Implement multi-API support: ChatGPT, Grok, Claude, and Gemini with automatic routing

server/analyzeStream.js

@@ -9,15 +9,16 @@ import {
 import { BAZI_SYSTEM_INSTRUCTION, buildUserPrompt } from './prompt.js';
 import { calculateLifeTimeline } from './baziCalculator.js';
 
-const DEFAULT_API_BASE_URL = process.env.API_BASE_URL || 'https://generativelanguage.googleapis.com/v1beta';
-const DEFAULT_API_KEY = process.env.API_KEY || 'AIzaSyBiz_9_zhb3c9mxl3dePVfIv1iiao-_6dw'; // Google Gemini API密钥
-const DEFAULT_MODEL = process.env.DEFAULT_MODEL || 'gemini-1.5-pro';
+import { buildApiRequest, parseApiResponse } from './apiConfig.js';
 
-// 备选模型列表 - 用于并发请求和降级（Google Gemini 支持的模型）
+const DEFAULT_MODEL = process.env.DEFAULT_MODEL || 'gpt-4o';
+
+// 备选模型列表 - 用于并发请求和降级
 const ALL_MODELS = [
+  'gpt-4o',
+  'grok-4',
+  'claude-3-5-sonnet-20241022',
   'gemini-1.5-pro',
-  'gemini-1.5-flash',
-  'gemini-pro',
 ];
 
 const COST_PER_ANALYSIS = process.env.COST_PER_ANALYSIS ? parseInt(process.env.COST_PER_ANALYSIS, 10) : 50;
@@ -35,7 +36,7 @@ const sendSSE = (res, event, data) => {
 /**
  * 单次API请求 - 返回Promise
  */
-const makeModelRequest = async (model, apiBaseUrl, apiKey, userPrompt, timeoutMs = 120000) => {
+const makeModelRequest = async (model, userPrompt, timeoutMs = 120000) => {
   const controller = new AbortController();
   const timeoutId = setTimeout(() => controller.abort(), timeoutMs);
 
@@ -43,44 +44,14 @@ const makeModelRequest = async (model, apiBaseUrl, apiKey, userPrompt, timeoutMs
     console.log(`[${model}] 开始请求...`);
     const startTime = Date.now();
 
-    // 检查是否是 Google Gemini API
-    const isGeminiApi = apiKey.startsWith('AIzaSy');
-    const apiUrl = isGeminiApi 
-      ? `${apiBaseUrl}/models/${model}:generateContent?key=${apiKey}`
-      : `${apiBaseUrl}/chat/completions`;
-    
-    const headers = isGeminiApi
-      ? { 'Content-Type': 'application/json' }
-      : {
-          'Content-Type': 'application/json',
-          Authorization: `Bearer ${apiKey}`,
-        };
-    
-    const requestBody = isGeminiApi
-      ? {
-          contents: [{
-            parts: [{
-              text: `${BAZI_SYSTEM_INSTRUCTION}\n\n${userPrompt}`
-            }]
-          }],
-          generationConfig: {
-            temperature: 0.7,
-          }
-        }
-      : {
-          model: model,
-          messages: [
-            { role: 'system', content: BAZI_SYSTEM_INSTRUCTION },
-            { role: 'user', content: userPrompt },
-          ],
-          temperature: 0.7,
-        };
-
-    const response = await fetch(apiUrl, {
+    // 使用新的 API 配置系统
+    const apiRequest = buildApiRequest(model, BAZI_SYSTEM_INSTRUCTION, userPrompt, 0.7);
+
+    const response = await fetch(apiRequest.url, {
       method: 'POST',
-      headers: headers,
+      headers: apiRequest.headers,
       signal: controller.signal,
-      body: JSON.stringify(requestBody),
+      body: JSON.stringify(apiRequest.body),
     });
 
     clearTimeout(timeoutId);
@@ -101,13 +72,8 @@ const makeModelRequest = async (model, apiBaseUrl, apiKey, userPrompt, timeoutMs
       return { success: false, model, error: 'INVALID_API_RESPONSE', elapsed };
     }
 
-    // 处理 Google Gemini API 响应格式
-    let content;
-    if (isGeminiApi && jsonResult.candidates?.[0]?.content?.parts?.[0]?.text) {
-      content = jsonResult.candidates[0].content.parts[0].text;
-    } else {
-      content = jsonResult.choices?.[0]?.message?.content;
-    }
+    // 使用新的响应解析系统
+    const content = parseApiResponse(jsonResult, model);
     if (!content) {
       console.warn(`[${model}] 无内容返回 (${elapsed}s)`);
       return { success: false, model, error: 'EMPTY_RESPONSE', elapsed };
@@ -158,12 +124,12 @@ const makeModelRequest = async (model, apiBaseUrl, apiKey, userPrompt, timeoutMs
 /**
  * 并发请求多个模型，返回第一个成功的结果
  */
-const raceModels = async (models, apiBaseUrl, apiKey, userPrompt, onProgress) => {
+const raceModels = async (models, userPrompt, onProgress) => {
   onProgress(`正在并发请求 ${models.length} 个模型...`);
 
   // 创建所有请求的Promise
   const promises = models.map(model =>
-    makeModelRequest(model, apiBaseUrl, apiKey, userPrompt, 180000)
+    makeModelRequest(model, userPrompt, 180000)
   );
 
   // 使用Promise.allSettled等待所有请求完成，但我们会在第一个成功时就返回
@@ -228,11 +194,13 @@ export const handleAnalyzeStream = async (req, res) => {
   };
 
   if (!useCustomApi) {
-    apiBaseUrl = DEFAULT_API_BASE_URL;
-    apiKey = DEFAULT_API_KEY;
+    // 不再需要固定的 API URL 和 Key，由 apiConfig.js 根据模型自动选择
+    apiBaseUrl = null; // 不再使用
+    apiKey = null; // 不再使用
     modelName = DEFAULT_MODEL;
 
-    if (!DEFAULT_API_KEY || DEFAULT_API_KEY === 'sk-example-key') {
+    // API 配置由 apiConfig.js 管理，无需检查
+    if (false) {
       sendSSE(res, 'error', {
         error: 'SERVER_DEFAULT_KEY_NOT_SET',
         message: '服务器未配置API密钥，请使用自定义API或联系管理员'
@@ -296,7 +264,7 @@ export const handleAnalyzeStream = async (req, res) => {
 
     for (let attempt = 1; attempt <= 3; attempt++) {
       onProgress(`尝试第 ${attempt} 次...`);
-      const response = await makeModelRequest(modelName, apiBaseUrl, apiKey, userPrompt, 60000);
+      const response = await makeModelRequest(modelName, userPrompt, 60000);
 
       if (response.success) {
         result = response.data;
@@ -316,8 +284,8 @@ export const handleAnalyzeStream = async (req, res) => {
     onProgress('启动多模型并发请求策略...');
 
     // 第一轮：并发请求主模型和一个备选模型
-    const firstRoundModels = [modelName, 'gemini-1.5-flash'];
-    let raceResult = await raceModels(firstRoundModels, apiBaseUrl, apiKey, userPrompt, onProgress);
+    const firstRoundModels = [modelName, 'gpt-4o'];
+    let raceResult = await raceModels(firstRoundModels, userPrompt, onProgress);
 
     if (raceResult.success) {
       result = raceResult.data;
@@ -325,8 +293,8 @@ export const handleAnalyzeStream = async (req, res) => {
     } else {
       // 第二轮：尝试其他模型
       onProgress('第一轮失败，启动第二轮备选模型...');
-      const secondRoundModels = ['gemini-1.5-pro', 'gemini-pro'];
-      raceResult = await raceModels(secondRoundModels, apiBaseUrl, apiKey, userPrompt, onProgress);
+      const secondRoundModels = ['grok-4', 'claude-3-5-sonnet-20241022'];
+      raceResult = await raceModels(secondRoundModels, userPrompt, onProgress);
 
       if (raceResult.success) {
         result = raceResult.data;
@@ -339,7 +307,7 @@ export const handleAnalyzeStream = async (req, res) => {
       onProgress('并发请求全部失败，尝试逐个请求...');
       for (const model of ALL_MODELS) {
         onProgress(`最后尝试: ${model}...`);
-        const response = await makeModelRequest(model, apiBaseUrl, apiKey, userPrompt, 45000);
+        const response = await makeModelRequest(model, userPrompt, 45000);
         if (response.success) {
           result = response.data;
           usedModel = model;

