fix: writing mode first-report allows only the pipeline to write the report

- Strip write_file/str_replace/bash from the model binding in the
  first-report run: after_model rewrites only fire after a full model
  response, so any bound write tool let weak models draft the whole
  essay into tool args (write_file content or bash cat>/python
  heredocs) for tens of invisible seconds before interception
- Hallucinated hand-writes are still handled: after_model rewrites
  bash cat >/python open('w')/tee and leftover write calls to
  deep_research_report; wrap_tool_call rejects whatever reaches the
  tool layer; post-success writes are dropped, nudged to a 2-3
  sentence summary, and patched with a fallback closing message so
  the turn never ends silently
- The rewritten pipeline call carries topic = original request
  (clarification answers skipped) plus focus = clarification answers,
  so the pipeline writes the clarified subject instead of the raw
  prompt text; prompts updated to match (tools unavailable, call the
  tool directly, do not draft first)
- Frontend write-step interception and streaming preview scoping now
  applies only in writing mode; normal mode shows/previews writes
  exactly as before

.gitignore

@@ -127,6 +127,9 @@ offline-backend-20260512/backend/tests/*
 !offline-backend-20260512/backend/tests/test_workflow_engine.py
 !offline-backend-20260512/backend/tests/test_workflow_runs.py
 !offline-backend-20260512/backend/tests/test_workflow_concurrency.py
+# Writing-mode first-report pipeline enforcement regressions.
+!offline-backend-20260512/backend/tests/test_writing_mode_report_middleware.py
+!offline-backend-20260512/backend/tests/test_writing_rewrite_prompt.py
 deploy
 .history
 

frontend-web/src/components/workspace/chats/chat-box.tsx

@@ -101,6 +101,9 @@ const ChatBox: React.FC<{
   const [pinnedReferenceId, setPinnedReferenceId] = useState<string | null>(null);
   const [backendReferenceBatches, setBackendReferenceBatches] = useState<BackendReferenceBatch[]>([]);
   const [settings] = useLocalSettings();
+  // 写作模式专属的产物拦截 / 沙箱打开策略只在开关开启时生效，普通模式保持
+  // 原有行为（新产物自动打开 + in-flight 预览不过滤）。
+  const writingModeEnabled = !!settings.context.writing_mode;
   const artifactDirectoryModeEnabled =
     settings.display.artifactDirectoryModeEnabled ?? false;
   const ragModeEnabled =
@@ -392,7 +395,7 @@ const ChatBox: React.FC<{
         ((hasNewArtifact || !hadArtifacts) && !selectedArtifact))
     ) {
       const newest = nextArtifacts[nextArtifacts.length - 1]!;
-      if (shouldAutoOpenWritingArtifact(newest, thread.messages)) {
+      if (shouldAutoOpenWritingArtifact(newest, thread.messages, writingModeEnabled)) {
         selectArtifact(newest);
         setArtifactsOpen(true);
         setSideTab("document");
@@ -429,6 +432,7 @@ const ChatBox: React.FC<{
     availableArtifacts,
     disableArtifacts,
     thread.messages,
+    writingModeEnabled,
   ]);
 
   // Live sandbox: open as soon as any in-flight write_file has a path or
@@ -439,8 +443,8 @@ const ChatBox: React.FC<{
     () =>
       disableArtifacts || !thread.isLoading
         ? null
-        : latestInFlightWriteFilePreview(thread.messages ?? []),
-    [disableArtifacts, thread.isLoading, thread.messages],
+        : latestInFlightWriteFilePreview(thread.messages ?? [], writingModeEnabled),
+    [disableArtifacts, thread.isLoading, thread.messages, writingModeEnabled],
   );
   useEffect(() => {
     if (!streamingWritePreview) return;

frontend-web/src/components/workspace/messages/message-group.tsx

@@ -101,8 +101,14 @@ export function MessageGroup({
   const [showLastThinking, setShowLastThinking] = useState(
     env.NEXT_PUBLIC_STATIC_WEBSITE_ONLY === "true",
   );
-  const steps = useMemo(() => convertToSteps(messages), [messages]);
   const [settings] = useLocalSettings();
+  // 写作模式的「拦截 outputs/*.md 手写」只在写作模式生效；普通模式的
+  // write_file / read_file 步骤条必须照旧显示。
+  const writingModeEnabled = !!settings.context.writing_mode;
+  const steps = useMemo(
+    () => convertToSteps(messages, writingModeEnabled),
+    [messages, writingModeEnabled],
+  );
   const { skills } = useSkills();
   const skillDisplayMap = useMemo(
     () => (settings.display.ragModeEnabled ? buildSkillDisplayMap(skills) : new Map()),
@@ -849,7 +855,7 @@ interface CoTToolCallStep extends GenericCoTStep<"toolCall"> {
 
 type CoTStep = CoTReasoningStep | CoTToolCallStep;
 
-function convertToSteps(messages: Message[]): CoTStep[] {
+function convertToSteps(messages: Message[], writingMode: boolean): CoTStep[] {
   const steps: CoTStep[] = [];
   for (const message of messages) {
     if (message.type === "ai") {
@@ -879,7 +885,7 @@ function convertToSteps(messages: Message[]): CoTStep[] {
             tool_call.name === "read_multiple_files" ||
             tool_call.name === "present_files"
           ) &&
-          isInterceptedWritingReportWrite(writePath, message.id, messages)
+          isInterceptedWritingReportWrite(writePath, message.id, messages, writingMode)
         ) {
           continue;
         }

frontend-web/src/core/artifacts/write-file-in-flight.test.ts

@@ -61,7 +61,27 @@ test("latestInFlightWriteFilePreview keeps markdown when a later json write is i
   assert.match(preview?.artifactPath ?? "", /report\.md/);
 });
 
-test("latestInFlightWriteFilePreview skips intercepted custom outputs markdown", () => {
+test("latestInFlightWriteFilePreview skips intercepted custom outputs markdown in writing mode", () => {
+  const messages = [
+    {
+      id: "m1",
+      type: "ai",
+      tool_calls: [
+        {
+          id: "w1",
+          name: "write_file",
+          args: {
+            path: "/mnt/user-data/outputs/ai-agent-architecture-paper.md",
+            content: "# 草稿\n",
+          },
+        },
+      ],
+    },
+  ];
+  assert.equal(latestInFlightWriteFilePreview(messages, true), null);
+});
+
+test("latestInFlightWriteFilePreview keeps custom outputs markdown live in normal mode", () => {
   const preview = latestInFlightWriteFilePreview([
     {
       id: "m1",
@@ -78,54 +98,114 @@ test("latestInFlightWriteFilePreview skips intercepted custom outputs markdown",
       ],
     },
   ]);
-  assert.equal(preview, null);
+  assert.ok(preview);
+  assert.match(preview?.artifactPath ?? "", /ai-agent-architecture-paper\.md/);
 });
 
 test("latestInFlightWriteFilePreview skips report.md while the first-turn pipeline is active", () => {
-  const preview = latestInFlightWriteFilePreview([
-    { type: "human", content: "写一篇论文" },
-    {
-      id: "m-pipe",
-      type: "ai",
-      tool_calls: [{ id: "p1", name: "deep_research_report", args: { topic: "课题" } }],
-    },
-    {
-      id: "m-write",
-      type: "ai",
-      tool_calls: [
-        {
-          id: "w1",
-          name: "write_file",
-          args: {
-            path: "/mnt/user-data/outputs/report.md",
-            content: "# 我自己写\n",
+  const preview = latestInFlightWriteFilePreview(
+    [
+      { type: "human", content: "写一篇论文" },
+      {
+        id: "m-pipe",
+        type: "ai",
+        tool_calls: [{ id: "p1", name: "deep_research_report", args: { topic: "课题" } }],
+      },
+      {
+        id: "m-write",
+        type: "ai",
+        tool_calls: [
+          {
+            id: "w1",
+            name: "write_file",
+            args: {
+              path: "/mnt/user-data/outputs/report.md",
+              content: "# 我自己写\n",
+            },
           },
-        },
-      ],
-    },
-  ]);
+        ],
+      },
+    ],
+    true,
+  );
   assert.equal(preview, null);
 });
 
