* scen
* scen2
* app
* fix
* Simplify workflow
* We can share more code in new scenarios
* rename model to rd loop
* Optimize data path
* Update rdagent/app/data_mining/model.py
* Add TODO
* Support GPU
* gpu
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Co-authored-by: SH-Src <suhan.c@outlook.com>
- Performed further optimizations on the factor loop and report extraction loop.
- Added log handling for both processes.
- Implemented a screenshot feature for report extraction.
* 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
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Co-authored-by: Xisen Wang <118058822+Xisen-Wang@users.noreply.github.com>
you-n-g