server/apiConfig.js

@@ -0,0 +1,135 @@
+/**
+ * 多 API 配置和路由
+ * 根据模型名称自动选择正确的 API 端点和密钥
+ */
+
+// API 配置
+const API_CONFIGS = {
+  // Google Gemini
+  gemini: {
+    baseUrl: 'https://generativelanguage.googleapis.com/v1beta',
+    apiKey: process.env.GEMINI_API_KEY || 'AIzaSyBiz_9_zhb3c9mxl3dePVfIv1iiao-_6dw',
+    models: ['gemini-1.5-pro', 'gemini-1.5-flash', 'gemini-pro', 'gemini-3-pro-preview'],
+    format: 'gemini', // 使用 Gemini 原生格式
+  },
+  
+  // OpenAI (ChatGPT)
+  openai: {
+    baseUrl: 'https://api.openai.com/v1',
+    apiKey: process.env.OPENAI_API_KEY || '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',
+    models: ['gpt-4', 'gpt-4-turbo', 'gpt-3.5-turbo', 'gpt-4o', 'gpt-4o-mini'],
+    format: 'openai', // 使用 OpenAI 格式
+  },
+  
+  // Grok (xAI)
+  grok: {
+    baseUrl: 'https://api.x.ai/v1',
+    apiKey: process.env.GROK_API_KEY || 'xai-5nPioW6r81dYiWzr6jYkLewyjM32YHEP2PWU2oRAcIpwHsaqL2azw3mnLu8PDNuI7ErkkHxn7jjejWpR',
+    models: ['grok-4', 'grok-4-auto', 'grok-4-1-non-thinking-w-tool', 'grok-4-mini-thinking-tahoe', 'grok-beta'],
+    format: 'openai', // Grok 使用 OpenAI 兼容格式
+  },
+  
+  // Claude (Anthropic)
+  claude: {
+    baseUrl: 'https://api.anthropic.com/v1',
+    apiKey: process.env.CLAUDE_API_KEY || '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',
+    models: ['claude-3-5-sonnet-20241022', 'claude-3-opus-20240229', 'claude-3-5-haiku-20241022', 'claude-haiku-4-5-20251001', 'claude-3-5-sonnet'],
+    format: 'claude', // 使用 Claude 格式
+  },
+};
+
+/**
+ * 根据模型名称获取 API 配置
+ */
+export function getApiConfigForModel(modelName) {
+  // 检查每个 API 提供商的模型列表
+  for (const [provider, config] of Object.entries(API_CONFIGS)) {
+    if (config.models.includes(modelName)) {
+      return { ...config, provider };
+    }
+  }
+  
+  // 默认使用 Gemini
+  return { ...API_CONFIGS.gemini, provider: 'gemini' };
+}
+
+/**
+ * 构建 API 请求
+ */
+export function buildApiRequest(modelName, systemPrompt, userPrompt, temperature = 0.7) {
+  const config = getApiConfigForModel(modelName);
+  
+  if (config.format === 'gemini') {
+    // Google Gemini 格式
+    return {
+      url: `${config.baseUrl}/models/${modelName}:generateContent?key=${config.apiKey}`,
+      headers: { 'Content-Type': 'application/json' },
+      body: {
+        contents: [{
+          parts: [{
+            text: `${systemPrompt}\n\n${userPrompt}`
+          }]
+        }],
+        generationConfig: {
+          temperature: temperature,
+        }
+      }
+    };
+  } else if (config.format === 'claude') {
+    // Claude 格式
+    return {
+      url: `${config.baseUrl}/messages`,
+      headers: {
+        'Content-Type': 'application/json',
+        'x-api-key': config.apiKey,
+        'anthropic-version': '2023-06-01',
+      },
+      body: {
+        model: modelName,
+        max_tokens: 8192,
+        temperature: temperature,
+        messages: [
+          { role: 'user', content: `${systemPrompt}\n\n${userPrompt}` }
+        ]
+      }
+    };
+  } else {
+    // OpenAI 兼容格式 (OpenAI, Grok)
+    return {
+      url: `${config.baseUrl}/chat/completions`,
+      headers: {
+        'Content-Type': 'application/json',
+        'Authorization': `Bearer ${config.apiKey}`,
+      },
+      body: {
+        model: modelName,
+        messages: [
+          { role: 'system', content: systemPrompt },
+          { role: 'user', content: userPrompt },
+        ],
+        temperature: temperature,
+      }
+    };
+  }
+}
+
+/**
+ * 解析 API 响应
+ */
+export function parseApiResponse(responseJson, modelName) {
+  const config = getApiConfigForModel(modelName);
+  
+  if (config.format === 'gemini') {
+    // Google Gemini 响应格式
+    return responseJson.candidates?.[0]?.content?.parts?.[0]?.text || null;
+  } else if (config.format === 'claude') {
+    // Claude 响应格式
+    return responseJson.content?.[0]?.text || null;
+  } else {
+    // OpenAI 兼容格式
+    return responseJson.choices?.[0]?.message?.content || null;
+  }
+}
+
+export default API_CONFIGS;
+

server/celebrityAnalyzer.js

@@ -5,12 +5,11 @@
 import fetch from 'node-fetch';
 import { AGENT_CELEBRITY_ANALYSIS_PROMPT } from './agentPrompts.js';
 
-const DEFAULT_API_BASE_URL = process.env.API_BASE_URL || 'https://generativelanguage.googleapis.com/v1beta';
-const DEFAULT_API_KEY = process.env.API_KEY || 'AIzaSyBiz_9_zhb3c9mxl3dePVfIv1iiao-_6dw'; // Google Gemini API密钥
+import { buildApiRequest, parseApiResponse } from './apiConfig.js';
 
 // 名人分析使用的模型 - 需要高质量输出
-const CELEBRITY_ANALYSIS_MODEL = 'gemini-1.5-pro';
-const FALLBACK_MODELS = ['gemini-1.5-flash', 'gemini-pro'];
+const CELEBRITY_ANALYSIS_MODEL = 'gpt-4o';
+const FALLBACK_MODELS = ['grok-4', 'claude-3-5-sonnet-20241022', 'gemini-1.5-pro'];
 
 /**
  * 构建名人分析的用户提示词
@@ -127,46 +126,21 @@ async function callLLMApi(model, userPrompt, timeoutMs = 120000) {
     console.log(`[celebrityAnalyzer] 使用模型 ${model} 开始生成分析...`);
     const startTime = Date.now();
 
-    // 检查是否是 Google Gemini API
-    const isGeminiApi = DEFAULT_API_KEY.startsWith('AIzaSy');
-    const apiUrl = isGeminiApi 
-      ? `${DEFAULT_API_BASE_URL}/models/${model}:generateContent?key=${DEFAULT_API_KEY}`
-      : `${DEFAULT_API_BASE_URL}/chat/completions`;
+    // 使用新的 API 配置系统
+    const apiRequest = buildApiRequest(model, AGENT_CELEBRITY_ANALYSIS_PROMPT, userPrompt, 0.7);
     
-    const headers = isGeminiApi
-      ? { 'Content-Type': 'application/json' }
-      : {
-          'Content-Type': 'application/json',
-          Authorization: `Bearer ${DEFAULT_API_KEY}`,
-        };
-    
-    const requestBody = isGeminiApi
-      ? {
-          contents: [{
-            parts: [{
-              text: `${AGENT_CELEBRITY_ANALYSIS_PROMPT}\n\n${userPrompt}`
-            }]
-          }],
-          generationConfig: {
-            temperature: 0.7,
-            maxOutputTokens: 8000,
-          }
-        }
-      : {
-          model: model,
-          messages: [
-            { role: 'system', content: AGENT_CELEBRITY_ANALYSIS_PROMPT },
-            { role: 'user', content: userPrompt },
-          ],
-          temperature: 0.7,
-          max_tokens: 8000,
-        };
+    // 如果是 OpenAI 格式，添加 max_tokens
+    if (apiRequest.body.max_tokens === undefined && apiRequest.body.generationConfig) {
+      apiRequest.body.generationConfig.maxOutputTokens = 8000;
+    } else if (apiRequest.body.max_tokens === undefined) {
+      apiRequest.body.max_tokens = 8000;
+    }
 
-    const response = await fetch(apiUrl, {
+    const response = await fetch(apiRequest.url, {
       method: 'POST',
-      headers: headers,
+      headers: apiRequest.headers,
       signal: controller.signal,
-      body: JSON.stringify(requestBody),
+      body: JSON.stringify(apiRequest.body),
     });
 
     clearTimeout(timeoutId);
@@ -180,13 +154,8 @@ async function callLLMApi(model, userPrompt, timeoutMs = 120000) {
 
     const responseJson = await response.json();
     
-    // 处理 Google Gemini API 响应格式
-    let content;
-    if (isGeminiApi && responseJson.candidates?.[0]?.content?.parts?.[0]?.text) {
-      content = responseJson.candidates[0].content.parts[0].text;
-    } else {
-      content = responseJson.choices?.[0]?.message?.content;
-    }
+    // 使用新的响应解析系统
+    const content = parseApiResponse(responseJson, model);
 
     if (!content) {
       return { success: false, error: 'EMPTY_RESPONSE', elapsed };

server/index.js

@@ -82,21 +82,24 @@ import { AGENT_DAILY_FORTUNE_PROMPT } from './agentPrompts.js';
 import { generateCelebrityAnalysis } from './celebrityAnalyzer.js';
 import { regenerateCoreDocument } from './coreDocumentEngine.js';
 import { startEmailScheduler } from './emailScheduler.js';
+import { buildApiRequest, parseApiResponse, getApiConfigForModel } from './apiConfig.js';
 
 dotenv.config();
 
 const PORT = process.env.PORT ? parseInt(process.env.PORT, 10) : (process.env.SPACE_ID ? 7860 : 3000);
 const JWT_SECRET = process.env.JWT_SECRET || 'dev-secret-change-me';
 
-// 使用 OpenAI 兼容的 Gemini API 代理服务
-const DEFAULT_API_BASE_URL = process.env.API_BASE_URL || 'https://generativelanguage.googleapis.com/v1beta';
-const DEFAULT_API_KEY = process.env.API_KEY || 'AIzaSyBiz_9_zhb3c9mxl3dePVfIv1iiao-_6dw'; // Google Gemini API密钥
-const DEFAULT_MODEL = process.env.DEFAULT_MODEL || 'gemini-1.5-pro';
+// 多 API 配置 - 使用 apiConfig.js 进行智能路由
+import { buildApiRequest, parseApiResponse, getApiConfigForModel } from './apiConfig.js';
 
-// 模型降级列表：当主模型失败时依次尝试（Google Gemini 支持的模型）
+const DEFAULT_MODEL = process.env.DEFAULT_MODEL || 'gpt-4o';
+
+// 模型降级列表：当主模型失败时依次尝试
 const FALLBACK_MODELS = [
-  'gemini-1.5-flash',
-  'gemini-pro',
+  'gpt-4o',
+  'grok-4',
+  'claude-3-5-sonnet-20241022',
+  'gemini-1.5-pro',
 ];
 
 const FREE_INIT_POINTS = process.env.FREE_INIT_POINTS ? parseInt(process.env.FREE_INIT_POINTS, 10) : 1000;
@@ -133,6 +136,25 @@ const getAuthedUser = (req) => {
 
 app.get('/api/health', (_req, res) => res.json({ ok: true }));
 
+// API 连接测试端点
+app.get('/api/test-apis', async (_req, res) => {
+  try {
+    const { testAllApis } = await import('./testApi.js');
+    const results = await testAllApis();
+    return res.json({ 
+      success: true, 
+      results,
+      timestamp: new Date().toISOString(),
+    });
+  } catch (error) {
+    console.error('API 测试失败:', error);
+    return res.status(500).json({ 
+      success: false, 
+      error: error.message 
+    });
+  }
+});
+
 app.post('/api/auth/register', async (req, res) => {
   const email = sanitizeEmail(req.body?.email);
   const password = String(req.body?.password || '');
@@ -310,17 +332,12 @@ app.post('/api/analyze', async (req, res) => {
     }
     // 未登录用户可以免费体验一次（游客模式，不扣点）
 
-    apiBaseUrl = DEFAULT_API_BASE_URL;
-    apiKey = DEFAULT_API_KEY;
+    // 不再需要固定的 API URL 和 Key，由 apiConfig.js 根据模型自动选择
+    apiBaseUrl = null; // 不再使用
+    apiKey = null; // 不再使用
     modelName = DEFAULT_MODEL;
 
-    // 检查 API 配置
-    if (!DEFAULT_API_KEY || DEFAULT_API_KEY === 'sk-example-key') {
-      return res.status(500).json({
-        error: 'SERVER_DEFAULT_KEY_NOT_SET',
-        message: 'Please configure API key on server or use custom API with your own key'
-      });
-    }
+    // API 配置由 apiConfig.js 管理，无需检查
   } else {
     if (!apiBaseUrl || !apiKey || !modelName) return res.status(400).json({ error: 'MISSING_CUSTOM_API_CONFIG' });
   }
@@ -347,50 +364,19 @@ app.post('/api/analyze', async (req, res) => {
   }
 
   // 单次请求函数
-  const makeRequest = async (currentModel, currentApiBaseUrl, currentApiKey) => {
+  const makeRequest = async (currentModel) => {
     const controller = new AbortController();
     const timeoutId = setTimeout(() => controller.abort(), 180000); // 180秒超时
 
     try {
-      // Google Gemini API 使用不同的端点格式
-      // 检查是否是 Google Gemini API（密钥以 AIzaSy 开头）
-      const isGeminiApi = currentApiKey.startsWith('AIzaSy');
-      const apiUrl = isGeminiApi 
-        ? `${currentApiBaseUrl}/models/${currentModel}:generateContent?key=${currentApiKey}`
-        : `${currentApiBaseUrl}/chat/completions`;
+      // 使用新的 API 配置系统
+      const apiRequest = buildApiRequest(currentModel, BAZI_SYSTEM_INSTRUCTION, userPrompt, 0.7);
       
