- Replace non-existent 'output_format' attribute with 'output_json'
- Update test_custom_format_instructions to use correct Pydantic model approach
- Enhance test_stop_words_configuration to properly test agent executor creation
- Update documentation example to use correct API (output_json instead of output_format)
- Validated API corrections work with local test script
Co-Authored-By: João <joao@crewai.com>
- Fix undefined i18n variable error in test_i18n_slice_access method
- Replace Mock tools with proper BaseTool instances to fix validation errors
- Add comprehensive docstrings to all test methods explaining validation purpose
- Add pytest fixtures for test isolation with @pytest.fixture(autouse=True)
- Add parametrized tests for agent initialization patterns using @pytest.mark.parametrize
- Add negative test cases for default template behavior and incomplete templates
- Remove unused Mock and patch imports to fix lint errors
- Improve test organization by moving Pydantic models to top of file
- Add metadata (title, description, categoryId, priority) to documentation frontmatter
- Add showLineNumbers to all Python code blocks for better readability
- Add explicit security warnings about stop sequence pitfalls and template injection
- Improve header hierarchy consistency using #### for subsections
- Add cross-references between troubleshooting sections
- Document default parameter behaviors explicitly
- Add additional troubleshooting steps for debugging prompts
Addresses all actionable feedback from GitHub reviews by joaomdmoura and mplachta.
Fixes failing CI tests by using proper CrewAI API patterns and BaseTool instances.
Co-Authored-By: João <joao@crewai.com>
- Create detailed guide explaining CrewAI's prompt generation system
- Document template system stored in translations/en.json
- Explain prompt assembly process using Prompts class
- Document LiteAgent prompt generation methods
- Show how to customize system/user prompts with templates
- Explain format parameter and structured output control
- Document stop words configuration through response_template
- Add practical examples for common customization scenarios
- Include test file validating all documentation examples
Addresses issue #3045: How system and user prompts are generated
Co-Authored-By: João <joao@crewai.com>
* docs: Fix major memory system documentation issues - Remove misleading deprecation warnings, fix confusing comments, clearly separate three memory approaches, provide accurate examples that match implementation
* fix: Correct broken image paths in README - Update crewai_logo.png and asset.png paths to point to docs/images/ directory instead of docs/ directly
* docs: Add system prompt transparency and customization guide - Add 'Understanding Default System Instructions' section to address black-box concerns - Document what CrewAI automatically injects into prompts - Provide code examples to inspect complete system prompts - Show 3 methods to override default instructions - Include observability integration examples with Langfuse - Add best practices for production prompt management
* docs: Fix implementation accuracy issues in memory documentation - Fix Ollama embedding URL parameter and remove unsupported Cohere input_type parameter
* docs: Reference observability docs instead of showing specific tool examples
* docs: Reorganize knowledge documentation for better developer experience - Move quickstart examples right after overview for immediate hands-on experience - Create logical learning progression: basics → configuration → advanced → troubleshooting - Add comprehensive agent vs crew knowledge guide with working examples - Consolidate debugging and troubleshooting in dedicated section - Organize best practices by topic in accordion format - Improve content flow from simple concepts to advanced features - Ensure all examples are grounded in actual codebase implementation
* docs: enhance custom LLM documentation with comprehensive examples and accurate imports
* docs: reorganize observability tools into dedicated section with comprehensive overview and improved navigation
* docs: rename how-to section to learn and add comprehensive overview page
* docs: finalize documentation reorganization and update navigation labels
* docs: enhance README with comprehensive badges, navigation links, and getting started video
* 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.
* Create Portkey-Observability-and-Guardrails.md
* crewAI update with new changes
* small change
---------
Co-authored-by: siddharthsambharia-portkey <siddhath.s@portkey.ai>
Co-authored-by: João Moura <joaomdmoura@gmail.com>
