增强各厂商思考与采样参数映射，并统一流式推理字段解析。

避免不同接口字段差异导致思考链丢失或采样参数被忽略。

Co-authored-by: Cursor <cursoragent@cursor.com>

src/llm/capabilities.ts

@@ -5,6 +5,7 @@
 
 import {
   applyRejectedGenerationField,
+  forceReasoningEffortNoneWhenTools,
   isToolsReasoningEffortConflictError,
   parseRejectedGenerationField,
 } from "./generation-compat.js";
@@ -186,7 +187,7 @@ async function postChat(
   const tried = new Set<string>();
 
   if (isToolsReasoningEffortConflictError(first.text, first.status)) {
-    retryBody.reasoning_effort = "none";
+    forceReasoningEffortNoneWhenTools(retryBody, config.model);
     tried.add("reasoning_effort_none");
     return postOnce(config, retryBody);
   }

src/llm/client.ts

@@ -148,8 +148,8 @@ export function buildRequestBody(
   applyOpenAiGeneration(body, options?.generation ?? {}, config.model, {
     reasoningEffort: config.reasoningEffort,
   });
-  // 对齐 imyai：带 tools 时强制 none（省略字段网关仍可能注入默认 effort）
-  forceReasoningEffortNoneWhenTools(body);
+  // 对齐 imyai：带 tools 时按型号改写思考参数（非 GLM 强制 none）
+  forceReasoningEffortNoneWhenTools(body, config.model);
 
   if (options?.responseFormat === "json_object") {
     body.response_format = { type: "json_object" };
@@ -231,10 +231,13 @@ function extractMessageParts(message: Record<string, unknown> | undefined): {
       : rawContent == null
         ? null
         : "";
-  const reasoning =
-    typeof message.reasoning_content === "string"
-      ? message.reasoning_content.trim()
-      : undefined;
+  const reasoningRaw =
+    (typeof message.reasoning_content === "string" &&
+      message.reasoning_content.trim()) ||
+    (typeof message.reasoning === "string" && message.reasoning.trim()) ||
+    (typeof message.thinking === "string" && message.thinking.trim()) ||
+    "";
+  const reasoning = reasoningRaw || undefined;
 
   const toolCalls: ParsedToolCall[] = [];
   const rawCalls = message.tool_calls;
@@ -422,8 +425,11 @@ export class OpenAiCompatibleProvider implements LlmProvider {
     if (!parts.content && parts.toolCalls.length === 0 && !parts.reasoning) {
       throw new Error("LLM stream returned empty content and no tool calls");
     }
+    const content =
+      parts.content ??
+      (parts.toolCalls.length === 0 ? parts.reasoning || null : null);
     return {
-      content: parts.content,
+      content,
       toolCalls: parts.toolCalls,
       reasoning: parts.reasoning || undefined,
       usage: parts.usage,

src/llm/generation-compat.ts

@@ -6,8 +6,9 @@ import type { GenerationParameters } from "../types/preset.js";
  * - top_k、min_p、repetition_penalty 不是官方 Chat Completions 字段，默认不发
  * - 推理模型去掉 temperature / top_p / penalty
  * - o 系列与 gpt-5 用 max_completion_tokens
- * - 带 tools 时强制 reasoning_effort=none（gpt-5.6-luna 等网关：省略字段仍会注入默认 effort）
- * - 仍 400 时按错误信息剥掉不支持字段再试；tools+reasoning 冲突则改 none 再试
+ * - GLM：按型号映射 thinking / reasoning_effort（5.3 拒收 none；旧版拒收 effort）
+ * - 带 tools 时：非 GLM 强制 reasoning_effort=none（gpt-5.6-luna 等）；GLM-5.3 保留合法档
+ * - 仍 400 时按错误信息剥掉不支持字段再试；tools+reasoning 冲突则按型号改写再试
  */
 
 const REASONING_EFFORT_VALUES = [
@@ -29,6 +30,17 @@ const REASONING_EFFORT_ALIASES: Record<string, ReasoningEffort> = {
 const VERBOSITY_VALUES = ["low", "medium", "high"] as const;
 type Verbosity = (typeof VERBOSITY_VALUES)[number];
 
+/** GLM 思考参数形态（智谱 / 中转常见型号） */
+export type GlmThinkingKind =
+  /** 非 GLM */
+  | "none"
+  /** 仅 thinking.type，不发 reasoning_effort（glm-4.5/4.6/4.7/5/5.1 等） */
+  | "thinking_only"
+  /** thinking + 完整 effort 枚举（glm-5.2） */
+  | "effort_full"
+  /** 强制思考；effort 仅 low/high/max（glm-5.3） */
+  | "effort_lhm_always_on";
+
 export const STRIPPABLE_GENERATION_FIELDS = new Set([
   "temperature",
   "top_p",
@@ -40,6 +52,7 @@ export const STRIPPABLE_GENERATION_FIELDS = new Set([
   "seed",
   "n",
   "reasoning_effort",
+  "thinking",
   "verbosity",
   "max_tokens",
   "max_completion_tokens",
@@ -82,6 +95,75 @@ export function classifyChatModel(model: string): ChatModelCompat {
   };
 }
 
+/**
+ * 识别 GLM 思考 API 形态。
+ * 名称含 glm 即走 GLM 路径；未知子版默认 thinking_only（不发 effort，避免 400）。
+ */
+export function classifyGlmThinking(model: string): GlmThinkingKind {
+  const id = modelLeaf(model);
+  if (!id.includes("glm")) return "none";
+  // 5.3 / 5.3-flash：不可 disabled，effort ∈ {low,high,max}
+  if (/glm-?5\.3/.test(id)) return "effort_lhm_always_on";
+  // 5.2：可 disabled；effort 枚举较全
+  if (/glm-?5\.2/.test(id)) return "effort_full";
+  return "thinking_only";
+}
+
+function mapGlm53Effort(
+  effort: ReasoningEffort,
+): "low" | "high" | "max" {
+  switch (effort) {
+    case "none":
+    case "minimal":
+    case "low":
+      return "low";
+    case "medium":
+    case "high":
+      return "high";
+    case "xhigh":
+    case "max":
+      return "max";
+  }
+}
+
+/** 把配置的 effort 落到当前模型可接受的 body 字段。 */
+function applyReasoningToBody(
+  body: Record<string, unknown>,
+  model: string,
+  effort: ReasoningEffort | undefined,
+): void {
+  if (effort === undefined) return;
+
+  const glm = classifyGlmThinking(model);
+  if (glm === "none") {
+    body.reasoning_effort = effort;
+    return;
+  }
+
+  if (glm === "effort_lhm_always_on") {
+    body.thinking = { type: "enabled" };
+    body.reasoning_effort = mapGlm53Effort(effort);
+    return;
+  }
+
+  if (glm === "effort_full") {
+    if (effort === "none" || effort === "minimal") {
+      body.thinking = { type: "disabled" };
+      body.reasoning_effort = "none";
+      return;
+    }
+    body.thinking = { type: "enabled" };
+    body.reasoning_effort = effort;
+    return;
+  }
+
+  // thinking_only：旧 GLM 拒收 reasoning_effort
+  body.thinking = {
+    type: effort === "none" || effort === "minimal" ? "disabled" : "enabled",
+  };
+  delete body.reasoning_effort;
+}
+
 export function sanitizeReasoningEffort(
   value: unknown,
 ): ReasoningEffort | undefined {
@@ -148,9 +230,7 @@ export function applyOpenAiGeneration(
   const reasoningEffort =
     sanitizeReasoningEffort(gen.reasoningEffort) ??
     sanitizeReasoningEffort(defaults?.reasoningEffort);
-  if (reasoningEffort !== undefined) {
-    body.reasoning_effort = reasoningEffort;
-  }
+  applyReasoningToBody(body, model, reasoningEffort);
 
   const verbosity = sanitizeVerbosity(gen.verbosity);
   if (verbosity !== undefined && supportsVerbosity) {
@@ -158,12 +238,36 @@ export function applyOpenAiGeneration(
   }
 }
 
-/** chat/completions + function tools 时须显式 none，否则网关可能注入默认 effort 并 400。 */
+/**
+ * 带 function tools 时改写思考参数。
+ * - 非 GLM（如 gpt-5.6-luna）：须显式 reasoning_effort=none
+ * - GLM-5.3：不能 none，保留/压到合法档（默认 low）
+ * - GLM-5.2 / 旧版：thinking disabled，去掉 effort
+ */
 export function forceReasoningEffortNoneWhenTools(
   body: Record<string, unknown>,
+  model?: string,
 ): void {
   const tools = body.tools;
   if (!Array.isArray(tools) || tools.length === 0) return;
+
+  const modelId =
+    (typeof model === "string" && model) ||
+    (typeof body.model === "string" ? body.model : "");
+  const glm = classifyGlmThinking(modelId);
+
+  if (glm === "effort_lhm_always_on") {
+    const current = sanitizeReasoningEffort(body.reasoning_effort) ?? "low";
+    body.thinking = { type: "enabled" };
+    body.reasoning_effort = mapGlm53Effort(current);
+    return;
+  }
+  if (glm === "effort_full" || glm === "thinking_only") {
+    body.thinking = { type: "disabled" };
+    delete body.reasoning_effort;
+    return;
+  }
+
   body.reasoning_effort = "none";
 }
 
@@ -279,17 +383,18 @@ export function applyRejectedGenerationField(
     return true;
   }
 
-  // tools + reasoning_effort 冲突：删字段不够，须显式 none
+  // tools + reasoning_effort 冲突：按型号改写（非 GLM → none；GLM 另处理）
   if (
     field === "reasoning_effort" &&
     Array.isArray(body.tools) &&
     body.tools.length > 0 &&
-    body.reasoning_effort !== "none" &&
     !tried.has("reasoning_effort_none")
   ) {
-    body.reasoning_effort = "none";
+    const before = snapshotThinkingFields(body);
+    forceReasoningEffortNoneWhenTools(body);
     tried.add("reasoning_effort_none");
-    return true;
+    if (snapshotThinkingFields(body) !== before) return true;
+    // 已是目标态仍报错 → 继续往下删字段
   }
 
   if (!(field in body)) return false;
@@ -298,6 +403,13 @@ export function applyRejectedGenerationField(
   return true;
 }
 
+function snapshotThinkingFields(body: Record<string, unknown>): string {
+  return JSON.stringify({
+    reasoning_effort: body.reasoning_effort ?? null,
+    thinking: body.thinking ?? null,
+  });
+}
+
 function applyToolsReasoningEffortNone(
   body: Record<string, unknown>,
   tried: Set<string>,
@@ -305,12 +417,13 @@ function applyToolsReasoningEffortNone(
   if (
     !Array.isArray(body.tools) ||
     body.tools.length === 0 ||
-    body.reasoning_effort === "none" ||
     tried.has("reasoning_effort_none")
   ) {
     return false;
   }
-  body.reasoning_effort = "none";
+  const before = snapshotThinkingFields(body);
+  forceReasoningEffortNoneWhenTools(body);
+  if (snapshotThinkingFields(body) === before) return false;
   tried.add("reasoning_effort_none");
   return true;
 }

src/llm/preset-wrapper.ts

@@ -1,4 +1,5 @@
 import { loadAppSettings } from "../config/settings.js";
+import type { PersonaDirective } from "../persona/store.js";
 import { frameMessagesWithPreset } from "../preset/play-frame.js";
 import { resolveActivePreset } from "../preset/store.js";
 import type { PresetPackage } from "../types/preset.js";
@@ -30,11 +31,12 @@ export function wrapLlmForSession(
   inner: LlmProvider,
   trackingRef?: LlmTrackingRef,
   getPreset: () => PresetPackage | null = readActivePreset,
+  getPersona?: () => PersonaDirective | null,
 ): LlmProvider {
   const tracked = trackingRef
     ? new TokenTrackingProvider(inner, () => trackingRef.current)
     : inner;
-  return new PresetLlmProvider(tracked, getPreset);
+  return new PresetLlmProvider(tracked, getPreset, getPersona);
 }
 
 /** 所有 LLM 请求：preset 夹心 + 生成参数。无选用预设则原样转发。 */
@@ -42,6 +44,7 @@ export class PresetLlmProvider implements LlmProvider {
   constructor(
     private readonly inner: LlmProvider,
     private readonly getPreset: () => PresetPackage | null,
+    private readonly getPersona?: () => PersonaDirective | null,
   ) {}
 
   private prepare(
@@ -50,8 +53,9 @@ export class PresetLlmProvider implements LlmProvider {
   ): { messages: ChatMessage[]; options: CompleteOptions | undefined } {
     const preset = this.getPreset();
     if (!preset) return { messages, options };
+    const persona = this.getPersona ? this.getPersona() : undefined;
     return {
-      messages: frameMessagesWithPreset(preset, messages),
+      messages: frameMessagesWithPreset(preset, messages, persona),
       options: {
         ...options,
         generation: options?.generation ?? preset.generation,

src/llm/stream-complete.ts

@@ -45,6 +45,20 @@ function toolCallsFromAccumulator(acc: ToolCallAccumulator): ParsedToolCall[] {
   return out;
 }
 
+/** DeepSeek `reasoning_content`；部分中转用 `reasoning` / `thinking` */
+function readReasoningDelta(row: Record<string, unknown>): string {
+  for (const key of ["reasoning_content", "reasoning", "thinking"] as const) {
+    const val = row[key];
+    if (typeof val === "string" && val) return val;
+  }
+  return "";
+}
+
+function readContentText(row: Record<string, unknown>): string {
+  const val = row.content;
+  return typeof val === "string" && val ? val : "";
+}
+
 /** 解析 OpenAI 兼容 SSE 流，累积 reasoning / content / tool_calls */
 export async function consumeOpenAiToolStream(
   body: ReadableStream<Uint8Array>,
@@ -91,19 +105,38 @@ export async function consumeOpenAiToolStream(
 
       const choice = (parsed.choices as unknown[])?.[0];
       if (!choice || typeof choice !== "object") continue;
-      const delta = (choice as Record<string, unknown>).delta;
-      if (!delta || typeof delta !== "object") continue;
-      const d = delta as Record<string, unknown>;
-
-      if (typeof d.reasoning_content === "string" && d.reasoning_content) {
-        reasoning += d.reasoning_content;
-        callbacks.onReasoningDelta?.(d.reasoning_content);
+      const row = choice as Record<string, unknown>;
+      const delta = row.delta;
+      const message = row.message;
+      if (delta && typeof delta === "object") {
+        const d = delta as Record<string, unknown>;
+        const think = readReasoningDelta(d);
+        if (think) {
+          reasoning += think;
+          callbacks.onReasoningDelta?.(think);
+        }
+        const chunk = readContentText(d);
+        if (chunk) {
+          content += chunk;
+          callbacks.onContentDelta?.(chunk);
+        }
+        if (d.tool_calls) applyToolCallDelta(toolAcc, d.tool_calls);
       }
-      if (typeof d.content === "string" && d.content) {
-        content += d.content;
-        callbacks.onContentDelta?.(d.content);
+      // 部分中转最后一帧把全文放在 message 而非 delta
+      if (message && typeof message === "object" && !content) {
+        const msg = message as Record<string, unknown>;
+        const think = readReasoningDelta(msg);
+        if (think && !reasoning) {
+          reasoning = think;
+          callbacks.onReasoningDelta?.(think);
+        }
+        const full = readContentText(msg);
+        if (full) {
+          content = full;
+          callbacks.onContentDelta?.(full);
+        }
+        if (msg.tool_calls) applyToolCallDelta(toolAcc, msg.tool_calls);
       }
-      if (d.tool_calls) applyToolCallDelta(toolAcc, d.tool_calls);
     }
   }