重构: 后端 df-ai/commands 拆分+df-nodes/workflow 改造+P0 bug 修复

- df-ai: context 历史中毒三档自愈 sanitize_messages(AC3)+anthropic_compat tool_use_id None 跳过(AC1/AC2)+删 router/stream 死码
- df-core: events 加 select_type+decisions 多选审批契约(F-260615-01)
- df-execute: shell run_command 工具复用(F-260615-05)
- df-nodes: human_node 多选校验+2 端到端测(F-01)+取消跳 set_failed(B-03b-R1/R2/R8)
- df-workflow: executor/dag/state cancel 闭环(B-06/07/03a/b)+provider approve options(R-PD-5)
- df-storage: find_path_conflict 抽公共(R-PD-11)+COLS 常量断言
- df-ideas: 删 IdeaPromoter/PromotionPolicy 死码(R-PD-14)
- src-tauri/commands/ai: secret keyring 迁移(FR-S1/R-PD-4)+GeneratingGuard RAII+disarm(B-09/26)+newConversation 软复位(B-10)+stream 心跳/stop select/空回复判错(B-02/04/05/15)+run_command(F-05)+mask audit(AR-3)
- src-tauri/commands/{project,task,workflow,mod,lib,state}: task detail IPC(F-02)+approve decisions+task list 联动(B-29)
- Cargo.lock+Cargo.toml 依赖同步

crates/df-ai/src/anthropic_compat.rs

@@ -14,7 +14,7 @@ use serde::{Deserialize, Serialize};
 use tracing::{debug, error, warn};
 
 use crate::provider::{
-    CompletionRequest, CompletionResponse, LlmProvider, MessageRole, ProviderFeatures,
+    CompletionRequest, CompletionResponse, LlmProvider, MessageRole,
     StreamChunk, StreamResult, TokenUsage, ToolCall, ToolCallDelta,
 };
 
@@ -102,7 +102,7 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
     let v: serde_json::Value = match serde_json::from_str(data) {
         Ok(v) => v,
         Err(_) => {
-            return StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None }
+            return StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
         }
     };
     let ty = v.get("type").and_then(|t| t.as_str()).unwrap_or("");
@@ -121,7 +121,7 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
                     total_tokens: inp as u32,
                 });
             }
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
         }
         // 消息增量：output_tokens 是累计值（非增量），直接覆盖 completion + 重算 total
         "message_delta" => {
@@ -131,14 +131,14 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
                 acc.completion_tokens = out as u32;
                 acc.total_tokens = acc.prompt_tokens + acc.completion_tokens;
             }
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
         }
         // 文本增量
         "content_block_delta" => {
             if let Some(delta) = v.get("delta") {
                 if delta.get("type").and_then(|t| t.as_str()) == Some("text_delta") {
                     let text = delta.get("text").and_then(|t| t.as_str()).unwrap_or("").to_string();
-                    return StreamChunk { delta: text, finished: false, tool_calls: None, usage: None };
+                    return StreamChunk { delta: text, finished: false, tool_calls: None, usage: None, error: None };
                 }
                 // 工具入参增量
                 if delta.get("type").and_then(|t| t.as_str()) == Some("input_json_delta") {
@@ -154,10 +154,11 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
                             function_arguments: Some(partial),
                         }]),
                         usage: None,
+                        error: None,
                     };
                 }
             }
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
         }
         // 工具块开始：带 id + name
         "content_block_start" => {
@@ -185,10 +186,11 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
                             function_arguments: None,
                         }]),
                         usage: None,
+                        error: None,
                     };
                 }
             }
-            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None }
         }
         // 消息结束：带出累积 usage
         "message_stop" => StreamChunk {
@@ -196,15 +198,17 @@ pub(crate) fn apply_anthropic_event(data: &str, usage_accum: &mut Option<TokenUs
             finished: true,
             tool_calls: None,
             usage: usage_accum.take(),
+            error: None,
         },
-        // 错误事件
+        // 错误事件：流中途出错。不走 finished 完成路径（避免残缺响应被当正常完成入库），
+        // 改由 stream_llm 识别 error 非空 → 发 AiError + 丢弃残缺（与 OpenAI 路径 Err 一致）。
         "error" => {
-            let msg = v.get("error").and_then(|e| e.get("message")).and_then(|m| m.as_str()).unwrap_or("stream error");
+            let msg = v.get("error").and_then(|e| e.get("message")).and_then(|m| m.as_str()).unwrap_or("stream error").to_string();
             error!(%msg, "Anthropic 流式错误事件");
-            StreamChunk { delta: String::new(), finished: true, tool_calls: None, usage: None }
+            StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: Some(msg) }
         }
         // content_block_stop / ping 等不产出 chunk
-        _ => StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None },
+        _ => StreamChunk { delta: String::new(), finished: false, tool_calls: None, usage: None, error: None },
     }
 }
 
@@ -236,7 +240,7 @@ impl AnthropicCompatProvider {
             .connect_timeout(std::time::Duration::from_secs(30))
             .build()
             .unwrap_or_else(|e| {
-                warn!("reqwest builder 失败，降级为默认 client: {}", e);
+                warn!("reqwest builder 失败，回退默认 client: {}", e);
                 Client::new()
             });
         Self {
@@ -508,12 +512,8 @@ impl LlmProvider for AnthropicCompatProvider {
         "anthropic-compat"
     }
 
-    fn supported_features(&self) -> ProviderFeatures {
-        ProviderFeatures {
-            streaming: true,
-            function_calling: true,
-            vision: false,
-        }
+    fn endpoint(&self) -> String {
+        self.messages_url()
     }
 }
 
@@ -663,17 +663,29 @@ mod tests {
         assert!(!c.finished);
     }
 
-    /// error 事件 → finished=true 终态空 chunk
+    /// error 事件 → error=Some + finished=false（R-P1-1：避免残缺响应被当正常完成入库，
+    /// 由 stream_llm 识别 error 非空发 AiError + 丢弃残缺，与 OpenAI 路径 Err 一致）
     #[test]
-    fn anthropic_error_event_finishes_stream() {
+    fn anthropic_error_event_yields_error_not_finished() {
         let mut acc: Option<TokenUsage> = None;
         apply_anthropic_event(&message_start(10), &mut acc);
         let c = apply_anthropic_event(r#"{"type":"error","error":{"message":"overloaded"}}"#, &mut acc);
-        assert!(c.finished, "error 应终止流");
+        assert!(!c.finished, "error 不走 finished 完成路径，否则残缺响应会被当正常完成");
+        assert_eq!(c.error.as_deref(), Some("overloaded"), "error 事件应携带错误消息");
         assert!(c.usage.is_none(), "error 不带出 usage");
+        assert!(c.delta.is_empty(), "error 不带文本增量");
         assert!(acc.is_some(), "error 不应清空已累积的 usage（与原实现一致）");
     }
 
+    /// error 事件无 error.message 字段时兜底为 "stream error"
+    #[test]
+    fn anthropic_error_event_missing_message_falls_back() {
+        let mut acc: Option<TokenUsage> = None;
+        let c = apply_anthropic_event(r#"{"type":"error"}"#, &mut acc);
+        assert_eq!(c.error.as_deref(), Some("stream error"));
+        assert!(!c.finished);
+    }
+
     /// ping / content_block_stop 等事件 → 空且不 finished
     #[test]
     fn anthropic_ping_and_block_stop_yield_empty_chunk() {