feat(turbo): add direct LLM chat mode with runtime toggle

Add 极速 mode that streams via /api/direct-chat without the lead agent stack, plus VITE_TURBO_MODE_VISIBLE in runtime-config.js (default off). Also disable global memory, tighten Qwen/vLLM thinking control for flash mode, and force thinking off on the direct-chat endpoint. Co-authored-by: Cursor <cursoragent@cursor.com>
2026-09-09 21:58:36 +08:00
1 parent 4f7f07504a
commit d765afe2ac
@@ -59,6 +59,9 @@
 # 简介模式左侧菜单类型：与菜单管理页「简介模式」的类型 A / B 对应。两套网页分别填 A 或 B。
 # 不填或留空时按类型 A，继续使用原来的简介菜单数据。
 # VITE_COMPACT_MENU_TYPE=A
+# 问答页「极速」模式：true=在模式菜单显示并直连大模型；false 或未设=隐藏。
+# 部署后优先改 dist/runtime-config.js 的 VITE_TURBO_MODE_VISIBLE，刷新即可。
+# VITE_TURBO_MODE_VISIBLE=false
 # VITE_GITHUB_OAUTH_TOKEN=

 # --- 官方 DeerFlow 风格页面入口（仅 Vite，不引入 Next.js）---
@@ -151,6 +151,11 @@ window.__CM_RUNTIME_CONFIG__ = {
  // GitHub OAuth Token；不使用 GitHub 相关能力时留空。
  VITE_GITHUB_OAUTH_TOKEN: "",

+  // 是否在问答输入框「模式」菜单显示「极速」："true" 显示，"false" 隐藏。
+  // 默认关闭。开启后可直连大模型流式问答，不走智能体工具与技能。
+  // 部署后改 dist/runtime-config.js 再刷新页面即可，无需重新打包。
+  VITE_TURBO_MODE_VISIBLE: "true",
+
  // 是否在智能体管理页显示「舆情分析」类型："true" 显示，"false" 隐藏。
  // 关闭后，该智能体的专用对话地址也会自动跳回智能体管理页。
  VITE_SENTIMENT_AGENT_VISIBLE: "true",
@@ -7,6 +7,7 @@ import {
  CheckIcon,
  FileTextIcon,
  FolderTreeIcon,
+  GaugeIcon,
  GraduationCapIcon,
  LightbulbIcon,
  PaperclipIcon,
@@ -68,6 +69,7 @@ import { isHiddenFromUIMessage } from "@/core/messages/utils";
 import { useModels } from "@/core/models/hooks";
 import type { Model } from "@/core/models/types";
 import type { AgentThreadContext } from "@/core/threads";
+import { isTurboModeVisible } from "@/core/threads/use-direct-chat";
 import { textOfMessage } from "@/core/threads/utils";
 import { desensitize } from "@/lib/desensitize";
 import { cn } from "@/lib/utils";
@@ -223,7 +225,11 @@ export function InputBox({
    context.execution_profile === "single_round_rag";
  const multiRoundRagActive =
    context.execution_profile === "multi_round_rag";
+  const turboModeVisible = isTurboModeVisible();
+  const directChatActive =
+    turboModeVisible && context.execution_profile === "direct";
  const frontendRagActive = singleRoundRagActive || multiRoundRagActive;
+  const bypassAgentActive = frontendRagActive || directChatActive;
  const modelOptions = useMemo(() => {
    return singleRoundRagActive ? extraModels : models;
  }, [extraModels, models, singleRoundRagActive]);
@@ -253,11 +259,37 @@ export function InputBox({
    recommendedQuestions.length > 0;

  useEffect(() => {
-    // Multi-round RAG is a frontend execution profile, not a model option.
-    // Do not let the normal model fallback clear it on every render.
+    // Frontend-only execution profiles are not model options.
+    // Do not let the normal model fallback clear them on every render.
+    if (!turboModeVisible && context.execution_profile === "direct") {
+      onContextChange?.({
+        ...context,
+        execution_profile: undefined,
+      });
+      return;
+    }
    if (multiRoundRagActive) {
      return;
    }
+    if (directChatActive) {
+      if (models.length === 0) {
+        return;
+      }
+      const currentModel = models.find((m) => m.name === context.model_name);
+      const fallbackModel = currentModel ?? models[0]!;
+      if (
+        context.model_name === fallbackModel.name &&
+        context.execution_profile === "direct"
+      ) {
+        return;
+      }
+      onContextChange?.({
+        ...context,
+        model_name: fallbackModel.name,
+        execution_profile: "direct",
+      });
+      return;
+    }
    if (modelOptions.length === 0) {
      return;
    }
@@ -281,7 +313,7 @@ export function InputBox({
      mode: nextMode,
      execution_profile: fallbackModel.execution_profile,
    });
-  }, [context, modelOptions, multiRoundRagActive, onContextChange]);
+  }, [context, directChatActive, modelOptions, models, multiRoundRagActive, onContextChange, turboModeVisible]);

  const selectedModel = useMemo(() => {
    if (modelOptions.length === 0) {
@@ -314,7 +346,10 @@ export function InputBox({
        model_name,
        mode: getResolvedMode(context.mode, model.supports_thinking ?? false),
        reasoning_effort: context.reasoning_effort,
-        execution_profile: model.execution_profile,
+        execution_profile:
+          context.execution_profile === "direct"
+            ? "direct"
+            : model.execution_profile,
      });
      setModelDialogOpen(false);
    },
@@ -346,6 +381,16 @@ export function InputBox({
    [onContextChange, context, models, supportThinking],
  );

+  const handleDirectChatSelect = useCallback(() => {
+    const ordinaryModel =
+      models.find((model) => model.name === context.model_name) ?? models[0];
+    onContextChange?.({
+      ...context,
+      model_name: ordinaryModel?.name ?? context.model_name,
+      execution_profile: "direct",
+    });
+  }, [context, models, onContextChange]);
+
  const handleSingleRoundRagSelect = useCallback(() => {
    const ragModel =
      extraModels.find((model) => model.name === context.model_name) ??
@@ -749,7 +794,7 @@ export function InputBox({
              />
            </PromptInputActionMenuContent>
          </PromptInputActionMenu> */}
-            {!frontendRagActive && (
+            {!bypassAgentActive && (
              <AddAttachmentsButton
                className={cn(
                  "rounded-full border-0 bg-transparent px-2.5! shadow-none text-muted-foreground hover:bg-muted/70 hover:text-foreground dark:text-slate-400 dark:hover:bg-slate-700/70 dark:hover:text-slate-100",
@@ -758,7 +803,7 @@ export function InputBox({
                )}
              />
            )}
-            {!frontendRagActive && !hideContextTools && <Tooltip
+            {!bypassAgentActive && !hideContextTools && <Tooltip
              content={
                context.writing_mode
                  ? "写作模式已开启：报告由深度研究管线按「通用分析结构」撰写，优先使用对话中已检索的资料"
@@ -784,7 +829,7 @@ export function InputBox({
                <span className="text-xs font-normal">写作</span>
              </PromptInputButton>
            </Tooltip>}
-            {!frontendRagActive && <Tooltip
+            {!bypassAgentActive && <Tooltip
              content={
                artifactDirectoryModeEnabled
                  ? "文件模式已开启：右侧会显示当前对话生成的全部文件目录"
@@ -813,7 +858,7 @@ export function InputBox({
                <span className="text-xs font-normal">文件</span>
              </PromptInputButton>
            </Tooltip>}
-            {!frontendRagActive && !hideContextTools && !hideMemoryTool && <Tooltip
+            {!bypassAgentActive && !hideContextTools && !hideMemoryTool && <Tooltip
              content={
                memoryInjectionEnabled
                  ? "记忆注入已开启：对话前会注入历史记忆"
@@ -839,7 +884,7 @@ export function InputBox({
                <span className="text-xs font-normal">记忆</span>
              </PromptInputButton>
            </Tooltip>}
-            {referenceModeEntryEnabled && !frontendRagActive && !hideContextTools && <Tooltip
+            {referenceModeEntryEnabled && !bypassAgentActive && !hideContextTools && <Tooltip
              content={
                ragModeEnabled
                  ? "参考文献模式已开启：检索类结果会按编号引用展示"
@@ -869,7 +914,7 @@ export function InputBox({
                <span className="text-xs font-normal">参考文献</span>
              </PromptInputButton>
            </Tooltip>}
-            {!frontendRagActive && <Tooltip
+            {!bypassAgentActive && <Tooltip
              content={
                contextCompressionEnabled
                  ? "上下文压缩已开启：超长对话会自动压缩历史以节省 token"
@@ -909,7 +954,9 @@ export function InputBox({
                    : "flash"
                }
                tooltipContent={
-                  singleRoundRagActive
+                  directChatActive
+                    ? `${t.inputBox.turboMode}：${t.inputBox.turboModeDescription}`
+                    : singleRoundRagActive
                    ? "单轮 RAG 问答：基于知识库检索生成答案，并展示参考资料"
                    : multiRoundRagActive
                      ? "多轮 RAG 问答：多次检索并展示检索过程与参考资料"
@@ -921,7 +968,9 @@ export function InputBox({
                    "gap-1.5! rounded-full border-0 bg-transparent px-3! text-muted-foreground shadow-none hover:bg-muted/70 hover:text-foreground dark:text-slate-400 dark:hover:bg-slate-700/70 dark:hover:text-slate-100",
                    compact && "rounded-lg border px-2.5! py-1! text-[11px] font-medium",
                    compact &&
-                      (frontendRagActive
+                      (directChatActive
+                        ? "border-sky-200 bg-sky-50/60 text-sky-700 hover:bg-sky-100 dark:border-sky-700 dark:bg-sky-950/40 dark:text-sky-200"
+                        : frontendRagActive
                        ? "border-emerald-200 bg-emerald-50/60 text-emerald-700 hover:bg-emerald-100 dark:border-emerald-700 dark:bg-emerald-950/40 dark:text-emerald-200"
                        : context.mode === "thinking"
                        ? "border-indigo-200 bg-indigo-50/60 text-indigo-700 hover:bg-indigo-100 dark:border-indigo-700 dark:bg-indigo-950/40 dark:text-indigo-200"
@@ -933,7 +982,9 @@ export function InputBox({
                  )}
                  >
                    <div>
-                    {frontendRagActive ? (
+                    {directChatActive ? (
+                      <GaugeIcon className="size-3" />
+                    ) : frontendRagActive ? (
                      <BookMarkedIcon className="size-3" />
                    ) : context.mode === "flash" ? (
                      <ZapIcon className="size-3" />
@@ -948,10 +999,14 @@ export function InputBox({
                  <div
                    className={cn(
                      "text-xs font-normal",
-                      context.mode === "ultra" ? "golden-text" : "",
+                      context.mode === "ultra" && !directChatActive && !frontendRagActive
+                        ? "golden-text"
+                        : "",
                    )}
                  >
-                    {frontendRagActive
+                    {directChatActive
+                      ? t.inputBox.turboMode
+                      : frontendRagActive
                      ? multiRoundRagActive
                        ? "多轮 RAG"
                        : "单轮 RAG"
@@ -969,9 +1024,39 @@ export function InputBox({
                    {t.inputBox.mode}
                  </DropdownMenuLabel>
                  <PromptInputActionMenu>
+                    {turboModeVisible && (
                    <PromptInputActionMenuItem
                      className={cn(
-                        !frontendRagActive && context.mode === "flash"
+                        directChatActive
+                          ? "bg-sky-50 text-sky-800 hover:bg-sky-100 focus:bg-sky-100 dark:bg-sky-950/40 dark:text-sky-200 dark:hover:bg-sky-950/60 dark:focus:bg-sky-950/60"
+                          : "text-muted-foreground/65",
+                      )}
+                      onSelect={handleDirectChatSelect}
+                    >
+                      <div className="flex flex-col gap-2">
+                        <div className="flex items-center gap-1 font-bold">
+                          <GaugeIcon
+                            className={cn(
+                              "mr-2 size-4",
+                              directChatActive && "text-sky-700 dark:text-sky-200",
+                            )}
+                          />
+                          {t.inputBox.turboMode}
+                        </div>
+                        <div className="pl-7 text-xs">
+                          {t.inputBox.turboModeDescription}
+                        </div>
+                      </div>
+                      {directChatActive ? (
+                        <CheckIcon className="ml-auto size-4" />
+                      ) : (
+                        <div className="ml-auto size-4" />
+                      )}
+                    </PromptInputActionMenuItem>
+                    )}
+                    <PromptInputActionMenuItem
+                      className={cn(
+                        !bypassAgentActive && context.mode === "flash"
                          ? "text-accent-foreground"
                          : "text-muted-foreground/65",
                      )}
@@ -982,7 +1067,7 @@ export function InputBox({
                          <ZapIcon
                            className={cn(
                              "mr-2 size-4",
-                              !frontendRagActive && context.mode === "flash" &&
+                              !bypassAgentActive && context.mode === "flash" &&