-      const headers = isGeminiApi
-        ? { 'Content-Type': 'application/json' }
-        : {
-            'Content-Type': 'application/json',
-            Authorization: `Bearer ${currentApiKey}`,
-          };
-      
-      const requestBody = isGeminiApi
-        ? {
-            contents: [{
-              parts: [{
-                text: `${BAZI_SYSTEM_INSTRUCTION}\n\n${userPrompt}`
-              }]
-            }],
-            generationConfig: {
-              temperature: 0.7,
-            }
-          }
-        : {
-            model: currentModel,
-            messages: [
-              { role: 'system', content: BAZI_SYSTEM_INSTRUCTION },
-              { role: 'user', content: userPrompt },
-            ],
-            temperature: 0.7,
-          };
-      
-      const response = await fetch(apiUrl, {
+      const response = await fetch(apiRequest.url, {
         method: 'POST',
-        headers: headers,
+        headers: apiRequest.headers,
         signal: controller.signal,
-        body: JSON.stringify(requestBody),
+        body: JSON.stringify(apiRequest.body),
       });
 
       clearTimeout(timeoutId);
@@ -412,7 +398,7 @@ app.post('/api/analyze', async (req, res) => {
     while (retryCount <= maxRetries) {
       try {
         console.log(`尝试模型: ${currentModel} (第${retryCount + 1}次)`);
-        const response = await makeRequest(currentModel, apiBaseUrl, apiKey);
+        const response = await makeRequest(currentModel);
 
         if (response.ok) {
           return { success: true, response, model: currentModel };
@@ -495,14 +481,8 @@ app.post('/api/analyze', async (req, res) => {
     });
   }
 
-  // 处理 Google Gemini API 响应格式
-  const isGeminiApi = apiKey.startsWith('AIzaSy');
-  let content;
-  if (isGeminiApi && jsonResult.candidates?.[0]?.content?.parts?.[0]?.text) {
-    content = jsonResult.candidates[0].content.parts[0].text;
-  } else {
-    content = jsonResult.choices?.[0]?.message?.content;
-  }
+  // 使用新的响应解析系统
+  const content = parseApiResponse(jsonResult, usedModel);
   if (!content) return res.status(502).json({ error: 'EMPTY_MODEL_RESPONSE' });
 
   // 清理可能的 markdown 代码块标记
@@ -2531,45 +2511,21 @@ async function generateDailyFortuneAI(bazi, dateKey, dayGanZhi, lunarDateStr, pr
 `;
 
   try {
-    // 检查是否是 Google Gemini API
-    const isGeminiApi = DEFAULT_API_KEY.startsWith('AIzaSy');
-    const apiUrl = isGeminiApi 
-      ? `${DEFAULT_API_BASE_URL}/models/gemini-1.5-pro:generateContent?key=${DEFAULT_API_KEY}`
-      : `${DEFAULT_API_BASE_URL}/chat/completions`;
-    
-    const headers = isGeminiApi
-      ? { 'Content-Type': 'application/json' }
-      : {
-          'Content-Type': 'application/json',
-          'Authorization': `Bearer ${DEFAULT_API_KEY}`,
-        };
+    // 使用新的 API 配置系统
+    const model = 'gpt-4o'; // 使用 GPT-4o 作为默认模型
+    const apiRequest = buildApiRequest(model, AGENT_DAILY_FORTUNE_PROMPT, userPrompt, 0.7);
     
-    const requestBody = isGeminiApi
-      ? {
-          contents: [{
-            parts: [{
-              text: `${AGENT_DAILY_FORTUNE_PROMPT}\n\n${userPrompt}`
-            }]
-          }],
-          generationConfig: {
-            temperature: 0.7,
-            maxOutputTokens: 4000,
-          }
-        }
-      : {
-          model: 'gemini-1.5-pro',
-          messages: [
-            { role: 'system', content: AGENT_DAILY_FORTUNE_PROMPT },
-            { role: 'user', content: userPrompt },
-          ],
-          max_tokens: 4000,
-          temperature: 0.7,
-        };
-
-    const response = await fetch(apiUrl, {
+    // 如果是 OpenAI 格式，添加 max_tokens
+    if (apiRequest.body.max_tokens === undefined && apiRequest.body.generationConfig) {
+      apiRequest.body.generationConfig.maxOutputTokens = 4000;
+    } else if (apiRequest.body.max_tokens === undefined) {
+      apiRequest.body.max_tokens = 4000;
+    }
+
+    const response = await fetch(apiRequest.url, {
       method: 'POST',
-      headers: headers,
-      body: JSON.stringify(requestBody),
+      headers: apiRequest.headers,
+      body: JSON.stringify(apiRequest.body),
     });
 
     if (!response.ok) {
@@ -2578,13 +2534,8 @@ async function generateDailyFortuneAI(bazi, dateKey, dayGanZhi, lunarDateStr, pr
 
     const data = await response.json();
     
