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refactor: move selector codes to an independent folder (#1059)
* refactor: move exp_gen selection files into select directory * fix selector value in data_science conf * fix selector template name * fix CI --------- Co-authored-by: Young <afe.young@gmail.com>
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@@ -84,7 +84,7 @@ class DataScienceBasePropSetting(KaggleBasePropSetting):
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"""The maximum number of traces to grow before merging"""
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#### multi-trace:checkpoint selector
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selector_name: str = "rdagent.scenarios.data_science.proposal.exp_gen.ckp_select.LatestCKPSelector"
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selector_name: str = "rdagent.scenarios.data_science.proposal.exp_gen.select.expand.LatestCKPSelector"
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"""The name of the selector to use"""
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sota_count_window: int = 5
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"""The number of trials to consider for SOTA count"""
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@@ -92,7 +92,7 @@ class DataScienceBasePropSetting(KaggleBasePropSetting):
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"""The threshold for SOTA count"""
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#### multi-trace: SOTA experiment selector
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sota_exp_selector_name: str = "rdagent.scenarios.data_science.proposal.exp_gen.sota_exp_select.GlobalSOTASelector"
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sota_exp_selector_name: str = "rdagent.scenarios.data_science.proposal.exp_gen.select.submit.GlobalSOTASelector"
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"""The name of the SOTA experiment selector to use"""
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### multi-trace:inject optimals for multi-trace
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@@ -98,7 +98,7 @@ class LiteLLMAPIBackend(APIBackend):
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if response_format and not supports_response_schema(model=LITELLM_SETTINGS.chat_model):
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# Deepseek will enter this branch
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logger.warning(
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f"{LogColors.RED}Model {LITELLM_SETTINGS.chat_model} does not support response schema, ignoring response_format argument.{LogColors.END}",
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f"{LogColors.YELLOW}Model {LITELLM_SETTINGS.chat_model} does not support response schema, ignoring response_format argument.{LogColors.END}",
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tag="llm_messages",
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)
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response_format = None
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+2
-4
@@ -115,11 +115,9 @@ class AutoSOTAexpSelector(SOTAexpSelector):
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Description: {desc}
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Final score: {current_final_score}\n\n"""
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system_prompt = T(".prompts_selector:auto_sota_selector.system").r(
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scenario=trace.scen.get_scenario_all_desc()
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)
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system_prompt = T(".prompts:auto_sota_selector.system").r(scenario=trace.scen.get_scenario_all_desc())
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user_prompt = T(".prompts_selector:auto_sota_selector.user").r(
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user_prompt = T(".prompts:auto_sota_selector.user").r(
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historical_sota_exp_with_desc_and_scores=SOAT_exp_with_desc_and_scores,
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)
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