                                "text-accent-foreground",
                            )}
                          />
@@ -992,7 +1077,7 @@ export function InputBox({
                          {t.inputBox.flashModeDescription}
                        </div>
                      </div>
-                      {!frontendRagActive && context.mode === "flash" ? (
+                      {!bypassAgentActive && context.mode === "flash" ? (
                        <CheckIcon className="ml-auto size-4" />
                      ) : (
                        <div className="ml-auto size-4" />
@@ -1001,7 +1086,7 @@ export function InputBox({
                    {supportThinking && (
                      <PromptInputActionMenuItem
                        className={cn(
-                          !frontendRagActive && context.mode === "thinking"
+                          !bypassAgentActive && context.mode === "thinking"
                            ? "text-accent-foreground"
                            : "text-muted-foreground/65",
                        )}
@@ -1012,7 +1097,7 @@ export function InputBox({
                            <LightbulbIcon
                              className={cn(
                                "mr-2 size-4",
-                                !frontendRagActive && context.mode === "thinking" &&
+                                !bypassAgentActive && context.mode === "thinking" &&
                                  "text-accent-foreground",
                              )}
                            />
@@ -1022,7 +1107,7 @@ export function InputBox({
                            {t.inputBox.reasoningModeDescription}
                          </div>
                        </div>
-                        {!frontendRagActive && context.mode === "thinking" ? (
+                        {!bypassAgentActive && context.mode === "thinking" ? (
                          <CheckIcon className="ml-auto size-4" />
                        ) : (
                          <div className="ml-auto size-4" />
@@ -1031,7 +1116,7 @@ export function InputBox({
                    )}
                    <PromptInputActionMenuItem
                      className={cn(
-                        !frontendRagActive && context.mode === "pro"
+                        !bypassAgentActive && context.mode === "pro"
                          ? "text-accent-foreground"
                          : "text-muted-foreground/65",
                      )}
@@ -1042,7 +1127,7 @@ export function InputBox({
                          <GraduationCapIcon
                            className={cn(
                              "mr-2 size-4",
-                              !frontendRagActive && context.mode === "pro" &&
+                              !bypassAgentActive && context.mode === "pro" &&
                                "text-accent-foreground",
                            )}
                          />
@@ -1052,7 +1137,7 @@ export function InputBox({
                          {t.inputBox.proModeDescription}
                        </div>
                      </div>
-                      {!frontendRagActive && context.mode === "pro" ? (
+                      {!bypassAgentActive && context.mode === "pro" ? (
                        <CheckIcon className="ml-auto size-4" />
                      ) : (
                        <div className="ml-auto size-4" />
@@ -1060,7 +1145,7 @@ export function InputBox({
                    </PromptInputActionMenuItem>
                    <PromptInputActionMenuItem
                      className={cn(
-                        !frontendRagActive && context.mode === "ultra"
+                        !bypassAgentActive && context.mode === "ultra"
                          ? "text-accent-foreground"
                          : "text-muted-foreground/65",
                      )}
@@ -1071,14 +1156,14 @@ export function InputBox({
                          <RocketIcon
                            className={cn(
                              "mr-2 size-4",
-                              !frontendRagActive &&
+                              !bypassAgentActive &&
                                context.mode === "ultra" &&
                                "text-[#dabb5e]",
                            )}
                          />
                          <div
                            className={cn(
-                              !frontendRagActive &&
+                              !bypassAgentActive &&
                                context.mode === "ultra" &&
                                "golden-text",
                            )}
@@ -1090,7 +1175,7 @@ export function InputBox({
                          {t.inputBox.ultraModeDescription}
                        </div>
                      </div>
-                      {!frontendRagActive && context.mode === "ultra" ? (
+                      {!bypassAgentActive && context.mode === "ultra" ? (
                        <CheckIcon className="ml-auto size-4" />
                      ) : (
                        <div className="ml-auto size-4" />
@@ -1161,7 +1246,7 @@ export function InputBox({
                </DropdownMenuGroup>
              </PromptInputActionMenuContent>
            </PromptInputActionMenu>
-            {!frontendRagActive && supportReasoningEffort && context.mode !== "flash" && (
+            {!bypassAgentActive && supportReasoningEffort && context.mode !== "flash" && (
              <PromptInputActionMenu>
                <PromptInputActionMenuTrigger className={cn("gap-1.5! rounded-full border-0 bg-transparent px-3! text-muted-foreground shadow-none hover:bg-muted/70 hover:text-foreground dark:text-slate-400 dark:hover:bg-slate-700/70 dark:hover:text-slate-100", compact && "rounded-lg border border-border px-2.5! py-1! text-[13px]")}>
                  <div className="text-xs font-normal">
@@ -1279,7 +1364,7 @@ export function InputBox({
            )}
          </PromptInputTools>
          <PromptInputTools className={cn("gap-1.5", compact && "gap-2")}>
-            {!frontendRagActive && agentSelector && (
+            {!bypassAgentActive && agentSelector && (
              <AgentSelector
                selectedAgentId={agentSelector.selectedAgentId}
                onAgentChange={agentSelector.onAgentChange}
@@ -1287,8 +1372,8 @@ export function InputBox({
                compact={compact}
              />
            )}
-            {!frontendRagActive && knowledgeSelector}
-            {!frontendRagActive && promptPrefix && (
+            {!bypassAgentActive && knowledgeSelector}
+            {!bypassAgentActive && promptPrefix && (
              <Tooltip
                content={
                  promptPrefix.on
@@ -96,6 +96,9 @@ export const enUS: Translations = {
    mode: "Mode",
    flashMode: "Flash",
    flashModeDescription: "Fast and efficient, but may not be accurate",
+    turboMode: "Turbo",
+    turboModeDescription:
+      "Talk to the model directly with no agent tools or skills, for lower first-token latency",
    reasoningMode: "Reasoning",
    reasoningModeDescription:
      "Reasoning before action, balance between time and accuracy",
@@ -91,6 +91,8 @@ export interface Translations {
    mode: string;
    flashMode: string;
    flashModeDescription: string;
+    turboMode: string;
+    turboModeDescription: string;
    reasoningMode: string;
    reasoningModeDescription: string;
    proMode: string;
@@ -95,6 +95,8 @@ export const zhCN: Translations = {
    mode: "模式",
    flashMode: "快速",
    flashModeDescription: "快速且高效的完成任务，但可能不够精准",
+    turboMode: "极速",
+    turboModeDescription: "直连大模型流式问答，不走智能体工具与技能，首字更快",
    reasoningMode: "思考",
    reasoningModeDescription: "思考后再行动，在时间与准确性之间取得平衡",
    proMode: "专业问答",
@@ -7,7 +7,7 @@ export interface Model {
  supports_thinking?: boolean;
  supports_reasoning_effort?: boolean;
  /** Execution profiles handled by the frontend instead of DeerFlow. */
-  execution_profile?: "single_round_rag" | "multi_round_rag";
+  execution_profile?: "single_round_rag" | "multi_round_rag" | "direct";
 }

