUsageEvent):
+    """Event emitted when a tool execution encounters an error"""
+
+    error: Any
+    type: str = "tool_usage_error"
+
+
+class ToolValidateInputErrorEvent(ToolUsageEvent):
+    """Event emitted when a tool input validation encounters an error"""
+
+    error: Any
+    type: str = "tool_validate_input_error"
+
+
+class ToolSelectionErrorEvent(ToolUsageEvent):
+    """Event emitted when a tool selection encounters an error"""
+
+    error: Any
+    type: str = "tool_selection_error"
+
+
+class ToolExecutionErrorEvent(CrewEvent):
+    """Event emitted when a tool execution encounters an error"""
+
+    error: Any
+    type: str = "tool_execution_error"
+    tool_name: str
+    tool_args: Dict[str, Any]
+    tool_class: Callable

src/crewai/utilities/llm_utils.py

@@ -44,6 +44,7 @@ def create_llm(
         # Extract attributes with explicit types
         model = (
             getattr(llm_value, "model_name", None)
+            or getattr(llm_value, "model", None)
             or getattr(llm_value, "deployment_name", None)
             or str(llm_value)
         )

src/crewai/utilities/logger.py

@@ -8,8 +8,11 @@ from crewai.utilities.printer import Printer
 class Logger(BaseModel):
     verbose: bool = Field(default=False)
     _printer: Printer = PrivateAttr(default_factory=Printer)
+    default_color: str = Field(default="bold_yellow")
 
-    def log(self, level, message, color="bold_yellow"):
+    def log(self, level, message, color=None):
+        if color is None:
+            color = self.default_color
         if self.verbose:
             timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
             self._printer.print(

src/crewai/utilities/token_counter_callback.py

@@ -30,8 +30,14 @@ class TokenCalcHandler(CustomLogger):
                     if hasattr(usage, "prompt_tokens"):
                         self.token_cost_process.sum_prompt_tokens(usage.prompt_tokens)
                     if hasattr(usage, "completion_tokens"):
-                        self.token_cost_process.sum_completion_tokens(usage.completion_tokens)
-                    if hasattr(usage, "prompt_tokens_details") and usage.prompt_tokens_details:
+                        self.token_cost_process.sum_completion_tokens(
+                            usage.completion_tokens
+                        )
+                    if (
+                        hasattr(usage, "prompt_tokens_details")
+                        and usage.prompt_tokens_details
+                        and usage.prompt_tokens_details.cached_tokens
+                    ):
                         self.token_cost_process.sum_cached_prompt_tokens(
                             usage.prompt_tokens_details.cached_tokens
                         )

tests/agent_test.py

@@ -8,7 +8,7 @@ import pytest
 
 from crewai import Agent, Crew, Task
 from crewai.agents.cache import CacheHandler
-from crewai.agents.crew_agent_executor import CrewAgentExecutor
+from crewai.agents.crew_agent_executor import AgentFinish, CrewAgentExecutor
 from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException
 from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
 from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
@@ -16,9 +16,9 @@ from crewai.llm import LLM
 from crewai.tools import tool
 from crewai.tools.tool_calling import InstructorToolCalling
 from crewai.tools.tool_usage import ToolUsage
-from crewai.tools.tool_usage_events import ToolUsageFinished
 from crewai.utilities import RPMController
-from crewai.utilities.events import Emitter
+from crewai.utilities.events import crewai_event_bus
+from crewai.utilities.events.tool_usage_events import ToolUsageFinishedEvent
 
 
 def test_agent_llm_creation_with_env_vars():
@@ -154,15 +154,19 @@ def test_agent_execution_with_tools():
         agent=agent,
         expected_output="The result of the multiplication.",
     )
-    with patch.object(Emitter, "emit") as emit:
-        output = agent.execute_task(task)
-        assert output == "The result of the multiplication is 12."
-        assert emit.call_count == 1
-        args, _ = emit.call_args
-        assert isinstance(args[1], ToolUsageFinished)
-        assert not args[1].from_cache
-        assert args[1].tool_name == "multiplier"
-        assert args[1].tool_args == {"first_number": 3, "second_number": 4}
+    received_events = []
+
+    @crewai_event_bus.on(ToolUsageFinishedEvent)
+    def handle_tool_end(source, event):
+        received_events.append(event)
+
+    output = agent.execute_task(task)
+    assert output == "The result of the multiplication is 12."
+
+    assert len(received_events) == 1
+    assert isinstance(received_events[0], ToolUsageFinishedEvent)
+    assert received_events[0].tool_name == "multiplier"
+    assert received_events[0].tool_args == {"first_number": 3, "second_number": 4}
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -249,10 +253,14 @@ def test_cache_hitting():
         "multiplier-{'first_number': 3, 'second_number': 3}": 9,
         "multiplier-{'first_number': 12, 'second_number': 3}": 36,
     }
+    received_events = []
+
+    @crewai_event_bus.on(ToolUsageFinishedEvent)
+    def handle_tool_end(source, event):
+        received_events.append(event)
 
     with (
         patch.object(CacheHandler, "read") as read,
-        patch.object(Emitter, "emit") as emit,
     ):
         read.return_value = "0"
         task = Task(
@@ -265,10 +273,9 @@ def test_cache_hitting():
         read.assert_called_with(
             tool="multiplier", input={"first_number": 2, "second_number": 6}
         )
-        assert emit.call_count == 1
-        args, _ = emit.call_args
-        assert isinstance(args[1], ToolUsageFinished)
-        assert args[1].from_cache
+        assert len(received_events) == 1
+        assert isinstance(received_events[0], ToolUsageFinishedEvent)
+        assert received_events[0].from_cache
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -983,23 +990,35 @@ def test_agent_human_input():
     # Side effect function for _ask_human_input to simulate multiple feedback iterations
     feedback_responses = iter(
         [
-            "Don't say hi, say Hello instead!",  # First feedback
-            "looks good",  # Second feedback to exit loop
+            "Don't say hi, say Hello instead!",  # First feedback: instruct change
+            "",  # Second feedback: empty string signals acceptance
         ]
     )
 
     def ask_human_input_side_effect(*args, **kwargs):
         return next(feedback_responses)
 
-    with patch.object(
-        CrewAgentExecutor, "_ask_human_input", side_effect=ask_human_input_side_effect
-    ) as mock_human_input:
+    # Patch both _ask_human_input and _invoke_loop to avoid real API/network calls.
+    with (
+        patch.object(
+            CrewAgentExecutor,
+            "_ask_human_input",
+            side_effect=ask_human_input_side_effect,
+        ) as mock_human_input,
+        patch.object(
+            CrewAgentExecutor,
+            "_invoke_loop",
+            return_value=AgentFinish(output="Hello", thought="", text=""),
+        ) as mock_invoke_loop,
+    ):
         # Execute the task
         output = agent.execute_task(task)
 
-        # Assertions to ensure the agent behaves correctly
-        assert mock_human_input.call_count == 2  # Should have asked for feedback twice
-        assert output.strip().lower() == "hello"  # Final output should be 'Hello'
+        # Assertions to ensure the agent behaves correctly.
+        # It should have requested feedback twice.
+        assert mock_human_input.call_count == 2
+        # The final result should be processed to "Hello"
+        assert output.strip().lower() == "hello"
 
 
 def test_interpolate_inputs():

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tests/crew_test.py

@@ -6,7 +6,6 @@ from concurrent.futures import Future
 from unittest import mock
 from unittest.mock import MagicMock, patch
 
-import instructor
 import pydantic_core
 import pytest
 
@@ -18,13 +17,21 @@ from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSourc
 from crewai.llm import LLM
 from crewai.memory.contextual.contextual_memory import ContextualMemory
 from crewai.process import Process
-from crewai.project import crew
 from crewai.task import Task
 from crewai.tasks.conditional_task import ConditionalTask
 from crewai.tasks.output_format import OutputFormat
 from crewai.tasks.task_output import TaskOutput
 from crewai.types.usage_metrics import UsageMetrics
 from crewai.utilities import Logger
+from crewai.utilities.events import (
+    CrewTrainCompletedEvent,
+    CrewTrainStartedEvent,
+    crewai_event_bus,
+)
+from crewai.utilities.events.crew_events import (
+    CrewTestCompletedEvent,
+    CrewTestStartedEvent,
+)
 from crewai.utilities.rpm_controller import RPMController
 from crewai.utilities.task_output_storage_handler import TaskOutputStorageHandler
 