 test("latestInFlightWriteFilePreview still opens the injected research stub", () => {
+  const preview = latestInFlightWriteFilePreview(
+    [
+      {
+        id: "research-report-j1",
+        type: "ai",
+        tool_calls: [
+          {
+            id: "research-report-j1-write",
+            name: "write_file",
+            args: {
+              path: "/mnt/user-data/outputs/report.md",
+              content: "# 报告\n",
+            },
+          },
+        ],
+      },
+    ],
+    true,
+  );
+  assert.ok(preview);
+  assert.match(preview?.artifactPath ?? "", /report\.md/);
+});
+
+test("writing mode still previews follow-up-turn writes after a later user message", () => {
+  // 续写轮（成功之后用户又发了新消息）：真实 write_file 编辑照常预览。
+  const preview = latestInFlightWriteFilePreview(
+    [
+      { type: "human", content: "写一篇论文" },
+      {
+        id: "m-pipe",
+        type: "ai",
+        tool_calls: [{ id: "p1", name: "deep_research_report", args: { topic: "课题" } }],
+      },
+      {
+        id: "m-result",
+        type: "tool",
+        tool_call_id: "p1",
+        name: "deep_research_report",
+        content: "研究报告已完成：已写入 report.md 并展示给用户。",
+      },
+      { type: "human", content: "把第二章改写得更学术一些" },
+      {
+        id: "m-edit",
+        type: "ai",
+        tool_calls: [
+          {
+            id: "w2",
+            name: "write_file",
+            args: {
+              path: "/mnt/user-data/outputs/report.md",
+              content: "# 修订后的报告\n",
+            },
+          },
+        ],
+      },
+    ],
+    true,
+  );
+  assert.ok(preview);
+  assert.equal(preview?.previewKey, "m-edit:w2");
+});
+
+test("normal mode keeps previewing pathless streaming drafts", () => {
   const preview = latestInFlightWriteFilePreview([
     {
-      id: "research-report-j1",
+      id: "m1",
       type: "ai",
       tool_calls: [
-        {
-          id: "research-report-j1-write",
-          name: "write_file",
-          args: {
-            path: "/mnt/user-data/outputs/report.md",
-            content: "# 报告\n",
-          },
-        },
+        { id: "w1", name: "write_file", args: { content: "# 没有路径的流式草稿\n" } },
       ],
     },
   ]);
   assert.ok(preview);
-  assert.match(preview?.artifactPath ?? "", /report\.md/);
+  assert.match(preview?.artifactPath ?? "", /\.md/);
 });
 
 test("latestInFlightWriteFilePreview does not auto-open a json-only write", () => {

frontend-web/src/core/artifacts/write-file-in-flight.ts

@@ -38,7 +38,10 @@ type WriteFileThreadLike = {
   messages: Array<{
     id?: string;
     type?: string;
+    name?: string;
+    content?: unknown;
     tool_call_id?: string;
+    additional_kwargs?: Record<string, unknown>;
     tool_calls?: Array<{
       id?: string;
       name?: string;
@@ -95,6 +98,7 @@ export function isWriteFileInFlight(
  */
 export function latestInFlightWriteFilePreview(
   messages: WriteFileThreadLike["messages"],
+  writingMode = false,
 ): { artifactPath: string; previewKey: string } | null {
   const thread = { messages };
   for (let messageIndex = messages.length - 1; messageIndex >= 0; messageIndex -= 1) {
@@ -125,8 +129,9 @@ export function latestInFlightWriteFilePreview(
         continue;
       }
       // Writing mode rewrites custom outputs/*.md to deep_research_report.
-      // Opening that filename would 404-poll until report.md lands.
-      if (isInterceptedWritingReportWrite(sourcePath, message.id, messages)) {
+      // Opening that filename would 404-poll until report.md lands. Normal
+      // mode never skips: the write is a real deliverable, not a rewrite.
+      if (isInterceptedWritingReportWrite(sourcePath, message.id, messages, writingMode)) {
         continue;
       }
       // JSON (e.g. agentfx task-reports.json) is too large to live-preview:

frontend-web/src/core/threads/use-research-writing-feed.ts

@@ -91,7 +91,8 @@ export function useResearchWritingFeed<T extends FeedThreadLike>(
       current !== null &&
       current !== virtualUrl &&
       current !== RESEARCH_REPORT_OUTPUT_PATH &&
-      !isInterceptedWritingReportWrite(currentPath);
+      // research 流存在即本线程跑过写作模式管线，这里恒按写作模式判定。
+      !isInterceptedWritingReportWrite(currentPath, undefined, undefined, true);
     if (keepUserSelection) {
       return;
     }

frontend-web/src/core/threads/writing-mode.test.ts

@@ -9,18 +9,33 @@ import {
 
 test("custom outputs markdown is always intercepted except the research stub", () => {
   assert.equal(
-    isInterceptedWritingReportWrite("/mnt/user-data/outputs/paper.md"),
+    isInterceptedWritingReportWrite("/mnt/user-data/outputs/paper.md", undefined, undefined, true),
     true,
   );
   assert.equal(
     isInterceptedWritingReportWrite(
       "/mnt/user-data/outputs/report.md",
       "research-report-j1",
+      undefined,
+      true,
     ),
     false,
   );
 });
 
+test("normal mode never intercepts outputs markdown writes", () => {
+  assert.equal(
+    isInterceptedWritingReportWrite("/mnt/user-data/outputs/paper.md"),
+    false,
+  );
+  assert.equal(
+    isInterceptedWritingReportWrite("/mnt/user-data/outputs/report.md", "m0", [
+      { type: "human", content: "写一篇论文" },
+    ]),
+    false,
+  );
+});
+
 test("report.md is intercepted for the whole first-report turn", () => {
   const beforePipeline = [{ type: "human", content: "写一篇论文" }];
   assert.equal(isWritingFirstReportTurn(beforePipeline), true);
@@ -29,6 +44,7 @@ test("report.md is intercepted for the whole first-report turn", () => {
       "/mnt/user-data/outputs/report.md",
       "m1",
       beforePipeline,
+      true,
     ),
     true,
   );
@@ -42,7 +58,7 @@ test("report.md is intercepted for the whole first-report turn", () => {
   ];
   assert.equal(isWritingFirstReportTurn(inFlight), true);
   assert.equal(
-    isInterceptedWritingReportWrite("/mnt/user-data/outputs/report.md", "m2", inFlight),
+    isInterceptedWritingReportWrite("/mnt/user-data/outputs/report.md", "m2", inFlight, true),
     true,
   );
 
@@ -56,7 +72,7 @@ test("report.md is intercepted for the whole first-report turn", () => {
   ];
   assert.equal(isWritingFirstReportTurn(succeeded), true);
   assert.equal(
-    isInterceptedWritingReportWrite("/mnt/user-data/outputs/report.md", "m3", succeeded),
+    isInterceptedWritingReportWrite("/mnt/user-data/outputs/report.md", "m3", succeeded, true),
     true,
   );
 });
@@ -70,9 +86,27 @@ test("sandbox auto-open waits for report.md on the first-report turn", () => {
     },
   ];
   assert.equal(
-    shouldAutoOpenWritingArtifact("/mnt/user-data/outputs/research-notes.md", firstTurn),
+    shouldAutoOpenWritingArtifact("/mnt/user-data/outputs/research-notes.md", firstTurn, true),
     false,
   );
+  assert.equal(
+    shouldAutoOpenWritingArtifact("/mnt/user-data/outputs/report.md", firstTurn, true),
+    true,
+  );
+});
+
+test("normal mode auto-opens every new artifact like before writing mode existed", () => {
+  const firstTurn = [
+    { type: "human", content: "写一篇论文" },
+    {
+      type: "ai",
+      tool_calls: [{ name: "deep_research_report" }],
+    },
+  ];
+  assert.equal(
+    shouldAutoOpenWritingArtifact("/mnt/user-data/outputs/research-notes.md", firstTurn),
+    true,
+  );
   assert.equal(
     shouldAutoOpenWritingArtifact("/mnt/user-data/outputs/report.md", firstTurn),
     true,
@@ -95,7 +129,7 @@ test("a later user turn releases report.md live edits", () => {
   ];
   assert.equal(isWritingFirstReportTurn(followUp), false);
   assert.equal(
-    isInterceptedWritingReportWrite("/mnt/user-data/outputs/report.md", "m4", followUp),
+    isInterceptedWritingReportWrite("/mnt/user-data/outputs/report.md", "m4", followUp, true),
     false,
   );
 });

frontend-web/src/core/threads/writing-mode.ts

@@ -67,12 +67,19 @@ export function isWritingFirstReportTurn(
  * Hand-written outputs/*.md writes the backend rewrites or drops:
  * custom filenames always, and `report.md` while the first-turn pipeline is
  * in-flight or just succeeded. The injected research stub stays visible.
+ *
+ * Everything above only exists in writing mode — normal mode writes md files
+ * by hand as always, so `writingMode=false` (the default) never intercepts.
  */
 export function isInterceptedWritingReportWrite(
   path: string | null | undefined,
   messageId?: string | null,
   messages?: readonly WritingPipelineMessage[] | null,
+  writingMode = false,
 ): boolean {
+  if (!writingMode) {
+    return false;
+  }
   if (typeof messageId === "string" && messageId.startsWith("research-report-")) {
     return false;
   }
@@ -85,18 +92,26 @@ export function isInterceptedWritingReportWrite(
   return isWritingFirstReportTurn(messages);
 }
 
-/** Auto-open the sandbox only for the real report during the first-report turn. */
+/**
+ * Auto-open the sandbox only for the real report during the first-report
+ * turn. Normal mode keeps the pre-writing-mode behavior: always auto-open
+ * the newest artifact.
+ */
 export function shouldAutoOpenWritingArtifact(
   path: string | null | undefined,
   messages?: readonly WritingPipelineMessage[] | null,
+  writingMode = false,
 ): boolean {
   if (!path) {
     return false;
   }
+  if (!writingMode) {
+    return true;
+  }
   if (isWritingFirstReportTurn(messages)) {
     return isWritingModeReportPath(path);
   }
-  return !isInterceptedWritingReportWrite(path, undefined, messages);
+  return !isInterceptedWritingReportWrite(path, undefined, messages, true);
 }
 
 export function resolveWritingModeReportPath(

offline-backend-20260512/backend/packages/harness/deerflow/agents/lead_agent/prompt.py

