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Lorenze/better tracing events (#3382)
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* 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.
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@@ -1,4 +1,4 @@
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from typing import Optional
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from typing import Optional, TYPE_CHECKING
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from crewai.memory import (
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EntityMemory,
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@@ -7,6 +7,10 @@ from crewai.memory import (
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ShortTermMemory,
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)
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if TYPE_CHECKING:
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from crewai.agent import Agent
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from crewai.task import Task
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class ContextualMemory:
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def __init__(
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@@ -15,11 +19,28 @@ class ContextualMemory:
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ltm: LongTermMemory,
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em: EntityMemory,
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exm: ExternalMemory,
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agent: Optional["Agent"] = None,
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task: Optional["Task"] = None,
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):
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self.stm = stm
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self.ltm = ltm
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self.em = em
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self.exm = exm
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self.agent = agent
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self.task = task
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if self.stm is not None:
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self.stm.agent = self.agent
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self.stm.task = self.task
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if self.ltm is not None:
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self.ltm.agent = self.agent
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self.ltm.task = self.task
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if self.em is not None:
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self.em.agent = self.agent
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self.em.task = self.task
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if self.exm is not None:
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self.exm.agent = self.agent
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self.exm.task = self.task
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def build_context_for_task(self, task, context) -> str:
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"""
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@@ -49,10 +70,7 @@ class ContextualMemory:
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stm_results = self.stm.search(query)
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formatted_results = "\n".join(
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[
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f"- {result['context']}"
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for result in stm_results
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]
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[f"- {result['context']}" for result in stm_results]
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)
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return f"Recent Insights:\n{formatted_results}" if stm_results else ""
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@@ -89,10 +107,7 @@ class ContextualMemory:
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em_results = self.em.search(query)
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formatted_results = "\n".join(
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[
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f"- {result['context']}"
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for result in em_results
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] # type: ignore # Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
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[f"- {result['context']}" for result in em_results] # type: ignore # Invalid index type "str" for "str"; expected type "SupportsIndex | slice"
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)
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return f"Entities:\n{formatted_results}" if em_results else ""
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