[ { "path": ".eslintrc.json", "content": "{\n \"extends\": \"next/core-web-vitals\"\n}\n" }, { "path": ".gitignore", "content": "# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.\n\n# dependencies\n/node_modules\n/.pnp\n.pnp.js\n\n# testing\n/coverage\n\n# next.js\n/.next/\n/out/\n\n# production\n/build\n\n# misc\n.DS_Store\n*.pem\n\n# debug\nnpm-debug.log*\nyarn-debug.log*\nyarn-error.log*\n\n# local env files\n.env\n.env*.local\n\n# vercel\n.vercel\n\n# typescript\n*.tsbuildinfo\nnext-env.d.ts\n" }, { "path": "README.md", "content": "# AI 翻译助手\n\n一个功能强大的 AI 驱动的多语言翻译和内容处理平台。\n\n## 主要功能\n\n### 1. 多模态翻译\n- **文本翻译**：支持无限次免费文本翻译，多种语言互译\n- **图片识别**：支持图片内容识别和翻译，可处理多种格式图片\n- **PDF 处理**：支持 PDF 文档内容提取和翻译，优化的文本提取算法\n- **语音识别**：支持语音内容识别和转换，多种语言支持\n- **视频处理**：支持视频内容提取和字幕生成，自动时间轴对齐\n\n### 2. 高级 AI 模型支持\n- **多模型集成**：支持 GPT、Gemini、Kimi、Mistral 等多种 AI 模型\n- **智能模型选择**：根据内容类型自动选择最佳模型处理\n- **模型备份机制**：当主要模型失败时自动切换到备用模型\n- **高质量翻译**：专业级翻译质量，保留原文格式和语义\n\n### 3. 会员订阅系统\n- **分级会员制**：支持试用版、月度会员和年度会员\n- **差异化配额**：不同会员等级享有不同的服务配额\n- **自动续期**：支持 Stripe 订阅自动续费\n- **订阅管理**：支持查看订阅状态、到期时间等\n- **订阅过期处理**：订阅到期后自动重置为试用版状态\n\n### 4. 用户系统\n- **账号管理**：支持邮箱注册和登录\n- **社交登录**：支持 GitHub 和 Google 账号登录\n- **个人资料**：支持修改用户名等基本信息\n- **使用统计**：实时显示各项功能的使用情况\n\n### 5. 配额管理\n- **每日重置**：免费用户的使用配额每日0点自动重置\n- **实时统计**：显示当日各项功能的剩余使用次数\n- **配额升级**：付费会员可获得更多使用次数\n - **试用版**：\n - 无限文本翻译\n - 5次/日图片识别\n - 3次/日PDF处理\n - 2次/日语音识别\n - 1次/日视频处理\n - **月度会员**：\n - 无限文本翻译\n - 50次/日图片识别\n - 40次/日PDF处理\n - 30次/日语音识别\n - 10次/日视频处理\n - **年度会员**：\n - 无限文本翻译\n - 100次/日图片识别\n - 80次/日PDF处理\n - 60次/日语音识别\n - 20次/日视频处理\n\n### 6. 性能优化\n- **PDF处理优化**：\n - 多种文本提取方法，提高成功率\n - 备用处理机制，当OCR API失败时使用聊天API提取内容\n - 减少重试次数和等待时间，提升用户体验\n- **响应式设计**：适配各种设备屏幕尺寸\n- **多语言界面**：支持中英文界面切换\n- **快速响应**：优化的API调用和缓存机制\n\n## 技术栈\n\n- **前端**：Next.js 14, React, TypeScript, Tailwind CSS\n- **后端**：Node.js, PostgreSQL (Neon Serverless)\n- **认证**：NextAuth.js\n- **支付**：Stripe\n- **国际化**：自定义i18n解决方案\n- **云服务**：\n - 阿里云 OSS（文件存储）\n - 腾讯云（AI 服务）\n - 多种AI模型API集成\n\n## 环境变量配置\n\n项目运行需要配置以下环境变量：\n\n```env\n# 数据库配置\nDATABASE_URL=\n\n# 认证相关\nNEXTAUTH_SECRET=\nNEXTAUTH_URL=\n\n# GitHub OAuth\nGITHUB_ID=\nGITHUB_SECRET=\n\n# Google OAuth\nGOOGLE_CLIENT_ID=\nGOOGLE_CLIENT_SECRET=\n\n# Stripe 配置\nSTRIPE_SECRET_KEY=\nNEXT_PUBLIC_STRIPE_PUBLISHABLE_KEY=\nSTRIPE_WEBHOOK_SECRET=\nNEXT_PUBLIC_STRIPE_MONTHLY_PRICE_ID=\nNEXT_PUBLIC_STRIPE_YEARLY_PRICE_ID=\nNEXT_PUBLIC_APP_URL=\n\n# 阿里云配置\nALIYUN_ACCESS_KEY_ID=\nALIYUN_ACCESS_KEY_SECRET=\nALIYUN_OSS_BUCKET=\nALIYUN_OSS_REGION=\nALIYUN_RAM_ROLE_ARN=\n\n# AI 模型 API Keys\nNEXT_PUBLIC_GEMINI_API_KEY=\nNEXT_PUBLIC_DEEPSEEK_API_KEY=\nNEXT_PUBLIC_QWEN_API_KEY=\nNEXT_PUBLIC_ZHIPU_API_KEY=\nNEXT_PUBLIC_TENCENT_API_KEY=\nNEXT_PUBLIC_KIMI_API_KEY=\nNEXT_PUBLIC_OPENAI_API_KEY=\nNEXT_PUBLIC_MINNIMAX_API_KEY=\nNEXT_PUBLIC_SILICONFLOW_API_KEY=\nNEXT_PUBLIC_OPENROUTER_API_KEY=\nMISTRAL_API_KEY=\n```\n\n## 开发说明\n\n1. 克隆项目\n```bash\ngit clone [repository-url]\ncd ai-translation-assistant-pro\n```\n\n2. 安装依赖\n```bash\nnpm install\n```\n\n3. 配置环境变量\n```bash\ncp .env.example .env.local\n# 编辑 .env.local 填入相应的值\n```\n\n4. 运行开发服务器\n```bash\nnpm run dev\n```\n\n## 部署\n\n项目可以部署到任何支持 Node.js 的平台。建议使用 Vercel 进行部署：\n\n1. 在 Vercel 中导入项目\n2. 配置环境变量\n3. 部署完成后即可访问\n\n## 许可证\n\n[MIT License](LICENSE) " }, { "path": "app/api/aliyun/oss/sts/route.ts", "content": "import { NextResponse } from 'next/server'\nimport * as $OpenApi from '@alicloud/openapi-client'\nimport * as $STS20150401 from '@alicloud/sts20150401'\n\nexport async function GET() {\n try {\n if (!process.env.ALIYUN_ACCESS_KEY_ID || \n !process.env.ALIYUN_ACCESS_KEY_SECRET || \n !process.env.ALIYUN_RAM_ROLE_ARN || \n !process.env.ALIYUN_OSS_BUCKET ||\n !process.env.ALIYUN_OSS_REGION) {\n throw new Error('缺少必要的环境变量配置');\n }\n\n // 打印 AccessKey 前缀，用于验证\n console.log('AccessKey 信息:', {\n accessKeyIdPrefix: process.env.ALIYUN_ACCESS_KEY_ID.substring(0, 8) + '****',\n region: process.env.ALIYUN_OSS_REGION,\n bucket: process.env.ALIYUN_OSS_BUCKET\n });\n\n console.log('RAM 角色信息:', {\n roleArn: process.env.ALIYUN_RAM_ROLE_ARN,\n accountId: process.env.ALIYUN_RAM_ROLE_ARN.split('::')[1]?.split(':')[0]\n });\n\n const config = new $OpenApi.Config({\n accessKeyId: process.env.ALIYUN_ACCESS_KEY_ID,\n accessKeySecret: process.env.ALIYUN_ACCESS_KEY_SECRET,\n endpoint: 'sts.aliyuncs.com',\n regionId: 'cn-hangzhou' // 使用默认的 cn-hangzhou 地区\n });\n\n const client = new $STS20150401.default(config);\n\n // 获取 STS token，有效期15分钟\n const result = await client.assumeRole({\n roleArn: process.env.ALIYUN_RAM_ROLE_ARN,\n roleSessionName: 'video-upload',\n durationSeconds: 900\n });\n\n console.log('STS 响应成功');\n\n // 检查返回结果的结构\n if (!result.body || !result.body.credentials) {\n console.error('无效的 STS 响应结构:', result);\n throw new Error('无效的 STS 响应');\n }\n\n return NextResponse.json({\n success: true,\n data: {\n region: process.env.ALIYUN_OSS_REGION,\n bucket: process.env.ALIYUN_OSS_BUCKET,\n credentials: {\n accessKeyId: result.body.credentials.accessKeyId,\n accessKeySecret: result.body.credentials.accessKeySecret,\n securityToken: result.body.credentials.securityToken,\n expiration: result.body.credentials.expiration\n }\n }\n });\n } catch (error: any) {\n console.error('获取 STS token 失败:', error);\n console.error('详细错误信息:', {\n code: error.code,\n message: error.message,\n data: error.data,\n statusCode: error.statusCode,\n stack: error.stack\n });\n return NextResponse.json({\n success: false,\n message: `获取上传凭证失败: ${error.message || '未知错误'}`,\n error: {\n code: error.code,\n message: error.message,\n data: error.data,\n statusCode: error.statusCode\n }\n }, { status: 500 });\n }\n} " }, { "path": "app/api/aliyun/oss/upload/route.ts", "content": "import { NextResponse } from 'next/server'\nimport OSS from 'ali-oss'\nimport { v4 as uuidv4 } from 'uuid'\n\nexport async function POST(request: Request) {\n try {\n const formData = await request.formData()\n const file = formData.get('file') as File\n \n if (!file) {\n return NextResponse.json(\n { message: '缺少文件' },\n { status: 400 }\n )\n }\n\n console.log('文件信息:', {\n name: file.name,\n type: file.type,\n size: file.size\n })\n\n // 创建 OSS 客户端\n const ossClient = new OSS({\n region: 'oss-cn-shanghai',\n accessKeyId: process.env.ALIYUN_ACCESS_KEY_ID || '',\n accessKeySecret: process.env.ALIYUN_ACCESS_KEY_SECRET || '',\n bucket: process.env.ALIYUN_OSS_BUCKET || ''\n })\n\n try {\n // 将文件转换为 Buffer\n const arrayBuffer = await file.arrayBuffer()\n const buffer = Buffer.from(arrayBuffer)\n\n // 上传到 OSS\n const ext = file.name.split('.').pop()\n const fileName = `videos/${uuidv4()}.${ext}`\n console.log('开始上传文件到 OSS...')\n \n // 使用 Promise 包装 put 方法\n const uploadResult = await new Promise((resolve, reject) => {\n try {\n // @ts-ignore\n ossClient.put(fileName, buffer).then(result => {\n resolve(result)\n }).catch(err => {\n reject(err)\n })\n } catch (err) {\n reject(err)\n }\n })\n\n console.log('文件上传成功:', uploadResult)\n\n return NextResponse.json({\n success: true,\n url: (uploadResult as any).url\n })\n } catch (uploadError: any) {\n console.error('OSS上传错误:', {\n name: uploadError.name,\n message: uploadError.message,\n code: uploadError.code,\n requestId: uploadError.requestId,\n stack: uploadError.stack\n })\n throw new Error(`文件上传失败: ${uploadError.message}`)\n }\n\n } catch (error: any) {\n console.error('处理请求错误:', error)\n return NextResponse.json(\n { message: error.message || '文件上传失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/aliyun/video-ocr/create/route.ts", "content": "import { NextResponse } from 'next/server'\nimport RPCClient from '@alicloud/pop-core'\n\ninterface AsyncJobResult {\n RequestId: string\n Message: string\n}\n\nexport async function POST(request: Request) {\n try {\n const body = await request.json()\n const { videoUrl } = body\n\n if (!videoUrl) {\n return NextResponse.json(\n { message: '缺少视频URL' },\n { status: 400 }\n )\n }\n\n // 创建视频识别客户端\n const client = new RPCClient({\n accessKeyId: process.env.ALIYUN_ACCESS_KEY_ID || '',\n accessKeySecret: process.env.ALIYUN_ACCESS_KEY_SECRET || '',\n endpoint: 'https://videorecog.cn-shanghai.aliyuncs.com',\n apiVersion: '2020-03-20'\n })\n\n try {\n // 创建视频识别任务\n console.log('开始创建视频识别任务...')\n const params = {\n VideoUrl: videoUrl,\n Params: JSON.stringify([{\n Type: 'subtitles'\n }])\n }\n\n // 发送请求\n const result = await client.request('RecognizeVideoCastCrewList', params, {\n method: 'POST',\n formatParams: false,\n headers: {\n 'content-type': 'application/json'\n }\n })\n \n console.log('创建任务结果:', result)\n\n if (!result.RequestId) {\n throw new Error('创建任务失败：未获取到任务ID')\n }\n\n return NextResponse.json({\n success: true,\n taskId: result.RequestId,\n message: result.Message\n })\n } catch (createError: any) {\n console.error('创建任务错误详情:', {\n name: createError.name,\n message: createError.message,\n code: createError.code,\n requestId: createError.RequestId,\n stack: createError.stack\n })\n throw new Error(`创建视频识别任务失败: ${createError.message}`)\n }\n\n } catch (error: any) {\n console.error('处理请求错误:', error)\n return NextResponse.json(\n { message: error.message || '创建视频识别任务失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/aliyun/video-ocr/query/route.ts", "content": "import { NextResponse } from 'next/server'\nimport RPCClient from '@alicloud/pop-core'\n\ninterface AsyncJobQueryResult {\n RequestId: string\n Data: {\n Status: string\n Result: string\n JobId: string\n }\n}\n\nexport async function POST(request: Request) {\n try {\n const body = await request.json()\n const { taskId } = body\n\n if (!taskId) {\n return NextResponse.json(\n { message: '缺少任务ID' },\n { status: 400 }\n )\n }\n\n // 创建视频识别客户端\n const client = new RPCClient({\n accessKeyId: process.env.ALIYUN_ACCESS_KEY_ID || '',\n accessKeySecret: process.env.ALIYUN_ACCESS_KEY_SECRET || '',\n endpoint: 'https://videorecog.cn-shanghai.aliyuncs.com',\n apiVersion: '2020-03-20'\n })\n\n try {\n // 查询任务结果\n console.log('开始查询任务结果, taskId:', taskId)\n const params = {\n JobId: taskId\n }\n\n // 发送请求\n const result = await client.request('GetAsyncJobResult', params)\n \n console.log('原始查询结果:', JSON.stringify(result, null, 2))\n\n if (!result.Data) {\n console.log('未获取到Data字段:', result)\n throw new Error('查询任务失败：未获取到任务结果')\n }\n\n console.log('任务状态:', result.Data.Status)\n console.log('任务结果:', result.Data.Result)\n\n // 如果任务还在处理中，返回特定状态码\n if (result.Data.Status === 'PROCESS_RUNNING') {\n console.log('任务正在处理中...')