Revert "feat(visualizer): 引入核心图按需加载和节点扩展功能"

This reverts commit 0c41cd2a13.
2025-11-08 11:17:37 +08:00
parent 96dbb8fc55
commit 6521e681cd
2 changed files with 72 additions and 207 deletions
--- a/src/api/memory_visualizer_router.py
+++ b/src/api/memory_visualizer_router.py
@@ -62,10 +62,7 @@ def find_available_data_files() -> List[Path]:


 def load_graph_data_from_file(file_path: Optional[Path] = None) -> Dict[str, Any]:
-    """
-    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。
-    """
+    """从磁盘加载图数据"""
    global graph_data_cache, current_data_file

    if file_path and file_path != current_data_file:
@@ -80,12 +77,12 @@ def load_graph_data_from_file(file_path: Optional[Path] = None) -> Dict[str, Any
        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": {}, "nodes_dict": {}, "adjacency_list": {}}
+                return {"error": "未找到数据文件", "nodes": [], "edges": [], "stats": {}}
            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": {}, "nodes_dict": {}, "adjacency_list": {}}
+            return {"error": f"文件不存在: {graph_file}", "nodes": [], "edges": [], "stats": {}}

        with open(graph_file, "r", encoding="utf-8") as f:
            data = orjson.loads(f.read())
@@ -100,7 +97,6 @@ def load_graph_data_from_file(file_path: Optional[Path] = None) -> Dict[str, Any
                "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")
@@ -108,39 +104,26 @@ def load_graph_data_from_file(file_path: Optional[Path] = None) -> Dict[str, Any

        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",
-                }
-                edges_list.append(formatted_edge)
+            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)

-        # 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),
@@ -155,9 +138,11 @@ def load_graph_data_from_file(file_path: Optional[Path] = None) -> Dict[str, Any

    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"""
@@ -218,91 +203,29 @@ def _format_graph_data_from_manager(memory_manager) -> Dict[str, Any]:
        "current_file": "memory_manager (实时数据)",
    }

-@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。
-    """
+
+@router.get("/api/graph/full")
+async def get_full_graph():
+    """获取完整记忆图数据"""
    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)
+        from src.memory_graph.manager_singleton import get_memory_manager

-        # 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", [])
-        
-        # 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}
+        memory_manager = get_memory_manager()

-        # 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", "")
-        }
+        data = {}
+        if memory_manager and memory_manager._initialized:
+            data = _format_graph_data_from_manager(memory_manager)
+        else:
+            # 如果内存管理器不可用，则从文件加载
+            data = load_graph_data_from_file()

-        return JSONResponse(content={"success": True, "data": data_to_send})
+        return JSONResponse(content={"success": True, "data": data})
    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/files")
 async def list_files_api():
--- a/src/api/templates/visualizer.html
+++ b/src/api/templates/visualizer.html
@@ -532,17 +532,12 @@
    <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: [], // 这将作为原始数据的备份
+            nodes: [],
            edges: [],
            memories: []
        };
-        let originalData = null; // 用于过滤器
+        let originalData = null;

        // 节点颜色配置
        const nodeColors = {
@@ -623,32 +618,26 @@
                    dragView: true
                }
            };
-// 初始化时使用我们可动态管理的 DataSet
-const data = {
-    nodes: nodesDataSet,
-    edges: edgesDataSet
-};

-network = new vis.Network(container, data, options);
+            const data = {
+                nodes: new vis.DataSet([]),
+                edges: new vis.DataSet([])
+            };
+
+            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);
-                    // 单击时只高亮,不再执行复杂的BFS
+                    highlightConnectedNodes(nodeId);
                } else {
-                    resetNodeHighlight(); // 点击空白处恢复
+                    // 点击空白处，恢复所有节点
+                    resetNodeHighlight();
                }
            });

-            // 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');
@@ -668,20 +657,16 @@ network = new vis.Network(container, data, options);
        async function loadGraph() {
            try {
                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 response = await fetch('/visualizer/api/graph/full');
                const result = await response.json();

                if (result.success) {
-                    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();
-                    
-                    updateGraph(result.data, true); // true表示是初始加载
+                    originalData = result.data;
+                    updateGraph(result.data);
                    updateStats(result.data.stats);
                } else {
-                    alert('加载核心节点失败: ' + result.error);
+                    alert('加载失败: ' + result.error);
                }
            } catch (error) {
                console.error('加载图形失败:', error);
@@ -690,62 +675,41 @@ network = new vis.Network(container, data, options);
                document.getElementById('loading').style.display = 'none';
            }
        }
+
        // 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);
-                    }
-                });
+        function updateGraph(data) {
+            graphData = data;

-                // 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);
-                    }
-                });
-            }
-
-            // 处理节点数据,添加或更新到DataSet
-            const nodesToAdd = data.nodes.map(node => ({
+            // 处理节点数据
+            const nodes = 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,添加到DataSet
-            const edgesToAdd = data.edges.map(edge => ({
+            // 处理边数据
+            const edges = 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
+                width: edge.importance * 3 + 1
            }));
-            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();
-            }
+            // 更新网络
+            network.setData({
+                nodes: new vis.DataSet(nodes),
+                edges: new vis.DataSet(edges)
+            });
+
+            // 注意：setData 会自动触发物理引擎重新布局
+            // stabilizationIterationsDone 事件监听器会自动停止物理引擎
        }
+
        // 更新统计信息
        function updateStats(stats) {
            document.getElementById('statNodes').textContent = stats.total_nodes;
@@ -1049,40 +1013,18 @@ network = new vis.Network(container, data, options);
                });
            }
        }
-// 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() {