Update main.ts

main.ts

@@ -1,21 +1,13 @@
 import { serve } from "https://deno.land/std@0.208.0/http/server.ts";
+// [新增] 导入 base64 解码库，用于处理音频数据
+import { decode } from "https://deno.land/std@0.208.0/encoding/base64.ts";
 
 // --- 常量定义 ---
 const MAX_DOCUMENT_SIZE_MB = 20; // 设置最大文档大小限制（单位：MB）
 const MAX_DOCUMENT_SIZE_BYTES = MAX_DOCUMENT_SIZE_MB * 1024 * 1024;
 const MODELS_CACHE_DURATION = 60000; // 1分钟模型缓存
 
-// Gemini 支持的声音列表
-const GEMINI_VOICES = [
-  { name: "Puck", language: "en-US", gender: "neutral" },
-  { name: "Charon", language: "en-US", gender: "neutral" },
-  { name: "Kore", language: "en-US", gender: "neutral" },
-  { name: "Fenrir", language: "en-US", gender: "neutral" },
-  { name: "Aoede", language: "en-US", gender: "neutral" },
-] as const;
-
-type VoiceName = typeof GEMINI_VOICES[number]["name"];
-
+// --- 接口定义 ---
 interface OpenAIMessage {
   role: "system" | "user" | "assistant";
   content: string | Array<{
@@ -34,17 +26,11 @@ interface OpenAIRequest {
   stream?: boolean;
 }
 
-// TTS 相关接口
-interface TTSRequest {
+// [新增] OpenAI TTS 请求接口定义
+interface OpenAITTSRequest {
   model: string;
   input: string;
-  voice?: VoiceName;
-  response_format?: "mp3" | "opus" | "aac" | "flac";
-  speed?: number;
-}
-
-interface TTSResponse {
-  audio: string; // base64 编码的音频数据
+  voice: 'alloy' | 'echo' | 'fable' | 'onyx' | 'shimmer' | 'nova' | string;
 }
 
 class GoogleAIService {
@@ -102,7 +88,6 @@ class GoogleAIService {
         console.log(`Fetched ${this.cachedModels.length} models from Google AI`);
         return this.cachedModels;
       }
-
       return this.getFallbackModels();
     } catch (error) {
       console.warn("Error fetching models from Google AI:", error.message, ". Using fallback models.");
@@ -114,14 +99,79 @@ class GoogleAIService {
     return [
       { name: "models/gemini-1.5-pro", displayName: "Gemini 1.5 Pro", description: "Mid-size multimodal model that supports up to 1 million tokens, images, and documents (PDF, TXT, MD)", supportedGenerationMethods: ["generateContent"], maxTokens: 1000000, supportsDocuments: true },
       { name: "models/gemini-1.5-flash", displayName: "Gemini 1.5 Flash", description: "Fast and versatile multimodal model for diverse tasks, supports images and documents (PDF, TXT, MD)", supportedGenerationMethods: ["generateContent"], maxTokens: 1000000, supportsDocuments: true },
-      { name: "models/gemini-2.0-flash-preview-image-generation", displayName: "Gemini 2.0 Flash Image Generation", description: "Advanced model for generating and editing high-quality images with text and image outputs", supportedGenerationMethods: ["generateContent"], maxTokens: 100000, capabilities: ["text", "image_generation", "image_editing"] }
+      { name: "models/gemini-2.0-flash-preview-image-generation", displayName: "Gemini 2.0 Flash Image Generation", description: "Advanced model for generating and editing high-quality images with text and image outputs", supportedGenerationMethods: ["generateContent"], maxTokens: 100000, capabilities: ["text", "image_generation", "image_editing"] },
+      // [新增] 添加TTS模型到回退列表，确保/v1/models能看到它
+      { name: "models/gemini-2.5-flash-preview-tts", displayName: "Gemini 2.5 Flash TTS", description: "Advanced model for generating high-quality speech from text.", supportedGenerationMethods: ["generateContent"] },
     ];
   }
 
