* wip restrcuturing agent executor and liteagent
* fix: handle None task in AgentExecutor to prevent errors
Added a check to ensure that if the task is None, the method returns early without attempting to access task properties. This change improves the robustness of the AgentExecutor by preventing potential errors when the task is not set.
* refactor: streamline AgentExecutor initialization by removing redundant parameters
Updated the Agent class to simplify the initialization of the AgentExecutor by removing unnecessary task and crew parameters in standalone mode. This change enhances code clarity and maintains backward compatibility by ensuring that the executor is correctly configured without redundant assignments.
* ensure executors work inside a flow due to flow in flow async structure
* refactor: enhance agent kickoff preparation by separating common logic
Updated the Agent class to introduce a new private method that consolidates the common setup logic for both synchronous and asynchronous kickoff executions. This change improves code clarity and maintainability by reducing redundancy in the kickoff process, while ensuring that the agent can still execute effectively within both standalone and flow contexts.
* linting and tests
* fix test
* refactor: improve test for Agent kickoff parameters
Updated the test for the Agent class to ensure that the kickoff method correctly preserves parameters. The test now verifies the configuration of the agent after kickoff, enhancing clarity and maintainability. Additionally, the test for asynchronous kickoff within a flow context has been updated to reflect the Agent class instead of LiteAgent.
* refactor: update test task guardrail process output for improved validation
Refactored the test for task guardrail process output to enhance the validation of the output against the OpenAPI schema. The changes include a more structured request body and updated response handling to ensure compliance with the guardrail requirements. This update aims to improve the clarity and reliability of the test cases, ensuring that task outputs are correctly validated and feedback is appropriately provided.
* test fix cassette
* test fix cassette
* working
* working cassette
* refactor: streamline agent execution and enhance flow compatibility
Refactored the Agent class to simplify the execution method by removing the event loop check and clarifying the behavior when called from synchronous and asynchronous contexts. The changes ensure that the method operates seamlessly within flow methods, improving clarity in the documentation. Additionally, updated the AgentExecutor to set the response model to None, enhancing flexibility. New test cassettes were added to validate the functionality of agents within flow contexts, ensuring robust testing for both synchronous and asynchronous operations.
* fixed cassette
* Enhance Flow Execution Logic
- Introduced conditional execution for start methods in the Flow class.
- Unconditional start methods are prioritized during kickoff, while conditional starts are executed only if no unconditional starts are present.
- Improved handling of cyclic flows by allowing re-execution of conditional start methods triggered by routers.
- Added checks to continue execution chains for completed conditional starts.
These changes improve the flexibility and control of flow execution, ensuring that the correct methods are triggered based on the defined conditions.
* Enhance Agent and Flow Execution Logic
- Updated the Agent class to automatically detect the event loop and return a coroutine when called within a Flow, simplifying async handling for users.
- Modified Flow class to execute listeners sequentially, preventing race conditions on shared state during listener execution.
- Improved handling of coroutine results from synchronous methods, ensuring proper execution flow and state management.
These changes enhance the overall execution logic and user experience when working with agents and flows in CrewAI.
* Enhance Flow Listener Logic and Agent Imports
- Updated the Flow class to track fired OR listeners, ensuring that multi-source OR listeners only trigger once during execution. This prevents redundant executions and improves flow efficiency.
- Cleared fired OR listeners during cyclic flow resets to allow re-execution in new cycles.
- Modified the Agent class imports to include Coroutine from collections.abc, enhancing type handling for asynchronous operations.
These changes improve the control and performance of flow execution in CrewAI, ensuring more predictable behavior in complex scenarios.
* adjusted test due to new cassette
* ensure we dont finalize batch on just a liteagent finishing
* feat: cancellable parallelized flow methods
* feat: allow methods to be cancelled & run parallelized
* feat: ensure state is thread safe through proxy
* fix: check for proxy state
* fix: mimic BaseModel method
* chore: update final attr checks; test
* better description
* fix test
* chore: update test assumptions
* extra
---------
Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
* doc changes for better deplyment guidelines and checklist
* chore: remove .claude folder from version control
The .claude folder contains local Claude Code skills and configuration
that should not be tracked in the repository. Already in .gitignore.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* Better project structure for flows
* docs.json updated structure
* Ko and Pt traslations for deploying guidelines to AMP
* fix broken links
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
- Updated the `supports_stop_words` method to accurately reflect support for stop sequences based on model type, specifically excluding GPT-5 and O-series models.
- Added comprehensive tests to verify that GPT-5 family and O-series models do not support stop words, ensuring correct behavior in completion parameter preparation.
- Ensured that stop words are not included in parameters for unsupported models while maintaining expected behavior for supported models.
This commit fixes a bug where `parent_flow` was not being set because
the maximum depth was not sufficient to search for an instance of `Flow`
in the current call stack frame during Flow instantiation.
* WIP docs for pii-redaction feat
* fix
* updated image
* Update PII Redaction documentation to clarify Enterprise plan requirements and version constraints
* visual re-ordering
* dropping not useful info
* improve docs
* better wording
* Add PII Redaction feature documentation in Korean and Portuguese, including details on activation, supported entity types, and best practices for usage.
- Added new features including native async chain for a2a, a2a update mechanisms, and global flow configuration for human-in-the-loop feedback.
- Improved event handling with enhancements to EventListener and TraceCollectionListener.
- Fixed bugs related to missing a2a dependencies and WorkOS login polling.
- Updated documentation for webhook-streaming and adjusted language in AOP to AMP documentation.
- Acknowledged contributors for this release.
* fix: handle HumanFeedbackPending in flow error management
Updated the flow error handling to treat HumanFeedbackPending as expected control flow rather than an error. This change ensures that the flow can appropriately manage human feedback scenarios without signaling an error, improving the robustness of the flow execution.
* fix: improve error handling for HumanFeedbackPending in flow execution
Refined the flow error management to emit a paused event for HumanFeedbackPending exceptions instead of treating them as failures. This enhancement allows the flow to better manage human feedback scenarios, ensuring that the execution state is preserved and appropriately handled without signaling an error. Regular failure events are still emitted for other exceptions, maintaining robust error reporting.
Updated the flow error handling to treat HumanFeedbackPending as expected control flow rather than an error. This change ensures that the flow can appropriately manage human feedback scenarios without signaling an error, improving the robustness of the flow execution.
* Adding usage info everywhere
* Changing the check
* Changing the logic
* Adding tests
* Adding casellets
* Minor change
* Fixing testcase
* remove the duplicated test case, thanks to cursor
* Adding async test cases
* Updating test case
---------
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
* feat: Introduce global flow configuration for human-in-the-loop feedback
- Added a new `flow_config` module to manage global Flow configuration, allowing customization of Flow behavior at runtime.
- Integrated the `hitl_provider` attribute to specify the human-in-the-loop feedback provider, enhancing flexibility in feedback collection.
- Updated the `human_feedback` function to utilize the configured HITL provider, improving the handling of feedback requests.
* TYPO