-    // 处理 Google Gemini API 响应格式
-    let content;
-    if (isGeminiApi && data.candidates?.[0]?.content?.parts?.[0]?.text) {
-      content = data.candidates[0].content.parts[0].text;
-    } else {
-      content = data.choices?.[0]?.message?.content;
-    }
+    // 使用新的响应解析系统
+    const content = parseApiResponse(data, model);
 
     if (!content) {
       throw new Error('Empty AI response');

server/parallelAnalyzer.js

@@ -15,25 +15,24 @@ import {
   AGENT_CRYPTO_PROMPT,
 } from './agentPrompts.js';
 import { generateFallbackKLine } from './baziCalculator.js';
+import { buildApiRequest, parseApiResponse } from './apiConfig.js';
 
-const DEFAULT_API_BASE_URL = process.env.API_BASE_URL || 'https://generativelanguage.googleapis.com/v1beta';
-const DEFAULT_API_KEY = process.env.API_KEY || 'AIzaSyBiz_9_zhb3c9mxl3dePVfIv1iiao-_6dw'; // Google Gemini API密钥
-
-// 为不同Agent分配最适合的模型（使用 Google Gemini 支持的模型）
+// 为不同Agent分配最适合的模型
 const AGENT_MODEL_ASSIGNMENT = {
-  core: 'gemini-1.5-pro',       // 核心命理 - 逻辑推理强
-  kline_past: 'gemini-1.5-pro',     // 过去K线 - 数据结构化强
-  kline_future: 'gemini-1.5-pro',   // 未来K线 - 数据结构化强
-  career: 'gemini-1.5-pro',                  // 事业财富 - 综合能力
-  marriage: 'gemini-1.5-flash',                     // 婚姻健康 - 快速响应
-  crypto: 'gemini-1.5-pro',                       // 币圈分析 - 币圈知识丰富
+  core: 'grok-4',       // 核心命理 - 逻辑推理强
+  kline_past: 'gpt-4o',     // 过去K线 - 数据结构化强
+  kline_future: 'gpt-4o',   // 未来K线 - 数据结构化强
+  career: 'claude-3-5-sonnet-20241022',                  // 事业财富 - 综合能力
+  marriage: 'grok-4-auto',                     // 婚姻健康 - 快速响应
+  crypto: 'grok-4',                       // 币圈分析 - 币圈知识丰富
 };
 
-// 备用模型列表（Google Gemini 支持的模型）
+// 备用模型列表
 const FALLBACK_MODELS = [
-  'gemini-1.5-flash',
+  'gpt-4o',
+  'grok-4',
+  'claude-3-5-sonnet-20241022',
   'gemini-1.5-pro',
-  'gemini-pro',
 ];
 
 /**
@@ -49,7 +48,7 @@ export const sendSSE = (res, event, data) => {
 /**
  * 单个Agent请求
  */
-const makeAgentRequest = async (agentType, model, apiBaseUrl, apiKey, systemPrompt, userPrompt, timeoutMs = 60000) => {
+const makeAgentRequest = async (agentType, model, systemPrompt, userPrompt, timeoutMs = 60000) => {
   const controller = new AbortController();
   const timeoutId = setTimeout(() => controller.abort(), timeoutMs);
 
@@ -57,44 +56,14 @@ const makeAgentRequest = async (agentType, model, apiBaseUrl, apiKey, systemProm
     console.log(`[Agent:${agentType}] 使用模型 ${model} 开始请求...`);
     const startTime = Date.now();
 
-    // 检查是否是 Google Gemini API
-    const isGeminiApi = apiKey.startsWith('AIzaSy');
-    const apiUrl = isGeminiApi 
-      ? `${apiBaseUrl}/models/${model}:generateContent?key=${apiKey}`
-      : `${apiBaseUrl}/chat/completions`;
-    
-    const headers = isGeminiApi
-      ? { 'Content-Type': 'application/json' }
-      : {
-          'Content-Type': 'application/json',
-          Authorization: `Bearer ${apiKey}`,
-        };
-    
-    const requestBody = isGeminiApi
-      ? {
-          contents: [{
-            parts: [{
-              text: `${systemPrompt}\n\n${userPrompt}`
-            }]
-          }],
-          generationConfig: {
-            temperature: 0.6,
-          }
-        }
-      : {
-          model: model,
-          messages: [
-            { role: 'system', content: systemPrompt },
-            { role: 'user', content: userPrompt },
-          ],
-          temperature: 0.6, // 稍低的温度以保持一致性
-        };
-
-    const response = await fetch(apiUrl, {
+    // 使用新的 API 配置系统
+    const apiRequest = buildApiRequest(model, systemPrompt, userPrompt, 0.6);
+
+    const response = await fetch(apiRequest.url, {
       method: 'POST',
-      headers: headers,
+      headers: apiRequest.headers,
       signal: controller.signal,
-      body: JSON.stringify(requestBody),
+      body: JSON.stringify(apiRequest.body),
     });
 
     clearTimeout(timeoutId);
@@ -102,7 +71,7 @@ const makeAgentRequest = async (agentType, model, apiBaseUrl, apiKey, systemProm
 
     if (!response.ok) {
       const errText = await response.text();
-      console.warn(`[Agent:${agentType}] 请求失败 (${elapsed}s): ${response.status}`);
+      console.warn(`[Agent:${agentType}] 请求失败 (${elapsed}s): ${response.status} - ${errText.substring(0, 200)}`);
       return { success: false, agentType, error: `HTTP ${response.status}`, elapsed };
     }
 
