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feat: use unified pickle cacher & move llm config into a isolated config (#424)

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* simplify RDAgent conf

* add unified cacher(untested)

* fix small bugs

* fix a bug

* fix a small bug in runner

* use hash_key = None to skip cache

* fix CI

* in factor execution, ignore cache when raise exception

* add file locker to avoid mp calling

* fix CI

* use function __module__ name as folder in cache
This commit is contained in:
Xu Yang
2024-10-14 17:34:09 +08:00
committed by GitHub
parent 8341430bc9
commit 25472fc1e3
25 changed files with 299 additions and 346 deletions
Download Patch File Download Diff File Expand all files Collapse all files
rdagent/components/coder/factor_coder/CoSTEER/evaluators.py
+3 -2
View File
@@ -19,6 +19,7 @@ from rdagent.core.experiment import Task, Workspace
from rdagent.core.prompts import Prompts
from rdagent.core.utils import multiprocessing_wrapper
from rdagent.log import rdagent_logger as logger
from rdagent.oai.llm_conf import LLM_SETTINGS
from rdagent.oai.llm_utils import APIBackend
evaluate_prompts = Prompts(file_path=Path(__file__).parent.parent / "prompts.yaml")
@@ -118,7 +119,7 @@ class FactorCodeEvaluator(FactorEvaluator):
user_prompt=user_prompt,
system_prompt=system_prompt,
)
> RD_AGENT_SETTINGS.chat_token_limit
> LLM_SETTINGS.chat_token_limit
):
execution_feedback_to_render = execution_feedback_to_render[len(execution_feedback_to_render) // 2 :]
else:
@@ -521,7 +522,7 @@ class FactorFinalDecisionEvaluator(Evaluator):
user_prompt=user_prompt,
system_prompt=system_prompt,
)
> RD_AGENT_SETTINGS.chat_token_limit
> LLM_SETTINGS.chat_token_limit
):
execution_feedback_to_render = execution_feedback_to_render[len(execution_feedback_to_render) // 2 :]
else:
rdagent/components/coder/factor_coder/CoSTEER/evolving_strategy.py
+4 -3
View File
@@ -22,6 +22,7 @@ from rdagent.core.evolving_framework import EvolvingStrategy, QueriedKnowledge
from rdagent.core.experiment import Workspace
from rdagent.core.prompts import Prompts
from rdagent.core.utils import multiprocessing_wrapper
from rdagent.oai.llm_conf import LLM_SETTINGS
from rdagent.oai.llm_utils import APIBackend
if TYPE_CHECKING:
@@ -160,7 +161,7 @@ class FactorEvolvingStrategy(MultiProcessEvolvingStrategy):
session.build_chat_completion_message_and_calculate_token(
user_prompt,
)
< RD_AGENT_SETTINGS.chat_token_limit
< LLM_SETTINGS.chat_token_limit
):
break
elif len(queried_former_failed_knowledge_to_render) > 1:
@@ -281,7 +282,7 @@ class FactorEvolvingStrategyWithGraph(MultiProcessEvolvingStrategy):
)
if (
session_summary.build_chat_completion_message_and_calculate_token(error_summary_user_prompt)
< RD_AGENT_SETTINGS.chat_token_limit
< LLM_SETTINGS.chat_token_limit
):
break
elif len(queried_similar_error_knowledge_to_render) > 0:
@@ -310,7 +311,7 @@ class FactorEvolvingStrategyWithGraph(MultiProcessEvolvingStrategy):
session.build_chat_completion_message_and_calculate_token(
user_prompt,
)
< RD_AGENT_SETTINGS.chat_token_limit
< LLM_SETTINGS.chat_token_limit
):
break
elif len(queried_former_failed_knowledge_to_render) > 1:
rdagent/components/coder/factor_coder/CoSTEER/scheduler.py
+2 -2
View File
@@ -7,10 +7,10 @@ from jinja2 import Environment, StrictUndefined
from rdagent.components.coder.factor_coder.CoSTEER.evolvable_subjects import (
FactorEvolvingItem,
)
from rdagent.core.conf import RD_AGENT_SETTINGS
from rdagent.core.prompts import Prompts
from rdagent.core.scenario import Scenario
from rdagent.log import rdagent_logger as logger
from rdagent.oai.llm_conf import LLM_SETTINGS
from rdagent.oai.llm_utils import APIBackend
scheduler_prompts = Prompts(file_path=Path(__file__).parent.parent / "prompts.yaml")
@@ -68,7 +68,7 @@ def LLMSelect(
user_prompt=user_prompt,
system_prompt=system_prompt,
)
< RD_AGENT_SETTINGS.chat_token_limit
< LLM_SETTINGS.chat_token_limit
):
break