Enhance event handling for tool usage and agent execution

- Add new events for tool usage: ToolSelectionErrorEvent, ToolValidateInputErrorEvent
- Improve error tracking and event emission in ToolUsage and LLM classes
- Update AgentExecutionStartedEvent to use task_prompt instead of inputs
- Add comprehensive test coverage for new event types and error scenarios

src/crewai/agent.py

@@ -22,6 +22,7 @@ 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
@@ -231,6 +232,15 @@ 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,
@@ -240,19 +250,27 @@ class Agent(BaseAgent):
                 }
             )["output"]
         except Exception as e:
-            crewai_event_bus.emit(
-                self,
-                event=AgentExecutionErrorEvent(
-                    agent=self,
-                    task=task,
-                    error=str(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)
 

src/crewai/agents/crew_agent_executor.py

@@ -19,10 +19,11 @@ 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 (
-    AgentExecutionErrorEvent,
+    ToolUsageErrorEvent,
-    AgentExecutionStartedEvent,
+    ToolUsageStartedEvent,
+    crewai_event_bus,
 )
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+from crewai.utilities.events.tool_usage_events import ToolUsageStartedEvent
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
@@ -90,16 +91,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
         self.llm.stop = list(set(self.llm.stop + self.stop))
 
     def invoke(self, inputs: Dict[str, str]) -> Dict[str, Any]:
-        if self.agent and self.task:
-            crewai_event_bus.emit(
-                self,
-                event=AgentExecutionStartedEvent(
-                    agent=self.agent,
-                    tools=self.tools,
-                    inputs=inputs,
-                    task=self.task,
-                ),
-            )
         if "system" in self.prompt:
             system_prompt = self._format_prompt(self.prompt.get("system", ""), inputs)
             user_prompt = self._format_prompt(self.prompt.get("user", ""), inputs)
@@ -192,13 +183,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
 
     def _handle_unknown_error(self, exception: Exception) -> None:
         """Handle unknown errors by informing the user."""
-        if self.agent:
-            crewai_event_bus.emit(
-                self,
-                event=AgentExecutionErrorEvent(
-                    agent=self.agent, task=self.task, error=str(exception)
-                ),
-            )
         self._printer.print(
             content="An unknown error occurred. Please check the details below.",
             color="red",
@@ -371,40 +355,68 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
                 )
 
     def _execute_tool_and_check_finality(self, agent_action: AgentAction) -> ToolResult:
-        tool_usage = ToolUsage(
+        try:
-            tools_handler=self.tools_handler,
+            if self.agent:
-            tools=self.tools,
+                crewai_event_bus.emit(
-            original_tools=self.original_tools,
+                    self,
-            tools_description=self.tools_description,
+                    event=ToolUsageStartedEvent(
-            tools_names=self.tools_names,
+                        agent_key=self.agent.key,
-            function_calling_llm=self.function_calling_llm,
+                        agent_role=self.agent.role,
-            task=self.task,  # type: ignore[arg-type]
+                        tool_name=agent_action.tool,
-            agent=self.agent,
+                        tool_args=agent_action.tool_input,
-            action=agent_action,
+                        tool_class=agent_action.tool,
-        )
+                    ),
-        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)
+            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 = []

src/crewai/llm.py

@@ -10,6 +10,8 @@ from typing import Any, Dict, List, Literal, Optional, Type, Union, cast
 from dotenv import load_dotenv
 from pydantic import BaseModel
 
+from crewai.utilities.events.tool_usage_events import ToolExecutionErrorEvent
+
 with warnings.catch_warnings():
     warnings.simplefilter("ignore", UserWarning)
     import litellm
@@ -18,6 +20,7 @@ with warnings.catch_warnings():
     from litellm.utils import supports_response_schema
 
