* fix: call asserts
* fix: test_increment_tool_errors
* fix: test_increment_delegations_for_sequential_process
* fix: test_increment_delegations_for_hierarchical_process
* fix: test_code_execution_flag_adds_code_tool_upon_kickoff
* fix: test_tool_usage_information_is_appended_to_agent
* fix: try to fix test_crew_full_output
* fix: try to fix test_crew_full_output
* fix: test remove vcr to test crew_test test
* fix: comment test to see if ci passes
* fix: comment test to see if ci passes
* fix: test changing prompt tokens to get error on CI
* fix: test changing prompt tokens to get error on CI
* fix: test changing prompt tokens to get error on CI
* fix: test changing prompt tokens to get error on CI
* fix: test new approach
* fix: comment funciont not working in CI
* fix: github python version
* fix: remove need of vcr
* fix: fix and add comments for all type checking errors
* Adding support to force a tool return to be the final answer.
This will at the end of the execution return the tool output.
It will return the output of the latest tool with the flag
* Update src/crewai/agent.py
Co-authored-by: Gui Vieira <guilherme_vieira@me.com>
* Update tests/agent_test.py
Co-authored-by: Gui Vieira <guilherme_vieira@me.com>
---------
Co-authored-by: Gui Vieira <guilherme_vieira@me.com>
* fixed bug for manager overriding task agent and then added pydanic valditors to sequential when no agent is added to task
* better test and fixed task.agent logic
* fixed tests and better validator message
* added validator for async_execution true in tasks whenever in hierarchical run
* 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
- 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!
* Fix issue agentop poetry install issue
* Updated install requirements tests to fail if .lock becomes out of sync with poetry install. Cleaned up old issues that were merged back in.
* implements agentops with a langchain handler, agent tracking and tool call recording
* track tool usage
* end session after completion
* track tool usage time
* better tool and llm tracking
* code cleanup
* make agentops optional
* optional dependency usage
* remove telemetry code
* optional agentops
* agentops version bump
* remove org key
* true dependency
* add crew org key to agentops
* cleanup
* Update pyproject.toml
* Revert "true dependency"
This reverts commit e52e8e9568.
* Revert "cleanup"
This reverts commit 7f5635fb9e.
* optional parent key
* agentops 0.1.5
* Revert "Revert "cleanup""
This reverts commit cea33d9a5d.
* Revert "Revert "true dependency""
This reverts commit 4d1b460b
* cleanup
* Forcing version 0.1.5
* Update pyproject.toml
* agentops update
* noop
* add crew tag
* black formatting
* use langchain callback handler to support all LLMs
* agentops version bump
* track task evaluator
* merge upstream
* Fix typo in instruction en.json (#676)
* Enable search in docs (#663)
* Clarify text in docstring (#662)
* Update agent.py (#655)
Changed default model value from gpt-4 to gpt-4o.
Reasoning.
gpt-4 costs 30$ per million tokens while gpt-4o costs 5$.
This is more cost friendly for default option.
* Update README.md (#652)
Rework example so that if you use a custom LLM it doesn't throw code errors by uncommenting.
* Update BrowserbaseLoadTool.md (#647)
* Update crew.py (#644)
Fixed Type on line 53
* fixes#665 (#666)
* Added timestamp to logger (#646)
* Added timestamp to logger
Updated the logger.py file to include timestamps when logging output. For example:
[2024-05-20 15:32:48][DEBUG]: == Working Agent: Researcher
[2024-05-20 15:32:48][INFO]: == Starting Task: Research the topic
[2024-05-20 15:33:22][DEBUG]: == [Researcher] Task output:
* Update tool_usage.py
* Revert "Update tool_usage.py"
This reverts commit 95d18d5b6f.
incorrect bramch for this commit
* support skip auto end session
* conditional protect agentops use
* fix crew logger bug
* fix crew logger bug
* Update crew.py
* Update tool_usage.py
---------
Co-authored-by: João Moura <joaomdmoura@gmail.com>
Co-authored-by: Howard Gil <howardbgil@gmail.com>
Co-authored-by: Olivier Roberdet <niox5199@gmail.com>
Co-authored-by: Paul Sanders <psanders1@gmail.com>
Co-authored-by: Anudeep Kolluri <50168940+Anudeep-Kolluri@users.noreply.github.com>
Co-authored-by: Mike Heavers <heaversm@users.noreply.github.com>
Co-authored-by: Mish Ushakov <10400064+mishushakov@users.noreply.github.com>
Co-authored-by: theCyberTech - Rip&Tear <84775494+theCyberTech@users.noreply.github.com>
Co-authored-by: Saif Mahmud <60409889+vmsaif@users.noreply.github.com>
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>
fixed error for some cases with Pandas DataFrame:
ValueError: The truth value of a DataFrame is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
