Refactor graph search and add local Vite config.

- Simplify graph search parameters in API
- Add inclusive search and min degree options
- Update Vite config for local development
- Enhance graph query endpoint in web UI
- Add new Vite config file for local setup

lightrag/api/routers/graph_routes.py

@@ -3,9 +3,9 @@ This module contains all graph-related routes for the LightRAG API.
 """
 
 from typing import Optional
-
 from fastapi import APIRouter, Depends
 
+from ...utils import logger
 from ..utils_api import get_api_key_dependency
 
 router = APIRouter(tags=["graph"])
@@ -25,7 +25,7 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
         return await rag.get_graph_labels()
 
     @router.get("/graphs", dependencies=[Depends(optional_api_key)])
-    async def get_knowledge_graph(label: str, max_depth: int = 3):
+    async def get_knowledge_graph(label: str, max_depth: int = 3, inclusive: bool = False, min_degree: int = 0):
         """
         Retrieve a connected subgraph of nodes where the label includes the specified label.
         Maximum number of nodes is constrained by the environment variable `MAX_GRAPH_NODES` (default: 1000).
@@ -34,50 +34,17 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
             2. Followed by nodes directly connected to the matching nodes
             3. Finally, the degree of the nodes
         Maximum number of nodes is limited to env MAX_GRAPH_NODES(default: 1000)
-        Control search mode by label content:
-            1. only label-name :  exact search with the label name (selecting from the label list return previously)
-            2. label-name follow by '>n' : exact search of nodes with degree more than n
-            3. label-name follow by* :  inclusive search of nodes with degree more than n
-            4. label-name follow by '>n*' : inclusive search 
 
         Args:
             label (str): Label to get knowledge graph for
             max_depth (int, optional): Maximum depth of graph. Defaults to 3.
+            inclusive_search (bool, optional): If True, search for nodes that include the label. Defaults to False.
+            min_degree (int, optional): Minimum degree of nodes. Defaults to 0.
 
         Returns:
             Dict[str, List[str]]: Knowledge graph for label
         """
-        # Parse label to extract search mode and min degree if specified
-        search_mode = "exact"  # Default search mode
-        min_degree = 0  # Default minimum degree
-        original_label = label
-        
-        # First check if label ends with *
-        if label.endswith("*"):
-            search_mode = "inclusive"  # Always set to inclusive if ends with *
-            label = label[:-1].strip()  # Remove trailing *
-            
-            # Try to parse >n if it exists
-            if ">" in label:
-                try:
-                    degree_pos = label.rfind(">")
-                    degree_str = label[degree_pos + 1:].strip()
-                    min_degree = int(degree_str) + 1
-                    label = label[:degree_pos].strip()
-                except ValueError:
-                    # If degree parsing fails, just remove * and keep the rest as label
-                    label = original_label[:-1].strip()
-        # If no *, check for >n pattern
-        elif ">" in label:
-            try:
-                degree_pos = label.rfind(">")
-                degree_str = label[degree_pos + 1:].strip()
-                min_degree = int(degree_str) + 1
-                label = label[:degree_pos].strip()
-            except ValueError:
-                # If degree parsing fails, treat the whole string as label
-                label = original_label
-                    
-        return await rag.get_knowledge_graph(node_label=label, max_depth=max_depth, search_mode=search_mode, min_degree=min_degree)
+        logger.info(f"Inclusive search : {inclusive}, Min degree: {min_degree}, Label: {label}")            
+        return await rag.get_knowledge_graph(node_label=label, max_depth=max_depth, inclusive=inclusive, min_degree=min_degree)
 
     return router

lightrag/lightrag.py

@@ -504,7 +504,7 @@ class LightRAG:
         return text
 
     async def get_knowledge_graph(
-        self, node_label: str, max_depth: int, search_mode: str = "exact", min_degree: int = 0
+        self, node_label: str, max_depth: int, inclusive: bool = False, min_degree: int = 0
     ) -> KnowledgeGraph:
         """Get knowledge graph for a given label
 
@@ -520,8 +520,6 @@ class LightRAG:
         return await self.chunk_entity_relation_graph.get_knowledge_graph(
             node_label=node_label,
             max_depth=max_depth,
-            search_mode=search_mode,
-            min_degree=min_degree
         )
 
     def _get_storage_class(self, storage_name: str) -> Callable[..., Any]: