To solve :
I encountered an error while trying to use the tool. This was the error: DuckDuckGoSearchRun._run() got an unexpected keyword argument 'q'.
Tool duckduckgo_search accepts these inputs: A wrapper around DuckDuckGo Search. Useful for when you need to answer questions about current events. Input should be a search query.
refer : https://github.com/joaomdmoura/crewAI/issues/316
The memory documentation left me with a lot of questions. After I went through the code to find an answer. I added this paragraph to explain what I found. Hope this is helpful.
* feat: add planning feature to crew
* feat: add test to planning handler and change to execute_async method
* docs: add planning parameter to the Core documentation
* docs: add planning docs
* fix: fix type checking issue
* fix: test and logic
* Cleaned up task execution to now have separate paths for async and sync execution. Updating all kickoff functions to return CrewOutput. WIP. Waiting for Joao feedback on async task execution with task_output
* Consistently storing async and sync output for context
* outline tests I need to create going forward
* Major rehaul of TaskOutput and CrewOutput. Updated all tests to work with new change. Need to add in a few final tricky async tests and add a few more to verify output types on TaskOutput and CrewOutput.
* Encountering issues with callback. Need to test on main. WIP
* working on tests. WIP
* WIP. Figuring out disconnect issue.
* Cleaned up logs now that I've isolated the issue to the LLM
* more wip.
* WIP. It looks like usage metrics has always been broken for async
* Update parent crew who is managing for_each loop
* Merge in main to bugfix/kickoff-for-each-usage-metrics
* Clean up code for review
* Add new tests
* Final cleanup. Ready for review.
* Moving copy functionality from Agent to BaseAgent
* Fix renaming issue
* Fix linting errors
* use BaseAgent instead of Agent where applicable
* Fixing missing function. Working on tests.
* WIP. Needing team to review change
* Fixing issues brought about by merge
* WIP: need to fix json encoder
* WIP need to fix encoder
* WIP
* WIP: replay working with async. need to add tests
* Implement major fixes from yesterdays group conversation. Now working on tests.
* The majority of tasks are working now. Need to fix converter class
* Fix final failing test
* Fix linting and type-checker issues
* Add more tests to fully test CrewOutput and TaskOutput changes
* Add in validation for async cannot depend on other async tasks.
* WIP: working replay feat fixing inputs, need tests
* WIP: core logic of seq and heir for executing tasks added into one
* Update validators and tests
* better logic for seq and hier
* replay working for both seq and hier just need tests
* fixed context
* added cli command + code cleanup TODO: need better refactoring
* refactoring for cleaner code
* added better tests
* removed todo comments and fixed some tests
* fix logging now all tests should pass
* cleaner code
* ensure replay is delcared when replaying specific tasks
* ensure hierarchical works
* better typing for stored_outputs and separated task_output_handler
* added better tests
* added replay feature to crew docs
* easier cli command name
* fixing changes
* using sqllite instead of .json file for logging previous task_outputs
* tools fix
* added to docs and fixed tests
* fixed .db
* fixed docs and removed unneeded comments
* separating ltm and replay db
* fixed printing colors
* added how to doc
---------
Co-authored-by: Brandon Hancock <brandon@brandonhancock.io>
- Added detailed steps for training the crew programmatically.
- Clarified the distinction between using the CLI and programmatic approaches.
This update makes it easier for users to understand how to train their crew both through the CLI and programmatically, whether using a UI or API endpoints.
Again Thank you to the author for the great project and the excellent foundation provided!
To Resolve :
pydantic_core._pydantic_core.ValidationError: 1 validation error for Task
expected_output
Field required [type=missing, input_value=, input_type=dict]
For further information visit https://errors.pydantic.dev/2.6/v/missing
"Expected Output" is mandatory now as it forces people to be specific about the expected result and get better result
refer : https://github.com/joaomdmoura/crewAI/issues/308
- Added a "Parameters" column to attribute tables. Improved overall document formatting for enhanced readability and ease of use.
Thank you to the author for the great project and the excellent foundation provided!
Revised to utilize Ollama from langchain.llms instead as the functionality from the other method simply doesn't work when delegating.
Co-authored-by: João Moura <joaomdmoura@gmail.com>
* better spacing
* works with llama index
* works on langchain custom just need delegation to work
* cleanup for custom_agent class
* works with different argument expectations for agent_executor
* cleanup for hierarchial process, better agent_executor args handler and added to the crew agent doc page
* removed code examples for langchain + llama index, added to docs instead
* added key output if return is not a str for and added some tests
* added hinting for CustomAgent class
* removed pass as it was not needed
* closer just need to figuire ou agentTools
* running agents - llamaindex and langchain with base agent
* some cleanup on baseAgent
* minimum for agent to run for base class and ensure it works with hierarchical process
* cleanup for original agent to take on BaseAgent class
* Agent takes on langchainagent and cleanup across
* token handling working for usage_metrics to continue working
* installed llama-index, updated docs and added better name
* fixed some type errors
* base agent holds token_process
* heirarchail process uses proper tools and no longer relies on hasattr for token_processes
* removal of test_custom_agent_executions
* this fixes copying agents
* leveraging an executor class for trigger llamaindex agent
* llama index now has ask_human
* executor mixins added
* added output converter base class
* type listed
* cleanup for output conversions and tokenprocess eliminated redundancy
* properly handling tokens
* simplified token calc handling
* original agent with base agent builder structure setup
* better docs
* no more llama-index dep
* cleaner docs
* test fixes
* poetry reverts and better docs
* base_agent_tools set for third party agents
* updated task and test fix
* feat: add CodeInterpreterTool to run when enable code execution is allowed on agent
* feat: change to allow_code_execution
* feat: add readme for CodeInterpreterTool
* mentioning ollama on the docs as embedder
* lowering barrier to match tool with simialr name
* Fixing agent tools to support co_worker
* Adding new tests
* Fixing type"
* updating tests
* fixing conflict
Created a short documentation on how to use Llama2 locally with crewAI thanks to the help of Ollama.
Co-authored-by: João Moura <joaomdmoura@gmail.com>
