* feat: Add inject_date flag to Agent for automatic date injection
Co-Authored-By: Joe Moura <joao@crewai.com>
* feat: Add date_format parameter and error handling to inject_date feature
Co-Authored-By: Joe Moura <joao@crewai.com>
* fix: Update test implementation for inject_date feature
Co-Authored-By: Joe Moura <joao@crewai.com>
* fix: Add date format validation to prevent invalid formats
Co-Authored-By: Joe Moura <joao@crewai.com>
* docs: Update documentation for inject_date feature
Co-Authored-By: Joe Moura <joao@crewai.com>
* unnecesary
* new tests
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>
Co-authored-by: João Moura <joaomdmoura@gmail.com>
* Add reasoning attribute to Agent class
Co-Authored-By: Joe Moura <joao@crewai.com>
* Address PR feedback: improve type hints, error handling, refactor reasoning handler, and enhance tests and docs
Co-Authored-By: Joe Moura <joao@crewai.com>
* Implement function calling for reasoning and move prompts to translations
Co-Authored-By: Joe Moura <joao@crewai.com>
* Simplify function calling implementation with better error handling
Co-Authored-By: Joe Moura <joao@crewai.com>
* Enhance system prompts to leverage agent context (role, goal, backstory)
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix lint and type-checker issues
Co-Authored-By: Joe Moura <joao@crewai.com>
* Enhance system prompts to better leverage agent context
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix backstory access in reasoning handler for Python 3.12 compatibility
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>
Co-authored-by: João Moura <joaomdmoura@gmail.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.
* Enhance knowledge management in CrewAI
- Added `KnowledgeConfig` class to configure knowledge retrieval parameters such as `limit` and `score_threshold`.
- Updated `Agent` and `Crew` classes to utilize the new knowledge configuration for querying knowledge sources.
- Enhanced documentation to clarify the addition of knowledge sources at both agent and crew levels.
- Introduced new tips in documentation to guide users on knowledge source management and configuration.
* Refactor knowledge configuration parameters in CrewAI
- Renamed `limit` to `results_limit` in `KnowledgeConfig`, `query_knowledge`, and `query` methods for consistency and clarity.
- Updated related documentation to reflect the new parameter name, ensuring users understand the configuration options for knowledge retrieval.
* Refactor agent tests to utilize mock knowledge storage
- Updated test cases in `agent_test.py` to use `KnowledgeStorage` for mocking knowledge sources, enhancing test reliability and clarity.
- Renamed `limit` to `results_limit` in `KnowledgeConfig` for consistency with recent changes.
- Ensured that knowledge queries are properly mocked to return expected results during tests.
* Add VCR support for agent tests with query limits and score thresholds
- Introduced `@pytest.mark.vcr` decorator in `agent_test.py` for tests involving knowledge sources, ensuring consistent recording of HTTP interactions.
- Added new YAML cassette files for `test_agent_with_knowledge_sources_with_query_limit_and_score_threshold` and `test_agent_with_knowledge_sources_with_query_limit_and_score_threshold_default`, capturing the expected API responses for these tests.
- Enhanced test reliability by utilizing VCR to manage external API calls during testing.
* Update documentation to format parameter names in code style
- Changed the formatting of `results_limit` and `score_threshold` in the documentation to use code style for better clarity and emphasis.
- Ensured consistency in documentation presentation to enhance user understanding of configuration options.
* Enhance KnowledgeConfig with field descriptions
- Updated `results_limit` and `score_threshold` in `KnowledgeConfig` to use Pydantic's `Field` for improved documentation and clarity.
- Added descriptions to both parameters to provide better context for their usage in knowledge retrieval configuration.
* docstrings added
* feat: support defining any memory in an isolated way
This change makes it easier to use a specific memory type without unintentionally enabling all others.
Previously, setting memory=True would implicitly configure all available memories (like LTM and STM), which might not be ideal in all cases. For example, when building a chatbot that only needs an external memory, users were forced to also configure LTM and STM — which rely on default OpenAPI embeddings — even if they weren’t needed.
With this update, users can now define a single memory in isolation, making the configuration process simpler and more flexible.
* feat: add tests to ensure we are able to use contextual memory by set individual memories
* docs: enhance memory documentation
* feat: warn when long-term memory is defined but entity memory is not
* KISS: Refactor LiteAgent integration in flows to use Agents instead. Update documentation and examples to reflect changes in class usage, including async support and structured output handling. Enhance tests for Agent functionality and ensure compatibility with new features.
