* removed hyphen in co-workers
* Fix issue with AgentTool agent selection. The LLM included double quotes in the agent name which messed up the string comparison. Added additional types. Cleaned up error messaging.
* Remove duplicate import
* Improve explanation
* Revert poetry.lock changes
* Fix missing line in poetry.lock
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Co-authored-by: madmag77 <goncharov.artemv@gmail.com>
* 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
* log_file
feature: added a new parameter for crew that creates a txt file to log agent execution
* unit tests and documentation
unit test if file is created but not what is inside the file
* 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
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Co-authored-by: João Moura <joaomdmoura@gmail.com>
This now will allow to add a max_inter option to agents while also making sure to force the agent to give it's best final answer before running out of it's max_inter.
* Refactoring task cache to be a tool
The previous implementation of the task caching system was early exiting
the agent executor due to the fact it was returning an AgentFinish object.
This now refactors it to use a cache specific tool that is dynamically
added and forced into the agent in case of a task execution that was
already executed with the same input.
* Adding tool caching a loop execution prevention.
This adds some guardrails, to both prevent the same tool to be used
consecutively and also caching tool's results across the entire crew
so it cuts down execution time and eventual LLM calls.
This plays a huge role for smaller opensource models that usually fall
into those behaviors patterns.
It also includes some smaller improvements around the tool prompt and
agent tools, all with the same intention of guiding models into
better conform with agent instructions.
