* 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
* Adjust checking for callable crew object.
Changes back to how it was being done before.
Fixes#2307
* Fix specific memory reset errors.
When not initiated, the function should raise
the "memory system is not initialized" RuntimeError.
* Remove print statement
* Fixes test case
---------
Co-authored-by: Carlos Souza <carloshrsouza@gmail.com>
* 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
* fix: Correctly copy memory objects during crew training (#2593)
Co-Authored-By: Joe Moura <joao@crewai.com>
* style: Fix import order in tests/crew_test.py
Co-Authored-By: Joe Moura <joao@crewai.com>
* fix: Rely on validator for memory copy, update test assertions
Removes manual deep copy of memory objects in Crew.copy().
The Pydantic model_validator 'create_crew_memory' handles the
initialization of new memory instances for the copied crew.
Updates test_crew_copy_with_memory assertions to verify that
the private memory attributes (_short_term_memory, etc.) are
correctly initialized as new instances in the copied crew.
Co-Authored-By: Joe Moura <joao@crewai.com>
* Revert "fix: Rely on validator for memory copy, update test assertions"
This reverts commit 8702bf1e34.
* fix: Re-add manual deep copy for all memory types in Crew.copy
Addresses feedback on PR #2594 to ensure all memory objects
(short_term, long_term, entity, external, user) are correctly
deep copied using model_copy(deep=True).
Also simplifies the test case to directly verify the copy behavior
instead of relying on the train method.
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>
* 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>
- Removed unused import of BaseTool from langchain_core.tools.
- Updated type hints in crew.py to streamline code and improve readability.
- Cleaned up whitespace for better code formatting.
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.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>
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>
* 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.
---------
Co-authored-by: Brandon Hancock <brandon@brandonhancock.io>
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
* Revert "feat: add prompt observability code (#2027)"
This reverts commit 90f1bee602.
* Fix issues with flows post merge
* Decoupling telemetry and ensure tests (#2212)
* feat: Enhance event listener and telemetry tracking
- Update event listener to improve telemetry span handling
- Add execution_span field to Task for better tracing
- Modify event handling in EventListener to use new span tracking
- Remove debug print statements
- Improve test coverage for crew and flow events
- Update cassettes to reflect new event tracking behavior
* Remove telemetry references from Crew class
- Remove Telemetry import and initialization from Crew class
- Delete _telemetry attribute from class configuration
- Clean up unused telemetry-related code
* test: Improve crew verbose output test with event log filtering
- Filter out event listener logs in verbose output test
- Ensure no output when verbose is set to False
- Enhance test coverage for crew logging behavior
* dropped comment
* refactor: Improve telemetry span tracking in EventListener
- Remove `execution_span` from Task class
- Add `execution_spans` dictionary to EventListener to track spans
- Update task event handlers to use new span tracking mechanism
- Simplify span management across task lifecycle events
* lint
* Fix failing test
---------
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
* feat: Enhance event listener and telemetry tracking
- Update event listener to improve telemetry span handling
- Add execution_span field to Task for better tracing
- Modify event handling in EventListener to use new span tracking
- Remove debug print statements
- Improve test coverage for crew and flow events
- Update cassettes to reflect new event tracking behavior
* Remove telemetry references from Crew class
- Remove Telemetry import and initialization from Crew class
- Delete _telemetry attribute from class configuration
- Clean up unused telemetry-related code
* test: Improve crew verbose output test with event log filtering
- Filter out event listener logs in verbose output test
- Ensure no output when verbose is set to False
- Enhance test coverage for crew logging behavior
* dropped comment
* refactor: Improve telemetry span tracking in EventListener
- Remove `execution_span` from Task class
- Add `execution_spans` dictionary to EventListener to track spans
- Update task event handlers to use new span tracking mechanism
- Simplify span management across task lifecycle events
* lint
* 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
* Added functionality to have any llm run test functionality
* Fixed lint issues
* Fixed Linting issues
* Fixed unit test case
* Fixed unit test
* Fixed test case
* Fixed unit test case
---------
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
* 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
* Added functionality to have json format as well for the logs
* Added additional comments, refractored logging functionality
* Fixed documentation to include the new paramter
* Fixed typo
* Added a Pydantic Error Check between output_log_file and save_as_json parameter
* Removed the save_to_json parameter, incorporated the functionality directly with output_log_file
* Fixed typo
* Sorted the imports using isort
---------
Co-authored-by: Vidit Ostwal <vidit.ostwal@piramal.com>
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
* Added reset memories function inside crew class
* Fixed typos
* Refractored the code
* Refactor memory reset functionality in Crew class
- Improved error handling and logging for memory reset operations
- Added private methods to modularize memory reset logic
- Enhanced type hints and docstrings
- Updated CLI reset memories command to use new Crew method
- Added utility function to get crew instance in CLI utils
* fix linting issues
* knowledge: Add null check in reset method for storage
* cli: Update memory reset tests to use Crew's reset_memories method
* cli: Enhance memory reset command with improved error handling and validation
---------
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
* Fixing training while refactoring code
* improve prompts
* make sure to raise an error when missing training data
* Drop comment
* fix failing tests
* add clear
* drop bad code
* fix failing test
* Fix type issues pointed out by lorenze
* simplify training
* 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>
* before kickoff breaks if inputs are none.
* improve none type
* Fix failing tests
* add tests for new code
* Fix failing test
* drop extra comments
* clean up based on eduardo feedback
* 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>
When using agentops, we have the option to pass the `skip_auto_end_session` parameter, which is supposed to not end the session if the `end_session` function is called by Crew.
Now the way it works is, the `agentops.end_session` accepts `is_auto_end` flag and crewai should have passed it as `True` (its `False` by default).
I have changed the code to pass is_auto_end=True
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
* 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
* 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
---------
Co-authored-by: João Moura <joaomdmoura@gmail.com>
Co-authored-by: Lorenze Jay <lorenzejaytech@gmail.com>