@@ -826,6 +833,12 @@ def test_crew_verbose_output(capsys):
 
     crew.kickoff()
     captured = capsys.readouterr()
+
+    # Filter out event listener logs (lines starting with '[')
+    filtered_output = "\n".join(
+        line for line in captured.out.split("\n") if not line.startswith("[")
+    )
+
     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.",
@@ -838,14 +851,19 @@ def test_crew_verbose_output(capsys):
     ]
 
     for expected_string in expected_strings:
-        assert expected_string in captured.out
+        assert expected_string in filtered_output
 
     # Now test with verbose set to False
     crew.verbose = False
     crew._logger = Logger(verbose=False)
     crew.kickoff()
     captured = capsys.readouterr()
-    assert captured.out == ""
+    filtered_output = "\n".join(
+        line
+        for line in captured.out.split("\n")
+        if not line.startswith("[") and line.strip() and not line.startswith("\x1b")
+    )
+    assert filtered_output == ""
 
 
 @pytest.mark.vcr(filter_headers=["authorization"])
@@ -1283,9 +1301,9 @@ def test_kickoff_for_each_invalid_input():
 
     crew = Crew(agents=[agent], tasks=[task])
 
-    with pytest.raises(TypeError):
+    with pytest.raises(pydantic_core._pydantic_core.ValidationError):
         # Pass a string instead of a list
-        crew.kickoff_for_each("invalid input")
+        crew.kickoff_for_each(["invalid input"])
 
 
 def test_kickoff_for_each_error_handling():
@@ -2569,6 +2587,16 @@ def test_crew_train_success(
     # Create a mock for the copied crew
     copy_mock.return_value = crew
 
+    received_events = []
+
+    @crewai_event_bus.on(CrewTrainStartedEvent)
+    def on_crew_train_started(source, event: CrewTrainStartedEvent):
+        received_events.append(event)
+
+    @crewai_event_bus.on(CrewTrainCompletedEvent)
+    def on_crew_train_completed(source, event: CrewTrainCompletedEvent):
+        received_events.append(event)
+
     crew.train(
         n_iterations=2, inputs={"topic": "AI"}, filename="trained_agents_data.pkl"
     )
@@ -2614,6 +2642,10 @@ def test_crew_train_success(
         ]
     )
 
+    assert len(received_events) == 2
+    assert isinstance(received_events[0], CrewTrainStartedEvent)
+    assert isinstance(received_events[1], CrewTrainCompletedEvent)
+
 
 def test_crew_train_error():
     task = Task(
@@ -3342,7 +3374,18 @@ def test_crew_testing_function(kickoff_mock, copy_mock, crew_evaluator):
     copy_mock.return_value = crew
 
     n_iterations = 2
-    llm_instance = LLM('gpt-4o-mini')
+    llm_instance = LLM("gpt-4o-mini")
+
+    received_events = []
+
+    @crewai_event_bus.on(CrewTestStartedEvent)
+    def on_crew_test_started(source, event: CrewTestStartedEvent):
+        received_events.append(event)
+
+    @crewai_event_bus.on(CrewTestCompletedEvent)
+    def on_crew_test_completed(source, event: CrewTestCompletedEvent):
+        received_events.append(event)
+
     crew.test(n_iterations, llm_instance, inputs={"topic": "AI"})
 
     # Ensure kickoff is called on the copied crew
@@ -3352,13 +3395,17 @@ def test_crew_testing_function(kickoff_mock, copy_mock, crew_evaluator):
 
     crew_evaluator.assert_has_calls(
         [
-            mock.call(crew,llm_instance),
+            mock.call(crew, llm_instance),
             mock.call().set_iteration(1),
             mock.call().set_iteration(2),
             mock.call().print_crew_evaluation_result(),
         ]
     )
 
+    assert len(received_events) == 2
+    assert isinstance(received_events[0], CrewTestStartedEvent)
+    assert isinstance(received_events[1], CrewTestCompletedEvent)
+
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_hierarchical_verbose_manager_agent():

tests/flow/test_state_utils.py

@@ -6,7 +6,7 @@ import pytest
 from pydantic import BaseModel
 
 from crewai.flow import Flow
-from crewai.flow.state_utils import export_state
+from crewai.flow.state_utils import export_state, to_string
 
 
 class Address(BaseModel):
@@ -119,16 +119,10 @@ def test_pydantic_model_serialization(mock_flow):
     )
 
     result = export_state(flow)
-
-    assert result["single_model"]["street"] == "123 Main St"
-
-    assert result["nested_model"]["name"] == "John Doe"
-    assert result["nested_model"]["address"]["city"] == "Tech City"
-    assert result["nested_model"]["birthday"] == "1994-01-01"
-
-    assert len(result["model_list"]) == 2
-    assert all(m["street"] == "123 Main St" for m in result["model_list"])
-    assert result["model_dict"]["home"]["city"] == "Tech City"
+    assert (
+        to_string(result)
+        == '{"single_model": {"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}, "nested_model": {"name": "John Doe", "age": 30, "address": {"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}, "birthday": "1994-01-01", "skills": ["Python", "Testing"]}, "model_list": [{"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}, {"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}], "model_dict": {"home": {"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}}}'
+    )
 
 
 def test_depth_limit(mock_flow):

tests/flow_test.py

@@ -7,12 +7,14 @@ import pytest
 from pydantic import BaseModel
 
 from crewai.flow.flow import Flow, and_, listen, or_, router, start
-from crewai.flow.flow_events import (
+from crewai.utilities.events import (
     FlowFinishedEvent,
     FlowStartedEvent,
     MethodExecutionFinishedEvent,
     MethodExecutionStartedEvent,
+    crewai_event_bus,
 )
+from crewai.utilities.events.flow_events import FlowPlotEvent
 
 
 def test_simple_sequential_flow():
@@ -434,90 +436,65 @@ def test_unstructured_flow_event_emission():
         @listen(finish_poem)
         def save_poem_to_database(self):
             # A method without args/kwargs to ensure events are sent correctly
-            pass
-
-    event_log = []
-
-    def handle_event(_, event):
-        event_log.append(event)
+            return "roses are red\nviolets are blue"
 
     flow = PoemFlow()
-    flow.event_emitter.connect(handle_event)
+    received_events = []
+
+    @crewai_event_bus.on(FlowStartedEvent)
+    def handle_flow_start(source, event):
+        received_events.append(event)
+
+    @crewai_event_bus.on(MethodExecutionStartedEvent)
+    def handle_method_start(source, event):
+        received_events.append(event)
+
+    @crewai_event_bus.on(FlowFinishedEvent)
+    def handle_flow_end(source, event):
+        received_events.append(event)
+
     flow.kickoff(inputs={"separator": ", "})
+    assert isinstance(received_events[0], FlowStartedEvent)
+    assert received_events[0].flow_name == "PoemFlow"
+    assert received_events[0].inputs == {"separator": ", "}
+    assert isinstance(received_events[0].timestamp, datetime)
 
-    assert isinstance(event_log[0], FlowStartedEvent)
-    assert event_log[0].flow_name == "PoemFlow"
-    assert event_log[0].inputs == {"separator": ", "}
-    assert isinstance(event_log[0].timestamp, datetime)
-
-    # Asserting for concurrent start method executions in a for loop as you
-    # can't guarantee ordering in asynchronous executions
-    for i in range(1, 5):
-        event = event_log[i]
+    # All subsequent events are MethodExecutionStartedEvent
+    for event in received_events[1:-1]:
+        assert isinstance(event, MethodExecutionStartedEvent)
+        assert event.flow_name == "PoemFlow"
         assert isinstance(event.state, dict)
         assert isinstance(event.state["id"], str)
+        assert event.state["separator"] == ", "
 
-        if event.method_name == "prepare_flower":
-            if isinstance(event, MethodExecutionStartedEvent):
-                assert event.params == {}
-                assert event.state["separator"] == ", "
-            elif isinstance(event, MethodExecutionFinishedEvent):
-                assert event.result == "foo"
-                assert event.state["flower"] == "roses"
-                assert event.state["separator"] == ", "
-            else:
-                assert False, "Unexpected event type for prepare_flower"
-        elif event.method_name == "prepare_color":
-            if isinstance(event, MethodExecutionStartedEvent):
-                assert event.params == {}
-                assert event.state["separator"] == ", "
-            elif isinstance(event, MethodExecutionFinishedEvent):
-                assert event.result == "bar"
-                assert event.state["color"] == "red"
-                assert event.state["separator"] == ", "
-            else:
-                assert False, "Unexpected event type for prepare_color"
-        else:
-            assert False, f"Unexpected method {event.method_name} in prepare events"
+    assert received_events[1].method_name == "prepare_flower"
+    assert received_events[1].params == {}
+    assert "flower" not in received_events[1].state
 
-    assert isinstance(event_log[5], MethodExecutionStartedEvent)
-    assert event_log[5].method_name == "write_first_sentence"
-    assert event_log[5].params == {}
-    assert isinstance(event_log[5].state, dict)
-    assert event_log[5].state["flower"] == "roses"
-    assert event_log[5].state["color"] == "red"
-    assert event_log[5].state["separator"] == ", "
+    assert received_events[2].method_name == "prepare_color"
+    assert received_events[2].params == {}
+    print("received_events[2]", received_events[2])
+    assert "flower" in received_events[2].state
 
-    assert isinstance(event_log[6], MethodExecutionFinishedEvent)
-    assert event_log[6].method_name == "write_first_sentence"
-    assert event_log[6].result == "roses are red"
+    assert received_events[3].method_name == "write_first_sentence"
+    assert received_events[3].params == {}
+    assert received_events[3].state["flower"] == "roses"
+    assert received_events[3].state["color"] == "red"
 
-    assert isinstance(event_log[7], MethodExecutionStartedEvent)
-    assert event_log[7].method_name == "finish_poem"
-    assert event_log[7].params == {"_0": "roses are red"}
-    assert isinstance(event_log[7].state, dict)
-    assert event_log[7].state["flower"] == "roses"
-    assert event_log[7].state["color"] == "red"
+    assert received_events[4].method_name == "finish_poem"
+    assert received_events[4].params == {"_0": "roses are red"}
+    assert received_events[4].state["flower"] == "roses"
+    assert received_events[4].state["color"] == "red"
 
-    assert isinstance(event_log[8], MethodExecutionFinishedEvent)
-    assert event_log[8].method_name == "finish_poem"
-    assert event_log[8].result == "roses are red, violets are blue"
+    assert received_events[5].method_name == "save_poem_to_database"
+    assert received_events[5].params == {}
+    assert received_events[5].state["flower"] == "roses"
+    assert received_events[5].state["color"] == "red"
 
-    assert isinstance(event_log[9], MethodExecutionStartedEvent)
-    assert event_log[9].method_name == "save_poem_to_database"
-    assert event_log[9].params == {}
-    assert isinstance(event_log[9].state, dict)
-    assert event_log[9].state["flower"] == "roses"
-    assert event_log[9].state["color"] == "red"
-
-    assert isinstance(event_log[10], MethodExecutionFinishedEvent)
-    assert event_log[10].method_name == "save_poem_to_database"
-    assert event_log[10].result is None
-
-    assert isinstance(event_log[11], FlowFinishedEvent)
-    assert event_log[11].flow_name == "PoemFlow"
-    assert event_log[11].result is None
-    assert isinstance(event_log[11].timestamp, datetime)
+    assert isinstance(received_events[6], FlowFinishedEvent)
+    assert received_events[6].flow_name == "PoemFlow"
+    assert received_events[6].result == "roses are red\nviolets are blue"
+    assert isinstance(received_events[6].timestamp, datetime)
 
 
 def test_structured_flow_event_emission():
@@ -538,40 +515,54 @@ def test_structured_flow_event_emission():
             self.state.sent = True
             return f"Welcome, {self.state.name}!"
 
-    event_log = []
-
-    def handle_event(_, event):
-        event_log.append(event)
-
     flow = OnboardingFlow()
-    flow.event_emitter.connect(handle_event)
     flow.kickoff(inputs={"name": "Anakin"})
 
-    assert isinstance(event_log[0], FlowStartedEvent)
-    assert event_log[0].flow_name == "OnboardingFlow"
-    assert event_log[0].inputs == {"name": "Anakin"}
-    assert isinstance(event_log[0].timestamp, datetime)
+    received_events = []
 
-    assert isinstance(event_log[1], MethodExecutionStartedEvent)
-    assert event_log[1].method_name == "user_signs_up"
+    @crewai_event_bus.on(FlowStartedEvent)
+    def handle_flow_start(source, event):
+        received_events.append(event)
 
-    assert isinstance(event_log[2], MethodExecutionFinishedEvent)
-    assert event_log[2].method_name == "user_signs_up"
+    @crewai_event_bus.on(MethodExecutionStartedEvent)
+    def handle_method_start(source, event):
+        received_events.append(event)
 
-    assert isinstance(event_log[3], MethodExecutionStartedEvent)
-    assert event_log[3].method_name == "send_welcome_message"
-    assert event_log[3].params == {}
-    assert getattr(event_log[3].state, "sent") is False
+    @crewai_event_bus.on(MethodExecutionFinishedEvent)
+    def handle_method_end(source, event):
+        received_events.append(event)
 
-    assert isinstance(event_log[4], MethodExecutionFinishedEvent)
-    assert event_log[4].method_name == "send_welcome_message"
-    assert getattr(event_log[4].state, "sent") is True
-    assert event_log[4].result == "Welcome, Anakin!"
+    @crewai_event_bus.on(FlowFinishedEvent)
+    def handle_flow_end(source, event):
+        received_events.append(event)
 
-    assert isinstance(event_log[5], FlowFinishedEvent)
-    assert event_log[5].flow_name == "OnboardingFlow"
-    assert event_log[5].result == "Welcome, Anakin!"
-    assert isinstance(event_log[5].timestamp, datetime)
+    flow.kickoff(inputs={"name": "Anakin"})
+
+    assert isinstance(received_events[0], FlowStartedEvent)
+    assert received_events[0].flow_name == "OnboardingFlow"
+    assert received_events[0].inputs == {"name": "Anakin"}
+    assert isinstance(received_events[0].timestamp, datetime)
+
+    assert isinstance(received_events[1], MethodExecutionStartedEvent)
+    assert received_events[1].method_name == "user_signs_up"
+
+    assert isinstance(received_events[2], MethodExecutionFinishedEvent)
+    assert received_events[2].method_name == "user_signs_up"
+
+    assert isinstance(received_events[3], MethodExecutionStartedEvent)
+    assert received_events[3].method_name == "send_welcome_message"
+    assert received_events[3].params == {}
+    assert getattr(received_events[3].state, "sent") is False
+
+    assert isinstance(received_events[4], MethodExecutionFinishedEvent)
+    assert received_events[4].method_name == "send_welcome_message"
+    assert getattr(received_events[4].state, "sent") is True
+    assert received_events[4].result == "Welcome, Anakin!"
+
+    assert isinstance(received_events[5], FlowFinishedEvent)
+    assert received_events[5].flow_name == "OnboardingFlow"
+    assert received_events[5].result == "Welcome, Anakin!"
+    assert isinstance(received_events[5].timestamp, datetime)
 
 
 def test_stateless_flow_event_emission():
@@ -593,30 +584,73 @@ def test_stateless_flow_event_emission():
         event_log.append(event)
 
     flow = StatelessFlow()
-    flow.event_emitter.connect(handle_event)
+    received_events = []
+
+    @crewai_event_bus.on(FlowStartedEvent)
+    def handle_flow_start(source, event):
+        received_events.append(event)
+
+    @crewai_event_bus.on(MethodExecutionStartedEvent)
+    def handle_method_start(source, event):
+        received_events.append(event)
+
+    @crewai_event_bus.on(MethodExecutionFinishedEvent)
+    def handle_method_end(source, event):
+        received_events.append(event)
+
+    @crewai_event_bus.on(FlowFinishedEvent)
+    def handle_flow_end(source, event):
+        received_events.append(event)
+
     flow.kickoff()
 