@@ -795,15 +795,14 @@ def apply_agent_only_prompt_template(
         # 对话行为照旧；只有开始写 md 时才走 deep_research_report。资料不足也直接开写。
         writing_mode_section = """<writing_mode>
 Writing mode is enabled for this run (first report turn — no existing artifact).
-- HARD RULE: the report file is produced ONLY by the `deep_research_report` tool — never write it yourself with `write_file`, never `present_files` it.
+- HARD RULE: the report file is produced ONLY by the `deep_research_report` tool — call it directly at delivery time and do NOT draft the full report body first (not in chat, not inside tool arguments). File-writing tools (`write_file` / `str_replace`) and the `bash` tool are NOT available in this run; any hand-write attempt is intercepted and redirected to `deep_research_report`. Never `present_files` the report.
 - Work normally (chat, search, clarify) until the report is due; then produce it by calling the `deep_research_report` tool:
-  `topic` = the user's subject copied faithfully, `focus` = the user's extra requirements (if any).
+  `topic` = the user's subject (the refined thesis after clarifications, not the raw first message), `focus` = the extra requirements from the user's answers (type, length, tone, must-cover points).
   The tool reuses the conversation's collected materials and writes the full report (general-analysis structure with references)
   to `/mnt/user-data/outputs/report.md`, presented automatically.
 - If harvested materials are thin, still call `deep_research_report` once and let it write immediately.
   Do NOT ask the user whether to search for more, and do NOT call `ask_clarification` for insufficient materials.
 - Search with your normal conversation tools. `deep_research_report` only writes the report file from materials already in this conversation; it does not search.
-- Do NOT write the report body yourself with `write_file`, and do NOT call `present_files` for it.
 - After the tool returns successfully: do NOT call `read_file`, `write_file`, `str_replace`, or `present_files` on the report. Reply briefly (2-3 sentences) summarizing the core conclusions. Do not rewrite even if you think materials were thin.
 - Only if the tool fails, tell the user and offer to retry.
 </writing_mode>
@@ -1479,20 +1478,18 @@ def apply_prompt_template(
 Writing mode is enabled for this run (first report turn — no existing artifact).
 
 **Mandatory Output Contract**
-- HARD RULE: the report file is produced ONLY by the `deep_research_report` tool. You are FORBIDDEN from writing the report yourself — do not call `write_file`
-  (or any file-writing tool) to create the report, and do not call `present_files` for it.
+- HARD RULE: the report file is produced ONLY by the `deep_research_report` tool. Call the tool directly when the report is due — do NOT draft the full report body first (not in chat, not inside tool arguments). File-writing tools (`write_file` / `str_replace`) and the `bash` tool are NOT available in this run; any hand-write attempt is intercepted and redirected to `deep_research_report`. Do not call `present_files` for the report.
 - Treat the user's request as a research-report writing task. Work normally until delivery time: discuss, search, and clarify exactly as you always would.
-- When the report file is due — the user asks to start writing, or you have finished gathering what the conversation needs — call the `deep_research_report` tool:
-  - `topic`: the user's subject/thesis, copied faithfully.
-  - `focus`: the user's extra requirements (length, tone, must-cover points), if any.
+- When the report file is due — the user asks to start writing, or you have finished gathering what the conversation needs — call the `deep_research_report` tool directly:
+  - `topic`: the user's subject/thesis — the refined one settled in the clarifications, not the raw first message.
+  - `focus`: the extra requirements from the user's answers (type, length, tone, must-cover points), if any.
 - The tool reuses the materials already collected in this conversation, then writes the full
   report (general-analysis structure with a numbered reference section) to `/mnt/user-data/outputs/report.md`, presented automatically.
 - If harvested materials are thin, still call `deep_research_report` once and let it start the writing pipeline immediately.
   Do NOT ask the user whether to search for more materials, and do NOT call `ask_clarification` for that reason.
 - Search with your normal conversation tools. `deep_research_report` only writes the report file from materials already in this conversation; it does not search.
-- Do NOT write the report body yourself with `write_file`, and do NOT call `present_files` for the report — the tool already handles both.
 - While the tool runs, stay silent. After it returns successfully: do NOT call `read_file`, `write_file`, `str_replace`, or `present_files` on the report. Reply briefly (2-3 sentences) summarizing the report's core conclusions and point the user to the Markdown artifact. Do not duplicate the report inline, and do not rewrite even if you think materials were thin.
-- Only if the tool fails, tell the user what went wrong and offer to retry; do not silently fall back to writing the report by hand unless the user explicitly asks.
+- Only if the tool fails, tell the user what went wrong and offer to retry; do not silently fall back to writing the report by hand.
 </writing_mode>
 """
     else:

offline-backend-20260512/backend/packages/harness/deerflow/agents/middlewares/writing_mode_report_middleware.py

@@ -1,19 +1,35 @@
 """Redirect writing-mode Markdown deliverables onto ``deep_research_report``.
 
-Writing mode still allows normal chat, search, and clarification. The pipeline
-starts only when the model begins writing the report file (``write_file`` /
-``str_replace`` of ``report.md`` or any Markdown under
-``/mnt/user-data/outputs/``): those calls are rewritten to
-``deep_research_report``. Sibling ``present_files`` of the same report are
-dropped because the pipeline presents the file itself.
+Writing mode still allows normal chat, search, and clarification. The report
+only comes from the pipeline, and no hand-write path can even start:
+
+1. ``wrap_model_call`` removes ``write_file`` / ``str_replace`` / ``bash``
+   from the model binding for the whole first-report run. ``after_model``
+   rewrites can only fire AFTER a model response completes, so any write tool
+   left bound lets weak models stream the full essay into its arguments first
+   (``write_file`` content or a bash ``cat > report.md << EOF`` heredoc) for
+   tens of seconds, invisible to the user. bash is the only execution tool
+   that writes files, so excluding it too leaves NO tool the model could use
+   to start a file write — at delivery time the only path is the
+   ``deep_research_report`` call itself.
+2. Hallucinated calls (emitted despite not being bound) are still handled:
+   bash heredoc / ``python open(..., 'w')`` / ``tee`` writes and leftover
+   ``write_file`` / ``str_replace`` calls are rewritten to the pipeline by
+   ``after_model``, and ``wrap_tool_call`` rejects whatever reaches the tool
+   layer.
+
+The rewritten pipeline call carries ``topic`` = the user's original request
+(clarification answers skipped) plus ``focus`` = the clarification answers
+(direction/type/length), so the pipeline writes the refined subject instead of
+the raw prompt text.
 
 After the pipeline has succeeded once in this thread, further
 ``deep_research_report`` / hand-written report writes / ``read_file`` of the
 report are dropped. The first time that happens, a hidden summary nudge is
 injected and the graph jumps back to the model so it can write the 2–3
-sentence wrap-up. If it still tries to loop after that nudge, the turn ends.
-Ending immediately on the first rewrite attempt left the model's
-"I will rewrite this" text as the visible summary.
+sentence wrap-up. If it still tries to loop after that nudge, the dropped
+message is patched to a fallback summary and the turn ends — the user always
+sees a closing message.
 
 This middleware never sets ``tool_choice``. Thinking-mode providers (Aliyun
 compatible-mode) reject ``required`` / object ``tool_choice`` with HTTP 400.
@@ -23,12 +39,14 @@ from __future__ import annotations
 
 import json
 import logging
+import re
 from collections.abc import Awaitable, Callable
 from copy import deepcopy
 from typing import Any, override
 
 from langchain.agents import AgentState
 from langchain.agents.middleware import AgentMiddleware, hook_config
+from langchain.agents.middleware.types import ModelCallResult, ModelRequest, ModelResponse
 from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
 from langgraph.prebuilt.tool_node import ToolCallRequest
 from langgraph.runtime import Runtime
@@ -42,24 +60,20 @@ TOOL_NAME = "deep_research_report"
 _WRITE_TOOLS = frozenset({"write_file", "str_replace"})
 _READ_TOOLS = frozenset({"read_file", "read_multiple_files"})
 _PRESENT_TOOL = "present_files"
+_BASH_TOOL = "bash"
 _OUTPUTS_PREFIX = "/mnt/user-data/outputs"
 _MAX_TOPIC_CHARS = 500
+_MAX_FOCUS_CHARS = 600
 _NUDGE_KWARG = "writing_mode_summary_nudge"
-_REJECT_HANDWRITTEN = (
-    "写作模式的报告文件必须由 `deep_research_report` 生成，禁止用 write_file / "
-    "str_replace 手写报告。请立即调用 `deep_research_report`（topic=用户课题原文）。"
-)
+_FALLBACK_SUMMARY = "写作管线已完成，报告已写入 /mnt/user-data/outputs/report.md 并展示在右侧沙箱，可直接查看。如需调整内容，请在下一条消息中告诉我具体要求。"
+_REJECT_HANDWRITTEN = "写作模式的报告文件必须由 `deep_research_report` 生成，禁止用 write_file / str_replace / bash 命令（cat > 重定向、python open(..., 'w')、tee 等）手写报告。请立即调用 `deep_research_report`（topic=用户课题原文）。"
 _REJECT_AFTER_SUCCESS = (
     "写作管线已经完成，报告已写入 /mnt/user-data/outputs/report.md 并展示给用户。"
-    "禁止再次调用 deep_research_report，也禁止用 write_file / str_replace / "
+    "禁止再次调用 deep_research_report，也禁止用 write_file / str_replace / bash / "
     "read_file 读写该报告。请只用 2-3 句话总结核心结论后结束本轮，不要再调用任何文件或写作工具。"
 )
 _SUMMARY_NUDGE = (
-    "<system_reminder>\n"
-    "写作管线已经完成，报告已写入 /mnt/user-data/outputs/report.md 并展示给用户。\n"
-    "请只用 2-3 句话总结核心结论，不要再调用任何工具，不要阅读或重写该文件。\n"
-    "不要评价材料是否不足，不要计划重写。\n"
-    "</system_reminder>"
+    "<system_reminder>\n写作管线已经完成，报告已写入 /mnt/user-data/outputs/report.md 并展示给用户。\n请只用 2-3 句话总结核心结论，不要再调用任何工具，不要阅读或重写该文件。\n不要评价材料是否不足，不要计划重写。\n</system_reminder>"
 )
 
