* simplify RDAgent conf
* add unified cacher(untested)
* fix small bugs
* fix a bug
* fix a small bug in runner
* use hash_key = None to skip cache
* fix CI
* in factor execution, ignore cache when raise exception
* add file locker to avoid mp calling
* fix CI
* use function __module__ name as folder in cache
* rename meta_tpl
* use a isolated coder to deal with model feature selection and refine the structure
* fix CI
* fix: fix some errors in scenario.py, proposal.py and runner.py and several complex competition scenarios(#365)
* fix several bugs in proposal and runner
* fix a bug in feedback-prize-english-language-learning
* fix some bugs and templates
* fix the bug in optiver and nlp problem
* delete unnecessary codes
* remove unnecessary codes
* complete forest and s4e8
* push
* feedback & s4e8 & forest
* optiver finished
* s3e11 & s3e26
* s4e9 finished
* sf-crime finished
* the last one finished
---------
Co-authored-by: WinstonLiyt <104308117+WinstonLiyt@users.noreply.github.com>
Co-authored-by: WinstonLiyte <1957922024@qq.com>
* init a scenario for kaggle feature engineering
* fix some bugs and add original features' description
* refine the process of data downloading
* fix a error
* revert the code
* fix a bug in feedback
* fix a ci bug
* fix a ci bug
* Init todo
* Evaluation & dataset
* Generate new data
* dataset generation
* add the result
* Analysis
* Factor update
* Updates
* Reformat analysis.py
* CI fix
* Revised Preprocessing & Supported Random Forest
* Revised to support three models with feature
* Further revised prompts
* Slight Revision
* docs: update contributors (#230)
* Revised to support three models with feature
* Further revised prompts
* Slight Revision
* feat: kaggle model and feature (#238)
* update first version code
* make hypothesis_gen and experiment_builder fit for both feature and model
* feat: continue kaggle feature and model coder (#239)
* use qlib docker to run qlib models
* feature coder ready
* model coder ready
* fix CI
* finish the first round of runner (#240)
* Optimized the factor scenario and added the front-end.
* fix a small bug
* fix a typo
* update the kaggle scenario
* delete model_template folder
* use experiment to run data preprocess script
* add source data to scenarios
* minor fix
* minor bug fix
* train.py debug
* fixed a bug in train.py and added some TODOs
* For Debugging
* fix two small bugs in based_exp
* fix some bugs
* update preprocess
* fix a bug in preprocess
* fix a bug in train.py
* reformat
* Follow-up
* fix a bug in train.py
* fix a bug in workspace
* fix a bug in feature duplication
* fix a bug in feedback
* fix a bug in preprocessed data
* fix a bug om feature engineering
* fix a ci error
* Debugged & Connected
* Fixed error on feedback & added other fixes
* fix CI errors
* fix a CI bug
* fix: fix_dotenv_error (#257)
* fix_dotenv_error
* format with isort
* Update rdagent/app/cli.py
---------
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
* chore(main): release 0.2.1 (#249)
Release-As: 0.2.1
* init a scenario for kaggle feature engineering
* delete error codes
* Delete rdagent/app/kaggle_feature/conf.py
---------
Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: Taozhi Wang <taozhi.mark.wang@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
Co-authored-by: cyncyw <47289405+taozhiwang@users.noreply.github.com>
Co-authored-by: Xisen-Wang <xisen_application@163.com>
Co-authored-by: Haotian Chen <113661982+Hytn@users.noreply.github.com>
Co-authored-by: WinstonLiye <1957922024@qq.com>
Co-authored-by: WinstonLiyt <104308117+WinstonLiyt@users.noreply.github.com>
Co-authored-by: Linlang <30293408+SunsetWolf@users.noreply.github.com>
* init commit for XGBoost
* fix some bugs
* CI issues
* CI issues
* CI issue
* edit prompts for kaggle scenario & fix some bugs
* Revised Prompts To Improve Performance on Model Type & Support of Random Forest
* edit prompts & modify evaluator.py to adapt to Kaggle scenario
* edit prompts
* fix some bugs
* CI issues
---------
Co-authored-by: Taozhi Wang <taozhi.mark.wang@gmail.com>
Co-authored-by: Xisen-Wang <xisen_application@163.com>
* Init todo
* Evaluation & dataset
* Generate new data
* dataset generation
* add the result
* Analysis
* Factor update
* Updates
* Reformat analysis.py
* CI fix
* Further Optimised Model Workflow by Incorporating Feedbacks on Exp Task Card
* Rebasing To build the extraction & implementation demo
* Revised for clean code
