Merge branch 'main' into add-Memgraph-graph-db

env.example

@@ -111,25 +111,37 @@ EMBEDDING_BINDING_HOST=http://localhost:11434
 ###########################
 ### Data storage selection
 ###########################
+### In-memory database with data persistence to local files
+# LIGHTRAG_KV_STORAGE=JsonKVStorage
+# LIGHTRAG_DOC_STATUS_STORAGE=JsonDocStatusStorage
+# LIGHTRAG_GRAPH_STORAGE=NetworkXStorage
+# LIGHTRAG_VECTOR_STORAGE=NanoVectorDBStorage
+# LIGHTRAG_VECTOR_STORAGE=FaissVectorDBStorage
 ### PostgreSQL
 # LIGHTRAG_KV_STORAGE=PGKVStorage
 # LIGHTRAG_DOC_STATUS_STORAGE=PGDocStatusStorage
-# LIGHTRAG_VECTOR_STORAGE=PGVectorStorage
 # LIGHTRAG_GRAPH_STORAGE=PGGraphStorage
-### MongoDB
+# LIGHTRAG_VECTOR_STORAGE=PGVectorStorage
+### MongoDB (recommended for production deploy)
 # LIGHTRAG_KV_STORAGE=MongoKVStorage
 # LIGHTRAG_DOC_STATUS_STORAGE=MongoDocStatusStorage
-# LIGHTRAG_VECTOR_STORAGE=MongoVectorDBStorage
 # LIGHTRAG_GRAPH_STORAGE=MongoGraphStorage
-### KV Storage
+# LIGHTRAG_VECTOR_STORAGE=MongoVectorDBStorage
+### Redis Storage (recommended for production deploy)
 # LIGHTRAG_KV_STORAGE=RedisKVStorage
 # LIGHTRAG_DOC_STATUS_STORAGE=RedisDocStatusStorage
-### Vector Storage
-# LIGHTRAG_VECTOR_STORAGE=FaissVectorDBStorage
+### Vector Storage (recommended for production deploy)
 # LIGHTRAG_VECTOR_STORAGE=MilvusVectorDBStorage
-### Graph Storage
+# LIGHTRAG_VECTOR_STORAGE=QdrantVectorDBStorage
+### Graph Storage (recommended for production deploy)
 # LIGHTRAG_GRAPH_STORAGE=Neo4JStorage
-# LIGHTRAG_GRAPH_STORAGE=MemgraphStorage
+
+####################################################################
+### Default workspace for all storage types
+### For the purpose of isolation of data for each LightRAG instance
+### Valid characters: a-z, A-Z, 0-9, and _
+####################################################################
+# WORKSPACE=doc—
 
 ### PostgreSQL Configuration
 POSTGRES_HOST=localhost
@@ -138,31 +150,19 @@ POSTGRES_USER=your_username
 POSTGRES_PASSWORD='your_password'
 POSTGRES_DATABASE=your_database
 POSTGRES_MAX_CONNECTIONS=12
-### separating all data from difference Lightrag instances
-# POSTGRES_WORKSPACE=default
+# POSTGRES_WORKSPACE=forced_workspace_name
 
 ### Neo4j Configuration
 NEO4J_URI=neo4j+s://xxxxxxxx.databases.neo4j.io
 NEO4J_USERNAME=neo4j
 NEO4J_PASSWORD='your_password'
-
-### Independent AGM Configuration(not for AMG embedded in PostreSQL)
-# AGE_POSTGRES_DB=
-# AGE_POSTGRES_USER=
-# AGE_POSTGRES_PASSWORD=
-# AGE_POSTGRES_HOST=
-# AGE_POSTGRES_PORT=8529
-
-# AGE Graph Name(apply to PostgreSQL and independent AGM)
-### AGE_GRAPH_NAME is deprecated
-# AGE_GRAPH_NAME=lightrag
+# NEO4J_WORKSPACE=forced_workspace_name
 
 ### MongoDB Configuration
 MONGO_URI=mongodb://root:root@localhost:27017/
+#MONGO_URI=mongodb+srv://root:[email protected]/?retryWrites=true&w=majority&appName=Cluster0
 MONGO_DATABASE=LightRAG
-### separating all data from difference Lightrag instances(deprecating)
-### separating all data from difference Lightrag instances
-# MONGODB_WORKSPACE=default
+# MONGODB_WORKSPACE=forced_workspace_name
 
 ### Milvus Configuration
 MILVUS_URI=http://localhost:19530
@@ -170,10 +170,13 @@ MILVUS_DB_NAME=lightrag
 # MILVUS_USER=root
 # MILVUS_PASSWORD=your_password
 # MILVUS_TOKEN=your_token
+# MILVUS_WORKSPACE=forced_workspace_name
 
 ### Qdrant
-QDRANT_URL=http://localhost:16333
+QDRANT_URL=http://localhost:6333
 # QDRANT_API_KEY=your-api-key
+# QDRANT_WORKSPACE=forced_workspace_name
 
 ### Redis
 REDIS_URI=redis://localhost:6379
+# REDIS_WORKSPACE=forced_workspace_name

lightrag/api/__init__.py

@@ -1 +1 @@
-__api_version__ = "0178"
+__api_version__ = "0179"

lightrag/api/config.py

@@ -184,10 +184,10 @@ def parse_args() -> argparse.Namespace:
 
     # Namespace
     parser.add_argument(
-        "--namespace-prefix",
+        "--workspace",
         type=str,
-        default=get_env_value("NAMESPACE_PREFIX", ""),
-        help="Prefix of the namespace",
+        default=get_env_value("WORKSPACE", ""),
+        help="Default workspace for all storage",
     )
 
     parser.add_argument(

lightrag/api/lightrag_server.py

@@ -112,8 +112,8 @@ def create_app(args):
     # Check if API key is provided either through env var or args
     api_key = os.getenv("LIGHTRAG_API_KEY") or args.key
 
-    # Initialize document manager
-    doc_manager = DocumentManager(args.input_dir)
+    # Initialize document manager with workspace support for data isolation
+    doc_manager = DocumentManager(args.input_dir, workspace=args.workspace)
 
     @asynccontextmanager
     async def lifespan(app: FastAPI):
@@ -295,6 +295,7 @@ def create_app(args):
     if args.llm_binding in ["lollms", "ollama", "openai"]:
         rag = LightRAG(
             working_dir=args.working_dir,
+            workspace=args.workspace,
             llm_model_func=lollms_model_complete
             if args.llm_binding == "lollms"
             else ollama_model_complete
@@ -330,6 +331,7 @@ def create_app(args):
     else:  # azure_openai
         rag = LightRAG(
             working_dir=args.working_dir,
+            workspace=args.workspace,
             llm_model_func=azure_openai_model_complete,
             chunk_token_size=int(args.chunk_size),
             chunk_overlap_token_size=int(args.chunk_overlap_size),
@@ -472,6 +474,8 @@ def create_app(args):
                     "vector_storage": args.vector_storage,
                     "enable_llm_cache_for_extract": args.enable_llm_cache_for_extract,
                     "enable_llm_cache": args.enable_llm_cache,
+                    "workspace": args.workspace,
+                    "max_graph_nodes": os.getenv("MAX_GRAPH_NODES"),
                 },
                 "auth_mode": auth_mode,
                 "pipeline_busy": pipeline_status.get("busy", False),

lightrag/api/routers/document_routes.py

@@ -475,6 +475,7 @@ class DocumentManager:
     def __init__(
         self,
         input_dir: str,
+        workspace: str = "",  # New parameter for workspace isolation
         supported_extensions: tuple = (
             ".txt",
             ".md",
@@ -515,10 +516,19 @@ class DocumentManager:
             ".less",  # LESS CSS
         ),
     ):
-        self.input_dir = Path(input_dir)
+        # Store the base input directory and workspace
+        self.base_input_dir = Path(input_dir)
+        self.workspace = workspace
         self.supported_extensions = supported_extensions
         self.indexed_files = set()
 
+        # Create workspace-specific input directory
+        # If workspace is provided, create a subdirectory for data isolation
+        if workspace:
+            self.input_dir = self.base_input_dir / workspace
+        else:
+            self.input_dir = self.base_input_dir
+
         # Create input directory if it doesn't exist
         self.input_dir.mkdir(parents=True, exist_ok=True)
 
@@ -714,6 +724,12 @@ async def pipeline_enqueue_file(rag: LightRAG, file_path: Path) -> bool:
 