 
@@ -119,11 +133,42 @@ def _is_outputs_markdown_path(path: str) -> bool:
     return relative == "outputs" or relative.startswith("outputs/")
 
 
+# bash 手写报告的识别：写入动作（重定向 / tee / python 只写打开 / write_text）
+# 的目标本身是交付物 Markdown。纯读取（mkdir、wc、cat 输出）不拦。
+_BASH_MD_PATH = re.compile(r"""['"]([^'"]{0,200}\.md)['"]|(^|[\s;|&<>()=])([^\s;'"&|<>(){},]{0,200}\.md)\b""")
+_BASH_MD_REDIRECT = re.compile(r">{1,2}\s*([^\s;|&>]{0,200}\.md)\b")
+_BASH_MD_TEE = re.compile(r"\btee\s+(?:-[A-Za-z]+\s+)*([^\s;|&<>]{0,200}\.md)\b")
+_BASH_MD_PY_WRITE = re.compile(r"""open\s*\(\s*['"][^'"]{0,200}\.md['"]\s*,\s*['"]w""")
+
+
+def _bash_command_writes_report(command: str) -> bool:
+    """True 当 bash 命令在向写作模式的 Markdown 交付物写入内容。
+
+    实测弱模型被禁用手写工具后会绕道 bash：``cat > report.md << 'EOF'``、
+    ``python3 << PYEOF`` + ``open(..., 'w')``、``tee`` 等。按「写入动作的
+    目标（或命令提到的路径）是 outputs Markdown / report.md」判定；
+    mkdir、wc、cat 读取这类无写入动作的命令不受影响。
+    """
+    if not command or ".md" not in command:
+        return False
+    for pattern in (_BASH_MD_REDIRECT, _BASH_MD_TEE):
+        if any(_is_outputs_markdown_path(match.group(1)) for match in pattern.finditer(command)):
+            return True
+    paths = [quoted or bare or "" for quoted, _, bare in _BASH_MD_PATH.findall(command)]
+    if not any(_is_outputs_markdown_path(path) for path in paths):
+        return False
+    return bool(_BASH_MD_PY_WRITE.search(command)) or "write_text" in command or "write_bytes" in command
+
+
 def is_handwritten_report_call(tool_call: object) -> bool:
     """True when the model is about to hand-write the writing-mode Markdown file."""
-    if _tool_name(tool_call) not in _WRITE_TOOLS:
-        return False
-    return _is_outputs_markdown_path(_tool_path(tool_call))
+    name = _tool_name(tool_call)
+    if name in _WRITE_TOOLS:
+        return _is_outputs_markdown_path(_tool_path(tool_call))
+    if name == _BASH_TOOL:
+        args = _normalize_args(_tool_field(tool_call, "args", {}))
+        return _bash_command_writes_report(str(args.get("command") or ""))
+    return False
 
 
 def is_report_present_call(tool_call: object) -> bool:
@@ -184,28 +229,6 @@ def _summary_nudge_message() -> HumanMessage:
     )
 
 
-def is_post_success_loop_call(tool_call: object) -> bool:
-    """After a successful pipeline, re-reading the report is also a loop."""
-    return is_deliverable_loop_call(tool_call) or is_report_reread_call(tool_call)
-
-
-def _already_nudged_summary(messages: list[Any]) -> bool:
-    for message in messages:
-        if not isinstance(message, HumanMessage):
-            continue
-        kwargs = getattr(message, "additional_kwargs", None) or {}
-        if kwargs.get(_NUDGE_KWARG):
-            return True
-    return False
-
-
-def _summary_nudge_message() -> HumanMessage:
-    return HumanMessage(
-        content=_SUMMARY_NUDGE,
-        additional_kwargs={"hide_from_ui": True, _NUDGE_KWARG: True},
-    )
-
-
 def _report_tool_succeeded(message: ToolMessage) -> bool:
     if str(getattr(message, "name", "") or "") != TOOL_NAME:
         return False
@@ -238,21 +261,58 @@ def _message_text(message: Any) -> str:
     return str(content or "").strip()
 
 
+def _is_clarification_result(message: Any) -> bool:
+    return isinstance(message, ToolMessage) and str(getattr(message, "name", "") or "") == "ask_clarification"
+
+
 def extract_report_topic(messages: list[Any]) -> str:
-    """Use the latest visible user text as ``deep_research_report.topic``."""
-    for message in reversed(messages):
-        if _is_visible_human(message):
-            text = " ".join(_message_text(message).split())
-            if text:
-                return text[:_MAX_TOPIC_CHARS]
+    """Use the latest visible user text that is not a clarification answer.
+
+    澄清轮里用户对 ask_clarification 的回答（紧跟着澄清 ToolMessage 的人类
+    消息，如「方向：AI Agent；用途：学术期刊论文」）不是课题本身；拿它当
+    topic 会让管线给「回答本身」写报告。向上跳过所有回答，取真正的课题原文
+    （最新一条非回答的用户消息）。
+    """
+    for index in range(len(messages) - 1, -1, -1):
+        message = messages[index]
+        if not _is_visible_human(message):
+            continue
+        if index > 0 and _is_clarification_result(messages[index - 1]):
+            continue
+        text = " ".join(_message_text(message).split())
+        if text:
+            return text[:_MAX_TOPIC_CHARS]
     return "当前课题"
 
 
-def _as_report_call(tool_call: object, topic: str) -> dict[str, Any]:
+def extract_report_focus(messages: list[Any], topic: str = "") -> str:
+    """Join the user's clarification answers as the pipeline's ``focus``.
+
+    澄清回答（方向/类型/篇幅/语气等）不是课题本身，但正是写作要求；
+    topic 取课题原文的同时把它们汇总进 focus，管线才能按澄清后的
+    精确主题（如「LLM 的能力边界…」+ 观点评论型 + 3000-5000 字）成稿，
+    而不是只拿原始请求一句泛写。
+    """
+    parts: list[str] = []
+    for index, message in enumerate(messages):
+        if not _is_visible_human(message):
+            continue
+        if index == 0 or not _is_clarification_result(messages[index - 1]):
+            continue
+        text = " ".join(_message_text(message).split())
+        if text and text != topic:
+            parts.append(text)
+    return "；".join(parts).strip()[:_MAX_FOCUS_CHARS]
+
+
+def _as_report_call(tool_call: object, topic: str, focus: str = "") -> dict[str, Any]:
     call_id = str(_tool_field(tool_call, "id") or "")
+    args: dict[str, Any] = {"topic": topic}
+    if focus:
+        args["focus"] = focus
     return {
         "name": TOOL_NAME,
-        "args": {"topic": topic},
+        "args": args,
         "id": call_id,
         "type": "tool_call",
     }
@@ -267,11 +327,7 @@ def _sync_raw_tool_calls(last: AIMessage, kept: list[Any]) -> dict[str, Any]:
     additional_kwargs = dict(getattr(last, "additional_kwargs", {}) or {})
     raw_calls = additional_kwargs.get("tool_calls")
     kept_ids = _kept_call_ids(kept)
-    rewritten_by_id = {
-        str(_tool_field(call, "id") or ""): call
-        for call in kept
-        if _tool_field(call, "id")
-    }
+    rewritten_by_id = {str(_tool_field(call, "id") or ""): call for call in kept if _tool_field(call, "id")}
     if isinstance(raw_calls, list) and raw_calls:
         synced: list[Any] = []
         for item in raw_calls:
@@ -312,12 +368,14 @@ def rewrite_handwritten_report_calls(
     last: AIMessage,
     *,
     topic: str,
+    focus: str = "",
     pipeline_already_done: bool = False,
 ) -> AIMessage | None:
     """Rewrite or drop report deliverable tool calls.
 
