This commit is contained in:
Windpicker-owo
2025-11-08 10:46:55 +08:00
2 changed files with 248 additions and 284 deletions

View File

@@ -61,27 +61,18 @@ def find_available_data_files() -> List[Path]:
return sorted(files, key=lambda f: f.stat().st_mtime, reverse=True)
def load_graph_data_from_file(
file_path: Optional[Path] = None,
nodes_page: Optional[int] = None,
nodes_per_page: Optional[int] = None,
edges_page: Optional[int] = None,
edges_per_page: Optional[int] = None,
) -> Dict[str, Any]:
def load_graph_data_from_file(file_path: Optional[Path] = None) -> Dict[str, Any]:
"""
从磁盘加载图数据, 支持分页
如果不提供分页参数, 则加载并缓存所有数据
从磁盘加载图数据,并构建索引以加速查询
哼,别看我代码写得多,这叫专业!一次性把事情做对,就不用返工了
"""
global graph_data_cache, current_data_file
# 如果是请求分页数据, 则不使用缓存的全量数据
is_paged_request = nodes_page is not None or edges_page is not None
if file_path and file_path != current_data_file:
graph_data_cache = None
current_data_file = file_path
if graph_data_cache and not is_paged_request:
if graph_data_cache:
return graph_data_cache
try:
@@ -89,92 +80,84 @@ def load_graph_data_from_file(
if not graph_file:
available_files = find_available_data_files()
if not available_files:
return {"error": "未找到数据文件", "nodes": [], "edges": [], "stats": {}}
return {"error": "未找到数据文件", "nodes": [], "edges": [], "stats": {}, "nodes_dict": {}, "adjacency_list": {}}
graph_file = available_files[0]
current_data_file = graph_file
if not graph_file.exists():
return {"error": f"文件不存在: {graph_file}", "nodes": [], "edges": [], "stats": {}}
return {"error": f"文件不存在: {graph_file}", "nodes": [], "edges": [], "stats": {}, "nodes_dict": {}, "adjacency_list": {}}
# 只有在没有缓存时才从磁盘读取和处理文件
if not graph_data_cache:
with open(graph_file, "r", encoding="utf-8") as f:
data = orjson.loads(f.read())
with open(graph_file, "r", encoding="utf-8") as f:
data = orjson.loads(f.read())
nodes = data.get("nodes", [])
edges = data.get("edges", [])
metadata = data.get("metadata", {})
nodes = data.get("nodes", [])
edges = data.get("edges", [])
metadata = data.get("metadata", {})
nodes_dict = {
node["id"]: {
**node,
"label": node.get("content", ""),
"group": node.get("node_type", ""),
"title": f"{node.get('node_type', '')}: {node.get('content', '')}",
nodes_dict = {
node["id"]: {
**node,
"label": node.get("content", ""),
"group": node.get("node_type", ""),
"title": f"{node.get('node_type', '')}: {node.get('content', '')}",
"degree": 0, # 初始化度为0
}
for node in nodes
if node.get("id")
}
edges_list = []
seen_edge_ids = set()
adjacency_list = {node_id: [] for node_id in nodes_dict}
for edge in edges:
edge_id = edge.get("id")
source_id = edge.get("source", edge.get("source_id"))
target_id = edge.get("target", edge.get("target_id"))
if edge_id and edge_id not in seen_edge_ids and source_id in nodes_dict and target_id in nodes_dict:
formatted_edge = {
**edge,
"from": source_id,
"to": target_id,
"label": edge.get("relation", ""),
"arrows": "to",
}
for node in nodes
if node.get("id")
}
edges_list.append(formatted_edge)
seen_edge_ids.add(edge_id)
edges_list = []
seen_edge_ids = set()
for edge in edges:
edge_id = edge.get("id")
if edge_id and edge_id not in seen_edge_ids:
edges_list.append(
{
**edge,
"from": edge.get("source", edge.get("source_id")),
"to": edge.get("target", edge.get("target_id")),
"label": edge.get("relation", ""),
"arrows": "to",
}
)
seen_edge_ids.add(edge_id)
# 构建邻接表并计算度
adjacency_list[source_id].append(formatted_edge)
adjacency_list[target_id].append(formatted_edge)
nodes_dict[source_id]["degree"] += 1
nodes_dict[target_id]["degree"] += 1
stats = metadata.get("statistics", {})
total_memories = stats.get("total_memories", 0)
graph_data_cache = {
"nodes": list(nodes_dict.values()),
"edges": edges_list,
"memories": [], # TODO: 未来也可以考虑分页加载记忆
"stats": {
"total_nodes": len(nodes_dict),
"total_edges": len(edges_list),
"total_memories": total_memories,
},
"current_file": str(graph_file),
"file_size": graph_file.stat().st_size,
