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>
This commit is contained in:
XianBW
2025-07-11 17:42:40 +08:00
committed by GitHub
parent 33c0362296
commit 2e1d0624d2
5 changed files with 5 additions and 7 deletions
+2 -2
View File
@@ -84,7 +84,7 @@ class DataScienceBasePropSetting(KaggleBasePropSetting):
"""The maximum number of traces to grow before merging"""
#### multi-trace:checkpoint selector
selector_name: str = "rdagent.scenarios.data_science.proposal.exp_gen.ckp_select.LatestCKPSelector"
selector_name: str = "rdagent.scenarios.data_science.proposal.exp_gen.select.expand.LatestCKPSelector"
"""The name of the selector to use"""
sota_count_window: int = 5
"""The number of trials to consider for SOTA count"""
@@ -92,7 +92,7 @@ class DataScienceBasePropSetting(KaggleBasePropSetting):
"""The threshold for SOTA count"""
#### multi-trace: SOTA experiment selector
sota_exp_selector_name: str = "rdagent.scenarios.data_science.proposal.exp_gen.sota_exp_select.GlobalSOTASelector"
sota_exp_selector_name: str = "rdagent.scenarios.data_science.proposal.exp_gen.select.submit.GlobalSOTASelector"
"""The name of the SOTA experiment selector to use"""
### multi-trace:inject optimals for multi-trace
+1 -1
View File
@@ -98,7 +98,7 @@ class LiteLLMAPIBackend(APIBackend):
if response_format and not supports_response_schema(model=LITELLM_SETTINGS.chat_model):
# Deepseek will enter this branch
logger.warning(
f"{LogColors.RED}Model {LITELLM_SETTINGS.chat_model} does not support response schema, ignoring response_format argument.{LogColors.END}",
f"{LogColors.YELLOW}Model {LITELLM_SETTINGS.chat_model} does not support response schema, ignoring response_format argument.{LogColors.END}",
tag="llm_messages",
)
response_format = None
@@ -115,11 +115,9 @@ class AutoSOTAexpSelector(SOTAexpSelector):
Description: {desc}
Final score: {current_final_score}\n\n"""
system_prompt = T(".prompts_selector:auto_sota_selector.system").r(
scenario=trace.scen.get_scenario_all_desc()
)
system_prompt = T(".prompts:auto_sota_selector.system").r(scenario=trace.scen.get_scenario_all_desc())
user_prompt = T(".prompts_selector:auto_sota_selector.user").r(
user_prompt = T(".prompts:auto_sota_selector.user").r(
historical_sota_exp_with_desc_and_scores=SOAT_exp_with_desc_and_scores,
)