mirror of https://github.com/Mai-with-u/MaiBot.git
添加知识库图谱可视化 API 路由，并在 WebUI 服务器中注册相关路由
墨梓柒
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b0a22011a4
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"""知识库图谱可视化 API 路由"""
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from typing import List, Optional
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from fastapi import APIRouter, Query
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from pydantic import BaseModel
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import logging
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logger = logging.getLogger(__name__)
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router = APIRouter(prefix="/api/webui/knowledge", tags=["knowledge"])
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class KnowledgeNode(BaseModel):
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"""知识节点"""
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id: str
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type: str # 'entity' or 'paragraph'
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content: str
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create_time: Optional[float] = None
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class KnowledgeEdge(BaseModel):
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"""知识边"""
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source: str
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target: str
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weight: float
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create_time: Optional[float] = None
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update_time: Optional[float] = None
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class KnowledgeGraph(BaseModel):
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"""知识图谱"""
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nodes: List[KnowledgeNode]
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edges: List[KnowledgeEdge]
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class KnowledgeStats(BaseModel):
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"""知识库统计信息"""
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total_nodes: int
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total_edges: int
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entity_nodes: int
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paragraph_nodes: int
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avg_connections: float
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def _load_kg_manager():
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"""延迟加载 KGManager"""
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try:
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from src.chat.knowledge.kg_manager import KGManager
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kg_manager = KGManager()
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kg_manager.load_from_file()
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return kg_manager
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except Exception as e:
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logger.error(f"加载 KGManager 失败: {e}")
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return None
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def _convert_graph_to_json(kg_manager) -> KnowledgeGraph:
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"""将 DiGraph 转换为 JSON 格式"""
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if kg_manager is None or kg_manager.graph is None:
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return KnowledgeGraph(nodes=[], edges=[])
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graph = kg_manager.graph
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nodes = []
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edges = []
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# 转换节点
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node_list = graph.get_node_list()
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for node_id in node_list:
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try:
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node_data = graph[node_id]
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# 节点类型: "ent" -> "entity", "pg" -> "paragraph"
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node_type = "entity" if ('type' in node_data and node_data['type'] == 'ent') else "paragraph"
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content = node_data['content'] if 'content' in node_data else node_id
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create_time = node_data['create_time'] if 'create_time' in node_data else None
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nodes.append(KnowledgeNode(
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id=node_id,
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type=node_type,
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content=content,
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create_time=create_time
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))
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except Exception as e:
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logger.warning(f"跳过节点 {node_id}: {e}")
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continue
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# 转换边
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edge_list = graph.get_edge_list()
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for edge_tuple in edge_list:
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try:
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# edge_tuple 是 (source, target) 元组
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source, target = edge_tuple[0], edge_tuple[1]
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# 通过 graph[source, target] 获取边的属性数据
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edge_data = graph[source, target]
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# edge_data 支持 [] 操作符但不支持 .get()
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weight = edge_data['weight'] if 'weight' in edge_data else 1.0
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create_time = edge_data['create_time'] if 'create_time' in edge_data else None
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update_time = edge_data['update_time'] if 'update_time' in edge_data else None
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edges.append(KnowledgeEdge(
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source=source,
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target=target,
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weight=weight,
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create_time=create_time,
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update_time=update_time
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))
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except Exception as e:
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logger.warning(f"跳过边 {edge_tuple}: {e}")
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continue
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return KnowledgeGraph(nodes=nodes, edges=edges)
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@router.get("/graph", response_model=KnowledgeGraph)
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async def get_knowledge_graph(
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limit: int = Query(100, ge=1, le=10000, description="返回的最大节点数"),
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node_type: str = Query("all", description="节点类型过滤: all, entity, paragraph")
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):
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"""获取知识图谱(限制节点数量)
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Args:
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limit: 返回的最大节点数,默认 100,最大 10000
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node_type: 节点类型过滤 - all(全部), entity(实体), paragraph(段落)
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Returns:
