feat: Make OpenAI and Anthropic API base URLs configurable

- Add openai_api_base and anthropic_api_base fields to Settings
- Update AnthropicClientWrapper to accept and use base_url parameter
- Update get_model_client to use configuration settings instead of env vars directly
- Fix import style to use absolute imports
- Format code with ruff

Co-authored-by: Andrew Brookins <[email protected]>

Author: claude[bot]

agent_memory_server/config.py

@@ -52,6 +52,8 @@ class Settings(BaseSettings):
     long_term_memory: bool = True
     openai_api_key: str | None = None
     anthropic_api_key: str | None = None
+    openai_api_base: str | None = None
+    anthropic_api_base: str | None = None
     generation_model: str = "gpt-4o"
     embedding_model: str = "text-embedding-3-small"
     port: int = 8000

agent_memory_server/llms.py

@@ -9,6 +9,8 @@
 from openai import AsyncOpenAI
 from pydantic import BaseModel
 
+from agent_memory_server.config import settings
+
 
 logger = logging.getLogger(__name__)
 
@@ -203,14 +205,21 @@ def total_tokens(self) -> int:
 class AnthropicClientWrapper:
     """Wrapper for Anthropic client"""
 
-    def __init__(self, api_key: str | None = None):
+    def __init__(self, api_key: str | None = None, base_url: str | None = None):
         """Initialize the Anthropic client"""
         anthropic_api_key = api_key or os.environ.get("ANTHROPIC_API_KEY")
+        anthropic_api_base = base_url or os.environ.get("ANTHROPIC_API_BASE")
 
         if not anthropic_api_key:
             raise ValueError("Anthropic API key is required")
 
-        self.client = anthropic.AsyncAnthropic(api_key=anthropic_api_key)
+        if anthropic_api_base:
+            self.client = anthropic.AsyncAnthropic(
+                api_key=anthropic_api_key,
+                base_url=anthropic_api_base,
+            )
+        else:
+            self.client = anthropic.AsyncAnthropic(api_key=anthropic_api_key)
 
     async def create_chat_completion(
         self,
@@ -397,9 +406,15 @@ async def get_model_client(
         model_config = get_model_config(model_name)
 
         if model_config.provider == ModelProvider.OPENAI:
-            model = OpenAIClientWrapper(api_key=os.environ.get("OPENAI_API_KEY"))
+            model = OpenAIClientWrapper(
+                api_key=settings.openai_api_key,
+                base_url=settings.openai_api_base,
+            )
         if model_config.provider == ModelProvider.ANTHROPIC:
-            model = AnthropicClientWrapper(api_key=os.environ.get("ANTHROPIC_API_KEY"))
+            model = AnthropicClientWrapper(
+                api_key=settings.anthropic_api_key,
+                base_url=settings.anthropic_api_base,
+            )
 
         if model:
             _model_clients[model_name] = model

tests/test_full_integration.py

@@ -772,9 +772,9 @@ async def test_memory_prompt_with_long_term_search(
             )
             for msg in messages
         )
-        assert (
-            relevant_context_found
-        ), f"No relevant memory context found in messages: {messages}"
+        assert relevant_context_found, (
+            f"No relevant memory context found in messages: {messages}"
+        )
 
         # Cleanup
         await client.delete_long_term_memories([m.id for m in test_memories])
@@ -1078,9 +1078,9 @@ async def test_full_workflow_integration(
             )
             print(f"No topic filter search results: {no_topic_search}")
 
-        assert (
-            len(search_results["memories"]) > 0
-        ), f"No memories found in search results: {search_results}"
+        assert len(search_results["memories"]) > 0, (
+            f"No memories found in search results: {search_results}"
+        )
 
         # 6. Test tool integration with a realistic scenario
         tool_call = {
@@ -1125,9 +1125,9 @@ async def test_full_workflow_integration(
             m for m in long_term_memories.memories if m.id.startswith(memory_id_prefix)
         ]
 
-        assert (
-            len(our_memories) == 0
-        ), f"Expected 0 of our memories but found {len(our_memories)}: {our_memories}"
+        assert len(our_memories) == 0, (
+            f"Expected 0 of our memories but found {len(our_memories)}: {our_memories}"
+        )
 
 
 @pytest.mark.integration