         # Insert into the RAG queue
         if content:
+            # Check if content contains only whitespace characters
+            if not content.strip():
+                logger.warning(
+                    f"File contains only whitespace characters. file_paths={file_path.name}"
+                )
+
             await rag.apipeline_enqueue_documents(content, file_paths=file_path.name)
             logger.info(f"Successfully fetched and enqueued file: {file_path.name}")
             return True

lightrag/api/utils_api.py

@@ -284,8 +284,10 @@ def display_splash_screen(args: argparse.Namespace) -> None:
     ASCIIColors.yellow(f"{args.vector_storage}")
     ASCIIColors.white("    ├─ Graph Storage: ", end="")
     ASCIIColors.yellow(f"{args.graph_storage}")
-    ASCIIColors.white("    └─ Document Status Storage: ", end="")
+    ASCIIColors.white("    ├─ Document Status Storage: ", end="")
     ASCIIColors.yellow(f"{args.doc_status_storage}")
+    ASCIIColors.white("    └─ Workspace: ", end="")
+    ASCIIColors.yellow(f"{args.workspace if args.workspace else '-'}")
 
     # Server Status
     ASCIIColors.green("\n✨ Server starting up...\n")

lightrag/base.py

@@ -103,6 +103,7 @@ class QueryParam:
 @dataclass
 class StorageNameSpace(ABC):
     namespace: str
+    workspace: str
     global_config: dict[str, Any]
 
     async def initialize(self):

lightrag/kg/faiss_impl.py

@@ -38,9 +38,19 @@ class FaissVectorDBStorage(BaseVectorStorage):
         self.cosine_better_than_threshold = cosine_threshold
 
         # Where to save index file if you want persistent storage
-        self._faiss_index_file = os.path.join(
-            self.global_config["working_dir"], f"faiss_index_{self.namespace}.index"
-        )
+        working_dir = self.global_config["working_dir"]
+        if self.workspace:
+            # Include workspace in the file path for data isolation
+            workspace_dir = os.path.join(working_dir, self.workspace)
+            os.makedirs(workspace_dir, exist_ok=True)
+            self._faiss_index_file = os.path.join(
+                workspace_dir, f"faiss_index_{self.namespace}.index"
+            )
+        else:
+            # Default behavior when workspace is empty
+            self._faiss_index_file = os.path.join(
+                working_dir, f"faiss_index_{self.namespace}.index"
+            )
         self._meta_file = self._faiss_index_file + ".meta.json"
 
         self._max_batch_size = self.global_config["embedding_batch_num"]

lightrag/kg/json_doc_status_impl.py

@@ -30,7 +30,18 @@ class JsonDocStatusStorage(DocStatusStorage):
 
     def __post_init__(self):
         working_dir = self.global_config["working_dir"]
-        self._file_name = os.path.join(working_dir, f"kv_store_{self.namespace}.json")
+        if self.workspace:
+            # Include workspace in the file path for data isolation
+            workspace_dir = os.path.join(working_dir, self.workspace)
+            os.makedirs(workspace_dir, exist_ok=True)
+            self._file_name = os.path.join(
+                workspace_dir, f"kv_store_{self.namespace}.json"
+            )
+        else:
+            # Default behavior when workspace is empty
+            self._file_name = os.path.join(
+                working_dir, f"kv_store_{self.namespace}.json"
+            )
         self._data = None
         self._storage_lock = None
         self.storage_updated = None

lightrag/kg/json_kv_impl.py

@@ -26,7 +26,18 @@ from .shared_storage import (
 class JsonKVStorage(BaseKVStorage):
     def __post_init__(self):
         working_dir = self.global_config["working_dir"]
-        self._file_name = os.path.join(working_dir, f"kv_store_{self.namespace}.json")
+        if self.workspace:
+            # Include workspace in the file path for data isolation
+            workspace_dir = os.path.join(working_dir, self.workspace)
+            os.makedirs(workspace_dir, exist_ok=True)
+            self._file_name = os.path.join(
+                workspace_dir, f"kv_store_{self.namespace}.json"
+            )
+        else:
+            # Default behavior when workspace is empty
+            self._file_name = os.path.join(
+                working_dir, f"kv_store_{self.namespace}.json"
+            )
         self._data = None
         self._storage_lock = None
         self.storage_updated = None

lightrag/kg/milvus_impl.py

@@ -7,10 +7,6 @@ from lightrag.utils import logger, compute_mdhash_id
 from ..base import BaseVectorStorage
 import pipmaster as pm
 
-
-if not pm.is_installed("configparser"):
-    pm.install("configparser")
-
 if not pm.is_installed("pymilvus"):
     pm.install("pymilvus")
 
@@ -660,6 +656,29 @@ class MilvusVectorDBStorage(BaseVectorStorage):
                 raise
 
     def __post_init__(self):
+        # Check for MILVUS_WORKSPACE environment variable first (higher priority)
+        # This allows administrators to force a specific workspace for all Milvus storage instances
+        milvus_workspace = os.environ.get("MILVUS_WORKSPACE")
+        if milvus_workspace and milvus_workspace.strip():
+            # Use environment variable value, overriding the passed workspace parameter
+            effective_workspace = milvus_workspace.strip()
+            logger.info(
+                f"Using MILVUS_WORKSPACE environment variable: '{effective_workspace}' (overriding passed workspace: '{self.workspace}')"
+            )
+        else:
+            # Use the workspace parameter passed during initialization
+            effective_workspace = self.workspace
+            if effective_workspace:
+                logger.debug(
+                    f"Using passed workspace parameter: '{effective_workspace}'"
+                )
+
+        # Build namespace with workspace prefix for data isolation
+        if effective_workspace:
+            self.namespace = f"{effective_workspace}_{self.namespace}"
+            logger.debug(f"Final namespace with workspace prefix: '{self.namespace}'")
+        # When workspace is empty, keep the original namespace unchanged
+
         kwargs = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = kwargs.get("cosine_better_than_threshold")
         if cosine_threshold is None:

lightrag/kg/mongo_impl.py

@@ -25,6 +25,7 @@ if not pm.is_installed("pymongo"):
     pm.install("pymongo")
 
 from pymongo import AsyncMongoClient  # type: ignore
+from pymongo import UpdateOne  # type: ignore
 from pymongo.asynchronous.database import AsyncDatabase  # type: ignore
 from pymongo.asynchronous.collection import AsyncCollection  # type: ignore
 from pymongo.operations import SearchIndexModel  # type: ignore
@@ -81,7 +82,39 @@ class MongoKVStorage(BaseKVStorage):
     db: AsyncDatabase = field(default=None)
     _data: AsyncCollection = field(default=None)
 
+    def __init__(self, namespace, global_config, embedding_func, workspace=None):
+        super().__init__(
+            namespace=namespace,
+            workspace=workspace or "",
+            global_config=global_config,
+            embedding_func=embedding_func,
+        )
+        self.__post_init__()
+
     def __post_init__(self):
+        # Check for MONGODB_WORKSPACE environment variable first (higher priority)
+        # This allows administrators to force a specific workspace for all MongoDB storage instances
+        mongodb_workspace = os.environ.get("MONGODB_WORKSPACE")
+        if mongodb_workspace and mongodb_workspace.strip():
+            # Use environment variable value, overriding the passed workspace parameter
+            effective_workspace = mongodb_workspace.strip()
+            logger.info(
+                f"Using MONGODB_WORKSPACE environment variable: '{effective_workspace}' (overriding passed workspace: '{self.workspace}')"
+            )
+        else:
+            # Use the workspace parameter passed during initialization
+            effective_workspace = self.workspace
+            if effective_workspace:
+                logger.debug(
+                    f"Using passed workspace parameter: '{effective_workspace}'"
+                )
+
+        # Build namespace with workspace prefix for data isolation
+        if effective_workspace:
+            self.namespace = f"{effective_workspace}_{self.namespace}"
+            logger.debug(f"Final namespace with workspace prefix: '{self.namespace}'")
+        # When workspace is empty, keep the original namespace unchanged
+
         self._collection_name = self.namespace
 
     async def initialize(self):
@@ -142,7 +175,6 @@ class MongoKVStorage(BaseKVStorage):
 
         # Unified handling for all namespaces with flattened keys
         # Use bulk_write for better performance
-        from pymongo import UpdateOne
 
         operations = []
         current_time = int(time.time())  # Get current Unix timestamp
@@ -252,7 +284,39 @@ class MongoDocStatusStorage(DocStatusStorage):
     db: AsyncDatabase = field(default=None)
     _data: AsyncCollection = field(default=None)
 
+    def __init__(self, namespace, global_config, embedding_func, workspace=None):
+        super().__init__(
+            namespace=namespace,
+            workspace=workspace or "",
+            global_config=global_config,
+            embedding_func=embedding_func,
+        )
+        self.__post_init__()
+
     def __post_init__(self):
+        # Check for MONGODB_WORKSPACE environment variable first (higher priority)
+        # This allows administrators to force a specific workspace for all MongoDB storage instances
+        mongodb_workspace = os.environ.get("MONGODB_WORKSPACE")
+        if mongodb_workspace and mongodb_workspace.strip():
+            # Use environment variable value, overriding the passed workspace parameter
+            effective_workspace = mongodb_workspace.strip()
+            logger.info(
+                f"Using MONGODB_WORKSPACE environment variable: '{effective_workspace}' (overriding passed workspace: '{self.workspace}')"
+            )
+        else:
+            # Use the workspace parameter passed during initialization
+            effective_workspace = self.workspace
+            if effective_workspace:
+                logger.debug(
+                    f"Using passed workspace parameter: '{effective_workspace}'"
+                )
+
+        # Build namespace with workspace prefix for data isolation
+        if effective_workspace:
+            self.namespace = f"{effective_workspace}_{self.namespace}"
+            logger.debug(f"Final namespace with workspace prefix: '{self.namespace}'")
+        # When workspace is empty, keep the original namespace unchanged
+
         self._collection_name = self.namespace
 
     async def initialize(self):
@@ -367,12 +431,36 @@ class MongoGraphStorage(BaseGraphStorage):
     # edge collection storing source_node_id, target_node_id, and edge_properties
     edgeCollection: AsyncCollection = field(default=None)
 
-    def __init__(self, namespace, global_config, embedding_func):
+    def __init__(self, namespace, global_config, embedding_func, workspace=None):
         super().__init__(
             namespace=namespace,
+            workspace=workspace or "",
             global_config=global_config,
             embedding_func=embedding_func,
         )
+        # Check for MONGODB_WORKSPACE environment variable first (higher priority)
+        # This allows administrators to force a specific workspace for all MongoDB storage instances
+        mongodb_workspace = os.environ.get("MONGODB_WORKSPACE")
+        if mongodb_workspace and mongodb_workspace.strip():
+            # Use environment variable value, overriding the passed workspace parameter
+            effective_workspace = mongodb_workspace.strip()
+            logger.info(
+                f"Using MONGODB_WORKSPACE environment variable: '{effective_workspace}' (overriding passed workspace: '{self.workspace}')"
+            )
+        else:
+            # Use the workspace parameter passed during initialization
+            effective_workspace = self.workspace
+            if effective_workspace:
+                logger.debug(
+                    f"Using passed workspace parameter: '{effective_workspace}'"
+                )
+
+        # Build namespace with workspace prefix for data isolation
+        if effective_workspace:
+            self.namespace = f"{effective_workspace}_{self.namespace}"
+            logger.debug(f"Final namespace with workspace prefix: '{self.namespace}'")
+        # When workspace is empty, keep the original namespace unchanged
+
         self._collection_name = self.namespace
         self._edge_collection_name = f"{self._collection_name}_edges"
 
@@ -1230,8 +1318,52 @@ class MongoGraphStorage(BaseGraphStorage):
 class MongoVectorDBStorage(BaseVectorStorage):
     db: AsyncDatabase | None = field(default=None)
     _data: AsyncCollection | None = field(default=None)
+    _index_name: str = field(default="", init=False)
+
+    def __init__(
+        self, namespace, global_config, embedding_func, workspace=None, meta_fields=None
+    ):
+        super().__init__(
+            namespace=namespace,
+            workspace=workspace or "",
+            global_config=global_config,
+            embedding_func=embedding_func,
+            meta_fields=meta_fields or set(),
+        )
+        self.__post_init__()
 
     def __post_init__(self):
+        # Check for MONGODB_WORKSPACE environment variable first (higher priority)
+        # This allows administrators to force a specific workspace for all MongoDB storage instances
+        mongodb_workspace = os.environ.get("MONGODB_WORKSPACE")
+        if mongodb_workspace and mongodb_workspace.strip():
+            # Use environment variable value, overriding the passed workspace parameter
+            effective_workspace = mongodb_workspace.strip()
+            logger.info(
+                f"Using MONGODB_WORKSPACE environment variable: '{effective_workspace}' (overriding passed workspace: '{self.workspace}')"
+            )
+        else:
+            # Use the workspace parameter passed during initialization
+            effective_workspace = self.workspace
+            if effective_workspace:
+                logger.debug(
+                    f"Using passed workspace parameter: '{effective_workspace}'"
+                )
+
+        # Build namespace with workspace prefix for data isolation
+        if effective_workspace:
+            self.namespace = f"{effective_workspace}_{self.namespace}"
+            logger.debug(f"Final namespace with workspace prefix: '{self.namespace}'")
+        # When workspace is empty, keep the original namespace unchanged
+
+        # Set index name based on workspace for backward compatibility
+        if effective_workspace:
+            # Use collection-specific index name for workspaced collections to avoid conflicts
+            self._index_name = f"vector_knn_index_{self.namespace}"
+        else:
+            # Keep original index name for backward compatibility with existing deployments
+            self._index_name = "vector_knn_index"
+
         kwargs = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = kwargs.get("cosine_better_than_threshold")
         if cosine_threshold is None:
@@ -1261,13 +1393,11 @@ class MongoVectorDBStorage(BaseVectorStorage):
     async def create_vector_index_if_not_exists(self):
         """Creates an Atlas Vector Search index."""
         try:
-            index_name = "vector_knn_index"
-
             indexes_cursor = await self._data.list_search_indexes()
             indexes = await indexes_cursor.to_list(length=None)
             for index in indexes:
-                if index["name"] == index_name:
-                    logger.debug("vector index already exist")
+                if index["name"] == self._index_name:
+                    logger.info(f"vector index {self._index_name} already exist")
                     return
 
             search_index_model = SearchIndexModel(
@@ -1281,15 +1411,15 @@ class MongoVectorDBStorage(BaseVectorStorage):
                         }
                     ]
                 },
-                name=index_name,
+                name=self._index_name,
                 type="vectorSearch",
             )
 
             await self._data.create_search_index(search_index_model)
-            logger.info("Vector index created successfully.")
+            logger.info(f"Vector index {self._index_name} created successfully.")
 
-        except PyMongoError as _:
-            logger.debug("vector index already exist")
+        except PyMongoError as e:
+            logger.error(f"Error creating vector index {self._index_name}: {e}")
 
     async def upsert(self, data: dict[str, dict[str, Any]]) -> None:
         logger.debug(f"Inserting {len(data)} to {self.namespace}")
@@ -1344,7 +1474,7 @@ class MongoVectorDBStorage(BaseVectorStorage):
         pipeline = [
             {
                 "$vectorSearch": {
-                    "index": "vector_knn_index",  # Ensure this matches the created index name
+                    "index": self._index_name,  # Use stored index name for consistency
                     "path": "vector",
                     "queryVector": query_vector,
                     "numCandidates": 100,  # Adjust for performance

lightrag/kg/nano_vector_db_impl.py

@@ -41,9 +41,19 @@ class NanoVectorDBStorage(BaseVectorStorage):
             )
         self.cosine_better_than_threshold = cosine_threshold
 
-        self._client_file_name = os.path.join(
-            self.global_config["working_dir"], f"vdb_{self.namespace}.json"
-        )
+        working_dir = self.global_config["working_dir"]
+        if self.workspace:
+            # Include workspace in the file path for data isolation
+            workspace_dir = os.path.join(working_dir, self.workspace)
+            os.makedirs(workspace_dir, exist_ok=True)
+            self._client_file_name = os.path.join(
+                workspace_dir, f"vdb_{self.namespace}.json"
+            )
+        else:
+            # Default behavior when workspace is empty
+            self._client_file_name = os.path.join(
+                working_dir, f"vdb_{self.namespace}.json"
+            )
         self._max_batch_size = self.global_config["embedding_batch_num"]
 
         self._client = NanoVectorDB(

lightrag/kg/neo4j_impl.py

@@ -50,14 +50,25 @@ logging.getLogger("neo4j").setLevel(logging.ERROR)
 @final
 @dataclass
 class Neo4JStorage(BaseGraphStorage):
-    def __init__(self, namespace, global_config, embedding_func):
+    def __init__(self, namespace, global_config, embedding_func, workspace=None):
+        # Check NEO4J_WORKSPACE environment variable and override workspace if set
+        neo4j_workspace = os.environ.get("NEO4J_WORKSPACE")
+        if neo4j_workspace and neo4j_workspace.strip():
+            workspace = neo4j_workspace
+
         super().__init__(
             namespace=namespace,
+            workspace=workspace or "",
             global_config=global_config,
             embedding_func=embedding_func,
         )
         self._driver = None
 
