use KnowledgeGraph typed dict for graph API response
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@@ -1424,8 +1424,8 @@ def create_app(args):
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# query all graph
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@app.get("/graphs")
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async def get_graphs(label: str):
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return await rag.get_graphs(nodel_label=label, max_depth=100)
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async def get_knowledge_graph(label: str):
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return await rag.get_knowledge_graph(nodel_label=label, max_depth=100)
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# Add Ollama API routes
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ollama_api = OllamaAPI(rag)
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@@ -13,6 +13,7 @@ from typing import (
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import numpy as np
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from .utils import EmbeddingFunc
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from .types import KnowledgeGraph
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class TextChunkSchema(TypedDict):
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@@ -175,7 +176,7 @@ class BaseGraphStorage(StorageNameSpace):
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async def get_knowledge_graph(
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self, node_label: str, max_depth: int = 5
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) -> dict[str, list[dict]]:
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) -> KnowledgeGraph:
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raise NotImplementedError
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@@ -25,6 +25,7 @@ from tenacity import (
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from ..utils import logger
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from ..base import BaseGraphStorage
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from ..types import KnowledgeGraph, KnowledgeGraphNode, KnowledgeGraphEdge
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@dataclass
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@@ -44,7 +45,8 @@ class Neo4JStorage(BaseGraphStorage):
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URI = os.environ["NEO4J_URI"]
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USERNAME = os.environ["NEO4J_USERNAME"]
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PASSWORD = os.environ["NEO4J_PASSWORD"]
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MAX_CONNECTION_POOL_SIZE = os.environ.get("NEO4J_MAX_CONNECTION_POOL_SIZE", 800)
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MAX_CONNECTION_POOL_SIZE = os.environ.get(
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"NEO4J_MAX_CONNECTION_POOL_SIZE", 800)
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DATABASE = os.environ.get(
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"NEO4J_DATABASE", re.sub(r"[^a-zA-Z0-9-]", "-", namespace)
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)
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@@ -74,19 +76,22 @@ class Neo4JStorage(BaseGraphStorage):
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)
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raise e
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except neo4jExceptions.AuthError as e:
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logger.error(f"Authentication failed for {database} at {URI}")
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logger.error(
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f"Authentication failed for {database} at {URI}")
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raise e
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except neo4jExceptions.ClientError as e:
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if e.code == "Neo.ClientError.Database.DatabaseNotFound":
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logger.info(
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f"{database} at {URI} not found. Try to create specified database.".capitalize()
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f"{database} at {URI} not found. Try to create specified database.".capitalize(
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)
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)
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try:
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with _sync_driver.session() as session:
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session.run(
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f"CREATE DATABASE `{database}` IF NOT EXISTS"
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)
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logger.info(f"{database} at {URI} created".capitalize())
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logger.info(
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f"{database} at {URI} created".capitalize())
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connected = True
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except (
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neo4jExceptions.ClientError,
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@@ -103,7 +108,8 @@ class Neo4JStorage(BaseGraphStorage):
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"This Neo4j instance does not support creating databases. Try to use Neo4j Desktop/Enterprise version or DozerDB instead. Fallback to use the default database."
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)
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if database is None:
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logger.error(f"Failed to create {database} at {URI}")
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logger.error(
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f"Failed to create {database} at {URI}")
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raise e
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if connected:
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@@ -365,7 +371,7 @@ class Neo4JStorage(BaseGraphStorage):
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async def get_knowledge_graph(
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self, node_label: str, max_depth: int = 5
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) -> Dict[str, List[Dict]]:
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) -> KnowledgeGraph:
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"""
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Get complete connected subgraph for specified node (including the starting node itself)
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@@ -376,7 +382,7 @@ class Neo4JStorage(BaseGraphStorage):
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4. Add depth control
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"""
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label = node_label.strip('"')
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result = {"nodes": [], "edges": []}
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result = KnowledgeGraph()
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seen_nodes = set()
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seen_edges = set()
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@@ -395,7 +401,8 @@ class Neo4JStorage(BaseGraphStorage):
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validate_query = f"MATCH (n:`{label}`) RETURN n LIMIT 1"
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validate_result = await session.run(validate_query)
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if not await validate_result.single():
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logger.warning(f"Starting node {label} does not exist!")
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logger.warning(
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f"Starting node {label} does not exist!")
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return result
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# Optimized query (including direction handling and self-loops)
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@@ -420,11 +427,11 @@ class Neo4JStorage(BaseGraphStorage):
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# Use node ID + label combination as unique identifier
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node_id = node.id
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if node_id not in seen_nodes:
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node_data = {}
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node_data["labels"] = list(node.labels) # Keep all labels
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node_data["id"] = f"{node_id}"
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node_data["properties"] = dict(node)
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result["nodes"].append(node_data)
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result.nodes.append(KnowledgeGraphNode(
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id=f"{node_id}",
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labels=list(node.labels),
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properties=dict(node),
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))
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seen_nodes.add(node_id)
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# Handle relationships (including direction information)
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@@ -433,21 +440,17 @@ class Neo4JStorage(BaseGraphStorage):
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if edge_id not in seen_edges:
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start = rel.start_node
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end = rel.end_node
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edge_data = {}
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edge_data.update(
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{
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"source": f"{start.id}",
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"target": f"{end.id}",
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"type": rel.type,
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"id": f"{edge_id}",
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"properties": dict(rel),
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}
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)
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result["edges"].append(edge_data)
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result.edges.append(KnowledgeGraphEdge(
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id=f"{edge_id}",
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type=rel.type,
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source=f"{start.id}",
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target=f"{end.id}",
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properties=dict(rel),
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))
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seen_edges.add(edge_id)
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logger.info(
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f"Subgraph query successful | Node count: {len(result['nodes'])} | Edge count: {len(result['edges'])}"
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f"Subgraph query successful | Node count: {len(result.nodes)} | Edge count: {len(result.edges)}"
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)
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except neo4jExceptions.ClientError as e:
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@@ -34,6 +34,7 @@ from .utils import (
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logger,
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set_logger,
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)
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from .types import KnowledgeGraph
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STORAGES = {
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"NetworkXStorage": ".kg.networkx_impl",
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@@ -385,7 +386,7 @@ class LightRAG:
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text = await self.chunk_entity_relation_graph.get_all_labels()
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return text
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async def get_graphs(self, nodel_label: str, max_depth: int):
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async def get_knowledge_graph(self, nodel_label: str, max_depth: int) -> KnowledgeGraph:
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return await self.chunk_entity_relation_graph.get_knowledge_graph(
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node_label=nodel_label, max_depth=max_depth
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)
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@@ -1,7 +1,26 @@
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from pydantic import BaseModel
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from typing import List
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from typing import List, Dict, Any
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class GPTKeywordExtractionFormat(BaseModel):
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high_level_keywords: List[str]
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low_level_keywords: List[str]
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class KnowledgeGraphNode(BaseModel):
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id: str
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labels: List[str]
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properties: Dict[str, Any] # anything else goes here
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class KnowledgeGraphEdge(BaseModel):
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id: str
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type: str
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source: str # id of source node
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target: str # id of target node
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properties: Dict[str, Any] # anything else goes here
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class KnowledgeGraph(BaseModel):
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nodes: List[KnowledgeGraphNode] = []
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edges: List[KnowledgeGraphEdge] = []
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