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Update Operator & Benchmark

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didi 2024-10-21 23:08:51 +08:00
parent fe3fca514a
commit 2d1d7ca219
8 changed files with 87 additions and 51 deletions
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14
optimize.py
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@ -4,6 +4,7 @@
# @Desc : Entrance of AFlow.
from examples.aflow.scripts.optimizer import Optimizer
from examples.aflow.data.download_data import download
from metagpt.configs.models_config import ModelsConfig
from typing import Literal
@ -12,10 +13,13 @@ DatasetType = Literal["HumanEval", "MBPP", "GSM8K", "MATH", "HotpotQA", "DROP"]
QuestionType = Literal["math", "code", "qa"]
OptimizerType = Literal["Graph", "Test"]
# When you fisrt use, please download the datasets and initial rounds; If you want to get a look of the results, please download the results.
# download(["datasets", "results", "initial_rounds"])
# Crucial Parameters
dataset: DatasetType = "HotpotQA" # Ensure the type is consistent with DatasetType
dataset: DatasetType = "GSM8K" # Ensure the type is consistent with DatasetType
sample: int = 4 # Sample Count, which means how many workflows will be resampled from generated workflows
question_type: QuestionType = "quiz" # Ensure the type is consistent with QuestionType
question_type: QuestionType = "code" # Ensure the type is consistent with QuestionType
optimized_path: str = "examples/aflow/scripts/optimized" # Optimized Result Save Path
initial_round: int = 1 # Corrected the case from Initial_round to initial_round
max_rounds: int = 20
@ -30,9 +34,9 @@ operators = [
"Custom", # It's basic unit of a fixed node. optimizer can modify its prompt to get vairous nodes.
# "AnswerGenerate" # It's for qa
# "CustomCodeGenerate", # It's for code
# "ScEnsemble", # It's for code, math and qa
"ScEnsemble", # It's for code, math and qa
# "Test", # It's for code
# "Programmer", # It's for math
"Programmer", # It's for math
]
# Create an optimizer instance
@ -53,4 +57,4 @@ if __name__ == "__main__":
# Optimize workflow via setting the optimizer's mode to 'Graph'
optimizer.optimize("Graph")
# Test workflow via setting the optimizer's mode to 'Test'
optimizer.optimize("Test")
# optimizer.optimize("Test")