* lint fix
* dropped for clarity
* fix: surfacing properly supported types by Mem0Storage
* feat: prepare Mem0Storage to accept config paramenter
We're planning to remove `memory_config` soon. This commit kindly prepare this storage to accept the config provided directly
* feat: add external memory
* fix: cleanup Mem0 warning while adding messages to the memory
* feat: support set the current crew in memory
This can be useful when a memory is initialized before the crew, but the crew might still be a very relevant attribute
* fix: allow to reset only an external_memory from crew
* test: add external memory test
* test: ensure the config takes precedence over memory_config when setting mem0
* fix: support to provide a custom storage to External Memory
* docs: add docs about external memory
* chore: add warning messages about the deprecation of UserMemory
* fix: fix typing check
---------
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
* 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>
* Add support for custom LLM implementations
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix import sorting and type annotations
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix linting issues with import sorting
Co-Authored-By: Joe Moura <joao@crewai.com>
* Fix type errors in crew.py by updating tool-related methods to return List[BaseTool]
Co-Authored-By: Joe Moura <joao@crewai.com>
* Enhance custom LLM implementation with better error handling, documentation, and test coverage
Co-Authored-By: Joe Moura <joao@crewai.com>
* Refactor LLM module by extracting BaseLLM to a separate file
This commit moves the BaseLLM abstract base class from llm.py to a new file llms/base_llm.py to improve code organization. The changes include:
- Creating a new file src/crewai/llms/base_llm.py
- Moving the BaseLLM class to the new file
- Updating imports in __init__.py and llm.py to reflect the new location
- Updating test cases to use the new import path
The refactoring maintains the existing functionality while improving the project's module structure.
* Add AISuite LLM support and update dependencies
- Integrate AISuite as a new third-party LLM option
- Update pyproject.toml and uv.lock to include aisuite package
- Modify BaseLLM to support more flexible initialization
- Remove unnecessary LLM imports across multiple files
- Implement AISuiteLLM with basic chat completion functionality
* Update AISuiteLLM and LLM utility type handling
- Modify AISuiteLLM to support more flexible input types for messages
- Update type hints in AISuiteLLM to allow string or list of message dictionaries
- Enhance LLM utility function to support broader LLM type annotations
- Remove default `self.stop` attribute from BaseLLM initialization
* Update LLM imports and type hints across multiple files
- Modify imports in crew_chat.py to use LLM instead of BaseLLM
- Update type hints in llm_utils.py to use LLM type
- Add optional `stop` parameter to BaseLLM initialization
- Refactor type handling for LLM creation and usage
* Improve stop words handling in CrewAgentExecutor
- Add support for handling existing stop words in LLM configuration
- Ensure stop words are correctly merged and deduplicated
- Update type hints to support both LLM and BaseLLM types
* Remove abstract method set_callbacks from BaseLLM class
* Enhance CustomLLM and JWTAuthLLM initialization with model parameter
- Update CustomLLM to accept a model parameter during initialization
- Modify test cases to include the new model argument
- Ensure JWTAuthLLM and TimeoutHandlingLLM also utilize the model parameter in their constructors
- Update type hints in create_llm function to support both LLM and BaseLLM types
* Enhance create_llm function to support BaseLLM type
- Update the create_llm function to accept both LLM and BaseLLM instances
- Ensure compatibility with existing LLM handling logic
* Update type hint for initialize_chat_llm to support BaseLLM
- Modify the return type of initialize_chat_llm function to allow for both LLM and BaseLLM instances
- Ensure compatibility with recent changes in create_llm function
* Refactor AISuiteLLM to include tools parameter in completion methods
- Update the _prepare_completion_params method to accept an optional tools parameter
- Modify the chat completion method to utilize the new tools parameter for enhanced functionality
- Clean up print statements for better code clarity
* Remove unused tool_calls handling in AISuiteLLM chat completion method for cleaner code.
* Refactor Crew class and LLM hierarchy for improved type handling and code clarity
- Update Crew class methods to enhance readability with consistent formatting and type hints.
- Change LLM class to inherit from BaseLLM for better structure.
- Remove unnecessary type checks and streamline tool handling in CrewAgentExecutor.
- Adjust BaseLLM to provide default implementations for stop words and context window size methods.
- Clean up AISuiteLLM by removing unused methods related to stop words and context window size.
* Remove unused `stream` method from `BaseLLM` class to enhance code clarity and maintainability.
---------
Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
Co-authored-by: João Moura <joaomdmoura@gmail.com>
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
- Modify `Agent` class to add `set_knowledge` method
- Allow setting embedder from crew-level configuration
- Remove `_set_knowledge` method from initialization
- Update `Crew` class to set agent knowledge during agent setup
- Add default implementation in `BaseAgent` for compatibility
* 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
* clean up. fix type safety. address memory config docs
* improve manager
* Include fix for o1 models not supporting system messages
* more broad with o1
* address fix: Typo in expected_output string #2045
* drop prints
* drop prints
* wip
* wip
* fix failing memory tests
* Fix memory provider issue
* clean up short term memory
* revert ltm
* drop
* clean up linting issues
* more linting
* clean up. fix type safety. address memory config docs
* improve manager
* Include fix for o1 models not supporting system messages
* more broad with o1
* address fix: Typo in expected_output string #2045
* drop prints
* drop prints
* wip
* wip
* fix failing memory tests
* Fix memory provider issue
* clean up short term memory
* revert ltm
* drop
* fix breakage when cloning agent/crew using knowledge_sources
* fixed typo
* better
* ensure use of other knowledge storage works
* fix copy and custom storage
* added tests
* normalized name
* updated cassette
* fix test
* remove fixture
* fixed test
* fix
* add fixture to this
* add fixture to this
* patch twice since
* fix again
* with fixtures
* better mocks
* fix
* simple
* try
* another
* hopefully fixes test
* hopefully fixes test
* this should fix it !
* WIP: test check with prints
* try this
* exclude knowledge
* fixes
* just drop clone for now
* rm print statements
* printing agent_copy
* checker
* linted
* cleanup
* better docs
---------
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
* wip
* More clean up
* Fix error
* clean up test
* Improve chat calling messages
* crewai chat improvements
* working but need to clean up
* Clean up chat
* Improving tool calling to pass dictionaries instead of strings
* Fix issues with parsing none/null
* remove prints and unnecessary comments
* Fix crew_test issues with function calling
* improve prompting
* add back in support for add_image
* add tests for tool validation
* revert back to figure out why tests are timing out
* Update cassette
* trying to find what is timing out
* add back in guardrails
* add back in manager delegation tests
* Trying to fix tests
* Force test to pass
* Trying to fix tests
* add in more role tests
* add back old tool validation
* updating tests
* vcr
* Fix tests
* improve function llm logic
* vcr 2
* drop llm
* Failing test
* add more tests back in
* Revert tool validation
* 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
* apply agent ops changes and resolve merge conflicts
* Trying to fix tests
* add back in vcr
* update tools
* remove pkg_resources which was causing issues
* Fix tests
* experimenting to see if unique content is an issue with knowledge
* experimenting to see if unique content is an issue with knowledge
* update chromadb which seems to have issues with upsert
* generate new yaml for failing test
* Investigating upsert
* Drop patch
* Update casettes
* Fix duplicate document issue
* more fixes
* add back in vcr
* new cassette for test
---------
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
* incorporate #1683
* add in --version flag to cli. closes#1679.
* Fix env issue
* Add in suggestions from @caike to make sure ragstorage doesnt exceed os file limit. Also, included additional checks to support windows.
* remove poetry.lock as pointed out by @sanders41 in #1574.
* Incorporate feedback from crewai reviewer
* Incorporate @lorenzejay feedback
* added knowledge to agent level
* linted
* added doc
* added from suggestions
* added test
* fixes from discussion
* fix docs
* fix test
* rm cassette for knowledge_sources test as its a mock and update agent doc string
* fix test
* rm unused
* linted
* 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
* initial knowledge
* WIP
* Adding core knowledge sources
* Improve types and better support for file paths
* added additional sources
* fix linting
* update yaml to include optional deps
* adding in lorenze feedback
* ensure embeddings are persisted
* improvements all around Knowledge class
* return this
* properly reset memory
* properly reset memory+knowledge
* consolodation and improvements
* linted
* cleanup rm unused embedder
* fix test
* fix duplicate
* generating cassettes for knowledge test
* updated default embedder
* None embedder to use default on pipeline cloning
* improvements
* fixed text_file_knowledge
* mypysrc fixes
* type check fixes
* added extra cassette
* just mocks
* linted
* mock knowledge query to not spin up db
* linted
* verbose run
* put a flag
* fix
* adding docs
* better docs
* improvements from review
* more docs
* linted
* rm print
* more fixes
* clearer docs
* added docstrings and type hints for cli
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Co-authored-by: João Moura <joaomdmoura@gmail.com>
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