+    def _get_workspace_label(self) -> str:
+        """Get workspace label, return 'base' for compatibility when workspace is empty"""
+        workspace = getattr(self, "workspace", None)
+        return workspace if workspace else "base"
+
     async def initialize(self):
         URI = os.environ.get("NEO4J_URI", config.get("neo4j", "uri", fallback=None))
         USERNAME = os.environ.get(
@@ -153,13 +164,14 @@ class Neo4JStorage(BaseGraphStorage):
                             raise e
 
             if connected:
-                # Create index for base nodes on entity_id if it doesn't exist
+                # Create index for workspace nodes on entity_id if it doesn't exist
+                workspace_label = self._get_workspace_label()
                 try:
                     async with self._driver.session(database=database) as session:
                         # Check if index exists first
-                        check_query = """
+                        check_query = f"""
                         CALL db.indexes() YIELD name, labelsOrTypes, properties
-                        WHERE labelsOrTypes = ['base'] AND properties = ['entity_id']
+                        WHERE labelsOrTypes = ['{workspace_label}'] AND properties = ['entity_id']
                         RETURN count(*) > 0 AS exists
                         """
                         try:
@@ -172,16 +184,16 @@ class Neo4JStorage(BaseGraphStorage):
                             if not index_exists:
                                 # Create index only if it doesn't exist
                                 result = await session.run(
-                                    "CREATE INDEX FOR (n:base) ON (n.entity_id)"
+                                    f"CREATE INDEX FOR (n:`{workspace_label}`) ON (n.entity_id)"
                                 )
                                 await result.consume()
                                 logger.info(
-                                    f"Created index for base nodes on entity_id in {database}"
+                                    f"Created index for {workspace_label} nodes on entity_id in {database}"
                                 )
                         except Exception:
                             # Fallback if db.indexes() is not supported in this Neo4j version
                             result = await session.run(
-                                "CREATE INDEX IF NOT EXISTS FOR (n:base) ON (n.entity_id)"
+                                f"CREATE INDEX IF NOT EXISTS FOR (n:`{workspace_label}`) ON (n.entity_id)"
                             )
                             await result.consume()
                 except Exception as e:
@@ -216,11 +228,12 @@ class Neo4JStorage(BaseGraphStorage):
             ValueError: If node_id is invalid
             Exception: If there is an error executing the query
         """
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
             try:
-                query = "MATCH (n:base {entity_id: $entity_id}) RETURN count(n) > 0 AS node_exists"
+                query = f"MATCH (n:`{workspace_label}` {{entity_id: $entity_id}}) RETURN count(n) > 0 AS node_exists"
                 result = await session.run(query, entity_id=node_id)
                 single_result = await result.single()
                 await result.consume()  # Ensure result is fully consumed
@@ -245,12 +258,13 @@ class Neo4JStorage(BaseGraphStorage):
             ValueError: If either node_id is invalid
             Exception: If there is an error executing the query
         """
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
             try:
                 query = (
-                    "MATCH (a:base {entity_id: $source_entity_id})-[r]-(b:base {entity_id: $target_entity_id}) "
+                    f"MATCH (a:`{workspace_label}` {{entity_id: $source_entity_id}})-[r]-(b:`{workspace_label}` {{entity_id: $target_entity_id}}) "
                     "RETURN COUNT(r) > 0 AS edgeExists"
                 )
                 result = await session.run(
@@ -282,11 +296,14 @@ class Neo4JStorage(BaseGraphStorage):
             ValueError: If node_id is invalid
             Exception: If there is an error executing the query
         """
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
             try:
-                query = "MATCH (n:base {entity_id: $entity_id}) RETURN n"
+                query = (
+                    f"MATCH (n:`{workspace_label}` {{entity_id: $entity_id}}) RETURN n"
+                )
                 result = await session.run(query, entity_id=node_id)
                 try:
                     records = await result.fetch(
@@ -300,12 +317,12 @@ class Neo4JStorage(BaseGraphStorage):
                     if records:
                         node = records[0]["n"]
                         node_dict = dict(node)
-                        # Remove base label from labels list if it exists
+                        # Remove workspace label from labels list if it exists
                         if "labels" in node_dict:
                             node_dict["labels"] = [
                                 label
                                 for label in node_dict["labels"]
-                                if label != "base"
+                                if label != workspace_label
                             ]
                         # logger.debug(f"Neo4j query node {query} return: {node_dict}")
                         return node_dict
@@ -326,12 +343,13 @@ class Neo4JStorage(BaseGraphStorage):
         Returns:
             A dictionary mapping each node_id to its node data (or None if not found).
         """
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
-            query = """
+            query = f"""
             UNWIND $node_ids AS id
-            MATCH (n:base {entity_id: id})
+            MATCH (n:`{workspace_label}` {{entity_id: id}})
             RETURN n.entity_id AS entity_id, n
             """
             result = await session.run(query, node_ids=node_ids)
@@ -340,10 +358,12 @@ class Neo4JStorage(BaseGraphStorage):
                 entity_id = record["entity_id"]
                 node = record["n"]
                 node_dict = dict(node)
-                # Remove the 'base' label if present in a 'labels' property
+                # Remove the workspace label if present in a 'labels' property
                 if "labels" in node_dict:
                     node_dict["labels"] = [
-                        label for label in node_dict["labels"] if label != "base"
+                        label
+                        for label in node_dict["labels"]
+                        if label != workspace_label
                     ]
                 nodes[entity_id] = node_dict
             await result.consume()  # Make sure to consume the result fully
@@ -364,12 +384,13 @@ class Neo4JStorage(BaseGraphStorage):
             ValueError: If node_id is invalid
             Exception: If there is an error executing the query
         """
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
             try:
-                query = """
-                    MATCH (n:base {entity_id: $entity_id})
+                query = f"""
+                    MATCH (n:`{workspace_label}` {{entity_id: $entity_id}})
                     OPTIONAL MATCH (n)-[r]-()
                     RETURN COUNT(r) AS degree
                 """
@@ -403,13 +424,14 @@ class Neo4JStorage(BaseGraphStorage):
             A dictionary mapping each node_id to its degree (number of relationships).
             If a node is not found, its degree will be set to 0.
         """
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
-            query = """
+            query = f"""
                 UNWIND $node_ids AS id
-                MATCH (n:base {entity_id: id})
-                RETURN n.entity_id AS entity_id, count { (n)--() } AS degree;
+                MATCH (n:`{workspace_label}` {{entity_id: id}})
+                RETURN n.entity_id AS entity_id, count {{ (n)--() }} AS degree;
             """
             result = await session.run(query, node_ids=node_ids)
             degrees = {}
@@ -489,12 +511,13 @@ class Neo4JStorage(BaseGraphStorage):
             ValueError: If either node_id is invalid
             Exception: If there is an error executing the query
         """
+        workspace_label = self._get_workspace_label()
         try:
             async with self._driver.session(
                 database=self._DATABASE, default_access_mode="READ"
             ) as session:
-                query = """
-                MATCH (start:base {entity_id: $source_entity_id})-[r]-(end:base {entity_id: $target_entity_id})
+                query = f"""
+                MATCH (start:`{workspace_label}` {{entity_id: $source_entity_id}})-[r]-(end:`{workspace_label}` {{entity_id: $target_entity_id}})
                 RETURN properties(r) as edge_properties
                 """
                 result = await session.run(
@@ -571,12 +594,13 @@ class Neo4JStorage(BaseGraphStorage):
         Returns:
             A dictionary mapping (src, tgt) tuples to their edge properties.
         """
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
-            query = """
+            query = f"""
             UNWIND $pairs AS pair
-            MATCH (start:base {entity_id: pair.src})-[r:DIRECTED]-(end:base {entity_id: pair.tgt})
+            MATCH (start:`{workspace_label}` {{entity_id: pair.src}})-[r:DIRECTED]-(end:`{workspace_label}` {{entity_id: pair.tgt}})
             RETURN pair.src AS src_id, pair.tgt AS tgt_id, collect(properties(r)) AS edges
             """
             result = await session.run(query, pairs=pairs)
@@ -627,8 +651,9 @@ class Neo4JStorage(BaseGraphStorage):
                 database=self._DATABASE, default_access_mode="READ"
             ) as session:
                 try:
-                    query = """MATCH (n:base {entity_id: $entity_id})
-                            OPTIONAL MATCH (n)-[r]-(connected:base)
+                    workspace_label = self._get_workspace_label()
+                    query = f"""MATCH (n:`{workspace_label}` {{entity_id: $entity_id}})
+                            OPTIONAL MATCH (n)-[r]-(connected:`{workspace_label}`)
                             WHERE connected.entity_id IS NOT NULL
                             RETURN n, r, connected"""
                     results = await session.run(query, entity_id=source_node_id)
@@ -689,10 +714,11 @@ class Neo4JStorage(BaseGraphStorage):
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
             # Query to get both outgoing and incoming edges
-            query = """
+            workspace_label = self._get_workspace_label()
+            query = f"""
                 UNWIND $node_ids AS id
-                MATCH (n:base {entity_id: id})
-                OPTIONAL MATCH (n)-[r]-(connected:base)
+                MATCH (n:`{workspace_label}` {{entity_id: id}})
+                OPTIONAL MATCH (n)-[r]-(connected:`{workspace_label}`)
                 RETURN id AS queried_id, n.entity_id AS node_entity_id,
                        connected.entity_id AS connected_entity_id,
                        startNode(r).entity_id AS start_entity_id
@@ -727,12 +753,13 @@ class Neo4JStorage(BaseGraphStorage):
             return edges_dict
 
     async def get_nodes_by_chunk_ids(self, chunk_ids: list[str]) -> list[dict]:
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
-            query = """
+            query = f"""
             UNWIND $chunk_ids AS chunk_id
-            MATCH (n:base)
+            MATCH (n:`{workspace_label}`)
             WHERE n.source_id IS NOT NULL AND chunk_id IN split(n.source_id, $sep)
             RETURN DISTINCT n
             """
@@ -748,12 +775,13 @@ class Neo4JStorage(BaseGraphStorage):
             return nodes
 
