Update metagpt/ext/spo/utils/llm_client.py

metagpt/ext/spo/utils/llm_client.py

@@ -33,9 +33,9 @@ class SPO_LLM:
             raise ValueError("'model' parameter is required")
 
         try:
-            model_config = ModelsConfig.default().get(model)
+            model_config = ModelsConfig.default().get("gpt-4o-mini")
             if model_config is None:
-                raise ValueError(f"Model '{model}' not found in configuration")
+                raise ValueError(f"Model gpt-4o-mini not found in configuration")
 
             config = model_config.model_copy()
 
@@ -83,25 +83,3 @@ def extract_content(xml_string: str, tag: str) -> Optional[str]:
     return match.group(1).strip() if match else None
 
 
-async def main():
-    # test LLM
-    SPO_LLM.initialize(
-        optimize_kwargs={"model": "gpt-4o", "temperature": 0.7},
-        evaluate_kwargs={"model": "gpt-4o-mini", "temperature": 0.3},
-        execute_kwargs={"model": "gpt-4o-mini", "temperature": 0.3},
-    )
-
-    llm = SPO_LLM.get_instance()
-
-    # test messages
-    hello_msg = [{"role": "user", "content": "hello"}]
-    response = await llm.responser(request_type=RequestType.EXECUTE, messages=hello_msg)
-    logger(f"AI: {response}")
-    response = await llm.responser(request_type=RequestType.OPTIMIZE, messages=hello_msg)
-    logger(f"AI: {response}")
-    response = await llm.responser(request_type=RequestType.EVALUATE, messages=hello_msg)
-    logger(f"AI: {response}")
-
-
-if __name__ == "__main__":
-    asyncio.run(main())