\n return NextResponse.json({\n success: true,\n status: 'running',\n message: '任务正在处理中'\n }, { status: 202 })\n }\n\n // 如果任务失败，抛出错误\n if (result.Data.Status === 'PROCESS_FAILED') {\n console.log('任务处理失败')\n throw new Error('任务处理失败')\n }\n\n // 如果任务成功完成，返回结果\n if (result.Data.Status === 'PROCESS_SUCCESS') {\n console.log('任务处理成功，开始解析结果')\n let ocrResult = {}\n try {\n if (typeof result.Data.Result === 'string') {\n console.log('解析字符串结果')\n ocrResult = JSON.parse(result.Data.Result)\n } else {\n console.log('使用原始结果对象')\n ocrResult = result.Data.Result\n }\n console.log('解析后的结果:', ocrResult)\n } catch (e) {\n console.error('解析OCR结果失败:', e)\n console.log('使用原始结果')\n ocrResult = result.Data.Result\n }\n\n return NextResponse.json({\n success: true,\n status: 'success',\n data: ocrResult\n })\n }\n\n // 其他状态\n console.log('未知的任务状态:', result.Data.Status)\n return NextResponse.json({\n success: false,\n status: result.Data.Status,\n message: '未知的任务状态',\n data: result.Data\n })\n\n } catch (queryError: any) {\n console.error('查询任务错误详情:', {\n name: queryError.name,\n message: queryError.message,\n code: queryError.code,\n requestId: queryError.RequestId,\n stack: queryError.stack\n })\n throw new Error(`查询视频识别任务失败: ${queryError.message}`)\n }\n\n } catch (error: any) {\n console.error('处理请求错误:', error)\n return NextResponse.json(\n { message: error.message || '查询视频识别任务失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/aliyun/video-ocr/status/route.ts", "content": "import { NextResponse } from 'next/server'\nimport RPCClient from '@alicloud/pop-core'\n\ninterface VideoOCRResult {\n OcrResults?: Array<{\n DetailInfo: Array<{\n Text: string\n TimeStamp: number\n }>\n StartTime: number\n EndTime: number\n }>\n VideoOcrResults?: Array<{\n DetailInfo: Array<{\n Text: string\n }>\n StartTime: number\n EndTime: number\n }>\n SubtitlesResults?: Array<{\n SubtitlesAllResults?: Record\n SubtitlesChineseResults?: Record\n SubtitlesEnglishResults?: Record\n SubtitlesAllResultsUrl?: string\n SubtitlesChineseResultsUrl?: string\n SubtitlesEnglishResultsUrl?: string\n }>\n}\n\ninterface AsyncJobQueryResult {\n RequestId: string\n Data: {\n Status: string\n Result: string\n JobId: string\n }\n}\n\nexport async function POST(request: Request) {\n try {\n const body = await request.json()\n const { taskId } = body\n\n if (!taskId) {\n return NextResponse.json(\n { message: '缺少任务ID' },\n { status: 400 }\n )\n }\n\n // 创建视频识别客户端\n const client = new RPCClient({\n accessKeyId: process.env.ALIYUN_ACCESS_KEY_ID || '',\n accessKeySecret: process.env.ALIYUN_ACCESS_KEY_SECRET || '',\n endpoint: 'https://videorecog.cn-shanghai.aliyuncs.com',\n apiVersion: '2020-03-20',\n opts: {\n method: 'POST',\n timeout: 60000\n }\n })\n\n try {\n // 查询任务结果\n console.log('开始查询任务结果, taskId:', taskId)\n const params = {\n JobId: taskId\n }\n\n // 发送请求\n const result = await client.request('GetAsyncJobResult', params, {\n method: 'POST',\n formatParams: true,\n headers: {\n 'content-type': 'application/x-www-form-urlencoded'\n }\n })\n \n console.log('原始查询结果:', JSON.stringify(result, null, 2))\n\n // 检查结果格式\n if (!result || !result.Data) {\n console.log('未获取到Data字段:', result)\n throw new Error('查询任务失败：未获取到任务结果')\n }\n\n console.log('任务状态:', result.Data.Status)\n\n // 处理不同的任务状态\n switch (result.Data.Status) {\n case 'PROCESS_RUNNING':\n console.log('任务正在处理中...')\n return NextResponse.json({\n success: true,\n status: 'running',\n message: '任务正在处理中'\n }, { status: 202 })\n\n case 'PROCESS_FAILED':\n console.log('任务处理失败:', result.Data)\n return NextResponse.json({\n success: false,\n status: 'failed',\n message: '任务处理失败',\n data: result.Data\n }, { status: 500 })\n\n case 'PROCESS_SUCCESS':\n console.log('任务处理成功，开始解析结果')\n let ocrResult: VideoOCRResult | null = null\n \n try {\n // 尝试解析结果\n if (result.Data.Result) {\n console.log('解析字符串结果:', result.Data.Result)\n if (typeof result.Data.Result === 'string') {\n ocrResult = JSON.parse(result.Data.Result)\n } else {\n ocrResult = result.Data.Result as VideoOCRResult\n }\n }\n\n // 提取所有文本内容\n const textContents: string[] = []\n \n // 处理 OcrResults\n if (ocrResult?.OcrResults) {\n ocrResult.OcrResults.forEach(result => {\n result.DetailInfo.forEach(detail => {\n if (detail.Text) {\n textContents.push(detail.Text)\n }\n })\n })\n }\n\n // 处理 VideoOcrResults\n if (ocrResult?.VideoOcrResults) {\n ocrResult.VideoOcrResults.forEach(result => {\n result.DetailInfo.forEach(detail => {\n if (detail.Text) {\n textContents.push(detail.Text)\n }\n })\n })\n }\n\n // 处理字幕结果\n if (ocrResult?.SubtitlesResults?.[0]) {\n const subtitles = ocrResult.SubtitlesResults[0]\n if (subtitles.SubtitlesChineseResults) {\n Object.values(subtitles.SubtitlesChineseResults).forEach(text => {\n textContents.push(text)\n })\n }\n return NextResponse.json({\n success: true,\n status: 'success',\n data: {\n text: textContents.join('\\n'),\n subtitles: {\n all: subtitles.SubtitlesAllResults,\n chinese: subtitles.SubtitlesChineseResults,\n english: subtitles.SubtitlesEnglishResults,\n allUrl: subtitles.SubtitlesAllResultsUrl,\n chineseUrl: subtitles.SubtitlesChineseResultsUrl,\n englishUrl: subtitles.SubtitlesEnglishResultsUrl\n },\n raw: ocrResult\n }\n })\n }\n\n // 如果没有字幕结果，返回文本内容\n return NextResponse.json({\n success: true,\n status: 'success',\n data: {\n text: textContents.join('\\n'),\n raw: ocrResult\n }\n })\n\n } catch (e) {\n console.error('解析OCR结果失败:', e)\n console.log('返回原始结果')\n return NextResponse.json({\n success: true,\n status: 'success',\n data: {\n text: result.Data.Result,\n raw: result.Data.Result\n }\n })\n }\n\n case 'PROCESS_PENDING':\n console.log('任务等待处理中...')\n return NextResponse.json({\n success: true,\n status: 'pending',\n message: '任务等待处理中'\n }, { status: 202 })\n\n default:\n console.log('收到未知任务状态:', result.Data.Status, '完整结果:', result.Data)\n return NextResponse.json({\n success: true,\n status: result.Data.Status,\n message: '任务状态未知，请继续轮询',\n data: result.Data\n }, { status: 202 })\n }\n\n } catch (queryError: any) {\n console.error('查询任务错误详情:', {\n name: queryError.name,\n message: queryError.message,\n code: queryError.code,\n requestId: queryError.RequestId,\n stack: queryError.stack\n })\n throw new Error(`查询视频识别任务失败: ${queryError.message}`)\n }\n\n } catch (error: any) {\n console.error('处理请求错误:', error)\n return NextResponse.json(\n { message: error.message || '查询视频识别任务失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/asr/aliyun/recognize/route.ts", "content": "import { NextResponse } from 'next/server';\n\nexport async function POST(request: Request) {\n try {\n const { audioUrl, appKey, token, taskId } = await request.json();\n\n // 调用阿里云语音识别 API\n const response = await fetch('https://nls-gateway.aliyuncs.com/stream/v1/asr', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'X-NLS-Token': token,\n },\n body: JSON.stringify({\n appkey: appKey,\n audio_url: audioUrl,\n format: 'wav',\n sample_rate: 16000,\n enable_intermediate_result: true,\n enable_punctuation_prediction: true,\n enable_inverse_text_normalization: true,\n }),\n });\n\n if (!response.ok) {\n throw new Error('阿里云 API 请求失败');\n }\n\n const data = await response.json();\n return NextResponse.json(data);\n } catch (error: any) {\n return NextResponse.json(\n { error: error.message || '识别失败' },\n { status: 500 }\n );\n }\n} " }, { "path": "app/api/asr/create/route.ts", "content": "import { NextResponse } from 'next/server';\nimport { sign } from '@/lib/server/tencent-sign';\n\nconst endpoint = 'asr.tencentcloudapi.com';\nconst service = 'asr';\nconst version = '2019-06-14';\nconst region = 'ap-guangzhou';\nconst action = 'CreateRecTask';\n\nexport async function POST(request: Request) {\n try {\n const { engineType, channelNum, resTextFormat, sourceType, data } = await request.json();\n\n const timestamp = Math.floor(Date.now() / 1000);\n const params = {\n EngineModelType: engineType,\n ChannelNum: channelNum,\n ResTextFormat: resTextFormat,\n SourceType: sourceType,\n Data: data,\n };\n\n const signature = sign({\n secretId: process.env.TENCENT_SECRET_ID || '',\n secretKey: process.env.TENCENT_SECRET_KEY || '',\n endpoint,\n service,\n version,\n region,\n action,\n timestamp,\n payload: params,\n });\n\n const response = await fetch(`https://${endpoint}`, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': signature,\n 'X-TC-Action': action,\n 'X-TC-Version': version,\n 'X-TC-Region': region,\n 'X-TC-Timestamp': timestamp.toString(),\n },\n body: JSON.stringify(params),\n });\n\n if (!response.ok) {\n const errorData = await response.json();\n throw new Error(errorData.Response?.Error?.Message || 'API request failed');\n }\n\n const result = await response.json();\n return NextResponse.json(result);\n } catch (error: any) {\n console.error('创建识别任务失败:', error);\n return NextResponse.json(\n { error: error.message || '创建识别任务失败' },\n { status: 500 }\n );\n }\n} " }, { "path": "app/api/asr/status/route.ts", "content": "import { NextResponse } from 'next/server';\nimport { sign } from '@/lib/server/tencent-sign';\n\nconst endpoint = 'asr.tencentcloudapi.com';\nconst service = 'asr';\nconst version = '2019-06-14';\nconst region = 'ap-guangzhou';\nconst action = 'DescribeTaskStatus';\n\nexport async function POST(request: Request) {\n try {\n const { taskId } = await request.json();\n\n const timestamp = Math.floor(Date.now() / 1000);\n const params = {\n TaskId: taskId,\n };\n\n const signature = sign({\n secretId: process.env.TENCENT_SECRET_ID || '',\n secretKey: process.env.TENCENT_SECRET_KEY || '',\n endpoint,\n service,\n version,\n region,\n action,\n timestamp,\n payload: params,\n });\n\n const response = await fetch(`https://${endpoint}`, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': signature,\n 'X-TC-Action': action,\n 'X-TC-Version': version,\n 'X-TC-Region': region,\n 'X-TC-Timestamp': timestamp.toString(),\n },\n body: JSON.stringify(params),\n });\n\n if (!response.ok) {\n const errorData = await response.json();\n throw new Error(errorData.Response?.Error?.Message || 'API request failed');\n }\n\n const result = await response.json();\n return NextResponse.json(result);\n } catch (error: any) {\n console.error('查询任务状态失败:', error);\n return NextResponse.json(\n { error: error.message || '查询任务状态失败' },\n { status: 500 }\n );\n }\n} " }, { "path": "app/api/auth/[...nextauth]/auth.ts", "content": "import { AuthOptions } from 'next-auth'\nimport CredentialsProvider from 'next-auth/providers/credentials'\nimport GitHubProvider from 'next-auth/providers/github'\nimport GoogleProvider from 'next-auth/providers/google'\nimport { neon } from '@neondatabase/serverless'\nimport bcrypt from 'bcryptjs'\n\nconst sql = neon(process.env.DATABASE_URL!)\n\nexport const authOptions: AuthOptions = {\n debug: process.env.NODE_ENV === 'development',\n session: {\n strategy: \"jwt\",\n maxAge: 30 * 24 * 60 * 60, // 30 days\n },\n providers: [\n CredentialsProvider({\n name: 'credentials',\n credentials: {\n email: { label: \"邮箱\", type: \"email\" },\n password: { label: \"密码\", type: \"password\" }\n },\n async authorize(credentials) {\n if (!credentials?.email || !credentials?.password) {\n throw new Error('Please enter email and password')\n }\n\n try {\n const result = await sql`\n SELECT * FROM auth_users WHERE email = ${credentials.email}\n `\n const user = result[0]\n console.log('查询到的用户数据:', user)\n\n if (!user || !user.password_hash) {\n throw new Error('Invalid email or password')\n }\n\n const isValid = await bcrypt.compare(credentials.password, user.password_hash)\n console.log('密码比较结果:', isValid)\n \n if (!isValid) {\n throw new Error('Invalid email or password')\n }\n\n return {\n id: user.id,\n email: user.email,\n name: user.name || null\n }\n } catch (error) {\n console.error('登录验证错误:', error)\n throw new Error('Authentication server error, please try again later')\n }\n }\n }),\n GoogleProvider({\n clientId: process.env.GOOGLE_CLIENT_ID!,\n clientSecret: process.env.GOOGLE_CLIENT_SECRET!,\n profile(profile) {\n return {\n id: profile.sub,\n name: profile.name,\n email: profile.email!,\n image: profile.picture,\n }\n },\n }),\n GitHubProvider({\n clientId: process.env.GITHUB_ID!,\n clientSecret: process.env.GITHUB_SECRET!,\n httpOptions: {\n timeout: 10000\n },\n profile(profile) {\n return {\n id: String(profile.id),\n name: profile.name || profile.login,\n email: profile.email!,\n image: profile.avatar_url,\n }\n },\n })\n ],\n pages: {\n signIn: '/login',\n error: '/login',\n },\n callbacks: {\n async signIn({ user, account }) {\n if (!user.email) return false\n\n try {\n // 检查用户是否存在\n const users = await sql`\n SELECT id, email FROM auth_users\n WHERE email = ${user.email}\n `\n\n // 如果是首次登录，创建新用户\n if (users.length === 0 && account?.providerAccountId) {\n if (account.provider === 'github') {\n await sql`\n INSERT INTO auth_users (\n email,\n name,\n github_id,\n text_quota,\n image_quota,\n pdf_quota,\n speech_quota,\n video_quota,\n created_at,\n updated_at\n ) VALUES (\n ${user.email},\n ${user.name},\n ${account.providerAccountId},\n -1,\n 10,\n 8,\n 5,\n 2,\n CURRENT_TIMESTAMP,\n CURRENT_TIMESTAMP\n )\n `\n } else {\n await sql`\n INSERT INTO auth_users (\n email,\n name,\n google_id,\n text_quota,\n image_quota,\n pdf_quota,\n speech_quota,\n video_quota,\n created_at,\n updated_at\n ) VALUES (\n ${user.email},\n ${user.name},\n ${account.providerAccountId},\n -1,\n 10,\n 8,\n 5,\n 2,\n CURRENT_TIMESTAMP,\n CURRENT_TIMESTAMP\n )\n `\n }\n }\n\n return true\n } catch (error) {\n console.error('Error in signIn callback:', error)\n return false\n }\n },\n async jwt({ token, user }) {\n if (user) {\n token.id = user.id\n }\n return token\n },\n async session({ session }) {\n if (session.user?.email) {\n const users = await sql`\n SELECT id\n FROM auth_users\n WHERE email = ${session.user.email}\n `\n if (users.length > 0) {\n session.user.id = users[0].id\n }\n }\n return session\n }\n }\n} " }, { "path": "app/api/auth/[...nextauth]/route.ts", "content": "import NextAuth from 'next-auth'\nimport { authOptions } from '@/app/api/auth/[...nextauth]/auth'\n\nconst handler = NextAuth(authOptions)\nexport { handler as GET, handler as POST } " }, { "path": "app/api/auth/register/route.ts", "content": "import { NextResponse } from 'next/server'\nimport { neon } from '@neondatabase/serverless'\nimport bcrypt from 'bcryptjs'\n\nexport async function POST(req: Request) {\n const sql = neon(process.env.DATABASE_URL!)\n \n try {\n const { email, password, name } = await req.json()\n\n if (!email || !password) {\n return new NextResponse('Missing email or password', { status: 400 })\n }\n\n // 检查邮箱是否已被注册\n const existingUser = await sql`\n SELECT * FROM users WHERE email = ${email}\n `\n\n if (existingUser.length > 0) {\n return new NextResponse('Email already exists', { status: 400 })\n }\n\n // 密码加密\n const hashedPassword = await bcrypt.hash(password, 10)\n\n // 创建用户\n await sql`\n INSERT INTO users (email, password)\n VALUES (${email}, ${hashedPassword})\n `\n\n return new NextResponse('User created successfully', { status: 201 })\n } catch (error: any) {\n console.error('注册失败:', error)\n return new NextResponse('Internal Server Error', { status: 500 })\n }\n} " }, { "path": "app/api/file/extract/route.ts", "content": "import { NextResponse } from 'next/server'\nimport { Mistral } from '@mistralai/mistralai';\n\nconst KIMI_API_KEY = process.env.NEXT_PUBLIC_KIMI_API_KEY\nconst KIMI_API_URL = 'https://api.moonshot.cn/v1'\nconst MISTRAL_API_KEY = process.env.MISTRAL_API_KEY\n\n// 增加超时时间\nconst TIMEOUT = {\n UPLOAD: 20000, // 20秒\n CONTENT: 30000, // 30秒\n PROCESS: 45000 // 45秒\n}\n\n// 带超时的 fetch\nasync function fetchWithTimeout(url: string, options: RequestInit, timeout: number) {\n const controller = new AbortController()\n const id = setTimeout(() => controller.abort(), timeout)\n\n try {\n const response = await fetch(url, {\n ...options,\n signal: controller.signal\n })\n clearTimeout(id)\n \n // 检查响应状态\n if (!response.ok) {\n const error = await response.json().catch(() => ({ error: { message: '请求失败' } }))\n throw new Error(error.error?.message || `请求失败: ${response.status}`)\n }\n \n return response\n } catch (error: any) {\n clearTimeout(id)\n if (error.name === 'AbortError') {\n throw new Error('请求超时，请重试')\n }\n throw error\n }\n}\n\n// 分步上传文件\nasync function uploadFile(file: string, filename: string) {\n try {\n const formData = new FormData()\n const fileBlob = new Blob([Buffer.from(file, 'base64')], { type: 'application/pdf' })\n const pdfFile = new File([fileBlob], filename, { type: 'application/pdf' })\n formData.append('file', pdfFile)\n formData.append('purpose', 'file-extract')\n\n const uploadResponse = await fetchWithTimeout(`${KIMI_API_URL}/files`, {\n method: 'POST',\n headers: {\n 'Authorization': `Bearer ${KIMI_API_KEY}`\n },\n body: formData\n }, TIMEOUT.UPLOAD)\n\n if (!uploadResponse.ok) {\n const error = await uploadResponse.json().catch(() => ({ error: { message: '文件上传失败' } }))\n console.error('KIMI文件上传错误:', error)\n throw new Error(error.error?.message || '文件上传失败')\n }\n\n return await uploadResponse.json()\n } catch (error: any) {\n if (error.name === 'AbortError') {\n throw new Error('文件上传超时')\n }\n throw error\n }\n}\n\n// 获取文件内容\nasync function getFileContent(fileId: string) {\n try {\n const contentResponse = await fetchWithTimeout(`${KIMI_API_URL}/files/${fileId}/content`, {\n headers: {\n 'Authorization': `Bearer ${KIMI_API_KEY}`\n }\n }, TIMEOUT.CONTENT)\n\n if (!contentResponse.ok) {\n const error = await contentResponse.json().catch(() => ({ error: { message: '文件内容获取失败' } }))\n console.error('KIMI文件内容获取错误:', error)\n throw new Error(error.error?.message || '文件内容获取失败')\n }\n\n return await contentResponse.text()\n } catch (error: any) {\n if (error.name === 'AbortError') {\n throw new Error('文件内容获取超时')\n }\n throw error\n }\n}\n\n// 处理文件内容\nasync function processContent(content: string) {\n try {\n const messages = [\n {\n role: 'system',\n content: '你是 Kimi，由 Moonshot AI 提供的人工智能助手。请提取文件中的所有文字内容，保持原文的格式和换行，不需要总结或解释。'\n },\n {\n role: 'system',\n content\n },\n {\n role: 'user',\n content: '请直接返回文件的原始内容，保持格式，不要添加任何解释或总结。'\n }\n ]\n\n const chatResponse = await fetchWithTimeout(`${KIMI_API_URL}/chat/completions`, {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': `Bearer ${KIMI_API_KEY}`\n },\n body: JSON.stringify({\n model: 'moonshot-v1-32k',\n messages,\n temperature: 0.3\n })\n }, TIMEOUT.PROCESS)\n\n if (!chatResponse.ok) {\n const error = await chatResponse.json().catch(() => ({ error: { message: 'API请求失败' } }))\n console.error('KIMI API错误:', error)\n throw new Error(error.error?.message || 'API请求失败')\n }\n\n const data = await chatResponse.json()\n if (!data.choices?.[0]?.message?.content) {\n console.error('KIMI API响应格式错误:', data)\n throw new Error('API返回格式错误')\n }\n\n return data.choices[0].message.content.trim()\n } catch (error: any) {\n if (error.name === 'AbortError') {\n throw new Error('内容处理超时')\n }\n throw error\n }\n}\n\n// 使用 Mistral OCR API 处理 PDF\nasync function processPdfWithMistral(file: string, filename: string) {\n try {\n console.log('开始使用 Mistral OCR 处理 PDF...')\n \n // 创建 Mistral 客户端\n const client = new Mistral({ apiKey: MISTRAL_API_KEY || '' });\n \n // 将 base64 转换为 Buffer\n const fileBuffer = Buffer.from(file, 'base64');\n \n // 上传文件到 Mistral\n console.log('上传文件到 Mistral...')\n let uploadData;\n try {\n uploadData = await client.files.upload({\n file: {\n fileName: filename,\n content: fileBuffer,\n },\n purpose: \"ocr\"\n });\n console.log('文件上传成功，ID:', uploadData.id);\n } catch (uploadError: any) {\n console.error('Mistral 文件上传错误:', uploadError);\n throw new Error(uploadError.message || 'Mistral 文件上传失败');\n }\n \n // 获取签名 URL\n console.log('获取签名 URL...');\n let signedUrlData;\n try {\n signedUrlData = await client.files.getSignedUrl({\n fileId: uploadData.id,\n });\n console.log('获取签名 URL 成功');\n } catch (signedUrlError: any) {\n console.error('获取签名 URL 错误:', signedUrlError);\n throw new Error(signedUrlError.message || '获取签名 URL 失败');\n }\n \n // 使用 OCR 处理文件\n console.log('开始 OCR 处理...');\n let ocrData: any;\n try {\n ocrData = await client.ocr.process({\n model: \"mistral-ocr-latest\",\n document: {\n type: \"document_url\",\n documentUrl: signedUrlData.url,\n }\n });\n console.log('OCR 处理完成，响应数据类型:', typeof ocrData);\n if (typeof ocrData === 'object' && ocrData !== null) {\n console.log('OCR 响应数据结构:', Object.keys(ocrData).join(', '));\n // 输出更详细的响应结构\n for (const key of Object.keys(ocrData)) {\n console.log(`OCR 响应字段 ${key} 类型:`, typeof ocrData[key]);\n if (key === 'pages' && Array.isArray(ocrData.pages)) {\n console.log('pages 数组长度:', ocrData.pages.length);\n if (ocrData.pages.length > 0) {\n console.log('第一页结构:', Object.keys(ocrData.pages[0]).join(', '));\n }\n }\n }\n }\n console.log('OCR 响应数据片段:', typeof ocrData === 'string' ? ocrData.substring(0, 500) : JSON.stringify(ocrData).substring(0, 500) + '...');\n } catch (ocrError: any) {\n console.error('Mistral OCR 错误:', ocrError);\n throw new Error(ocrError.message || 'OCR 处理失败');\n }\n \n // 提取文本内容\n let extractedText = '';\n \n // 检查响应格式并记录详细信息\n if (!ocrData) {\n console.error('Mistral OCR 返回空响应');\n throw new Error('OCR 返回空响应');\n }\n \n // 处理 Markdown 格式的响应\n if (typeof ocrData === 'string') {\n console.log('OCR 返回 Markdown 格式的文本');\n // 直接返回 Markdown 文本，不需要额外处理\n return ocrData.trim();\n }\n \n // 检查响应对象中的各种可能字段\n if (ocrData.markdown) {\n console.log('从 markdown 字段提取文本');\n return String(ocrData.markdown).trim();\n }\n \n // 检查各种可能的文本字段\n if (ocrData.text) {\n console.log('从 text 字段提取文本');\n return String(ocrData.text).trim();\n }\n \n if (ocrData.content) {\n console.log('从 content 字段提取文本');\n return typeof ocrData.content === 'string' ? ocrData.content.trim() : JSON.stringify(ocrData.content);\n }\n \n // 检查是否有结果字段\n if (ocrData.result) {\n console.log('从 result 字段提取文本');\n if (typeof ocrData.result === 'string') {\n return ocrData.result.trim();\n } else if (typeof ocrData.result === 'object' && ocrData.result !== null) {\n // 检查result对象中的可能字段\n if (ocrData.result.text) {\n return String(ocrData.result.text).trim();\n } else if (ocrData.result.content) {\n return typeof ocrData.result.content === 'string' ? ocrData.result.content.trim() : JSON.stringify(ocrData.result.content);\n } else {\n return JSON.stringify(ocrData.result);\n }\n }\n }\n \n // 检查 ocrData 是否有 pages 属性\n if (ocrData.pages) {\n console.log(`发现 pages 字段，包含 ${Array.isArray(ocrData.pages) ? ocrData.pages.length : '未知数量'} 页`);\n \n // 正常处理 pages 数组\n if (Array.isArray(ocrData.pages)) {\n console.log(`提取 ${ocrData.pages.length} 页的文本`);\n \n extractedText = ocrData.pages.map((page: any, index: number) => {\n if (!page) {\n console.log(`第 ${index + 1} 页为空`);\n return '';\n }\n \n // 首先检查markdown字段，这是Mistral OCR的主要输出格式\n if (page.markdown) {\n console.log(`从第 ${index + 1} 页的markdown字段提取文本`);\n return page.markdown;\n } else if (page.text) {\n return page.text;\n } else if (page.content) {\n return typeof page.content === 'string' ? page.content : JSON.stringify(page.content);\n } else {\n console.log(`第 ${index + 1} 页没有文本内容:`, page);\n return '';\n }\n }).join('\\n\\n');\n } else {\n console.error('Mistral OCR 响应中 pages 不是数组:', ocrData.pages);\n // 尝试将 pages 作为文本返回\n if (typeof ocrData.pages === 'string') {\n return ocrData.pages.trim();\n } else {\n return JSON.stringify(ocrData.pages);\n }\n }\n } else {\n console.log('OCR 响应中没有找到 pages 字段，尝试从整个响应中提取文本');\n // 如果找不到任何已知字段，尝试将整个响应作为文本返回\n return JSON.stringify(ocrData);\n }\n \n console.log(`提取的文本长度: ${extractedText.length} 字符`);\n \n // 确保返回非空文本\n if (!extractedText || extractedText.trim() === '') {\n console.log('提取的文本为空，返回默认消息');\n return '无法从PDF中提取文本。这可能是因为PDF包含扫描图像或其他不可提取的内容。