     Before the pipeline has succeeded: rewrite the first hand-written report
-    write to ``deep_research_report`` and drop sibling presents.
+    write to ``deep_research_report`` (carrying ``topic`` + ``focus``) and drop
+    sibling presents.
 
     After it has succeeded: drop every pipeline / hand-written / present /
     report-reread call so the model cannot start another writing loop.
@@ -347,12 +405,10 @@ def rewrite_handwritten_report_calls(
             changed = True
             if redirected:
                 continue
-            rewritten.append(_as_report_call(call, topic))
+            rewritten.append(_as_report_call(call, topic, focus))
             redirected = True
             continue
-        if is_report_present_call(call) and (
-            has_pipeline or redirected or any(is_handwritten_report_call(item) for item in tool_calls)
-        ):
+        if is_report_present_call(call) and (has_pipeline or redirected or any(is_handwritten_report_call(item) for item in tool_calls)):
             changed = True
             continue
         rewritten.append(call)
@@ -371,10 +427,45 @@ def _messages_from_tool_request(request: ToolCallRequest) -> list[Any]:
 
 
 class WritingModeReportMiddleware(AgentMiddleware[AgentState]):
-    """Start the writing pipeline only when the model begins writing the Markdown file."""
+    """The first-report run's report only comes from ``deep_research_report``.
+
+    ``wrap_model_call`` 把 write_file / str_replace / bash 一并从模型绑定中
+    剥离（本中间件只在首报轮挂载）——after_model 的改写只能在整个模型响应
+    结束后触发，任何留在绑定里的写入口都会被弱模型用来先把全文起草进参数
+    （write_file 内容或 bash heredoc 命令），流式几十秒前端不可见后才被拦
+    截。bash 是唯一能写文件的执行类工具，剥离后模型没有任何可发起文件写
+    入的工具，交付只能直接调管线；幻觉出的调用仍由 after_model 改写/丢弃、
+    wrap_tool_call 拒绝兜底，管线成功后再写会被丢弃并保证一段收尾总结。
+    """
 
     state_schema = AgentState
 
+    @staticmethod
+    def _binding_tool_name(tool: Any) -> str:
+        if isinstance(tool, str):
+            return tool
+        return str(getattr(tool, "name", "") or "")
+
+    def _strip_handwrite_tools(self, request: ModelRequest) -> ModelRequest:
+        """Remove ``write_file`` / ``str_replace`` / ``bash`` from the model binding.
+
+        ``after_model`` 的改写只能在模型整个响应结束后触发，所以任何留在绑定里
+        的写入口都会被弱模型用来先把全文起草进参数（write_file 参数、bash
+        heredoc 命令），流式输出几十秒且前端不可见后才被拦截。bash 是唯一能
+        写文件的执行类工具，一并剥离后首报轮**不存在可发起文件写入的工具**，
+        交付只能直接调 ``deep_research_report``。ToolNode 仍持有全部工具；
+        模型幻觉出的调用由 after_model 改写/丢弃、wrap_tool_call 拒绝兜底。
+        """
+        tools = list(getattr(request, "tools", None) or [])
+        if not tools:
+            return request
+        excluded = _WRITE_TOOLS | {_BASH_TOOL}
+        removed = sorted({self._binding_tool_name(tool) for tool in tools if self._binding_tool_name(tool) in excluded})
+        if not removed:
+            return request
+        logger.info("Writing-mode first-report run: removed hand-write tools %s from model binding", removed)
+        return request.override(tools=[tool for tool in tools if self._binding_tool_name(tool) not in excluded])
+
     def _redirect_or_stop(self, state: AgentState) -> dict[str, Any] | None:
         messages = list(state.get("messages") or [])
         if not messages:
@@ -383,26 +474,38 @@ class WritingModeReportMiddleware(AgentMiddleware[AgentState]):
         if not isinstance(last, AIMessage):
             return None
         already_done = pipeline_already_succeeded(messages)
+        topic = extract_report_topic(messages)
         patched = rewrite_handwritten_report_calls(
             last,
-            topic=extract_report_topic(messages),
+            topic=topic,
+            focus=extract_report_focus(messages, topic),
             pipeline_already_done=already_done,
         )
         if patched is None:
             return None
         result: dict[str, Any] = {"messages": [patched]}
-        if already_done and not (patched.tool_calls or []):
-            if _already_nudged_summary(messages):
+        if already_done:
+            if not (patched.tool_calls or []):
+                if _already_nudged_summary(messages):
+                    logger.info("Writing-mode pipeline already succeeded; summary nudge ignored, ending turn")
+                    # 模型无视总结提示仍要继续读写：丢弃其调用后补一段兜底
+                    # 总结再结束，保证用户总能看到收尾消息而不是静默结束。
+                    if not _message_text(patched):
+                        patched = patched.model_copy(update={"content": _FALLBACK_SUMMARY})
+                        result["messages"] = [patched]
+                    result["jump_to"] = "end"
+                    return result
+                logger.info("Writing-mode pipeline already succeeded; dropping deliverable tools and nudging summary")
+                result["messages"] = [patched, _summary_nudge_message()]
+                result["jump_to"] = "model"
+        else:
+            redirected_names = sorted({_tool_name(call) for call in getattr(last, "tool_calls", None) or [] if is_handwritten_report_call(call)})
+            if redirected_names:
                 logger.info(
-                    "Writing-mode pipeline already succeeded; summary nudge ignored, ending turn"
+                    "Writing-mode: redirected hand-written report call(s) %s to %s",
+                    redirected_names,
+                    TOOL_NAME,
                 )
-                result["jump_to"] = "end"
-                return result
-            logger.info(
-                "Writing-mode pipeline already succeeded; dropping deliverable tools and nudging summary"
-            )
-            result["messages"] = [patched, _summary_nudge_message()]
-            result["jump_to"] = "model"
         return result
 
     def _reject_loop_tool(self, request: ToolCallRequest) -> ToolMessage | None:
@@ -427,6 +530,22 @@ class WritingModeReportMiddleware(AgentMiddleware[AgentState]):
     def after_model(self, state: AgentState, runtime: Runtime) -> dict[str, Any] | None:
         return self._redirect_or_stop(state)
 
+    @override
+    def wrap_model_call(
+        self,
+        request: ModelRequest,
+        handler: Callable[[ModelRequest], ModelResponse],
+    ) -> ModelCallResult:
+        return handler(self._strip_handwrite_tools(request))
+
+    @override
+    async def awrap_model_call(
+        self,
+        request: ModelRequest,
+        handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
+    ) -> ModelCallResult:
+        return await handler(self._strip_handwrite_tools(request))
+
     @hook_config(can_jump_to=["end", "model"])
     @override
     async def aafter_model(self, state: AgentState, runtime: Runtime) -> dict[str, Any] | None:
@@ -458,6 +577,7 @@ class WritingModeReportMiddleware(AgentMiddleware[AgentState]):
 __all__ = [
     "TOOL_NAME",
     "WritingModeReportMiddleware",
+    "extract_report_focus",
     "extract_report_topic",
     "is_handwritten_report_call",
     "is_post_success_loop_call",