 export interface TokenUsageSettings {
@@ -1579,6 +1579,7 @@ export function useThreadStream({
            context: {
              ...mergedContext,
              thinking_enabled: mergedContext.mode !== "flash",
+              thinking_force_disabled: mergedContext.mode === "flash",
              is_plan_mode:
                mergedContext.mode === "pro" || mergedContext.mode === "ultra",
              subagent_enabled: mergedContext.mode === "ultra",
@@ -14,6 +14,8 @@ export interface AgentThreadContext extends Record<string, unknown> {
  thread_id: string;
  model_name: string | undefined;
  thinking_enabled: boolean;
+  /** Flash mode: force vLLM/Qwen ``enable_thinking=false`` even without a per-model disable shape. */
+  thinking_force_disabled?: boolean;
  is_plan_mode: boolean;
  subagent_enabled: boolean;
  reasoning_effort?: "minimal" | "low" | "medium" | "high";
@@ -29,8 +31,8 @@ export interface AgentThreadContext extends Record<string, unknown> {
  llmwiki_knowledge_base_ids?: string[];
  /** Assistant knowledge-base ids selected for this conversation. */
  assistant_knowledge_base_ids?: string[];
-  /** Direct RAG modes handled in the frontend; these requests never enter Lead Agent. */
-  execution_profile?: "single_round_rag" | "multi_round_rag";
+  /** Frontend-only execution paths that never enter Lead Agent (RAG / 极速直连). */
+  execution_profile?: "single_round_rag" | "multi_round_rag" | "direct";
  agent_id?: string;
  /** @deprecated kept for reading legacy thread metadata; prefer agent_id */
  agent_name?: string;
@@ -0,0 +1,312 @@
+import type { Message } from "@langchain/langgraph-sdk";
+import { useCallback, useEffect, useRef, useState } from "react";
+
+import { apiFetch } from "@/core/api/fetch-client";
+import { getBackendBaseURL } from "@/core/config";
+import { readRuntimeFlag } from "@/env";
+import { createClientId } from "@/lib/client-id";
+
+import { textOfMessage } from "./utils";
+
+const STORAGE_PREFIX = "workspace.direct-chat.";
+const MAX_HISTORY_MESSAGES = 20;
+
+export function isDirectChatProfile(context: unknown): boolean {
+  return (
+    typeof context === "object" &&
+    context !== null &&
+    (context as { execution_profile?: unknown }).execution_profile === "direct"
+  );
+}
+
+/** 是否在模式菜单展示「极速」。仅 runtime-config.js 显式为 "true" 时开启，默认关闭。 */
+export function isTurboModeVisible(): boolean {
+  return readRuntimeFlag("VITE_TURBO_MODE_VISIBLE");
+}
+
+function storageKey(threadId: string) {
+  return `${STORAGE_PREFIX}${threadId}`;
+}
+
+function readStoredMessages(threadId: string): Message[] {
+  if (typeof window === "undefined" || !threadId) return [];
+  try {
+    const raw = window.sessionStorage.getItem(storageKey(threadId));
+    const parsed: unknown = raw ? JSON.parse(raw) : [];
+    return Array.isArray(parsed) ? (parsed as Message[]) : [];
+  } catch {
+    return [];
+  }
+}
+
+function writeStoredMessages(threadId: string, messages: Message[]) {
+  if (typeof window === "undefined" || !threadId) return;
+  try {
+    window.sessionStorage.setItem(storageKey(threadId), JSON.stringify(messages));
+  } catch {
+    // Quota errors must never interrupt an already-running answer.
+  }
+}
+
+function isAbortError(error: unknown): boolean {
+  return error instanceof DOMException
+    ? error.name === "AbortError"
+    : error instanceof Error && error.name === "AbortError";
+}
+
+function historyFromMessages(messages: Message[]): Array<{
+  role: "user" | "assistant";
+  content: string;
+}> {
+  const history: Array<{ role: "user" | "assistant"; content: string }> = [];
+  for (const message of messages) {
+    if (message.type !== "human" && message.type !== "ai") continue;
+    const content = textOfMessage(message)?.trim();
+    if (!content) continue;
+    history.push({
+      role: message.type === "human" ? "user" : "assistant",
+      content,
+    });
+  }
+  return history.slice(-MAX_HISTORY_MESSAGES);
+}
+
+function parseSseBlocks(buffer: string): {
+  events: Array<{ event?: string; data: string }>;
+  rest: string;
+} {
+  const parts = buffer.split("\n\n");
+  const rest = parts.pop() ?? "";
+  const events: Array<{ event?: string; data: string }> = [];
+  for (const part of parts) {
+    let event: string | undefined;
+    const dataLines: string[] = [];
+    for (const line of part.split("\n")) {
+      if (line.startsWith(":")) continue;
+      if (line.startsWith("event:")) event = line.slice(6).trim();
+      else if (line.startsWith("data:")) dataLines.push(line.slice(5).trimStart());
+    }
+    if (dataLines.length > 0) {
+      events.push({ event, data: dataLines.join("\n") });
+    }
+  }
+  return { events, rest };
+}
+
+async function readErrorDetail(response: Response): Promise<string> {
+  try {
+    const payload: unknown = await response.json();
+    if (
+      payload &&
+      typeof payload === "object" &&
+      "detail" in payload &&
+      typeof (payload as { detail: unknown }).detail === "string"
+    ) {
+      return (payload as { detail: string }).detail;
+    }
+  } catch {
+    // Fall through to status text.
+  }
+  return `极速问答失败（${response.status}）`;
+}
+
+/**
+ * Frontend-only adapter that talks to Gateway ``POST /api/direct-chat/stream``.
+ * It never submits a LangGraph run or touches the lead-agent stack.
+ */
+export function useDirectChatMessages(threadId: string | undefined) {
+  const [messages, setMessages] = useState<Message[]>(() =>
+    readStoredMessages(threadId ?? ""),
+  );
+  const messagesRef = useRef(messages);
+  const [isLoading, setIsLoading] = useState(false);
+  const [error, setError] = useState<string | null>(null);
+  const controllerRef = useRef<AbortController | null>(null);
+
+  useEffect(() => {
+    const stored = readStoredMessages(threadId ?? "");
+    messagesRef.current = stored;
+    setMessages(stored);
+    setError(null);
+  }, [threadId]);
+
+  useEffect(() => {
+    messagesRef.current = messages;
+  }, [messages]);
+
+  useEffect(() => () => controllerRef.current?.abort(), []);
+
+  const updateMessages = useCallback(
+    (targetThreadId: string, updater: (current: Message[]) => Message[]) => {
+      setMessages((current) => {
+        const next = updater(current);
+        messagesRef.current = next;
+        writeStoredMessages(targetThreadId, next);
+        return next;
+      });
+    },
+    [],
+  );
+
+  const stop = useCallback(() => controllerRef.current?.abort(), []);
+
+  const submit = useCallback(
+    async ({
+      targetThreadId,
+      query,
+      modelName,
+    }: {
+      targetThreadId: string;
+      query: string;
+      modelName?: string;
+    }) => {
+      if (isLoading) return;
+      const question = query.trim();
+      if (!question) return;
+
+      const humanId = createClientId("direct-human");
+      const assistantId = createClientId("direct-ai");
+      const clientTs = new Date().toISOString();
+      const history = historyFromMessages(messagesRef.current);
+      const userMessage: Message = {
+        id: humanId,
+        type: "human",
+        content: [{ type: "text", text: question }],
+        additional_kwargs: { client_ts: clientTs, direct_chat: true },
+      };
+      const initialAssistant: Message = {
+        id: assistantId,
+        type: "ai",
+        content: "",
+        additional_kwargs: { direct_chat: true },
+      };
+      updateMessages(targetThreadId, (current) => [
+        ...current,
+        userMessage,
+        initialAssistant,
+      ]);
+      setError(null);
+      setIsLoading(true);
+
+      const controller = new AbortController();
+      controllerRef.current = controller;
+      let answer = "";
+
+      const refreshAssistant = (content: string) => {
+        updateMessages(targetThreadId, (current) =>
+          current.map((item) =>
+            item.id === assistantId
+              ? ({
+                  ...item,
+                  content,
+                  additional_kwargs: {
+                    ...item.additional_kwargs,
+                    direct_chat: true,
+                  },
+                } as Message)
+              : item,
+          ),
+        );
+      };
+
+      try {
+        const response = await apiFetch(
+          `${getBackendBaseURL()}/api/direct-chat/stream`,
+          {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            signal: controller.signal,
+            body: JSON.stringify({
+              model_name: modelName,
+              messages: [...history, { role: "user", content: question }],
+            }),
+          },
+        );
+        if (!response.ok) {
+          throw new Error(await readErrorDetail(response));
+        }
+        if (!response.body) {
+          throw new Error("极速问答未返回数据流。");
+        }
+
+        const reader = response.body.getReader();
+        const decoder = new TextDecoder();
+        let buffer = "";
+        while (true) {
+          const { done, value } = await reader.read();
+          if (done) break;
+          buffer += decoder.decode(value, { stream: true });
+          const parsed = parseSseBlocks(buffer);
+          buffer = parsed.rest;
+          for (const block of parsed.events) {
+            let payload: unknown = null;
+            try {
+              payload = JSON.parse(block.data);
+            } catch {
+              continue;
+            }
+            if (block.event === "error") {
+              const detail =
+                payload &&
+                typeof payload === "object" &&
+                "detail" in payload &&
+                typeof (payload as { detail: unknown }).detail === "string"
+                  ? (payload as { detail: string }).detail
+                  : "极速问答失败。";
+              throw new Error(detail);
+            }
+            if (
+              block.event === "delta" &&
+              payload &&
+              typeof payload === "object" &&
+              "text" in payload &&
+              typeof (payload as { text: unknown }).text === "string"
+            ) {
+              answer += (payload as { text: string }).text;
+              refreshAssistant(answer);
+            }
+            if (
+              block.event === "result" &&
+              payload &&
+              typeof payload === "object" &&
+              "answer" in payload &&
+              typeof (payload as { answer: unknown }).answer === "string"
+            ) {
+              answer = (payload as { answer: string }).answer;
+              refreshAssistant(answer);
+            }
+          }
+        }
+        if (!answer) {
+          throw new Error("模型未返回任何文本。");
+        }
+      } catch (caught) {
+        if (!isAbortError(caught)) {
+          const message =
+            caught instanceof Error ? caught.message : "极速问答失败。";
+          setError(message);
+          updateMessages(targetThreadId, (current) =>
+            current.map((item) =>
+              item.id === assistantId
+                ? ({
+                    ...item,
+                    content: answer || message,
+                    additional_kwargs: {
+                      ...item.additional_kwargs,
+                      direct_chat: true,
+                    },
+                  } as Message)
+                : item,
+            ),
+          );
+        }
+      } finally {
+        if (controllerRef.current === controller) controllerRef.current = null;
+        setIsLoading(false);
+      }
+    },
+    [isLoading, updateMessages],
+  );
+
+  return { messages, isLoading, error, submit, stop };
+}
@@ -13,6 +13,7 @@ import { useLocation } from "react-router-dom";
 import { useRouteBase } from "@/core/route-base";
 import { useCallback, useEffect, useMemo, useRef, useState, type ReactNode } from "react";
 import { useQuery } from "@tanstack/react-query";
+import { toast } from "sonner";

