* feat: enhance knowledge event handling in Agent class
- Updated the Agent class to include task context in knowledge retrieval events.
- Emitted new events for knowledge retrieval and query processes, capturing task and agent details.
- Refactored knowledge event classes to inherit from a base class for better structure and maintainability.
- Added tracing for knowledge events in the TraceCollectionListener to improve observability.
This change improves the tracking and management of knowledge queries and retrievals, facilitating better debugging and performance monitoring.
* refactor: remove task_id from knowledge event emissions in Agent class
- Removed the task_id parameter from various knowledge event emissions in the Agent class to streamline event handling.
- This change simplifies the event structure and focuses on the essential context of knowledge retrieval and query processes.
This refactor enhances the clarity of knowledge events and aligns with the recent improvements in event handling.
* surface association for guardrail events
* fix: improve LLM selection logic in converter
- Updated the logic for selecting the LLM in the convert_with_instructions function to handle cases where the agent may not have a function_calling_llm attribute.
- This change ensures that the converter can still function correctly by falling back to the standard LLM if necessary, enhancing robustness and preventing potential errors.
This fix improves the reliability of the conversion process when working with different agent configurations.
* fix test
* fix: enforce valid LLM instance requirement in converter
- Updated the convert_with_instructions function to ensure that a valid LLM instance is provided by the agent.
- If neither function_calling_llm nor the standard llm is available, a ValueError is raised, enhancing error handling and robustness.
- Improved error messaging for conversion failures to provide clearer feedback on issues encountered during the conversion process.
This change strengthens the reliability of the conversion process by ensuring that agents are properly configured with a valid LLM.
refactor(events): relocate events module & update imports
- Move events from utilities/ to top-level events/ with types/, listeners/, utils/ structure
- Update all source/tests/docs to new import paths
- Add backwards compatibility stubs in crewai.utilities.events with deprecation warnings
- Restore test mocks and fix related test imports
* 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.
* Fix#3149: Add missing create_directory parameter to Task class
- Add create_directory field with default value True for backward compatibility
- Update _save_file method to respect create_directory parameter
- Add comprehensive tests covering all scenarios
- Maintain existing behavior when create_directory=True (default)
The create_directory parameter was documented but missing from implementation.
Users can now control directory creation behavior:
- create_directory=True (default): Creates directories if they don't exist
- create_directory=False: Raises RuntimeError if directory doesn't exist
Fixes issue where users got TypeError when trying to use the documented
create_directory parameter.
Co-Authored-By: Jo\u00E3o <joao@crewai.com>
* Fix lint: Remove unused import os from test_create_directory_true
- Removes F401 lint error: 'os' imported but unused
- All lint checks should now pass
Co-Authored-By: Jo\u00E3o <joao@crewai.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Jo\u00E3o <joao@crewai.com>
* Added Union of List of Task, None, NotSpecified
* Seems like a flaky test
* Fixed run time issue
* Fixed Linting issues
* fix pydantic error
* aesthetic changes
---------
Co-authored-by: Lucas Gomide <lucaslg200@gmail.com>
* feat: add guardrail support for Agents when using direct kickoff calls
* refactor: expose guardrail func in a proper utils file
* fix: resolve Self import on python 3.10
* Add markdown attribute to Task class for formatting responses in Markdown
Co-Authored-By: Joe Moura <joao@crewai.com>
* Enhance markdown feature based on PR feedback
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix lint error and validation error in test_markdown_task.py
Co-Authored-By: Joe Moura <joao@crewai.com>
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>
* feat: support to define a guardrail task no-code
* feat: add auto-discovery for Guardrail code execution mode
* feat: handle malformed or invalid response from CodeInterpreterTool
* feat: allow to set unsafe_mode from Guardrail task
* feat: renaming GuardrailTask to TaskGuardrail
* feat: ensure guardrail is callable while initializing Task
* feat: remove Docker availability check from TaskGuardrail
The CodeInterpreterTool already ensures compliance with this requirement.
* refactor: replace if/raise with assert
For this use case `assert` is more appropriate choice
* test: remove useless or duplicated test
* fix: attempt to fix type-checker
* feat: support to define a task guardrail using YAML config
* refactor: simplify TaskGuardrail to use LLM for validation, no code generation
* docs: update TaskGuardrail doc strings
* refactor: drop task paramenter from TaskGuardrail
This parameter was used to get the model from the `task.agent` which is a quite bit redudant since we could propagate the llm directly
Previously copying a Task always returned an instance of Task even when we are cloning a subclass, such ConditionalTask.
This commit ensures that the clone preserve the original class type
* Support wildcard handling in `emit()`
Change `emit()` to call handlers registered for parent classes using
`isinstance()`. Ensures that base event handlers receive derived
events.
* Fix failing test
* Remove unused variable
* update interpolation to work with example response types in yaml docs
* make tests
* fix circular deps
* Fixing interpolation imports
* Improve test
---------
Co-authored-by: Vinicius Brasil <vini@hey.com>
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
* WIP crew events emitter
* Refactor event handling and introduce new event types
- Migrate from global `emit` function to `event_bus.emit`
- Add new event types for task failures, tool usage, and agent execution
- Update event listeners and event bus to support more granular event tracking
- Remove deprecated event emission methods
- Improve event type consistency and add more detailed event information
* Add event emission for agent execution lifecycle
- Emit AgentExecutionStarted and AgentExecutionError events
- Update CrewAgentExecutor to use event_bus for tracking agent execution
- Refactor error handling to include event emission
- Minor code formatting improvements in task.py and crew_agent_executor.py
- Fix a typo in test file
* Refactor event system and add third-party event listeners
- Move event_bus import to correct module paths
- Introduce BaseEventListener abstract base class
- Add AgentOpsListener for third-party event tracking
- Update event listener initialization and setup
- Clean up event-related imports and exports
* Enhance event system type safety and error handling
- Improve type annotations for event bus and event types
- Add null checks for agent and task in event emissions
- Update import paths for base tool and base agent
- Refactor event listener type hints
- Remove unnecessary print statements
- Update test configurations to match new event handling
* Refactor event classes to improve type safety and naming consistency
- Rename event classes to have explicit 'Event' suffix (e.g., TaskStartedEvent)
- Update import statements and references across multiple files
- Remove deprecated events.py module
- Enhance event type hints and configurations
- Clean up unnecessary event-related code
* Add default model for CrewEvaluator and fix event import order
- Set default model to "gpt-4o-mini" in CrewEvaluator when no model is specified
- Reorder event-related imports in task.py to follow standard import conventions
- Update event bus initialization method return type hint
- Export event_bus in events/__init__.py
* Fix tool usage and event import handling
- Update tool usage to use `.get()` method when checking tool name
- Remove unnecessary `__all__` export list in events/__init__.py
* Refactor Flow and Agent event handling to use event_bus
- Remove `event_emitter` from Flow class and replace with `event_bus.emit()`
- Update Flow and Agent tests to use event_bus event listeners
- Remove redundant event emissions in Flow methods
- Add debug print statements in Flow execution
- Simplify event tracking in test cases
* Enhance event handling for Crew, Task, and Event classes
- Add crew name to failed event types (CrewKickoffFailedEvent, CrewTrainFailedEvent, CrewTestFailedEvent)
- Update Task events to remove redundant task and context attributes
- Refactor EventListener to use Logger for consistent event logging
- Add new event types for Crew train and test events
- Improve event bus event tracking in test cases
* Remove telemetry and tracing dependencies from Task and Flow classes
- Remove telemetry-related imports and private attributes from Task class
- Remove `_telemetry` attribute from Flow class
- Update event handling to emit events without direct telemetry tracking
- Simplify task and flow execution by removing explicit telemetry spans
- Move telemetry-related event handling to EventListener
* Clean up unused imports and event-related code
- Remove unused imports from various event and flow-related files
- Reorder event imports to follow standard conventions
- Remove unnecessary event type references
- Simplify import statements in event and flow modules
* Update crew test to validate verbose output and kickoff_for_each method
- Enhance test_crew_verbose_output to check specific listener log messages
- Modify test_kickoff_for_each_invalid_input to use Pydantic validation error
- Improve test coverage for crew logging and input validation
* Update crew test verbose output with improved emoji icons
- Replace task and agent completion icons from 👍 to ✅
- Enhance readability of test output logging
- Maintain consistent test coverage for crew verbose output
* Add MethodExecutionFailedEvent to handle flow method execution failures
- Introduce new MethodExecutionFailedEvent in flow_events module
- Update Flow class to catch and emit method execution failures
- Add event listener for method execution failure events
- Update event-related imports to include new event type
- Enhance test coverage for method execution failure handling
* Propagate method execution failures in Flow class
