feat(聊天): 支持 OpenAI 兼容格式的 API 调用
- 新增 handleOpenAICompatibleChat 处理函数 - 支持第三方中转站的 /v1/chat/completions 端点 - 优化处理器选择逻辑（apiFormat -> isCodex -> Claude原生） - 过滤空内容消息避免 API 错误 - 规范化 URL 处理，避免双斜杠问题 - 支持多模态消息和工具调用
This commit is contained in:
gaoziman
parent
99ca472dd2
commit
6e37e61420
@ -72,6 +72,11 @@ function isCodexModel(modelId: string): boolean {
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return modelId.startsWith('gpt-') && modelId.includes('codex');
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}
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// 规范化 URL（移除末尾斜杠，避免拼接时出现双斜杠）
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function normalizeBaseUrl(url: string): string {
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return url.replace(/\/+$/, '');
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}
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// 默认系统提示词 - 用于生成更详细、更有结构的回复
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const DEFAULT_SYSTEM_PROMPT = `你是一个专业、友好的 AI 助手。请遵循以下规则来回复用户：
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@ -282,6 +287,7 @@ export async function POST(request: Request) {
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async start(controller) {
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try {
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const cchUrl = settings.cchUrl || process.env.CCH_DEFAULT_URL || 'https://claude.leocoder.cn/';
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const apiFormat = (settings.apiFormat as 'claude' | 'openai') || 'claude';
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// 获取系统提示词（叠加模式）
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// 1. 始终使用 DEFAULT_SYSTEM_PROMPT 作为基础
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@ -312,8 +318,41 @@ export async function POST(request: Request) {
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let totalInputTokens = 0;
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let totalOutputTokens = 0;
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if (isCodex) {
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// ==================== Codex 模型处理（OpenAI 格式） ====================
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// 【重要】处理器选择优先级说明：
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// 1. 首先检查 apiFormat === 'openai'：如果用户选择了 "OpenAI 兼容" 格式，
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// 则所有模型（包括 Codex 模型）都统一使用 /v1/chat/completions 端点
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// 这是因为第三方中转站通常只支持 OpenAI 兼容的 /v1/chat/completions 端点
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// 2. 然后检查 isCodex：如果是 Claude 原生格式 + Codex 模型，才使用 /v1/responses 端点
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// 3. 最后是普通的 Claude 原生格式，使用 /v1/messages 端点
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if (apiFormat === 'openai') {
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// ==================== OpenAI 兼容格式处理 ====================
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// 当用户选择 "OpenAI 兼容" 时，无论什么模型都走这个分支
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// 第三方中转站统一使用 /v1/chat/completions 端点
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console.log('[API/chat] 使用 OpenAI 兼容格式，模型:', useModel, '(isCodex:', isCodex, ')');
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const result = await handleOpenAICompatibleChat({
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cchUrl,
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apiKey: decryptedApiKey,
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model: useModel,
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systemPrompt,
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temperature,
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historyMessages,
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message,
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tools: tools || (conversation.tools as string[]) || [],
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controller,
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encoder,
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images,
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});
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fullContent = result.fullContent;
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thinkingContent = result.thinkingContent;
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totalInputTokens = result.inputTokens;
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totalOutputTokens = result.outputTokens;
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} else if (isCodex) {
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// ==================== Codex 模型处理（使用 Codex Response API） ====================
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// 仅当使用 Claude 原生格式 + Codex 模型时，才使用 /v1/responses 端点
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// 这是 CCH 项目特有的 Codex Response API
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console.log('[API/chat] 使用 Codex Response API (Claude 原生格式 + Codex 模型)');
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const result = await handleCodexChat({
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cchUrl,
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apiKey: decryptedApiKey,
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@ -332,7 +371,8 @@ export async function POST(request: Request) {
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totalInputTokens = result.inputTokens;
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totalOutputTokens = result.outputTokens;
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} else {
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// ==================== Claude 模型处理（原有逻辑） ====================
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// ==================== Claude 原生格式处理 ====================
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console.log('[API/chat] 使用 Claude 原生格式 (/v1/messages)');
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const result = await handleClaudeChat({
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cchUrl,
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apiKey: decryptedApiKey,
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@ -476,9 +516,11 @@ async function handleCodexChat(params: CodexChatParams): Promise<{
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images,
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} = params;
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// 构建 Codex Response API 格式的输入
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// 构建 Codex Response API 格式的输入（过滤空内容的消息）
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const inputItems: CodexInputItem[] = [
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...historyMessages.map((msg) => ({
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...historyMessages
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.filter((msg) => msg.content && msg.content.trim() !== '')
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.map((msg) => ({
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type: 'message' as const,
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role: msg.role as 'user' | 'assistant',
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content: msg.content,
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@ -556,7 +598,7 @@ async function handleCodexChat(params: CodexChatParams): Promise<{
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}
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// 使用 Codex Response API 端点
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const response = await fetch(`${cchUrl}/v1/responses`, {
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const response = await fetch(`${normalizeBaseUrl(cchUrl)}/v1/responses`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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@ -796,8 +838,10 @@ async function handleClaudeChat(params: ClaudeChatParams): Promise<{
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images,
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} = params;
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// 构建消息历史
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const messageHistory: APIMessage[] = historyMessages.map((msg) => ({
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// 构建消息历史（过滤空内容的消息）
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const messageHistory: APIMessage[] = historyMessages
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.filter((msg) => msg.content && msg.content.trim() !== '')
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.map((msg) => ({
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role: msg.role as 'user' | 'assistant',
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content: msg.content,
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}));
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@ -900,7 +944,7 @@ async function handleClaudeChat(params: ClaudeChatParams): Promise<{
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requestBody.temperature = temperature;
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}
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const response = await fetch(`${cchUrl}/v1/messages`, {
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const response = await fetch(`${normalizeBaseUrl(cchUrl)}/v1/messages`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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@ -1126,6 +1170,462 @@ async function handleClaudeChat(params: ClaudeChatParams): Promise<{
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};
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}
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// ==================== OpenAI 兼容格式处理函数 ====================
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interface OpenAICompatibleChatParams {
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cchUrl: string;
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apiKey: string;
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model: string;
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systemPrompt: string;
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temperature: number;
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historyMessages: { role: string; content: string }[];
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message: string;
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tools: string[];
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controller: ReadableStreamDefaultController;
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encoder: TextEncoder;
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images?: {
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type: 'image';
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media_type: string;
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data: string;
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}[];
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}
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// OpenAI 消息格式
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interface OpenAIMessageContent {
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type: 'text' | 'image_url';
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text?: string;
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image_url?: {
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url: string;
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};
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}
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interface OpenAICompatibleMessage {
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role: 'system' | 'user' | 'assistant' | 'tool';
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content: string | OpenAIMessageContent[] | null;
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tool_calls?: {
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id: string;
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type: 'function';
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function: {
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name: string;
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arguments: string;
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};
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}[];
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tool_call_id?: string;
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}
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async function handleOpenAICompatibleChat(params: OpenAICompatibleChatParams): Promise<{
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fullContent: string;
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thinkingContent: string;
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inputTokens: number;
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outputTokens: number;
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}> {
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const {
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cchUrl,
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apiKey,
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model,
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systemPrompt,
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temperature,
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historyMessages,
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message,
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tools,
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controller,
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encoder,
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images,
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} = params;
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// 构建 OpenAI 格式的消息历史（过滤空内容的消息）
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const openaiMessages: OpenAICompatibleMessage[] = [
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{ role: 'system', content: systemPrompt },
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...historyMessages
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.filter((msg) => msg.content && msg.content.trim() !== '')
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.map((msg) => ({
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role: msg.role as 'user' | 'assistant',
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content: msg.content,
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})),
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];
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// 添加当前用户消息（支持多模态）
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if (images && images.length > 0) {
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console.log('[handleOpenAICompatibleChat] Building multimodal message with', images.length, 'images');
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const multimodalContent: OpenAIMessageContent[] = [];
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// 添加图片
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for (const img of images) {
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console.log('[handleOpenAICompatibleChat] Adding image:', {
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type: img.type,
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media_type: img.media_type,
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dataLength: img.data?.length || 0,
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});
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multimodalContent.push({
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type: 'image_url',
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image_url: {
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url: `data:${img.media_type};base64,${img.data}`,
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},
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});
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}
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// 添加文本
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if (message) {
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multimodalContent.push({
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type: 'text',
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text: message,
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});
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}
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openaiMessages.push({
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role: 'user',
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content: multimodalContent,
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});
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} else {
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console.log('[handleOpenAICompatibleChat] No images, using simple text message');
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openaiMessages.push({
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role: 'user',
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content: message,
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});
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}
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// 构建 OpenAI 格式的工具定义
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const openaiTools = buildOpenAIToolDefinitions(tools);
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let fullContent = '';
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let thinkingContent = ''; // 用于收集 <think> 标签中的思考内容
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let totalInputTokens = 0;
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let totalOutputTokens = 0;
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let loopCount = 0;
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const maxLoops = 10;
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// 用于处理 <think> 标签的状态变量（跨 chunk 处理）
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let isInThinkingMode = false;
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let pendingBuffer = ''; // 用于处理标签可能跨 chunk 的情况
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while (loopCount < maxLoops) {
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loopCount++;
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// 构建请求体
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const requestBody: Record<string, unknown> = {
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model,
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messages: openaiMessages,
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stream: true,
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temperature,
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};
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if (openaiTools.length > 0) {
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requestBody.tools = openaiTools;
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}
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console.log('[handleOpenAICompatibleChat] Sending to OpenAI-compatible API:', {
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model,
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messagesCount: openaiMessages.length,
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url: `${normalizeBaseUrl(cchUrl)}/v1/chat/completions`,
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});
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const response = await fetch(`${normalizeBaseUrl(cchUrl)}/v1/chat/completions`, {
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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 ${apiKey}`,
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},
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body: JSON.stringify(requestBody),
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});
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if (!response.ok) {
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const errorText = await response.text();
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throw new Error(`OpenAI-compatible API error: ${response.status} - ${errorText}`);
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}
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const reader = response.body?.getReader();
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if (!reader) {
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throw new Error('No response body');
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}
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// 收集当前轮次的内容
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let currentTextContent = '';
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const toolCalls: { id: string; name: string; arguments: string }[] = [];
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const currentToolCallsMap: Map<number, { id: string; name: string; arguments: string }> = new Map();
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let stopReason: string | null = null;
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const decoder = new TextDecoder();
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let buffer = '';
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// 处理流式响应
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while (true) {
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const { done, value } = await reader.read();
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if (done) break;
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buffer += decoder.decode(value, { stream: true });
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const lines = buffer.split('\n');
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buffer = lines.pop() || '';
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for (const line of lines) {
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if (line.startsWith('data: ')) {
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const data = line.slice(6).trim();
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if (data === '[DONE]') continue;
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if (!data) continue;
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try {
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const event = JSON.parse(data);
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// 处理文本内容（包含 <think> 标签过滤）
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if (event.choices?.[0]?.delta?.content) {
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const rawContent = event.choices[0].delta.content;
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// 将新内容追加到待处理缓冲区
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pendingBuffer += rawContent;
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// 处理缓冲区中的内容
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while (pendingBuffer.length > 0) {
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if (isInThinkingMode) {
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// 在 thinking 模式中，查找 </think> 结束标签
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const endTagIndex = pendingBuffer.indexOf('</think>');
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if (endTagIndex !== -1) {
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// 找到结束标签，提取 thinking 内容
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const thinkPart = pendingBuffer.slice(0, endTagIndex);
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if (thinkPart) {
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thinkingContent += thinkPart;
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// 发送 thinking 事件（让前端可以展示折叠的思考内容）
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controller.enqueue(encoder.encode(`data: ${JSON.stringify({
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type: 'thinking',
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content: thinkPart,
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})}\n\n`));
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}
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// 移除已处理的内容和结束标签
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pendingBuffer = pendingBuffer.slice(endTagIndex + 8); // 8 = '</think>'.length
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isInThinkingMode = false;
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} else {
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// 没找到结束标签，检查是否可能是部分标签
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// 保留最后 7 个字符以防 </think> 被截断（7 = '</think'.length - 1）
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if (pendingBuffer.length > 7) {
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const safePart = pendingBuffer.slice(0, -7);
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const keepPart = pendingBuffer.slice(-7);
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if (safePart) {
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thinkingContent += safePart;
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controller.enqueue(encoder.encode(`data: ${JSON.stringify({
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type: 'thinking',
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content: safePart,
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})}\n\n`));
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}
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pendingBuffer = keepPart;
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}
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// 等待更多数据
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break;
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}
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} else {
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// 不在 thinking 模式，查找 <think> 开始标签
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const startTagIndex = pendingBuffer.indexOf('<think>');
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if (startTagIndex !== -1) {
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// 找到开始标签，先输出标签前的普通文本
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const textPart = pendingBuffer.slice(0, startTagIndex);
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if (textPart) {
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currentTextContent += textPart;
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fullContent += textPart;
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controller.enqueue(encoder.encode(`data: ${JSON.stringify({
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type: 'text',
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content: textPart,
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})}\n\n`));
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}
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// 移除已处理的内容和开始标签
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pendingBuffer = pendingBuffer.slice(startTagIndex + 7); // 7 = '<think>'.length
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isInThinkingMode = true;
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} else {
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// 没找到开始标签，检查是否可能是部分标签
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// 保留最后 6 个字符以防 <think> 被截断（6 = '<think'.length - 1）
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const potentialTagStart = pendingBuffer.lastIndexOf('<');
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if (potentialTagStart !== -1 && potentialTagStart > pendingBuffer.length - 7) {
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// 可能是部分的 <think> 标签，保留这部分
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const safePart = pendingBuffer.slice(0, potentialTagStart);
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const keepPart = pendingBuffer.slice(potentialTagStart);
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if (safePart) {
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currentTextContent += safePart;
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fullContent += safePart;
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controller.enqueue(encoder.encode(`data: ${JSON.stringify({
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type: 'text',
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content: safePart,
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})}\n\n`));
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}
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pendingBuffer = keepPart;
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// 等待更多数据
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break;
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} else {
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// 安全输出所有内容
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currentTextContent += pendingBuffer;
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fullContent += pendingBuffer;
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controller.enqueue(encoder.encode(`data: ${JSON.stringify({
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type: 'text',
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content: pendingBuffer,
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})}\n\n`));
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pendingBuffer = '';
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}
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}
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}
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}
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}
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// 处理工具调用
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if (event.choices?.[0]?.delta?.tool_calls) {
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for (const toolCall of event.choices[0].delta.tool_calls) {
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const index = toolCall.index ?? 0;
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if (!currentToolCallsMap.has(index)) {
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// 新的工具调用开始
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currentToolCallsMap.set(index, {
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id: toolCall.id || '',
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name: toolCall.function?.name || '',
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arguments: '',
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});
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if (toolCall.id) {
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controller.enqueue(encoder.encode(`data: ${JSON.stringify({
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type: 'tool_use_start',
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id: toolCall.id,
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name: toolCall.function?.name || '',
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})}\n\n`));
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}
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}
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const current = currentToolCallsMap.get(index)!;
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// 更新工具调用信息
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if (toolCall.id) current.id = toolCall.id;
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if (toolCall.function?.name) current.name = toolCall.function.name;
|
||||
if (toolCall.function?.arguments) {
|
||||
current.arguments += toolCall.function.arguments;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 处理结束原因
|
||||
if (event.choices?.[0]?.finish_reason) {
|
||||
stopReason = event.choices[0].finish_reason;
|
||||
}
|
||||
|
||||
// 处理 usage 信息
|
||||
if (event.usage) {
|
||||
totalInputTokens = event.usage.prompt_tokens || 0;
|
||||
totalOutputTokens = event.usage.completion_tokens || 0;
|
||||
}
|
||||
} catch (e) {
|
||||
console.error('[handleOpenAICompatibleChat] Parse error:', e, 'Line:', line);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// 流结束后，处理可能残留在 pendingBuffer 中的内容
|
||||
if (pendingBuffer.length > 0) {
|
||||
if (isInThinkingMode) {
|
||||
// 如果还在 thinking 模式，说明 </think> 标签没有正常闭合
|
||||
// 将剩余内容作为 thinking 内容处理
|
||||
thinkingContent += pendingBuffer;
|
||||
controller.enqueue(encoder.encode(`data: ${JSON.stringify({
|
||||
type: 'thinking',
|
||||
content: pendingBuffer,
|
||||
})}\n\n`));
|
||||
} else {
|
||||
// 普通文本模式，输出剩余内容
|
||||
currentTextContent += pendingBuffer;
|
||||
fullContent += pendingBuffer;
|
||||
controller.enqueue(encoder.encode(`data: ${JSON.stringify({
|
||||
type: 'text',
|
||||
content: pendingBuffer,
|
||||
})}\n\n`));
|
||||
}
|
||||
pendingBuffer = '';
|
||||
}
|
||||
|
||||
// 收集所有工具调用
|
||||
for (const [, tc] of currentToolCallsMap) {
|
||||
if (tc.id && tc.name) {
|
||||
toolCalls.push(tc);
|
||||
controller.enqueue(encoder.encode(`data: ${JSON.stringify({
|
||||
type: 'tool_use_complete',
|
||||
id: tc.id,
|
||||
name: tc.name,
|
||||
input: JSON.parse(tc.arguments || '{}'),
|
||||
})}\n\n`));
|
||||
}
|
||||
}
|
||||
|
||||
// 检查是否需要执行工具
|
||||
if ((stopReason === 'tool_calls' || toolCalls.length > 0) && toolCalls.length > 0) {
|
||||
// 将助手消息添加到历史
|
||||
const assistantMessage: OpenAICompatibleMessage = {
|
||||
role: 'assistant',
|
||||
content: currentTextContent || null,
|
||||
tool_calls: toolCalls.map((tc) => ({
|
||||
id: tc.id,
|
||||
type: 'function' as const,
|
||||
function: {
|
||||
name: tc.name,
|
||||
arguments: tc.arguments,
|
||||
},
|
||||
})),
|
||||
};
|
||||
openaiMessages.push(assistantMessage);
|
||||
|
||||
// 执行所有工具并收集结果
|
||||
for (const tc of toolCalls) {
|
||||
controller.enqueue(encoder.encode(`data: ${JSON.stringify({
|
||||
type: 'tool_execution_start',
|
||||
id: tc.id,
|
||||
name: tc.name,
|
||||
})}\n\n`));
|
||||
|
||||
// 解析工具参数
|
||||
let toolInput: Record<string, unknown> = {};
|
||||
try {
|
||||
toolInput = JSON.parse(tc.arguments || '{}');
|
||||
} catch {
|
||||
console.error('[handleOpenAICompatibleChat] Failed to parse tool arguments');
|
||||
}
|
||||
|
||||
// 执行工具
|
||||
const result = await executeTool(tc.name, toolInput);
|
||||
|
||||
controller.enqueue(encoder.encode(`data: ${JSON.stringify({
|
||||
type: 'tool_execution_result',
|
||||
id: tc.id,
|
||||
name: tc.name,
|
||||
success: result.success,
|
||||
result: result.displayResult,
|
||||
images: result.images,
|
||||
})}\n\n`));
|
||||
|
||||
// 将工具结果显示给用户
|
||||
const toolDisplayText = `\n\n${result.displayResult}\n\n`;
|
||||
fullContent += toolDisplayText;
|
||||
controller.enqueue(encoder.encode(`data: ${JSON.stringify({
|
||||
type: 'text',
|
||||
content: toolDisplayText,
|
||||
})}\n\n`));
|
||||
|
||||
// 将工具结果添加到消息历史（OpenAI 格式）
|
||||
openaiMessages.push({
|
||||
role: 'tool',
|
||||
content: result.fullResult,
|
||||
tool_call_id: tc.id,
|
||||
});
|
||||
}
|
||||
|
||||
// 继续循环，让 AI 基于工具结果继续回复
|
||||
continue;
|
||||
}
|
||||
|
||||
// 如果没有工具调用，结束循环
|
||||
break;
|
||||
}
|
||||
|
||||
return {
|
||||
fullContent,
|
||||
thinkingContent,
|
||||
inputTokens: totalInputTokens,
|
||||
outputTokens: totalOutputTokens,
|
||||
};
|
||||
}
|
||||
|
||||
// 构建 Claude 工具定义
|
||||
function buildClaudeToolDefinitions(toolIds: string[]) {
|
||||
const toolMap: Record<string, object> = {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user