 import type { PromptInputMessage } from "@/components/ai-elements/prompt-input";
 import { Button } from "@/components/ui/button";
@@ -48,6 +49,7 @@ import { useNotification } from "@/core/notification/hooks";
 import { saveLastAgentId, useThreadSettings } from "@/core/settings";
 import { stopActiveThreadBeforeClarificationReply, stopThreadRun, useThreadStream } from "@/core/threads/hooks";
 import { useResearchWritingFeed } from "@/core/threads/use-research-writing-feed";
+import { useDirectChatMessages, isDirectChatProfile, isTurboModeVisible } from "@/core/threads/use-direct-chat";
 import { clearResearchReportStream } from "@/core/threads/use-research-report-stream";
 import { textOfMessage } from "@/core/threads/utils";
 import { resolveWritingModeReportPath } from "@/core/threads/writing-mode";
@@ -560,9 +562,26 @@ export default function AgentChatPage({
    },
  });

+  const directChat = useDirectChatMessages(threadId);
+  const directChatSelected =
+    isDirectChatProfile(settings.context) && isTurboModeVisible();
+
  // 写作模式深度研究进度：注入 displayThread 尾部（进度步骤条 + report.md
  // 流式 stub），成功且真实产物落地后自动撤出。
-  const { displayThread } = useResearchWritingFeed(threadId, thread);
+  const { displayThread: researchDisplayThread } = useResearchWritingFeed(threadId, thread);
+  const displayThread = useMemo(() => {
+    const base = researchDisplayThread;
+    if (directChat.messages.length === 0 && !directChat.isLoading) {
+      return base;
+    }
+    const messages = [...base.messages, ...directChat.messages];
+    return {
+      ...base,
+      values: { ...base.values, messages },
+      messages,
+      isLoading: base.isLoading || directChat.isLoading,
+    } as typeof base;
+  }, [directChat.isLoading, directChat.messages, researchDisplayThread]);

  // ── agentfx「入库」协助卡 ──────────────────────────────────────────────────
  // 任务工作区（taskBind）里，内置研判智能体写出的 task-reports.json 产物落地且
@@ -743,6 +762,62 @@ export default function AgentChatPage({

  const handleSubmit = useCallback(
    (message: PromptInputMessage, extraContext?: Record<string, unknown>) => {
+      if (directChatSelected) {
+        if (message.files && message.files.length > 0) {
+          toast.error("极速问答暂不支持附件，请移除附件后重试。");
+          return;
+        }
+        setHasStartedConversation(true);
+        saveLastAgentId(agent_id);
+        window.dispatchEvent(
+          new CustomEvent("workspace:sandbox-resume-autoscroll"),
+        );
+        void (async () => {
+          try {
+            let targetThreadId = threadId;
+            if (isNewThread) {
+              const created = await getAPIClient().threads.create({
+                metadata: {
+                  agent_id,
+                  ...(Object.keys(conversationMetadata).length > 0
+                    ? conversationMetadata
+                    : {}),
+                },
+              });
+              targetThreadId = created.thread_id;
+              knowledgeSelectionThread.current = targetThreadId;
+              activeThreadIdRef.current = targetThreadId;
+              setThreadId(targetThreadId);
+              setIsNewThread(false);
+              history.replaceState(
+                null,
+                "",
+                `${window.location.pathname}${window.location.search}#${agentChatsBase}/${targetThreadId}`,
+              );
+              const title = message.text.trim().replace(/\s+/g, " ").slice(0, 60);
+              if (title) {
+                void getAPIClient().threads
+                  .updateState(targetThreadId, { values: { title } })
+                  .catch(() => undefined);
+              }
+            }
+            if (!targetThreadId) {
+              toast.error("无法创建会话。");
+              return;
+            }
+            await directChat.submit({
+              targetThreadId,
+              query: message.text,
+              modelName: settings.context.model_name,
+            });
+          } catch (error) {
+            toast.error(
+              error instanceof Error ? error.message : "极速问答失败。",
+            );
+          }
+        })();
+        return;
+      }
      setHasStartedConversation(true);
      // Remember this agent so the new-chat landing screen pre-selects it next
      // time (covers both direct agent chats and the ChatPage handoff replay).
@@ -767,7 +842,7 @@ export default function AgentChatPage({
        ...pageReportThemeContext,
      });
    },
-    [sendMessage, threadId, agent_id, settings.context.writing_mode, writingArtifactPath, baseMode],
+    [sendMessage, threadId, agent_id, settings.context.writing_mode, settings.context.model_name, writingArtifactPath, baseMode, directChat, directChatSelected, isNewThread, conversationMetadata, agentChatsBase, setThreadId, setIsNewThread],
  );

  // 任务流程：切换 / 新建会话时，停掉「上一会话服务端在跑」的 run（老对话要停止）。
@@ -852,8 +927,12 @@ export default function AgentChatPage({
  );

  const handleStop = useCallback(async () => {
+    if (directChat.isLoading) {
+      directChat.stop();
+      return;
+    }
    await thread.stop();
-  }, [thread]);
+  }, [directChat, thread]);

  const isLandingState = isNewThread && !hasStartedConversation;
  // 任务闸门面板：仅 rwfx（taskGate）在新建对话且尚未开始时，于问答页顶部展示目的树 + 覆盖确认。
@@ -867,7 +946,7 @@ export default function AgentChatPage({

  const status = thread.error
    ? "error"
-    : thread.isLoading
+    : thread.isLoading || directChat.isLoading
      ? "streaming"
      : "ready";

@@ -1084,7 +1163,7 @@ export default function AgentChatPage({
                        autoFocus
                        status={status}
                        context={settings.context}
-                        disabled={isDemoMode || knowledgeSelectionLoading}
+                        disabled={isDemoMode || knowledgeSelectionLoading || directChat.isLoading}
                        onContextChange={(context) =>
                          setSettings("context", context)
                        }
@@ -1104,7 +1183,7 @@ export default function AgentChatPage({
                                pendingKnowledgeSelection.current === null &&
                                pendingAssistantKnowledgeSelection.current === null
                              }
-                              disabled={isDemoMode || knowledgeSelectionLoading}
+                              disabled={isDemoMode || knowledgeSelectionLoading || directChat.isLoading}
                              label="知识空间"
                            />
                          )
@@ -1175,7 +1254,7 @@ export default function AgentChatPage({
                        assistantId={agent_id}
                        status={status}
                        context={settings.context}
-                        disabled={isDemoMode || knowledgeSelectionLoading}
+                        disabled={isDemoMode || knowledgeSelectionLoading || directChat.isLoading}
                        onContextChange={(context) =>
                          setSettings("context", context)
                        }
@@ -1190,7 +1269,7 @@ export default function AgentChatPage({
                              assistantValue={selectedAssistantKnowledgeBaseIds}
                              onChange={changeKnowledgeSelection}
                              onAssistantChange={changeAssistantKnowledgeSelection}
-                              disabled={isDemoMode || knowledgeSelectionLoading}
+                              disabled={isDemoMode || knowledgeSelectionLoading || directChat.isLoading}
                              readOnly
                              label="知识空间"
                            />
@@ -69,6 +69,7 @@ import { clearResearchReportStream } from "@/core/threads/use-research-report-st
 import { resolveWritingModeReportPath } from "@/core/threads/writing-mode";
 import { queueLlmWikiConversationDeposit } from "@/core/llmwiki/conversation-deposit";
 import { useSingleRoundRagMessages } from "@/core/threads/use-single-round-rag";
+import { useDirectChatMessages, isDirectChatProfile, isTurboModeVisible } from "@/core/threads/use-direct-chat";
 import { useMultiRoundRagMessages, mergeMessagesByTime, toLangGraphMessages } from "@/core/threads/use-multi-round-rag";
 import { useLayoutMode } from "@/core/system-settings/hooks";
 import { useRouteBase } from "@/core/route-base";
@@ -348,9 +349,12 @@ export default function ChatPage() {
  });
  const singleRoundRag = useSingleRoundRagMessages(threadId);
  const multiRoundRag = useMultiRoundRagMessages(threadId);
+  const directChat = useDirectChatMessages(threadId);
  const singleRoundRagSelected = isSingleRoundRagProfile(settings.context);
  const multiRoundRagSelected = isMultiRoundRagProfile(settings.context);
  const frontendRagSelected = isFrontendRagProfile(settings.context);
+  const directChatSelected =
+    isDirectChatProfile(settings.context) && isTurboModeVisible();
  // 写作模式深度研究进度：注入 displayThread 尾部（进度步骤条 + report.md
  // 流式 stub），成功且真实产物落地后自动撤出。
  const { displayThread: researchDisplayThread } = useResearchWritingFeed(threadId, thread);
@@ -360,13 +364,15 @@ export default function ChatPage() {
    if (
      singleRoundRag.messages.length === 0 &&
      ragMessages.length === 0 &&
+      directChat.messages.length === 0 &&
      !singleRoundRag.isLoading &&
-      !multiRoundRag.isLoading
+      !multiRoundRag.isLoading &&
+      !directChat.isLoading
    ) {
      return base;
    }
    const messages = mergeMessagesByTime(
-      [...base.messages, ...singleRoundRag.messages],
+      [...base.messages, ...singleRoundRag.messages, ...directChat.messages],
      ragMessages,
    );
    return {
@@ -374,9 +380,14 @@ export default function ChatPage() {
      values: { ...base.values, messages },
      messages,
      isLoading:
-        base.isLoading || singleRoundRag.isLoading || multiRoundRag.isLoading,
+        base.isLoading ||
+        singleRoundRag.isLoading ||
+        multiRoundRag.isLoading ||
+        directChat.isLoading,
    } as typeof base;
  }, [
+    directChat.isLoading,
+    directChat.messages,
    multiRoundRag.isLoading,
    multiRoundRag.messages,
    researchDisplayThread,
@@ -392,6 +403,52 @@ export default function ChatPage() {

