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().
* 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
* feat: add training logic to agent and crew
* feat: add training logic to agent executor
* feat: add input parameter to cli command
* feat: add utilities for the training logic
* feat: polish code, logic and add private variables
* feat: add docstring and type hinting to executor
* feat: add constant file, add constant to code
* feat: fix name of training handler function
* feat: remove unused var
* feat: change file handler file name
* feat: Add training handler file, class and change on the code
* feat: fix name error from file
* fix: change import to adapt to logic
* feat: add training handler test
* feat: add tests for file and training_handler
* feat: add test for task evaluator function
* feat: change text to fit in-screen
* feat: add test for train function
* feat: add test for agent training_handler function
* feat: add test for agent._use_trained_data
