* 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.
* chore: update dependencies and versioning for CrewAI
- Bump `crewai-tools` dependency version from `0.71.0` to `0.73.0` in `pyproject.toml`.
- Update CrewAI version from `0.186.1` to `0.193.0` in `__init__.py`.
- Adjust dependency versions in CLI templates for crew, flow, and tool to reflect the new CrewAI version.
This update ensures compatibility with the latest features and improvements in CrewAI.
* remove embedchain mock
* fix: remove last embedchain mocks
* fix: remove langchain_openai from tests
---------
Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
- Update to Python 3.10+ typing across LLM, callbacks, storage, and errors
- Complete typing updates for crew_chat and hitl
- Add stop attr to mock LLM, suppress test warnings
- Add type-ignore for aisuite import
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
fix: resolve flaky tests and race conditions in test suite
- Fix telemetry/event tests by patching class methods instead of instances
- Use unique temp files/directories to prevent CI race conditions
- Reset singleton state between tests
- Mock embedchain.Client.setup() to prevent JSON corruption
- Rename test files to test_*.py convention
- Move agent tests to tests/agents directory
- Fix repeated tool usage detection
- Remove database-dependent tools causing initialization errors
Add `__init__.py` files to 20 directories to conform with Python package standards. This ensures directories are properly recognized as packages, enabling cleaner imports.
* feat: add OpenAI agent adapter implementation
- Introduced OpenAIAgentAdapter class to facilitate interaction with OpenAI Assistants.
- Implemented methods for task execution, tool configuration, and response processing.
- Added support for converting CrewAI tools to OpenAI format and handling delegation tools.
* created an adapter for the delegate and ask_question tools
* delegate and ask_questions work and it delegates to crewai agents*
* refactor: introduce OpenAIAgentToolAdapter for tool management
- Created OpenAIAgentToolAdapter class to encapsulate tool configuration and conversion for OpenAI Assistant.
- Removed tool configuration logic from OpenAIAgentAdapter and integrated it into the new adapter.
- Enhanced the tool conversion process to ensure compatibility with OpenAI's requirements.
* feat: implement BaseAgentAdapter for agent integration
- Introduced BaseAgentAdapter as an abstract base class for agent adapters in CrewAI.
- Defined common interface and methods for configuring tools and structured output.
- Updated OpenAIAgentAdapter to inherit from BaseAgentAdapter, enhancing its structure and functionality.
* feat: add LangGraph agent and tool adapter for CrewAI integration
- Introduced LangGraphAgentAdapter to facilitate interaction with LangGraph agents.
- Implemented methods for task execution, context handling, and tool configuration.
- Created LangGraphToolAdapter to convert CrewAI tools into LangGraph-compatible format.
- Enhanced error handling and logging for task execution and streaming processes.
* feat: enhance LangGraphToolAdapter and improve conversion instructions
- Added type hints for better clarity and type checking in LangGraphToolAdapter.
- Updated conversion instructions to ensure compatibility with optional LLM checks.
* feat: integrate structured output handling in LangGraph and OpenAI agents
- Added LangGraphConverterAdapter for managing structured output in LangGraph agents.
- Enhanced LangGraphAgentAdapter to utilize the new converter for system prompt and task execution.
- Updated LangGraphToolAdapter to use StructuredTool for better compatibility.
- Introduced OpenAIConverterAdapter for structured output management in OpenAI agents.
- Improved task execution flow in OpenAIAgentAdapter to incorporate structured output configuration and post-processing.
* feat: implement BaseToolAdapter for tool integration
- Introduced BaseToolAdapter as an abstract base class for tool adapters in CrewAI.
- Updated LangGraphToolAdapter and OpenAIAgentToolAdapter to inherit from BaseToolAdapter, enhancing their structure and functionality.
- Improved tool configuration methods to support better integration with various frameworks.
- Added type hints and documentation for clarity and maintainability.
* feat: enhance OpenAIAgentAdapter with configurable agent properties
- Refactored OpenAIAgentAdapter to accept agent configuration as an argument.
- Introduced a method to build a system prompt for the OpenAI agent, improving task execution context.
- Updated initialization to utilize role, goal, and backstory from kwargs, enhancing flexibility in agent setup.
- Improved tool handling and integration within the adapter.
* feat: enhance agent adapters with structured output support
- Introduced BaseConverterAdapter as an abstract class for structured output handling.
- Implemented LangGraphConverterAdapter and OpenAIConverterAdapter to manage structured output in their respective agents.
- Updated BaseAgentAdapter to accept an agent configuration dictionary during initialization.
