358deeb380
- 添加完整的 Docker 配置 (Dockerfile, docker-compose.yml) - 修复前端硬编码端口 4000，改用相对路径 /api - 实现多 OCR 提供商架构 (Tesseract.js/Baidu/RapidOCR) - 修复 Docker 环境中图片上传路径问题 - 添加用户设置页面和 AI 分析服务 - 更新 Prisma schema 支持 AI 分析结果 - 添加部署文档和 OCR 配置指南 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
476 lines
12 KiB
TypeScript
476 lines
12 KiB
TypeScript
/**
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* AI Service
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* 支持 6 个主流 AI 服务商进行文档智能分析
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* - GLM (智谱 AI)
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* - MiniMax
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* - DeepSeek
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* - Kimi (月之暗面)
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* - OpenAI
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* - Anthropic (Claude)
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*/
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import { prisma } from '../lib/prisma';
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// AI Provider 类型
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export type AIProviderType = 'glm' | 'minimax' | 'deepseek' | 'kimi' | 'openai' | 'anthropic';
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// AI 分析结果
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export interface AIAnalysisResult {
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suggested_tags: string[];
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suggested_category?: string;
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summary?: string;
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raw_response: string;
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provider: AIProviderType;
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model: string;
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}
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// AI Provider 配置
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export interface AIProviderConfig {
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apiKey: string;
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apiUrl: string;
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model: string;
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}
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// Provider 配置映射
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export interface AIConfig {
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defaultProvider: AIProviderType;
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glm: AIProviderConfig;
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minimax: AIProviderConfig;
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deepseek: AIProviderConfig;
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kimi: AIProviderConfig;
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openai: AIProviderConfig;
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anthropic: AIProviderConfig;
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}
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// 分析选项
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export interface AnalyzeOptions {
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provider?: AIProviderType;
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config?: AIConfig;
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generateSummary?: boolean;
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maxTags?: number;
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}
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// API 响应接口
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interface ChatMessage {
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role: 'system' | 'user' | 'assistant';
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content: string;
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}
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interface ChatCompletionResponse {
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choices: Array<{
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message: {
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content: string;
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};
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}>;
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usage?: {
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prompt_tokens: number;
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completion_tokens: number;
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total_tokens: number;
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};
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}
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interface AnthropicResponse {
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content: Array<{
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type: string;
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text: string;
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}>;
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usage?: {
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input_tokens: number;
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output_tokens: number;
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};
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}
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/**
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* AI 服务类
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*/
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export class AIService {
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/**
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* 从环境变量或用户配置获取 AI 配置
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*/
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private static getAIConfig(_userId: string): AIConfig {
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return {
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defaultProvider: 'glm',
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glm: {
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apiKey: process.env.GLM_API_KEY || '',
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apiUrl: process.env.GLM_API_URL || 'https://open.bigmodel.cn/api/paas/v4/chat/completions',
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model: process.env.GLM_MODEL || 'glm-4-flash',
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},
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minimax: {
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apiKey: process.env.MINIMAX_API_KEY || '',
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apiUrl: process.env.MINIMAX_API_URL || 'https://api.minimax.chat/v1/chat/completions',
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model: process.env.MINIMAX_MODEL || 'abab6.5s-chat',
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},
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deepseek: {
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apiKey: process.env.DEEPSEEK_API_KEY || '',
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apiUrl: process.env.DEEPSEEK_API_URL || 'https://api.deepseek.com/v1/chat/completions',
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model: process.env.DEEPSEEK_MODEL || 'deepseek-chat',
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},
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kimi: {
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apiKey: process.env.KIMI_API_KEY || '',
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apiUrl: process.env.KIMI_API_URL || 'https://api.moonshot.cn/v1/chat/completions',
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model: process.env.KIMI_MODEL || 'moonshot-v1-8k',
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},
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openai: {
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apiKey: process.env.OPENAI_API_KEY || '',
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apiUrl: process.env.OPENAI_API_URL || 'https://api.openai.com/v1/chat/completions',
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model: process.env.OPENAI_MODEL || 'gpt-4o-mini',
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},
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anthropic: {
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apiKey: process.env.ANTHROPIC_API_KEY || '',
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apiUrl: process.env.ANTHROPIC_API_URL || 'https://api.anthropic.com/v1/messages',
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model: process.env.ANTHROPIC_MODEL || 'claude-3-5-sonnet-20241022',
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},
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};
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}
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/**
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* 调用 OpenAI 兼容的 API (GLM, MiniMax, DeepSeek, Kimi, OpenAI)
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*/
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private static async callOpenAICompatibleAPI(
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config: AIProviderConfig,
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messages: ChatMessage[]
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): Promise<string> {
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const response = await fetch(config.apiUrl, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${config.apiKey}`,
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},
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body: JSON.stringify({
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model: config.model,
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messages,
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temperature: 0.3,
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max_tokens: 1000,
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}),
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});
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if (!response.ok) {
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const errorText = await response.text();
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throw new Error(`API 请求失败 (${response.status}): ${errorText}`);
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}