-    assert isinstance(event_log[0], FlowStartedEvent)
-    assert event_log[0].flow_name == "StatelessFlow"
-    assert event_log[0].inputs is None
-    assert isinstance(event_log[0].timestamp, datetime)
+    assert isinstance(received_events[0], FlowStartedEvent)
+    assert received_events[0].flow_name == "StatelessFlow"
+    assert received_events[0].inputs is None
+    assert isinstance(received_events[0].timestamp, datetime)
 
-    assert isinstance(event_log[1], MethodExecutionStartedEvent)
-    assert event_log[1].method_name == "init"
+    assert isinstance(received_events[1], MethodExecutionStartedEvent)
+    assert received_events[1].method_name == "init"
 
-    assert isinstance(event_log[2], MethodExecutionFinishedEvent)
-    assert event_log[2].method_name == "init"
+    assert isinstance(received_events[2], MethodExecutionFinishedEvent)
+    assert received_events[2].method_name == "init"
 
-    assert isinstance(event_log[3], MethodExecutionStartedEvent)
-    assert event_log[3].method_name == "process"
+    assert isinstance(received_events[3], MethodExecutionStartedEvent)
+    assert received_events[3].method_name == "process"
 
-    assert isinstance(event_log[4], MethodExecutionFinishedEvent)
-    assert event_log[4].method_name == "process"
+    assert isinstance(received_events[4], MethodExecutionFinishedEvent)
+    assert received_events[4].method_name == "process"
 
-    assert isinstance(event_log[5], FlowFinishedEvent)
-    assert event_log[5].flow_name == "StatelessFlow"
+    assert isinstance(received_events[5], FlowFinishedEvent)
+    assert received_events[5].flow_name == "StatelessFlow"
     assert (
-        event_log[5].result
+        received_events[5].result
         == "Deeds will not be less valiant because they are unpraised."
     )
-    assert isinstance(event_log[5].timestamp, datetime)
+    assert isinstance(received_events[5].timestamp, datetime)
+
+
+def test_flow_plotting():
+    class StatelessFlow(Flow):
+        @start()
+        def init(self):
+            return "Initializing flow..."
+
+        @listen(init)
+        def process(self):
+            return "Deeds will not be less valiant because they are unpraised."
+
+    flow = StatelessFlow()
+    flow.kickoff()
+    received_events = []
+
+    @crewai_event_bus.on(FlowPlotEvent)
+    def handle_flow_plot(source, event):
+        received_events.append(event)
+
+    flow.plot("test_flow")
+
+    assert len(received_events) == 1
+    assert isinstance(received_events[0], FlowPlotEvent)
+    assert received_events[0].flow_name == "StatelessFlow"
+    assert isinstance(received_events[0].timestamp, datetime)

tests/llm_test.py

@@ -6,8 +6,9 @@ import pytest
 from pydantic import BaseModel
 
 from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
-from crewai.llm import LLM
-from crewai.tools import tool
+from crewai.llm import CONTEXT_WINDOW_USAGE_RATIO, LLM
+from crewai.utilities.events import crewai_event_bus
+from crewai.utilities.events.tool_usage_events import ToolExecutionErrorEvent
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 
 
@@ -284,6 +285,23 @@ def test_o3_mini_reasoning_effort_medium():
     assert isinstance(result, str)
     assert "Paris" in result
 
+def test_context_window_validation():
+    """Test that context window validation works correctly."""
+    # Test valid window size
+    llm = LLM(model="o3-mini")
+    assert llm.get_context_window_size() == int(200000 * CONTEXT_WINDOW_USAGE_RATIO)
+
+    # Test invalid window size
+    with pytest.raises(ValueError) as excinfo:
+        with patch.dict(
+            "crewai.llm.LLM_CONTEXT_WINDOW_SIZES",
+            {"test-model": 500},  # Below minimum
+            clear=True,
+        ):
+            llm = LLM(model="test-model")
+            llm.get_context_window_size()
+    assert "must be between 1024 and 2097152" in str(excinfo.value)
+
 
 @pytest.mark.vcr(filter_headers=["authorization"])
 @pytest.fixture
@@ -291,32 +309,36 @@ def anthropic_llm():
     """Fixture providing an Anthropic LLM instance."""
     return LLM(model="anthropic/claude-3-sonnet")
 
+
 @pytest.fixture
 def system_message():
     """Fixture providing a system message."""
     return {"role": "system", "content": "test"}
 
+
 @pytest.fixture
 def user_message():
     """Fixture providing a user message."""
     return {"role": "user", "content": "test"}
 
+
 def test_anthropic_message_formatting_edge_cases(anthropic_llm):
     """Test edge cases for Anthropic message formatting."""
     # Test None messages
     with pytest.raises(TypeError, match="Messages cannot be None"):
         anthropic_llm._format_messages_for_provider(None)
-        
+
     # Test empty message list
     formatted = anthropic_llm._format_messages_for_provider([])
     assert len(formatted) == 1
     assert formatted[0]["role"] == "user"
     assert formatted[0]["content"] == "."
-    
+
     # Test invalid message format
     with pytest.raises(TypeError, match="Invalid message format"):
         anthropic_llm._format_messages_for_provider([{"invalid": "message"}])
 
+
 def test_anthropic_model_detection():
     """Test Anthropic model detection with various formats."""
     models = [
@@ -327,11 +349,12 @@ def test_anthropic_model_detection():
         ("", False),
         ("anthropomorphic", False),  # Should not match partial words
     ]
-    
+
     for model, expected in models:
         llm = LLM(model=model)
         assert llm.is_anthropic == expected, f"Failed for model: {model}"
 
+
 def test_anthropic_message_formatting(anthropic_llm, system_message, user_message):
     """Test Anthropic message formatting with fixtures."""
     # Test when first message is system
@@ -371,3 +394,51 @@ def test_deepseek_r1_with_open_router():
     result = llm.call("What is the capital of France?")
     assert isinstance(result, str)
     assert "Paris" in result
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_tool_execution_error_event():
+    llm = LLM(model="gpt-4o-mini")
+
+    def failing_tool(param: str) -> str:
+        """This tool always fails."""
+        raise Exception("Tool execution failed!")
+
+    tool_schema = {
+        "type": "function",
+        "function": {
+            "name": "failing_tool",
+            "description": "This tool always fails.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "param": {"type": "string", "description": "A test parameter"}
+                },
+                "required": ["param"],
+            },
+        },
+    }
+
+    received_events = []
+
+    @crewai_event_bus.on(ToolExecutionErrorEvent)
+    def event_handler(source, event):
+        received_events.append(event)
+
+    available_functions = {"failing_tool": failing_tool}
+
+    messages = [{"role": "user", "content": "Use the failing tool"}]
+
+    llm.call(
+        messages,
+        tools=[tool_schema],
+        available_functions=available_functions,
+    )
+
+    assert len(received_events) == 1
+    event = received_events[0]
+    assert isinstance(event, ToolExecutionErrorEvent)
+    assert event.tool_name == "failing_tool"
+    assert event.tool_args == {"param": "test"}
+    assert event.tool_class == failing_tool
+    assert "Tool execution failed!" in event.error

tests/test_flow_persistence.py

@@ -13,11 +13,12 @@ from crewai.flow.persistence.sqlite import SQLiteFlowPersistence
 
 class TestState(FlowState):
     """Test state model with required id field."""
+
     counter: int = 0
     message: str = ""
 
 
-def test_persist_decorator_saves_state(tmp_path):
+def test_persist_decorator_saves_state(tmp_path, caplog):
     """Test that @persist decorator saves state in SQLite."""
     db_path = os.path.join(tmp_path, "test_flows.db")
     persistence = SQLiteFlowPersistence(db_path)
@@ -73,7 +74,6 @@ def test_flow_state_restoration(tmp_path):
 
     # First flow execution to create initial state
     class RestorableFlow(Flow[TestState]):
-
         @start()
         @persist(persistence)
         def set_message(self):
@@ -89,10 +89,7 @@ def test_flow_state_restoration(tmp_path):
 
