Add detailed error message for missing model configurations

.gitignore

@@ -192,3 +192,6 @@ cov.xml
 *.csv
 metagpt/ext/sela/results/*
 .chainlit/
+
+metagpt/ext/aflow/data
+metagpt/ext/aflow/scripts/optimized

examples/aflow/optimize.py

@@ -78,23 +78,48 @@ def parse_args():
         default=True,
         help="Whether to download dataset for the first time",
     )
+    parser.add_argument(
+        "--opt_model_name",
+        type=str,
+        default="claude-3-5-sonnet-20240620",
+        help="Specifies the name of the model used for optimization tasks.",
+    )
+    parser.add_argument(
+        "--exec_model_name",
+        type=str,
+        default="gpt-4o-mini",
+        help="Specifies the name of the model used for execution tasks.",
+    )
     return parser.parse_args()
 
 
 if __name__ == "__main__":
     args = parse_args()
 
-    download(["datasets", "initial_rounds"], if_first_download=args.if_first_optimize)
     config = EXPERIMENT_CONFIGS[args.dataset]
 
-    mini_llm_config = ModelsConfig.default().get("gpt-4o-mini")
-    claude_llm_config = ModelsConfig.default().get("claude-3-5-sonnet-20240620")
+    models_config = ModelsConfig.default()
+    opt_llm_config = models_config.get(args.opt_model_name)
+    if opt_llm_config is None:
+        raise ValueError(
+            f"The optimization model '{args.opt_model_name}' was not found in the 'models' section of the configuration file. "
+            "Please add it to the configuration file or specify a valid model using the --opt_model_name flag. "
+        )
+
+    exec_llm_config = models_config.get(args.exec_model_name)
+    if exec_llm_config is None:
+        raise ValueError(
+            f"The execution model '{args.exec_model_name}' was not found in the 'models' section of the configuration file. "
+            "Please add it to the configuration file or specify a valid model using the --exec_model_name flag. "
+        )
+
+    download(["datasets", "initial_rounds"], if_first_download=args.if_first_optimize)
 
     optimizer = Optimizer(
         dataset=config.dataset,
         question_type=config.question_type,
-        opt_llm_config=claude_llm_config,
-        exec_llm_config=mini_llm_config,
+        opt_llm_config=opt_llm_config,
+        exec_llm_config=exec_llm_config,
         check_convergence=args.check_convergence,
         operators=config.operators,
         optimized_path=args.optimized_path,