* fix: possible fix for Thinking stuck
* feat: add agent logging events for execution tracking
- Introduced AgentLogsStartedEvent and AgentLogsExecutionEvent to enhance logging capabilities during agent execution.
- Updated CrewAgentExecutor to emit these events at the start and during execution, respectively.
- Modified EventListener to handle the new logging events and format output accordingly in the console.
- Enhanced ConsoleFormatter to display agent logs in a structured format, improving visibility of agent actions and outputs.
* drop emoji
* refactor: improve code structure and logging in LiteAgent and ConsoleFormatter
- Refactored imports in lite_agent.py for better readability.
- Enhanced guardrail property initialization in LiteAgent.
- Updated logging functionality to emit AgentLogsExecutionEvent for better tracking.
- Modified ConsoleFormatter to include tool arguments and final output in status updates.
- Improved output formatting for long text in ConsoleFormatter.
* fix tests
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Co-authored-by: Eduardo Chiarotti <dudumelgaco@hotmail.com>
* Fix issue 2993: Prevent Flow status logs from hiding human input
- Add pause_live_updates() and resume_live_updates() methods to ConsoleFormatter
- Modify _ask_human_input() to pause Flow status updates during human input
- Add comprehensive tests for pause/resume functionality and integration
- Ensure Live session is properly managed during human input prompts
- Fix prevents Flow status logs from overwriting user input prompts
Fixes#2993
Co-Authored-By: João <joao@crewai.com>
* Fix lint: Remove unused pytest import
- Remove unused pytest import from test_console_formatter_pause_resume.py
- Fixes F401 lint error identified in CI
Co-Authored-By: João <joao@crewai.com>
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Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: João <joao@crewai.com>
* feat: implement knowledge retrieval events in Agent
This commit introduces a series of knowledge retrieval events in the Agent class, enhancing its ability to handle knowledge queries. New events include KnowledgeRetrievalStartedEvent, KnowledgeRetrievalCompletedEvent, KnowledgeQueryGeneratedEvent, KnowledgeQueryFailedEvent, and KnowledgeSearchQueryCompletedEvent. The Agent now emits these events during knowledge retrieval processes, allowing for better tracking and handling of knowledge queries. Additionally, the console formatter has been updated to handle these new events, providing visual feedback during knowledge retrieval operations.
* refactor: update knowledge query handling in Agent
This commit refines the knowledge query processing in the Agent class by renaming variables for clarity and optimizing the query rewriting logic. The system prompt has been updated in the translation file to enhance clarity and context for the query rewriting process. These changes aim to improve the overall readability and maintainability of the code.
* fix: add missing newline at end of en.json file
* fix broken tests
* refactor: rename knowledge query events and enhance retrieval handling
This commit renames the KnowledgeQueryGeneratedEvent to KnowledgeQueryStartedEvent to better reflect its purpose. It also updates the event handling in the EventListener and ConsoleFormatter classes to accommodate the new event structure. Additionally, the retrieval knowledge is now included in the KnowledgeRetrievalCompletedEvent, improving the overall knowledge retrieval process.
* docs for transparancy
* refactor: improve error handling in knowledge query processing
This commit refactors the knowledge query handling in the Agent class by changing the order of checks for LLM compatibility. It now logs a warning and emits a failure event if the LLM is not an instance of BaseLLM before attempting to call the LLM. Additionally, the task_prompt attribute has been removed from the KnowledgeQueryFailedEvent, simplifying the event structure.
* test: add unit test for knowledge search query and VCR cassette
This commit introduces a new test, `test_get_knowledge_search_query`, to verify that the `_get_knowledge_search_query` method in the Agent class correctly interacts with the LLM using the appropriate prompts. Additionally, a VCR cassette is added to record the interactions with the OpenAI API for this test, ensuring consistent and reliable test results.
* 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.
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Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
* Enhance Event Listener with Rich Visualization and Improved Logging
* Add verbose flag to EventListener for controlled logging
* Update crew test to set EventListener verbose flag
* Refactor EventListener logging and visualization with improved tool usage tracking
* Improve task logging with task ID display in EventListener
* Fix EventListener tool branch removal and type hinting
* Add type hints to EventListener class attributes
* Simplify EventListener import in Crew class
* Refactor EventListener tree node creation and remove unused method
* Refactor EventListener to utilize ConsoleFormatter for improved logging and visualization
* Enhance EventListener with property setters for crew, task, agent, tool, flow, and method branches to streamline state management
* Refactor crew test to instantiate EventListener and set verbose flags for improved clarity in logging
* Keep private parts private
* Remove unused import and clean up type hints in EventListener
* Enhance flow logging in EventListener and ConsoleFormatter by including flow ID in tree creation and status updates for better traceability.
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Co-authored-by: Brandon Hancock <brandon@brandonhancock.io>
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