     async def get_edges_by_chunk_ids(self, chunk_ids: list[str]) -> list[dict]:
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
-            query = """
+            query = f"""
             UNWIND $chunk_ids AS chunk_id
-            MATCH (a:base)-[r]-(b:base)
+            MATCH (a:`{workspace_label}`)-[r]-(b:`{workspace_label}`)
             WHERE r.source_id IS NOT NULL AND chunk_id IN split(r.source_id, $sep)
             RETURN DISTINCT a.entity_id AS source, b.entity_id AS target, properties(r) AS properties
             """
@@ -787,6 +815,7 @@ class Neo4JStorage(BaseGraphStorage):
             node_id: The unique identifier for the node (used as label)
             node_data: Dictionary of node properties
         """
+        workspace_label = self._get_workspace_label()
         properties = node_data
         entity_type = properties["entity_type"]
         if "entity_id" not in properties:
@@ -796,14 +825,11 @@ class Neo4JStorage(BaseGraphStorage):
             async with self._driver.session(database=self._DATABASE) as session:
 
                 async def execute_upsert(tx: AsyncManagedTransaction):
-                    query = (
-                        """
-                    MERGE (n:base {entity_id: $entity_id})
+                    query = f"""
+                    MERGE (n:`{workspace_label}` {{entity_id: $entity_id}})
                     SET n += $properties
-                    SET n:`%s`
+                    SET n:`{entity_type}`
                     """
-                        % entity_type
-                    )
                     result = await tx.run(
                         query, entity_id=node_id, properties=properties
                     )
@@ -847,10 +873,11 @@ class Neo4JStorage(BaseGraphStorage):
             async with self._driver.session(database=self._DATABASE) as session:
 
                 async def execute_upsert(tx: AsyncManagedTransaction):
-                    query = """
-                    MATCH (source:base {entity_id: $source_entity_id})
+                    workspace_label = self._get_workspace_label()
+                    query = f"""
+                    MATCH (source:`{workspace_label}` {{entity_id: $source_entity_id}})
                     WITH source
-                    MATCH (target:base {entity_id: $target_entity_id})
+                    MATCH (target:`{workspace_label}` {{entity_id: $target_entity_id}})
                     MERGE (source)-[r:DIRECTED]-(target)
                     SET r += $properties
                     RETURN r, source, target
@@ -889,6 +916,7 @@ class Neo4JStorage(BaseGraphStorage):
             KnowledgeGraph object containing nodes and edges, with an is_truncated flag
             indicating whether the graph was truncated due to max_nodes limit
         """
+        workspace_label = self._get_workspace_label()
         result = KnowledgeGraph()
         seen_nodes = set()
         seen_edges = set()
@@ -899,7 +927,9 @@ class Neo4JStorage(BaseGraphStorage):
             try:
                 if node_label == "*":
                     # First check total node count to determine if graph is truncated
-                    count_query = "MATCH (n) RETURN count(n) as total"
+                    count_query = (
+                        f"MATCH (n:`{workspace_label}`) RETURN count(n) as total"
+                    )
                     count_result = None
                     try:
                         count_result = await session.run(count_query)
@@ -915,13 +945,13 @@ class Neo4JStorage(BaseGraphStorage):
                             await count_result.consume()
 
                     # Run main query to get nodes with highest degree
-                    main_query = """
-                    MATCH (n)
+                    main_query = f"""
+                    MATCH (n:`{workspace_label}`)
                     OPTIONAL MATCH (n)-[r]-()
                     WITH n, COALESCE(count(r), 0) AS degree
                     ORDER BY degree DESC
                     LIMIT $max_nodes
-                    WITH collect({node: n}) AS filtered_nodes
+                    WITH collect({{node: n}}) AS filtered_nodes
                     UNWIND filtered_nodes AS node_info
                     WITH collect(node_info.node) AS kept_nodes, filtered_nodes
                     OPTIONAL MATCH (a)-[r]-(b)
@@ -943,20 +973,21 @@ class Neo4JStorage(BaseGraphStorage):
                 else:
                     # return await self._robust_fallback(node_label, max_depth, max_nodes)
                     # First try without limit to check if we need to truncate
-                    full_query = """
-                    MATCH (start)
+                    full_query = f"""
+                    MATCH (start:`{workspace_label}`)
                     WHERE start.entity_id = $entity_id
                     WITH start
-                    CALL apoc.path.subgraphAll(start, {
+                    CALL apoc.path.subgraphAll(start, {{
                         relationshipFilter: '',
+                        labelFilter: '{workspace_label}',
                         minLevel: 0,
                         maxLevel: $max_depth,
                         bfs: true
-                    })
+                    }})
                     YIELD nodes, relationships
                     WITH nodes, relationships, size(nodes) AS total_nodes
                     UNWIND nodes AS node
-                    WITH collect({node: node}) AS node_info, relationships, total_nodes
+                    WITH collect({{node: node}}) AS node_info, relationships, total_nodes
                     RETURN node_info, relationships, total_nodes
                     """
 
@@ -994,20 +1025,21 @@ class Neo4JStorage(BaseGraphStorage):
                             )
 
                             # Run limited query
-                            limited_query = """
-                            MATCH (start)
+                            limited_query = f"""
+                            MATCH (start:`{workspace_label}`)
                             WHERE start.entity_id = $entity_id
                             WITH start
-                            CALL apoc.path.subgraphAll(start, {
+                            CALL apoc.path.subgraphAll(start, {{
                                 relationshipFilter: '',
+                                labelFilter: '{workspace_label}',
                                 minLevel: 0,
                                 maxLevel: $max_depth,
                                 limit: $max_nodes,
                                 bfs: true
-                            })
+                            }})
                             YIELD nodes, relationships
                             UNWIND nodes AS node
-                            WITH collect({node: node}) AS node_info, relationships
+                            WITH collect({{node: node}}) AS node_info, relationships
                             RETURN node_info, relationships
                             """
                             result_set = None
@@ -1094,11 +1126,12 @@ class Neo4JStorage(BaseGraphStorage):
         visited_edge_pairs = set()
 
         # Get the starting node's data
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
-            query = """
-            MATCH (n:base {entity_id: $entity_id})
+            query = f"""
+            MATCH (n:`{workspace_label}` {{entity_id: $entity_id}})
             RETURN id(n) as node_id, n
             """
             node_result = await session.run(query, entity_id=node_label)
@@ -1156,8 +1189,9 @@ class Neo4JStorage(BaseGraphStorage):
             async with self._driver.session(
                 database=self._DATABASE, default_access_mode="READ"
             ) as session:
-                query = """
-                MATCH (a:base {entity_id: $entity_id})-[r]-(b)
+                workspace_label = self._get_workspace_label()
+                query = f"""
+                MATCH (a:`{workspace_label}` {{entity_id: $entity_id}})-[r]-(b)
                 WITH r, b, id(r) as edge_id, id(b) as target_id
                 RETURN r, b, edge_id, target_id
                 """
@@ -1241,6 +1275,7 @@ class Neo4JStorage(BaseGraphStorage):
         Returns:
             ["Person", "Company", ...]  # Alphabetically sorted label list
         """
+        workspace_label = self._get_workspace_label()
         async with self._driver.session(
             database=self._DATABASE, default_access_mode="READ"
         ) as session:
@@ -1248,8 +1283,8 @@ class Neo4JStorage(BaseGraphStorage):
             # query = "CALL db.labels() YIELD label RETURN label"
 
             # Method 2: Query compatible with older versions
-            query = """
-            MATCH (n:base)
+            query = f"""
+            MATCH (n:`{workspace_label}`)
             WHERE n.entity_id IS NOT NULL
             RETURN DISTINCT n.entity_id AS label
             ORDER BY label
@@ -1285,8 +1320,9 @@ class Neo4JStorage(BaseGraphStorage):
         """
 
         async def _do_delete(tx: AsyncManagedTransaction):
-            query = """
-            MATCH (n:base {entity_id: $entity_id})
+            workspace_label = self._get_workspace_label()
+            query = f"""
+            MATCH (n:`{workspace_label}` {{entity_id: $entity_id}})
             DETACH DELETE n
             """
             result = await tx.run(query, entity_id=node_id)
@@ -1342,8 +1378,9 @@ class Neo4JStorage(BaseGraphStorage):
         for source, target in edges:
 
             async def _do_delete_edge(tx: AsyncManagedTransaction):
-                query = """
-                MATCH (source:base {entity_id: $source_entity_id})-[r]-(target:base {entity_id: $target_entity_id})
+                workspace_label = self._get_workspace_label()
+                query = f"""
+                MATCH (source:`{workspace_label}` {{entity_id: $source_entity_id}})-[r]-(target:`{workspace_label}` {{entity_id: $target_entity_id}})
                 DELETE r
                 """
                 result = await tx.run(
@@ -1360,26 +1397,32 @@ class Neo4JStorage(BaseGraphStorage):
                 raise
 
     async def drop(self) -> dict[str, str]:
-        """Drop all data from storage and clean up resources
+        """Drop all data from current workspace storage and clean up resources
 
-        This method will delete all nodes and relationships in the Neo4j database.
+        This method will delete all nodes and relationships in the current workspace only.
 
