新增: 初始化 DevFlow 项目仓库

Tauri 2 + Vue 3 + Vite 6 桌面应用，Rust workspace 含 13 个 crate
(df-ai / df-storage / df-workflow / df-core / df-execute 等)。
核心能力：AI 聊天 agentic 循环(工具调用+人工审批)、工作流引擎、
任务/想法/项目/阶段管理、可追溯性，及配套前端组件。

crates/df-workflow/src/dag.rs

@@ -0,0 +1,141 @@
+//! DAG（有向无环图）定义与拓扑排序
+
+use std::collections::{HashMap, HashSet, VecDeque};
+
+use df_core::error::Result;
+use df_core::types::NodeId;
+
+use crate::node::Node;
+
+/// 图的边：从 source 到 target
+#[derive(Debug, Clone)]
+pub struct Edge {
+    pub source: NodeId,
+    pub target: NodeId,
+    /// 边的条件表达式（可选）
+    pub condition: Option<String>,
+}
+
+/// DAG 结构
+pub struct Dag {
+    /// 节点集合
+    pub nodes: HashMap<NodeId, Box<dyn Node>>,
+    /// 边集合
+    pub edges: Vec<Edge>,
+}
+
+impl Dag {
+    /// 创建空 DAG
+    pub fn new() -> Self {
+        Self {
+            nodes: HashMap::new(),
+            edges: Vec::new(),
+        }
+    }
+
+    /// 添加节点
+    pub fn add_node(&mut self, id: NodeId, node: Box<dyn Node>) {
+        self.nodes.insert(id, node);
+    }
+
+    /// 添加边
+    pub fn add_edge(&mut self, source: NodeId, target: NodeId) {
+        self.edges.push(Edge {
+            source,
+            target,
+            condition: None,
+        });
+    }
+
+    /// 添加带条件的边
+    pub fn add_edge_with_condition(
+        &mut self,
+        source: NodeId,
+        target: NodeId,
+        condition: String,
+    ) {
+        self.edges.push(Edge {
+            source,
+            target,
+            condition: Some(condition),
+        });
+    }
+
+    /// 获取指定节点的所有上游节点 ID
+    pub fn predecessors(&self, node_id: &NodeId) -> Vec<NodeId> {
+        self.edges
+            .iter()
+            .filter(|e| &e.target == node_id)
+            .map(|e| e.source.clone())
+            .collect()
+    }
+
+    /// 获取指定节点的所有下游节点 ID
+    pub fn successors(&self, node_id: &NodeId) -> Vec<NodeId> {
+        self.edges
+            .iter()
+            .filter(|e| &e.source == node_id)
+            .map(|e| e.target.clone())
+            .collect()
+    }
+
+    /// 拓扑排序 — 返回按执行顺序排列的节点 ID 层级
+    ///
+    /// 返回 Vec<Vec<NodeId>>，每层内的节点可以并行执行
+    pub fn topological_layers(&self) -> Result<Vec<Vec<NodeId>>> {
+        let node_ids: HashSet<NodeId> = self.nodes.keys().cloned().collect();
+        let mut in_degree: HashMap<NodeId, usize> = HashMap::new();
+
+        // 初始化入度
+        for id in &node_ids {
+            in_degree.insert(id.clone(), 0);
+        }
+        for edge in &self.edges {
+            if node_ids.contains(&edge.source) && node_ids.contains(&edge.target) {
+                *in_degree.entry(edge.target.clone()).or_insert(0) += 1;
+            }
+        }
+
+        // BFS 分层
+        let mut layers = Vec::new();
+        let mut queue: VecDeque<NodeId> = in_degree
+            .iter()
+            .filter(|(_, &deg)| deg == 0)
+            .map(|(id, _)| id.clone())
+            .collect();
+
+        let mut processed = 0usize;
+        while !queue.is_empty() {
+            let mut layer: Vec<NodeId> = Vec::new();
+            let layer_size = queue.len();
+            for _ in 0..layer_size {
+                if let Some(id) = queue.pop_front() {
+                    layer.push(id.clone());
+                    for succ in self.successors(&id) {
+                        let deg = in_degree.get_mut(&succ).unwrap();
+                        *deg -= 1;
+                        if *deg == 0 {
+                            queue.push_back(succ);
+                        }
+                    }
+                    processed += 1;
+                }
+            }
+            layers.push(layer);
+        }
+
+        if processed != node_ids.len() {
+            return Err(df_core::error::Error::Workflow(
+                "DAG 中存在环，无法进行拓扑排序".to_string(),
+            ));
+        }
+
+        Ok(layers)
+    }
+}
+
+impl Default for Dag {
+    fn default() -> Self {
+        Self::new()
+    }
+}