+  // --- 模型能力判断辅助函数 ---
   public isVisionModel = (modelName: string): boolean => modelName.toLowerCase().includes('vision') || modelName.toLowerCase().includes('pro');
   public isImageGenerationModel = (modelName: string): boolean => modelName.includes('image-generation') || modelName === 'gemini-2.0-flash-preview-image-generation';
   public isImageEditingModel = (modelName: string): boolean => modelName.includes('image-generation') || modelName === 'gemini-2.0-flash-preview-image-generation';
   public isDocumentModel = (modelName: string): boolean => modelName.toLowerCase().includes('gemini-1.5') || modelName.toLowerCase().includes('pro') || modelName.toLowerCase().includes('flash');
+  // [新增] 判断是否为TTS模型
+  public isTTSModel = (modelName: string): boolean => modelName.toLowerCase().includes('tts');
+
+
+  /**
+   * [新增] 调用 Gemini TTS API 生成语音
+   * @param text 要转换为语音的文本
+   * @param modelName 使用的TTS模型名称
+   * @param voiceName 使用的语音名称 (e.g., "Kore", "Krew")
+   * @returns 返回 Base64 编码的 MP3 音频数据字符串
+   */
+  async generateSpeech(text: string, modelName: string, voiceName: string): Promise<string> {
+    const apiKey = this.getNextApiKey();
+    const fullModelName = modelName.startsWith('models/') ? modelName : `models/${modelName}`;
+
+    console.log(`Generating speech with model: ${fullModelName}, voice: ${voiceName}`);
+
+    const requestBody = {
+      contents: [{
+        parts: [{ "text": text }]
+      }],
+      generationConfig: {
+        responseModalities: ["AUDIO"],
+        speechConfig: {
+          // 直接请求 MP3 格式，兼容性最好
+          outputAudioEncoding: "MP3",
+          voiceConfig: {
+            prebuiltVoiceConfig: {
+              voiceName: voiceName
+            }
+          }
+        }
+      },
+      model: fullModelName,
+    };
+
+    const response = await fetch(
+      `https://generativelanguage.googleapis.com/v1beta/${fullModelName}:generateContent?key=${apiKey}`,
+      {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify(requestBody),
+      }
+    );
+
+    if (!response.ok) {
+      const errorBody = await response.json().catch(() => response.text());
+      const errorMessage = errorBody?.error?.message || JSON.stringify(errorBody);
+      console.error(`Google TTS API Error: ${response.status} - ${errorMessage}`);
+      throw new Error(`Google TTS API request failed with status ${response.status}: ${errorMessage}`);
+    }
+
+    const data = await response.json();
+    const audioData = data.candidates?.[0]?.content?.parts?.[0]?.inlineData?.data;
+    
+    if (!audioData) {
+      console.error("Invalid TTS response from Google AI:", JSON.stringify(data));
+      throw new Error("No audio data received from Google AI TTS service.");
+    }
+
+    return audioData;
+  }
 
   private getDocumentType(url: string): string {
     const lowerUrl = url.toLowerCase();
@@ -133,17 +183,13 @@ class GoogleAIService {
     return 'unknown';
   }
 
-  /**
-   * [关键改进] 提取并验证文档数据，增加大小检查和更稳健的解析
-   */
   private extractDocumentData(documentUrl: string): { mimeType: string; data: string; text?: string; docType: string } {
     const docType = this.getDocumentType(documentUrl);
+
     if (!documentUrl.startsWith("data:")) {
       if (documentUrl.startsWith("http")) {
         throw new Error("Document URL downloads are not supported. Please provide base64 encoded data URLs.");
       }
-      // 如果不是data url或http url，则假定为纯base64数据，但这是一种不推荐的格式
-      // 为了健壮性，我们强制要求使用标准的 data URL
       throw new Error("Document must be provided as a standard base64 data URL (e.g., 'data:application/pdf;base64,...').");
     }
 