offline-backend-20260512/backend/tests/test_writing_mode_report_middleware.py

@@ -0,0 +1,707 @@
+"""写作模式：仅在开始写 md 时改走 deep_research_report，且不强制 tool_choice。"""
+
+from __future__ import annotations
+
+from types import SimpleNamespace
+
+from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
+
+from deerflow.agents.middlewares.writing_mode_report_middleware import (
+    TOOL_NAME,
+    WritingModeReportMiddleware,
+    extract_report_focus,
+    extract_report_topic,
+    is_handwritten_report_call,
+    is_report_reread_call,
+    pipeline_already_succeeded,
+    rewrite_handwritten_report_calls,
+)
+from deerflow.tools.builtins.deep_research_report_tool import is_writing_mode_report_path
+
+
+def test_only_report_md_is_writing_mode_follow_up() -> None:
+    assert is_writing_mode_report_path("/mnt/user-data/outputs/report.md") is True
+    assert is_writing_mode_report_path("report.md") is True
+    assert is_writing_mode_report_path("/mnt/user-data/outputs/notes.md") is False
+    assert is_writing_mode_report_path("/mnt/user-data/outputs/analysis.markdown") is False
+    assert is_writing_mode_report_path("") is False
+    assert is_writing_mode_report_path(None) is False
+
+
+def test_handwritten_report_detects_outputs_markdown() -> None:
+    assert is_handwritten_report_call({"name": "write_file", "args": {"path": "/mnt/user-data/outputs/report.md"}, "id": "c1"})
+    assert is_handwritten_report_call({"name": "write_file", "args": {"path": "/mnt/user-data/outputs/analysis.md"}, "id": "c1"})
+    assert is_handwritten_report_call({"name": "str_replace", "args": {"path": "report.md"}, "id": "c1"})
+    assert not is_handwritten_report_call({"name": "write_file", "args": {"path": "/mnt/user-data/workspace/notes.md"}, "id": "c1"})
+    assert not is_handwritten_report_call({"name": "web_search", "args": {"query": "课题"}, "id": "c1"})
+
+
+def test_extract_topic_uses_latest_visible_user_text() -> None:
+    topic = extract_report_topic(
+        [
+            HumanMessage(content="旧课题"),
+            HumanMessage(content="hidden", additional_kwargs={"hide_from_ui": True}),
+            HumanMessage(content="写一份新能源汽车产业报告，重点看产能"),
+        ]
+    )
+    assert topic.startswith("写一份新能源汽车产业报告")
+
+
+def test_rewrite_write_file_to_pipeline() -> None:
+    last = AIMessage(
+        content="",
+        tool_calls=[
+            {
+                "id": "c1",
+                "name": "write_file",
+                "args": {"path": "/mnt/user-data/outputs/report.md", "content": "# 草稿"},
+                "type": "tool_call",
+            },
+            {
+                "id": "c2",
+                "name": "present_files",
+                "args": {"path": "/mnt/user-data/outputs/report.md"},
+                "type": "tool_call",
+            },
+        ],
+    )
+
+    patched = rewrite_handwritten_report_calls(last, topic="新能源汽车")
+
+    assert patched is not None
+    assert len(patched.tool_calls) == 1
+    assert patched.tool_calls[0]["name"] == TOOL_NAME
+    assert patched.tool_calls[0]["args"] == {"topic": "新能源汽车"}
+    assert patched.tool_calls[0]["id"] == "c1"
+
+
+def test_rewrite_keeps_existing_pipeline_and_drops_handwritten() -> None:
+    last = AIMessage(
+        content="",
+        tool_calls=[
+            {
+                "id": "c1",
+                "name": TOOL_NAME,
+                "args": {"topic": "课题"},
+                "type": "tool_call",
+            },
+            {
+                "id": "c2",
+                "name": "write_file",
+                "args": {"path": "/mnt/user-data/outputs/report.md", "content": "x"},
+                "type": "tool_call",
+            },
+        ],
+    )
+
+    patched = rewrite_handwritten_report_calls(last, topic="课题")
+
+    assert patched is not None
+    assert [call["name"] for call in patched.tool_calls] == [TOOL_NAME]
+
+
+def test_rewrite_leaves_chat_and_search_alone() -> None:
+    chat = AIMessage(content="先确认一下研究范围。")
+    assert rewrite_handwritten_report_calls(chat, topic="课题") is None
+
+    search = AIMessage(
+        content="",
+        tool_calls=[
+            {"id": "s1", "name": "web_search", "args": {"query": "课题"}, "type": "tool_call"},
+        ],
+    )
+    assert rewrite_handwritten_report_calls(search, topic="课题") is None
+
+    pipeline = AIMessage(
+        content="",
+        tool_calls=[
+            {"id": "c1", "name": TOOL_NAME, "args": {"topic": "课题"}, "type": "tool_call"},
+        ],
+    )
+    assert rewrite_handwritten_report_calls(pipeline, topic="课题") is None
+
+
+def test_middleware_allows_chat_before_writing() -> None:
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="先聊聊这个课题"),
+            AIMessage(content="好的，我们先明确范围。"),
+        ]
+    }
+    assert middleware.after_model(state, runtime=SimpleNamespace()) is None
+
+
+def test_middleware_rewrites_write_file_on_after_model() -> None:
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="写一份新能源汽车报告"),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "c1",
+                        "name": "write_file",
+                        "args": {"path": "/mnt/user-data/outputs/report.md", "content": "# 报告"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    }
+
+    update = middleware.after_model(state, runtime=SimpleNamespace())
+
+    assert update is not None
+    patched = update["messages"][0]
+    assert patched.tool_calls[0]["name"] == TOOL_NAME
+    assert patched.tool_calls[0]["args"]["topic"].startswith("写一份新能源汽车报告")
+
+
+def test_wrap_tool_call_rejects_handwritten_report() -> None:
+    middleware = WritingModeReportMiddleware()
+    request = SimpleNamespace(
+        tool_call={
+            "id": "c1",
+            "name": "write_file",
+            "args": {"path": "/mnt/user-data/outputs/report.md", "content": "x"},
+        }
+    )
+    called = {"handler": False}
+
+    def handler(_request):
+        called["handler"] = True
+        return ToolMessage(content="wrote", tool_call_id="c1", name="write_file")
+
+    result = middleware.wrap_tool_call(request, handler)
+
+    assert called["handler"] is False
+    assert isinstance(result, ToolMessage)
+    assert result.content.startswith("Error:")
+    assert TOOL_NAME in result.content
+
+
+def test_pipeline_success_is_detected() -> None:
+    messages = [
+        HumanMessage(content="写一份报告"),
+        AIMessage(
+            content="",
+            tool_calls=[{"id": "c1", "name": TOOL_NAME, "args": {"topic": "课题"}, "type": "tool_call"}],
+        ),
+        ToolMessage(content="研究报告已完成：已写入 report.md。", tool_call_id="c1", name=TOOL_NAME),
+    ]
+    assert pipeline_already_succeeded(messages) is True
+    assert pipeline_already_succeeded(messages[:-1]) is False
+    failed = [
+        *messages[:-1],
+        ToolMessage(content="Error: 深度研究报告生成失败。", tool_call_id="c1", name=TOOL_NAME),
+    ]
+    assert pipeline_already_succeeded(failed) is False
+
+
+def test_reread_detects_outputs_markdown() -> None:
+    assert is_report_reread_call({"name": "read_file", "args": {"path": "/mnt/user-data/outputs/report.md"}, "id": "c1"})
+    assert is_report_reread_call({"name": "read_file", "args": {"path": "/mnt/user-data/outputs/ai-agents-paper.md"}, "id": "c1"})
+    assert not is_report_reread_call({"name": "read_file", "args": {"path": "/mnt/user-data/workspace/notes.md"}, "id": "c1"})
+    assert not is_report_reread_call({"name": "write_file", "args": {"path": "/mnt/user-data/outputs/report.md"}, "id": "c1"})
+
+
+def test_rewrite_after_success_drops_deliverable_tools() -> None:
+    last = AIMessage(
+        content="我再重写一版",
+        tool_calls=[
+            {
+                "id": "c2",
+                "name": "write_file",
+                "args": {"path": "/mnt/user-data/outputs/ai-agents-paper.md", "content": "# 新稿"},
+                "type": "tool_call",
+            },
+            {
+                "id": "c3",
+                "name": TOOL_NAME,
+                "args": {"topic": "课题"},
+                "type": "tool_call",
+            },
+        ],
+    )
+
+    patched = rewrite_handwritten_report_calls(last, topic="课题", pipeline_already_done=True)
+
+    assert patched is not None
+    assert patched.tool_calls == []
+
+
+def test_rewrite_after_success_drops_reread() -> None:
+    last = AIMessage(
+        content="先看看报告",
+        tool_calls=[
+            {
+                "id": "c2",
+                "name": "read_file",
+                "args": {"path": "/mnt/user-data/outputs/report.md"},
+                "type": "tool_call",
+            }
+        ],
+    )
+
+    patched = rewrite_handwritten_report_calls(last, topic="课题", pipeline_already_done=True)
+
+    assert patched is not None
+    assert patched.tool_calls == []
+    assert patched.content == ""
+
+
+def test_middleware_nudges_summary_after_successful_pipeline() -> None:
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="写一份新能源汽车报告"),
+            AIMessage(
+                content="",
+                tool_calls=[{"id": "c1", "name": TOOL_NAME, "args": {"topic": "课题"}, "type": "tool_call"}],
+            ),
+            ToolMessage(content="研究报告已完成：已写入 report.md。", tool_call_id="c1", name=TOOL_NAME),
+            AIMessage(
+                content="报告太泛化，我要重写",
+                tool_calls=[
+                    {
+                        "id": "c2",
+                        "name": "write_file",
+                        "args": {"path": "/mnt/user-data/outputs/ai-agents-paper.md", "content": "# 重写"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    }
+
+    update = middleware.after_model(state, runtime=SimpleNamespace())
+
+    assert update is not None
+    assert update["jump_to"] == "model"
+    assert update["messages"][0].tool_calls == []
+    assert update["messages"][0].content == ""
+    nudge = update["messages"][1]
+    assert nudge.additional_kwargs["hide_from_ui"] is True
+    assert nudge.additional_kwargs["writing_mode_summary_nudge"] is True
+    assert "2-3" in nudge.content
+
+
+def test_middleware_ends_turn_after_ignored_summary_nudge() -> None:
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="写一份新能源汽车报告"),
+            AIMessage(
+                content="",
+                tool_calls=[{"id": "c1", "name": TOOL_NAME, "args": {"topic": "课题"}, "type": "tool_call"}],
+            ),
+            ToolMessage(content="研究报告已完成：已写入 report.md。", tool_call_id="c1", name=TOOL_NAME),
+            HumanMessage(
+                content="请总结",
+                additional_kwargs={"hide_from_ui": True, "writing_mode_summary_nudge": True},
+            ),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "c2",
+                        "name": "read_file",
+                        "args": {"path": "/mnt/user-data/outputs/report.md"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    }
+
+    update = middleware.after_model(state, runtime=SimpleNamespace())
+
+    assert update is not None
+    assert update["jump_to"] == "end"
+    assert update["messages"][0].tool_calls == []
+
+
+def test_wrap_tool_call_rejects_rerun_after_success() -> None:
+    middleware = WritingModeReportMiddleware()
+    prior = [
+        HumanMessage(content="写一份报告"),
+        AIMessage(
+            content="",
+            tool_calls=[{"id": "c1", "name": TOOL_NAME, "args": {"topic": "课题"}, "type": "tool_call"}],
+        ),
+        ToolMessage(content="研究报告已完成：已写入 report.md。", tool_call_id="c1", name=TOOL_NAME),
+    ]
+    request = SimpleNamespace(
+        tool_call={"id": "c2", "name": TOOL_NAME, "args": {"topic": "课题"}},
+        state={"messages": prior},
+    )
+    called = {"handler": False}
+
+    def handler(_request):
+        called["handler"] = True
+        return ToolMessage(content="ran", tool_call_id="c2", name=TOOL_NAME)
+
+    result = middleware.wrap_tool_call(request, handler)
+
+    assert called["handler"] is False
+    assert isinstance(result, ToolMessage)
+    assert result.content.startswith("Error:")
+    assert "已经完成" in result.content
+    assert "请立即调用" not in result.content
+
+
+def test_wrap_tool_call_rejects_reread_after_success() -> None:
+    middleware = WritingModeReportMiddleware()
+    prior = [
+        HumanMessage(content="写一份报告"),
+        AIMessage(
+            content="",
+            tool_calls=[{"id": "c1", "name": TOOL_NAME, "args": {"topic": "课题"}, "type": "tool_call"}],
+        ),
+        ToolMessage(content="研究报告已完成：已写入 report.md。", tool_call_id="c1", name=TOOL_NAME),
+    ]
+    request = SimpleNamespace(
+        tool_call={
+            "id": "c2",
+            "name": "read_file",
+            "args": {"path": "/mnt/user-data/outputs/report.md"},
+        },
+        state={"messages": prior},
+    )
+    called = {"handler": False}
+
+    def handler(_request):
+        called["handler"] = True
+        return ToolMessage(content="read", tool_call_id="c2", name="read_file")
+
+    result = middleware.wrap_tool_call(request, handler)
+
+    assert called["handler"] is False
+    assert isinstance(result, ToolMessage)
+    assert result.content.startswith("Error:")
+    assert "已经完成" in result.content
+
+
+def test_wrap_tool_call_allows_unrelated_writes() -> None:
+    middleware = WritingModeReportMiddleware()
+    request = SimpleNamespace(
+        tool_call={
+            "id": "c1",
+            "name": "write_file",
+            "args": {"path": "/mnt/user-data/workspace/notes.md", "content": "x"},
+        }
+    )
+    expected = ToolMessage(content="wrote", tool_call_id="c1", name="write_file")
+
+    result = middleware.wrap_tool_call(request, lambda _request: expected)
+
+    assert result is expected
+
+
+def test_extract_topic_skips_clarification_answers() -> None:
+    """澄清回答不是课题：向上取真正的写作请求原文。"""
+    topic = extract_report_topic(
+        [
+            HumanMessage(content="写人工智能领域的论文md"),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "q1",
+                        "name": "ask_clarification",
+                        "args": {"question": "方向？"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+            ToolMessage(content="需要澄清：方向？", tool_call_id="q1", name="ask_clarification"),
+            HumanMessage(content="方向：AI Agent；用途：学术期刊论文；篇幅：短篇2000-4000字"),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "c1",
+                        "name": "write_file",
+                        "args": {"path": "/mnt/user-data/outputs/report.md"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    )
+    assert topic.startswith("写人工智能领域的论文md")
+
+
+def test_bash_heredoc_write_is_redirected_to_pipeline() -> None:
+    """模型被剥离不了工具时会绕道 bash heredoc 手写报告——同样改写为管线。"""
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="写人工智能领域的论文md"),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "b1",
+                        "name": "bash",
+                        "args": {"command": "cat > /mnt/user-data/outputs/report.md << 'ENDOFFILE'\n# 报告全文……\nENDOFFILE"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    }
+
+    update = middleware.after_model(state, runtime=SimpleNamespace())
+
+    assert update is not None
+    patched = update["messages"][0]
+    assert patched.tool_calls[0]["name"] == TOOL_NAME
+    assert patched.tool_calls[0]["args"]["topic"].startswith("写人工智能领域的论文md")
+
+
+def test_bash_python_open_write_is_redirected_to_pipeline() -> None:
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="写一份新能源汽车报告"),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "b2",
+                        "name": "bash",
+                        "args": {"command": ("python3 << 'PYEOF'\ncontent = r'''# 报告'''\nwith open('/mnt/user-data/outputs/report.md', 'w', encoding='utf-8') as f:\n    f.write(content)\nPYEOF")},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    }
+
+    update = middleware.after_model(state, runtime=SimpleNamespace())
+
+    assert update is not None
+    patched = update["messages"][0]
+    assert patched.tool_calls[0]["name"] == TOOL_NAME
+
+
+def test_bash_readonly_and_non_outputs_commands_are_left_alone() -> None:
+    """mkdir / wc / cat 读取、非 outputs 的 .md 写入都不是手写报告。"""
+    middleware = WritingModeReportMiddleware()
+    for command in (
+        "mkdir -p /mnt/user-data/outputs",
+        "wc -m /mnt/user-data/outputs/report.md",
+        "cat /mnt/user-data/outputs/report.md",
+        "echo hi > /tmp/scratch.md",
+    ):
+        state = {
+            "messages": [
+                HumanMessage(content="写一份报告"),
+                AIMessage(
+                    content="",
+                    tool_calls=[{"id": "b3", "name": "bash", "args": {"command": command}, "type": "tool_call"}],
+                ),
+            ]
+        }
+        assert middleware.after_model(state, runtime=SimpleNamespace()) is None, command
+
+
+def test_bash_write_after_success_is_dropped() -> None:
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="写一份报告"),
+            AIMessage(
+                content="",
+                tool_calls=[{"id": "c1", "name": TOOL_NAME, "args": {"topic": "课题"}, "type": "tool_call"}],
+            ),
+            ToolMessage(content="研究报告已完成：基于 3 条资料…", tool_call_id="c1", name=TOOL_NAME),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "b4",
+                        "name": "bash",
+                        "args": {"command": "echo '# 新版' > /mnt/user-data/outputs/report.md"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    }
+
+    update = middleware.after_model(state, runtime=SimpleNamespace())
+
+    assert update is not None
+    patched = update["messages"][0]
+    assert patched.tool_calls == []
+    nudged = update["messages"][1]
+    assert getattr(nudged, "additional_kwargs", {}).get("writing_mode_summary_nudge") is True
+
+
+def test_wrap_tool_call_rejects_bash_report_write() -> None:
+    """漏网到执行层的 bash 手写（如裸 report.md 重定向）也要拒绝并引导走管线。"""
+    middleware = WritingModeReportMiddleware()
+    request = SimpleNamespace(
+        tool_call={
+            "id": "b5",
+            "name": "bash",
+            "args": {"command": "cat > report.md << 'EOF'\n# x\nEOF"},
+        }
+    )
+    called = {"handler": False}
+
+    def handler(_request):
+        called["handler"] = True
+        return ToolMessage(content="ran", tool_call_id="b5", name="bash")
+
+    result = middleware.wrap_tool_call(request, handler)
+
+    assert called["handler"] is False
+    assert isinstance(result, ToolMessage)
+    assert result.content.startswith("Error:")
+    assert TOOL_NAME in result.content
+
+
+def test_wrap_model_call_strips_handwrite_tools_from_binding() -> None:
+    """首报轮从模型绑定中剥离 write_file/str_replace/bash——bash 是唯一能写
+    文件的执行类工具（实测模型会把全文起草进 heredoc 参数流式几十秒后才被
+    after_model 拦截），剥离后模型没有任何可发起文件写入的工具。"""
+    middleware = WritingModeReportMiddleware()
+
+    def make_request(tools):
+        return SimpleNamespace(
+            tools=tools,
+            override=lambda **kwargs: SimpleNamespace(tools=kwargs.get("tools", [])),
+        )
+
+    seen: dict[str, list] = {}
+
+    def handler(request):
+        seen["tools"] = list(request.tools)
+        return SimpleNamespace()
+
+    middleware.wrap_model_call(
+        make_request(
+            [
+                SimpleNamespace(name="write_file"),
+                SimpleNamespace(name="web_search"),
+                SimpleNamespace(name="str_replace"),
+                SimpleNamespace(name="bash"),
+                SimpleNamespace(name=TOOL_NAME),
+            ]
+        ),
+        handler,
+    )
+
+    assert [getattr(t, "name", "") for t in seen["tools"]] == ["web_search", TOOL_NAME]
+
+
+def test_wrap_model_call_passes_through_when_no_handwrite_tools() -> None:
+    middleware = WritingModeReportMiddleware()
+    request = SimpleNamespace(
+        tools=[SimpleNamespace(name="web_search"), SimpleNamespace(name=TOOL_NAME)],
+        override=lambda **kwargs: SimpleNamespace(tools=kwargs.get("tools", [])),
+    )
+
+    def handler(passed):
+        assert passed is request
+        return "unchanged"
+
+    assert middleware.wrap_model_call(request, handler) == "unchanged"
+
+
+def test_extract_focus_joins_clarification_answers() -> None:
+    focus = extract_report_focus(
+        [
+            HumanMessage(content="写人工智能领域的论文md"),
+            AIMessage(
+                content="",
+                tool_calls=[{"id": "q1", "name": "ask_clarification", "args": {"question": "方向？"}, "type": "tool_call"}],
+            ),
+            ToolMessage(content="需要澄清", tool_call_id="q1", name="ask_clarification"),
+            HumanMessage(content="主题：LLM的能力边界；类型：观点评论型"),
+        ],
+        topic="写人工智能领域的论文md",
+    )
+    assert "LLM的能力边界" in focus
+    assert "观点评论型" in focus
+    assert "写人工智能领域的论文md" not in focus
+
+
+def test_rewrite_carries_focus_from_clarification_answers() -> None:
+    """改写进管线的调用要带上澄清回答（方向/类型/篇幅），否则管线只拿到
+    原始请求一句泛写。"""
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="写人工智能领域的论文md，有不懂的可以问我"),
+            AIMessage(
+                content="",
+                tool_calls=[{"id": "q1", "name": "ask_clarification", "args": {"question": "主题？"}, "type": "tool_call"}],
+            ),
+            ToolMessage(content="需要澄清", tool_call_id="q1", name="ask_clarification"),
+            HumanMessage(content="主题：LLM的能力边界；篇幅：3000-5000字"),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "c1",
+                        "name": "bash",
+                        "args": {"command": "cat > /mnt/user-data/outputs/report.md << 'EOF'\n# x\nEOF"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    }
+
+    update = middleware.after_model(state, runtime=SimpleNamespace())
+
+    assert update is not None
+    patched = update["messages"][0]
+    assert patched.tool_calls[0]["name"] == TOOL_NAME
+    assert patched.tool_calls[0]["args"]["topic"].startswith("写人工智能领域的论文md")
+    assert "LLM的能力边界" in patched.tool_calls[0]["args"]["focus"]
+
+
+def test_second_offense_after_nudge_gets_fallback_summary() -> None:
+    """模型无视总结提示仍要继续：丢弃调用后必须留一段兜底总结，不能静默结束。"""
+    middleware = WritingModeReportMiddleware()
+    state = {
+        "messages": [
+            HumanMessage(content="写一份新能源汽车报告"),
+            AIMessage(
+                content="",
+                tool_calls=[{"id": "c1", "name": TOOL_NAME, "args": {"topic": "课题"}, "type": "tool_call"}],
+            ),
+            ToolMessage(content="研究报告已完成：已写入 report.md。", tool_call_id="c1", name=TOOL_NAME),
+            HumanMessage(
+                content="请总结",
+                additional_kwargs={"hide_from_ui": True, "writing_mode_summary_nudge": True},
+            ),
+            AIMessage(
+                content="",
+                tool_calls=[
+                    {
+                        "id": "c2",
+                        "name": "read_file",
+                        "args": {"path": "/mnt/user-data/outputs/report.md"},
+                        "type": "tool_call",
+                    }
+                ],
+            ),
+        ]
+    }
+
+    update = middleware.after_model(state, runtime=SimpleNamespace())
+
+    assert update is not None
+    assert update["jump_to"] == "end"
+    patched = update["messages"][0]
+    assert patched.tool_calls == []
+    assert "report.md" in patched.content
+    assert "已完成" in patched.content