         Returns:
             dict[str, str]: Operation status and message
-            - On success: {"status": "success", "message": "data dropped"}
+            - On success: {"status": "success", "message": "workspace data dropped"}
             - On failure: {"status": "error", "message": "<error details>"}
         """
+        workspace_label = self._get_workspace_label()
         try:
             async with self._driver.session(database=self._DATABASE) as session:
-                # Delete all nodes and relationships
-                query = "MATCH (n) DETACH DELETE n"
+                # Delete all nodes and relationships in current workspace only
+                query = f"MATCH (n:`{workspace_label}`) DETACH DELETE n"
                 result = await session.run(query)
                 await result.consume()  # Ensure result is fully consumed
 
                 logger.info(
-                    f"Process {os.getpid()} drop Neo4j database {self._DATABASE}"
+                    f"Process {os.getpid()} drop Neo4j workspace '{workspace_label}' in database {self._DATABASE}"
                 )
-                return {"status": "success", "message": "data dropped"}
+                return {
+                    "status": "success",
+                    "message": f"workspace '{workspace_label}' data dropped",
+                }
         except Exception as e:
-            logger.error(f"Error dropping Neo4j database {self._DATABASE}: {e}")
+            logger.error(
+                f"Error dropping Neo4j workspace '{workspace_label}' in database {self._DATABASE}: {e}"
+            )
             return {"status": "error", "message": str(e)}

lightrag/kg/networkx_impl.py

@@ -46,9 +46,19 @@ class NetworkXStorage(BaseGraphStorage):
         nx.write_graphml(graph, file_name)
 
     def __post_init__(self):
-        self._graphml_xml_file = os.path.join(
-            self.global_config["working_dir"], f"graph_{self.namespace}.graphml"
-        )
+        working_dir = self.global_config["working_dir"]
+        if self.workspace:
+            # Include workspace in the file path for data isolation
+            workspace_dir = os.path.join(working_dir, self.workspace)
+            os.makedirs(workspace_dir, exist_ok=True)
+            self._graphml_xml_file = os.path.join(
+                workspace_dir, f"graph_{self.namespace}.graphml"
+            )
+        else:
+            # Default behavior when workspace is empty
+            self._graphml_xml_file = os.path.join(
+                working_dir, f"graph_{self.namespace}.graphml"
+            )
         self._storage_lock = None
         self.storage_updated = None
         self._graph = None

lightrag/kg/postgres_impl.py

@@ -1,6 +1,7 @@
 import asyncio
 import json
 import os
+import re
 import datetime
 from datetime import timezone
 from dataclasses import dataclass, field
@@ -319,7 +320,7 @@ class PostgreSQLDB:
             # Get all old format data
             old_data_sql = """
             SELECT id, mode, original_prompt, return_value, chunk_id,
-                   create_time, update_time
+                workspace, create_time, update_time
             FROM LIGHTRAG_LLM_CACHE
             WHERE id NOT LIKE '%:%'
             """
@@ -364,7 +365,9 @@ class PostgreSQLDB:
                     await self.execute(
                         insert_sql,
                         {
-                            "workspace": self.workspace,
+                            "workspace": record[
+                                "workspace"
+                            ],  # Use original record's workspace
                             "id": new_key,
                             "mode": record["mode"],
                             "original_prompt": record["original_prompt"],
@@ -384,7 +387,9 @@ class PostgreSQLDB:
                     await self.execute(
                         delete_sql,
                         {
-                            "workspace": self.workspace,
+                            "workspace": record[
+                                "workspace"
+                            ],  # Use original record's workspace
                             "mode": record["mode"],
                             "id": record["id"],  # Old id
                         },
@@ -505,6 +510,29 @@ class PostgreSQLDB:
                     f"PostgreSQL, Failed to create index on table {k}, Got: {e}"
                 )
 
+            # Create composite index for (workspace, id) columns in each table
+            try:
+                composite_index_name = f"idx_{k.lower()}_workspace_id"
+                check_composite_index_sql = f"""
+                SELECT 1 FROM pg_indexes
+                WHERE indexname = '{composite_index_name}'
+                AND tablename = '{k.lower()}'
+                """
+                composite_index_exists = await self.query(check_composite_index_sql)
+
+                if not composite_index_exists:
+                    create_composite_index_sql = (
+                        f"CREATE INDEX {composite_index_name} ON {k}(workspace, id)"
+                    )
+                    logger.info(
+                        f"PostgreSQL, Creating composite index {composite_index_name} on table {k}"
+                    )
+                    await self.execute(create_composite_index_sql)
+            except Exception as e:
+                logger.error(
+                    f"PostgreSQL, Failed to create composite index on table {k}, Got: {e}"
+                )
+
         # After all tables are created, attempt to migrate timestamp fields
         try:
             await self._migrate_timestamp_columns()
@@ -670,7 +698,7 @@ class ClientManager:
             ),
             "workspace": os.environ.get(
                 "POSTGRES_WORKSPACE",
-                config.get("postgres", "workspace", fallback="default"),
+                config.get("postgres", "workspace", fallback=None),
             ),
             "max_connections": os.environ.get(
                 "POSTGRES_MAX_CONNECTIONS",
@@ -716,6 +744,18 @@ class PGKVStorage(BaseKVStorage):
     async def initialize(self):
         if self.db is None:
             self.db = await ClientManager.get_client()
+            # Implement workspace priority: PostgreSQLDB.workspace > self.workspace > "default"
+            if self.db.workspace:
+                # Use PostgreSQLDB's workspace (highest priority)
+                final_workspace = self.db.workspace
+            elif hasattr(self, "workspace") and self.workspace:
+                # Use storage class's workspace (medium priority)
+                final_workspace = self.workspace
+                self.db.workspace = final_workspace
+            else:
+                # Use "default" for compatibility (lowest priority)
+                final_workspace = "default"
+                self.db.workspace = final_workspace
 
     async def finalize(self):
         if self.db is not None:
@@ -1047,6 +1087,18 @@ class PGVectorStorage(BaseVectorStorage):
     async def initialize(self):
         if self.db is None:
             self.db = await ClientManager.get_client()
+            # Implement workspace priority: PostgreSQLDB.workspace > self.workspace > "default"
+            if self.db.workspace:
+                # Use PostgreSQLDB's workspace (highest priority)
+                final_workspace = self.db.workspace
+            elif hasattr(self, "workspace") and self.workspace:
+                # Use storage class's workspace (medium priority)
+                final_workspace = self.workspace
+                self.db.workspace = final_workspace
+            else:
+                # Use "default" for compatibility (lowest priority)
+                final_workspace = "default"
+                self.db.workspace = final_workspace
 
     async def finalize(self):
         if self.db is not None:
@@ -1328,6 +1380,18 @@ class PGDocStatusStorage(DocStatusStorage):
     async def initialize(self):
         if self.db is None:
             self.db = await ClientManager.get_client()
+            # Implement workspace priority: PostgreSQLDB.workspace > self.workspace > "default"
+            if self.db.workspace:
+                # Use PostgreSQLDB's workspace (highest priority)
+                final_workspace = self.db.workspace
+            elif hasattr(self, "workspace") and self.workspace:
+                # Use storage class's workspace (medium priority)
+                final_workspace = self.workspace
+                self.db.workspace = final_workspace
+            else:
+                # Use "default" for compatibility (lowest priority)
+                final_workspace = "default"
+                self.db.workspace = final_workspace
 
     async def finalize(self):
         if self.db is not None:
@@ -1606,9 +1670,34 @@ class PGGraphQueryException(Exception):
 @dataclass
 class PGGraphStorage(BaseGraphStorage):
     def __post_init__(self):
-        self.graph_name = self.namespace or os.environ.get("AGE_GRAPH_NAME", "lightrag")
+        # Graph name will be dynamically generated in initialize() based on workspace
         self.db: PostgreSQLDB | None = None
 