"file_modified": datetime.fromtimestamp(graph_file.stat().st_mtime).isoformat(),
}
# 如果是分页请求, 则从缓存中切片数据
if is_paged_request:
paged_data = graph_data_cache.copy() # 浅拷贝一份, 避免修改缓存
# 分页节点
if nodes_page is not None and nodes_per_page is not None:
node_start = (nodes_page - 1) * nodes_per_page
node_end = node_start + nodes_per_page
paged_data["nodes"] = graph_data_cache["nodes"][node_start:node_end]
# 分页边
if edges_page is not None and edges_per_page is not None:
edge_start = (edges_page - 1) * edges_per_page
edge_end = edge_start + edges_per_page
paged_data["edges"] = graph_data_cache["edges"][edge_start:edge_end]
return paged_data
stats = metadata.get("statistics", {})
total_memories = stats.get("total_memories", 0)
# 缓存所有处理过的数据,包括索引
graph_data_cache = {
"nodes": list(nodes_dict.values()),
"edges": edges_list,
"nodes_dict": nodes_dict, # 缓存节点字典,方便快速查找
"adjacency_list": adjacency_list, # 缓存邻接表,光速定位邻居
"memories": [],
"stats": {
"total_nodes": len(nodes_dict),
"total_edges": len(edges_list),
"total_memories": total_memories,
},
"current_file": str(graph_file),
"file_size": graph_file.stat().st_size,
"file_modified": datetime.fromtimestamp(graph_file.stat().st_mtime).isoformat(),
}
return graph_data_cache
except Exception as e:
import traceback
traceback.print_exc()
raise HTTPException(status_code=500, detail=f"加载图数据失败: {e}")
@router.get("/", response_class=HTMLResponse)
async def index(request: Request):
"""主页面"""
@@ -235,67 +218,90 @@ def _format_graph_data_from_manager(memory_manager) -> Dict[str, Any]:
"current_file": "memory_manager (实时数据)",
}
@router.get("/api/graph/paged")
async def get_paged_graph(
nodes_page: int = 1, nodes_per_page: int = 100, edges_page: int = 1, edges_per_page: int = 200
):
"""获取分页的记忆图数据"""
@router.get("/api/graph/core")
async def get_core_graph(limit: int = 100):
"""
获取核心图数据。
这可比一下子把所有东西都丢给前端聪明多了,哼。
"""
try:
# 确保全量数据已加载到缓存
full_data = load_graph_data_from_file()
if "error" in full_data:
raise HTTPException(status_code=404, detail=full_data["error"])
return JSONResponse(content={"success": False, "error": full_data["error"]}, status_code=404)
# 从缓存中获取全量数据
# 智能选择核心节点: 优先选择度最高的节点
# 这是一个简单的策略,但比随机选择要好得多
all_nodes = full_data.get("nodes", [])
all_edges = full_data.get("edges", [])
total_nodes = len(all_nodes)
total_edges = len(all_edges)
# 计算节点分页
node_start = (nodes_page - 1) * nodes_per_page
node_end = node_start + nodes_per_page
paginated_nodes = all_nodes[node_start:node_end]
# 计算边分页
edge_start = (edges_page - 1) * edges_per_page
edge_end = edge_start + edges_per_page
paginated_edges = all_edges[edge_start:edge_end]
return JSONResponse(
content={
"success": True,
"data": {
"nodes": paginated_nodes,
"edges": paginated_edges,
"pagination": {
"nodes": {
"page": nodes_page,
"per_page": nodes_per_page,
"total": total_nodes,
"total_pages": (total_nodes + nodes_per_page - 1) // nodes_per_page,
},
"edges": {
"page": edges_page,
"per_page": edges_per_page,
"total": total_edges,
"total_pages": (total_edges + edges_per_page - 1) // edges_per_page,
},
},
},
}
# 按度(degree)降序排序,如果度相同,则按创建时间(如果可用)降序
sorted_nodes = sorted(
all_nodes,
key=lambda n: (n.get("degree", 0), n.get("created_at", 0)),
reverse=True
)
core_nodes = sorted_nodes[:limit]
core_node_ids = {node["id"] for node in core_nodes}
# 只包含核心节点之间的边,保持初始视图的整洁
core_edges = [
edge for edge in full_data.get("edges", [])
if edge.get("from") in core_node_ids and edge.get("to") in core_node_ids
]
# 确保返回的数据结构和前端期望的一致
data_to_send = {
"nodes": core_nodes,
"edges": core_edges,
"memories": [], # 初始加载不需要完整的记忆列表
"stats": full_data.get("stats", {}), # 统计数据还是完整的
"current_file": full_data.get("current_file", "")
}
return JSONResponse(content={"success": True, "data": data_to_send})
except Exception as e:
import traceback
traceback.print_exc()
return JSONResponse(content={"success": False, "error": str(e)}, status_code=500)
@router.get("/api/nodes/{node_id}/expand")
async def expand_node(node_id: str):
"""
获取指定节点的所有邻居节点和相关的边。
看,这就是按需加载的魔法。我可真是个天才,哼!
"""
try:
full_data = load_graph_data_from_file()
if "error" in full_data:
return JSONResponse(content={"success": False, "error": full_data["error"]}, status_code=404)
nodes_dict = full_data.get("nodes_dict", {})
adjacency_list = full_data.get("adjacency_list", {})
if node_id not in nodes_dict:
return JSONResponse(content={"success": False, "error": "节点未找到"}, status_code=404)
neighbor_edges = adjacency_list.get(node_id, [])
neighbor_node_ids = set()
for edge in neighbor_edges:
neighbor_node_ids.add(edge["from"])
neighbor_node_ids.add(edge["to"])
# 从 nodes_dict 中获取完整的邻居节点信息
neighbor_nodes = [nodes_dict[nid] for nid in neighbor_node_ids if nid in nodes_dict]
return JSONResponse(content={
"success": True,
"data": {
"nodes": neighbor_nodes,
"edges": neighbor_edges
}
})
except Exception as e:
import traceback
traceback.print_exc()
return JSONResponse(content={"success": False, "error": str(e)}, status_code=500)
@router.get("/api/graph/full")
async def get_full_graph_deprecated():
"""
(已废弃) 获取完整记忆图数据。
此接口现在只返回第一页的数据, 请使用 /api/graph/paged 进行分页获取。
"""
return await get_paged_graph(nodes_page=1, nodes_per_page=100, edges_page=1, edges_per_page=200)
@router.get("/api/files")

View File

@@ -532,20 +532,18 @@
<script>
let network = null;
let availableFiles = [];
// 现在的数据集是动态增长的,我们需要用 vis.DataSet 来管理
let nodesDataSet = new vis.DataSet([])
;
let edgesDataSet = new vis.DataSet([]);
let graphData = {
nodes: new vis.DataSet([])
,
edges: new vis.DataSet([])
nodes: [], // 这将作为原始数据的备份
edges: [],
memories: []
};
let originalData = null; // 用于过滤器
// 分页状态
let pagination = {
nodes: { page: 1, per_page: 200, total_pages: 1, total: 0 },
edges: { page: 1, per_page: 500, total_pages: 1, total: 0 }
};
let isLoading = false;
// 节点颜色配置
const nodeColors = {
'SUBJECT': '#FF6B6B',
@@ -625,26 +623,32 @@
dragView: true
}
};
// 初始化时使用我们可动态管理的 DataSet
const data = {
nodes: nodesDataSet,
edges: edgesDataSet
};
const data = {
nodes: new vis.DataSet([]),
edges: new vis.DataSet([])
};
network = new vis.Network(container, data, options);
network = new vis.Network(container, data, options);
// 添加事件监听
network.on('click', function(params) {
if (params.nodes.length > 0) {
const nodeId = params.nodes[0];
showNodeInfo(nodeId);
highlightConnectedNodes(nodeId);
// 单击时只高亮,不再执行复杂的BFS
} else {
// 点击空白处恢复所有节点
resetNodeHighlight();
resetNodeHighlight(); // 点击空白处恢复
}
});
// 这才是我们的秘密武器: 双击扩展! 哼哼~
network.on('doubleClick', async function(params) {
if (params.nodes.length > 0) {
const nodeId = params.nodes[0];
await expandNode(nodeId);
}
});
// 稳定化完成后停止物理引擎
network.on('stabilizationIterationsDone', function() {
console.log('初始稳定化完成,停止物理引擎');
@@ -660,125 +664,86 @@
});
}
// 重置并加载第一页数据
// 加载图形数据
async function loadGraph() {
if (isLoading) return;
console.log('开始加载初始图数据...');
// 重置状态
graphData.nodes.clear();
graphData.edges.clear();
pagination.nodes.page = 1;
pagination.edges.page = 1;
try {
// 先获取一次完整的统计信息
const statsResponse = await fetch('/visualizer/api/stats');
const statsResult = await statsResponse.json();
if(statsResult.success) {
updateStats(statsResult.data);
pagination.nodes.total = statsResult.data.total_nodes;
