More LLM tests

tests/unit/test_text_completion/test_ollama_processor.py

@@ -312,6 +312,150 @@ class TestOllamaProcessorSimple(IsolatedAsyncioTestCase):
         # Verify the combined prompt
         mock_client.generate.assert_called_once_with('llama2', "You are a helpful assistant\n\nWhat is AI?", options={'temperature': 0.0})
 
+    @patch('trustgraph.model.text_completion.ollama.llm.Client')
+    @patch('trustgraph.base.async_processor.AsyncProcessor.__init__')
+    @patch('trustgraph.base.llm_service.LlmService.__init__')
+    async def test_generate_content_temperature_override(self, mock_llm_init, mock_async_init, mock_client_class):
+        """Test temperature parameter override functionality"""
+        # Arrange
+        mock_client = MagicMock()
+        mock_response = {
+            'response': 'Response with custom temperature',
+            'prompt_eval_count': 20,
+            'eval_count': 12
+        }
+        mock_client.generate.return_value = mock_response
+        mock_client_class.return_value = mock_client
+
+        mock_async_init.return_value = None
+        mock_llm_init.return_value = None
+
+        config = {
+            'model': 'llama2',
+            'ollama': 'http://localhost:11434',
+            'temperature': 0.0,  # Default temperature
+            'concurrency': 1,
+            'taskgroup': AsyncMock(),
+            'id': 'test-processor'
+        }
+
+        processor = Processor(**config)
+
+        # Act - Override temperature at runtime
+        result = await processor.generate_content(
+            "System prompt",
+            "User prompt",
+            model=None,      # Use default model
+            temperature=0.8  # Override temperature
+        )
+
+        # Assert
+        assert isinstance(result, LlmResult)
+        assert result.text == "Response with custom temperature"
+
+        # Verify Ollama API was called with overridden temperature
+        mock_client.generate.assert_called_once_with(
+            'llama2',
+            "System prompt\n\nUser prompt",
+            options={'temperature': 0.8}  # Should use runtime override
+        )
+
+    @patch('trustgraph.model.text_completion.ollama.llm.Client')
+    @patch('trustgraph.base.async_processor.AsyncProcessor.__init__')
+    @patch('trustgraph.base.llm_service.LlmService.__init__')
+    async def test_generate_content_model_override(self, mock_llm_init, mock_async_init, mock_client_class):
+        """Test model parameter override functionality"""
+        # Arrange
+        mock_client = MagicMock()
+        mock_response = {
+            'response': 'Response with custom model',
+            'prompt_eval_count': 18,
+            'eval_count': 14
+        }
+        mock_client.generate.return_value = mock_response
+        mock_client_class.return_value = mock_client
+
+        mock_async_init.return_value = None
+        mock_llm_init.return_value = None
+
+        config = {
+            'model': 'llama2',    # Default model
+            'ollama': 'http://localhost:11434',
+            'temperature': 0.1,   # Default temperature
+            'concurrency': 1,
+            'taskgroup': AsyncMock(),
+            'id': 'test-processor'
+        }
+
+        processor = Processor(**config)
+
+        # Act - Override model at runtime
+        result = await processor.generate_content(
+            "System prompt",
+            "User prompt",
+            model="mistral",    # Override model
+            temperature=None    # Use default temperature
+        )
+
+        # Assert
+        assert isinstance(result, LlmResult)
+        assert result.text == "Response with custom model"
+
+        # Verify Ollama API was called with overridden model
+        mock_client.generate.assert_called_once_with(
+            'mistral',  # Should use runtime override
+            "System prompt\n\nUser prompt",
+            options={'temperature': 0.1}  # Should use processor default
+        )
+
+    @patch('trustgraph.model.text_completion.ollama.llm.Client')
+    @patch('trustgraph.base.async_processor.AsyncProcessor.__init__')
+    @patch('trustgraph.base.llm_service.LlmService.__init__')
+    async def test_generate_content_both_parameters_override(self, mock_llm_init, mock_async_init, mock_client_class):
+        """Test overriding both model and temperature parameters simultaneously"""
+        # Arrange
+        mock_client = MagicMock()
+        mock_response = {
+            'response': 'Response with both overrides',
+            'prompt_eval_count': 22,
+            'eval_count': 16
+        }
+        mock_client.generate.return_value = mock_response
+        mock_client_class.return_value = mock_client
+
+        mock_async_init.return_value = None
+        mock_llm_init.return_value = None
+
+        config = {
+            'model': 'llama2',    # Default model
+            'ollama': 'http://localhost:11434',
+            'temperature': 0.0,   # Default temperature
+            'concurrency': 1,
+            'taskgroup': AsyncMock(),
+            'id': 'test-processor'
+        }
+
+        processor = Processor(**config)
+
+        # Act - Override both parameters at runtime
+        result = await processor.generate_content(
+            "System prompt",
+            "User prompt",
+            model="codellama",  # Override model
+            temperature=0.9     # Override temperature
+        )
+
+        # Assert
+        assert isinstance(result, LlmResult)
+        assert result.text == "Response with both overrides"
+
+        # Verify Ollama API was called with both overrides
+        mock_client.generate.assert_called_once_with(
+            'codellama',  # Should use runtime override
+            "System prompt\n\nUser prompt",
+            options={'temperature': 0.9}  # Should use runtime override
+        )
+
 
 if __name__ == '__main__':
     pytest.main([__file__])