+    def _get_workspace_graph_name(self) -> str:
+        """
+        Generate graph name based on workspace and namespace for data isolation.
+        Rules:
+        - If workspace is empty: graph_name = namespace
+        - If workspace has value: graph_name = workspace_namespace
+
+        Args:
+            None
+
+        Returns:
+            str: The graph name for the current workspace
+        """
+        workspace = getattr(self, "workspace", None)
+        namespace = self.namespace or os.environ.get("AGE_GRAPH_NAME", "lightrag")
+
+        if workspace and workspace.strip():
+            # Ensure names comply with PostgreSQL identifier specifications
+            safe_workspace = re.sub(r"[^a-zA-Z0-9_]", "_", workspace.strip())
+            safe_namespace = re.sub(r"[^a-zA-Z0-9_]", "_", namespace)
+            return f"{safe_workspace}_{safe_namespace}"
+        else:
+            # When workspace is empty, use namespace directly
+            return re.sub(r"[^a-zA-Z0-9_]", "_", namespace)
+
     @staticmethod
     def _normalize_node_id(node_id: str) -> str:
         """
@@ -1629,6 +1718,27 @@ class PGGraphStorage(BaseGraphStorage):
     async def initialize(self):
         if self.db is None:
             self.db = await ClientManager.get_client()
+            # Implement workspace priority: PostgreSQLDB.workspace > self.workspace > None
+            if self.db.workspace:
+                # Use PostgreSQLDB's workspace (highest priority)
+                final_workspace = self.db.workspace
+            elif hasattr(self, "workspace") and self.workspace:
+                # Use storage class's workspace (medium priority)
+                final_workspace = self.workspace
+                self.db.workspace = final_workspace
+            else:
+                # Use None for compatibility (lowest priority)
+                final_workspace = None
+                self.db.workspace = final_workspace
+
+        # Dynamically generate graph name based on workspace
+        self.workspace = self.db.workspace
+        self.graph_name = self._get_workspace_graph_name()
+
+        # Log the graph initialization for debugging
+        logger.info(
+            f"PostgreSQL Graph initialized: workspace='{self.workspace}', graph_name='{self.graph_name}'"
+        )
 
         # Execute each statement separately and ignore errors
         queries = [
@@ -2833,7 +2943,10 @@ class PGGraphStorage(BaseGraphStorage):
                             $$) AS (result agtype)"""
 
             await self._query(drop_query, readonly=False)
-            return {"status": "success", "message": "graph data dropped"}
+            return {
+                "status": "success",
+                "message": f"workspace '{self.workspace}' graph data dropped",
+            }
         except Exception as e:
             logger.error(f"Error dropping graph: {e}")
             return {"status": "error", "message": str(e)}

lightrag/kg/qdrant_impl.py

@@ -50,6 +50,18 @@ def compute_mdhash_id_for_qdrant(
 @final
 @dataclass
 class QdrantVectorDBStorage(BaseVectorStorage):
+    def __init__(
+        self, namespace, global_config, embedding_func, workspace=None, meta_fields=None
+    ):
+        super().__init__(
+            namespace=namespace,
+            workspace=workspace or "",
+            global_config=global_config,
+            embedding_func=embedding_func,
+            meta_fields=meta_fields or set(),
+        )
+        self.__post_init__()
+
     @staticmethod
     def create_collection_if_not_exist(
         client: QdrantClient, collection_name: str, **kwargs
@@ -59,6 +71,29 @@ class QdrantVectorDBStorage(BaseVectorStorage):
         client.create_collection(collection_name, **kwargs)
 
     def __post_init__(self):
+        # Check for QDRANT_WORKSPACE environment variable first (higher priority)
+        # This allows administrators to force a specific workspace for all Qdrant storage instances
+        qdrant_workspace = os.environ.get("QDRANT_WORKSPACE")
+        if qdrant_workspace and qdrant_workspace.strip():
+            # Use environment variable value, overriding the passed workspace parameter
+            effective_workspace = qdrant_workspace.strip()
+            logger.info(
+                f"Using QDRANT_WORKSPACE environment variable: '{effective_workspace}' (overriding passed workspace: '{self.workspace}')"
+            )
+        else:
+            # Use the workspace parameter passed during initialization
+            effective_workspace = self.workspace
+            if effective_workspace:
+                logger.debug(
+                    f"Using passed workspace parameter: '{effective_workspace}'"
+                )
+
+        # Build namespace with workspace prefix for data isolation
+        if effective_workspace:
+            self.namespace = f"{effective_workspace}_{self.namespace}"
+            logger.debug(f"Final namespace with workspace prefix: '{self.namespace}'")
+        # When workspace is empty, keep the original namespace unchanged
+
         kwargs = self.global_config.get("vector_db_storage_cls_kwargs", {})
         cosine_threshold = kwargs.get("cosine_better_than_threshold")
         if cosine_threshold is None:

lightrag/kg/redis_impl.py

@@ -71,6 +71,29 @@ class RedisConnectionManager:
 @dataclass
 class RedisKVStorage(BaseKVStorage):
     def __post_init__(self):
+        # Check for REDIS_WORKSPACE environment variable first (higher priority)
+        # This allows administrators to force a specific workspace for all Redis storage instances
+        redis_workspace = os.environ.get("REDIS_WORKSPACE")
+        if redis_workspace and redis_workspace.strip():
+            # Use environment variable value, overriding the passed workspace parameter
+            effective_workspace = redis_workspace.strip()
+            logger.info(
+                f"Using REDIS_WORKSPACE environment variable: '{effective_workspace}' (overriding passed workspace: '{self.workspace}')"
+            )
+        else:
+            # Use the workspace parameter passed during initialization
+            effective_workspace = self.workspace
+            if effective_workspace:
+                logger.debug(
+                    f"Using passed workspace parameter: '{effective_workspace}'"
+                )
+
+        # Build namespace with workspace prefix for data isolation
+        if effective_workspace:
+            self.namespace = f"{effective_workspace}_{self.namespace}"
+            logger.debug(f"Final namespace with workspace prefix: '{self.namespace}'")
+        # When workspace is empty, keep the original namespace unchanged
+
         redis_url = os.environ.get(
             "REDIS_URI", config.get("redis", "uri", fallback="redis://localhost:6379")
         )
@@ -461,6 +484,29 @@ class RedisDocStatusStorage(DocStatusStorage):
     """Redis implementation of document status storage"""
 
     def __post_init__(self):
+        # Check for REDIS_WORKSPACE environment variable first (higher priority)
+        # This allows administrators to force a specific workspace for all Redis storage instances
+        redis_workspace = os.environ.get("REDIS_WORKSPACE")
+        if redis_workspace and redis_workspace.strip():
+            # Use environment variable value, overriding the passed workspace parameter
+            effective_workspace = redis_workspace.strip()
+            logger.info(
+                f"Using REDIS_WORKSPACE environment variable: '{effective_workspace}' (overriding passed workspace: '{self.workspace}')"
+            )
+        else:
+            # Use the workspace parameter passed during initialization
+            effective_workspace = self.workspace
+            if effective_workspace:
+                logger.debug(
+                    f"Using passed workspace parameter: '{effective_workspace}'"
+                )
+
+        # Build namespace with workspace prefix for data isolation
+        if effective_workspace:
+            self.namespace = f"{effective_workspace}_{self.namespace}"
+            logger.debug(f"Final namespace with workspace prefix: '{self.namespace}'")
+        # When workspace is empty, keep the original namespace unchanged
+
         redis_url = os.environ.get(
             "REDIS_URI", config.get("redis", "uri", fallback="redis://localhost:6379")
         )

lightrag/lightrag.py

@@ -51,7 +51,7 @@ from .base import (
     StoragesStatus,
     DeletionResult,
 )
-from .namespace import NameSpace, make_namespace
+from .namespace import NameSpace
 from .operate import (
     chunking_by_token_size,
     extract_entities,
@@ -97,9 +97,7 @@ class LightRAG:
     # Directory
     # ---
 
-    working_dir: str = field(
-        default=f"./lightrag_cache_{datetime.now().strftime('%Y-%m-%d-%H:%M:%S')}"
-    )
+    working_dir: str = field(default="./rag_storage")
     """Directory where cache and temporary files are stored."""
 
     # Storage
@@ -117,6 +115,12 @@ class LightRAG:
     doc_status_storage: str = field(default="JsonDocStatusStorage")
     """Storage type for tracking document processing statuses."""
 
+    # Workspace
+    # ---
+
+    workspace: str = field(default_factory=lambda: os.getenv("WORKSPACE", ""))
+    """Workspace for data isolation. Defaults to empty string if WORKSPACE environment variable is not set."""
+
     # Logging (Deprecated, use setup_logger in utils.py instead)
     # ---
     log_level: int | None = field(default=None)
@@ -242,10 +246,6 @@ class LightRAG:
     vector_db_storage_cls_kwargs: dict[str, Any] = field(default_factory=dict)
     """Additional parameters for vector database storage."""
 
-    # TODO：deprecated, remove in the future, use WORKSPACE instead
-    namespace_prefix: str = field(default="")
-    """Prefix for namespacing stored data across different environments."""
-
     enable_llm_cache: bool = field(default=True)
     """Enables caching for LLM responses to avoid redundant computations."""
 
@@ -382,61 +382,53 @@ class LightRAG:
         self.doc_status_storage_cls = self._get_storage_class(self.doc_status_storage)
 
         self.llm_response_cache: BaseKVStorage = self.key_string_value_json_storage_cls(  # type: ignore
-            namespace=make_namespace(
-                self.namespace_prefix, NameSpace.KV_STORE_LLM_RESPONSE_CACHE
-            ),
-            global_config=asdict(
-                self
-            ),  # Add global_config to ensure cache works properly
+            namespace=NameSpace.KV_STORE_LLM_RESPONSE_CACHE,
+            workspace=self.workspace,
+            global_config=global_config,
             embedding_func=self.embedding_func,
         )
 
         self.full_docs: BaseKVStorage = self.key_string_value_json_storage_cls(  # type: ignore
-            namespace=make_namespace(
-                self.namespace_prefix, NameSpace.KV_STORE_FULL_DOCS
-            ),
+            namespace=NameSpace.KV_STORE_FULL_DOCS,
+            workspace=self.workspace,
             embedding_func=self.embedding_func,
         )
 
         self.text_chunks: BaseKVStorage = self.key_string_value_json_storage_cls(  # type: ignore
-            namespace=make_namespace(
-                self.namespace_prefix, NameSpace.KV_STORE_TEXT_CHUNKS
-            ),
+            namespace=NameSpace.KV_STORE_TEXT_CHUNKS,
+            workspace=self.workspace,
             embedding_func=self.embedding_func,
         )
 
         self.chunk_entity_relation_graph: BaseGraphStorage = self.graph_storage_cls(  # type: ignore
-            namespace=make_namespace(
-                self.namespace_prefix, NameSpace.GRAPH_STORE_CHUNK_ENTITY_RELATION
-            ),
+            namespace=NameSpace.GRAPH_STORE_CHUNK_ENTITY_RELATION,
+            workspace=self.workspace,
             embedding_func=self.embedding_func,
         )
 
         self.entities_vdb: BaseVectorStorage = self.vector_db_storage_cls(  # type: ignore
-            namespace=make_namespace(
-                self.namespace_prefix, NameSpace.VECTOR_STORE_ENTITIES
-            ),
+            namespace=NameSpace.VECTOR_STORE_ENTITIES,
+            workspace=self.workspace,
             embedding_func=self.embedding_func,
             meta_fields={"entity_name", "source_id", "content", "file_path"},
         )
         self.relationships_vdb: BaseVectorStorage = self.vector_db_storage_cls(  # type: ignore
-            namespace=make_namespace(
-                self.namespace_prefix, NameSpace.VECTOR_STORE_RELATIONSHIPS
-            ),
+            namespace=NameSpace.VECTOR_STORE_RELATIONSHIPS,
+            workspace=self.workspace,
             embedding_func=self.embedding_func,
             meta_fields={"src_id", "tgt_id", "source_id", "content", "file_path"},
         )
         self.chunks_vdb: BaseVectorStorage = self.vector_db_storage_cls(  # type: ignore
-            namespace=make_namespace(
-                self.namespace_prefix, NameSpace.VECTOR_STORE_CHUNKS
-            ),
+            namespace=NameSpace.VECTOR_STORE_CHUNKS,
+            workspace=self.workspace,
             embedding_func=self.embedding_func,
             meta_fields={"full_doc_id", "content", "file_path"},
         )
 
         # Initialize document status storage
         self.doc_status: DocStatusStorage = self.doc_status_storage_cls(
-            namespace=make_namespace(self.namespace_prefix, NameSpace.DOC_STATUS),
+            namespace=NameSpace.DOC_STATUS,
+            workspace=self.workspace,
             global_config=global_config,
             embedding_func=None,
         )
@@ -965,6 +957,9 @@ class LightRAG:
                                 )
                             }
 
+                            if not chunks:
+                                logger.warning("No document chunks to process")
+
                             # Process document in two stages
                             # Stage 1: Process text chunks and docs (parallel execution)
                             doc_status_task = asyncio.create_task(

lightrag/namespace.py

@@ -17,10 +17,6 @@ class NameSpace:
     DOC_STATUS = "doc_status"
 
 
-def make_namespace(prefix: str, base_namespace: str):
-    return prefix + base_namespace
-
-
 def is_namespace(namespace: str, base_namespace: str | Iterable[str]):
     if isinstance(base_namespace, str):
         return namespace.endswith(base_namespace)

lightrag_webui/src/api/lightrag.ts

@@ -40,6 +40,8 @@ export type LightragStatus = {
     doc_status_storage: string
     graph_storage: string
     vector_storage: string
+    workspace?: string
+    max_graph_nodes?: string
   }
   update_status?: Record<string, any>
   core_version?: string

lightrag_webui/src/components/status/StatusCard.tsx

@@ -56,6 +56,10 @@ const StatusCard = ({ status }: { status: LightragStatus | null }) => {
           <span>{status.configuration.graph_storage}</span>
           <span>{t('graphPanel.statusCard.vectorStorage')}:</span>
           <span>{status.configuration.vector_storage}</span>
+          <span>{t('graphPanel.statusCard.workspace')}:</span>
+          <span>{status.configuration.workspace || '-'}</span>
+          <span>{t('graphPanel.statusCard.maxGraphNodes')}:</span>
+          <span>{status.configuration.max_graph_nodes || '-'}</span>
         </div>
       </div>
     </div>

lightrag_webui/src/locales/ar.json

@@ -263,7 +263,9 @@
       "kvStorage": "تخزين المفتاح-القيمة",
       "docStatusStorage": "تخزين حالة المستند",
       "graphStorage": "تخزين الرسم البياني",
-      "vectorStorage": "تخزين المتجهات"
+      "vectorStorage": "تخزين المتجهات",
+      "workspace": "مساحة العمل",
+      "maxGraphNodes": "الحد الأقصى لعقد الرسم البياني"
     },
     "propertiesView": {
       "editProperty": "تعديل {{property}}",

lightrag_webui/src/locales/en.json

@@ -263,7 +263,9 @@
       "kvStorage": "KV Storage",
       "docStatusStorage": "Doc Status Storage",
       "graphStorage": "Graph Storage",
-      "vectorStorage": "Vector Storage"
+      "vectorStorage": "Vector Storage",
+      "workspace": "Workspace",
+      "maxGraphNodes": "Max Graph Nodes"
     },
     "propertiesView": {
       "editProperty": "Edit {{property}}",

lightrag_webui/src/locales/fr.json

@@ -263,7 +263,9 @@
       "kvStorage": "Stockage clé-valeur",
       "docStatusStorage": "Stockage de l'état des documents",
       "graphStorage": "Stockage du graphe",
-      "vectorStorage": "Stockage vectoriel"
+      "vectorStorage": "Stockage vectoriel",
+      "workspace": "Espace de travail",
+      "maxGraphNodes": "Nombre maximum de nœuds du graphe"
     },
     "propertiesView": {
       "editProperty": "Modifier {{property}}",

lightrag_webui/src/locales/zh.json

@@ -263,7 +263,9 @@
       "kvStorage": "KV存储",
       "docStatusStorage": "文档状态存储",
       "graphStorage": "图存储",
-      "vectorStorage": "向量存储"
+      "vectorStorage": "向量存储",
+      "workspace": "工作空间",
+      "maxGraphNodes": "最大图节点数"
     },
     "propertiesView": {
       "editProperty": "编辑{{property}}",

lightrag_webui/src/locales/zh_TW.json

@@ -263,7 +263,9 @@
       "kvStorage": "KV 儲存",
       "docStatusStorage": "文件狀態儲存",
       "graphStorage": "圖形儲存",
-      "vectorStorage": "向量儲存"
+      "vectorStorage": "向量儲存",
+      "workspace": "工作空間",
+      "maxGraphNodes": "最大圖形節點數"
     },
     "propertiesView": {
       "editProperty": "編輯{{property}}",

pyproject.toml

@@ -11,7 +11,7 @@ authors = [
 description = "LightRAG: Simple and Fast Retrieval-Augmented Generation"
 readme = "README.md"
 license = {text = "MIT"}
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 classifiers = [
     "Development Status :: 4 - Beta",
     "Programming Language :: Python :: 3",
@@ -91,3 +91,6 @@ version = {attr = "lightrag.__version__"}
 
 [tool.setuptools.package-data]
 lightrag = ["api/webui/**/*"]
+
+[tool.ruff]
+target-version = "py310"

reproduce/Step_3.py

@@ -28,9 +28,10 @@ def run_queries_and_save_to_json(
 ):
     loop = always_get_an_event_loop()
 
-    with open(output_file, "a", encoding="utf-8") as result_file, open(
-        error_file, "a", encoding="utf-8"
-    ) as err_file:
+    with (
+        open(output_file, "a", encoding="utf-8") as result_file,
+        open(error_file, "a", encoding="utf-8") as err_file,
+    ):
         result_file.write("[\n")
         first_entry = True
 

reproduce/Step_3_openai_compatible.py

@@ -59,9 +59,10 @@ def run_queries_and_save_to_json(
 ):
     loop = always_get_an_event_loop()
 
-    with open(output_file, "a", encoding="utf-8") as result_file, open(
-        error_file, "a", encoding="utf-8"
-    ) as err_file:
+    with (
+        open(output_file, "a", encoding="utf-8") as result_file,
+        open(error_file, "a", encoding="utf-8") as err_file,
+    ):
         result_file.write("[\n")
         first_entry = True