* chat completion check

* add test

* doc

* timeout

* bump version to 1.2.4

* Mark experimental classes

* template

* multi model

* test

* multi-config doc

* doc

* doc

* test

---------

Co-authored-by: Li Jiang <bnujli@gmail.com>

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* coding agent

* tsp

* tsp

* aoai

* logging

* compact

* Handle Import Error

* cost function

* reset counter; doc

* reset_counter

* home page update

* use case

* catboost in linux

* catboost

* catboost

* catboost

* doc

* intro

* catboost

* fixing the typo #990

* Update website/docs/Use-Cases/Auto-Generation.md

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* removing extra space : Update website/docs/Use-Cases/Auto-Generation.md

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update website/docs/Use-Cases/Auto-Generation.md

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update website/docs/Use-Cases/Auto-Generation.md

---------

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* extract code from text

* solve_problem; request_timeout in config

* improve

* move import statement

* improve code

* generate assertions

* constant

* configs for implement; voting

* doc

* execute code in docker

* success indicator of code executation in docker

* success indicator

* execute code

* strip n

* add cost in generate_code

* add docstr

* filename

* bytes

* check docker version

* print log

* python test

* remove api key address

* rename exit code

* success exit code

* datasets

* exit code

* recover openai tests

* cache and pattern match

* wait

* wait

* cache and test

* timeout test

* python image name and skip macos

* windows image

* docker images

* volume path and yaml

* win path -> posix

* extensions

* path

* path

* path

* path

* path

* path

* path

* path

* path

* path

* path

* skip windows

* path

* timeout in windows

* use_docker

* use_docker

* hot fix from #1000

---------

Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>

* make context optional

* better error handling and doc

* skip instantiation if no context

* skip test

* news update

* doc update

* avoid KeyError

* bump version to 1.2.1

* handle empty responses

* typo

* eval function

* math utils in autogen

* cleanup

* code utils

* remove check function from code response

* comment out test

* GPT-4

* increase request timeout

* name

* logging and error handling

* better doc

* doc

* codegen optimized

* GPT series

* text

* no demo example

* math

* import openai

* import openai

* azure model name

* azure model name

* openai version

* generate assertion if necessary

* condition to generate assertions

* init region key

* rename

* comments about budget

* prompt

---------

Co-authored-by: Susan Xueqing Liu <liususan091219@users.noreply.github.com>

* tentatively implement holt-winters-no covariates

* fix forecast method, clean class

* checking external regressors too

* update test forecast

* remove duplicated test file, re-add sarimax, search space cleanup

* Update flaml/automl/model.py

removed links. Most important one probably was: https://robjhyndman.com/hyndsight/ets-regressors/

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* prevent short series

* add docs

---------

Co-authored-by: Andrea W <a.ruggerini@ammagamma.com>
Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* indentation space #884 changing indentation of python code blocks

* indentation space #884 changing indentation of python code blocks 2

* update

* update doc

---------

Co-authored-by: “skzhang1” <“shaokunzhang529@gmail.com”>

* precommit: end-of-file-fixer

* exclude .gitignore

* apply

---------

Co-authored-by: Shaokun <shaokunzhang529@gmail.com>

* added documentation about small time budget

* small change for better clarity

* Update website/docs/Use-Cases/Task-Oriented-AutoML.md

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

---------

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Added spark support for parallel training.

* Added tests and fixed a bug

* Added more tests and updated docs

* Updated setup.py and docs

* Added customize_learner and tests

* Update spark tests and setup.py

* Update docs and verbose

* Update logging, fix issue in cloud notebook

* Update github workflow for spark tests

* Update github workflow

* Remove hack of handling _choice_

* Allow for failures

* Fix tests, update docs

* Update setup.py

* Update Dockerfile for Spark

* Update tests, remove some warnings

* Add test for notebooks, update utils

* Add performance test for Spark

* Fix lru_cache maxsize

* Fix test failures on some platforms

* Fix coverage report failure

* resovle PR comments

* resovle PR comments 2nd round

* resovle PR comments 3rd round

* fix lint and rename test class

* resovle PR comments 4th round

* refactor customize_learner to broadcast_code

* fix_doc

* update

* fix lint

* fix lint

* reformat

Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>

* Refactor into automl subpackage

Moved some of the packages into an automl subpackage to tidy before the
task-based refactor. This is in response to discussions with the group
and a comment on the first task-based PR.

Only changes here are moving subpackages and modules into the new
automl, fixing imports to work with this structure and fixing some
dependencies in setup.py.

* Fix doc building post automl subpackage refactor

* Fix broken links in website post automl subpackage refactor

* Fix broken links in website post automl subpackage refactor

* Remove vw from test deps as this is breaking the build

* Move default back to the top-level

I'd moved this to automl as that's where it's used internally, but had
missed that this is actually part of the public interface so makes sense
to live where it was.

* Re-add top level modules with deprecation warnings

flaml.data, flaml.ml and flaml.model are re-added to the top level,
being re-exported from flaml.automl for backwards compatability. Adding
a deprecation warning so that we can have a planned removal later.

* Fix model.py line-endings

* Pin pytorch-lightning to less than 1.8.0

We're seeing strange lightning related bugs from pytorch-forecasting
since the release of lightning 1.8.0. Going to try constraining this to
see if we have a fix.

* Fix the lightning version pin

Was optimistic with setting it in the 1.7.x range, but that isn't
compatible with python 3.6

* Remove lightning version pin

* Revert dependency version changes

* Minor change to retrigger the build

* Fix line endings in ml.py and model.py

Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
Co-authored-by: EgorKraevTransferwise <egor.kraev@transferwise.com>

* make performance test reproducible

* fix test error

* Doc update and disable logging

* document random_state and version

* remove hardcoded budget

* fix test error and dependency; close #777

* iloc

* Pending changes exported from your codespace

* Update flaml/automl.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update flaml/automl.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update flaml/ml.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update flaml/ml.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update website/docs/Examples/Integrate - Scikit-learn Pipeline.md

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* added documentation for new metric

* Update flaml/ml.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* minor notebook changes

* Update Integrate - Scikit-learn Pipeline.md

* Update notebook/automl_classification.ipynb

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update integrate_azureml.ipynb

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* install editable package in codespace

* fix test error in test_forecast

* fix test error in test_space

* openml version

* break tests; pre-commit

* skip on py10+win32

* install mlflow in test

* install mlflow in [test]

* skip test in windows

* import

* handle PermissionError

* skip test in windows

* skip test in windows

* skip test in windows

* skip test in windows

* remove ts_forecast_panel from doc

limiting the scope to tabular data.

* Small docstring change for clarity

* Added tentative changes to docs

* Update website/docs/Use-Cases/Task-Oriented-AutoML.md

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Update flaml/model.py

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* Updated model.py to reflect `n_jobs = None` suggestion

* Updated tutorial to reflect `n_jobs=None` suggestion

* Update model.py

Improved string

Co-authored-by: Chi Wang <wang.chi@microsoft.com>
Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>

Co-authored-by: Chi Wang <wang.chi@microsoft.com>

* version update in notebook

* comment about optuna install

* monotone constraints

* add guideline collection

* remove redundancy