* Revised further to show "Knowledge"
* Revised to make model_research_copilot better
* Further Optimised Model Workflow by Incorporating Feedbacks on Exp Task Card
* Rebasing To build the extraction & implementation demo
* Revised for clean code
* Revised further to show "Knowledge"
* Revised to make model_research_copilot better
---------
Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: Taozhi Wang <taozhi.mark.wang@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
Co-authored-by: cyncyw <47289405+taozhiwang@users.noreply.github.com>
* fix mypy error
* fix mypy error
* fix ruff error
* change command
* delete python 3.8&3.9 from CI
* change command
* Some modifications according to the comments
* Add literal type
* Update .github/workflows/ci.yml
* Some modifications according to the comments
* fix ruff error
* fix meta dict
* Fix type
* Some modifications according to the comments
* merge latest code
* Some modifications according to the comments
* Some modifications according to the comments
* fix ci error
* fix ruff error
* Update Makefile
* Update Makefile
---------
Co-authored-by: Ubuntu <debug@debug.qjtqi00gqezu1eqs55bqdrf51f.px.internal.cloudapp.net>
Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
* ignore result csv file
* fix app scripts
* rename taskgenerator to developer and generate to develop
* fix a config bug in coder
* fix a small bug in factor coder evaluators
* remove a single logger in factor coder evaluators
* fix a small bug in model coder main.py
* rename Implementation to Workspace
* move the prepare the inject_code into FBWorkspace to align all the behavior
* fix a small bug in model feedback
* remove debug lines for multi processing and simplify evaluators multi proc
* add a copy function to workspace to freeze the workspace && add config prefix to speed up debugging
* make hypothesisgen a abc class
* use Qlib***Experiment
* fix a small bug
* rename Imp to Ws
* rename sub_implementations to sub_workspace_list
* fix a bug in feedback not presented as content in prompts
* move proposal pys to proposal folder
* reformat the folder
* align factor and model qlib workspace and use template to handle the workspace
* add a filter to evoagent to filter out false evo
* align multi_proc_n into RDAGENT seeting
* handle when runner gets empty experiment
* fix logger merge remaining problems
* fix black and isort automatically
* remove ruff comment in log.py
* change log framework and fix llm_utils.py's logs
* Some thoughts for logging
* fix SingletonMeta's definition, maintain an instance dict for each class that inherits it
* adjust log codes directory, add some tag for factor implementation logging
* Update rdagent/core/conf.py
* fix factor task app & log
* fix log import
* Streamlet framework
* fix log tag to path logic
* Add todos
* Add example in docstring
* add log tag for llm_utils.py
* Capture lost content
---------
Co-authored-by: Young <afe.young@gmail.com>
Co-authored-by: you-n-g <you-n-g@users.noreply.github.com>
* Implemented model.py
- Need to run within the RDAgent folder (relevant path)
- Each time copy a template & insert code & run qlib & store result back to experiment
* Create model.py
* Create conf.yaml
This is the sample conf.yaml to be copied each time.
This has gone several times of iteration and is now working for both tabular and Time-Series data.
* Create read_exp.py
This is to read the results within Qlib
* Create ReadMe.md
* Update model.py
* Create test_model.py
A testing file that separates model code generation and running&feedback section.
* move the template folder
* help xisen finish the model runner
* help xisen fix improve model feedback generation
* delete debug file
* rename readme.md
---------
Co-authored-by: Xisen Wang <118058822+Xisen-Wang@users.noreply.github.com>
* store code into FBImplementation
* fix path related bugs
* fix a bug
* fix factor related small bugs
* re-submit all model related code
* new code to model coder
* finish the model evolving code
---------
Co-authored-by: xuyang1 <xuyang1@microsoft.com>
* use CoSTEER as component name
* rename factorimplementation to avoid confusion
* rename modelimplementation
* align benchmark and evolving evaluators
* add scenario to evaluator init function
* rename all factorimplementationknowledge in CoSTEER
* remove all scenario related information in component
* remove useless code
---------
Co-authored-by: xuyang1 <xuyang1@microsoft.com>
Linlang