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KnowledgeGraph: 包含指定数量节点和相关边的知识图谱
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"""
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try:
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kg_manager = _load_kg_manager()
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if kg_manager is None:
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logger.warning("KGManager 未初始化，返回空图谱")
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return KnowledgeGraph(nodes=[], edges=[])
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graph = kg_manager.graph
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all_node_list = graph.get_node_list()
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# 按类型过滤节点
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if node_type == "entity":
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all_node_list = [n for n in all_node_list if n in graph and 'type' in graph[n] and graph[n]['type'] == 'ent']
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elif node_type == "paragraph":
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all_node_list = [n for n in all_node_list if n in graph and 'type' in graph[n] and graph[n]['type'] == 'pg']
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# 限制节点数量
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total_nodes = len(all_node_list)
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if len(all_node_list) > limit:
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node_list = all_node_list[:limit]
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else:
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node_list = all_node_list
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logger.info(f"总节点数: {total_nodes}, 返回节点: {len(node_list)} (limit={limit}, type={node_type})")
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# 转换节点
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nodes = []
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node_ids = set()
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for node_id in node_list:
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try:
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node_data = graph[node_id]
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node_type_val = "entity" if ('type' in node_data and node_data['type'] == 'ent') else "paragraph"
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content = node_data['content'] if 'content' in node_data else node_id
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create_time = node_data['create_time'] if 'create_time' in node_data else None
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nodes.append(KnowledgeNode(
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id=node_id,
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type=node_type_val,
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content=content,
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create_time=create_time
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))
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node_ids.add(node_id)
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except Exception as e:
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logger.warning(f"跳过节点 {node_id}: {e}")
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continue
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# 只获取涉及当前节点集的边(保证图的完整性)
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edges = []
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edge_list = graph.get_edge_list()
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for edge_tuple in edge_list:
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try:
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source, target = edge_tuple[0], edge_tuple[1]
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# 只包含两端都在当前节点集中的边
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if source not in node_ids or target not in node_ids:
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continue
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edge_data = graph[source, target]
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weight = edge_data['weight'] if 'weight' in edge_data else 1.0
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create_time = edge_data['create_time'] if 'create_time' in edge_data else None
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update_time = edge_data['update_time'] if 'update_time' in edge_data else None
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edges.append(KnowledgeEdge(
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source=source,
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target=target,
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weight=weight,
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create_time=create_time,
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update_time=update_time
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))
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except Exception as e:
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logger.warning(f"跳过边 {edge_tuple}: {e}")
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continue
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graph_data = KnowledgeGraph(nodes=nodes, edges=edges)
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logger.info(f"返回知识图谱: {len(nodes)} 个节点, {len(edges)} 条边")
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return graph_data
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except Exception as e:
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logger.error(f"获取知识图谱失败: {e}", exc_info=True)
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return KnowledgeGraph(nodes=[], edges=[])
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@router.get("/stats", response_model=KnowledgeStats)
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async def get_knowledge_stats():
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"""获取知识库统计信息
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Returns:
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KnowledgeStats: 统计信息
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"""
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try:
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kg_manager = _load_kg_manager()
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if kg_manager is None or kg_manager.graph is None:
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return KnowledgeStats(
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total_nodes=0,
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total_edges=0,
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entity_nodes=0,
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paragraph_nodes=0,
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avg_connections=0.0
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)
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graph = kg_manager.graph
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node_list = graph.get_node_list()
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edge_list = graph.get_edge_list()
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total_nodes = len(node_list)
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total_edges = len(edge_list)
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# 统计节点类型
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entity_nodes = 0
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paragraph_nodes = 0
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for node_id in node_list:
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try:
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node_data = graph[node_id]
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node_type = node_data['type'] if 'type' in node_data else 'ent'
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if node_type == 'ent':
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entity_nodes += 1
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elif node_type == 'pg':
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paragraph_nodes += 1
