Update graph retrival api(abandon pydantic model)

lightrag/api/routers/graph_routes.py

@@ -2,61 +2,32 @@
 This module contains all graph-related routes for the LightRAG API.
 """
 
-from typing import Optional, List, Dict, Any
+from typing import Optional
 from fastapi import APIRouter, Depends, Query
-from pydantic import BaseModel, Field
 
 from ..utils_api import get_combined_auth_dependency
 
 router = APIRouter(tags=["graph"])
 
-# Pydantic models for graph routes
-class GraphLabelsResponse(BaseModel):
-    """Response model: List of graph labels"""
-    labels: List[str] = Field(description="List of graph labels")
-
-class KnowledgeGraphNode(BaseModel):
-    """Model for a node in the knowledge graph"""
-    id: str = Field(description="Unique identifier of the node")
-    label: str = Field(description="Label of the node")
-    properties: Dict[str, Any] = Field(default_factory=dict, description="Properties of the node")
-
-class KnowledgeGraphEdge(BaseModel):
-    """Model for an edge in the knowledge graph"""
-    source: str = Field(description="Source node ID")
-    target: str = Field(description="Target node ID")
-    type: str = Field(description="Type of the relationship")
-    properties: Dict[str, Any] = Field(default_factory=dict, description="Properties of the edge")
-
-class KnowledgeGraphResponse(BaseModel):
-    """Response model: Knowledge graph data"""
-    nodes: List[KnowledgeGraphNode] = Field(description="List of nodes in the graph")
-    edges: List[KnowledgeGraphEdge] = Field(description="List of edges in the graph")
-
 
 def create_graph_routes(rag, api_key: Optional[str] = None):
     combined_auth = get_combined_auth_dependency(api_key)
 
-    @router.get("/graph/label/list", 
-                dependencies=[Depends(combined_auth)],
-                response_model=GraphLabelsResponse)
+    @router.get("/graph/label/list", dependencies=[Depends(combined_auth)])
     async def get_graph_labels():
         """
         Get all graph labels
 
         Returns:
-            GraphLabelsResponse: List of graph labels
+            List[str]: List of graph labels
         """
-        labels = await rag.get_graph_labels()
-        return GraphLabelsResponse(labels=labels)
+        return await rag.get_graph_labels()
 
-    @router.get("/graphs", 
-                dependencies=[Depends(combined_auth)],
-                response_model=KnowledgeGraphResponse)
+    @router.get("/graphs", dependencies=[Depends(combined_auth)])
     async def get_knowledge_graph(
         label: str = Query(..., description="Label to get knowledge graph for"),
         max_depth: int = Query(3, description="Maximum depth of graph", ge=1),
-        max_nodes: int = Query(1000, description="Maxiumu nodes to return", ge=1),
+        max_nodes: int = Query(1000, description="Maximum nodes to return", ge=1),
     ):
         """
         Retrieve a connected subgraph of nodes where the label includes the specified label.
@@ -70,19 +41,12 @@ def create_graph_routes(rag, api_key: Optional[str] = None):
             max_nodes: Maxiumu nodes to return
 
         Returns:
-            KnowledgeGraphResponse: Knowledge graph containing nodes and edges
+            Dict[str, List[str]]: Knowledge graph for label
         """
-        graph_data = await rag.get_knowledge_graph(
+        return await rag.get_knowledge_graph(
             node_label=label,
             max_depth=max_depth,
             max_nodes=max_nodes,
         )
-        
-        # Convert the returned dictionary to our response model format
-        # Assuming the returned dictionary has 'nodes' and 'edges' keys
-        return KnowledgeGraphResponse(
-            nodes=graph_data.get("nodes", []),
-            edges=graph_data.get("edges", [])
-        )
 
     return router

lightrag/base.py

@@ -341,7 +341,7 @@ class BaseGraphStorage(StorageNameSpace, ABC):
 
     @abstractmethod
     async def get_knowledge_graph(
-        self, node_label: str, max_depth: int = 3
+        self, node_label: str, max_depth: int = 3, max_nodes: int = 1000
     ) -> KnowledgeGraph:
         """Retrieve a subgraph of the knowledge graph starting from a given node."""
 

lightrag/lightrag.py

@@ -510,36 +510,20 @@ class LightRAG:
         self,
         node_label: str,
         max_depth: int = 3,
-        min_degree: int = 0,
-        inclusive: bool = False,
+        max_nodes: int = 1000,
     ) -> KnowledgeGraph:
         """Get knowledge graph for a given label
 
         Args:
             node_label (str): Label to get knowledge graph for
             max_depth (int): Maximum depth of graph
-            min_degree (int, optional): Minimum degree of nodes to include. Defaults to 0.
-            inclusive (bool, optional): Whether to use inclusive search mode. Defaults to False.
+            max_nodes (int, optional): Maximum number of nodes to return. Defaults to 1000.
 
         Returns:
             KnowledgeGraph: Knowledge graph containing nodes and edges
         """
-        # get params supported by get_knowledge_graph of specified storage
-        import inspect
 
-        storage_params = inspect.signature(
-            self.chunk_entity_relation_graph.get_knowledge_graph
-        ).parameters
-
-        kwargs = {"node_label": node_label, "max_depth": max_depth}
-
-        if "min_degree" in storage_params and min_degree > 0:
-            kwargs["min_degree"] = min_degree
-
-        if "inclusive" in storage_params:
-            kwargs["inclusive"] = inclusive
-
-        return await self.chunk_entity_relation_graph.get_knowledge_graph(**kwargs)
+        return await self.chunk_entity_relation_graph.get_knowledge_graph(node_label, max_depth, max_nodes)
 
     def _get_storage_class(self, storage_name: str) -> Callable[..., Any]:
         import_path = STORAGES[storage_name]