[pull] main from agentscope-ai:main#44
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pull[bot] merged 1 commit intopan-x-c:mainfrom Mar 24, 2026
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) * feat(tuner): naive adaption of dspy * feat(tuner): implement naive prompt tuning with dspy integration * refactor(tuner): add config and logs for prompt tuning * fix(tuner): remove trailing whitespace and unused code * feat(tuner): export prompt tuning config and function in module init * feat(tuner): add training summary * docs(tuner): add comprehensive docstrings for prompt tuning module * refactor(tuner): rename Dataset to DatasetConfig and TunerChatModel to TunerModelConfig * feat(tuner): add model selection optimizer * fix(tuner): avoid sharing agent context in all prompt tuning dataset * feat(tuner): add local file loading support for training datasets * fix(tuner): fix dataset loading by using data_files parameter * feat(tuner): add local file loading support for evaluation datasets * feat(tuner): use deepcopy for agent to prevent shared state during optimization * feat(tuner): simplify prompt-tune example prompt * refactor(tuner): change prompt tuning to optimize prompt strings instead of agent instances * docs(tuner): add comprehensive prompt tuning guide and relocate example * chore: clear code * docs(tuner): clarify that example uses GSM8K subset in README * chore(tuner): format code * refactor(tuner): make prompt_tune internal modules private * chore(tuner): format code * feat(tuner): add model select * fix(tuner): improve model selection and built-in judges robustness * refactor(tuner): rename and encapsulate prompt tuning internals * fix(tuner): specify response type as WorkflowOutput in judge functions * fix(tuner): correct response usage extraction in avg_token_consumption_judge * refactor(tuner): simplify prompt tuning interface with minimal workflow signature * refactor(tuner): return optimization metrics in tune_prompt * chore(deps): reorganize dependencies for tuner support * fix(tuner): modify model selection logic according to pr comments, mainly to record metrics and unify optimization direction * fix: fix issues for getting token usage; add examples for model selection * add naive implementation of model selection tuning function, including metrics by time and token usage * refactor(tuner): simplify WorkflowType and update prompt tuning integration * chore(deps): update datasets and trinity-rft * refactor(tuner): simplify JudgeType and remove auxiliary_models parameter from prompt tuning * refactor(tuner): validate functions and simplify invocation in model selection * refactor(tuner): clean up imports and improve code formatting * docs(tuner): update docstrings for clarity in prompt tuning and its example * fix(tuner): remove duplicated code * fix(tuner): add concurrent execution for efficiency in model selection * chore: format code * chore: remove empty code * docs(tuner): update example name * refactor(tuner): model select use response any * docs(tuner): update tuning docs * deps: switch trinity to seperate tuner-gpu deps * docs(tuner): apply suggestion from @pan-x-c Co-authored-by: Xuchen Pan <32844285+pan-x-c@users.noreply.github.com> * refactor(tuner): update bleu example * docs(tuner): update url * chore: pre-commit check * backup: clean wrongly commit user configs * fix(tuner): minor typo of dependencies * fix(tuner): fix for pre-commit flake8 * fix(tuner): fix for pre-commit pylint * fix(tuner): minor fixes * fix(tuner): pre-commit issues * fix(tuner): pre-commit issues * fix(tuner): minor fixes * fix(tuner): minor fixes * fix(tuner): pre-commit black * fix(tuner): trailing coma fix * fix(tuner): typo fix * fix(tuner): pyproject fix * fix(tuner): fix black pre-commit * chore(tuner): format code --------- Co-authored-by: wce <wce@pku.edu.cn> Co-authored-by: 天置 <wce@pku> Co-authored-by: Xuchen Pan <32844285+pan-x-c@users.noreply.github.com>
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