fix configuration errors of mongodb, neo4j, and qdrant backends.

lightrag/api/lightrag_server.py

@@ -101,6 +101,7 @@ def estimate_tokens(text: str) -> int:
 
     return int(tokens)
 
+
 def get_default_host(binding_type: str) -> str:
     default_hosts = {
         "ollama": os.getenv("LLM_BINDING_HOST", "http://localhost:11434"),

lightrag/kg/mongo_impl.py

@@ -44,7 +44,7 @@ class MongoKVStorage(BaseKVStorage):
         database = client.get_database(
             os.environ.get(
                 "MONGO_DATABASE",
-                mongo_database=config.get("mongodb", "database", fallback="LightRAG"),
+                config.get("mongodb", "database", fallback="LightRAG"),
             )
         )
         self._data = database.get_collection(self.namespace)

lightrag/kg/neo4j_impl.py

@@ -48,13 +48,13 @@ class Neo4JStorage(BaseGraphStorage):
         self._driver = None
         self._driver_lock = asyncio.Lock()
 
-        URI = os.environ["NEO4J_URI", config.get("neo4j", "uri", fallback=None)]
-        USERNAME = os.environ[
+        URI = os.environ.get("NEO4J_URI", config.get("neo4j", "uri", fallback=None))
+        USERNAME = os.environ.get(
             "NEO4J_USERNAME", config.get("neo4j", "username", fallback=None)
-        ]
-        PASSWORD = os.environ[
+        )
+        PASSWORD = os.environ.get(
             "NEO4J_PASSWORD", config.get("neo4j", "password", fallback=None)
-        ]
+        )
         MAX_CONNECTION_POOL_SIZE = os.environ.get(
             "NEO4J_MAX_CONNECTION_POOL_SIZE",
             config.get("neo4j", "connection_pool_size", fallback=800),

lightrag/kg/qdrant_impl.py

@@ -61,8 +61,8 @@ class QdrantVectorDBStorage(BaseVectorStorage):
         client.create_collection(collection_name, **kwargs)
 
     def __post_init__(self):
-        config = self.global_config.get("vector_db_storage_cls_kwargs", {})
-        cosine_threshold = config.get("cosine_better_than_threshold")
+        kwargs = self.global_config.get("vector_db_storage_cls_kwargs", {})
+        cosine_threshold = kwargs.get("cosine_better_than_threshold")
         if cosine_threshold is None:
             raise ValueError(
                 "cosine_better_than_threshold must be specified in vector_db_storage_cls_kwargs"