Egor Kraev

@rmackay9 could this be related to https://github.com/ArduPilot/ardupilot/issues/17767?

Hi @luigif2000 ! The `enable_categorical` flag is actually an [experimental feature](https://xgboost.readthedocs.io/en/stable/tutorials/categorical.html) of xgboost and we don't support it yet. However FLAML (including its XGBoost wrapper) handles categorical features just fine,...

You can access the individual models via [MultiOutputRegressor.estimators_](https://scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html) and then save them as usual using `pickle`, or if pickle doesn't work, then `clouldpickle` or `dill`

hcrystalball just collects lagged values of the series and feeds them as features to a sklearn model, treating the next value as the target. lags is just the number of...

Just give the argument `estimator_list=['arima', 'sarimax', 'holt-winters']` to the `fit()` method

How about looking at marginal probabilities for all possible labels in a given position (that functionality exists in the Python wrapper as pycrfsuite.Tagger.marginal() so I presume also in the CFRSuite...

I'd love to see that example ;)

If https://github.com/joaomdmoura/crewAI/pull/246 is accepted, you could just use eg a Langchain agent and LangSmith :)

That's exactly the idea, so one would only need to provide a minimal wrapper (and for the major APIs, such as LangChain agents, we could just include one out of...

Something like this perhaps? ``` from typing import Any, Optional, List from abc import ABC, abstractmethod from pydantic import BaseModel, Field, PrivateAttr from langchain.agents import AgentExecutor, create_openai_tools_agent from langchain_core.messages import...