- Modify Flow class to re-raise exceptions after emitting MethodExecutionFailedEvent
- Reorder MethodExecutionFailedEvent import to maintain consistent import style
* Enable test coverage for Flow method execution failure event
- Uncomment pytest.raises() in test_events to verify exception handling
- Ensure test validates MethodExecutionFailedEvent emission during flow kickoff
* Add event handling for tool usage events
- Introduce event listeners for ToolUsageFinishedEvent and ToolUsageErrorEvent
- Log tool usage events with descriptive emoji icons (✅ and ❌)
- Update event_listener to track and log tool usage lifecycle
* Reorder and clean up event imports in event_listener
- Reorganize imports for tool usage events and other event types
- Maintain consistent import ordering and remove unused imports
- Ensure clean and organized import structure in event_listener module
* moving to dedicated eventlistener
* dont forget crew level
* Refactor AgentOps event listener for crew-level tracking
- Modify AgentOpsListener to handle crew-level events
- Initialize and end AgentOps session at crew kickoff and completion
- Create agents for each crew member during session initialization
- Improve session management and event recording
- Clean up and simplify event handling logic
* Update test_events to validate tool usage error event handling
- Modify test to assert single error event with correct attributes
- Use pytest.raises() to verify error event generation
- Simplify error event validation in test case
* Improve AgentOps listener type hints and formatting
- Add string type hints for AgentOps classes to resolve potential import issues
- Clean up unnecessary whitespace and improve code indentation
- Simplify initialization and event handling logic
* Update test_events to validate multiple tool usage events
- Modify test to assert 75 events instead of a single error event
- Remove pytest.raises() check, allowing crew kickoff to complete
- Adjust event validation to support broader event tracking
* Rename event_bus to crewai_event_bus for improved clarity and specificity
- Replace all references to `event_bus` with `crewai_event_bus`
- Update import statements across multiple files
- Remove the old `event_bus.py` file
- Maintain existing event handling functionality
* Enhance EventListener with singleton pattern and color configuration
- Implement singleton pattern for EventListener to ensure single instance
- Add default color configuration using EMITTER_COLOR from constants
- Modify log method calls to use default color and remove redundant color parameters
- Improve initialization logic to prevent multiple initializations
* Add FlowPlotEvent and update event bus to support flow plotting
- Introduce FlowPlotEvent to track flow plotting events
- Replace Telemetry method with event bus emission in Flow.plot()
- Update event bus to support new FlowPlotEvent type
- Add test case to validate flow plotting event emission
* Remove RunType enum and clean up crew events module
- Delete unused RunType enum from crew_events.py
- Simplify crew_events.py by removing unnecessary enum definition
- Improve code clarity by removing unneeded imports
* 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
* Refactor event system and improve crew testing
- Extract base CrewEvent class to a new base_events.py module
- Update event imports across multiple event-related files
- Modify CrewTestStartedEvent to use eval_llm instead of openai_model_name
- Add LLM creation validation in crew testing method
- Improve type handling and event consistency
* Refactor task events to use base CrewEvent
- Move CrewEvent import from crew_events to base_events
- Remove unnecessary blank lines in task_events.py
- Simplify event class structure for task-related events
* Update AgentExecutionStartedEvent to use task_prompt
- Modify test_events.py to use task_prompt instead of inputs
- Simplify event input validation in test case
- Align with recent event system refactoring
* Improve type hinting for TaskCompletedEvent handler
- Add explicit type annotation for TaskCompletedEvent in event_listener.py
- Enhance type safety for event handling in EventListener
* Improve test_validate_tool_input_invalid_input with mock objects
- Add explicit mock objects for agent and action in test case
- Ensure proper string values for mock agent and action attributes
- Simplify test setup for ToolUsage validation method
* Remove ToolUsageStartedEvent emission in tool usage process
- Remove unnecessary event emission for tool usage start
- Simplify tool usage event handling
- Eliminate redundant event data preparation step
* refactor: clean up and organize imports in llm and flow modules
* test: Improve flow persistence test cases and logging
* fixes interpolation issues when inputs are type dict,list specifically when defined on expected_output
* improvements with type hints, doc fixes and rm print statements
* more tests
* test passing
---------
Co-authored-by: Brandon Hancock <brandon@brandonhancock.io>
* worked on foundation for new conversational crews. Now going to work on chatting.
* core loop should be working and ready for testing.
* high level chat working
* its alive!!
* Added in Joaos feedback to steer crew chats back towards the purpose of the crew
* properly return tool call result
* accessing crew directly instead of through uv commands
* everything is working for conversation now
* Fix linting
* fix llm_utils.py and other type errors
* fix more type errors
* fixing type error
* More fixing of types
* fix failing tests
* Fix more failing tests
* adding tests. cleaing up pr.
* improve
* drop old functions
* improve type hintings
* V1 working
* clean up imports and prints
* more clean up and add tests
* fixing tests
* fix test
* fix linting
* Fix tests
* Fix linting
* add doc string as requested by eduardo
* rebuilding executor
* removing langchain
* Making all tests good
* fixing types and adding ability for nor using system prompts
* improving types
* pleasing the types gods
* pleasing the types gods
* fixing parser, tools and executor
* making sure all tests pass
* final pass
* fixing type
* Updating Docs
* preparing to cut new version
* Fixed agents. Now need to fix tasks.
* Add type fixes and fix task decorator
* Clean up logs
* fix more type errors
* Revert back to required
* Undo changes.
* Remove default none for properties that cannot be none
* Clean up comments
* Implement all of Guis feedback
* Add name and expected_output to TaskOutput
This commit adds task information to the TaskOutput class. This is
useful to provide extra context to callbacks.
* Populate task name from function names
This commit populates task name from function names when using
annotations.
* WIP. Procedure appears to be working well. Working on mocking properly for tests
* All tests are passing now
* rshift working
* Add back in Gui's tool_usage fix
* WIP
* Going to start refactoring for pipeline_output
* Update terminology
* new pipeline flow with traces and usage metrics working. need to add more tests and make sure PipelineOutput behaves likew CrewOutput
* Fix pipelineoutput to look more like crewoutput and taskoutput
* Implemented additional tests for pipeline. One test is failing. Need team support
* Update docs for pipeline
* Update pipeline to properly process input and ouput dictionary
* Update Pipeline docs
* Add back in commentary at top of pipeline file
* Starting to work on router
* Drop router for now. will add in separately
* In the middle of fixing router. A ton of circular dependencies. Moving over to a new design.
* WIP.
* Fix circular dependencies and updated PipelineRouter
* Add in Eduardo feedback. Still need to add in more commentary describing the design decisions for pipeline
* Add developer notes to explain what is going on in pipelines.
* Add doc strings
* Fix missing rag datatype
* WIP. Converting usage metrics from a dict to an object
* Fix tests that were checking usage metrics
* Drop todo
* Fix 1 type error in pipeline
* Update pipeline to use UsageMetric
* Add missing doc string
* WIP.
* Change names
* Rename variables based on joaos feedback
* Fix critical circular dependency issues. Now needing to fix trace issue.
* Tests working now!
* Add more tests which showed underlying issue with traces
* Fix tests
* Remove overly complicated test
* Add router example to docs
* Clean up end of docs
* Clean up docs
* Working on creating Crew templates and pipeline templates
* WIP.
* WIP
* Fix poetry install from templates
* WIP
* Restructure
* changes for lorenze
* more todos
* WIP: create pipelines cli working
* wrapped up router
* ignore mypy src on templates
* ignored signature of copy
* fix all verbose
* rm print statements
* brought back correct folders
* fixes missing folders and then rm print statements
* fixed tests
* fixed broken test
* fixed type checker
* fixed type ignore
* ignore types for templates
* needed
* revert
* exclude only required
* rm type errors on templates
* rm excluding type checks for template files on github action
* fixed missing quotes
---------
Co-authored-by: Brandon Hancock <brandon@brandonhancock.io>
* feat: Add execution time to both task and testing feature
* feat: Remove unused functions
* feat: change test_crew to evalaute_crew to avoid issues with testing libs
* feat: fix tests
* Performed spell check across the entire documentation
Thank you once again!
* Performed spell check across the most of code base
Folders been checked:
- agents
- cli
- memory
- project
- tasks
- telemetry
- tools
- translations
* Trying to add a max_token for the agents, so they limited by number of tokens.
* Performed spell check across the rest of code base, and enahnced the yaml paraser code a little
* Small change in the main agent doc
* Improve _save_file method to handle both dict and str inputs
- Add check for dict type input
- Use json.dump for dict serialization
- Convert non-dict inputs to string
- Remove type ignore comments
---------
Co-authored-by: João Moura <joaomdmoura@gmail.com>