pagination.edges.total = statsResult.data.total_edges;
pagination.nodes.total_pages = Math.ceil(statsResult.data.total_nodes / pagination.nodes.per_page);
pagination.edges.total_pages = Math.ceil(statsResult.data.total_edges / pagination.edges.per_page);
} else {
throw new Error('获取统计信息失败: ' + statsResult.error);
}
// 加载第一页
await loadMoreData();
} catch (error) {
console.error('初始加载失败:', error);
alert('初始加载失败: ' + error.message);
}
}
// 加载更多数据(分页核心)
async function loadMoreData() {
if (isLoading) return;
const canLoadNodes = pagination.nodes.page <= pagination.nodes.total_pages;
const canLoadEdges = pagination.edges.page <= pagination.edges.total_pages;
if (!canLoadNodes && !canLoadEdges) {
console.log('所有数据已加载完毕');
return;
}
isLoading = true;
document.getElementById('loading').style.display = 'block';
try {
const url = `/visualizer/api/graph/paged?nodes_page=${pagination.nodes.page}&nodes_per_page=${pagination.nodes.per_page}&edges_page=${pagination.edges.page}&edges_per_page=${pagination.edges.per_page}`;
console.log(`正在请求: ${url}`);
const response = await fetch(url);
document.getElementById('loading').style.display = 'block';
// 请求新的核心节点接口,而不是那个又笨又重的full接口
const response = await fetch('/visualizer/api/graph/core');
const result = await response.json();
if (result.success) {
console.log(`成功获取 ${result.data.nodes.length} 个节点, ${result.data.edges.length} 个边`);
updateGraph(result.data); // 追加数据
originalData = result.data; // 保存原始数据用于过滤
// 初始加载时,清空旧数据
nodesDataSet.clear();
edgesDataSet.clear();
// 更新分页信息
if (result.data.pagination) {
pagination.nodes.page++;
pagination.edges.page++;
}
updateGraph(result.data, true); // true表示是初始加载
updateStats(result.data.stats);
} else {
throw new Error('加载分页数据失败: ' + result.error);
alert('加载核心节点失败: ' + result.error);
}
} catch (error) {
console.error('加载更多数据失败:', error);
console.error('加载图形失败:', error);
alert('加载失败: ' + error.message);
} finally {
isLoading = false;
document.getElementById('loading').style.display = 'none';
}
}
// 更新图形显示(追加数据)
function updateGraph(data) {
// originalData 用于过滤器, 这里只追加, 不完全覆盖
if (!originalData) {
originalData = { nodes: [], edges: [] };
// 更新图形显示
function updateGraph(data, isInitialLoad = false) {
if (isInitialLoad) {
// 如果是初始加载,则完全替换数据
graphData = data;
} else {
// 如果是扩展,则合并数据
// 使用一个Set来避免重复添加节点
const existingNodeIds = new Set(graphData.nodes.map(n => n.id));
data.nodes.forEach(newNode => {
if (!existingNodeIds.has(newNode.id)) {
graphData.nodes.push(newNode);
existingNodeIds.add(newNode.id);
}
});
// 同样避免重复添加边
const existingEdgeIds = new Set(graphData.edges.map(e => e.id));
data.edges.forEach(newEdge => {
if (!existingEdgeIds.has(newEdge.id)) {
graphData.edges.push(newEdge);
existingEdgeIds.add(newEdge.id);
}
});
}
originalData.nodes.push(...data.nodes);
originalData.edges.push(...data.edges);
// 处理节点数据
const newNodes = data.nodes.map(node => ({
// 处理节点数据,添加或更新到DataSet
const nodesToAdd = data.nodes.map(node => ({
id: node.id,
label: node.label,
title: node.title,
group: node.group,
color: nodeColors[node.group] || '#999',
// 瞧,现在节点越大,就说明它越重要,是不是很酷?