 
+from crewai.utilities.events import crewai_event_bus
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
@@ -181,14 +184,14 @@ 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 +202,7 @@ 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 +214,22 @@ 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"},
@@ -315,7 +318,7 @@ class LLM:
                 # --- 5) Handle the tool call
                 tool_call = tool_calls[0]
                 function_name = tool_call.function.name
-
+                print("function_name", function_name)
                 if function_name in available_functions:
                     try:
                         function_args = json.loads(tool_call.function.arguments)
@@ -333,6 +336,15 @@ class LLM:
                         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),
+                            ),
+                        )
                         return text_response
 
                 else:
@@ -348,36 +360,40 @@ class LLM:
                     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 _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:

src/crewai/tools/tool_usage.py

@@ -17,12 +17,14 @@ from crewai.tools import BaseTool
 from crewai.tools.structured_tool import CrewStructuredTool
 from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
 from crewai.utilities import I18N, Converter, ConverterError, Printer
-from crewai.utilities.events import (
+from crewai.utilities.events.crewai_event_bus import crewai_event_bus
+from crewai.utilities.events.tool_usage_events import (
+    ToolSelectionErrorEvent,
     ToolUsageErrorEvent,
     ToolUsageFinishedEvent,
     ToolUsageStartedEvent,
+    ToolValidateInputErrorEvent,
 )
-from crewai.utilities.events.crewai_event_bus import crewai_event_bus
 
 OPENAI_BIGGER_MODELS = [
     "gpt-4",
@@ -306,14 +308,33 @@ 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(
+            error = f"Action '{tool_name}' don't exist, these are the only available Actions:\n{self.tools_description}"
-                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(
+            error = f"I forgot the Action name, these are the only available Actions: {self.tools_description}"
-                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."""
@@ -449,18 +470,33 @@ 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
+        error_message = (
-        raise Exception(
             "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)
-        crewai_event_bus.emit(
+        crewai_event_bus.emit(self, ToolUsageErrorEvent(**{**event_data, "error": e}))
-            self, event=ToolUsageErrorEvent(**{**event_data, "error": e})
-        )
 
     def on_tool_use_finished(
         self, tool: Any, tool_calling: ToolCalling, from_cache: bool, started_at: float
@@ -474,7 +510,7 @@ class ToolUsage:
                 "from_cache": from_cache,
             }
         )
-        crewai_event_bus.emit(self, event=ToolUsageFinishedEvent(**event_data))
+        crewai_event_bus.emit(self, ToolUsageFinishedEvent(**event_data))
 
     def _prepare_event_data(self, tool: Any, tool_calling: ToolCalling) -> dict:
         return {

src/crewai/utilities/events/__init__.py

@@ -25,7 +25,15 @@ from .flow_events import (
     MethodExecutionFailedEvent,
 )
 from .crewai_event_bus import CrewAIEventsBus, crewai_event_bus
-from .tool_usage_events import ToolUsageFinishedEvent, ToolUsageErrorEvent, ToolUsageStartedEvent
+from .tool_usage_events import (
+    ToolUsageFinishedEvent,
+    ToolUsageErrorEvent,
+    ToolUsageStartedEvent,
+    ToolExecutionErrorEvent,
+    ToolSelectionErrorEvent,
+    ToolUsageEvent,
+    ToolValidateInputErrorEvent,
+)
 
 # events
 from .event_listener import EventListener

src/crewai/utilities/events/agent_events.py

@@ -16,7 +16,7 @@ class AgentExecutionStartedEvent(CrewEvent):
     agent: BaseAgent
     task: Any
     tools: Optional[Sequence[Union[BaseTool, CrewStructuredTool]]]
-    inputs: Dict[str, Any]
+    task_prompt: str
     type: str = "agent_execution_started"
 
     model_config = {"arbitrary_types_allowed": True}

src/crewai/utilities/events/crewai_event_bus.py

@@ -5,6 +5,7 @@ from typing import Any, Callable, Dict, List, Type, TypeVar, cast
 from blinker import Signal
 
 from crewai.utilities.events.crew_events import CrewEvent
+from crewai.utilities.events.event_types import EventTypes
 
 EventT = TypeVar("EventT", bound=CrewEvent)
 
@@ -29,9 +30,7 @@ class CrewAIEventsBus:
     def _initialize(self) -> None:
         """Initialize the event bus internal state"""
         self._signal = Signal("crewai_event_bus")
-        self._handlers: Dict[
+        self._handlers: Dict[Type[CrewEvent], List[Callable]] = {}
-            Type[CrewEvent], List[Callable[[Any, CrewEvent], None]]
-        ] = {}
 
     def on(
         self, event_type: Type[EventT]
@@ -54,7 +53,7 @@ class CrewAIEventsBus:
             if event_type not in self._handlers:
                 self._handlers[event_type] = []
             self._handlers[event_type].append(
-                cast(Callable[[Any, CrewEvent], None], handler)
+                cast(Callable[[Any, EventT], None], handler)
             )
             return handler
 