请尝试使用其他服务或上传不同的文件。';\n }\n \n return extractedText.trim();\n } catch (error: any) {\n console.error('Mistral OCR 处理错误:', error);\n if (error.name === 'AbortError') {\n throw new Error('Mistral OCR 处理超时');\n }\n throw error;\n }\n}\n\nexport async function POST(request: Request) {\n try {\n const { file, filename, service } = await request.json()\n\n if (!file) {\n return NextResponse.json(\n { error: '未提供文件' },\n { status: 400 }\n )\n }\n\n // 检查文件大小\n const base64Size = file.length * 0.75 // base64到字节的近似转换\n if (base64Size > 5 * 1024 * 1024) { // 5MB\n return NextResponse.json(\n { error: '文件大小超过限制' },\n { status: 400 }\n )\n }\n\n if (service !== 'kimi' && service !== 'mistral') {\n return NextResponse.json(\n { error: '不支持的服务' },\n { status: 400 }\n )\n }\n\n if (service === 'kimi' && !KIMI_API_KEY) {\n return NextResponse.json(\n { error: '未配置Kimi API密钥' },\n { status: 500 }\n )\n }\n\n if (service === 'mistral' && !MISTRAL_API_KEY) {\n return NextResponse.json(\n { error: '未配置Mistral API密钥' },\n { status: 500 }\n )\n }\n\n // 分步处理\n try {\n let result = ''\n \n if (service === 'kimi') {\n // 使用 Kimi API 处理\n console.log('开始使用 Kimi API 处理...')\n // 步骤1：上传文件\n console.log('开始上传文件...')\n const fileObject = await uploadFile(file, filename)\n \n // 步骤2：获取文件内容\n console.log('开始获取文件内容...')\n const fileContent = await getFileContent(fileObject.id)\n \n // 步骤3：处理内容\n console.log('开始处理文件内容...')\n result = await processContent(fileContent)\n } else if (service === 'mistral') {\n // 使用 Mistral OCR API 处理\n console.log('开始使用 Mistral OCR API 处理...')\n result = await processPdfWithMistral(file, filename)\n }\n\n // 检查响应大小\n if (result.length > 5 * 1024 * 1024) { // 5MB\n throw new Error('响应内容过大')\n }\n\n return NextResponse.json({ text: result })\n } catch (error: any) {\n console.error('处理步骤错误:', error)\n if (error.name === 'AbortError' || error.message.includes('超时')) {\n return NextResponse.json(\n { error: '处理超时，请稍后重试' },\n { status: 503 }\n )\n }\n \n // 根据错误类型返回不同的状态码\n if (error.message.includes('文件大小超过限制') || error.message.includes('响应内容过大')) {\n return NextResponse.json(\n { error: error.message },\n { status: 413 }\n )\n }\n \n return NextResponse.json(\n { error: error.message || 'PDF处理失败' },\n { status: 500 }\n )\n }\n } catch (error: any) {\n console.error('PDF处理错误:', error)\n return NextResponse.json(\n { error: error.message || 'PDF处理失败' },\n { status: error.status || 500 }\n )\n }\n}" }, { "path": "app/api/ocr/kimi/route.ts", "content": "import { NextResponse } from 'next/server'\nimport OpenAI from 'openai'\n\nconst KIMI_API_KEY = process.env.NEXT_PUBLIC_KIMI_API_KEY\nconst KIMI_API_URL = 'https://api.moonshot.cn/v1'\n\nexport async function POST(request: Request) {\n try {\n const { image } = await request.json()\n \n if (!image) {\n return NextResponse.json(\n { error: 'No image data provided' },\n { status: 400 }\n )\n }\n\n if (!KIMI_API_KEY) {\n return NextResponse.json(\n { error: 'Kimi API key not found' },\n { status: 500 }\n )\n }\n\n // 从完整的 data URL 中提取 base64 数据\n const base64Data = image.split(';base64,').pop() || image;\n\n const openai = new OpenAI({\n apiKey: KIMI_API_KEY,\n baseURL: KIMI_API_URL\n })\n\n const response = await openai.chat.completions.create({\n model: 'moonshot-v1-32k-vision-preview',\n messages: [\n {\n role: 'system',\n content: '你是一个专业的图片文字识别助手。请提取图片中的所有文字，保持原有格式，不要添加任何解释。'\n },\n {\n role: 'user',\n content: [\n { type: 'text', text: '请提取这张图片中的所有文字：' },\n { type: 'image_url', image_url: { url: image } }\n ]\n }\n ],\n temperature: 0.1\n })\n\n const extractedText = response.choices[0]?.message?.content\n if (!extractedText) {\n return NextResponse.json(\n { error: 'No text extracted' },\n { status: 400 }\n )\n }\n\n return NextResponse.json({ text: extractedText.trim() })\n } catch (error: any) {\n console.error('Error extracting text with Kimi:', error)\n return NextResponse.json(\n { error: error.message || '文字识别失败，请稍后重试' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/ocr/route.ts", "content": "import { NextResponse } from 'next/server'\nimport * as tencentcloud from 'tencentcloud-sdk-nodejs-ocr'\n\nconst OcrClient = tencentcloud.ocr.v20181119.Client\n\ninterface TextDetection {\n DetectedText: string;\n Confidence: number;\n Polygon: Array<{\n X: number;\n Y: number;\n }>;\n AdvancedInfo: string;\n}\n\ninterface OCRResponse {\n TextDetections: TextDetection[];\n Language: string;\n RequestId: string;\n}\n\nconst client = new OcrClient({\n credential: {\n secretId: process.env.TENCENT_SECRET_ID || '',\n secretKey: process.env.TENCENT_SECRET_KEY || '',\n },\n region: 'ap-guangzhou',\n profile: {\n signMethod: 'TC3-HMAC-SHA256',\n httpProfile: {\n reqMethod: 'POST',\n reqTimeout: 30,\n endpoint: 'ocr.tencentcloudapi.com',\n },\n },\n})\n\nexport async function POST(request: Request) {\n try {\n const { image } = await request.json()\n\n if (!image) {\n return NextResponse.json(\n { success: false, message: '未找到图片数据' },\n { status: 400 }\n )\n }\n\n const result = await client.GeneralBasicOCR({\n ImageBase64: image,\n }) as OCRResponse\n\n if (!result || !result.TextDetections || result.TextDetections.length === 0) {\n return NextResponse.json(\n { success: false, message: '未识别到文字' },\n { status: 400 }\n )\n }\n\n const text = result.TextDetections.map((item: TextDetection) => item.DetectedText).join('\\n')\n\n return NextResponse.json({\n success: true,\n text\n })\n } catch (error: any) {\n console.error('腾讯云OCR错误:', error)\n return NextResponse.json(\n { success: false, message: error.message || 'OCR识别失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/ocr/step/route.ts", "content": "import { NextResponse } from 'next/server'\nimport OpenAI from 'openai'\n\n// 设置较长的超时时间\nexport const maxDuration = 60; // 设置为60秒\n\nexport async function POST(request: Request) {\n const apiKey = process.env.NEXT_PUBLIC_STEP_API_KEY;\n if (!apiKey) {\n return NextResponse.json(\n { error: 'API key not configured' },\n { status: 500 }\n );\n }\n\n try {\n const formData = await request.formData();\n const image = formData.get('image');\n \n if (!image) {\n return NextResponse.json(\n { error: 'No image provided' },\n { status: 400 }\n );\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.stepfun.com/v1',\n dangerouslyAllowBrowser: true,\n timeout: 30000 // 30秒超时\n });\n\n // 最多重试3次\n let retries = 3;\n let lastError;\n\n while (retries > 0) {\n try {\n const response = await openai.chat.completions.create({\n model: 'step-1v-32k',\n messages: [\n {\n role: 'system',\n content: 'You are an OCR assistant. Extract text from the provided image accurately.'\n },\n {\n role: 'user',\n content: [\n { type: 'text', text: 'Please extract text from this image:' },\n { type: 'image_url', image_url: { url: image instanceof File ? URL.createObjectURL(image) : image.toString() } }\n ]\n }\n ]\n });\n\n const extractedText = response.choices[0]?.message?.content;\n if (!extractedText) {\n throw new Error('No text extracted');\n }\n\n return NextResponse.json({ text: extractedText });\n } catch (error: any) {\n lastError = error;\n if (error.status === 504) {\n retries--;\n if (retries > 0) {\n // 等待1秒后重试\n await new Promise(resolve => setTimeout(resolve, 1000));\n continue;\n }\n }\n break;\n }\n }\n\n console.error('Step OCR error after retries:', lastError);\n return NextResponse.json(\n { error: lastError?.message || 'OCR failed after retries' },\n { status: lastError?.status || 500 }\n );\n } catch (error: any) {\n console.error('Step OCR error:', error);\n return NextResponse.json(\n { error: error.message || 'OCR failed' },\n { status: error.status || 500 }\n );\n }\n} " }, { "path": "app/api/qwen/ocr/route.ts", "content": "import { NextResponse } from 'next/server'\n\nif (!process.env.NEXT_PUBLIC_QWEN_API_KEY) {\n throw new Error('Missing NEXT_PUBLIC_QWEN_API_KEY environment variable')\n}\n\nexport async function POST(request: Request) {\n try {\n const { image } = await request.json()\n\n if (!image) {\n return NextResponse.json(\n { message: '缺少图片数据' },\n { status: 400 }\n )\n }\n\n const response = await fetch('https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions', {\n method: 'POST',\n headers: {\n 'Authorization': `Bearer ${process.env.NEXT_PUBLIC_QWEN_API_KEY}`,\n 'Content-Type': 'application/json'\n },\n body: JSON.stringify({\n model: 'qwen-vl-ocr',\n messages: [\n {\n role: 'user',\n content: [\n {\n type: 'image_url',\n image_url: {\n url: `data:image/jpeg;base64,${image}`\n },\n min_pixels: 28 * 28 * 4,\n max_pixels: 28 * 28 * 1280\n },\n {\n type: 'text',\n text: 'Read all the text in the image.'\n }\n ]\n }\n ]\n })\n })\n\n if (!response.ok) {\n const error = await response.json()\n throw new Error(error.message || '文字识别失败')\n }\n\n const result = await response.json()\n const text = result.choices[0].message.content\n return NextResponse.json({ text })\n } catch (error: any) {\n console.error('通义千问OCR错误:', error)\n return NextResponse.json(\n { message: error.message || '文字识别失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/qwen/translate/route.ts", "content": "import { NextResponse } from 'next/server';\n\nexport const runtime = 'edge';\n\nexport async function POST(request: Request) {\n try {\n const { text, targetLang } = await request.json();\n\n if (!text || !targetLang) {\n return NextResponse.json(\n { error: '缺少必要参数' },\n { status: 400 }\n );\n }\n\n const response = await fetch('https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation', {\n method: 'POST',\n headers: {\n 'Content-Type': 'application/json',\n 'Authorization': `Bearer ${process.env.NEXT_PUBLIC_QWEN_API_KEY}`,\n },\n body: JSON.stringify({\n model: 'qwen-max',\n input: {\n messages: [\n {\n role: 'system',\n content: 'You are a professional translator. Translate the text directly without any explanations.'\n },\n {\n role: 'user',\n content: `Translate to ${targetLang}:\\n${text}`\n }\n ]\n },\n parameters: {\n temperature: 0.1,\n max_tokens: 2048,\n }\n }),\n });\n\n if (!response.ok) {\n const error = await response.json();\n return NextResponse.json(\n { error: error.message || '翻译请求失败' },\n { status: response.status }\n );\n }\n\n const result = await response.json();\n return NextResponse.json({ text: result.output.text });\n } catch (error: any) {\n console.error('Error in Qwen translation:', error);\n return NextResponse.json(\n { error: error.message || '翻译服务出错' },\n { status: 500 }\n );\n }\n} " }, { "path": "app/api/register/route.ts", "content": "import { NextResponse } from 'next/server'\nimport { neon } from '@neondatabase/serverless'\nimport bcrypt from 'bcryptjs'\n\nconst sql = neon(process.env.DATABASE_URL!)\n\nexport async function POST(req: Request) {\n try {\n console.log('开始处理注册请求')\n const { email, password } = await req.json()\n console.log('收到注册数据:', { email, hasPassword: !!password })\n\n // 验证输入\n if (!email || !password) {\n console.log('输入验证失败')\n return NextResponse.json(\n { error: '请输入邮箱和密码' },\n { status: 400 }\n )\n }\n\n // 检查邮箱是否已存在\n console.log('检查邮箱是否存在:', email)\n const existingUser = await sql`\n SELECT id FROM auth_users WHERE email = ${email}\n `\n console.log('查询结果:', existingUser)\n \n if (existingUser.length > 0) {\n console.log('邮箱已存在')\n return NextResponse.json(\n { error: '该邮箱已被注册' },\n { status: 400 }\n )\n }\n\n // 加密密码\n console.log('开始加密密码')\n const hashedPassword = await bcrypt.hash(password, 10)\n\n // 创建用户\n console.log('开始创建用户')\n const result = await sql`\n INSERT INTO auth_users (\n email, \n password_hash,\n text_quota,\n image_quota,\n pdf_quota,\n speech_quota,\n video_quota\n )\n VALUES (\n ${email}, \n ${hashedPassword},\n -1,\n 10,\n 8,\n 5,\n 2\n )\n RETURNING *\n `\n console.log('创建的用户数据:', result[0])\n\n return NextResponse.json(\n { \n message: '注册成功',\n user: {\n id: result[0].id,\n email: result[0].email\n }\n },\n { status: 201 }\n )\n } catch (error: any) {\n console.error('注册错误:', error)\n console.error('错误堆栈:', error.stack)\n return NextResponse.json(\n { error: error.message || '注册失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/subscription/route.ts", "content": "import { getServerSession } from 'next-auth'\nimport { NextResponse } from 'next/server'\nimport { stripe, PLANS } from '@/lib/stripe'\nimport { authOptions } from '../auth/[...nextauth]/auth'\n\nexport async function POST(req: Request) {\n try {\n const session = await getServerSession(authOptions)\n if (!session?.user?.email) {\n return new NextResponse('Unauthorized', { status: 401 })\n }\n\n const { priceId } = await req.json()\n if (!priceId) {\n return new NextResponse('Price ID is required', { status: 400 })\n }\n\n if (!stripe) {\n return new NextResponse('Stripe is not configured', { status: 500 })\n }\n\n // 检查价格 ID 是否有效\n const paidPlans = [PLANS.monthly, PLANS.yearly]\n const plan = paidPlans.find(p => p.priceId === priceId)\n if (!plan) {\n return new NextResponse('Invalid price ID', { status: 400 })\n }\n\n // 创建或获取 Stripe 客户\n const customer = await stripe.customers.create({\n email: session.user.email,\n metadata: {\n userId: session.user.id\n }\n })\n\n // 创建结账会话\n const checkoutSession = await stripe.checkout.sessions.create({\n customer: customer.id,\n line_items: [\n {\n price: priceId,\n quantity: 1,\n },\n ],\n mode: 'subscription',\n success_url: `${process.env.NEXT_PUBLIC_APP_URL}/profile?subscription=success`,\n cancel_url: `${process.env.NEXT_PUBLIC_APP_URL}/pricing?canceled=true`,\n subscription_data: {\n metadata: {\n userId: session.user.id,\n },\n },\n })\n\n return NextResponse.json({ url: checkoutSession.url })\n } catch (error) {\n console.error('Subscription error:', error)\n return new NextResponse('Internal error', { status: 500 })\n }\n} " }, { "path": "app/api/tencent/ocr/route.ts", "content": "import { NextResponse } from 'next/server';\n\n// 使用 require 导入腾讯云 SDK\nconst tencentcloud = require(\"tencentcloud-sdk-nodejs\");\nconst OcrClient = tencentcloud.ocr.v20181119.Client;\n\nexport async function POST(request: Request) {\n try {\n const { image } = await request.json();\n\n if (!image) {\n return NextResponse.json(\n { success: false, message: '缺少图片数据' },\n { status: 400 }\n );\n }\n\n const client = new OcrClient({\n credential: {\n secretId: process.env.TENCENT_SECRET_ID || '',\n secretKey: process.env.TENCENT_SECRET_KEY || '',\n },\n region: 'ap-guangzhou',\n profile: {\n signMethod: 'TC3-HMAC-SHA256',\n httpProfile: {\n reqMethod: 'POST',\n reqTimeout: 30,\n endpoint: 'ocr.tencentcloudapi.com',\n },\n },\n });\n\n const base64Data = image.split(',')[1];\n const result = await client.GeneralBasicOCR({\n ImageBase64: base64Data,\n LanguageType: 'auto',\n });\n\n if (!result || !result.TextDetections) {\n throw new Error('文字识别失败');\n }\n\n const textLines = result.TextDetections.map((item: any) => item.DetectedText).filter(Boolean);\n const text = textLines.join('\\n');\n\n return NextResponse.json({\n success: true,\n result: text\n });\n } catch (error: any) {\n console.error('腾讯云 OCR 错误:', error);\n return NextResponse.json(\n { \n success: false, \n message: error.code === 'AuthFailure' \n ? '腾讯云认证失败，请检查密钥配置' \n : '文字识别失败'\n },\n { status: 500 }\n );\n }\n} " }, { "path": "app/api/translate/claude/route.ts", "content": "import { NextResponse } from 'next/server';\nimport OpenAI from 'openai';\n\nexport async function POST(request: Request) {\n try {\n const { text, targetLanguage } = await request.json();\n\n if (!text || !targetLanguage) {\n return NextResponse.json(\n { error: '缺少必要参数' },\n { status: 400 }\n );\n }\n\n const apiKey = process.env.NEXT_PUBLIC_OPENROUTER_API_KEY;\n if (!apiKey) {\n return NextResponse.json(\n { error: 'OpenRouter API key not found' },\n { status: 500 }\n );\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://openrouter.ai/api/v1'\n });\n\n const completion = await openai.chat.completions.create({\n model: 'anthropic/claude-3-haiku',\n messages: [\n {\n role: 'system',\n content: 'You are a professional translator. Translate the text directly without any explanations.'\n },\n {\n role: 'user',\n content: `Translate to ${targetLanguage}:\\n${text}`\n }\n ],\n temperature: 0.3,\n max_tokens: 2000,\n });\n\n const translatedText = completion.choices[0].message.content;\n return NextResponse.json({ text: translatedText });\n\n } catch (error: any) {\n console.error('Claude translation error:', error);\n return NextResponse.json(\n { error: error.message || '翻译失败' },\n { status: 500 }\n );\n }\n} " }, { "path": "app/api/translate/kimi/route.ts", "content": "import { NextResponse } from 'next/server';\nimport OpenAI from 'openai';\n\nexport async function POST(request: Request) {\n try {\n const { text, targetLanguage } = await request.json();\n\n if (!text || !targetLanguage) {\n return NextResponse.json(\n { error: 'Missing required parameters' },\n { status: 400 }\n );\n }\n\n const apiKey = process.env.NEXT_PUBLIC_KIMI_API_KEY;\n if (!apiKey) {\n return NextResponse.json(\n { error: 'API key not found' },\n { status: 500 }\n );\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.moonshot.cn/v1',\n });\n\n const completion = await openai.chat.completions.create({\n model: 'moonshot-v1-128k',\n messages: [\n {\n role: 'system',\n content: `You are a professional translator. Translate the following text to ${targetLanguage}. Keep the original format and style.`\n },\n {\n role: 'user',\n content: text\n }\n ],\n temperature: 0.3,\n max_tokens: 2000\n });\n\n const translatedText = completion.choices[0]?.message?.content;\n if (!translatedText) {\n return NextResponse.json(\n { error: 'No translation result' },\n { status: 500 }\n );\n }\n\n return NextResponse.json({ translatedText });\n } catch (error: any) {\n console.error('Kimi translation error:', error);\n return NextResponse.json(\n { error: error.message || 'Translation failed' },\n { status: 500 }\n );\n }\n} " }, { "path": "app/api/translate/route.ts", "content": "import OpenAI from 'openai';\nimport { sign } from '@/lib/server/tencent-sign';\nimport { translateWithKimiAPI } from '@/lib/server/translate';\n\nexport async function POST(request: Request) {\n try {\n const { text, targetLanguage, service } = await request.json();\n\n if (!text || !targetLanguage) {\n return new Response(JSON.stringify({ error: '缺少必要参数' }), {\n status: 400,\n headers: { 'Content-Type': 'application/json' },\n });\n }\n\n let translatedText;\n\n try {\n switch (service) {\n case 'deepseek':\n translatedText = await translateWithDeepSeekAPI(text, targetLanguage);\n break;\n case 'qwen':\n translatedText = await translateWithQwenAPI(text, targetLanguage);\n break;\n case 'zhipu':\n translatedText = await translateWithZhipuAPI(text, targetLanguage);\n break;\n case '4o-mini':\n translatedText = await translateWith4oMiniAPI(text, targetLanguage);\n break;\n case 'hunyuan':\n translatedText = await translateWithHunyuanAPI(text, targetLanguage);\n break;\n case 'minnimax':\n translatedText = await translateWithMinniMaxAPI(text, targetLanguage);\n break;\n case 'siliconflow':\n translatedText = await translateWithSiliconFlowAPI(text, targetLanguage);\n break;\n case 'claude_3_5':\n translatedText = await translateWithClaudeAPI(text, targetLanguage);\n break;\n case 'kimi':\n translatedText = await translateWithKimiAPI(text, targetLanguage);\n break;\n case 'step':\n translatedText = await translateWithStepAPI(text, targetLanguage);\n break;\n default:\n translatedText = await translateWithDeepSeekAPI(text, targetLanguage);\n }\n } catch (serviceError: any) {\n console.error(`${service} translation service error:`, serviceError);\n // 如果当前服务失败，尝试使用 DeepSeek 作为备选\n if (service !== 'deepseek') {\n console.log('Trying DeepSeek as fallback service...');\n translatedText = await translateWithDeepSeekAPI(text, targetLanguage);\n } else {\n throw serviceError;\n }\n }\n\n return new Response(JSON.stringify({ text: translatedText }), {\n headers: { 'Content-Type': 'application/json' },\n });\n } catch (error: any) {\n console.error('Translation error:', error);\n return new Response(JSON.stringify({ error: error.message || '翻译失败' }), {\n status: 500,\n headers: { 'Content-Type': 'application/json' },\n });\n }\n}\n\nasync function translateWithDeepSeekAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_DEEPSEEK_API_KEY;\n if (!apiKey) {\n throw new Error('DeepSeek API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.deepseek.com/v1'\n });\n\n const response = await openai.chat.completions.create({\n model: 'deepseek-chat',\n messages: [\n {\n role: 'system',\n content: `You are a professional translator. Translate the following text to ${targetLanguage}. Only return the translated text, no explanations.`\n },\n {\n role: 'user',\n content: text\n }\n ],\n temperature: 0.3,\n max_tokens: 2000\n });\n\n return response.choices[0].message.content || '';\n}\n\nasync function translateWithQwenAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_QWEN_API_KEY;\n if (!apiKey) {\n throw new Error('Qwen API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://dashscope.aliyuncs.com/compatible-mode/v1'\n });\n\n const response = await openai.chat.completions.create({\n model: 'qwen-max',\n messages: [\n {\n role: 'system',\n content: `You are a professional translator. Translate the following text to ${targetLanguage}. Only return the translated text, no explanations.`\n },\n {\n role: 'user',\n content: text\n }\n ],\n temperature: 0.3,\n max_tokens: 2000\n });\n\n return response.choices[0].message.content || '';\n}\n\nasync function translateWithZhipuAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_ZHIPU_API_KEY;\n if (!apiKey) {\n throw new Error('Zhipu API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://open.bigmodel.cn/api/paas/v4'\n });\n\n const response = await openai.chat.completions.create({\n model: 'glm-4',\n messages: [\n {\n role: 'system',\n content: `You are a professional translator. Translate the following text to ${targetLanguage}. Only return the translated text, no explanations.`\n },\n {\n role: 'user',\n content: text\n }\n ],\n temperature: 0.3,\n max_tokens: 2000\n });\n\n return response.choices[0].message.content || '';\n}\n\nasync function translateWith4oMiniAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_OPENAI_API_KEY;\n if (!apiKey) {\n throw new Error('OpenAI API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.openai.com/v1'\n });\n\n const response = await openai.chat.completions.create({\n model: 'gpt-4o-mini',\n messages: [\n {\n role: 'system',\n content: `You are a professional translator. Translate the following text to ${targetLanguage}. Only return the translated text, no explanations.