@@ -151,16 +197,15 @@ class GoogleAIService {
     if (parts.length !== 2) {
         throw new Error("Invalid data URL format for document. Expected 'data:[mime];base64,[data]'.");
     }
-
     const [mimeInfo, base64Data] = parts;
-    // **改进1: 检查文件大小**
-    // Base64 字符串的长度约是原始数据的 4/3。
+
     const approxSizeInBytes = base64Data.length * 0.75;
     if (approxSizeInBytes > MAX_DOCUMENT_SIZE_BYTES) {
         throw new Error(`Document size (${(approxSizeInBytes / 1024 / 1024).toFixed(2)}MB) exceeds the ${MAX_DOCUMENT_SIZE_MB}MB limit.`);
     }
 
     const mimeType = mimeInfo.split(":")[1]?.split(";")[0] || 'application/octet-stream';
+
     if (docType === 'txt' || docType === 'md') {
       try {
         const textContent = atob(base64Data);
@@ -170,12 +215,11 @@ class GoogleAIService {
         throw new Error(`Invalid base64 encoding for ${docType} document.`);
       }
     }
-
-    // 自动识别PDF的MIME类型
+    
     const finalMimeType = docType === 'pdf' ? 'application/pdf' : mimeType;
     return { mimeType: finalMimeType, data: base64Data, docType };
   }
-
+  
   private extractImageData(imageUrl: string): { mimeType: string; data: string } {
     if (imageUrl.startsWith("data:image/")) {
       const [mimeInfo, base64Data] = imageUrl.split(",");
@@ -192,6 +236,7 @@ class GoogleAIService {
     const apiKey = this.getNextApiKey();
     const fullModelName = modelName.startsWith('models/') ? modelName : `models/${modelName}`;
     const documentModel = this.isDocumentModel(fullModelName) ? fullModelName : 'models/gemini-1.5-pro-latest';
+
     console.log(`Processing document with model: ${documentModel}`);
 
     let contents;
@@ -203,28 +248,27 @@ class GoogleAIService {
 
         const messageParts = msg.content.map(part => {
           if (part.type === "text") return { text: part.text };
+
           if (part.type === "image_url" && part.image_url) {
             const { mimeType, data } = this.extractImageData(part.image_url.url);
             return { inlineData: { mimeType, data } };
           }
+
           if (part.type === "document" && part.document) {
             const docData = this.extractDocumentData(part.document.url);
             console.log(`Processing document: ${docData.docType}, mime: ${docData.mimeType}, size: ${(docData.data.length * 0.75 / 1024).toFixed(2)} KB`);
 
             if (docData.docType === 'txt' || docData.docType === 'md') {
-              const prefix = docData.docType === 'md' ? 'Markdown document content:\\n' : 'Text document content:\\n';
+              const prefix = docData.docType === 'md' ? 'Markdown document content:\n' : 'Text document content:\n';
               return { text: `${prefix}${docData.text}` };
             }
-
             if (docData.docType === 'pdf') {
               return { inlineData: { mimeType: docData.mimeType, data: docData.data } };
             }
-
             return { text: `[Document type '${docData.docType}' is not supported for direct processing. Please convert to PDF, TXT, or MD.]` };
           }
           return { text: "" };
         });
-
         return { role: msg.role === "assistant" ? "model" : "user", parts: messageParts.filter(p => p.text || p.inlineData) };
       });
     } catch (error) {
@@ -268,70 +312,13 @@ class GoogleAIService {
     if (candidate.finishReason === "SAFETY") {
         throw new Error("Response blocked due to safety filters. Check content for sensitive topics.");
     }
-
     if (candidate.finishReason === "RECITATION") {
         throw new Error("Response blocked due to recitation policy. The model's output was too similar to a copyrighted source.");
     }
 
     return candidate.content?.parts[0]?.text || "Document processed, but no text response was generated.";
   }
-
-  // TTS 功能
-  async generateSpeech(text: string, voice: VoiceName = "Puck", model: string): Promise<string> {
-    const apiKey = this.getNextApiKey();
-
-    const requestBody = {
-      "contents": [{
-          "parts":[{
-            "text": text
-          }]
-        }],
-      "generationConfig": {
-        "responseModalities": ["AUDIO"],
-        "speechConfig": {
-          "voiceConfig": {
-            "prebuiltVoiceConfig": {
-              "voiceName": voice
-            }
-          }
-        }
-      },
-      "model": model,
-    };
-
-    try {
-      const response = await fetch(
-        `https://generativelanguage.googleapis.com/v1beta/models/${model}:generateContent?key=${apiKey}`,
-        {
-          method: "POST",
-          headers: { "Content-Type": "application/json" },
-          body: JSON.stringify(requestBody)
-        }
-      );
-
-      if (!response.ok) {
-        const errorText = await response.text();
-        throw new Error(`Gemini TTS API error: ${response.status} - ${errorText}`);
-      }
-
-      const data = await response.json();
-
-      if (!data.audioContent) {
-        throw new Error("No audio content returned from Gemini TTS");
-      }
-
-      return data.audioContent; // 返回 base64 编码的音频数据
-    } catch (error) {
-      console.error("Error generating speech:", error);
-      throw error;
-    }
-  }
-
-  // 获取可用的声音列表
-  getAvailableVoices(): typeof GEMINI_VOICES {
-    return GEMINI_VOICES;
-  }
-
+  
   async generateContent(messages: OpenAIMessage[], modelName: string, enableSearch: boolean = false): Promise<string> {
     const hasDocument = messages.some(msg => Array.isArray(msg.content) && msg.content.some(part => part.type === "document"));
     if (hasDocument) {
@@ -340,6 +327,7 @@ class GoogleAIService {
 
     const apiKey = this.getNextApiKey();
     const fullModelName = modelName.startsWith('models/') ? modelName : `models/${modelName}`;
+
     const contents = messages.map(msg => {
       if (typeof msg.content === "string") {
         return { role: msg.role === "assistant" ? "model" : "user", parts: [{ text: msg.content }] };
@@ -366,7 +354,6 @@ class GoogleAIService {
       contents,
       generationConfig: { temperature: 0.7, maxOutputTokens: 4096 }
     };
-
     if (enableSearch) {
       requestBody.tools = [{ googleSearchRetrieval: {} }];
     }
@@ -380,17 +367,14 @@ class GoogleAIService {
       const errorText = await response.text();
       throw new Error(`Google AI API error: ${response.status} - ${errorText}`);
     }
-
     const data = await response.json();
     if (!data.candidates || data.candidates.length === 0) {
       throw new Error("No response generated from Google AI");
     }
-
     const candidate = data.candidates[0];
     if (candidate.finishReason === "SAFETY") {
       throw new Error("Response blocked due to safety filters");
     }
-
     return candidate.content?.parts[0]?.text || "No response generated";
   }
 
@@ -420,7 +404,6 @@ class GoogleAIService {
       const errorText = await response.text();
       throw new Error(`Image ${inputImage ? 'editing' : 'generation'} failed: ${response.status} - ${errorText}`);
     }
-
     const data = await response.json();
     if (!data.candidates || data.candidates.length === 0) {
       throw new Error(`No ${inputImage ? 'edited' : 'generated'} image returned`);
@@ -447,10 +430,9 @@ class GoogleAIService {
       result.imageBase64 = imageBase64;
       result.imageUrl = `data:image/png;base64,${imageBase64}`;
     }
-
     return result;
   }
-
+    
   async generateContentWithGrounding(messages: OpenAIMessage[], modelName: string): Promise<string> {
     const apiKey = this.getNextApiKey();
     const fullModelName = modelName.startsWith('models/') ? modelName : `models/${modelName}`;
@@ -481,7 +463,6 @@ class GoogleAIService {
     if (candidate.finishReason === "SAFETY") {
       throw new Error("Response blocked due to safety filters");
     }
-
     return candidate.content?.parts[0]?.text || "No response generated";
   }
 
@@ -529,102 +510,62 @@ class OpenAICompatibleServer {
     return authHeader ? authHeader.replace("Bearer ", "") === this.authKey : false;
   }
 
-  private isDocumentContent(url?: string): boolean {
-    if (!url) return false;
-    const lowerUrl = url.toLowerCase();
-    return lowerUrl.includes('.pdf') || lowerUrl.startsWith('data:application/pdf') ||
-           lowerUrl.includes('.txt') || lowerUrl.startsWith('data:text/plain') ||
-           lowerUrl.includes('.md') || lowerUrl.startsWith('data:text/markdown');
-  }
-
-  private async handleTTS(request: Request): Promise<Response> {
+  /**
+   * [新增] 处理 TTS 请求的句柄
+   * @param request - HTTP 请求对象
+   * @returns 返回包含 MP3 音频数据的响应
+   */
+  private async handleAudioSpeech(request: Request): Promise<Response> {
     try {
-      const body: TTSRequest = await request.json();
-      const { input, voice = "Puck", model } = body;
-
-      // 验证输入
-      if (!input || input.trim().length === 0) {
-        return new Response(
-          JSON.stringify({
-            error: {
-              message: "Input text is required",
-              type: "invalid_request_error",
-              code: null
-            }
-          }),
-          { status: 400, headers: { "Content-Type": "application/json" } }
-        );
-      }
+      const body: OpenAITTSRequest = await request.json();
 
-      // 验证声音
-      const availableVoices = this.googleAI.getAvailableVoices();
-      const isValidVoice = availableVoices.some(v => v.name === voice);
-      if (!isValidVoice) {
-        return new Response(
-          JSON.stringify({
-            error: {
-              message: `Invalid voice "${voice}". Available voices: ${availableVoices.map(v => v.name).join(", ")}`,
-              type: "invalid_request_error",
-              code: null
-            }
-          }),
-          { status: 400, headers: { "Content-Type": "application/json" } }
-        );
-      }
+      // 模型映射: 将 OpenAI 标准模型名映射到 Gemini 模型名
+      const modelMap: { [key: string]: string } = {
+        'tts-1': 'gemini-2.5-flash-preview-tts',
+        'tts-1-hd': 'gemini-2.5-flash-preview-tts', // HD 也暂时映射到同一个
+      };
+      const geminiModel = modelMap[body.model] || (this.googleAI.isTTSModel(body.model) ? body.model : 'gemini-2.5-flash-preview-tts');
 
-      console.log(`TTS request: voice=${voice}, text length=${input.length}`);
+      // 语音映射: 将 OpenAI 标准语音名映射到 Gemini 语音名
+      const voiceMap: { [key: string]: string } = {
+        'alloy': 'Krew', 'echo': 'Kore', 'fable': 'Chiron',
+        'onyx': 'Calypso', 'nova': 'Cria', 'shimmer': 'Estrella',
+      };
+      const geminiVoice = voiceMap[body.voice] || 'Kore'; // 默认使用 Kore
 
-      // 生成语音
-      const audioBase64 = await this.googleAI.generateSpeech(input, voice, model);
+      if (!body.input) {
+        throw new Error("The 'input' field is required for TTS requests.");
+      }
 
-      // 将 base64 转换为二进制数据
-      const audioData = Uint8Array.from(atob(audioBase64), c => c.charCodeAt(0));
+      const audioBase64 = await this.googleAI.generateSpeech(body.input, geminiModel, geminiVoice);
+      const audioBytes = decode(audioBase64);
 
-      return new Response(audioData, {
-        headers: {
-          "Content-Type": "audio/mpeg",
-          "Content-Length": audioData.length.toString()
-        }
+      return new Response(audioBytes, {
+        headers: { "Content-Type": "audio/mpeg" }
       });
 
     } catch (error) {
-      console.error("Error in TTS:", error.message);
+      console.error("Error in audio speech generation:", error.message);
+      const status = error.message.includes("required") ? 400 : 500;
       return new Response(
         JSON.stringify({
           error: {
             message: error.message,
-            type: "api_error",
-            code: null
+            type: status === 400 ? "invalid_request_error" : "api_error",
+            code: "tts_failed"
           }
         }),
-        { status: 500, headers: { "Content-Type": "application/json" } }
+        { status, headers: { "Content-Type": "application/json" } }
       );
     }
   }
 
-  private async handleVoices(): Promise<Response> {
-    try {
-      const voices = this.googleAI.getAvailableVoices();
-      const voicesResponse = {
-        object: "list",
-        data: voices.map(voice => ({
-          id: voice.name,
-          name: voice.name,
-          language: voice.language,
-          gender: voice.gender
-        }))
-      };
-
-      return new Response(JSON.stringify(voicesResponse), {
-        headers: { "Content-Type": "application/json" }
-      });
-    } catch (error) {
-      console.error("Error fetching voices:", error);
-      return new Response(
-        JSON.stringify({ error: { message: "Failed to fetch voices." } }),
-        { status: 500, headers: { "Content-Type": "application/json" } }
-      );
-    }
+  private isDocumentContent(url?: string): boolean {
+    if (!url) return false;
+    const lowerUrl = url.toLowerCase();
+    return lowerUrl.includes('.pdf') || lowerUrl.startsWith('data:application/pdf') ||
+           lowerUrl.includes('.txt') || lowerUrl.startsWith('data:text/plain') ||
+           lowerUrl.includes('.md') || lowerUrl.startsWith('data:text/markdown');
   }
 
   private async handleChatCompletions(request: Request): Promise<Response> {
@@ -645,7 +586,7 @@ class OpenAICompatibleServer {
       );
 
       const hasImages = body.messages.some(msg => Array.isArray(msg.content) && msg.content.some(part => part.type === "image_url"));
-
+      
       let inputImages: any[] = [];
       if (hasImages) {
         body.messages.forEach(msg => {
@@ -656,8 +597,9 @@ class OpenAICompatibleServer {
           }
         });
       }
-
+      
       let responseText: string;
+
       // Routing logic based on keywords and content types
       if (hasDocument) {
         responseText = await this.googleAI.generateContentWithDocument(body.messages, requestedModel);
@@ -701,7 +643,7 @@ class OpenAICompatibleServer {
       );
     }
   }
-
+  
   private async streamStringAsOpenAIResponse(content: string, modelName: string): Promise<ReadableStream<Uint8Array>> {
     const encoder = new TextEncoder();
     const streamId = `chatcmpl-${Date.now()}`;
@@ -711,56 +653,62 @@ class OpenAICompatibleServer {
     return new ReadableStream({
         start(controller) {
             const initialChunk = { id: streamId, object: 'chat.completion.chunk', created: creationTime, model: modelName, choices: [{ index: 0, delta: { role: 'assistant', content: '' }, finish_reason: null }] };
-            controller.enqueue(encoder.encode(`data: ${JSON.stringify(initialChunk)}\\n\\n`));
+            controller.enqueue(encoder.encode(`data: ${JSON.stringify(initialChunk)}\n\n`));
         },
         pull(controller) {
             if (contentQueue.length === 0) {
                 const finalChunk = { id: streamId, object: 'chat.completion.chunk', created: creationTime, model: modelName, choices: [{ index: 0, delta: {}, finish_reason: 'stop' }] };
-                controller.enqueue(encoder.encode(`data: ${JSON.stringify(finalChunk)}\\n\\n`));
-                controller.enqueue(encoder.encode('data: [DONE]\\n\\n'));
+                controller.enqueue(encoder.encode(`data: ${JSON.stringify(finalChunk)}\n\n`));
+                controller.enqueue(encoder.encode('data: [DONE]\n\n'));
                 controller.close();
                 return;
             }
             const char = contentQueue.shift();
             const chunk = { id: streamId, object: 'chat.completion.chunk', created: creationTime, model: modelName, choices: [{ index: 0, delta: { content: char }, finish_reason: null }] };
-            controller.enqueue(encoder.encode(`data: ${JSON.stringify(chunk)}\\n\\n`));
+            controller.enqueue(encoder.encode(`data: ${JSON.stringify(chunk)}\n\n`));
         }
     });
   }
-
+  
   private async handleModels(): Promise<Response> {
     try {
       const googleModels = await this.googleAI.fetchOfficialModels();
-      const models = {
-        object: "list",
-        data: googleModels.map(model => {
-          const modelId = model.name.replace('models/', '');
-          return {
-            id: modelId, object: "model", created: Math.floor(Date.now() / 1000), owned_by: "google",
-            description: model.description || model.displayName, maxTokens: model.inputTokenLimit || model.maxTokens
-          };
-        })
-      };
+      const openAIFormattedModels = googleModels.map(model => {
+        const modelId = model.name.replace('models/', '');
+        return {
+          id: modelId,
+          object: "model",
+          created: Math.floor(Date.now() / 1000),
+          owned_by: "google",
+          description: model.description || model.displayName,
+          maxTokens: model.inputTokenLimit || model.maxTokens
+        };
+      });
+
+      // 确保TTS模型以OpenAI兼容的名称存在
+      if (openAIFormattedModels.some(m => this.googleAI.isTTSModel(m.id))) {
+          if (!openAIFormattedModels.some(m => m.id === 'tts-1')) {
+              openAIFormattedModels.push({
+                  id: 'tts-1', object: "model", created: Math.floor(Date.now() / 1000), owned_by: "google",
+                  description: "Text-to-speech model, mapped to gemini-2.5-flash-preview-tts", maxTokens: 4096
+              });
+          }
+      }
+
+      const models = { object: "list", data: openAIFormattedModels };
       return new Response(JSON.stringify(models), { headers: { "Content-Type": "application/json" } });
     } catch (error) {
       console.error("Error fetching models:", error);
       return new Response(JSON.stringify({ error: { message: "Failed to fetch models." } }), { status: 500 });
     }
   }
-
+  
   private async handleStatus(): Promise<Response> {
       const status = {
-          status: "healthy", timestamp: new Date().toISOString(), version: "2.6.0",
+          status: "healthy", timestamp: new Date().toISOString(), version: "2.5.0",
           api_keys_loaded: this.googleAI.apiKeys.length,
           models_in_cache: this.googleAI.cachedModels.length,
-          models_last_fetched: this.googleAI.modelsLastFetch > 0 ? new Date(this.googleAI.modelsLastFetch).toISOString() : "never",
-          features: {
-            chat_completions: true,
-            image_generation: true,
-            document_processing: true,
-            text_to_speech: true,
-            voice_list: true
-          }
+          models_last_fetched: this.googleAI.modelsLastFetch > 0 ? new Date(this.googleAI.modelsLastFetch).toISOString() : "never"
       };
       return new Response(JSON.stringify(status), { headers: { "Content-Type": "application/json" } });
   }
@@ -779,19 +727,18 @@ class OpenAICompatibleServer {
     const url = new URL(request.url);
     let response: Response;
 
