Fixed error handling

L3Score.py

@@ -122,8 +122,7 @@ class L3Score(evaluate.Metric):
             )
         
         # Check whether the model is available
-        print(provider,model)
-        
+    
         if provider == "openai":
             client = openai.OpenAI(api_key=api_key)
             model_names = set([model.id for model in client.models.list()])
@@ -131,17 +130,14 @@ class L3Score(evaluate.Metric):
                 raise ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")
             
         elif provider == "deepseek":
-            print("Checking DeepSeek model")
             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:
                 raise 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:
                 raise ValueError(f"Model {model} not found for provider {provider}, available models: {model_names}")