size: 15 + Math.min((node.degree || 0) * 2, 20),
metadata: node.metadata
}));
nodesDataSet.update(nodesToAdd);
// 处理边数据
const newEdges = data.edges.map(edge => ({
// 处理边数据,添加到DataSet
const edgesToAdd = data.edges.map(edge => ({
id: edge.id,
from: edge.from,
to: edge.to,
label: edge.label,
title: edge.title,
// 根据重要性调整边的宽度
width: (edge.importance || 0.5) * 2 + 1
}));
// 追加数据到 DataSet
if (newNodes.length > 0) {
graphData.nodes.add(newNodes);
}
if (newEdges.length > 0) {
graphData.edges.add(newEdges);
}
// 第一次加载时设置数据
if (pagination.nodes.page === 2) { // 意味着第一页刚加载完
network.setData({
nodes: graphData.nodes,
edges: graphData.edges
});
edgesDataSet.update(edgesToAdd);
// 只有在添加新节点时才需要重新稳定布局
if (nodesToAdd.length > 0) {
network.stabilize();
}
}
// 更新统计信息
@@ -1084,18 +1049,40 @@
});
}
}
// 适应窗口
function fitNetwork() {
if (network) {
network.fit({
animation: {
duration: 1000,
easingFunction: 'easeInOutQuad'
}
});
// 适应窗口
function fitNetwork() {
if (network) {
network.fit({
animation: {
duration: 1000,
easingFunction: 'easeInOutQuad'
}
});
}
}
// 新增: 扩展节点的函数
async function expandNode(nodeId) {
console.log(`正在扩展节点: ${nodeId}`);
document.getElementById('loading').style.display = 'block';
try {
const response = await fetch(`/visualizer/api/nodes/${nodeId}/expand`);
const result = await response.json();
if (result.success) {
console.log(`收到 ${result.data.nodes.length} 个新节点, ${result.data.edges.length} 条新边`);
updateGraph(result.data);
} else {
alert(`扩展节点失败: ${result.error}`);
}
} catch (error) {
console.error('扩展节点失败:', error);
alert('扩展节点失败: ' + error.message);
} finally {
document.getElementById('loading').style.display = 'none';
}
}
// 导出图形数据
function exportGraph() {
@@ -1234,42 +1221,13 @@
closeFileSelector();
}
}
// 页面加载完成后初始化
window.addEventListener('load', function() {
initNetwork();
loadGraph(); // 加载初始数据
loadFileList();
// 添加滚动加载监听器
const graphContainer = document.getElementById('memory-graph');
graphContainer.addEventListener('mousewheel', async (event) => {
if(network) {
const canvasHeight = network.canvas.body.height;
const viewPosition = network.getViewPosition();
const scale = network.getScale();
const viewHeight = canvasHeight / scale;
// 简单的滚动到底部检测(可能需要根据实际情况微调)
if (event.deltaY > 0 && !isLoading) {
const isAtBottom = viewPosition.y > (canvasHeight/2 - viewHeight/2) * 0.8;
if (isAtBottom) {
console.log("滚动到底部,加载更多数据...");
await loadMoreData();
}
}
}
});
// 添加一个按钮用于手动加载
const loadMoreBtn = document.createElement('button');
loadMoreBtn.textContent = '加载更多';
loadMoreBtn.className = 'btn';
loadMoreBtn.style.position = 'absolute';
loadMoreBtn.style.bottom = '20px';
loadMoreBtn.style.right = '20px';
loadMoreBtn.style.zIndex = '10';
loadMoreBtn.onclick = loadMoreData;
document.querySelector('.graph-container').appendChild(loadMoreBtn);
});
// 页面加载完成后初始化
window.addEventListener('load', function() {
initNetwork();
loadGraph();
loadFileList();
});
</script>
</body>
</html>