Update

optimize.py

@@ -3,43 +3,41 @@
 # @Author  : didi
 # @Desc    : Experiment of graph optimization
 
-from examples.ags.w_action_node.optimizer import Optimizer
+from examples.ags.scripts.optimizer import Optimizer
 from metagpt.configs.models_config import ModelsConfig
 
-# 配置实验参数
-dataset = "Gsm8K"  # 数据集选择为GSM8K
-sample = 6  # 采样数量
-q_type = "math"  # 问题类型为数学
-optimized_path = "examples/ags/w_action_node/optimized"  # 优化结果保存路径
 
-# 初始化LLM模型
-deepseek_llm_config = ModelsConfig.default().get("deepseek-coder")
+# Crucial Parameters
+dataset = "HumanEval"  # DatasetType
+sample = 4  # Sample Count, which means how many workflows will be resampled from generated workflows
+question_type = "code"  # Question Type
+optimized_path = "examples/ags/scripts/optimized"  # Optimized Result Save Path
+
+# Initialize LLM Model
+mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")
 claude_llm_config = ModelsConfig.default().get("claude-3-5-sonnet-20240620")
-# claude_llm_config = ModelsConfig.default().get("deepseek-coder")
-# 初始化操作符列表
-gsm8k_operators = [
+
+# Initialize Operators List
+operators = [
     "Custom",
-    "Generate",
-    "ContextualGenerate",
-    "Format",
-    "Review",
-    "Revise",
-    "FuEnsemble",
-    "MdEnsemble",
+    "CustomCodeGenerate",
     "ScEnsemble",
-    "Rephrase",
+    "Test",
 ]
 
-# 创建优化器实例
+# Create an optimizer instance
 optimizer = Optimizer(
     dataset=dataset,
     opt_llm_config=claude_llm_config,
-    exec_llm_config=deepseek_llm_config,
-    operators=gsm8k_operators,
+    exec_llm_config=mini_llm_config,
+    operators=operators,
     optimized_path=optimized_path,
     sample=sample,
-    q_type=q_type,
+    question_type=question_type,
 )
 
-# 运行优化器
-optimizer.optimize("Operator")
+# Run the optimizer
+optimizer.optimize("Graph", 10)
+# optimizer.optimize("Graph")
+# optimizer.optimize("Operator")
+