`\n },\n {\n role: 'user',\n content: text\n }\n ],\n temperature: 0.3,\n max_tokens: 2000\n });\n\n return response.choices[0].message.content || '';\n}\n\nasync function translateWithHunyuanAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_TENCENT_API_KEY;\n if (!apiKey) {\n throw new Error('Tencent API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.hunyuan.cloud.tencent.com/v1'\n });\n\n const response = await openai.chat.completions.create({\n model: 'hunyuan-turbo',\n messages: [\n {\n role: 'system',\n content: `你是一个专业的翻译助手，请直接翻译文本，不要添加任何解释。`\n },\n {\n role: 'user',\n content: `将以下文本翻译成${targetLanguage}：\\n\\n${text}`\n }\n ],\n temperature: 0.1,\n top_p: 0.7,\n // @ts-expect-error key is not yet public\n enable_enhancement: true\n });\n\n return response.choices[0].message.content || '';\n}\n\nasync function translateWithMinniMaxAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_MINNIMAX_API_KEY;\n if (!apiKey) {\n throw new Error('MinniMax API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.minimax.chat/v1',\n });\n\n try {\n const completion = await openai.chat.completions.create({\n model: 'abab6.5s-chat',\n messages: [\n {\n role: 'system',\n content: 'You are a professional translator. Translate the text directly without any explanations.'\n },\n {\n role: 'user',\n content: `Translate to ${targetLanguage}:\\n${text}`\n }\n ],\n temperature: 0.3,\n max_tokens: 2000,\n });\n\n return completion.choices[0].message.content;\n } catch (error: any) {\n console.error('MinniMax translation error:', error);\n throw new Error(error.message || '翻译失败');\n }\n}\n\nasync function translateWithSiliconFlowAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_SILICONFLOW_API_KEY;\n if (!apiKey) {\n throw new Error('SiliconFlow API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.siliconflow.com/v1'\n });\n\n try {\n const completion = await openai.chat.completions.create({\n model: 'meta-llama/Llama-3.3-70B-Instruct',\n messages: [\n {\n role: 'system',\n content: 'You are a professional translator. Translate the text directly without any explanations.'\n },\n {\n role: 'user',\n content: `Translate to ${targetLanguage}:\\n${text}`\n }\n ],\n temperature: 0.3,\n max_tokens: 2000,\n });\n\n return completion.choices[0].message.content;\n } catch (error: any) {\n console.error('SiliconFlow translation error:', error);\n throw new Error(error.message || '翻译失败');\n }\n}\n\nasync function translateWithClaudeAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_OPENROUTER_API_KEY;\n if (!apiKey) {\n throw new Error('OpenRouter API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://openrouter.ai/api/v1'\n });\n\n const completion = await openai.chat.completions.create({\n model: 'anthropic/claude-3-haiku',\n messages: [\n {\n role: 'system',\n content: 'You are a professional translator. Translate the text directly without any explanations.'\n },\n {\n role: 'user',\n content: `Translate to ${targetLanguage}:\\n${text}`\n }\n ],\n temperature: 0.3,\n max_tokens: 2000,\n });\n\n return completion.choices[0].message.content || '';\n}\n\nasync function translateWithStepAPI(text: string, targetLanguage: string) {\n const apiKey = process.env.NEXT_PUBLIC_STEP_API_KEY;\n if (!apiKey) {\n throw new Error('Step API key not found');\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.stepfun.com/v1'\n });\n\n const response = await openai.chat.completions.create({\n model: 'step-2-16k',\n messages: [\n {\n role: 'system',\n content: `You are a professional translator. Translate the following text to ${targetLanguage}. Only return the translated text, no explanations.`\n },\n {\n role: 'user',\n content: text\n }\n ],\n temperature: 0.3,\n max_tokens: 2000\n });\n\n return response.choices[0].message.content || '';\n} " }, { "path": "app/api/translate/siliconflow/route.ts", "content": "import { NextResponse } from 'next/server';\nimport OpenAI from 'openai';\n\nexport async function POST(request: Request) {\n try {\n const { text, targetLanguage } = await request.json();\n\n if (!text || !targetLanguage) {\n return NextResponse.json(\n { error: '缺少必要参数' },\n { status: 400 }\n );\n }\n\n const apiKey = process.env.NEXT_PUBLIC_SILICONFLOW_API_KEY;\n if (!apiKey) {\n return NextResponse.json(\n { error: 'SiliconFlow API key not found' },\n { status: 500 }\n );\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.siliconflow.com/v1'\n });\n\n const completion = await openai.chat.completions.create({\n model: 'meta-llama/Llama-3.3-70B-Instruct',\n messages: [\n {\n role: 'system',\n content: 'You are a professional translator. Translate the text directly without any explanations.'\n },\n {\n role: 'user',\n content: `Translate to ${targetLanguage}:\\n${text}`\n }\n ],\n temperature: 0.3,\n max_tokens: 2000,\n });\n\n const translatedText = completion.choices[0].message.content;\n return NextResponse.json({ text: translatedText });\n\n } catch (error: any) {\n console.error('SiliconFlow translation error:', error);\n return NextResponse.json(\n { error: error.message || '翻译失败' },\n { status: 500 }\n );\n }\n} " }, { "path": "app/api/translate/step/route.ts", "content": "import { NextResponse } from 'next/server'\nimport OpenAI from 'openai'\n\nexport async function POST(req: Request) {\n try {\n const apiKey = process.env.NEXT_PUBLIC_STEP_API_KEY;\n if (!apiKey) {\n return new NextResponse('API key not configured', { status: 500 })\n }\n\n const openai = new OpenAI({\n apiKey: apiKey,\n baseURL: 'https://api.stepfun.com/v1'\n })\n\n const { text, targetLanguage } = await req.json()\n\n if (!text) {\n return new NextResponse('Text is required', { status: 400 })\n }\n\n if (!targetLanguage) {\n return new NextResponse('Target language is required', { status: 400 })\n }\n\n const completion = await openai.chat.completions.create({\n model: 'step-2-16k',\n messages: [\n {\n role: 'system',\n content: `You are a professional translator. Translate the following text to ${targetLanguage}. Keep the original format and style.`\n },\n {\n role: 'user',\n content: text\n }\n ],\n temperature: 0.3,\n max_tokens: 2000\n })\n\n const translation = completion.choices[0]?.message?.content || ''\n if (!translation) {\n return new NextResponse('No translation result', { status: 500 })\n }\n\n return NextResponse.json({ translation })\n } catch (error: any) {\n console.error('Translation error:', error)\n return new NextResponse(error.message || 'Internal Server Error', {\n status: error.status || 500,\n })\n }\n} " }, { "path": "app/api/upload/route.ts", "content": "import { NextResponse } from 'next/server'\nimport { put } from '@vercel/blob'\n\nexport async function POST(request: Request) {\n try {\n const { file, type } = await request.json()\n\n if (!file) {\n return NextResponse.json(\n { error: '未提供文件' },\n { status: 400 }\n )\n }\n\n // 从 base64 中提取实际的文件数据\n const base64Data = file.replace(/^data:.*?;base64,/, '')\n const buffer = Buffer.from(base64Data, 'base64')\n\n // 生成唯一的文件名\n const filename = `${Date.now()}-${Math.random().toString(36).substring(7)}.${type === 'video' ? 'mp4' : 'jpg'}`\n\n // 上传到 Vercel Blob\n const blob = await put(filename, buffer, {\n access: 'public',\n contentType: type === 'video' ? 'video/mp4' : 'image/jpeg'\n })\n\n return NextResponse.json({ url: blob.url })\n } catch (error: any) {\n console.error('文件上传错误:', error)\n return NextResponse.json(\n { error: error.message || '文件上传失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/user/info/route.ts", "content": "import { getServerSession } from 'next-auth'\nimport { NextResponse } from 'next/server'\nimport { neon } from '@neondatabase/serverless'\nimport { authOptions } from '../../auth/[...nextauth]/auth'\n\ninterface User {\n id: string;\n email: string;\n name: string | null;\n github_id: string | null;\n google_id: string | null;\n stripe_customer_id: string | null;\n stripe_subscription_id: string | null;\n stripe_price_id: string | null;\n stripe_current_period_end: string | null;\n text_quota: number;\n image_quota: number;\n pdf_quota: number;\n speech_quota: number;\n video_quota: number;\n quota_reset_at: string | null;\n created_at: string;\n updated_at: string;\n}\n\ntype UsageType = 'text' | 'image' | 'pdf' | 'speech' | 'video';\n\ninterface UsageRecord {\n type: UsageType;\n count: string;\n}\n\ninterface UsageInfo {\n [key: string]: number;\n text: number;\n image: number;\n pdf: number;\n speech: number;\n video: number;\n}\n\nexport async function GET() {\n try {\n console.log('开始获取用户信息')\n const session = await getServerSession(authOptions)\n if (!session?.user?.email) {\n console.log('未找到用户会话')\n return new NextResponse('Unauthorized', { status: 401 })\n }\n\n console.log('用户邮箱:', session.user.email)\n const sql = neon(process.env.DATABASE_URL!)\n \n // 获取用户基本信息和订阅信息\n const users = await sql`\n SELECT \n id,\n email,\n name,\n github_id,\n google_id,\n stripe_customer_id,\n stripe_subscription_id,\n stripe_price_id,\n stripe_current_period_end,\n text_quota,\n image_quota,\n pdf_quota,\n speech_quota,\n video_quota,\n quota_reset_at,\n created_at,\n updated_at\n FROM auth_users \n WHERE email = ${session.user.email}\n ` as User[]\n\n if (!users.length) {\n console.log('未找到用户记录')\n return new NextResponse('User not found', { status: 404 })\n }\n\n const user = users[0]\n console.log('查询到的用户信息:', {\n id: user.id,\n email: user.email,\n subscription: {\n customerId: user.stripe_customer_id,\n subscriptionId: user.stripe_subscription_id,\n priceId: user.stripe_price_id,\n currentPeriodEnd: user.stripe_current_period_end\n },\n quotas: {\n text: user.text_quota,\n image: user.image_quota,\n pdf: user.pdf_quota,\n speech: user.speech_quota,\n video: user.video_quota\n }\n })\n\n // 检查订阅是否已过期\n if (user.stripe_current_period_end) {\n const currentPeriodEnd = new Date(user.stripe_current_period_end).getTime()\n const now = new Date().getTime()\n \n if (now > currentPeriodEnd) {\n console.log('订阅已过期，重置为试用版')\n await sql`\n UPDATE auth_users \n SET \n stripe_subscription_id = NULL,\n stripe_price_id = NULL,\n stripe_current_period_end = NULL,\n text_quota = -1,\n image_quota = 5,\n pdf_quota = 3,\n speech_quota = 2,\n video_quota = 1\n WHERE id = ${user.id}\n `\n \n user.stripe_subscription_id = null\n user.stripe_price_id = null\n user.stripe_current_period_end = null\n user.text_quota = -1\n user.image_quota = 5\n user.pdf_quota = 3\n user.speech_quota = 2\n user.video_quota = 1\n }\n }\n\n const today = new Date().toISOString().split('T')[0]\n console.log('当前日期:', today, '上次配额重置日期:', user.quota_reset_at)\n\n // 如果配额重置日期不是今天，根据用户的订阅计划重置配额\n if (user.quota_reset_at !