Better error handling in L3Score computation

L3Score.py

@@ -133,12 +133,14 @@ class L3Score(evaluate.Metric):
             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()]
+                print(model_names)  
                 if model not in 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()]
+                print(model_names)
                 if model not in model_names:
                     return ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")