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Refine all the implementation code to higher quality for release (#29)

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* refine CI script

* refine all the code to higher quality

* refine the script to factor extraction and implementation

* add task loader interface

* add a task loader interface && move pdf analysis to pdf task loader

* change the name to global variables

---------

Co-authored-by: xuyang1 <xuyang1@microsoft.com>
This commit is contained in:
Xu Yang
2024-06-18 11:50:03 +08:00
committed by GitHub
parent ebb659a018
commit a126c84c92
30 changed files with 567 additions and 564 deletions
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rdagent/factor_implementation/evolving/evolving_strategy.py
+17 -15
View File
@@ -8,10 +8,11 @@ from typing import TYPE_CHECKING
from jinja2 import Template
from rdagent.core.conf import RD_AGENT_SETTINGS
from rdagent.core.evolving_framework import EvolvingStrategy, QueriedKnowledge
from rdagent.oai.llm_utils import APIBackend
from rdagent.factor_implementation.share_modules.factor_implementation_config import (
FactorImplementSettings,
FACTOR_IMPLEMENT_SETTINGS,
)
from rdagent.core.task import (
@@ -81,18 +82,18 @@ class MultiProcessEvolvingStrategy(EvolvingStrategy):
# 2. 选择selection方法
# if the number of factors to be implemented is larger than the limit, we need to select some of them
if FactorImplementSettings().select_ratio < 1:
if FACTOR_IMPLEMENT_SETTINGS.select_ratio < 1:
# if the number of loops is equal to the select_loop, we need to select some of them
implementation_factors_per_round = int(
FactorImplementSettings().select_ratio * len(to_be_finished_task_index)
FACTOR_IMPLEMENT_SETTINGS.select_ratio * len(to_be_finished_task_index)
)
if FactorImplementSettings().select_method == "random":
if FACTOR_IMPLEMENT_SETTINGS.select_method == "random":
to_be_finished_task_index = RandomSelect(
to_be_finished_task_index,
implementation_factors_per_round,
)
if FactorImplementSettings().select_method == "scheduler":
if FACTOR_IMPLEMENT_SETTINGS.select_method == "scheduler":
to_be_finished_task_index = LLMSelect(
to_be_finished_task_index,
implementation_factors_per_round,
@@ -105,17 +106,18 @@ class MultiProcessEvolvingStrategy(EvolvingStrategy):
(self.implement_one_factor, (new_evo.target_factor_tasks[target_index], queried_knowledge))
for target_index in to_be_finished_task_index
],
n=FactorImplementSettings().evo_multi_proc_n,
n=FACTOR_IMPLEMENT_SETTINGS.evo_multi_proc_n,
)
for index, target_index in enumerate(to_be_finished_task_index):
new_evo.corresponding_implementations[target_index] = result[index]
if result[index].target_task.factor_name in new_evo.evolve_trace:
new_evo.evolve_trace[result[index].target_task.factor_name].append(result[index])
else:
new_evo.evolve_trace[result[index].target_task.factor_name] = [result[index]]
new_evo.corresponding_selection.append(to_be_finished_task_index)
# for target_index in to_be_finished_task_index:
# new_evo.corresponding_implementations[target_index] = self.implement_one_factor(
# new_evo.target_factor_tasks[target_index], queried_knowledge
# )
new_evo.corresponding_selection = to_be_finished_task_index
return new_evo
@@ -172,7 +174,7 @@ class FactorEvolvingStrategy(MultiProcessEvolvingStrategy):
session.build_chat_completion_message_and_calculate_token(
user_prompt,
)
< FactorImplementSettings().chat_token_limit
< RD_AGENT_SETTINGS.chat_token_limit
):
break
elif len(queried_former_failed_knowledge_to_render) > 1:
@@ -205,7 +207,7 @@ class FactorEvolvingStrategyWithGraph(MultiProcessEvolvingStrategy):
target_task: FactorImplementTask,
queried_knowledge,
) -> TaskImplementation:
error_summary = FactorImplementSettings().v2_error_summary
error_summary = FACTOR_IMPLEMENT_SETTINGS.v2_error_summary
# 1. 提取因子的背景信息
target_factor_task_information = target_task.get_factor_information()
@@ -284,7 +286,7 @@ class FactorEvolvingStrategyWithGraph(MultiProcessEvolvingStrategy):
)
if (
session_summary.build_chat_completion_message_and_calculate_token(error_summary_user_prompt)
< FactorImplementSettings().chat_token_limit
< RD_AGENT_SETTINGS.chat_token_limit
):
break
elif len(queried_similar_error_knowledge_to_render) > 0:
@@ -311,7 +313,7 @@ class FactorEvolvingStrategyWithGraph(MultiProcessEvolvingStrategy):
session.build_chat_completion_message_and_calculate_token(
user_prompt,
)
< FactorImplementSettings().chat_token_limit
< RD_AGENT_SETTINGS.chat_token_limit
):
break
elif len(queried_former_failed_knowledge_to_render) > 1: