55879396c8
- 在 CodexConverter 和 ClaudeConverter 中增加 metadata 字段，透传上游元数据 - 重构 CodexApiService 的缓存键生成逻辑，优先使用 session_id 或 conversation_id - 从上游请求体中移除 metadata 避免透传，仅用于生成缓存键
1219 lines
44 KiB
JavaScript
1219 lines
44 KiB
JavaScript
/**
|
||
* Codex 转换器
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* 处理 OpenAI 协议与 Codex 协议之间的转换
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*/
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import { v4 as uuidv4 } from 'uuid';
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import { BaseConverter } from '../BaseConverter.js';
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import { MODEL_PROTOCOL_PREFIX } from '../../utils/common.js';
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import {
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generateResponseCreated,
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generateResponseInProgress,
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generateOutputItemAdded,
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generateContentPartAdded,
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generateOutputTextDone,
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generateContentPartDone,
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generateOutputItemDone,
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generateResponseCompleted
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} from '../../providers/openai/openai-responses-core.mjs';
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export class CodexConverter extends BaseConverter {
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constructor() {
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super('codex');
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this.toolNameMap = new Map(); // 工具名称缩短映射: original -> short
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this.reverseToolNameMap = new Map(); // 反向映射: short -> original
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this.streamParams = new Map(); // 用于存储流式状态，key 为响应 ID 或临时标识
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}
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/**
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* 转换请求
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*/
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convertRequest(data, targetProtocol) {
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throw new Error(`Unsupported target protocol: ${targetProtocol}`);
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}
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/**
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* 转换响应
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*/
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convertResponse(data, targetProtocol, model) {
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switch (targetProtocol) {
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case MODEL_PROTOCOL_PREFIX.OPENAI:
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return this.toOpenAIResponse(data, model);
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case MODEL_PROTOCOL_PREFIX.OPENAI_RESPONSES:
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return this.toOpenAIResponsesResponse(data, model);
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case MODEL_PROTOCOL_PREFIX.GEMINI:
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return this.toGeminiResponse(data, model);
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case MODEL_PROTOCOL_PREFIX.CLAUDE:
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return this.toClaudeResponse(data, model);
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case MODEL_PROTOCOL_PREFIX.CODEX:
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return data; // Codex to Codex
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default:
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throw new Error(`Unsupported target protocol: ${targetProtocol}`);
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}
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}
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/**
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* 转换流式响应块
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*/
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convertStreamChunk(chunk, targetProtocol, model) {
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switch (targetProtocol) {
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case MODEL_PROTOCOL_PREFIX.OPENAI:
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return this.toOpenAIStreamChunk(chunk, model);
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case MODEL_PROTOCOL_PREFIX.OPENAI_RESPONSES:
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return this.toOpenAIResponsesStreamChunk(chunk, model);
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case MODEL_PROTOCOL_PREFIX.GEMINI:
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return this.toGeminiStreamChunk(chunk, model);
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case MODEL_PROTOCOL_PREFIX.CLAUDE:
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return this.toClaudeStreamChunk(chunk, model);
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case MODEL_PROTOCOL_PREFIX.CODEX:
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return chunk; // Codex to Codex
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default:
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throw new Error(`Unsupported target protocol: ${targetProtocol}`);
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}
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}
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/**
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* 转换模型列表
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*/
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convertModelList(data, targetProtocol) {
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return data;
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}
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/**
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* OpenAI Responses → Codex 请求转换
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*/
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toOpenAIResponsesToCodexRequest(responsesRequest) {
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let codexRequest = { ...responsesRequest };
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// 处理 input 字段，如果它是字符串，则转换为消息数组
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if (codexRequest.input && typeof codexRequest.input === 'string') {
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const inputText = codexRequest.input;
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codexRequest.input = [{
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type: "message",
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role: "user",
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content: [{
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type: "input_text",
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text: inputText
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}]
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}];
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}
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// 设置Codex特定的字段
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codexRequest.stream = true;
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codexRequest.store = false;
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codexRequest.parallel_tool_calls = true;
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codexRequest.include = ['reasoning.encrypted_content'];
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// 删除Codex不支持的字段
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delete codexRequest.max_output_tokens;
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delete codexRequest.max_completion_tokens;
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delete codexRequest.temperature;
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delete codexRequest.top_p;
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delete codexRequest.service_tier;
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delete codexRequest.user;
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delete codexRequest.reasoning;
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// 添加 reasoning 配置
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codexRequest.reasoning = {
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"effort": "medium",
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"summary": "auto"
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};
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// 确保 input 数组中的每个项都有 type: "message"，并将系统角色转换为开发者角色
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if (codexRequest.input && Array.isArray(codexRequest.input)) {
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codexRequest.input = codexRequest.input.map(item => {
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// 如果没有 type 或者 type 不是 message，则添加 type: "message"
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if (!item.type || item.type !== 'message') {
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item = { type: "message", ...item };
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}
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// 将系统角色转换为开发者角色
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if (item.role === 'system') {
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item = { ...item, role: 'developer' };
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}
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return item;
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});
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}
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return codexRequest;
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}
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/**
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* OpenAI → Codex 请求转换
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*/
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toOpenAIRequestToCodexRequest(data) {
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// 构建工具名称映射
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this.buildToolNameMap(data.tools || []);
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const codexRequest = {
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model: data.model,
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instructions: this.buildInstructions(data),
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input: this.convertMessages(data.messages || []),
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stream: true,
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store: false,
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metadata: data.metadata || {},
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reasoning: {
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effort: data.reasoning_effort || 'medium',
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summary: 'auto'
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},
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parallel_tool_calls: true,
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include: ['reasoning.encrypted_content']
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};
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// 处理 OpenAI Responses 特有的 instructions 和 input 字段（如果存在）
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if (data.instructions && !codexRequest.instructions) {
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codexRequest.instructions = data.instructions;
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}
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if (data.input && Array.isArray(data.input) && codexRequest.input.length === 0) {
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// 如果是 OpenAI Responses 格式的 input
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for (const item of data.input) {
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if (item.type === 'message') {
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codexRequest.input.push({
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type: 'message',
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role: item.role === 'system' ? 'developer' : item.role,
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content: Array.isArray(item.content) ? item.content.map(c => ({
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type: item.role === 'assistant' ? 'output_text' : 'input_text',
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text: c.text
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})) : [{
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type: item.role === 'assistant' ? 'output_text' : 'input_text',
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text: item.content
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}]
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});
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}
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}
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}
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if (data.tools && data.tools.length > 0) {
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codexRequest.tools = this.convertTools(data.tools);
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}
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if (data.tool_choice) {
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codexRequest.tool_choice = this.convertToolChoice(data.tool_choice);
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}
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if (data.response_format || data.text?.verbosity) {
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const textObj = {};
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if (data.response_format) {
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textObj.format = this.convertResponseFormat(data.response_format);
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}
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if (data.text?.verbosity) {
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textObj.verbosity = data.text.verbosity;
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}
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codexRequest.text = textObj;
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}
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// 在 input 开头注入特殊指令（如果配置允许）
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// 这里我们默认开启，因为这是为了确保 Codex 遵循指令
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if (codexRequest.input.length > 0 && codexRequest.instructions) {
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const firstMsg = codexRequest.input[0];
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const specialInstruction = "EXECUTE ACCORDING TO THE FOLLOWING INSTRUCTIONS!!!";
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const firstText = firstMsg.content?.[0]?.text;
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if (firstMsg.role === 'user' && firstText !== specialInstruction) {
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codexRequest.input.unshift({
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type: "message",
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role: "user",
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content: [{
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type: "input_text",
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text: specialInstruction
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}]
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});
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}
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}
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return codexRequest;
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}
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/**
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* 构建指令
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*/
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buildInstructions(data) {
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// 首先检查显式的 instructions 字段 (OpenAI Responses)
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if (data.instructions) return data.instructions;
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const systemMessages = (data.messages || []).filter(m => m.role === 'system');
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if (systemMessages.length > 0) {
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return systemMessages.map(m => {
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if (typeof m.content === 'string') {
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return m.content;
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} else if (Array.isArray(m.content)) {
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const textPart = m.content.find(part => part.type === 'text');
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return textPart ? textPart.text : '';
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}
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return '';
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}).join('\n').trim();
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}
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return '';
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}
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/**
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* 转换消息
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*/
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convertMessages(messages) {
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const input = [];
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for (const msg of messages) {
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const role = msg.role;
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if (role === 'tool' || role === 'tool_result') {
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input.push({
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type: 'function_call_output',
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call_id: msg.tool_call_id || msg.tool_use_id,
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output: typeof msg.content === 'string' ? msg.content : JSON.stringify(msg.content)
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});
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} else {
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const codexMsg = {
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type: 'message',
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role: role === 'system' ? 'developer' : (role === 'model' ? 'assistant' : role),
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content: this.convertMessageContent(msg.content, role)
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};
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if (codexMsg.content.length > 0) {
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input.push(codexMsg);
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}
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if ((role === 'assistant' || role === 'model') && msg.tool_calls) {
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for (const toolCall of msg.tool_calls) {
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if (toolCall.type === 'function' || toolCall.function) {
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const func = toolCall.function || toolCall;
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const originalName = func.name;
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const shortName = this.toolNameMap.get(originalName) || this.shortenToolName(originalName);
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input.push({
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type: 'function_call',
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call_id: toolCall.id,
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name: shortName,
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arguments: typeof func.arguments === 'string' ? func.arguments : JSON.stringify(func.arguments)
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});
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}
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}
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||
}
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||
|
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// 处理 Claude 格式的 tool_use
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if (role === 'assistant' && Array.isArray(msg.content)) {
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for (const part of msg.content) {
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if (part.type === 'tool_use') {
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const originalName = part.name;
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const shortName = this.toolNameMap.get(originalName) || this.shortenToolName(originalName);
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input.push({
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type: 'function_call',
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call_id: part.id,
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||
name: shortName,
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||
arguments: typeof part.input === 'string' ? part.input : JSON.stringify(part.input)
|
||
});
|
||
}
|
||
}
|
||
}
|
||
}
|
||
}
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||
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return input;
|
||
}
|
||
|
||
/**
|
||
* 转换消息内容
|
||
*/
|
||
convertMessageContent(content, role) {
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if (!content) return [];
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||
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||
const isAssistant = role === 'assistant' || role === 'model';
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||
|
||
if (typeof content === 'string') {
|
||
return [{
|
||
type: isAssistant ? 'output_text' : 'input_text',
|
||
text: content
|
||
}];
|
||
}
|
||
|
||
if (Array.isArray(content)) {
|
||
return content.map(part => {
|
||
if (typeof part === 'string') {
|
||
return {
|
||
type: isAssistant ? 'output_text' : 'input_text',
|
||
text: part
|
||
};
|
||
}
|
||
if (part.type === 'text') {
|
||
return {
|
||
type: isAssistant ? 'output_text' : 'input_text',
|
||
text: part.text
|
||
};
|
||
} else if ((part.type === 'image_url' || part.type === 'image') && !isAssistant) {
|
||
let url = '';
|
||
if (part.image_url) {
|
||
url = typeof part.image_url === 'string' ? part.image_url : part.image_url.url;
|
||
} else if (part.source && part.source.type === 'base64') {
|
||
url = `data:${part.source.media_type};base64,${part.source.data}`;
|
||
}
|
||
return url ? {
|
||
type: 'input_image',
|
||
image_url: url
|
||
} : null;
|
||
}
|
||
return null;
|
||
}).filter(Boolean);
|
||
}
|
||
|
||
return [];
|
||
}
|
||
|
||
/**
|
||
* 构建工具名称映射
|
||
*/
|
||
buildToolNameMap(tools) {
|
||
this.toolNameMap.clear();
|
||
this.reverseToolNameMap.clear();
|
||
|
||
const names = [];
|
||
for (const t of tools) {
|
||
if (t.type === 'function' && t.function?.name) {
|
||
names.push(t.function.name);
|
||
} else if (t.name) {
|
||
names.push(t.name);
|
||
}
|
||
}
|
||
|
||
if (names.length === 0) return;
|
||
|
||
const limit = 64;
|
||
const used = new Set();
|
||
|
||
const baseCandidate = (n) => {
|
||
if (n.length <= limit) return n;
|
||
if (n.startsWith('mcp__')) {
|
||
const idx = n.lastIndexOf('__');
|
||
if (idx > 0) {
|
||
let cand = 'mcp__' + n.slice(idx + 2);
|
||
return cand.length > limit ? cand.slice(0, limit) : cand;
|
||
}
|
||
}
|
||
return n.slice(0, limit);
|
||
};
|
||
|
||
for (const n of names) {
|
||
let cand = baseCandidate(n);
|
||
let uniq = cand;
|
||
if (used.has(uniq)) {
|
||
for (let i = 1; ; i++) {
|
||
const suffix = '_' + i;
|
||
const allowed = limit - suffix.length;
|
||
const base = cand.slice(0, Math.max(0, allowed));
|
||
const tmp = base + suffix;
|
||
if (!used.has(tmp)) {
|
||
uniq = tmp;
|
||
break;
|
||
}
|
||
}
|
||
}
|
||
used.add(uniq);
|
||
this.toolNameMap.set(n, uniq);
|
||
this.reverseToolNameMap.set(uniq, n);
|
||
}
|
||
}
|
||
|
||
/**
|
||
* 转换工具
|
||
*/
|
||
convertTools(tools) {
|
||
return tools.map(tool => {
|
||
// 处理 Claude 的 web_search
|
||
if (tool.type === "web_search_20250305") {
|
||
return { type: "web_search" };
|
||
}
|
||
|
||
if (tool.type !== 'function' && !tool.name) {
|
||
return tool;
|
||
}
|
||
|
||
const func = tool.function || tool;
|
||
const originalName = func.name;
|
||
const shortName = this.toolNameMap.get(originalName) || this.shortenToolName(originalName);
|
||
|
||
const result = {
|
||
type: 'function',
|
||
name: shortName,
|
||
description: func.description,
|
||
parameters: func.parameters || func.input_schema || { type: 'object', properties: {} },
|
||
strict: func.strict !== undefined ? func.strict : false
|
||
};
|
||
|
||
// 清理参数
|
||
if (result.parameters && result.parameters.$schema) {
|
||
delete result.parameters.$schema;
|
||
}
|
||
|
||
return result;
|
||
});
|
||
}
|
||
|
||
/**
|
||
* 转换 tool_choice
|
||
*/
|
||
convertToolChoice(toolChoice) {
|
||
if (typeof toolChoice === 'string') {
|
||
return toolChoice;
|
||
}
|
||
|
||
if (toolChoice.type === 'function') {
|
||
const name = toolChoice.function?.name;
|
||
const shortName = name ? (this.toolNameMap.get(name) || this.shortenToolName(name)) : '';
|
||
return {
|
||
type: 'function',
|
||
name: shortName
|
||
};
|
||
}
|
||
|
||
return toolChoice;
|
||
}
|
||
|
||
/**
|
||
* 缩短工具名称
|
||
*/
|
||
shortenToolName(name) {
|
||
const limit = 64;
|
||
if (name.length <= limit) return name;
|
||
if (name.startsWith('mcp__')) {
|
||
const idx = name.lastIndexOf('__');
|
||
if (idx > 0) {
|
||
let cand = 'mcp__' + name.slice(idx + 2);
|
||
return cand.length > limit ? cand.slice(0, limit) : cand;
|
||
}
|
||
}
|
||
return name.slice(0, limit);
|
||
}
|
||
|
||
/**
|
||
* 获取原始工具名称
|
||
*/
|
||
getOriginalToolName(shortName) {
|
||
return this.reverseToolNameMap.get(shortName) || shortName;
|
||
}
|
||
|
||
/**
|
||
* 转换响应格式
|
||
*/
|
||
convertResponseFormat(responseFormat) {
|
||
if (responseFormat.type === 'json_schema') {
|
||
return {
|
||
type: 'json_schema',
|
||
name: responseFormat.json_schema?.name || 'response',
|
||
schema: responseFormat.json_schema?.schema || {}
|
||
};
|
||
} else if (responseFormat.type === 'json_object') {
|
||
return {
|
||
type: 'json_object'
|
||
};
|
||
}
|
||
return responseFormat;
|
||
}
|
||
|
||
/**
|
||
* Codex → OpenAI 响应转换（非流式）
|
||
*/
|
||
toOpenAIResponse(rawJSON, model) {
|
||
const root = typeof rawJSON === 'string' ? JSON.parse(rawJSON) : rawJSON;
|
||
if (root.type !== 'response.completed') {
|
||
return null;
|
||
}
|
||
|
||
const response = root.response;
|
||
const unixTimestamp = response.created_at || Math.floor(Date.now() / 1000);
|
||
|
||
const openaiResponse = {
|
||
id: response.id || `chatcmpl-${Date.now()}`,
|
||
object: 'chat.completion',
|
||
created: unixTimestamp,
|
||
model: response.model || model,
|
||
choices: [{
|
||
index: 0,
|
||
message: {
|
||
role: 'assistant',
|
||
content: null,
|
||
reasoning_content: null,
|
||
tool_calls: null
|
||
},
|
||
finish_reason: null,
|
||
native_finish_reason: null
|
||
}],
|
||
usage: {
|
||
prompt_tokens: response.usage?.input_tokens || 0,
|
||
completion_tokens: response.usage?.output_tokens || 0,
|
||
total_tokens: response.usage?.total_tokens || 0
|
||
}
|
||
};
|
||
|
||
if (response.usage?.output_tokens_details?.reasoning_tokens) {
|
||
openaiResponse.usage.completion_tokens_details = {
|
||
reasoning_tokens: response.usage.output_tokens_details.reasoning_tokens
|
||
};
|
||
}
|
||
|
||
const output = response.output || [];
|
||
let contentText = '';
|
||
let reasoningText = '';
|
||
const toolCalls = [];
|
||
|
||
for (const item of output) {
|
||
switch (item.type) {
|
||
case 'reasoning':
|
||
if (Array.isArray(item.summary)) {
|
||
const summaryItem = item.summary.find(s => s.type === 'summary_text');
|
||
if (summaryItem) reasoningText = summaryItem.text;
|
||
}
|
||
break;
|
||
case 'message':
|
||
if (Array.isArray(item.content)) {
|
||
const contentItem = item.content.find(c => c.type === 'output_text');
|
||
if (contentItem) contentText = contentItem.text;
|
||
}
|
||
break;
|
||
case 'function_call':
|
||
toolCalls.push({
|
||
id: item.call_id || `call_${Date.now()}_${toolCalls.length}`,
|
||
type: 'function',
|
||
function: {
|
||
name: this.getOriginalToolName(item.name),
|
||
arguments: typeof item.arguments === 'string' ? item.arguments : JSON.stringify(item.arguments)
|
||
}
|
||
});
|
||
break;
|
||
}
|
||
}
|
||
|
||
if (contentText) openaiResponse.choices[0].message.content = contentText;
|
||
if (reasoningText) openaiResponse.choices[0].message.reasoning_content = reasoningText;
|
||
if (toolCalls.length > 0) openaiResponse.choices[0].message.tool_calls = toolCalls;
|
||
|
||
if (response.status === 'completed') {
|
||
openaiResponse.choices[0].finish_reason = toolCalls.length > 0 ? 'tool_calls' : 'stop';
|
||
openaiResponse.choices[0].native_finish_reason = 'stop';
|
||
}
|
||
|
||
return openaiResponse;
|
||
}
|
||
|
||
/**
|
||
* Codex → OpenAI Responses 响应转换
|
||
*/
|
||
toOpenAIResponsesResponse(rawJSON, model) {
|
||
const root = typeof rawJSON === 'string' ? JSON.parse(rawJSON) : rawJSON;
|
||
if (root.type !== 'response.completed') {
|
||
return null;
|
||
}
|
||
|
||
const response = root.response;
|
||
const unixTimestamp = response.created_at || Math.floor(Date.now() / 1000);
|
||
|
||
const output = [];
|
||
|
||
if (response.output && Array.isArray(response.output)) {
|
||
for (const item of response.output) {
|
||
if (item.type === 'reasoning') {
|
||
let reasoningText = '';
|
||
if (Array.isArray(item.summary)) {
|
||
const summaryItem = item.summary.find(s => s.type === 'summary_text');
|
||
if (summaryItem) reasoningText = summaryItem.text;
|
||
}
|
||
if (reasoningText) {
|
||
output.push({
|
||
id: `msg_${uuidv4().replace(/-/g, '')}`,
|
||
type: "message",
|
||
role: "assistant",
|
||
status: "completed",
|
||
content: [{
|
||
type: "reasoning",
|
||
text: reasoningText
|
||
}]
|
||
});
|
||
}
|
||
} else if (item.type === 'message') {
|
||
let contentText = '';
|
||
if (Array.isArray(item.content)) {
|
||
const contentItem = item.content.find(c => c.type === 'output_text');
|
||
if (contentItem) contentText = contentItem.text;
|
||
}
|
||
if (contentText) {
|
||
output.push({
|
||
id: `msg_${uuidv4().replace(/-/g, '')}`,
|
||
type: "message",
|
||
role: "assistant",
|
||
status: "completed",
|
||
content: [{
|
||
type: "output_text",
|
||
text: contentText,
|
||
annotations: []
|
||
}]
|
||
});
|
||
}
|
||
} else if (item.type === 'function_call') {
|
||
output.push({
|
||
id: item.call_id || `call_${uuidv4().replace(/-/g, '')}`,
|
||
type: "function_call",
|
||
name: this.getOriginalToolName(item.name),
|
||
arguments: typeof item.arguments === 'string' ? item.arguments : JSON.stringify(item.arguments),
|
||
status: "completed"
|
||
});
|
||
}
|
||
}
|
||
}
|
||
|
||
return {
|
||
id: response.id || `resp_${uuidv4().replace(/-/g, '')}`,
|
||
object: "response",
|
||
created_at: unixTimestamp,
|
||
model: response.model || model,
|
||
status: "completed",
|
||
output: output,
|
||
incomplete_details: response.incomplete_details || null,
|
||
usage: {
|
||
input_tokens: response.usage?.input_tokens || 0,
|
||
output_tokens: response.usage?.output_tokens || 0,
|
||
total_tokens: response.usage?.total_tokens || 0,
|
||
output_tokens_details: {
|
||
reasoning_tokens: response.usage?.output_tokens_details?.reasoning_tokens || 0
|
||
}
|
||
}
|
||
};
|
||
}
|
||
|
||
/**
|
||
* Codex → Gemini 响应转换
|
||
*/
|
||
toGeminiResponse(rawJSON, model) {
|
||
const root = typeof rawJSON === 'string' ? JSON.parse(rawJSON) : rawJSON;
|
||
if (root.type !== 'response.completed') {
|
||
return null;
|
||
}
|
||
|
||
const response = root.response;
|
||
const parts = [];
|
||
|
||
if (response.output && Array.isArray(response.output)) {
|
||
for (const item of response.output) {
|
||
if (item.type === 'reasoning') {
|
||
let reasoningText = '';
|
||
if (Array.isArray(item.summary)) {
|
||
const summaryItem = item.summary.find(s => s.type === 'summary_text');
|
||
if (summaryItem) reasoningText = summaryItem.text;
|
||
}
|
||
if (reasoningText) {
|
||
parts.push({ text: reasoningText, thought: true });
|
||
}
|
||
} else if (item.type === 'message') {
|
||
let contentText = '';
|
||
if (Array.isArray(item.content)) {
|
||
const contentItem = item.content.find(c => c.type === 'output_text');
|
||
if (contentItem) contentText = contentItem.text;
|
||
}
|
||
if (contentText) {
|
||
parts.push({ text: contentText });
|
||
}
|
||
} else if (item.type === 'function_call') {
|
||
parts.push({
|
||
functionCall: {
|
||
name: this.getOriginalToolName(item.name),
|
||
args: typeof item.arguments === 'string' ? JSON.parse(item.arguments) : item.arguments
|
||
}
|
||
});
|
||
}
|
||
}
|
||
}
|
||
|
||
return {
|
||
candidates: [{
|
||
content: {
|
||
role: "model",
|
||
parts: parts
|
||
},
|
||
finishReason: "STOP"
|
||
}],
|
||
usageMetadata: {
|
||
promptTokenCount: response.usage?.input_tokens || 0,
|
||
candidatesTokenCount: response.usage?.output_tokens || 0,
|
||
totalTokenCount: response.usage?.total_tokens || 0
|
||
},
|
||
modelVersion: response.model || model,
|
||
responseId: response.id
|
||
};
|
||
}
|
||
|
||
/**
|
||
* Codex → Claude 响应转换
|
||
*/
|
||
toClaudeResponse(rawJSON, model) {
|
||
const root = typeof rawJSON === 'string' ? JSON.parse(rawJSON) : rawJSON;
|
||
if (root.type !== 'response.completed') {
|
||
return null;
|
||
}
|
||
|
||
const response = root.response;
|
||
const content = [];
|
||
let stopReason = "end_turn";
|
||
|
||
if (response.output && Array.isArray(response.output)) {
|
||
for (const item of response.output) {
|
||
if (item.type === 'reasoning') {
|
||
let reasoningText = '';
|
||
if (Array.isArray(item.summary)) {
|
||
const summaryItem = item.summary.find(s => s.type === 'summary_text');
|
||
if (summaryItem) reasoningText = summaryItem.text;
|
||
}
|
||
if (reasoningText) {
|
||
content.push({ type: "thinking", thinking: reasoningText });
|
||
}
|
||
} else if (item.type === 'message') {
|
||
let contentText = '';
|
||
if (Array.isArray(item.content)) {
|
||
const contentItem = item.content.find(c => c.type === 'output_text');
|
||
if (contentItem) contentText = contentItem.text;
|
||
}
|
||
if (contentText) {
|
||
content.push({ type: "text", text: contentText });
|
||
}
|
||
} else if (item.type === 'function_call') {
|
||
stopReason = "tool_use";
|
||
content.push({
|
||
type: "tool_use",
|
||
id: item.call_id || `call_${uuidv4().replace(/-/g, '')}`,
|
||
name: this.getOriginalToolName(item.name),
|
||
input: typeof item.arguments === 'string' ? JSON.parse(item.arguments) : item.arguments
|
||
});
|
||
}
|
||
}
|
||
}
|
||
|
||
return {
|
||
id: response.id || `msg_${uuidv4().replace(/-/g, '')}`,
|
||
type: "message",
|
||
role: "assistant",
|
||
model: response.model || model,
|
||
content: content,
|
||
stop_reason: stopReason,
|
||
usage: {
|
||
input_tokens: response.usage?.input_tokens || 0,
|
||
output_tokens: response.usage?.output_tokens || 0
|
||
}
|
||
};
|
||
}
|
||
|
||
/**
|
||
* Codex → OpenAI 流式响应块转换
|
||
*/
|
||
toOpenAIStreamChunk(chunk, model) {
|
||
const type = chunk.type;
|
||
// 使用固定的 key 来存储当前流的状态
|
||
const stateKey = 'openai_stream_current';
|
||
|
||
if (!this.streamParams.has(stateKey)) {
|
||
this.streamParams.set(stateKey, {
|
||
model: model,
|
||
createdAt: Math.floor(Date.now() / 1000),
|
||
responseID: chunk.response?.id || `chatcmpl-${Date.now()}`,
|
||
functionCallIndex: 0, // 初始值为 0，第一个 function_call 的 index 为 0
|
||
isFirstChunk: true // 标记是否是第一个内容 chunk
|
||
});
|
||
}
|
||
const state = this.streamParams.get(stateKey);
|
||
|
||
// 构建模板时使用当前状态中的值
|
||
const buildTemplate = () => ({
|
||
id: state.responseID,
|
||
object: 'chat.completion.chunk',
|
||
created: state.createdAt,
|
||
model: state.model,
|
||
choices: [{
|
||
index: 0,
|
||
delta: {
|
||
role: 'assistant',
|
||
content: null,
|
||
reasoning_content: null,
|
||
tool_calls: null
|
||
},
|
||
finish_reason: null,
|
||
native_finish_reason: null
|
||
}]
|
||
});
|
||
|
||
if (type === 'response.created') {
|
||
// 更新状态中的 responseID
|
||
state.responseID = chunk.response.id;
|
||
state.createdAt = chunk.response.created_at || state.createdAt;
|
||
state.model = chunk.response.model || state.model;
|
||
// 重置 functionCallIndex，确保每个新请求从 0 开始
|
||
state.functionCallIndex = 0;
|
||
state.isFirstChunk = true;
|
||
// response.created 不发送 chunk，等待第一个内容 chunk
|
||
return null;
|
||
}
|
||
|
||
if (type === 'response.reasoning_summary_text.delta') {
|
||
const results = [];
|
||
// 如果是第一个内容 chunk，先发送带 role 的 chunk
|
||
if (state.isFirstChunk) {
|
||
const firstTemplate = buildTemplate();
|
||
firstTemplate.choices[0].delta = {
|
||
role: 'assistant',
|
||
content: null,
|
||
reasoning_content: chunk.delta,
|
||
tool_calls: null
|
||
};
|
||
results.push(firstTemplate);
|
||
state.isFirstChunk = false;
|
||
} else {
|
||
const template = buildTemplate();
|
||
template.choices[0].delta = {
|
||
role: 'assistant',
|
||
content: null,
|
||
reasoning_content: chunk.delta,
|
||
tool_calls: null
|
||
};
|
||
results.push(template);
|
||
}
|
||
return results.length === 1 ? results[0] : results;
|
||
}
|
||
|
||
if (type === 'response.reasoning_summary_text.done') {
|
||
const template = buildTemplate();
|
||
template.choices[0].delta = {
|
||
role: 'assistant',
|
||
content: null,
|
||
reasoning_content: '\n\n',
|
||
tool_calls: null
|
||
};
|
||
return template;
|
||
}
|
||
|
||
if (type === 'response.output_text.delta') {
|
||
const results = [];
|
||
// 如果是第一个内容 chunk，先发送带 role 的 chunk
|
||
if (state.isFirstChunk) {
|
||
const firstTemplate = buildTemplate();
|
||
firstTemplate.choices[0].delta = {
|
||
role: 'assistant',
|
||
content: chunk.delta,
|
||
reasoning_content: null,
|
||
tool_calls: null
|
||
};
|
||
results.push(firstTemplate);
|
||
state.isFirstChunk = false;
|
||
} else {
|
||
const template = buildTemplate();
|
||
template.choices[0].delta = {
|
||
role: 'assistant',
|
||
content: chunk.delta,
|
||
reasoning_content: null,
|
||
tool_calls: null
|
||
};
|
||
results.push(template);
|
||
}
|
||
return results.length === 1 ? results[0] : results;
|
||
}
|
||
|
||
if (type === 'response.output_item.done' && chunk.item?.type === 'function_call') {
|
||
const currentIndex = state.functionCallIndex;
|
||
state.functionCallIndex++; // 递增，为下一个 function_call 准备
|
||
const template = buildTemplate();
|
||
template.choices[0].delta = {
|
||
role: 'assistant',
|
||
content: null,
|
||
reasoning_content: null,
|
||
tool_calls: [{
|
||
index: currentIndex,
|
||
id: chunk.item.call_id,
|
||
type: 'function',
|
||
function: {
|
||
name: this.getOriginalToolName(chunk.item.name),
|
||
arguments: typeof chunk.item.arguments === 'string' ? chunk.item.arguments : JSON.stringify(chunk.item.arguments)
|
||
}
|
||
}]
|
||
};
|
||
return template;
|
||
}
|
||
|
||
if (type === 'response.completed') {
|
||
const template = buildTemplate();
|
||
const finishReason = state.functionCallIndex > 0 ? 'tool_calls' : 'stop';
|
||
template.choices[0].delta = {
|
||
role: null,
|
||
content: null,
|
||
reasoning_content: null,
|
||
tool_calls: null
|
||
};
|
||
template.choices[0].finish_reason = finishReason;
|
||
template.choices[0].native_finish_reason = finishReason;
|
||
template.usage = {
|
||
prompt_tokens: chunk.response.usage?.input_tokens || 0,
|
||
completion_tokens: chunk.response.usage?.output_tokens || 0,
|
||
total_tokens: chunk.response.usage?.total_tokens || 0
|
||
};
|
||
if (chunk.response.usage?.output_tokens_details?.reasoning_tokens) {
|
||
template.usage.completion_tokens_details = {
|
||
reasoning_tokens: chunk.response.usage.output_tokens_details.reasoning_tokens
|
||
};
|
||
}
|
||
// 完成后清理状态
|
||
this.streamParams.delete(stateKey);
|
||
return template;
|
||
}
|
||
|
||
return null;
|
||
}
|
||
|
||
/**
|
||
* Codex → OpenAI Responses 流式响应转换
|
||
*/
|
||
toOpenAIResponsesStreamChunk(chunk, model) {
|
||
if(true){
|
||
return chunk;
|
||
}
|
||
|
||
const type = chunk.type;
|
||
const resId = chunk.response?.id || 'default';
|
||
|
||
if (!this.streamParams.has(resId)) {
|
||
this.streamParams.set(resId, {
|
||
model: model,
|
||
createdAt: Math.floor(Date.now() / 1000),
|
||
responseID: resId,
|
||
functionCallIndex: -1,
|
||
eventsSent: new Set()
|
||
});
|
||
}
|
||
const state = this.streamParams.get(resId);
|
||
const events = [];
|
||
|
||
if (type === 'response.created') {
|
||
state.responseID = chunk.response.id;
|
||
state.model = chunk.response.model || state.model;
|
||
events.push(
|
||
generateResponseCreated(state.responseID, state.model),
|
||
generateResponseInProgress(state.responseID)
|
||
);
|
||
return events;
|
||
}
|
||
|
||
if (type === 'response.reasoning_summary_text.delta') {
|
||
events.push({
|
||
type: "response.reasoning_summary_text.delta",
|
||
response_id: state.responseID,
|
||
delta: chunk.delta
|
||
});
|
||
return events;
|
||
}
|
||
|
||
if (type === 'response.output_text.delta') {
|
||
if (!state.eventsSent.has('output_item_added')) {
|
||
events.push(generateOutputItemAdded(state.responseID));
|
||
state.eventsSent.add('output_item_added');
|
||
}
|
||
if (!state.eventsSent.has('content_part_added')) {
|
||
events.push(generateContentPartAdded(state.responseID));
|
||
state.eventsSent.add('content_part_added');
|
||
}
|
||
events.push({
|
||
type: "response.output_text.delta",
|
||
response_id: state.responseID,
|
||
delta: chunk.delta
|
||
});
|
||
return events;
|
||
}
|
||
|
||
if (type === 'response.output_item.done' && chunk.item?.type === 'function_call') {
|
||
events.push({
|
||
type: "response.output_item.added",
|
||
response_id: state.responseID,
|
||
item: {
|
||
id: chunk.item.call_id,
|
||
type: "function_call",
|
||
name: this.getOriginalToolName(chunk.item.name),
|
||
arguments: typeof chunk.item.arguments === 'string' ? chunk.item.arguments : JSON.stringify(chunk.item.arguments),
|
||
status: "completed"
|
||
}
|
||
});
|
||
events.push({
|
||
type: "response.output_item.done",
|
||
response_id: state.responseID,
|
||
item_id: chunk.item.call_id
|
||
});
|
||
return events;
|
||
}
|
||
|
||
if (type === 'response.completed') {
|
||
events.push(
|
||
generateOutputTextDone(state.responseID),
|
||
generateContentPartDone(state.responseID),
|
||
generateOutputItemDone(state.responseID)
|
||
);
|
||
const completedEvent = generateResponseCompleted(state.responseID);
|
||
completedEvent.response.usage = {
|
||
input_tokens: chunk.response.usage?.input_tokens || 0,
|
||
output_tokens: chunk.response.usage?.output_tokens || 0,
|
||
total_tokens: chunk.response.usage?.total_tokens || 0
|
||
};
|
||
events.push(completedEvent);
|
||
this.streamParams.delete(resId);
|
||
return events;
|
||
}
|
||
|
||
return null;
|
||
}
|
||
|
||
/**
|
||
* Codex → Gemini 流式响应转换
|
||
*/
|
||
toGeminiStreamChunk(chunk, model) {
|
||
const type = chunk.type;
|
||
const resId = chunk.response?.id || 'default';
|
||
|
||
if (!this.streamParams.has(resId)) {
|
||
this.streamParams.set(resId, {
|
||
model: model,
|
||
createdAt: Math.floor(Date.now() / 1000),
|
||
responseID: resId
|
||
});
|
||
}
|
||
const state = this.streamParams.get(resId);
|
||
|
||
const template = {
|
||
candidates: [{
|
||
content: {
|
||
role: "model",
|
||
parts: []
|
||
}
|
||
}],
|
||
modelVersion: state.model,
|
||
responseId: state.responseID
|
||
};
|
||
|
||
if (type === 'response.reasoning_summary_text.delta') {
|
||
template.candidates[0].content.parts.push({ text: chunk.delta, thought: true });
|
||
return template;
|
||
}
|
||
|
||
if (type === 'response.output_text.delta') {
|
||
template.candidates[0].content.parts.push({ text: chunk.delta });
|
||
return template;
|
||
}
|
||
|
||
if (type === 'response.output_item.done' && chunk.item?.type === 'function_call') {
|
||
template.candidates[0].content.parts.push({
|
||
functionCall: {
|
||
name: this.getOriginalToolName(chunk.item.name),
|
||
args: typeof chunk.item.arguments === 'string' ? JSON.parse(chunk.item.arguments) : chunk.item.arguments
|
||
}
|
||
});
|
||
return template;
|
||
}
|
||
|
||
if (type === 'response.completed') {
|
||
template.candidates[0].finishReason = "STOP";
|
||
template.usageMetadata = {
|
||
promptTokenCount: chunk.response.usage?.input_tokens || 0,
|
||
candidatesTokenCount: chunk.response.usage?.output_tokens || 0,
|
||
totalTokenCount: chunk.response.usage?.total_tokens || 0
|
||
};
|
||
this.streamParams.delete(resId);
|
||
return template;
|
||
}
|
||
|
||
return null;
|
||
}
|
||
|
||
/**
|
||
* Codex → Claude 流式响应转换
|
||
*/
|
||
toClaudeStreamChunk(chunk, model) {
|
||
const type = chunk.type;
|
||
const resId = chunk.response?.id || 'default';
|
||
|
||
if (!this.streamParams.has(resId)) {
|
||
this.streamParams.set(resId, {
|
||
model: model,
|
||
createdAt: Math.floor(Date.now() / 1000),
|
||
responseID: resId,
|
||
blockIndex: 0
|
||
});
|
||
}
|
||
const state = this.streamParams.get(resId);
|
||
|
||
if (type === 'response.created') {
|
||
state.responseID = chunk.response.id;
|
||
return {
|
||
type: "message_start",
|
||
message: {
|
||
id: state.responseID,
|
||
type: "message",
|
||
role: "assistant",
|
||
model: state.model,
|
||
usage: { input_tokens: 0, output_tokens: 0 }
|
||
}
|
||
};
|
||
}
|
||
|
||
if (type === 'response.reasoning_summary_text.delta') {
|
||
return {
|
||
type: "content_block_delta",
|
||
index: state.blockIndex,
|
||
delta: { type: "thinking_delta", thinking: chunk.delta }
|
||
};
|
||
}
|
||
|
||
if (type === 'response.output_text.delta') {
|
||
return {
|
||
type: "content_block_delta",
|
||
index: state.blockIndex,
|
||
delta: { type: "text_delta", text: chunk.delta }
|
||
};
|
||
}
|
||
|
||
if (type === 'response.output_item.done' && chunk.item?.type === 'function_call') {
|
||
const events = [
|
||
{
|
||
type: "content_block_start",
|
||
index: state.blockIndex,
|
||
content_block: {
|
||
type: "tool_use",
|
||
id: chunk.item.call_id,
|
||
name: this.getOriginalToolName(chunk.item.name),
|
||
input: {}
|
||
}
|
||
},
|
||
{
|
||
type: "content_block_delta",
|
||
index: state.blockIndex,
|
||
delta: {
|
||
type: "input_json_delta",
|
||
partial_json: typeof chunk.item.arguments === 'string' ? chunk.item.arguments : JSON.stringify(chunk.item.arguments)
|
||
}
|
||
},
|
||
{
|
||
type: "content_block_stop",
|
||
index: state.blockIndex
|
||
}
|
||
];
|
||
state.blockIndex++;
|
||
return events;
|
||
}
|
||
|
||
if (type === 'response.completed') {
|
||
const events = [
|
||
{
|
||
type: "message_delta",
|
||
delta: { stop_reason: "end_turn" },
|
||
usage: {
|
||
input_tokens: chunk.response.usage?.input_tokens || 0,
|
||
output_tokens: chunk.response.usage?.output_tokens || 0
|
||
}
|
||
},
|
||
{ type: "message_stop" }
|
||
];
|
||
this.streamParams.delete(resId);
|
||
return events;
|
||
}
|
||
|
||
return null;
|
||
}
|
||
|
||
}
|