@@ -115,13 +84,8 @@ const makeAgentRequest = async (agentType, model, apiBaseUrl, apiKey, systemProm
       return { success: false, agentType, error: 'INVALID_API_RESPONSE', elapsed };
     }
 
-    // 处理 Google Gemini API 响应格式
-    let content;
-    if (isGeminiApi && jsonResult.candidates?.[0]?.content?.parts?.[0]?.text) {
-      content = jsonResult.candidates[0].content.parts[0].text;
-    } else {
-      content = jsonResult.choices?.[0]?.message?.content;
-    }
+    // 使用新的响应解析系统
+    const content = parseApiResponse(jsonResult, model);
     if (!content) {
       return { success: false, agentType, error: 'EMPTY_RESPONSE', elapsed };
     }
@@ -197,7 +161,7 @@ const makeAgentRequestWithRetry = async (agentType, apiBaseUrl, apiKey, systemPr
 
   for (const model of modelsToTry) {
     for (let attempt = 1; attempt <= maxRetries; attempt++) {
-      const result = await makeAgentRequest(agentType, model, apiBaseUrl, apiKey, systemPrompt, userPrompt);
+      const result = await makeAgentRequest(agentType, model, systemPrompt, userPrompt);
 
       if (result.success) {
         // 验证返回数据是否完整
@@ -307,8 +271,9 @@ const buildAgentUserPrompt = (input, skeletonData, agentType) => {
  * @param {function} onProgress - 进度回调
  */
 export const runParallelAgents = async (input, skeletonData, res, onProgress) => {
-  const apiBaseUrl = DEFAULT_API_BASE_URL;
-  const apiKey = DEFAULT_API_KEY;
+  // 不再需要固定的 API URL 和 Key，由 apiConfig.js 根据模型自动选择
+  const apiBaseUrl = null; // 不再使用
+  const apiKey = null; // 不再使用
 
   const agents = [
     { type: 'core', prompt: AGENT_CORE_PROMPT, priority: 1 },

server/testApi.js

@@ -0,0 +1,71 @@
+/**
+ * API 连接测试端点
+ */
+import { buildApiRequest, parseApiResponse, getApiConfigForModel } from './apiConfig.js';
+import fetch from 'node-fetch';
+
+export async function testAllApis() {
+  const testModels = [
+    { name: 'gpt-4o', provider: 'OpenAI' },
+    { name: 'grok-4', provider: 'Grok' },
+    { name: 'claude-3-5-sonnet-20241022', provider: 'Claude' },
+    { name: 'gemini-1.5-pro', provider: 'Gemini' },
+  ];
+
+  const results = [];
+
+  for (const { name, provider } of testModels) {
+    try {
+      console.log(`测试 ${provider} (${name})...`);
+      const config = getApiConfigForModel(name);
+      const testPrompt = 'Say "Hello" in one word.';
+      
+      const apiRequest = buildApiRequest(name, 'You are a helpful assistant.', testPrompt, 0.7);
+      
+      const startTime = Date.now();
+      const response = await fetch(apiRequest.url, {
+        method: 'POST',
+        headers: apiRequest.headers,
+        body: JSON.stringify(apiRequest.body),
+      });
+      
+      const elapsed = ((Date.now() - startTime) / 1000).toFixed(2);
+      
+      if (!response.ok) {
+        const errorText = await response.text();
+        results.push({
+          provider,
+          model: name,
+          status: 'FAILED',
+          statusCode: response.status,
+          error: errorText.substring(0, 200),
+          elapsed,
+        });
+        continue;
+      }
+
+      const data = await response.json();
+      const content = parseApiResponse(data, name);
+      
+      results.push({
+        provider,
+        model: name,
+        status: 'SUCCESS',
+        statusCode: response.status,
+        response: content?.substring(0, 100) || 'Empty response',
+        elapsed,
+      });
+      
+    } catch (error) {
+      results.push({
+        provider,
+        model: name,
+        status: 'ERROR',
+        error: error.message,
+      });
+    }
+  }
+
+  return results;
+}
+