== today) {\n console.log('重置用户配额，订阅计划:', user.stripe_price_id)\n \n let quotaUpdate\n if (user.stripe_price_id === process.env.NEXT_PUBLIC_STRIPE_MONTHLY_PRICE_ID) {\n quotaUpdate = {\n text_quota: -1,\n image_quota: 50,\n pdf_quota: 40,\n speech_quota: 30,\n video_quota: 10\n }\n } else if (user.stripe_price_id === process.env.NEXT_PUBLIC_STRIPE_YEARLY_PRICE_ID) {\n quotaUpdate = {\n text_quota: -1,\n image_quota: 100,\n pdf_quota: 80,\n speech_quota: 60,\n video_quota: 20\n }\n } else {\n quotaUpdate = {\n text_quota: -1,\n image_quota: 5,\n pdf_quota: 3,\n speech_quota: 2,\n video_quota: 1\n }\n }\n\n await sql`\n UPDATE auth_users\n SET \n image_quota = ${quotaUpdate.image_quota},\n pdf_quota = ${quotaUpdate.pdf_quota},\n speech_quota = ${quotaUpdate.speech_quota},\n video_quota = ${quotaUpdate.video_quota},\n quota_reset_at = ${today}\n WHERE id = ${user.id}\n `\n \n user.text_quota = quotaUpdate.text_quota\n user.image_quota = quotaUpdate.image_quota\n user.pdf_quota = quotaUpdate.pdf_quota\n user.speech_quota = quotaUpdate.speech_quota\n user.video_quota = quotaUpdate.video_quota\n console.log('配额重置完成，新配额:', quotaUpdate)\n }\n\n // 获取今日使用次数\n console.log('开始获取今日使用次数')\n const usage = await sql`\n SELECT type, COUNT(*) as count\n FROM usage_records\n WHERE user_id = ${user.id}\n AND DATE(used_at) = CURRENT_DATE\n GROUP BY type\n ` as UsageRecord[]\n\n console.log('今日使用记录:', usage)\n\n // 构建响应数据\n const response = {\n user: {\n id: user.id,\n email: user.email,\n name: user.name,\n github_id: user.github_id,\n google_id: user.google_id,\n created_at: user.created_at,\n updated_at: user.updated_at\n },\n subscription: {\n stripe_customer_id: user.stripe_customer_id,\n stripe_subscription_id: user.stripe_subscription_id,\n stripe_price_id: user.stripe_price_id,\n stripe_current_period_end: user.stripe_current_period_end\n },\n quota: {\n text_quota: user.text_quota,\n image_quota: user.image_quota,\n pdf_quota: user.pdf_quota,\n speech_quota: user.speech_quota,\n video_quota: user.video_quota\n },\n usage: {\n text: 0,\n image: 0,\n pdf: 0,\n speech: 0,\n video: 0\n } as UsageInfo\n }\n\n // 填充使用次数\n usage.forEach((record) => {\n response.usage[record.type] = parseInt(record.count)\n })\n\n console.log('返回的用户信息:', response)\n return NextResponse.json(response)\n } catch (error) {\n console.error('获取用户信息失败:', error)\n return new NextResponse('Internal error', { status: 500 })\n }\n} " }, { "path": "app/api/user/update/route.ts", "content": "import { getServerSession } from 'next-auth'\nimport { NextResponse } from 'next/server'\nimport { neon } from '@neondatabase/serverless'\nimport { authOptions } from '../../auth/[...nextauth]/auth'\n\nexport async function PUT(req: Request) {\n try {\n const session = await getServerSession(authOptions)\n if (!session?.user?.email) {\n return new NextResponse('Unauthorized', { status: 401 })\n }\n\n const body = await req.json()\n const { name } = body\n\n if (typeof name !== 'string' || name.length > 50) {\n return new NextResponse('Invalid name', { status: 400 })\n }\n\n const sql = neon(process.env.DATABASE_URL!)\n \n // 更新用户名\n await sql`\n UPDATE auth_users\n SET name = ${name}, updated_at = CURRENT_TIMESTAMP\n WHERE email = ${session.user.email}\n `\n\n return new NextResponse('OK')\n } catch (error) {\n console.error('Failed to update user:', error)\n return new NextResponse('Internal error', { status: 500 })\n }\n} " }, { "path": "app/api/user/usage/route.ts", "content": "import { NextResponse } from 'next/server'\nimport { getServerSession } from 'next-auth'\nimport { authOptions } from '@/app/api/auth/[...nextauth]/auth'\nimport { neon } from '@neondatabase/serverless'\n\nconst sql = neon(process.env.DATABASE_URL!)\n\n// 检查配额是否足够\nasync function checkQuota(userId: number, type: string) {\n const quotaField = `${type}_quota`\n \n // 获取用户配额信息\n const result = await sql`\n SELECT ${sql(quotaField)}, quota_reset_at\n FROM auth_users\n WHERE id = ${userId}\n `\n \n if (result.length === 0) {\n throw new Error('用户不存在')\n }\n\n const user = result[0]\n const today = new Date().toISOString().split('T')[0]\n\n // 如果是新的一天，重置配额\n if (user.quota_reset_at !== today) {\n const defaultQuotas = {\n text: -1,\n image: 10,\n pdf: 8,\n speech: 5,\n video: 2\n }\n\n await sql`\n UPDATE auth_users\n SET \n image_quota = ${defaultQuotas.image},\n pdf_quota = ${defaultQuotas.pdf},\n speech_quota = ${defaultQuotas.speech},\n video_quota = ${defaultQuotas.video},\n quota_reset_at = ${today}\n WHERE id = ${userId}\n `\n \n return defaultQuotas[type as keyof typeof defaultQuotas]\n }\n\n return user[quotaField]\n}\n\n// 获取今日使用次数\nasync function getUsageCount(userId: number, type: string) {\n const result = await sql`\n SELECT COUNT(*) as count\n FROM usage_records\n WHERE user_id = ${userId}\n AND type = ${type}\n AND DATE(used_at) = CURRENT_DATE\n `\n return parseInt(result[0].count)\n}\n\n// 记录使用并减少配额\nasync function recordUsage(userId: number, type: string) {\n console.log('开始记录使用情况:', { userId, type })\n \n try {\n // 开始事务\n await sql`BEGIN`\n\n try {\n // 插入使用记录\n await sql`\n INSERT INTO usage_records (user_id, type)\n VALUES (${userId}, ${type})\n `\n console.log('使用记录已插入')\n\n // 如果不是无限制配额，减少剩余次数\n if (type !== 'text') {\n // 根据类型选择不同的更新语句\n let updateResult;\n switch (type) {\n case 'image':\n updateResult = await sql`\n UPDATE auth_users \n SET image_quota = GREATEST(image_quota - 1, 0),\n updated_at = CURRENT_TIMESTAMP\n WHERE id = ${userId}\n RETURNING image_quota as remaining_quota\n `\n break;\n case 'pdf':\n updateResult = await sql`\n UPDATE auth_users \n SET pdf_quota = GREATEST(pdf_quota - 1, 0),\n updated_at = CURRENT_TIMESTAMP\n WHERE id = ${userId}\n RETURNING pdf_quota as remaining_quota\n `\n break;\n case 'speech':\n updateResult = await sql`\n UPDATE auth_users \n SET speech_quota = GREATEST(speech_quota - 1, 0),\n updated_at = CURRENT_TIMESTAMP\n WHERE id = ${userId}\n RETURNING speech_quota as remaining_quota\n `\n break;\n case 'video':\n updateResult = await sql`\n UPDATE auth_users \n SET video_quota = GREATEST(video_quota - 1, 0),\n updated_at = CURRENT_TIMESTAMP\n WHERE id = ${userId}\n RETURNING video_quota as remaining_quota\n `\n break;\n }\n console.log('配额已更新，剩余:', updateResult?.[0]?.remaining_quota)\n }\n\n // 提交事务\n await sql`COMMIT`\n console.log('事务已提交')\n } catch (error) {\n // 如果出错，回滚事务\n await sql`ROLLBACK`\n console.error('事务回滚:', error)\n throw error\n }\n } catch (error) {\n console.error('记录使用情况失败:', error)\n throw error\n }\n}\n\nexport async function POST(req: Request) {\n try {\n const session = await getServerSession(authOptions)\n console.log('当前会话:', session?.user)\n \n if (!session?.user?.email) {\n return NextResponse.json(\n { error: '未登录' },\n { status: 401 }\n )\n }\n\n const { type } = await req.json()\n \n if (!type || !['text', 'image', 'pdf', 'speech', 'video'].includes(type)) {\n return NextResponse.json(\n { error: '无效的使用类型' },\n { status: 400 }\n )\n }\n\n // 获取用户ID\n const users = await sql`\n SELECT id FROM auth_users WHERE email = ${session.user.email}\n `\n\n if (users.length === 0) {\n return NextResponse.json(\n { error: '用户不存在' },\n { status: 404 }\n )\n }\n\n const userId = users[0].id\n\n // 检查配额\n const quota = await checkQuota(userId, type)\n const usageCount = await getUsageCount(userId, type)\n\n // 如果是无限制配额，直接记录使用\n if (quota === -1) {\n await recordUsage(userId, type)\n return NextResponse.json({\n success: true,\n remaining: -1\n })\n }\n\n // 计算剩余次数\n const remainingQuota = quota - usageCount\n\n console.log('配额检查:', {\n type,\n quota,\n usageCount,\n remainingQuota\n })\n\n // 如果没有剩余次数，返回错误\n if (remainingQuota <= 0) {\n return NextResponse.json(\n { error: '今日使用次数已达上限' },\n { status: 403 }\n )\n }\n\n // 记录使用\n await recordUsage(userId, type)\n\n // 返回更新后的配额信息\n console.log('更新后的配额:', {\n type,\n quota,\n usageCount: usageCount + 1,\n remaining: remainingQuota - 1\n })\n\n return NextResponse.json({\n success: true,\n remaining: remainingQuota - 1\n })\n\n } catch (error: any) {\n console.error('记录使用情况失败:', error)\n return NextResponse.json(\n { error: error.message || '记录使用失败' },\n { status: 500 }\n )\n }\n} " }, { "path": "app/api/webhook/route.ts", "content": "import { headers } from 'next/headers'\nimport { NextResponse } from 'next/server'\nimport { stripe } from '@/lib/stripe'\nimport { neon } from '@neondatabase/serverless'\n\nconst webhookSecret = process.env.STRIPE_WEBHOOK_SECRET!\n\nexport async function POST(req: Request) {\n console.log('收到 Stripe Webhook 请求')\n const body = await req.text()\n const signature = headers().get('stripe-signature')\n\n let event\n\n try {\n if (!stripe) {\n console.error('Stripe 未配置')\n return new NextResponse('Stripe is not configured', { status: 500 })\n }\n \n event = stripe.webhooks.constructEvent(\n body,\n signature!,\n webhookSecret\n )\n console.log('Webhook 事件验证成功:', event.type)\n } catch (err: any) {\n console.error('Webhook 签名验证失败:', err)\n return new NextResponse(`Webhook Error: ${err.message}`, { status: 400 })\n }\n\n const sql = neon(process.env.DATABASE_URL!)\n\n try {\n switch (event.type) {\n case 'customer.subscription.created':\n case 'customer.subscription.updated': {\n const subscription = event.data.object\n const userId = subscription.metadata.userId\n const priceId = subscription.items.data[0].price.id\n\n console.log('处理订阅事件:', {\n type: event.type,\n userId,\n priceId,\n customerId: subscription.customer,\n subscriptionId: subscription.id,\n currentPeriodEnd: new Date(subscription.current_period_end * 1000).toISOString()\n })\n\n // 根据价格ID设置对应的配额\n const quotaUpdate = priceId === process.env.NEXT_PUBLIC_STRIPE_MONTHLY_PRICE_ID ? {\n text_quota: -1,\n image_quota: 50,\n pdf_quota: 40,\n speech_quota: 30,\n video_quota: 10\n } : priceId === process.env.NEXT_PUBLIC_STRIPE_YEARLY_PRICE_ID ? {\n text_quota: -1,\n image_quota: 100,\n pdf_quota: 80,\n speech_quota: 60,\n video_quota: 20\n } : {\n text_quota: -1,\n image_quota: 10,\n pdf_quota: 8,\n speech_quota: 5,\n video_quota: 2\n }\n\n console.log('执行数据库更新:', {\n customerId: subscription.customer,\n subscriptionId: subscription.id,\n priceId: subscription.items.data[0].price.id,\n currentPeriodEnd: new Date(subscription.current_period_end * 1000).toISOString(),\n quotaUpdate\n })\n\n // 更新用户订阅状态和配额\n const updateResult = await sql`\n UPDATE auth_users \n SET \n stripe_customer_id = ${subscription.customer},\n stripe_subscription_id = ${subscription.id},\n stripe_price_id = ${subscription.items.data[0].price.id},\n stripe_current_period_end = to_timestamp(${subscription.current_period_end}),\n text_quota = ${quotaUpdate.text_quota},\n image_quota = ${quotaUpdate.image_quota},\n pdf_quota = ${quotaUpdate.pdf_quota},\n speech_quota = ${quotaUpdate.speech_quota},\n video_quota = ${quotaUpdate.video_quota}\n WHERE id = ${userId}\n RETURNING *\n `\n console.log('数据库更新结果:', updateResult[0])\n break\n }\n\n case 'customer.subscription.deleted': {\n const subscription = event.data.object\n const userId = subscription.metadata.userId\n\n // 重置用户为免费计划\n await sql`\n UPDATE auth_users \n SET \n stripe_subscription_id = NULL,\n stripe_price_id = NULL,\n stripe_current_period_end = NULL,\n text_quota = -1,\n image_quota = 5,\n pdf_quota = 3,\n speech_quota = 2,\n video_quota = 1\n WHERE id = ${userId}\n `\n break\n }\n\n case 'invoice.payment_succeeded': {\n const invoice = event.data.object\n const subscription = await stripe.subscriptions.retrieve(invoice.subscription as string)\n const userId = subscription.metadata.userId\n\n // 更新发票支付状态\n await sql`\n INSERT INTO payment_history (\n user_id,\n stripe_invoice_id,\n amount,\n status,\n payment_date\n ) VALUES (\n ${userId},\n ${invoice.id},\n ${invoice.amount_paid},\n 'succeeded',\n to_timestamp(${invoice.created})\n )\n `\n break\n }\n\n case 'invoice.payment_failed': {\n const invoice = event.data.object\n const subscription = await stripe.subscriptions.retrieve(invoice.subscription as string)\n const userId = subscription.metadata.userId\n\n // 记录支付失败\n await sql`\n INSERT INTO payment_history (\n user_id,\n stripe_invoice_id,\n amount,\n status,\n payment_date\n ) VALUES (\n ${userId},\n ${invoice.id},\n ${invoice.amount_due},\n 'failed',\n to_timestamp(${invoice.created})\n )\n `\n\n // 可以在这里添加通知用户的逻辑\n break\n }\n }\n\n return new NextResponse(null, { status: 200 })\n } catch (error: any) {\n console.error('Webhook