Fix cosine threshold parameter setting error for chroma

lightrag/kg/chroma_impl.py

@@ -1,3 +1,4 @@
+import os
 import asyncio
 from dataclasses import dataclass
 from typing import Union
@@ -12,16 +13,16 @@ from lightrag.utils import logger
 class ChromaVectorDBStorage(BaseVectorStorage):
     """ChromaDB vector storage implementation."""
 
-    cosine_better_than_threshold: float = 0.2
+    cosine_better_than_threshold: float = float(os.getenv("COSINE_THRESHOLD", "0.2"))
 
     def __post_init__(self):
         try:
             # Use global config value if specified, otherwise use default
-            self.cosine_better_than_threshold = self.global_config.get(
+            config = self.global_config.get("vector_db_storage_cls_kwargs", {})
+            self.cosine_better_than_threshold = config.get(
                 "cosine_better_than_threshold", self.cosine_better_than_threshold
             )
 
-            config = self.global_config.get("vector_db_storage_cls_kwargs", {})
             user_collection_settings = config.get("collection_settings", {})
             # Default HNSW index settings for ChromaDB
             default_collection_settings = {

lightrag/kg/nano_vector_db_impl.py

@@ -76,6 +76,12 @@ class NanoVectorDBStorage(BaseVectorStorage):
     cosine_better_than_threshold: float = float(os.getenv("COSINE_THRESHOLD", "0.2"))
 
     def __post_init__(self):
+        # Use global config value if specified, otherwise use default
+        config = self.global_config.get("vector_db_storage_cls_kwargs", {})
+        self.cosine_better_than_threshold = config.get(
+            "cosine_better_than_threshold", self.cosine_better_than_threshold
+        )
+
         self._client_file_name = os.path.join(
             self.global_config["working_dir"], f"vdb_{self.namespace}.json"
         )
@@ -83,14 +89,6 @@ class NanoVectorDBStorage(BaseVectorStorage):
         self._client = NanoVectorDB(
             self.embedding_func.embedding_dim, storage_file=self._client_file_name
         )
-        # get cosine_better_than_threshold from LightRAG
-        vector_db_kwargs = self.global_config.get("vector_db_storage_cls_kwargs", {})
-        self.cosine_better_than_threshold = vector_db_kwargs.get(
-            "cosine_better_than_threshold",
-            self.global_config.get(
-                "cosine_better_than_threshold", self.cosine_better_than_threshold
-            ),
-        )
 
     async def upsert(self, data: dict[str, dict]):
         logger.info(f"Inserting {len(data)} vectors to {self.namespace}")