     # Test case 1: Restore using restore_uuid with field override
     flow2 = RestorableFlow(persistence=persistence)
-    flow2.kickoff(inputs={
-        "id": original_uuid,
-        "counter": 43
-    })
+    flow2.kickoff(inputs={"id": original_uuid, "counter": 43})
 
     # Verify state restoration and selective field override
     assert flow2.state.id == original_uuid
@@ -101,10 +98,7 @@ def test_flow_state_restoration(tmp_path):
 
     # Test case 2: Restore using kwargs['id']
     flow3 = RestorableFlow(persistence=persistence)
-    flow3.kickoff(inputs={
-        "id": original_uuid,
-        "message": "Updated message"
-    })
+    flow3.kickoff(inputs={"id": original_uuid, "message": "Updated message"})
 
     # Verify state restoration and selective field override
     assert flow3.state.id == original_uuid
@@ -174,3 +168,43 @@ def test_multiple_method_persistence(tmp_path):
     final_state = flow2.state
     assert final_state.counter == 99999
     assert final_state.message == "Step 99999"
+
+
+def test_persist_decorator_verbose_logging(tmp_path, caplog):
+    """Test that @persist decorator's verbose parameter controls logging."""
+    # Set logging level to ensure we capture all logs
+    caplog.set_level("INFO")
+
+    db_path = os.path.join(tmp_path, "test_flows.db")
+    persistence = SQLiteFlowPersistence(db_path)
+
+    # Test with verbose=False (default)
+    class QuietFlow(Flow[Dict[str, str]]):
+        initial_state = dict()
+
+        @start()
+        @persist(persistence)  # Default verbose=False
+        def init_step(self):
+            self.state["message"] = "Hello, World!"
+            self.state["id"] = "test-uuid-1"
+
+    flow = QuietFlow(persistence=persistence)
+    flow.kickoff()
+    assert "Saving flow state" not in caplog.text
+
+    # Clear the log
+    caplog.clear()
+
+    # Test with verbose=True
+    class VerboseFlow(Flow[Dict[str, str]]):
+        initial_state = dict()
+
+        @start()
+        @persist(persistence, verbose=True)
+        def init_step(self):
+            self.state["message"] = "Hello, World!"
+            self.state["id"] = "test-uuid-2"
+
+    flow = VerboseFlow(persistence=persistence)
+    flow.kickoff()
+    assert "Saving flow state" in caplog.text

tests/tools/test_tool_usage.py

@@ -1,6 +1,6 @@
 import json
 import random
-from unittest.mock import MagicMock
+from unittest.mock import MagicMock, patch
 
 import pytest
 from pydantic import BaseModel, Field
@@ -8,6 +8,11 @@ from pydantic import BaseModel, Field
 from crewai import Agent, Task
 from crewai.tools import BaseTool
 from crewai.tools.tool_usage import ToolUsage
+from crewai.utilities.events import crewai_event_bus
+from crewai.utilities.events.tool_usage_events import (
+    ToolSelectionErrorEvent,
+    ToolValidateInputErrorEvent,
+)
 
 
 class RandomNumberToolInput(BaseModel):
@@ -226,7 +231,7 @@ def test_validate_tool_input_with_special_characters():
     )
 
     # Input with special characters
-    tool_input = '{"message": "Hello, world! \u263A", "valid": True}'
+    tool_input = '{"message": "Hello, world! \u263a", "valid": True}'
     expected_arguments = {"message": "Hello, world! ☺", "valid": True}
 
     arguments = tool_usage._validate_tool_input(tool_input)
@@ -331,6 +336,19 @@ def test_validate_tool_input_with_trailing_commas():
 
 
 def test_validate_tool_input_invalid_input():
+    # Create mock agent with proper string values
+    mock_agent = MagicMock()
+    mock_agent.key = "test_agent_key"  # Must be a string
+    mock_agent.role = "test_agent_role"  # Must be a string
+    mock_agent._original_role = "test_agent_role"  # Must be a string
+    mock_agent.i18n = MagicMock()
+    mock_agent.verbose = False
+
+    # Create mock action with proper string value
+    mock_action = MagicMock()
+    mock_action.tool = "test_tool"  # Must be a string
+    mock_action.tool_input = "test_input"  # Must be a string
+
     tool_usage = ToolUsage(
         tools_handler=MagicMock(),
         tools=[],
@@ -339,8 +357,8 @@ def test_validate_tool_input_invalid_input():
         tools_names="",
         task=MagicMock(),
         function_calling_llm=None,
-        agent=MagicMock(),
-        action=MagicMock(),
+        agent=mock_agent,
+        action=mock_action,
     )
 
     invalid_inputs = [
@@ -360,7 +378,7 @@ def test_validate_tool_input_invalid_input():
 
     # Test for None input separately
     arguments = tool_usage._validate_tool_input(None)
-    assert arguments == {}  # Expecting an empty dictionary
+    assert arguments == {}
 
 
 def test_validate_tool_input_complex_structure():
@@ -468,18 +486,141 @@ def test_validate_tool_input_large_json_content():
     assert arguments == expected_arguments
 
 
-def test_validate_tool_input_none_input():
+def test_tool_selection_error_event_direct():
+    """Test tool selection error event emission directly from ToolUsage class."""
+    mock_agent = MagicMock()
+    mock_agent.key = "test_key"
+    mock_agent.role = "test_role"
+    mock_agent.i18n = MagicMock()
+    mock_agent.verbose = False
+
+    mock_task = MagicMock()
+    mock_tools_handler = MagicMock()
+
+    class TestTool(BaseTool):
+        name: str = "Test Tool"
+        description: str = "A test tool"
+
+        def _run(self, input: dict) -> str:
+            return "test result"
+
+    test_tool = TestTool()
+
     tool_usage = ToolUsage(
-        tools_handler=MagicMock(),
-        tools=[],
-        original_tools=[],
-        tools_description="",
-        tools_names="",
-        task=MagicMock(),
+        tools_handler=mock_tools_handler,
+        tools=[test_tool],
+        original_tools=[test_tool],
+        tools_description="Test Tool Description",
+        tools_names="Test Tool",
+        task=mock_task,
         function_calling_llm=None,
-        agent=MagicMock(),
+        agent=mock_agent,
         action=MagicMock(),
     )
 
-    arguments = tool_usage._validate_tool_input(None)
-    assert arguments == {}  # Expecting an empty dictionary
+    received_events = []
+
+    @crewai_event_bus.on(ToolSelectionErrorEvent)
+    def event_handler(source, event):
+        received_events.append(event)
+
+    with pytest.raises(Exception) as exc_info:
+        tool_usage._select_tool("Non Existent Tool")
+    assert len(received_events) == 1
+    event = received_events[0]
+    assert isinstance(event, ToolSelectionErrorEvent)
+    assert event.agent_key == "test_key"
+    assert event.agent_role == "test_role"
+    assert event.tool_name == "Non Existent Tool"
+    assert event.tool_args == {}
+    assert event.tool_class == "Test Tool Description"
+    assert "don't exist" in event.error
+
+    received_events.clear()
+    with pytest.raises(Exception) as exc_info:
+        tool_usage._select_tool("")
+
+    assert len(received_events) == 1
+    event = received_events[0]
+    assert isinstance(event, ToolSelectionErrorEvent)
+    assert event.agent_key == "test_key"
+    assert event.agent_role == "test_role"
+    assert event.tool_name == ""
+    assert event.tool_args == {}
+    assert event.tool_class == "Test Tool Description"
+    assert "forgot the Action name" in event.error
+
+
+def test_tool_validate_input_error_event():
+    """Test tool validation input error event emission from ToolUsage class."""
+    # Mock agent and required components
+    mock_agent = MagicMock()
+    mock_agent.key = "test_key"
+    mock_agent.role = "test_role"
+    mock_agent.verbose = False
+    mock_agent._original_role = "test_role"
+
+    # Mock i18n with error message
+    mock_i18n = MagicMock()
+    mock_i18n.errors.return_value = (
+        "Tool input must be a valid dictionary in JSON or Python literal format"
+    )
+    mock_agent.i18n = mock_i18n
+
+    # Mock task and tools handler
+    mock_task = MagicMock()
+    mock_tools_handler = MagicMock()
+
+    # Mock printer
+    mock_printer = MagicMock()
+
+    # Create test tool
+    class TestTool(BaseTool):
+        name: str = "Test Tool"
+        description: str = "A test tool"
+
+        def _run(self, input: dict) -> str:
+            return "test result"
+
+    test_tool = TestTool()
+
+    # Create ToolUsage instance
+    tool_usage = ToolUsage(
+        tools_handler=mock_tools_handler,
+        tools=[test_tool],
+        original_tools=[test_tool],
+        tools_description="Test Tool Description",
+        tools_names="Test Tool",
+        task=mock_task,
+        function_calling_llm=None,
+        agent=mock_agent,
+        action=MagicMock(tool="test_tool"),
+    )
+    tool_usage._printer = mock_printer
+
+    # Mock all parsing attempts to fail
+    with (
+        patch("json.loads", side_effect=json.JSONDecodeError("Test Error", "", 0)),
+        patch("ast.literal_eval", side_effect=ValueError),
+        patch("json5.loads", side_effect=json.JSONDecodeError("Test Error", "", 0)),
+        patch("json_repair.repair_json", side_effect=Exception("Failed to repair")),
+    ):
+        received_events = []
+
+        @crewai_event_bus.on(ToolValidateInputErrorEvent)
+        def event_handler(source, event):
+            received_events.append(event)
+
+        # Test invalid input
+        invalid_input = "invalid json {[}"
+        with pytest.raises(Exception) as exc_info:
+            tool_usage._validate_tool_input(invalid_input)
+
+        # Verify event was emitted
+        assert len(received_events) == 1, "Expected one event to be emitted"
+        event = received_events[0]
+        assert isinstance(event, ToolValidateInputErrorEvent)
+        assert event.agent_key == "test_key"
+        assert event.agent_role == "test_role"
+        assert event.tool_name == "test_tool"
+        assert "must be a valid dictionary" in event.error

tests/utilities/cassettes/test_agent_emits_execution_started_and_completed_events.yaml

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tests/utilities/cassettes/test_converter_with_llama3_2_model.yaml

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+    body: '{"model": "llama3.2:3b", "prompt": "### System:\nPlease convert the following
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+      - litellm/1.60.2
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tests/utilities/test_converter.py

@@ -1,4 +1,5 @@
 import json
+import os
 from typing import Dict, List, Optional
 from unittest.mock import MagicMock, Mock, patch
 
@@ -220,10 +221,13 @@ def test_get_conversion_instructions_gpt():
         supports_function_calling.return_value = True
         instructions = get_conversion_instructions(SimpleModel, llm)
         model_schema = PydanticSchemaParser(model=SimpleModel).get_schema()
-        assert (
-            instructions
-            == f"Please convert the following text into valid JSON.\n\nThe JSON should follow this schema:\n```json\n{model_schema}\n```"
+        expected_instructions = (
+            "Please convert the following text into valid JSON.\n\n"
+            "Output ONLY the valid JSON and nothing else.\n\n"
+            "The JSON must follow this schema exactly:\n```json\n"
+            f"{model_schema}\n```"
         )
+        assert instructions == expected_instructions
 
 
 def test_get_conversion_instructions_non_gpt():
@@ -346,12 +350,17 @@ def test_convert_with_instructions():
     assert output.age == 30
 
 
-@pytest.mark.vcr(filter_headers=["authorization"])
+# Skip tests that call external APIs when running in CI/CD
+skip_external_api = pytest.mark.skipif(
+    os.getenv("CI") is not None, reason="Skipping tests that call external API in CI/CD"
+)
+
+
+@skip_external_api
+@pytest.mark.vcr(filter_headers=["authorization"], record_mode="once")
 def test_converter_with_llama3_2_model():
     llm = LLM(model="ollama/llama3.2:3b", base_url="http://localhost:11434")
-
     sample_text = "Name: Alice Llama, Age: 30"
-
     instructions = get_conversion_instructions(SimpleModel, llm)
     converter = Converter(
         llm=llm,
@@ -359,19 +368,17 @@ def test_converter_with_llama3_2_model():
         model=SimpleModel,
         instructions=instructions,
     )
-
     output = converter.to_pydantic()
-
     assert isinstance(output, SimpleModel)
     assert output.name == "Alice Llama"
     assert output.age == 30
 
 
-@pytest.mark.vcr(filter_headers=["authorization"])
+@skip_external_api
+@pytest.mark.vcr(filter_headers=["authorization"], record_mode="once")
 def test_converter_with_llama3_1_model():
     llm = LLM(model="ollama/llama3.1", base_url="http://localhost:11434")
     sample_text = "Name: Alice Llama, Age: 30"
-
     instructions = get_conversion_instructions(SimpleModel, llm)
     converter = Converter(
         llm=llm,
@@ -379,14 +386,19 @@ def test_converter_with_llama3_1_model():
         model=SimpleModel,
         instructions=instructions,
     )
-
     output = converter.to_pydantic()
-
     assert isinstance(output, SimpleModel)
     assert output.name == "Alice Llama"
     assert output.age == 30
 
 
+# Skip tests that call external APIs when running in CI/CD
+skip_external_api = pytest.mark.skipif(
+    os.getenv("CI") is not None, reason="Skipping tests that call external API in CI/CD"
+)
+
+
+@skip_external_api
 @pytest.mark.vcr(filter_headers=["authorization"])
 def test_converter_with_nested_model():
     llm = LLM(model="gpt-4o-mini")
@@ -563,7 +575,7 @@ def test_converter_with_ambiguous_input():
     with pytest.raises(ConverterError) as exc_info:
         output = converter.to_pydantic()
 
-    assert "validation error" in str(exc_info.value).lower()
+    assert "failed to convert text into a pydantic model" in str(exc_info.value).lower()
 
 
 # Tests for function calling support

tests/utilities/test_events.py

@@ -0,0 +1,617 @@
+from datetime import datetime
+from unittest.mock import Mock, patch
+
+import pytest
+from pydantic import Field
+
+from crewai.agent import Agent
+from crewai.agents.crew_agent_executor import CrewAgentExecutor
+from crewai.crew import Crew
+from crewai.flow.flow import Flow, listen, start
+from crewai.llm import LLM
+from crewai.task import Task
+from crewai.tools.base_tool import BaseTool
+from crewai.utilities.events.agent_events import (
+    AgentExecutionCompletedEvent,
+    AgentExecutionErrorEvent,
+    AgentExecutionStartedEvent,
+)
+from crewai.utilities.events.crew_events import (
+    CrewKickoffCompletedEvent,
+    CrewKickoffFailedEvent,
+    CrewKickoffStartedEvent,
+    CrewTestCompletedEvent,
+    CrewTestStartedEvent,
+)
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+from crewai.utilities.events.event_listener import EventListener
+from crewai.utilities.events.event_types import ToolUsageFinishedEvent
+from crewai.utilities.events.flow_events import (
+    FlowCreatedEvent,
+    FlowFinishedEvent,
+    FlowStartedEvent,
+    MethodExecutionFailedEvent,
+    MethodExecutionStartedEvent,
+)
+from crewai.utilities.events.llm_events import (
+    LLMCallCompletedEvent,
+    LLMCallFailedEvent,
+    LLMCallStartedEvent,
+    LLMCallType,
+)
+from crewai.utilities.events.task_events import (
+    TaskCompletedEvent,
+    TaskFailedEvent,
+    TaskStartedEvent,
+)
+from crewai.utilities.events.tool_usage_events import (
+    ToolUsageErrorEvent,
+)
+
+base_agent = Agent(
+    role="base_agent",
+    llm="gpt-4o-mini",
+    goal="Just say hi",
+    backstory="You are a helpful assistant that just says hi",
+)
+
+base_task = Task(
+    description="Just say hi",
+    expected_output="hi",
+    agent=base_agent,
+)
+event_listener = EventListener()
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_crew_emits_start_kickoff_event():
+    received_events = []
+    mock_span = Mock()
+
+    @crewai_event_bus.on(CrewKickoffStartedEvent)
+    def handle_crew_start(source, event):
+        received_events.append(event)
+
+    crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+    with (
+        patch.object(
+            event_listener._telemetry, "crew_execution_span", return_value=mock_span
+        ) as mock_crew_execution_span,
+        patch.object(
+            event_listener._telemetry, "end_crew", return_value=mock_span
+        ) as mock_crew_ended,
+    ):
+        crew.kickoff()
+    mock_crew_execution_span.assert_called_once_with(crew, None)
+    mock_crew_ended.assert_called_once_with(crew, "hi")
+
+    assert len(received_events) == 1
+    assert received_events[0].crew_name == "TestCrew"
+    assert isinstance(received_events[0].timestamp, datetime)
+    assert received_events[0].type == "crew_kickoff_started"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_crew_emits_end_kickoff_event():
+    received_events = []
+
+    @crewai_event_bus.on(CrewKickoffCompletedEvent)
+    def handle_crew_end(source, event):
+        received_events.append(event)
+
+    crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+
+    crew.kickoff()
+
+    assert len(received_events) == 1
+    assert received_events[0].crew_name == "TestCrew"
+    assert isinstance(received_events[0].timestamp, datetime)
+    assert received_events[0].type == "crew_kickoff_completed"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_crew_emits_test_kickoff_type_event():
+    received_events = []
+    mock_span = Mock()
+
+    @crewai_event_bus.on(CrewTestStartedEvent)
+    def handle_crew_end(source, event):
+        received_events.append(event)
+
+    @crewai_event_bus.on(CrewTestCompletedEvent)
+    def handle_crew_test_end(source, event):
+        received_events.append(event)
+
+    eval_llm = LLM(model="gpt-4o-mini")
+    with (
+        patch.object(
+            event_listener._telemetry, "test_execution_span", return_value=mock_span
+        ) as mock_crew_execution_span,
+    ):
+        crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+        crew.test(n_iterations=1, eval_llm=eval_llm)
+
+        # Verify the call was made with correct argument types and values
+        assert mock_crew_execution_span.call_count == 1
+        args = mock_crew_execution_span.call_args[0]
+        assert isinstance(args[0], Crew)
+        assert args[1] == 1
+        assert args[2] is None
+        assert args[3] == eval_llm
+
+    assert len(received_events) == 2
+    assert received_events[0].crew_name == "TestCrew"
+    assert isinstance(received_events[0].timestamp, datetime)
+    assert received_events[0].type == "crew_test_started"
+    assert received_events[1].crew_name == "TestCrew"
+    assert isinstance(received_events[1].timestamp, datetime)
+    assert received_events[1].type == "crew_test_completed"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_crew_emits_kickoff_failed_event():
+    received_events = []
+
+    with crewai_event_bus.scoped_handlers():
+
+        @crewai_event_bus.on(CrewKickoffFailedEvent)
+        def handle_crew_failed(source, event):
+            received_events.append(event)
+
+        crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+
+        with patch.object(Crew, "_execute_tasks") as mock_execute:
+            error_message = "Simulated crew kickoff failure"
+            mock_execute.side_effect = Exception(error_message)
+
+            with pytest.raises(Exception):
+                crew.kickoff()
+
+        assert len(received_events) == 1
+        assert received_events[0].error == error_message
+        assert isinstance(received_events[0].timestamp, datetime)
+        assert received_events[0].type == "crew_kickoff_failed"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_crew_emits_start_task_event():
+    received_events = []
+
+    @crewai_event_bus.on(TaskStartedEvent)
+    def handle_task_start(source, event):
+        received_events.append(event)
+
+    crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+
+    crew.kickoff()
+
+    assert len(received_events) == 1
+    assert isinstance(received_events[0].timestamp, datetime)
+    assert received_events[0].type == "task_started"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_crew_emits_end_task_event():
+    received_events = []
+
+    @crewai_event_bus.on(TaskCompletedEvent)
+    def handle_task_end(source, event):
+        received_events.append(event)
+
+    mock_span = Mock()
+    crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+    with (
+        patch.object(
+            event_listener._telemetry, "task_started", return_value=mock_span
+        ) as mock_task_started,
+        patch.object(
+            event_listener._telemetry, "task_ended", return_value=mock_span
+        ) as mock_task_ended,
+    ):
+        crew.kickoff()
+
+    mock_task_started.assert_called_once_with(crew=crew, task=base_task)
+    mock_task_ended.assert_called_once_with(mock_span, base_task, crew)
+
+    assert len(received_events) == 1
+    assert isinstance(received_events[0].timestamp, datetime)
+    assert received_events[0].type == "task_completed"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_task_emits_failed_event_on_execution_error():
+    received_events = []
+    received_sources = []
+
+    @crewai_event_bus.on(TaskFailedEvent)
+    def handle_task_failed(source, event):
+        received_events.append(event)
+        received_sources.append(source)
+
+    with patch.object(
+        Task,
+        "_execute_core",
+    ) as mock_execute:
+        error_message = "Simulated task failure"
+        mock_execute.side_effect = Exception(error_message)
+        agent = Agent(
+            role="base_agent",
+            goal="Just say hi",
+            backstory="You are a helpful assistant that just says hi",
+        )
+        task = Task(
+            description="Just say hi",
+            expected_output="hi",
+            agent=agent,
+        )
+
+        with pytest.raises(Exception):
+            agent.execute_task(task=task)
+
+            assert len(received_events) == 1
+            assert received_sources[0] == task
+            assert received_events[0].error == error_message
+            assert isinstance(received_events[0].timestamp, datetime)
+            assert received_events[0].type == "task_failed"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_emits_execution_started_and_completed_events():
+    received_events = []
+
+    @crewai_event_bus.on(AgentExecutionStartedEvent)
+    def handle_agent_start(source, event):
+        received_events.append(event)
+
+    @crewai_event_bus.on(AgentExecutionCompletedEvent)
+    def handle_agent_completed(source, event):
+        received_events.append(event)
+
+    crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+    crew.kickoff()
+    assert len(received_events) == 2
+    assert received_events[0].agent == base_agent
+    assert received_events[0].task == base_task
+    assert received_events[0].tools == []
+    assert isinstance(received_events[0].task_prompt, str)
+    assert (
+        received_events[0].task_prompt
+        == "Just say hi\n\nThis is the expected criteria for your final answer: hi\nyou MUST return the actual complete content as the final answer, not a summary."
+    )
+    assert isinstance(received_events[0].timestamp, datetime)
+    assert received_events[0].type == "agent_execution_started"
+    assert isinstance(received_events[1].timestamp, datetime)
+    assert received_events[1].type == "agent_execution_completed"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_agent_emits_execution_error_event():
+    received_events = []
+
+    @crewai_event_bus.on(AgentExecutionErrorEvent)
+    def handle_agent_start(source, event):
+        received_events.append(event)
+
+    error_message = "Error happening while sending prompt to model."
+    base_agent.max_retry_limit = 0
+    with patch.object(
+        CrewAgentExecutor, "invoke", wraps=base_agent.agent_executor.invoke
+    ) as invoke_mock:
+        invoke_mock.side_effect = Exception(error_message)
+
+        with pytest.raises(Exception) as e:
+            base_agent.execute_task(
+                task=base_task,
+            )
+
+        assert len(received_events) == 1
+        assert received_events[0].agent == base_agent
+        assert received_events[0].task == base_task
+        assert received_events[0].error == error_message
+        assert isinstance(received_events[0].timestamp, datetime)
+        assert received_events[0].type == "agent_execution_error"
+
+
+class SayHiTool(BaseTool):
+    name: str = Field(default="say_hi", description="The name of the tool")
+    description: str = Field(
+        default="Say hi", description="The description of the tool"
+    )
+
+    def _run(self) -> str:
+        return "hi"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_tools_emits_finished_events():
+    received_events = []
+
+    @crewai_event_bus.on(ToolUsageFinishedEvent)
+    def handle_tool_end(source, event):
+        received_events.append(event)
+
+    agent = Agent(
+        role="base_agent",
+        goal="Just say hi",
+        backstory="You are a helpful assistant that just says hi",
+        tools=[SayHiTool()],
+    )
+
+    task = Task(
+        description="Just say hi",
+        expected_output="hi",
+        agent=agent,
+    )
+    crew = Crew(agents=[agent], tasks=[task], name="TestCrew")
+    crew.kickoff()
+    assert len(received_events) == 1
+    assert received_events[0].agent_key == agent.key
+    assert received_events[0].agent_role == agent.role
+    assert received_events[0].tool_name == SayHiTool().name
+    assert received_events[0].tool_args == {}
+    assert received_events[0].type == "tool_usage_finished"
+    assert isinstance(received_events[0].timestamp, datetime)
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_tools_emits_error_events():
+    received_events = []
+
+    @crewai_event_bus.on(ToolUsageErrorEvent)
+    def handle_tool_end(source, event):
+        received_events.append(event)
+
+    class ErrorTool(BaseTool):
+        name: str = Field(
+            default="error_tool", description="A tool that raises an error"
+        )
+        description: str = Field(
+            default="This tool always raises an error",
+            description="The description of the tool",
+        )
+
+        def _run(self) -> str:
+            raise Exception("Simulated tool error")
+
+    agent = Agent(
+        role="base_agent",
+        goal="Try to use the error tool",
+        backstory="You are an assistant that tests error handling",
+        tools=[ErrorTool()],
+    )
+
+    task = Task(
+        description="Use the error tool",
+        expected_output="This should error",
+        agent=agent,
+    )
+
+    crew = Crew(agents=[agent], tasks=[task], name="TestCrew")
+    crew.kickoff()
+
+    assert len(received_events) == 75
+    assert received_events[0].agent_key == agent.key
+    assert received_events[0].agent_role == agent.role
+    assert received_events[0].tool_name == "error_tool"
+    assert received_events[0].tool_args == {}
+    assert str(received_events[0].error) == "Simulated tool error"
+    assert received_events[0].type == "tool_usage_error"
+    assert isinstance(received_events[0].timestamp, datetime)
+
+
+def test_flow_emits_start_event():
+    received_events = []
+    mock_span = Mock()
+
+    @crewai_event_bus.on(FlowStartedEvent)
+    def handle_flow_start(source, event):
+        received_events.append(event)
+
+    class TestFlow(Flow[dict]):
+        @start()
+        def begin(self):
+            return "started"
+
+    with (
+        patch.object(
+            event_listener._telemetry, "flow_execution_span", return_value=mock_span
+        ) as mock_flow_execution_span,
+    ):
+        flow = TestFlow()
+        flow.kickoff()
+
+    mock_flow_execution_span.assert_called_once_with("TestFlow", ["begin"])
+    assert len(received_events) == 1
+    assert received_events[0].flow_name == "TestFlow"
+    assert received_events[0].type == "flow_started"
+
+
+def test_flow_emits_finish_event():
+    received_events = []
+
+    with crewai_event_bus.scoped_handlers():
+
+        @crewai_event_bus.on(FlowFinishedEvent)
+        def handle_flow_finish(source, event):
+            received_events.append(event)
+
+        class TestFlow(Flow[dict]):
+            @start()
+            def begin(self):
+                return "completed"
+
+        flow = TestFlow()
+        result = flow.kickoff()
+
+        assert len(received_events) == 1
+        assert received_events[0].flow_name == "TestFlow"
+        assert received_events[0].type == "flow_finished"
+        assert received_events[0].result == "completed"
+        assert result == "completed"
+
+
+def test_flow_emits_method_execution_started_event():
+    received_events = []
+
+    with crewai_event_bus.scoped_handlers():
+
+        @crewai_event_bus.on(MethodExecutionStartedEvent)
+        def handle_method_start(source, event):
+            print("event in method name", event.method_name)
+            received_events.append(event)
+
+        class TestFlow(Flow[dict]):
+            @start()
+            def begin(self):
+                return "started"
+
+            @listen("begin")
+            def second_method(self):
+                return "executed"
+
+        flow = TestFlow()
+        flow.kickoff()
+
+        assert len(received_events) == 2
+
+        assert received_events[0].method_name == "begin"
+        assert received_events[0].flow_name == "TestFlow"
+        assert received_events[0].type == "method_execution_started"
+
+        assert received_events[1].method_name == "second_method"
+        assert received_events[1].flow_name == "TestFlow"
+        assert received_events[1].type == "method_execution_started"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_register_handler_adds_new_handler():
+    received_events = []
+
+    def custom_handler(source, event):
+        received_events.append(event)
+
+    with crewai_event_bus.scoped_handlers():
+        crewai_event_bus.register_handler(CrewKickoffStartedEvent, custom_handler)
+
+        crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+        crew.kickoff()
+
+        assert len(received_events) == 1
+        assert isinstance(received_events[0].timestamp, datetime)
+        assert received_events[0].type == "crew_kickoff_started"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_multiple_handlers_for_same_event():
+    received_events_1 = []
+    received_events_2 = []
+
+    def handler_1(source, event):
+        received_events_1.append(event)
+
+    def handler_2(source, event):
+        received_events_2.append(event)
+
+    with crewai_event_bus.scoped_handlers():
+        crewai_event_bus.register_handler(CrewKickoffStartedEvent, handler_1)
+        crewai_event_bus.register_handler(CrewKickoffStartedEvent, handler_2)
+
+        crew = Crew(agents=[base_agent], tasks=[base_task], name="TestCrew")
+        crew.kickoff()
+
+        assert len(received_events_1) == 1
+        assert len(received_events_2) == 1
+        assert received_events_1[0].type == "crew_kickoff_started"
+        assert received_events_2[0].type == "crew_kickoff_started"
+
+
+def test_flow_emits_created_event():
+    received_events = []
+    mock_span = Mock()
+
+    @crewai_event_bus.on(FlowCreatedEvent)
+    def handle_flow_created(source, event):
+        received_events.append(event)
+
+    class TestFlow(Flow[dict]):
+        @start()
+        def begin(self):
+            return "started"
+
+    with (
+        patch.object(
+            event_listener._telemetry, "flow_creation_span", return_value=mock_span
+        ) as mock_flow_creation_span,
+    ):
+        flow = TestFlow()
+        flow.kickoff()
+
+    mock_flow_creation_span.assert_called_once_with("TestFlow")
+
+    assert len(received_events) == 1
+    assert received_events[0].flow_name == "TestFlow"
+    assert received_events[0].type == "flow_created"
+
+
+def test_flow_emits_method_execution_failed_event():
+    received_events = []
+    error = Exception("Simulated method failure")
+
+    @crewai_event_bus.on(MethodExecutionFailedEvent)
+    def handle_method_failed(source, event):
+        received_events.append(event)
+
+    class TestFlow(Flow[dict]):
+        @start()
+        def begin(self):
+            raise error
+
+    flow = TestFlow()
+    with pytest.raises(Exception):
+        flow.kickoff()
+
+    assert len(received_events) == 1
+    assert received_events[0].method_name == "begin"
+    assert received_events[0].flow_name == "TestFlow"
+    assert received_events[0].type == "method_execution_failed"
+    assert received_events[0].error == error
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_llm_emits_call_started_event():
+    received_events = []
+
+    @crewai_event_bus.on(LLMCallStartedEvent)
+    def handle_llm_call_started(source, event):
+        received_events.append(event)
+
+    @crewai_event_bus.on(LLMCallCompletedEvent)
+    def handle_llm_call_completed(source, event):
+        received_events.append(event)
+
+    llm = LLM(model="gpt-4o-mini")
+    llm.call("Hello, how are you?")
+
+    assert len(received_events) == 2
+    assert received_events[0].type == "llm_call_started"
+    assert received_events[1].type == "llm_call_completed"
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_llm_emits_call_failed_event():
+    received_events = []
+
+    @crewai_event_bus.on(LLMCallFailedEvent)
+    def handle_llm_call_failed(source, event):
+        received_events.append(event)
+
+    error_message = "Simulated LLM call failure"
+    with patch("crewai.llm.litellm.completion", side_effect=Exception(error_message)):
+        llm = LLM(model="gpt-4o-mini")
+        with pytest.raises(Exception) as exc_info:
+            llm.call("Hello, how are you?")
+
+        assert str(exc_info.value) == error_message
+        assert len(received_events) == 1
+        assert received_events[0].type == "llm_call_failed"
+        assert received_events[0].error == error_message