- Enhanced LangGraphAgentAdapter to utilize the new converter and improved tool handling.
- Added methods for configuring structured output and enhancing system prompts in converter adapters.
* refactor: remove _parse_tools method from OpenAIAgentAdapter and BaseAgent
- Eliminated the _parse_tools method from OpenAIAgentAdapter and its abstract declaration in BaseAgent.
- Cleaned up related test code in MockAgent to reflect the removal of the method.
* also removed _parse_tools here as not used
* feat: add dynamic import handling for LangGraph dependencies
- Implemented conditional imports for LangGraph components to handle ImportError gracefully.
- Updated LangGraphAgentAdapter initialization to check for LangGraph availability and raise an informative error if dependencies are missing.
- Enhanced the agent adapter's robustness by ensuring it only initializes components when the required libraries are present.
* fix: improve error handling for agent adapters
- Updated LangGraphAgentAdapter to raise an ImportError with a clear message if LangGraph dependencies are not installed.
- Refactored OpenAIAgentAdapter to include a similar check for OpenAI dependencies, ensuring robust initialization and user guidance for missing libraries.
- Enhanced overall error handling in agent adapters to prevent runtime issues when dependencies are unavailable.
* refactor: enhance tool handling in agent adapters
- Updated BaseToolAdapter to initialize original and converted tools in the constructor.
- Renamed method `all_tools` to `tools` for clarity in BaseToolAdapter.
- Added `sanitize_tool_name` method to ensure tool names are API compatible.
- Modified LangGraphAgentAdapter to utilize the updated tool handling and ensure proper tool configuration.
- Refactored LangGraphToolAdapter to streamline tool conversion and ensure consistent naming conventions.
* feat: emit AgentExecutionCompletedEvent in agent adapters
- Added emission of AgentExecutionCompletedEvent in both LangGraphAgentAdapter and OpenAIAgentAdapter to signal task completion.
- Enhanced event handling to include agent, task, and output details for better tracking of execution results.
* docs: Enhance BaseConverterAdapter documentation
- Added a detailed docstring to the BaseConverterAdapter class, outlining its purpose and the expected functionality for all converter adapters.
- Updated the post_process_result method's docstring to specify the expected format of the result as a string.
* docs: Add comprehensive guide for bringing custom agents into CrewAI
- Introduced a new documentation file detailing the process of integrating custom agents using the BaseAgentAdapter, BaseToolAdapter, and BaseConverter.
- Included step-by-step instructions for creating custom adapters, configuring tools, and handling structured output.
- Provided examples for implementing adapters for various frameworks, enhancing the usability of CrewAI for developers.
* feat: Introduce adapted_agent flag in BaseAgent and update BaseAgentAdapter initialization
- Added an `adapted_agent` boolean field to the BaseAgent class to indicate if the agent is adapted.
- Updated the BaseAgentAdapter's constructor to pass `adapted_agent=True` to the superclass, ensuring proper initialization of the new field.
* feat: Enhance LangGraphAgentAdapter to support optional agent configuration
- Updated LangGraphAgentAdapter to conditionally apply agent configuration when creating the agent graph, allowing for more flexible initialization.
- Modified LangGraphToolAdapter to ensure only instances of BaseTool are converted, improving tool compatibility and handling.
* feat: Introduce OpenAIConverterAdapter for structured output handling
- Added OpenAIConverterAdapter to manage structured output conversion for OpenAI agents, enhancing their ability to process and format results.
- Updated OpenAIAgentAdapter to utilize the new converter for configuring structured output and post-processing results.
- Removed the deprecated get_output_converter method from OpenAIAgentAdapter.
- Added unit tests for BaseAgentAdapter and BaseToolAdapter to ensure proper functionality and integration of new features.
* feat: Enhance tool adapters to support asynchronous execution
- Updated LangGraphToolAdapter and OpenAIAgentToolAdapter to handle asynchronous tool execution by checking if the output is awaitable.
- Introduced `inspect` import to facilitate the awaitability check.
- Refactored tool wrapper functions to ensure proper handling of both synchronous and asynchronous tool results.
* fix: Correct method definition syntax and enhance tool adapter implementation
- Updated the method definition for `configure_structured_output` to include the `def` keyword for clarity.
- Added an asynchronous tool wrapper to ensure tools can operate in both synchronous and asynchronous contexts.
- Modified the constructor of the custom converter adapter to directly assign the agent adapter, improving clarity and functionality.
* linted
* refactor: Improve tool processing logic in BaseAgent
- Added a check to return an empty list if no tools are provided.
- Simplified the tool attribute validation by using a list of required attributes.
- Removed commented-out abstract method definition for clarity.
* refactor: Simplify tool handling in agent adapters
- Changed default value of `tools` parameter in LangGraphAgentAdapter to None for better handling of empty tool lists.
- Updated tool initialization in both LangGraphAgentAdapter and OpenAIAgentAdapter to directly pass the `tools` parameter, removing unnecessary list handling.
- Cleaned up commented-out code in OpenAIConverterAdapter to improve readability.
* refactor: Remove unused stream_task method from LangGraphAgentAdapter
- Deleted the `stream_task` method from LangGraphAgentAdapter to streamline the code and eliminate unnecessary complexity.
- This change enhances maintainability by focusing on essential functionalities within the agent adapter.
* WIP
* WIP
* wip
* wip
* WIP
* More WIP
* Its working but needs a massive clean up
* output type works now
* Usage metrics fixed
* more testing
* WIP
* cleaning up
* Update logger
* 99% done. Need to make docs match new example
* cleanup
* drop hard coded examples
* docs
* Clean up
* Fix errors
* Trying to fix CI issues
* more type checker fixes
* More type checking fixes
* Update LiteAgent documentation for clarity and consistency; replace WebsiteSearchTool with SerperDevTool, and improve formatting in examples.
* fix fingerprinting issues
* fix type-checker
* Fix type-checker issue by adding type ignore comment for cache read in ToolUsage class
* Add optional agent parameter to CrewAgentParser and enhance action handling logic
* Remove unused parameters from ToolUsage instantiation in tests and clean up debug print statement in CrewAgentParser.
* Remove deprecated test files and examples for LiteAgent; add comprehensive tests for LiteAgent functionality, including tool usage and structured output handling.
* Remove unused variable 'result' from ToolUsage class to clean up code.
* Add initialization for 'result' variable in ToolUsage class to resolve type-checker warnings
* Refactor agent_utils.py by removing unused event imports and adding missing commas in function definitions. Update test_events.py to reflect changes in expected event counts and adjust assertions accordingly. Modify test_tools_emits_error_events.yaml to include new headers and update response content for consistency with recent API changes.
* Enhance tests in crew_test.py by verifying cache behavior in test_tools_with_custom_caching and ensuring proper agent initialization with added commas in test_crew_kickoff_for_each_works_with_manager_agent_copy.
* Update agent tests to reflect changes in expected call counts and improve response formatting in YAML cassette. Adjusted mock call count from 2 to 3 and refined interaction formats for clarity and consistency.
* Refactor agent tests to update model versions and improve response formatting in YAML cassettes. Changed model references from 'o1-preview' to 'o3-mini' and adjusted interaction formats for consistency. Enhanced error handling in context length tests and refined mock setups for better clarity.
* Update tool usage logging to ensure tool arguments are consistently formatted as strings. Adjust agent test cases to reflect changes in maximum iterations and expected outputs, enhancing clarity in assertions. Update YAML cassettes to align with new response formats and improve overall consistency across tests.
* Update YAML cassette for LLM tests to reflect changes in response structure and model version. Adjusted request and response headers, including updated content length and user agent. Enhanced token limits and request counts for improved testing accuracy.
* Update tool usage logging to store tool arguments as native types instead of strings, enhancing data integrity and usability.
* Refactor agent tests by removing outdated test cases and updating YAML cassettes to reflect changes in tool usage and response formats. Adjusted request and response headers, including user agent and content length, for improved accuracy in testing. Enhanced interaction formats for consistency across tests.
* Add Excalidraw diagram file for visual representation of input-output flow
Created a new Excalidraw file that includes a diagram illustrating the input box, database, and output box with connecting arrows. This visual aid enhances understanding of the data flow within the application.
* Remove redundant error handling for action and final answer in CrewAgentParser. Update tests to reflect this change by deleting the corresponding test case.
---------
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
* 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
* Exploring output being passed to tool selector to see if we can better format data
* WIP. Adding JSON repair functionality
* Almost done implementing JSON repair. Testing fixes vs current base case.
* More action cleanup with additional tests
* WIP. Trying to figure out what is going on with tool descriptions
* Update tool description generation
* WIP. Trying to find out what is causing the tools to duplicate
* Replacing tools properly instead of duplicating them accidentally
* Fixing issues for MR
* Update dependencies for JSON_REPAIR
* More cleaning up pull request
* preppering for call
* Fix type-checking issues
---------
Co-authored-by: João Moura <joaomdmoura@gmail.com>
