【根因(main.log 实证)】 19:04 / 19:05 / 19:06 三次会话终止均为同一报错: DeepSeek 400 "Messages with role 'tool' must be a response to a preceding message with 'tool_calls'" 缺陷链:engine 主循环仅在 step.thought 存在(该轮有文本或思考内容)时才 将 assistant 消息加入请求历史。当模型发起纯工具调用(零文本零思考 — DeepSeek 高频行为)时: - assistant(tool_calls) 消息不进 messages - 但 tool 结果消息照常 push → 下一轮请求出现孤立 tool 消息 → 协议 400(不可重试)→ 会话 ERROR 终止 "不稳定" = 模型每轮是否附带文本是概率性行为:带文本正常,纯调用必崩。 DB 持久化侧同源缺陷(if (!step.thought) continue)导致这些步骤的 assistant 与 tool 结果全部不落库 — 重启后工具上下文丢失,模型重复调用。 【修复】 - engine.ts: 有 toolCalls 的轮次必 push assistant(content=null,C-6 规范) - agent.ts: 持久化条件同步修复(无 thought 但有 toolCalls 的步骤落库) - 回归测试: 纯 tool_calls 轮后第二次请求中 tool 消息前必须是带 tool_calls 的 assistant(请求契约断言,engine-toolchain.test.ts) 【纵深防御 — 孤立 tool 消息过滤】 - openai-format.ts(DeepSeek/Agnes/MiMo/OpenAI 四家共享): 构建请求时 按 tool_call_id 配对过滤孤立 tool 消息(任何来源的历史污染不再 400 死锁) - anthropic.adapter.ts: tool_use/tool_result 同策略配对过滤 - 单测 ×6: 正常配对保留 / 孤立丢弃 / id 不匹配丢弃 / 多轮配对 / includeImages 原位转换 / 非 vision 静默丢弃 【多模态索引对齐收敛】 4 家 adapter 的 images 处理循环原按未过滤的 nonSystemMsgs[i-1] 对齐索引, 孤立 tool 过滤引入后会错位 — 统一收进 buildOpenAICompatibleMessages (includeImages 参数,基于 sanitized 序列原位转换),4 家 adapter 删除 各自的索引对齐循环(DeepSeek vision 判断 / OpenAI 推理模型拒绝保留在 adapter)。 【终止原因可见化】 MAX_ITERATIONS / TIMEOUT 终止此前无任何提示(用户感知"会话直接停止")— 前端 DONE 事件非 completed 终止原因显示为 system 消息。 【v0.6.1 回归缓解】 web_fetch timeoutMs 120s → 240s:浏览器回退串行化后并发 3 个排队最坏 ~127.5s,旧值让排队末位抓取被工具超时杀掉(表现为抓取不稳定)。 【验证】 lint 0/0;typecheck 双工程 0 错误;test:electron 259/259(+7); electron-vite build 成功
248 lines
8.0 KiB
TypeScript
248 lines
8.0 KiB
TypeScript
/**
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* OpenAI Provider Adapter(P3)
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*
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* OpenAI Chat Completions API(/v1/chat/completions),支持 Tool Calling、
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* 流式输出、多模态图片、o 系列推理模型的 reasoning_effort 参数。
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*
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* 与 DeepSeek 适配器的关键差异:
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* - o 系列 / gpt-5 系列模型使用 max_completion_tokens(非 max_tokens)
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* - Thinking 模式通过顶层 reasoning_effort 参数(o 系列模型)
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* - 模型列表从 /v1/models 动态获取
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*
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* @see apis 官方文档 https://platform.openai.com/docs/api-reference/chat
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*/
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import { BaseAdapter } from './base-adapter';
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import type { MetonaRequest, MetonaResponse, MetonaStreamEvent } from '../types';
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import { MetonaFinishReason } from '../types';
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import type { MetonaModelInfo } from '../types/metona-adapter';
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import { buildOpenAICompatibleMessages, buildOpenAICompatibleTools } from './shared/openai-format';
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import { parseSSEStream, parseOpenAICompatibleResponse } from './shared/sse-stream';
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export class OpenAIAdapter extends BaseAdapter {
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override readonly providerId: string = 'openai';
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readonly supportedModels = ['gpt-4o', 'gpt-4o-mini', 'gpt-4.1', 'o3-mini'];
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readonly supportsToolCalling = true;
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readonly supportsThinking = true;
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private static readonly MODEL_INFO: Record<string, MetonaModelInfo> = {
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'gpt-4o': {
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id: 'gpt-4o',
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name: 'GPT-4o',
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contextWindow: 128_000,
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maxOutputTokens: 16_384,
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supportsToolCalling: true,
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supportsThinking: false,
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description: 'OpenAI 旗舰多模态模型,128K 上下文',
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},
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'gpt-4o-mini': {
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id: 'gpt-4o-mini',
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name: 'GPT-4o mini',
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contextWindow: 128_000,
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maxOutputTokens: 16_384,
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supportsToolCalling: true,
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supportsThinking: false,
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description: 'OpenAI 高性价比模型,128K 上下文',
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},
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'gpt-4.1': {
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id: 'gpt-4.1',
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name: 'GPT-4.1',
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contextWindow: 1_000_000,
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maxOutputTokens: 32_768,
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supportsToolCalling: true,
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supportsThinking: false,
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description: 'OpenAI 长上下文模型,1M 上下文',
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},
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'o3-mini': {
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id: 'o3-mini',
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name: 'o3-mini',
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contextWindow: 200_000,
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maxOutputTokens: 100_000,
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supportsToolCalling: true,
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supportsThinking: true,
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description: 'OpenAI 推理模型,支持 reasoning_effort',
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},
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};
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// ===== POST /v1/chat/completions(非流式) =====
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async send(request: MetonaRequest): Promise<MetonaResponse> {
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const body = this.toNativeRequest(request, false);
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const response = await this.fetchWithTimeout(
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`${this.config.baseURL}/chat/completions`,
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{
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${this.config.apiKey}`,
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...this.config.headers,
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},
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body: JSON.stringify(body),
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},
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this.config.timeoutMs ?? 120_000,
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);
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if (!response.ok) {
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await this.throwHttpError(response, 'OpenAI API error');
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}
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const data = (await response.json()) as Record<string, unknown>;
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const parsed = parseOpenAICompatibleResponse(data);
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return {
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meta: {
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requestId: request.meta.requestId,
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provider: this.providerId,
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model: (data.model as string) ?? this.config.defaultModel,
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latencyMs: 0,
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timestamp: Date.now(),
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},
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content: parsed.content,
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reasoningContent: parsed.reasoningContent,
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toolCalls: parsed.toolCalls,
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usage: parsed.usage,
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finishReason: parsed.finishReason as MetonaFinishReason,
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};
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}
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// ===== POST /v1/chat/completions(流式) =====
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async *sendStream(request: MetonaRequest): AsyncIterable<MetonaStreamEvent> {
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const body = this.toNativeRequest(request, true);
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const response = await this.fetchWithTimeout(
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`${this.config.baseURL}/chat/completions`,
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{
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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Authorization: `Bearer ${this.config.apiKey}`,
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...this.config.headers,
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},
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body: JSON.stringify(body),
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},
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this.config.timeoutMs ?? 300_000,
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);
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if (!response.ok || !response.body) {
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await this.throwHttpError(response, 'OpenAI stream error');
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}
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yield* parseSSEStream(
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// 非空断言:上方 if 已确保 response.body 不为 null
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response.body!,
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request.meta.requestId,
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request.meta.sessionId,
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request.meta.iteration,
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);
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}
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// ===== GET /v1/models =====
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override async listModels(): Promise<MetonaModelInfo[]> {
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try {
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const response = await fetch(`${this.config.baseURL}/models`, {
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headers: { Authorization: `Bearer ${this.config.apiKey}` },
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signal: AbortSignal.timeout(10_000),
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});
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if (response.ok) {
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const data = (await response.json()) as { data?: Array<{ id: string }> };
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if (data.data?.length) {
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return data.data.map((m) => OpenAIAdapter.MODEL_INFO[m.id] ?? { id: m.id });
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}
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}
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} catch {
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// API 不可用时降级
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}
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return this.supportedModels.map((id) => OpenAIAdapter.MODEL_INFO[id] ?? { id });
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}
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override getContextWindow(): number {
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if (typeof this.config.contextWindow === 'number' && this.config.contextWindow > 0) {
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return this.config.contextWindow;
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}
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const modelInfo = OpenAIAdapter.MODEL_INFO[this.config.defaultModel];
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return modelInfo?.contextWindow ?? 128_000;
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}
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// ========== 私有方法 ==========
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/**
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* 构建 OpenAI 原生请求体
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*
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* OpenAI 特有处理:
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* - 多模态图片:user 消息 images[] → content 数组
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* - o 系列(o1/o3/o4)与 gpt-5 系列使用 max_completion_tokens + reasoning_effort
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* - 思考模式下 temperature 被部分推理模型拒绝,不传
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*/
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private toNativeRequest(request: MetonaRequest, stream: boolean): Record<string, unknown> {
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// 推理模型检测(o 系列使用新参数名)
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const model = this.config.defaultModel;
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const isReasoningModel = /^(o\d|gpt-5)/.test(model);
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// 推理模型不支持图片输入 — 前置校验(转换在共享层,此处仅拦截)
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if (isReasoningModel) {
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const hasImages = request.messages.some((m) => m.images?.length);
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if (hasImages) {
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throw new Error(`Model "${model}" does not support image inputs`);
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}
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}
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// v0.6.2: images 处理收敛至共享层(原索引对齐循环在孤立 tool 过滤后会错位)
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const messages = buildOpenAICompatibleMessages(request, true);
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const tools = buildOpenAICompatibleTools(request.tools);
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const body: Record<string, unknown> = {
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model,
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messages,
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stream,
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};
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// Token 上限参数:o 系列/gpt-5 使用 max_completion_tokens
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// v0.5.3: 按模型上限钳制(gpt-4o 16384 / gpt-4.1 32768 / o3-mini 100000)—
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// 引擎默认 63488 超过 gpt-4o/gpt-4.1 上限时 API 直接 400
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const oaMaxOutput = OpenAIAdapter.MODEL_INFO[model]?.maxOutputTokens ?? 128_000;
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const oaMaxTokens = Math.min(
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request.params.maxTokens ?? (isReasoningModel ? 32_768 : oaMaxOutput),
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oaMaxOutput,
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);
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if (oaMaxTokens) {
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if (isReasoningModel) {
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body.max_completion_tokens = oaMaxTokens;
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} else {
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body.max_tokens = oaMaxTokens;
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}
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}
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if (stream) {
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body.stream_options = { include_usage: true };
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}
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if (tools) {
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body.tools = tools;
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}
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// Thinking 模式:推理模型映射 reasoning_effort;非推理模型忽略
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if (request.params.thinkingEnabled && isReasoningModel) {
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const effortMap: Record<string, string> = {
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low: 'low',
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medium: 'medium',
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high: 'high',
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max: 'high',
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};
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body.reasoning_effort = effortMap[request.params.thinkingEffort ?? 'high'] ?? 'high';
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} else if (!isReasoningModel) {
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// 非推理模型使用温度控制
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body.temperature = request.params.temperature;
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}
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// 停止序列
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if (request.params.stopSequences?.length) {
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body.stop = request.params.stopSequences;
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}
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return body;
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}
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}
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