test(model): update ModelProxy tests to use proper mocking and parameters

Update the unit tests for ModelProxy completions and responses methods
to properly mock litellm functions instead of mocking the data client
completions/responses methods. Also correct the test_responses method
to pass the correct 'input' parameter instead of 'messages'.

The changes ensure that the tests accurately reflect how the ModelProxy
interacts with the underlying litellm API while maintaining proper
mocking behavior.

更新 ModelProxy 测试以使用正确的模拟和参数

更新 ModelProxy 完成和响应方法的单元测试，以正确模拟 litellm 函数，
而不是模拟数据客户端的完成/响应方法。同时修正 test_responses 方法，
传递正确的 'input' 参数而不是 'messages'。

这些更改确保测试准确反映 ModelProxy 如何与底层 litellm API 交互，
同时保持适当的模拟行为。

Change-Id: I5fffbf165d23efa7607c2618b1fd9604df3caeb6
Signed-off-by: OhYee <oyohyee@oyohyee.com>

Author: OhYee

tests/unittests/model/test_model_proxy.py

@@ -527,23 +527,25 @@ class TestModelProxyCompletions:
             "AGENTRUN_ACCOUNT_ID": "test-account",
         },
     )
-    def test_completions(self):
+    @patch("litellm.completion")
+    def test_completions(self, mock_completion):
         from agentrun.model.api.data import BaseInfo
 
+        mock_completion.return_value = {"choices": []}
+
         proxy = ModelProxy(model_proxy_name="test-proxy")
 
-        # Create a mock _data_client directly
+        # Create a mock _data_client to provide model_info
         mock_data_client = MagicMock()
         mock_info = BaseInfo(model="gpt-4", base_url="https://api.example.com")
         mock_data_client.model_info.return_value = mock_info
-        mock_data_client.completions.return_value = {"choices": []}
 
-        # Bypass the model_info call by setting _data_client
+        # Set _data_client so model_info() returns our mock info
         proxy._data_client = mock_data_client
 
         proxy.completions(messages=[{"role": "user", "content": "Hello"}])
 
-        mock_data_client.completions.assert_called_once()
+        mock_completion.assert_called_once()
 
 
 class TestModelProxyResponses:
@@ -557,20 +559,24 @@ class TestModelProxyResponses:
             "AGENTRUN_ACCOUNT_ID": "test-account",
         },
     )
-    def test_responses(self):
+    @patch("litellm.responses")
+    def test_responses(self, mock_responses):
         from agentrun.model.api.data import BaseInfo
 
+        mock_responses.return_value = {}
+
         proxy = ModelProxy(model_proxy_name="test-proxy")
 
-        # Create a mock _data_client directly
+        # Create a mock _data_client to provide model_info
         mock_data_client = MagicMock()
         mock_info = BaseInfo(model="gpt-4", base_url="https://api.example.com")
         mock_data_client.model_info.return_value = mock_info
-        mock_data_client.responses.return_value = {}
 
-        # Bypass the model_info call by setting _data_client
+        # Set _data_client so model_info() returns our mock info
         proxy._data_client = mock_data_client
 
-        proxy.responses(messages=[{"role": "user", "content": "Hello"}])
+        # Note: The responses method expects 'input' parameter (not 'messages')
+        # based on the ModelAPI.responses signature
+        proxy.responses(input="Hello")
 
-        mock_data_client.responses.assert_called_once()
+        mock_responses.assert_called_once()