@@ -79,13 +78,13 @@ class CrewAIEventsBus:
         self._handlers.clear()
 
     def register_handler(
-        self, event_type: Type[EventT], handler: Callable[[Any, EventT], None]
+        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, CrewEvent], None], handler)
+            cast(Callable[[Any, EventTypes], None], handler)
         )
 
     @contextmanager

src/crewai/utilities/events/tool_usage_events.py

@@ -1,5 +1,5 @@
 from datetime import datetime
-from typing import Any, Dict
+from typing import Any, Callable, Dict
 
 from .crew_events import CrewEvent
 
@@ -10,7 +10,7 @@ class ToolUsageEvent(CrewEvent):
     agent_key: str
     agent_role: str
     tool_name: str
-    tool_args: Dict[str, Any]
+    tool_args: Dict[str, Any] | str
     tool_class: str
     run_attempts: int | None = None
     delegations: int | None = None
@@ -38,3 +38,27 @@ class ToolUsageErrorEvent(ToolUsageEvent):
 
     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

tests/cassettes/test_tool_execution_error_event.yaml

@@ -0,0 +1,112 @@
+interactions:
+- request:
+    body: '{"messages": [{"role": "user", "content": "Use the failing tool"}], "model":
+      "gpt-4o-mini", "stop": [], "tools": [{"type": "function", "function": {"name":
+      "failing_tool", "description": "This tool always fails.", "parameters": {"type":
+      "object", "properties": {"param": {"type": "string", "description": "A test
+      parameter"}}, "required": ["param"]}}}]}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate
+      connection:
+      - keep-alive
+      content-length:
+      - '353'
+      content-type:
+      - application/json
+      host:
+      - api.openai.com
+      user-agent:
+      - OpenAI/Python 1.61.0
+      x-stainless-arch:
+      - arm64
+      x-stainless-async:
+      - 'false'
+      x-stainless-lang:
+      - python
+      x-stainless-os:
+      - MacOS
+      x-stainless-package-version:
+      - 1.61.0
+      x-stainless-raw-response:
+      - 'true'
+      x-stainless-retry-count:
+      - '0'
+      x-stainless-runtime:
+      - CPython
+      x-stainless-runtime-version:
+      - 3.12.8
+    method: POST
+    uri: https://api.openai.com/v1/chat/completions
+  response:
+    content: "{\n  \"id\": \"chatcmpl-B2P4zoJZuES7Aom8ugEq1modz5Vsl\",\n  \"object\":
+      \"chat.completion\",\n  \"created\": 1739912761,\n  \"model\": \"gpt-4o-mini-2024-07-18\",\n
+      \ \"choices\": [\n    {\n      \"index\": 0,\n      \"message\": {\n        \"role\":
+      \"assistant\",\n        \"content\": null,\n        \"tool_calls\": [\n          {\n
+      \           \"id\": \"call_F6fJxISpMKUBIGV6dd2vjRNG\",\n            \"type\":
+      \"function\",\n            \"function\": {\n              \"name\": \"failing_tool\",\n
+      \             \"arguments\": \"{\\\"param\\\":\\\"test\\\"}\"\n            }\n
+      \         }\n        ],\n        \"refusal\": null\n      },\n      \"logprobs\":
+      null,\n      \"finish_reason\": \"tool_calls\"\n    }\n  ],\n  \"usage\": {\n
+      \   \"prompt_tokens\": 51,\n    \"completion_tokens\": 15,\n    \"total_tokens\":
+      66,\n    \"prompt_tokens_details\": {\n      \"cached_tokens\": 0,\n      \"audio_tokens\":
+      0\n    },\n    \"completion_tokens_details\": {\n      \"reasoning_tokens\":
+      0,\n      \"audio_tokens\": 0,\n      \"accepted_prediction_tokens\": 0,\n      \"rejected_prediction_tokens\":
+      0\n    }\n  },\n  \"service_tier\": \"default\",\n  \"system_fingerprint\":
+      \"fp_00428b782a\"\n}\n"
+    headers:
+      CF-RAY:
+      - 9140fa827f38eb1e-SJC
+      Connection:
+      - keep-alive
+      Content-Encoding:
+      - gzip
+      Content-Type:
+      - application/json
+      Date:
+      - Tue, 18 Feb 2025 21:06:02 GMT
+      Server:
+      - cloudflare
+      Set-Cookie:
+      - __cf_bm=xbuu3IQpCMh.43ZrqL1TRMECOc6QldgHV0hzOX1GrWI-1739912762-1.0.1.1-t7iyq5xMioPrwfeaHLvPT9rwRPp7Q9A9uIm69icH9dPxRD4xMA3cWqb1aXj1_e2IyAEQQWFe1UWjlmJ22aHh3Q;
+        path=/; expires=Tue, 18-Feb-25 21:36:02 GMT; domain=.api.openai.com; HttpOnly;
+        Secure; SameSite=None
+      - _cfuvid=x9l.Rhja8_wXDN.j8qcEU1PvvEqAwZp4Fd3s_aj4qwM-1739912762161-0.0.1.1-604800000;
+        path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None
+      Transfer-Encoding:
+      - chunked
+      X-Content-Type-Options:
+      - nosniff
+      access-control-expose-headers:
+      - X-Request-ID
+      alt-svc:
+      - h3=":443"; ma=86400
+      cf-cache-status:
+      - DYNAMIC
+      openai-organization:
+      - crewai-iuxna1
+      openai-processing-ms:
+      - '861'
+      openai-version:
+      - '2020-10-01'
+      strict-transport-security:
+      - max-age=31536000; includeSubDomains; preload
+      x-ratelimit-limit-requests:
+      - '30000'
+      x-ratelimit-limit-tokens:
+      - '150000000'
+      x-ratelimit-remaining-requests:
+      - '29999'
+      x-ratelimit-remaining-tokens:
+      - '149999978'
+      x-ratelimit-reset-requests:
+      - 2ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_8666ec3aa6677cb346ba00993556051d
+    http_version: HTTP/1.1
+    status_code: 200
+version: 1