-    // Handle routes
+    // --- [更新] 路由处理 ---
     if (url.pathname === "/health" || url.pathname === "/status") {
       response = await this.handleStatus();
     } else if (!this.authenticate(request)) {
       response = new Response(JSON.stringify({ error: { message: "Unauthorized" } }), { status: 401 });
+    } else if (url.pathname === "/v1/audio/speech" && request.method === "POST") {
+      // [新增] 路由到 TTS 处理器
+      response = await this.handleAudioSpeech(request);
     } else if (url.pathname === "/v1/chat/completions" && request.method === "POST") {
       response = await this.handleChatCompletions(request);
     } else if (url.pathname === "/v1/models" && request.method === "GET") {
       response = await this.handleModels();
-    } else if (url.pathname === "/v1/audio/speech" && request.method === "POST") {
-      response = await this.handleTTS(request);
-    } else if (url.pathname === "/v1/voices" && request.method === "GET") {
-      response = await this.handleVoices();
     } else {
       response = new Response("Not Found", { status: 404 });
     }
@@ -808,7 +755,8 @@ class OpenAICompatibleServer {
 
 // --- 服务器启动 ---
 const server = new OpenAICompatibleServer();
-console.log("🚀 OpenAI Compatible Server with Google AI and TTS starting on port 7860...");
+
+console.log("🚀 OpenAI Compatible Server with Google AI starting on port 8000...");
 console.log(`✅ Loaded ${server.googleAI.apiKeys.length} API key(s).`);
 console.log(`📄 Max document size set to ${MAX_DOCUMENT_SIZE_MB}MB.`);
 
@@ -819,17 +767,13 @@ server.googleAI.fetchOfficialModels().then(models => {
   console.warn(`⚠️ Could not pre-fetch models: ${error.message}. Will use fallbacks or fetch on first request.`);
 });
 
-console.log("\\n🔗 Endpoints:");
+console.log("\n🔗 Endpoints:");
 console.log("   POST /v1/chat/completions");
+console.log("   POST /v1/audio/speech"); // [新增]
 console.log("   GET  /v1/models");
-console.log("   POST /v1/audio/speech (TTS)");
-console.log("   GET  /v1/voices");
 console.log("   GET  /status");
 
-const voices = server.googleAI.getAvailableVoices();
-console.log(`\\n🎤 Available TTS voices: ${voices.map(v => v.name).join(", ")}`);
-
 await serve(
   (request: Request) => server.handleRequest(request),
   { port: 7860 }
-);
+);