  const handleSubmit = useCallback(
    (message: PromptInputMessage) => {
+      if (directChatSelected) {
+        if (message.files && message.files.length > 0) {
+          toast.error("极速问答暂不支持附件，请移除附件后重试。");
+          return;
+        }
+        setHasStartedConversation(true);
+        window.dispatchEvent(
+          new CustomEvent("workspace:sandbox-resume-autoscroll"),
+        );
+        void (async () => {
+          try {
+            let targetThreadId = threadId;
+            if (isNewThread) {
+              const created = await getAPIClient(isMock).threads.create({});
+              targetThreadId = created.thread_id;
+              setThreadId(targetThreadId);
+              setIsNewThread(false);
+              history.replaceState(
+                null,
+                "",
+                `${window.location.pathname}${window.location.search}#${routeBase}/chats/${targetThreadId}`,
+              );
+              const title = message.text.trim().replace(/\s+/g, " ").slice(0, 60);
+              if (title) {
+                void getAPIClient(isMock).threads
+                  .updateState(targetThreadId, { values: { title } })
+                  .catch(() => undefined);
+              }
+            }
+            if (!targetThreadId) {
+              toast.error("无法创建会话。");
+              return;
+            }
+            await directChat.submit({
+              targetThreadId,
+              query: message.text,
+              modelName: settings.context.model_name,
+            });
+          } catch (error) {
+            toast.error(
+              error instanceof Error ? error.message : "极速问答失败。",
+            );
+          }
+        })();
+        return;
+      }
      if (frontendRagSelected) {
        if (message.files && message.files.length > 0) {
          toast.error("RAG 问答暂不支持附件，请移除附件后重试。");
@@ -560,6 +617,8 @@ export default function ChatPage() {
      multiRoundRag,
      multiRoundRagSelected,
      frontendRagSelected,
+      directChat,
+      directChatSelected,
      routeBase,
      setIsNewThread,
      setThreadId,
@@ -655,6 +714,10 @@ export default function ChatPage() {
    saveLastAgentId(agentId);
  }, []);
  const handleStop = useCallback(async () => {
+    if (directChat.isLoading) {
+      directChat.stop();
+      return;
+    }
    if (singleRoundRag.isLoading) {
      singleRoundRag.stop();
      return;
@@ -664,7 +727,7 @@ export default function ChatPage() {
      return;
    }
    await thread.stop();
-  }, [multiRoundRag, singleRoundRag, thread]);
+  }, [directChat, multiRoundRag, singleRoundRag, thread]);

  const promptPrefixProp = useMemo(() => {
    if (!promptPrefixSettings?.enabled) return undefined;
@@ -914,7 +977,8 @@ export default function ChatPage() {
                        agentHandoffPending ||
                        knowledgeSelectionLoading ||
                        singleRoundRag.isLoading ||
-                        multiRoundRag.isLoading
+                        multiRoundRag.isLoading ||
+                        directChat.isLoading
                      }
                      onContextChange={(context) =>
                        setSettings("context", context)
@@ -42,6 +42,7 @@ from app.gateway.routers import (
    compact_menu_overrides,
    dashboard_sessions,
    deep_research,
+    direct_chat,
    external_llmwiki,
    feedback,
    fixed_questions,
@@ -1803,6 +1804,9 @@ This gateway provides custom endpoints for models, MCP configuration, skills, an
    # 开放问答接口 /api/open/chat —— 无需登录,指定模型 + 智能体做问答,可关闭思考模式
    app.include_router(open_chat.router)

+    # 极速问答 /api/direct-chat/stream —— 直连大模型流式输出,不走 lead agent / 工具 / 技能
+    app.include_router(direct_chat.router)
+
    # 开放接口 /api/open/3qfx/ask —— 无需登录,按 taskId 直接发起 3qfx 第一次问答(后台运行,落成真实会话)
    app.include_router(open_3qfx.router)

@@ -0,0 +1,149 @@
+"""Direct LLM chat — no lead agent, tools, skills, or memory.
+
+Used by the frontend 「极速」mode: stream tokens from ``create_chat_model``
+with thinking forced off so first-token latency matches a bare chat client.
+"""
+
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+from collections.abc import AsyncIterator
+from typing import Any, Literal
+
+from fastapi import APIRouter, HTTPException
+from fastapi.responses import StreamingResponse
+from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
+from pydantic import BaseModel, Field
+
+from deerflow.config import get_app_config
+from deerflow.models import create_chat_model
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/direct-chat", tags=["direct-chat"])
+
+_HEARTBEAT_SECONDS = 15.0
+_MAX_MESSAGES = 40
+
+
+class DirectChatMessage(BaseModel):
+    role: Literal["user", "assistant", "system"]
+    content: str = ""
+
+
+class DirectChatRequest(BaseModel):
+    messages: list[DirectChatMessage] = Field(..., min_length=1)
+    model_name: str | None = None
+
+
+def _chunk_text(chunk: Any) -> str:
+    content = getattr(chunk, "content", None)
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        parts: list[str] = []
+        for block in content:
+            if isinstance(block, str):
+                parts.append(block)
+            elif isinstance(block, dict) and isinstance(block.get("text"), str):
+                parts.append(block["text"])
+        return "".join(parts)
+    return ""
+
+
+def _build_lc_messages(body: DirectChatRequest) -> list[BaseMessage]:
+    built: list[BaseMessage] = []
+    for item in body.messages[-_MAX_MESSAGES:]:
+        text = (item.content or "").strip()
+        if not text:
+            continue
+        if item.role == "user":
+            built.append(HumanMessage(content=text))
+        elif item.role == "assistant":
+            built.append(AIMessage(content=text))
+        else:
+            built.append(SystemMessage(content=text))
+    if not any(isinstance(msg, HumanMessage) for msg in built):
+        raise HTTPException(status_code=400, detail="至少需要一条 user 消息")
+    return built
+
+
+def _sse(event: str, data: Any) -> str:
+    return f"event: {event}\ndata: {json.dumps(data, ensure_ascii=False)}\n\n"
+
+
+def _resolve_model_name(name: str | None) -> str:
+    config = get_app_config()
+    if not name:
+        if not config.models:
+            raise HTTPException(status_code=400, detail="未配置可用模型")
+        return config.models[0].name
+    if config.get_model_config(name) is None:
+        raise HTTPException(status_code=400, detail=f"模型不存在: {name}")
+    return name
+
+
+async def _direct_chat_event_stream(body: DirectChatRequest, model_name: str) -> AsyncIterator[str]:
+    lc_messages = _build_lc_messages(body)
+    queue: asyncio.Queue[tuple[str, Any]] = asyncio.Queue()
+    pieces: list[str] = []
+
+    async def produce() -> None:
+        try:
+            model = create_chat_model(
+                name=model_name,
+                thinking_enabled=False,
+                force_disable_thinking=True,
+            )
+            async for chunk in model.astream(lc_messages):
+                text = _chunk_text(chunk)
+                if text:
+                    pieces.append(text)
+                    await queue.put(("delta", {"text": text}))
+        except Exception as exc:  # noqa: BLE001 — stream errors become SSE error events
+            logger.exception("direct_chat 调用模型失败 (model=%s)", model_name)
+            await queue.put(("error", {"detail": f"模型调用失败:{exc}"}))
+        finally:
+            await queue.put(("__end__", None))
+
+    task = asyncio.create_task(produce())
+    try:
+        while True:
+            try:
+                event, data = await asyncio.wait_for(queue.get(), timeout=_HEARTBEAT_SECONDS)
+            except asyncio.TimeoutError:
+                yield ": keepalive\n\n"
+                continue
+            if event == "__end__":
+                break
+            if event == "error":
+                yield _sse("error", data)
+                return
+            yield _sse(event, data)
+
+        answer = "".join(pieces)
+        if not answer:
+            yield _sse("error", {"detail": "模型未返回任何文本。"})
+            return
+        yield _sse("result", {"answer": answer, "model_name": model_name})
+    finally:
+        if not task.done():
+            task.cancel()
+
+
+@router.post("/stream")
+async def direct_chat_stream(body: DirectChatRequest) -> StreamingResponse:
+    """Stream a plain chat completion. No agent graph, tools, or skills."""
+    model_name = _resolve_model_name(body.model_name)
+    _build_lc_messages(body)
+    return StreamingResponse(
+        _direct_chat_event_stream(body, model_name),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no",
+        },
+    )
@@ -33,6 +33,16 @@ concurrency:
    fail_open: true

 models: 
+- name: MiniMax-M2.7
+  display_name: MiniMax-M2.7
+  use: langchain_openai:ChatOpenAI
+  model: MiniMax-M2.7
+  api_key: sk-cp-mrsAGtzDpUl0TpOBPVoiRG_pWF1kDDN9_mDAnONBs6HIPcNUexSKtSbx2QOxfKBvJT6Xw6hDTV6hdkJYFWfNA8UtHQ08TiGJiosdRoW6q1sGb6Cb7D85NHk
+  base_url: https://api.minimaxi.com/v1
+  max_tokens: 4096
+  temperature: 1.0
+  supports_vision: true
+  supports_thinking: true
 - name: MiniMax-M2.7-fash
  display_name: MiniMax-M2.7-fash
  use: langchain_openai:ChatOpenAI
@@ -466,7 +476,7 @@ checkpointer:
 # 三层覆盖优先级(高->低):
 #   users/{user_id}/memory_config.json > .deer-flow/memory_user_overrides.json > 此处
 memory:
-  enabled: true
+  enabled: false # 临时关闭跨会话记忆（提取/注入/Hindsight 召回与 retain、memory 工具）
  version:
    v1 # 记忆版本: 'v1'(原版 DeerFlow, memory.json + LLM 自动提取)
    #           'v2'(USER.md/MEMORY.md + 可选 Hindsight)
@@ -433,7 +433,9 @@ def _build_middlewares(

    # Add MemoryMiddleware (after TitleMiddleware) — skip in bootstrap mode (agent creation flow) and ephemeral runs
    memory_injection_enabled = cfg.get("memory_injection_enabled", True)
-    if not is_bootstrap and not is_writing_setup and not is_report_structure_setup and not is_ephemeral:
+    memory_cfg = getattr(resolved_app_config, "memory", None)
+    memory_globally_enabled = memory_cfg is not None and getattr(memory_cfg, "enabled", False)
+    if memory_globally_enabled and not is_bootstrap and not is_writing_setup and not is_report_structure_setup and not is_ephemeral:
        middlewares.append(MemoryMiddleware(agent_name=agent_name, memory_config=resolved_app_config.memory, injection_enabled=memory_injection_enabled))

    # KnowledgeRagMiddleware — inject knowledge-base recall (phase 2). Gated
@@ -883,11 +883,16 @@ def _get_memory_context(agent_name: str | None = None, *, app_config: AppConfig
        return ""
    try:
        from deerflow.agents.memory.manager import build_memory_manager
-        from deerflow.config.memory_config import get_effective_memory_config
+        from deerflow.config.memory_config import get_effective_memory_config, get_memory_config
        from deerflow.runtime.user_context import get_effective_user_id

+        if not get_memory_config().enabled:
+            return ""
+
        user_id = get_effective_user_id()
        config = get_effective_memory_config(user_id)
+        if not config.enabled or not config.injection.enabled:
+            return ""

        manager = build_memory_manager(
            user_id=user_id,
@@ -16,7 +16,7 @@
 ============
 ``get_effective_memory_config(user_id)`` 按优先级合并 (高 -> 低):
  1. per-user 覆盖   数据库 ``user_memory_configs`` 表 (经进程内 cache 读取)
-     (有 per-user 记录时自动强制 enabled=True)
+     (仅白名单字段,不能覆盖 ``enabled``)
  2. config.yaml     ``memory:`` 段 (即 ``get_memory_config()``)
  3. Pydantic 默认值

@@ -254,13 +254,12 @@ def get_effective_memory_config(user_id: str) -> MemoryConfig:
    """返回某用户的生效记忆配置 (同步,从进程内 cache 读取 per-user 覆盖)。

    优先级 (高 -> 低):per-user DB 覆盖 (经 cache) > config.yaml > 默认值。
-    有 per-user 记录时自动强制 enabled=True。
+    ``enabled`` 始终以 config.yaml 为准,用户覆盖不能把它重新打开。
    """
    base = _memory_config.model_dump()
    recall_budget = _recall_budget_cache.get(user_id)
    if recall_budget is not None:
        base.setdefault("hindsight", {})["recall_budget"] = recall_budget
-        base["enabled"] = True
    try:
        return MemoryConfig(**base)
    except Exception as exc:  # noqa: BLE001 - 覆盖产生非法配置时降级
@@ -31,6 +31,96 @@ def _vllm_disable_chat_template_kwargs(chat_template_kwargs: dict) -> dict:
    return disable_kwargs


+# Qwen3.8 chat templates only accept these three effort names.
+_QWEN_REASONING_EFFORT = {
+    "minimal": "low",
+    "low": "low",
+    "medium": "medium",
+    "high": "xhigh",
+    "xhigh": "xhigh",
+}
+
+_OPENAI_THINKING_OFF_EXTRA_BODY = {
+    "enable_thinking": False,
+    "chat_template_kwargs": {"enable_thinking": False},
+    "thinking": {"type": "disabled"},
+}
+
+
+def _is_vllm_provider(model_use: str) -> bool:
+    lowered = (model_use or "").lower()
+    return "vllm_provider" in lowered or lowered.endswith(":vllmchatmodel")
+
+
+def _is_qwen38_model(model_config) -> bool:
+    blob = f"{getattr(model_config, 'name', '')} {getattr(model_config, 'model', '')}".lower()
+    return "qwen3.8" in blob
+
+
+def _should_control_openai_thinking(model_config) -> bool:
+    """Whether this OpenAI-compatible model needs explicit thinking on/off flags.
+
+    Qwen3.8 (and current vLLM reasoning parsers) default to thinking at ``xhigh``.
+    If DeerFlow does not send ``enable_thinking: false``, the first visible answer
+    token waits until that hidden reasoning finishes — third-party chat UIs that
+    disable thinking or stream the reasoning field therefore feel much faster.
+    """
+    if getattr(model_config, "supports_thinking", False):
+        return True
+    if _is_vllm_provider(getattr(model_config, "use", "")):
+        return True
+    return _is_qwen38_model(model_config)
+
+
+def _map_qwen_reasoning_effort(effort: object) -> str | None:
+    if effort is None:
+        return None
+    return _QWEN_REASONING_EFFORT.get(str(effort).strip().lower())
+
+
+def _apply_openai_thinking_control(
+    model_config,
+    model_class,
+    model_settings_from_config: dict,
+    *,
+    thinking_enabled: bool,
+    reasoning_effort: object,
+) -> None:
+    """Inject vLLM/Qwen thinking flags when the UI toggle is on or off."""
+    if "extra_body" not in getattr(model_class, "model_fields", {}):
+        return
+    qwen_vllm = _is_vllm_provider(getattr(model_config, "use", "")) or _is_qwen38_model(model_config)
+    if thinking_enabled:
+        if not qwen_vllm:
+            return
+        enable_body: dict = {
+            "enable_thinking": True,
+            "chat_template_kwargs": {"enable_thinking": True},
+        }
+        mapped_effort = _map_qwen_reasoning_effort(reasoning_effort)
+        if mapped_effort:
+            enable_body["chat_template_kwargs"]["reasoning_effort"] = mapped_effort
+        model_settings_from_config["extra_body"] = _deep_merge_dicts(
+            model_settings_from_config.get("extra_body"),
+            enable_body,
+        )
+        return
+    if not _should_control_openai_thinking(model_config):
+        return
+    disable_body = (
+        {
+            "enable_thinking": False,
+            "chat_template_kwargs": {"enable_thinking": False},
+        }
+        if qwen_vllm
+        else _OPENAI_THINKING_OFF_EXTRA_BODY
+    )
+    model_settings_from_config["extra_body"] = _deep_merge_dicts(
+        model_settings_from_config.get("extra_body"),
+        disable_body,
+    )
+
+
 def _enable_stream_usage_by_default(model_use_path: str, model_settings_from_config: dict) -> None:
    """Enable stream usage for OpenAI-compatible models unless explicitly configured.

@@ -127,10 +217,19 @@ def create_chat_model(name: str | None = None, thinking_enabled: bool = False, *
        elif has_thinking_settings and effective_wte.get("thinking", {}).get("type"):
            # Native langchain_anthropic: thinking is a direct constructor parameter
            model_settings_from_config["thinking"] = {"type": "disabled"}
+    requested_reasoning_effort = kwargs.get("reasoning_effort")
    if not model_config.supports_reasoning_effort:
        kwargs.pop("reasoning_effort", None)
        model_settings_from_config.pop("reasoning_effort", None)

+    _apply_openai_thinking_control(
+        model_config,
+        model_class,
+        model_settings_from_config,
+        thinking_enabled=thinking_enabled,
+        reasoning_effort=requested_reasoning_effort,
+    )
+
    # Hard override: force-disable thinking regardless of the per-model config shape.
    # Injected only for OpenAI-compatible classes (those declaring `extra_body`);
    # other providers would reject the kwarg, so they are skipped (they ignore it).
@@ -208,11 +208,21 @@ def _restore_reasoning_content(payload_msg: dict, orig_msg: AIMessage) -> None:


 def _extract_reasoning_content(payload: dict | None) -> str | None:
-    """Extract reasoning text from provider payload delta/message objects."""
+    """Extract reasoning text from provider payload delta/message objects.
+
+    vLLM Qwen reasoning parsers use ``reasoning_content`` on streaming deltas
+    and ``reasoning`` on some non-stream / older builds. Read both so the UI
+    can show the first thinking token instead of waiting for answer content.
+    """
    if not isinstance(payload, dict):
        return None
    reasoning_content = payload.get("reasoning_content")
-    return reasoning_content if isinstance(reasoning_content, str) and reasoning_content else None
+    if isinstance(reasoning_content, str) and reasoning_content:
+        return reasoning_content
+    reasoning = payload.get("reasoning")
+    if isinstance(reasoning, str) and reasoning:
+        return reasoning
+    return None


 def _append_reasoning_content(message: AIMessage | AIMessageChunk, reasoning_content: str) -> AIMessage | AIMessageChunk:
@@ -107,6 +107,8 @@ def _convert_delta_to_message_chunk_with_reasoning(_dict: Mapping[str, Any], def
        additional_kwargs["function_call"] = function_call

    reasoning = _dict.get("reasoning")
+    if reasoning is None:
+        reasoning = _dict.get("reasoning_content")
    if reasoning is not None:
        additional_kwargs["reasoning"] = reasoning
        reasoning_text = _reasoning_to_text(reasoning)
@@ -239,3 +239,66 @@ def test_force_disable_thinking_skips_generic_openai_models_without_thinking_sup
    )

    assert chat_model.extra_body is None
+
+
+def _extra_body(chat_model) -> dict:
+    body = chat_model.extra_body or {}
+    return body if isinstance(body, dict) else dict(body)
+
+
+def test_qwen38_flash_mode_disables_default_xhigh_thinking() -> None:
+    """Qwen3.8 defaults to thinking=xhigh; flash must send enable_thinking=false."""
+    config = AppConfig.model_construct(
+        models=[
+            ModelConfig(
+                name="qwen3.8-27b",
+                use="langchain_openai:ChatOpenAI",
+                model="Qwen/Qwen3.8-27B",
+                api_key="test-key",
+                base_url="http://vllm.example/v1",
+                supports_thinking=False,
+            )
+        ]
+    )
+
+    chat_model = create_chat_model("qwen3.8-27b", thinking_enabled=False, app_config=config)
+    extra_body = _extra_body(chat_model)
+
+    assert extra_body.get("enable_thinking") is False
+    assert extra_body.get("chat_template_kwargs", {}).get("enable_thinking") is False
+
+
+def test_qwen38_thinking_mode_sends_medium_reasoning_effort() -> None:
+    config = AppConfig.model_construct(
+        models=[
+            ModelConfig(
+                name="qwen3.8-27b",
+                use="langchain_openai:ChatOpenAI",
+                model="qwen3.8-27b",
+                api_key="test-key",
+                base_url="http://vllm.example/v1",
+                supports_thinking=True,
+            )
+        ]
+    )
+
+    chat_model = create_chat_model(
+        "qwen3.8-27b",
+        thinking_enabled=True,
+        reasoning_effort="medium",
+        app_config=config,
+    )
+    extra_body = _extra_body(chat_model)
+    kwargs = extra_body.get("chat_template_kwargs") or {}
+
+    assert extra_body.get("enable_thinking") is True
+    assert kwargs.get("enable_thinking") is True
+    assert kwargs.get("reasoning_effort") == "medium"
+
+
+def test_extract_reasoning_reads_vllm_reasoning_field() -> None:
+    from deerflow.models.patched_openai import _extract_reasoning_content
+
+    assert _extract_reasoning_content({"reasoning": "先分析问题"}) == "先分析问题"
+    assert _extract_reasoning_content({"reasoning_content": "逐步推理"}) == "逐步推理"
+    assert _extract_reasoning_content({"content": "答案"}) is None
@@ -264,7 +264,7 @@ ai_writing:
 # 三层覆盖优先级(高->低):
 #   users/{user_id}/memory_config.json > .deer-flow/memory_user_overrides.json > 此处
 memory:
-  enabled: true
+  enabled: false # 临时关闭跨会话记忆（提取/注入/Hindsight 召回与 retain、memory 工具）
  version: v1
  provider: hindsight              # 'builtin' | 'hindsight'(外部 provider 名)
                                   # builtin 始终启用,这里只决定 external 选哪个