tests/llm_test.py

@@ -7,7 +7,8 @@ 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.utilities.events import crewai_event_bus
+from crewai.utilities.events.tool_usage_events import ToolExecutionErrorEvent
 from crewai.utilities.token_counter_callback import TokenCalcHandler
 
 
@@ -291,32 +292,36 @@ 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 +332,12 @@ 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 +377,51 @@ 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/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)
@@ -468,18 +473,141 @@ 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_handler=mock_tools_handler,
-        tools=[],
+        tools=[test_tool],
-        original_tools=[],
+        original_tools=[test_tool],
-        tools_description="",
+        tools_description="Test Tool Description",
-        tools_names="",
+        tools_names="Test Tool",
-        task=MagicMock(),
+        task=mock_task,
         function_calling_llm=None,
-        agent=MagicMock(),
+        agent=mock_agent,
         action=MagicMock(),
     )
 
-    arguments = tool_usage._validate_tool_input(None)
+    received_events = []
-    assert arguments == {}  # Expecting an empty dictionary
+
+    @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/test_events.py

@@ -1,5 +1,6 @@
+import json
 from datetime import datetime
-from unittest.mock import patch
+from unittest.mock import MagicMock, patch
 
 import pytest
 from pydantic import Field
@@ -10,6 +11,7 @@ from crewai.crew import Crew
 from crewai.flow.flow import Flow, listen, start
 from crewai.task import Task
 from crewai.tools.base_tool import BaseTool
+from crewai.tools.tool_usage import ToolUsage
 from crewai.utilities.events.agent_events import (
     AgentExecutionCompletedEvent,
     AgentExecutionErrorEvent,
@@ -34,7 +36,9 @@ from crewai.utilities.events.task_events import (
     TaskFailedEvent,
     TaskStartedEvent,
 )
-from crewai.utilities.events.tool_usage_events import ToolUsageErrorEvent
+from crewai.utilities.events.tool_usage_events import (
+    ToolUsageErrorEvent,
+)
 
 base_agent = Agent(
     role="base_agent",