fix: writing mode uses chat search then pipeline write only

Keep deep_research_report as a write-only deliverable from conversation materials, block post-success rewrite loops with a summary nudge, fill thin/empty pools from model knowledge, and open the sandbox only on real report.md content. Co-authored-by: Cursor <cursoragent@cursor.com>
2026-08-30 12:41:04 +08:00
1 parent 9afb9750e5
commit 49c01cb72b
@@ -1,5 +1,5 @@
-import hashlib
-import logging
+import hashlib
+import logging

 from langchain.agents import create_agent
 from langchain.agents.middleware import AgentMiddleware
@@ -38,45 +38,45 @@ logger = logging.getLogger(__name__)
 # 写作配置 Q&A 现在「先生成大纲并与用户多轮确认 → 再提交配置」，需要更多来回，故上限放宽。
 # 仍是兜底安全阀：到顶才用 tool_choice 强制提交，正常流程由用户确认大纲后自然提交。
 WRITING_SETUP_MAX_ROUNDS = 8
-REPORT_STRUCTURE_SETUP_MAX_ROUNDS = 8
-
-_ES_QUERY_ROUTING_OPEN_TAG = '<skill_routing skill="es_query">'
-
-
-def _log_es_query_routing_registration(
-    *,
-    system_prompt: str,
-    app_config: AppConfig,
-    agent_id: str | None,
-    available_skills: set[str] | None,
-) -> None:
-    """Log whether the exact configured ES routing block reached this Q&A prompt."""
-    routing = app_config.skills.es_query_routing
-    configured_prompt = (routing.prompt or "").strip()
-    expected_block = (
-        f"{_ES_QUERY_ROUTING_OPEN_TAG}\n{configured_prompt}\n</skill_routing>"
-        if configured_prompt
-        else ""
-    )
-    eligible = available_skills is None or "es_query" in available_skills
-    registered = bool(expected_block) and expected_block in system_prompt
-    fingerprint = (
-        hashlib.sha256(configured_prompt.encode("utf-8")).hexdigest()[:12]
-        if configured_prompt
-        else "-"
-    )
-
-    log = logger.info if registered or not routing.enabled or not eligible else logger.warning
-    log(
-        "ES query routing prompt registration: agent_id=%s enabled=%s eligible=%s "
-        "registered=%s prompt_chars=%d prompt_sha256=%s",
-        agent_id or "default",
-        routing.enabled,
-        eligible,
-        registered,
-        len(configured_prompt),
-        fingerprint,
-    )
+REPORT_STRUCTURE_SETUP_MAX_ROUNDS = 8
+
+_ES_QUERY_ROUTING_OPEN_TAG = '<skill_routing skill="es_query">'
+
+
+def _log_es_query_routing_registration(
+    *,
+    system_prompt: str,
+    app_config: AppConfig,
+    agent_id: str | None,
+    available_skills: set[str] | None,
+) -> None:
+    """Log whether the exact configured ES routing block reached this Q&A prompt."""
+    routing = app_config.skills.es_query_routing
+    configured_prompt = (routing.prompt or "").strip()
+    expected_block = (
+        f"{_ES_QUERY_ROUTING_OPEN_TAG}\n{configured_prompt}\n</skill_routing>"
+        if configured_prompt
+        else ""
+    )
+    eligible = available_skills is None or "es_query" in available_skills
+    registered = bool(expected_block) and expected_block in system_prompt
+    fingerprint = (
+        hashlib.sha256(configured_prompt.encode("utf-8")).hexdigest()[:12]
+        if configured_prompt
+        else "-"
+    )
+
+    log = logger.info if registered or not routing.enabled or not eligible else logger.warning
+    log(
+        "ES query routing prompt registration: agent_id=%s enabled=%s eligible=%s "
+        "registered=%s prompt_chars=%d prompt_sha256=%s",
+        agent_id or "default",
+        routing.enabled,
+        eligible,
+        registered,
+        len(configured_prompt),
+        fingerprint,
+    )


 def _get_runtime_config(config: RunnableConfig) -> dict:
@@ -426,6 +426,18 @@ def _build_middlewares(
    if agent_name == FORCED_RESEARCH_AGENT_ID:
        middlewares.append(ForcedResearchMiddleware())

+    # 写作模式首轮：允许先聊/检索；只有模型开始写 md 时才改走 deep_research_report。
+    # 不设 tool_choice——thinking 模式的兼容接口会 400。
+    writing_mode = bool(cfg.get("writing_mode", False))
+    writing_artifact_path = cfg.get("writing_artifact_path") if writing_mode else None
+    if writing_mode:
+        from deerflow.tools.builtins.deep_research_report_tool import is_writing_mode_report_path
+
+        if not is_writing_mode_report_path(writing_artifact_path if isinstance(writing_artifact_path, str) else None):
+            from deerflow.agents.middlewares.writing_mode_report_middleware import WritingModeReportMiddleware
+
+            middlewares.append(WritingModeReportMiddleware())
+
    # LoopDetectionMiddleware — detect and break repetitive tool call loops
    middlewares.append(LoopDetectionMiddleware())

@@ -517,6 +529,12 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
    writing_artifact_path = cfg.get("writing_artifact_path") if writing_mode else None
    if not isinstance(writing_artifact_path, str) or not writing_artifact_path.strip():
        writing_artifact_path = None
+    # 只有写作模式产物 report.md 才走续写；其它 leftover .md 不得跳过管线。
+    if writing_artifact_path is not None:
+        from deerflow.tools.builtins.deep_research_report_tool import is_writing_mode_report_path
+
+        if not is_writing_mode_report_path(writing_artifact_path):
+            writing_artifact_path = None
    agent_id = validate_agent_id(cfg.get("agent_id") or cfg.get("agent_name"))
    requested_excluded_tools = cfg.get("excluded_tools") or None

@@ -691,10 +709,10 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
        from deerflow.tools.builtins.notebook_search_tool import notebook_search_tool

        default_tools = [notebook_search_tool] + default_tools
-    # 写作模式首轮（尚无 md 产物）：挂深度研究报告工具，报告由管线生成而非
-    # 模型手工 write_file。续写轮（已有 writing_artifact_path）不挂，保持
-    # 原有「直接编辑该文件」行为。不受 tool_groups/excluded_tools 过滤——
-    # 它是写作模式合约的核心交付手段。
+    # 写作模式首轮（尚无 report.md）：挂深度研究报告工具，报告由管线生成而非
+    # 模型手工 write_file。续写轮（已有 report.md）不挂，保持原有「直接编辑
+    # 该文件」行为。不受 tool_groups/excluded_tools 过滤——它是写作模式合约
+    # 的核心交付手段。
    if writing_mode and not writing_artifact_path:
        from deerflow.tools.builtins.deep_research_report_tool import deep_research_report_tool

@@ -726,8 +744,8 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
            writing_mode=writing_mode,
            writing_artifact_path=writing_artifact_path,
        )
-    else:
-        system_prompt = apply_prompt_template(
+    else:
+        system_prompt = apply_prompt_template(
            subagent_enabled=subagent_enabled,
            max_concurrent_subagents=max_concurrent_subagents,
            agent_id=agent_id,
@@ -737,20 +755,20 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
            available_skills=prompt_available_skills,
            app_config=resolved_app_config,
            memory_injection_enabled=memory_injection_enabled,
-            rag_mode_enabled=rag_mode_enabled,
-            is_notebook_mode=is_notebook_mode,
-            notebook_source_ids=notebook_source_ids,
-            is_scheduled_run=bool(cfg.get("is_scheduled_run", False)),
-        )
-
-    _log_es_query_routing_registration(
-        system_prompt=system_prompt,
-        app_config=resolved_app_config,
-        agent_id=agent_id,
-        available_skills=prompt_available_skills,
-    )
-
-    return create_agent(
+            rag_mode_enabled=rag_mode_enabled,
+            is_notebook_mode=is_notebook_mode,
+            notebook_source_ids=notebook_source_ids,
+            is_scheduled_run=bool(cfg.get("is_scheduled_run", False)),
+        )
+
+    _log_es_query_routing_registration(
+        system_prompt=system_prompt,
+        app_config=resolved_app_config,
+        agent_id=agent_id,
+        available_skills=prompt_available_skills,
+    )
+
+    return create_agent(
        model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled, reasoning_effort=reasoning_effort, force_disable_thinking=thinking_force_disabled, app_config=resolved_app_config),
        tools=default_tools,
        middleware=_build_middlewares(config, model_name=model_name, agent_name=agent_id, app_config=resolved_app_config),