wip

README.md

@@ -151,12 +151,6 @@ For a complete working example, see the [Quickstart Example](./examples/quicksta
 
 The example is fully documented with clear explanations of each functionality and includes a comprehensive README with setup instructions and next steps.
 
-## Graph Service
-
-The `server` directory contains an API service for interacting with the Graphiti API. It is built using FastAPI.
-
-Please see the [server README](./server/README.md) for more information.
-
 ## MCP Server
 
 The `mcp_server` directory contains a Model Context Protocol (MCP) server implementation for Graphiti. This server allows AI assistants to interact with Graphiti's knowledge graph capabilities through the MCP protocol.
@@ -173,6 +167,12 @@ The MCP server can be deployed using Docker with Neo4j, making it easy to integr
 
 For detailed setup instructions and usage examples, see the [MCP server README](./mcp_server/README.md).
 
+## Graph Service
+
+The `server` directory contains an API service for interacting with the Graphiti API. It is built using FastAPI.
+
+Please see the [server README](./server/README.md) for more information.
+
 ## Optional Environment Variables
 
 In addition to the Neo4j and OpenAi-compatible credentials, Graphiti also has a few optional environment variables.

graphiti_core/llm_client/openai_client.py

@@ -19,7 +19,7 @@ import typing
 from typing import ClassVar
 
 import openai
-from openai import AsyncOpenAI
+from openai import AsyncAzureOpenAI, AsyncOpenAI
 from openai.types.chat import ChatCompletionMessageParam
 from pydantic import BaseModel
 
@@ -61,7 +61,7 @@ class OpenAIClient(LLMClient):
         self,
         config: LLMConfig | None = None,
         cache: bool = False,
-        client: typing.Any = None,
+        client: AsyncOpenAI | AsyncAzureOpenAI | None = None,
         max_tokens: int = DEFAULT_MAX_TOKENS,
     ):
         """

graphiti_core/utils/maintenance/community_operations.py

@@ -101,9 +101,7 @@ def label_propagation(projection: dict[str, list[Neighbor]]) -> list[list[str]]:
             ]
 
             community_lst.sort(reverse=True)
-            candidate_rank, community_candidate = (
-                community_lst[0] if community_lst else (0, -1)
-            )
+            candidate_rank, community_candidate = community_lst[0] if community_lst else (0, -1)
             if community_candidate != -1 and candidate_rank > 1:
                 new_community = community_candidate
             else: