* 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
* 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
* added extra parameter for kickoff to return token usage count after result
* added output_token_usage to class and in full_output
* logger duplicated
* added more types
* added usage_metrics to full output instead
* added more to the description on full_output
* possible mispacing
* Sync with deep copy working now
* async working!!
* Clean up code for review
* Fix naming
---------
Co-authored-by: João Moura <joaomdmoura@gmail.com>
* fix: fix test actually running
* fix: fix test to not send request to openai
* fix: fix linting to remove cli files
* fix: exclude only files that breaks black
* fix: Fix all Ruff checkings on the code and Fix Test with repeated name
* fix: Change linter name on yml file
* feat: update pre-commit
* feat: remove need for isort on the code
* feat: add mypy as type checker, update code and add comment to reference
* feat: remove black linter
* feat: remove poetry to run the command
* feat: change logic to test mypy
* feat: update tests yml to try to fix the tests gh action
* feat: try to add just mypy to run on gh action
* feat: fix yml file
* feat: add comment to avoid issue on gh action
* feat: decouple pytest from the necessity of poetry install
* feat: change tests.yml to test different approach
* feat: change to poetry run
* fix: parameter field on yml file
* fix: update parameters to be on the pyproject
* fix: update pyproject to remove import untyped errors
* fix: fix test actually running
* fix: fix test to not send request to openai
* fix: fix linting to remove cli files
* fix: exclude only files that breaks black
* fix: Fix all Ruff checkings on the code and Fix Test with repeated name
* fix: Change linter name on yml file
* feat: update pre-commit
* feat: remove need for isort on the code
* feat: remove black linter
* feat: update tests yml to try to fix the tests gh action
* Update task.py: try to find json in task output using regex
Sometimes the model replies with a valid and additional text, let's try to extract and validate it first. It's cheaper than calling LLM for that.
* Update task.py
---------
Co-authored-by: João Moura <joaomdmoura@gmail.com>
This commit adds a conditional check to ensure that the output file directory exists before attempting to create it. This ensures that the code does not
fail in cases where the directory does not exist and needs to be created. The condition is added in the `_save_file` method of the `Task` class, ensuring
that the correct behavior is maintained for saving results to a file.
* tasks.py: don't call Converter when model response is valid
Try to convert the task output to the expected Pydantic model before sending it to Converter, maybe the model got it right.
* feature: human input per task
* Update executor.py
* Update executor.py
* Update executor.py
* Update executor.py
* Update executor.py
* feat: change human input for unit testing
added documentation and unit test
* Create test_agent_human_input.yaml
add yaml for test
---------
Co-authored-by: João Moura <joaomdmoura@gmail.com>
