Lorenze/better tracing events (#3382)

* feat: implement tool usage limit exception handling

- Introduced `ToolUsageLimitExceeded` exception to manage maximum usage limits for tools.
- Enhanced `CrewStructuredTool` to check and raise this exception when the usage limit is reached.
- Updated `_run` and `_execute` methods to include usage limit checks and handle exceptions appropriately, improving reliability and user feedback.

* feat: enhance PlusAPI and ToolUsage with task metadata

- Removed the `send_trace_batch` method from PlusAPI to streamline the API.
- Added timeout parameters to trace event methods in PlusAPI for improved reliability.
- Updated ToolUsage to include task metadata (task name and ID) in event emissions, enhancing traceability and context during tool usage.
- Refactored event handling in LLM and ToolUsage events to ensure task information is consistently captured.

* feat: enhance memory and event handling with task and agent metadata

- Added task and agent metadata to various memory and event classes, improving traceability and context during memory operations.
- Updated the `ContextualMemory` and `Memory` classes to associate tasks and agents, allowing for better context management.
- Enhanced event emissions in `LLM`, `ToolUsage`, and memory events to include task and agent information, facilitating improved debugging and monitoring.
- Refactored event handling to ensure consistent capture of task and agent details across the system.

* drop

* refactor: clean up unused imports in memory and event modules

- Removed unused TYPE_CHECKING imports from long_term_memory.py to streamline the code.
- Eliminated unnecessary import from memory_events.py, enhancing clarity and maintainability.

* fix memory tests

* fix task_completed payload

* fix: remove unused test agent variable in external memory tests

* refactor: remove unused agent parameter from Memory class save method

- Eliminated the agent parameter from the save method in the Memory class to streamline the code and improve clarity.
- Updated the TraceBatchManager class by moving initialization of attributes into the constructor for better organization and readability.

* refactor: enhance ExecutionState and ReasoningEvent classes with optional task and agent identifiers

- Added optional `current_agent_id` and `current_task_id` attributes to the `ExecutionState` class for better tracking of agent and task states.
- Updated the `from_task` attribute in the `ReasoningEvent` class to use `Optional[Any]` instead of a specific type, improving flexibility in event handling.

* refactor: update ExecutionState class by removing unused agent and task identifiers

- Removed the `current_agent_id` and `current_task_id` attributes from the `ExecutionState` class to simplify the code and enhance clarity.
- Adjusted the import statements to include `Optional` for better type handling.

* refactor: streamline LLM event handling in LiteAgent

- Removed unused LLM event emissions (LLMCallStartedEvent, LLMCallCompletedEvent, LLMCallFailedEvent) from the LiteAgent class to simplify the code and improve performance.
- Adjusted the flow of LLM response handling by eliminating unnecessary event bus interactions, enhancing clarity and maintainability.

* flow ownership and not emitting events when a crew is done

* refactor: remove unused agent parameter from ShortTermMemory save method

- Eliminated the agent parameter from the save method in the ShortTermMemory class to streamline the code and improve clarity.
- This change enhances the maintainability of the memory management system by reducing unnecessary complexity.

* runtype check fix

* fixing tests

* fix lints

* fix: update event assertions in test_llm_emits_event_with_lite_agent

- Adjusted the expected counts for completed and started events in the test to reflect the correct behavior of the LiteAgent.
- Updated assertions for agent roles and IDs to match the expected values after recent changes in event handling.

* fix: update task name assertions in event tests

- Modified assertions in `test_stream_llm_emits_event_with_task_and_agent_info` and `test_llm_emits_event_with_task_and_agent_info` to use `task.description` as a fallback for `task.name`. This ensures that the tests correctly validate the task name even when it is not explicitly set.

* fix: update test assertions for output values and improve readability

- Updated assertions in `test_output_json_dict_hierarchical` to reflect the correct expected score value.
- Enhanced readability of assertions in `test_output_pydantic_to_another_task` and `test_key` by formatting the error messages for clarity.
- These changes ensure that the tests accurately validate the expected outputs and improve overall code quality.

* test fixes

* fix crew_test

* added another fixture

* fix: ensure agent and task assignments in contextual memory are conditional

- Updated the ContextualMemory class to check for the existence of short-term, long-term, external, and extended memory before assigning agent and task attributes. This prevents potential attribute errors when memory types are not initialized.

src/crewai/llm.py

@@ -851,7 +851,9 @@ class LLM(BaseLLM):
             return tool_calls
 
         # --- 7) Handle tool calls if present
-        tool_result = self._handle_tool_call(tool_calls, available_functions)
+        tool_result = self._handle_tool_call(
+            tool_calls, available_functions, from_task, from_agent
+        )
         if tool_result is not None:
             return tool_result
         # --- 8) If tool call handling didn't return a result, emit completion event and return text response
@@ -868,6 +870,8 @@ class LLM(BaseLLM):
         self,
         tool_calls: List[Any],
         available_functions: Optional[Dict[str, Any]] = None,
+        from_task: Optional[Any] = None,
+        from_agent: Optional[Any] = None,
     ) -> Optional[str]:
         """Handle a tool call from the LLM.
 
@@ -902,6 +906,8 @@ class LLM(BaseLLM):
                     event=ToolUsageStartedEvent(
                         tool_name=function_name,
                         tool_args=function_args,
+                        from_agent=from_agent,
+                        from_task=from_task,
                     ),
                 )
 
@@ -914,12 +920,17 @@ class LLM(BaseLLM):
                         tool_args=function_args,
                         started_at=started_at,
                         finished_at=datetime.now(),
+                        from_task=from_task,
+                        from_agent=from_agent,
                     ),
                 )
 
                 # --- 3.3) Emit success event
                 self._handle_emit_call_events(
-                    response=result, call_type=LLMCallType.TOOL_CALL
+                    response=result,
+                    call_type=LLMCallType.TOOL_CALL,
+                    from_task=from_task,
+                    from_agent=from_agent,
                 )
                 return result
             except Exception as e:
@@ -1139,7 +1150,11 @@ class LLM(BaseLLM):
 
         # TODO: Remove this code after merging PR https://github.com/BerriAI/litellm/pull/10917
         # Ollama doesn't supports last message to be 'assistant'
-        if "ollama" in self.model.lower() and messages and messages[-1]["role"] == "assistant":
+        if (
+            "ollama" in self.model.lower()
+            and messages
+            and messages[-1]["role"] == "assistant"
+        ):
             return messages + [{"role": "user", "content": ""}]
 
         # Handle Anthropic models