offline-backend-20260512/backend/tests/test_writing_rewrite_prompt.py

@@ -0,0 +1,166 @@
+"""Unit tests for the AI 改写 prompt builder (app.gateway.routers.writing).
+
+Focus: the 仿写 (imitate) action injects the reference sample into the prompt,
+and existing actions are unaffected.
+"""
+
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+from app.gateway.routers.writing import (
+    _REFERENCE_MAX_CHARS,
+    RewriteRequest,
+    SelectionInfo,
+    _release_document_rewrite,
+    _reserve_document_rewrite,
+    build_rewrite_messages,
+)
+
+
+def _req(**kwargs) -> RewriteRequest:
+    base = {
+        "selection": SelectionInfo(**{"from": 0, "to": 4, "text": "原始文字"}),
+    }
+    base.update(kwargs)
+    return RewriteRequest(**base)
+
+
+def test_imitate_injects_reference_text():
+    body = _req(action="imitate", reference_text="这是一段范文，节奏明快，排比有力。")
+    action, messages = build_rewrite_messages(body)
+
+    assert action == "imitate"
+    human = messages[1].content
+    assert "范文" in human
+    assert "这是一段范文，节奏明快，排比有力。" in human
+    assert "原始文字" in human
+
+
+def test_imitate_without_reference_has_no_reference_block():
+    body = _req(action="imitate", reference_text="   ")
+    action, messages = build_rewrite_messages(body)
+
+    assert action == "imitate"
+    # No reference → the 范文 block is not appended
+    assert "【范文】" not in messages[1].content
+
+
+def test_imitate_reference_is_truncated():
+    long_ref = "甲" * (_REFERENCE_MAX_CHARS + 500)
+    body = _req(action="imitate", reference_text=long_ref)
+    _, messages = build_rewrite_messages(body)
+
+    human = messages[1].content
+    # The reference is capped — the 500 extra chars are dropped
+    assert human.count("甲") == _REFERENCE_MAX_CHARS
+
+
+def test_polish_action_unaffected_by_reference_field():
+    # A stray reference_text on a non-imitate action must be ignored
+    body = _req(action="polish", reference_text="不应出现的范文")
+    action, messages = build_rewrite_messages(body)
+
+    assert action == "polish"
+    assert "范文" not in messages[1].content
+    assert "不应出现的范文" not in messages[1].content
+
+
+def test_unknown_action_falls_back_to_polish():
+    body = _req(action="not-a-real-action")
+    action, _ = build_rewrite_messages(body)
+    assert action == "polish"
+
+
+def test_imitate_follow_up_preserves_reference_and_previous_result():
+    body = _req(
+        action="imitate",
+        reference_text="范文样例",
+        previous_result="上一版仿写结果",
+        follow_up_instruction="再正式一点",
+    )
+    _, messages = build_rewrite_messages(body)
+
+    # system, human(original w/ reference), ai(previous), human(follow-up)
+    assert len(messages) == 4
+    assert "范文样例" in messages[1].content
+    assert messages[2].content == "上一版仿写结果"
+    assert messages[3].content == "再正式一点"
+
+
+@pytest.mark.asyncio
+async def test_full_document_rewrite_reservation_rejects_a_second_live_request(tmp_path: Path):
+    """Two streams must never generate competing commits for one real file."""
+    path = tmp_path / "report.md"
+    path.write_text("# report", encoding="utf-8")
+
+    assert await _reserve_document_rewrite(path) is True
+    try:
+        assert await _reserve_document_rewrite(path) is False
+    finally:
+        await _release_document_rewrite(path)
+
+    assert await _reserve_document_rewrite(path) is True
+    await _release_document_rewrite(path)
+
+
+@pytest.mark.asyncio
+async def test_full_document_rewrite_keeps_committed_file_when_undo_snapshot_fails(
+    monkeypatch,
+    tmp_path: Path,
+):
+    """Undo persistence is best effort and must not restore a valid rewrite."""
+    from app.gateway.routers import writing
+
+    path = tmp_path / "report.md"
+    path.write_text("# 原文\n\n正文", encoding="utf-8")
+
+    class _Model:
+        async def astream(self, *_args, **_kwargs):
+            yield "# 改写后\n\n新正文"
+
+    class _BrokenVersionStore:
+        async def create(self, **_kwargs):
+            raise RuntimeError("version store unavailable")
+
+    class _Config:
+        models: list[object] = []
+
+        @staticmethod
+        def get_model_config(_name):
+            return None
+
+    async def resolve_path(*_args):
+        return path
+
+    async def current_user(*_args):
+        return "user-a"
+
+    async def requirements(*_args, **_kwargs):
+        yield "保留事实。"
+
+    monkeypatch.setattr(writing, "aresolve_thread_virtual_path", resolve_path)
+    monkeypatch.setattr(writing, "get_current_user", current_user)
+    monkeypatch.setattr(writing, "create_chat_model", lambda **_kwargs: _Model())
+    monkeypatch.setattr(writing, "_astream_rewrite_requirements", requirements)
+    monkeypatch.setattr(writing, "_extract_chunk_parts", lambda chunk: ("", chunk))
+    response = await writing.rewrite_document(
+        body=writing.DocumentRewriteRequest(
+            threadId="thread-a",
+            path="/mnt/user-data/report.md",
+            instruction="统一表达风格",
+        ),
+        request=SimpleNamespace(
+            _deerflow_test_bypass_auth=True,
+            app=SimpleNamespace(state=SimpleNamespace(document_rewrite_version_store=_BrokenVersionStore())),
+        ),
+        config=_Config(),
+    )
+
+    events = "".join([frame async for frame in response.body_iterator])
+
+    assert path.read_text(encoding="utf-8") == "# 改写后\n\n新正文"
+    assert "event: committed" in events
+    assert '"versionSnapshotFailed": true' in events
+    assert "event: error" not in events