handler failed:', error)\n return new NextResponse('Webhook handler failed', { status: 500 })\n }\n} " }, { "path": "app/globals.css", "content": "@tailwind base;\n@tailwind components;\n@tailwind utilities;\n\n:root {\n --foreground-rgb: 0, 0, 0;\n --background-start-rgb: 214, 219, 220;\n --background-end-rgb: 255, 255, 255;\n}\n\n@media (prefers-color-scheme: dark) {\n :root {\n --foreground-rgb: 255, 255, 255;\n --background-start-rgb: 0, 0, 0;\n --background-end-rgb: 0, 0, 0;\n }\n}\n\n@layer base {\n :root {\n --background: 0 0% 100%;\n --foreground: 222.2 84% 4.9%;\n --card: 0 0% 100%;\n --card-foreground: 222.2 84% 4.9%;\n --popover: 0 0% 100%;\n --popover-foreground: 222.2 84% 4.9%;\n \n /* 更新为 #8cc63f 绿色 */\n --primary: 84 68% 51%;\n --primary-foreground: 210 40% 98%;\n \n /* 更新为匹配绿色的渐变色 */\n --secondary: 100 65% 45%;\n --secondary-foreground: 222.2 47.4% 11.2%;\n \n /* 更新为匹配绿色的渐变色 */\n --accent: 70 70% 50%;\n --accent-foreground: 222.2 47.4% 11.2%;\n \n --muted: 210 40% 96.1%;\n --muted-foreground: 215.4 16.3% 46.9%;\n --destructive: 0 84.2% 60.2%;\n --destructive-foreground: 210 40% 98%;\n --border: 214.3 31.8% 91.4%;\n --input: 214.3 31.8% 91.4%;\n --ring: 222.2 84% 4.9%;\n --chart-1: 84 68% 51%;\n --chart-2: 70 70% 50%;\n --chart-3: 100 65% 45%;\n --chart-4: 120 60% 45%;\n --chart-5: 140 65% 40%;\n --radius: 0.5rem;\n }\n .dark {\n --background: 222.2 84% 4.9%;\n --foreground: 210 40% 98%;\n --card: 222.2 84% 4.9%;\n --card-foreground: 210 40% 98%;\n --popover: 222.2 84% 4.9%;\n --popover-foreground: 210 40% 98%;\n \n /* 更新为 #8cc63f 绿色 */\n --primary: 84 68% 51%;\n --primary-foreground: 222.2 47.4% 11.2%;\n \n /* 更新为匹配绿色的渐变色 */\n --secondary: 100 65% 45%;\n --secondary-foreground: 210 40% 98%;\n \n /* 更新为匹配绿色的渐变色 */\n --accent: 70 70% 50%;\n --accent-foreground: 210 40% 98%;\n \n --muted: 217.2 32.6% 17.5%;\n --muted-foreground: 215 20.2% 65.1%;\n --destructive: 0 62.8% 30.6%;\n --destructive-foreground: 210 40% 98%;\n --border: 217.2 32.6% 17.5%;\n --input: 217.2 32.6% 17.5%;\n --ring: 212.7 26.8% 83.9%;\n --chart-1: 84 68% 51%;\n --chart-2: 70 70% 50%;\n --chart-3: 100 65% 45%;\n --chart-4: 120 60% 45%;\n --chart-5: 140 65% 40%;\n }\n}\n\n@layer base {\n * {\n @apply border-border;\n }\n body {\n @apply bg-background text-foreground;\n }\n}\n\n@keyframes fadeIn {\n from {\n opacity: 0;\n }\n to {\n opacity: 1;\n }\n}\n\n.animate-fadeIn {\n animation: fadeIn 0.5s ease-in forwards;\n}\n\n/* Swiper 自定义样式 */\n.testimonials-swiper {\n padding-bottom: 3rem !important;\n}\n\n.testimonials-swiper .swiper-pagination-bullet {\n width: 10px;\n height: 10px;\n background: hsl(var(--muted-foreground));\n opacity: 0.5;\n}\n\n.testimonials-swiper .swiper-pagination-bullet-active {\n background: hsl(var(--primary));\n opacity: 1;\n}\n\n.testimonials-swiper .swiper-button-next,\n.testimonials-swiper .swiper-button-prev {\n color: hsl(var(--primary));\n transition: all 0.2s;\n}\n\n.testimonials-swiper .swiper-button-next:hover,\n.testimonials-swiper .swiper-button-prev:hover {\n transform: scale(1.1);\n}\n\n.testimonials-swiper .swiper-button-next::after,\n.testimonials-swiper .swiper-button-prev::after {\n font-size: 1.5rem;\n font-weight: bold;\n}\n\n/* 暗色模式样式 */\n.dark .testimonials-swiper .swiper-pagination-bullet {\n background: hsl(var(--muted-foreground));\n}\n\n.dark .testimonials-swiper .swiper-pagination-bullet-active {\n background: hsl(var(--primary));\n}\n\n.dark .testimonials-swiper .swiper-button-next,\n.dark .testimonials-swiper .swiper-button-prev {\n color: hsl(var(--primary));\n}\n" }, { "path": "app/layout.tsx", "content": "import './globals.css';\nimport { Inter } from 'next/font/google';\nimport { Providers } from \"./providers\";\nimport GoogleAnalytics from '@/components/google-analytics';\nimport { LanguageProvider } from \"@/components/language-provider\";\nimport type { Metadata, Viewport } from 'next';\n\nconst inter = Inter({ subsets: ['latin'] });\n\nexport const viewport: Viewport = {\n width: 'device-width',\n initialScale: 1,\n};\n\nexport const metadata: Metadata = {\n metadataBase: new URL('https://aitranslate.site'),\n title: {\n template: '%s | AI Translation Assistant',\n default: 'AI Translation Assistant - Smart Multilingual Translation Platform',\n },\n description: 'All-in-one intelligent translation solution supporting text, image, PDF, speech, and video translation, making cross-language communication simpler.',\n keywords: ['AI Translation', 'Multilingual Translation', 'Image Translation', 'PDF Translation', 'Speech Translation', 'Video Translation', 'Machine Translation'],\n authors: [{ name: 'AI Translation Assistant Team' }],\n creator: 'AI Translation Assistant Team',\n publisher: 'AI Translation Assistant',\n icons: {\n icon: [\n { url: '/favicon.ico', sizes: 'any' },\n { url: '/favicon-16x16.png', sizes: '16x16', type: 'image/png' },\n { url: '/favicon-32x32.png', sizes: '32x32', type: 'image/png' },\n ],\n apple: [\n { url: '/apple-touch-icon.png', sizes: '180x180', type: 'image/png' },\n ],\n },\n manifest: '/site.webmanifest',\n robots: {\n index: true,\n follow: true,\n },\n openGraph: {\n type: 'website',\n locale: 'en_US',\n url: '/',\n title: 'AI Translation Assistant - Smart Multilingual Translation Platform',\n description: 'All-in-one intelligent translation solution supporting text, image, PDF, speech, and video translation, making cross-language communication simpler.',\n siteName: 'AI Translation Assistant',\n images: [\n {\n url: '/og-image.png',\n width: 1200,\n height: 630,\n alt: 'AI Translation Assistant',\n },\n ],\n },\n twitter: {\n card: 'summary_large_image',\n title: 'AI Translation Assistant - Smart Multilingual Translation Platform',\n description: 'All-in-one intelligent translation solution supporting text, image, PDF, speech, and video translation, making cross-language communication simpler.',\n images: ['/og-image.png'],\n },\n verification: {\n google: 'yLQ9THm_U56rW0n0VsGzM6IXvWmlbS3fV7NGl-SZT3k',\n },\n};\n\nexport default function RootLayout({\n children,\n}: {\n children: React.ReactNode;\n}) {\n return (\n \n \n \n \n \n \n \n \n \n \n \n \n {children}\n \n \n \n \n );\n}" }, { "path": "app/login/error.tsx", "content": "'use client';\n\nimport { useSearchParams } from 'next/navigation';\nimport { useEffect } from 'react';\nimport { toast } from 'sonner';\nimport { useI18n } from '@/lib/i18n/use-translations';\n\nexport default function ErrorPage() {\n const { t } = useI18n();\n const searchParams = useSearchParams();\n const error = searchParams.get('error');\n\n useEffect(() => {\n if (error === 'AccessDenied') {\n toast.error(t('auth.error.accessDenied'));\n } else if (error) {\n toast.error(t('auth.error.default'));\n }\n }, [error, t]);\n\n return null;\n} " }, { "path": "app/login/layout.tsx", "content": "import { Metadata } from 'next'\n\nexport const metadata: Metadata = {\n title: 'Sign in',\n description: 'Sign in to your account',\n}\n\nexport default function LoginLayout({\n children,\n}: {\n children: React.ReactNode\n}) {\n return children\n} " }, { "path": "app/login/page.tsx", "content": "\"use client\";\n\nimport Link from 'next/link'\nimport { useRouter, useSearchParams } from 'next/navigation'\nimport { useState, useEffect } from 'react'\nimport { signIn, useSession } from 'next-auth/react'\nimport { Button } from '@/components/ui/button'\nimport { Input } from '@/components/ui/input'\nimport { Label } from '@/components/ui/label'\nimport { toast } from 'sonner'\nimport { useI18n } from '@/lib/i18n/use-translations'\nimport { Github } from 'lucide-react'\nimport { Separator } from '@/components/ui/separator'\n\nexport default function LoginPage() {\n const { t } = useI18n()\n const router = useRouter()\n const searchParams = useSearchParams()\n const { data: session } = useSession()\n const [loading, setLoading] = useState(false)\n const [email, setEmail] = useState('')\n const [password, setPassword] = useState('')\n\n const callbackUrl = searchParams.get('returnUrl') || searchParams.get('callbackUrl') || '/'\n\n useEffect(() => {\n if (session) {\n router.push(callbackUrl)\n }\n }, [session, router, callbackUrl])\n\n const handleSubmit = async (e: React.FormEvent) => {\n e.preventDefault()\n setLoading(true)\n\n try {\n if (!email || !password) {\n throw new Error(t('auth.login.error.required'))\n }\n\n console.log('Attempting to sign in with credentials, callbackUrl:', callbackUrl)\n \n const result = await signIn('credentials', {\n email,\n password,\n redirect: true,\n callbackUrl,\n })\n\n // 由于设置了 redirect: true，下面的代码不会执行\n // 登录成功后会自动重定向到 callbackUrl\n console.log('Sign in result:', result)\n } catch (error: any) {\n console.error('Sign in error:', error)\n toast.error(error.message || t('auth.signIn.error'))\n } finally {\n setLoading(false)\n }\n }\n\n const handleGitHubLogin = async () => {\n setLoading(true)\n try {\n console.log('Attempting GitHub login, callbackUrl:', callbackUrl)\n await signIn('github', { \n callbackUrl,\n redirect: true\n })\n } catch (error) {\n console.error('GitHub login error:', error)\n toast.error(t('auth.signIn.error'))\n }\n }\n\n const handleGoogleLogin = async () => {\n setLoading(true)\n try {\n console.log('Attempting Google login, callbackUrl:', callbackUrl)\n await signIn('google', { \n callbackUrl,\n redirect: true\n })\n } catch (error) {\n console.error('Google login error:', error)\n toast.error(t('auth.signIn.error'))\n }\n }\n\n if (session) {\n return null\n }\n\n return (\n
\n
\n
\n

\n {t('auth.login.title')}\n

\n

\n {t('auth.login.subtitle')}\n

\n
\n
\n \n \n
\n
\n
\n \n
\n
\n \n {t('auth.login.or')}\n \n
\n
\n
\n
\n \n setEmail(e.target.value)}\n disabled={loading}\n />\n
\n
\n \n setPassword(e.target.value)}\n disabled={loading}\n />\n
\n \n
\n
\n {t('auth.login.noAccount')}{' '}\n \n {t('auth.signUp')}\n \n
\n
\n
\n )\n} " }, { "path": "app/page.tsx", "content": "\"use client\"\n\nimport Link from 'next/link'\nimport { useI18n } from '@/lib/i18n/use-translations'\nimport { Button } from '@/components/ui/button'\nimport { Card, CardContent } from '@/components/ui/card'\nimport { Badge } from '@/components/ui/badge'\nimport { cn } from '@/lib/utils'\nimport { motion } from 'framer-motion'\nimport { Swiper, SwiperSlide } from 'swiper/react'\nimport { Autoplay, Navigation, Pagination } from 'swiper/modules'\nimport 'swiper/css'\nimport 'swiper/css/navigation'\nimport 'swiper/css/pagination'\nimport { \n Languages, \n Image, \n FileText, \n Mic, \n Video, \n Moon, \n Lock, \n Crown, \n Globe2, \n Chrome, \n MonitorSmartphone, \n ArrowRight, \n Sparkles \n} from 'lucide-react'\n\nexport default function Home() {\n const { t } = useI18n()\n\n const container = {\n hidden: { opacity: 0 },\n show: {\n opacity: 1,\n transition: {\n staggerChildren: 0.1\n }\n }\n }\n\n const item = {\n hidden: { opacity: 0, y: 20 },\n show: { opacity: 1, y: 0 }\n }\n\n const features = [\n {\n icon: ,\n title: t('landing.features.text.title'),\n description: t('landing.features.text.description'),\n },\n {\n icon: ,\n title: t('landing.features.image.title'),\n description: t('landing.features.image.description'),\n },\n {\n icon: ,\n title: t('landing.features.pdf.title'),\n description: t('landing.features.pdf.description'),\n },\n {\n icon: ,\n title: t('landing.features.speech.title'),\n description: t('landing.features.speech.description'),\n },\n {\n icon: