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Code Issues Packages Projects Releases Wiki Activity

feat: Factor Implement Search Enhancement (#294)

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* Search enhancement

* refactor: reorganize imports for consistency with isort

* reformatterd by black

---------

Co-authored-by: Tim <illking@foxmail.com>
This commit is contained in:
cyncyw
2024-09-23 03:24:26 -04:00
committed by GitHub
parent bfce8a6371
commit 972bb2d99f
5 changed files with 132 additions and 2 deletions
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rdagent/components/coder/factor_coder/CoSTEER/evolving_strategy.py
+50
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@@ -183,6 +183,19 @@ class FactorEvolvingStrategyWithGraph(MultiProcessEvolvingStrategy):
self.num_loop = 0
self.haveSelected = False
def _query_data_tables(self, user_prompt, session):
for _ in range(10): # max attempt to reduce the length of user_prompt
response = session.build_chat_completion(
user_prompt=user_prompt,
json_mode=True,
)
try:
result = json.loads(response)
return result
except json.JSONDecodeError:
continue
return None
def implement_one_factor(
self,
target_task: FactorTask,
@@ -218,6 +231,42 @@ class FactorEvolvingStrategyWithGraph(MultiProcessEvolvingStrategy):
queried_knowledge.former_traces[target_factor_task_information] if queried_knowledge is not None else []
)
queried_data_tables = (
queried_knowledge.data_set_knowledge_dict[target_factor_task_information]
if queried_knowledge is not None
else []
)
queried_data_tables_str = json.dumps(queried_data_tables, indent=2)
system_prompt = (
Environment(undefined=StrictUndefined)
.from_string(
implement_prompts["evolving_strategy_search_data_table_system_prompt"],
)
.render()
)
user_prompt = (
Environment(undefined=StrictUndefined)
.from_string(
implement_prompts["evolving_strategy_search_data_table"],
)
.render(
scenario=self.scen.get_scenario_all_desc(),
factor_information_str=target_factor_task_information,
data_tables=queried_data_tables_str,
)
)
session = APIBackend(use_chat_cache=FACTOR_IMPLEMENT_SETTINGS.coder_use_cache).build_chat_session(
session_system_prompt=system_prompt,
)
useful_data_table = self._query_data_tables(user_prompt, session)
selected_knowledge_dict = {}
for key in useful_data_table:
if key in queried_knowledge.data_set_knowledge_dict:
selected_knowledge_dict[key] = queried_knowledge.data_set_knowledge_dict[key]
queried_former_failed_knowledge_to_render = queried_former_failed_knowledge
system_prompt = (
@@ -228,6 +277,7 @@ class FactorEvolvingStrategyWithGraph(MultiProcessEvolvingStrategy):
.render(
scenario=self.scen.get_scenario_all_desc(),
queried_former_failed_knowledge=queried_former_failed_knowledge_to_render,
selected_knowledge_dict=selected_knowledge_dict,
)
)