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except Exception:
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continue
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# 计算平均连接数
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avg_connections = (total_edges * 2) / total_nodes if total_nodes > 0 else 0.0
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return KnowledgeStats(
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total_nodes=total_nodes,
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total_edges=total_edges,
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entity_nodes=entity_nodes,
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paragraph_nodes=paragraph_nodes,
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avg_connections=round(avg_connections, 2)
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)
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except Exception as e:
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logger.error(f"获取统计信息失败: {e}", exc_info=True)
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return KnowledgeStats(
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total_nodes=0,
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total_edges=0,
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entity_nodes=0,
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paragraph_nodes=0,
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avg_connections=0.0
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)
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@router.get("/search", response_model=List[KnowledgeNode])
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async def search_knowledge_node(query: str = Query(..., min_length=1)):
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"""搜索知识节点
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Args:
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query: 搜索关键词
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Returns:
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List[KnowledgeNode]: 匹配的节点列表
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"""
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try:
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kg_manager = _load_kg_manager()
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if kg_manager is None or kg_manager.graph is None:
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return []
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graph = kg_manager.graph
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node_list = graph.get_node_list()
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results = []
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query_lower = query.lower()
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# 在节点内容中搜索
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for node_id in node_list:
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try:
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node_data = graph[node_id]
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content = node_data['content'] if 'content' in node_data else node_id
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node_type = "entity" if ('type' in node_data and node_data['type'] == 'ent') else "paragraph"
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if query_lower in content.lower() or query_lower in node_id.lower():
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create_time = node_data['create_time'] if 'create_time' in node_data else None
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results.append(KnowledgeNode(
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id=node_id,
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type=node_type,
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content=content,
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create_time=create_time
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))
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except Exception:
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continue
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logger.info(f"搜索 '{query}' 找到 {len(results)} 个节点")
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return results[:50] # 限制返回数量
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except Exception as e:
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logger.error(f"搜索节点失败: {e}", exc_info=True)
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return []
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@ -89,13 +89,19 @@ class WebUIServer:
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from src.webui.routes import router as webui_router
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from src.webui.logs_ws import router as logs_router
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logger.info("开始导入 knowledge_routes...")
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from src.webui.knowledge_routes import router as knowledge_router
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logger.info("knowledge_routes 导入成功")
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# 注册路由
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self.app.include_router(webui_router)
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self.app.include_router(logs_router)
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self.app.include_router(knowledge_router)
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logger.info(f"knowledge_router 路由前缀: {knowledge_router.prefix}")
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logger.info("✅ WebUI API 路由已注册")
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except Exception as e:
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logger.error(f"❌ 注册 WebUI API 路由失败: {e}")
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logger.error(f"❌ 注册 WebUI API 路由失败: {e}", exc_info=True)
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async def start(self):
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"""启动服务器"""
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@ -0,0 +1,30 @@
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from src.chat.knowledge.kg_manager import KGManager
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kg = KGManager()
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kg.load_from_file()
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edges = kg.graph.get_edge_list()
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if edges:
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e = edges[0]
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print(f"Edge tuple: {e}")
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print(f"Edge tuple type: {type(e)}")
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edge_data = kg.graph[e[0], e[1]]
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print(f"\nEdge data type: {type(edge_data)}")
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print(f"Edge data: {edge_data}")
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print(f"Has 'get' method: {hasattr(edge_data, 'get')}")
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print(f"Is dict: {isinstance(edge_data, dict)}")
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# 尝试不同的访问方式
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try:
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print(f"\nUsing []: {edge_data['weight']}")
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except Exception as e:
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print(f"Using [] failed: {e}")
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try:
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print(f"Using .get(): {edge_data.get('weight')}")
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except Exception as e:
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print(f"Using .get() failed: {e}")
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# 查看所有属性
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print(f"\nDir: {[x for x in dir(edge_data) if not x.startswith('_')]}")
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