Better error handling in L3Score computation

L3Score.py

@@ -128,19 +128,19 @@ class L3Score(evaluate.Metric):
                 client = openai.OpenAI(api_key=api_key)
                 model_names = set([model.id for model in client.models.list()])
                 if model not in model_names:
-                    raise ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")
+                    return ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")
                 
             elif provider == "deepseek":
                 client = openai.OpenAI(api_key=api_key,base_url="https://api.deepseek.com")
                 model_names = [model.id for model in client.models.list()]
                 if model not in model_names:
-                    raise ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")
+                    return ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")
             
             elif provider == "xai":
                 client = openai.OpenAI(api_key=api_key, base_url="https://api.xai.com")
                 model_names = [model.id for model in client.models.list()]
                 if model not in model_names:
-                    raise ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")
+                    return ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")
                 
         except openai.AuthenticationError as e:
             message = e.body["message"]