Anthropic cleanup (#431)

* remove temporary debug logging

* add anthropic api to .env.example

* move anthropic int tests to llm_client dir to better match existing test structure

* update `TestLLMClient` to `MockLLMClient` to eliminate pytest warning

.env.example

@@ -7,4 +7,5 @@ DEFAULT_DATABASE=
 USE_PARALLEL_RUNTIME=
 SEMAPHORE_LIMIT=
 GITHUB_SHA=
-MAX_REFLEXION_ITERATIONS=
+MAX_REFLEXION_ITERATIONS=
+ANTHROPIC_API_KEY=

graphiti_core/llm_client/anthropic_client.py

@@ -139,15 +139,11 @@ class AnthropicClient(LLMClient):
             A list containing a single tool definition for use with the Anthropic API.
         """
         if response_model is not None:
-            # temporary debug log
-            logger.info(f'Creating tool for response_model: {response_model}')
             # Use the response_model to define the tool
             model_schema = response_model.model_json_schema()
             tool_name = response_model.__name__
             description = model_schema.get('description', f'Extract {tool_name} information')
         else:
-            # temporary debug log
-            logger.info('Creating generic JSON output tool')
             # Create a generic JSON output tool
             tool_name = 'generic_json_output'
             description = 'Output data in JSON format'
@@ -205,8 +201,6 @@ class AnthropicClient(LLMClient):
         try:
             # Create the appropriate tool based on whether response_model is provided
             tools, tool_choice = self._create_tool(response_model)
-            # temporary debug log
-            logger.info(f'using model: {self.model} with max_tokens: {self.max_tokens}')
             result = await self.client.messages.create(
                 system=system_message.content,
                 max_tokens=max_creation_tokens,
@@ -227,13 +221,6 @@ class AnthropicClient(LLMClient):
                     return tool_args
 
             # If we didn't get a proper tool_use response, try to extract from text
-            # logger.debug(
-            #     f'Did not get a tool_use response, trying to extract json from text. Result: {result.content}'
-            # )
-            # temporary debug log
-            logger.info(
-                f'Did not get a tool_use response, trying to extract json from text. Result: {result.content}'
-            )
             for content_item in result.content:
                 if content_item.type == 'text':
                     return self._extract_json_from_text(content_item.text)

tests/llm_client/test_anthropic_client_int.py

@@ -78,7 +78,7 @@ async def test_extract_json_from_text():
     # A string with embedded JSON
     text = 'Some text before {"message": "Hello, world!"} and after'
 
-    result = client._extract_json_from_text(text)
+    result = client._extract_json_from_text(text)  # type: ignore # ignore type check for private method
 
     assert isinstance(result, dict)
     assert 'message' in result

tests/llm_client/test_client.py

@@ -18,7 +18,7 @@ from graphiti_core.llm_client.client import LLMClient
 from graphiti_core.llm_client.config import LLMConfig
 
 
-class TestLLMClient(LLMClient):
+class MockLLMClient(LLMClient):
     """Concrete implementation of LLMClient for testing"""
 
     async def _generate_response(self, messages, response_model=None):
@@ -26,7 +26,7 @@ class TestLLMClient(LLMClient):
 
 
 def test_clean_input():
-    client = TestLLMClient(LLMConfig())
+    client = MockLLMClient(LLMConfig())
 
     test_cases = [
         # Basic text should remain unchanged