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const data = await response.json() as ChatCompletionResponse;
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return data.choices[0]?.message?.content || '';
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}
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/**
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* 调用 Anthropic Claude API
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*/
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private static async callAnthropicAPI(
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config: AIProviderConfig,
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messages: ChatMessage[]
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): Promise<string> {
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// Anthropic API 需要提取 system 消息
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const systemMessage = messages.find(m => m.role === 'system')?.content || '';
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const userMessages = messages.filter(m => m.role !== 'system');
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const response = await fetch(config.apiUrl, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'x-api-key': config.apiKey,
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'anthropic-version': '2023-06-01',
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},
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body: JSON.stringify({
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model: config.model,
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system: systemMessage,
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messages: userMessages,
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max_tokens: 1000,
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}),
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});
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if (!response.ok) {
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const errorText = await response.text();
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throw new Error(`Anthropic API 请求失败 (${response.status}): ${errorText}`);
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}
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const data = await response.json() as AnthropicResponse;
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return data.content[0]?.text || '';
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}
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/**
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* 调用 AI Provider 分析文档
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*/
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private static async callAIProvider(
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provider: AIProviderType,
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config: AIConfig,
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content: string,
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prompt: string
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): Promise<string> {
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const providerConfig = config[provider];
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if (!providerConfig.apiKey) {
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throw new Error(`${provider} API Key 未配置`);
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}
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const messages: ChatMessage[] = [
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{
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role: 'system',
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content: `你是一个智能文档分析助手。${prompt}`,
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},
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{
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role: 'user',
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content: `请分析以下文档内容：\n\n${content}`,
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},
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];
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// Anthropic 使用不同的 API 格式
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if (provider === 'anthropic') {
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return this.callAnthropicAPI(providerConfig, messages);
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}
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// 其他 Provider 使用 OpenAI 兼容格式
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return this.callOpenAICompatibleAPI(providerConfig, messages);
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}
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/**
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* 解析 AI 响应，提取结构化数据
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*/
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private static parseAIResponse(response: string): {
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tags: string[];
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category?: string;
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summary?: string;
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} {
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const result = {
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tags: [] as string[],
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category: undefined as string | undefined,
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summary: undefined as string | undefined,
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};
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// 尝试解析 JSON 格式响应
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try {
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// 查找 JSON 块
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const jsonMatch = response.match(/\{[\s\S]*\}/);
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if (jsonMatch) {
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const parsed = JSON.parse(jsonMatch[0]);
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result.tags = parsed.tags || [];
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result.category = parsed.category;
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result.summary = parsed.summary;
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return result;
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}
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} catch (e) {
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// JSON 解析失败，使用文本解析
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}
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// 文本解析：按行查找标签、分类和摘要
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const lines = response.split('\n');
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for (const line of lines) {
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const lowerLine = line.toLowerCase().trim();
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if (lowerLine.startsWith('标签:') || lowerLine.startsWith('tags:')) {
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const tags = line.substring(line.indexOf(':') + 1).trim();
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result.tags = tags.split(/[,，、]/).map(t => t.trim()).filter(t => t);
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} else if (lowerLine.startsWith('分类:') || lowerLine.startsWith('category:')) {
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result.category = line.substring(line.indexOf(':') + 1).trim();
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} else if (lowerLine.startsWith('摘要:') || lowerLine.startsWith('summary:')) {
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result.summary = line.substring(line.indexOf(':') + 1).trim();
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}
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}
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// 如果没有找到标签，尝试从响应中提取关键词
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if (result.tags.length === 0) {
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const words = response.match(/[\u4e00-\u9fa5]{2,4}/g) || [];
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result.tags = [...new Set(words)].slice(0, 5);
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}
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return result;
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}
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/**
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* 分析文档内容，生成智能标签和分类
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*/
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static async analyzeDocument(
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documentId: string,
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userId: string,
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options: AnalyzeOptions = {}
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): Promise<AIAnalysisResult> {
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// 获取文档
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const document = await prisma.document.findFirst({
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where: {
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id: documentId,
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user_id: userId,
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},
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});
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if (!document) {
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throw new Error('文档不存在或无权访问');
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}
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// 获取 AI 配置
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const config = options.config || this.getAIConfig(userId);
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const provider = options.provider || config.defaultProvider;
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// 检查 API Key
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const providerConfig = config[provider];
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if (!providerConfig.apiKey) {
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throw new Error(`${provider} API Key 未配置，请在设置页面配置`);
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}
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// 构建分析提示词
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const prompt = `请分析文档内容，返回以下信息（JSON 格式）：
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{
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"tags": ["标签1", "标签2", "标签3"], // 3-5个关键词标签
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"category": "建议的分类名称", // 可选
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"summary": "一句话摘要" // 可选
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}
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要求：
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1. 标签应该能体现文档的核心内容
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2. 分类应该简洁明了（如：工作、学习、生活、技术等）
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3. 摘要应该简洁概括文档要点
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4. 直接返回 JSON，不要有其他内容`;
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// 调用 AI API
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try {
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const rawResponse = await this.callAIProvider(
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provider,
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config,
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document.content,
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prompt
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);
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// 解析响应
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const parsed = this.parseAIResponse(rawResponse);
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// 限制标签数量
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const maxTags = options.maxTags || 5;
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const suggestedTags = parsed.tags.slice(0, maxTags);
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// 保存分析结果到数据库
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await prisma.aIAnalysis.upsert({
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where: { document_id: documentId },
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create: {
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document_id: documentId,
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provider,
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model: providerConfig.model,
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suggested_tags: JSON.stringify(suggestedTags),
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suggested_category: parsed.category,
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summary: parsed.summary,
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raw_response: rawResponse,
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},
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update: {
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provider,
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model: providerConfig.model,
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suggested_tags: JSON.stringify(suggestedTags),
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suggested_category: parsed.category,
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summary: parsed.summary,
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raw_response: rawResponse,
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},
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});
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return {
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suggested_tags: suggestedTags,
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suggested_category: parsed.category,
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summary: parsed.summary,
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raw_response: rawResponse,
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provider,
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model: providerConfig.model,
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};
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} catch (error) {
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console.error('[AI] 分析失败:', error);
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throw error;
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}
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}
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/**
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* 获取文档的 AI 分析结果
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*/
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static async getAnalysis(documentId: string, userId: string) {
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// 验证文档所有权
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const document = await prisma.document.findFirst({
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where: {
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id: documentId,
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user_id: userId,
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},
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});
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if (!document) {
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throw new Error('文档不存在或无权访问');
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}
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const analysis = await prisma.aIAnalysis.findUnique({
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where: { document_id: documentId },
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});
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if (!analysis) {
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return null;
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}
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return {
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...analysis,
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suggested_tags: JSON.parse(analysis.suggested_tags),
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};
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}
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/**
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* 删除文档的 AI 分析结果
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*/
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static async deleteAnalysis(documentId: string, userId: string) {
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// 验证文档所有权
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const document = await prisma.document.findFirst({
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where: {
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id: documentId,
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user_id: userId,
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},
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});
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if (!document) {
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throw new Error('文档不存在或无权访问');
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}
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await prisma.aIAnalysis.delete({
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where: { document_id: documentId },
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});
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}
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/**
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* 测试 AI Provider 连接
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*/
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static async testProvider(
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provider: AIProviderType,
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config?: Partial<AIConfig>
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): Promise<{
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success: boolean;
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message: string;
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error?: string;
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}> {
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try {
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const fullConfig = config ? { ...this.getAIConfig(''), ...config } : this.getAIConfig('');
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const providerConfig = fullConfig[provider];
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if (!providerConfig.apiKey) {
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return {
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success: false,
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message: 'API Key 未配置',
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error: `${provider} API Key 未配置`,
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};
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}
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// 发送简单测试请求
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const messages: ChatMessage[] = [
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{
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role: 'user',
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content: 'Hi',
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},
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];
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if (provider === 'anthropic') {
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await this.callAnthropicAPI(providerConfig, messages);
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} else {
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await this.callOpenAICompatibleAPI(providerConfig, messages);
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}
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return {
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success: true,
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message: `${provider} 连接成功`,
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};
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} catch (error) {
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return {
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success: false,
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message: '连接失败',
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error: error instanceof Error ? error.message : String(error),
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};
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}
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}
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}
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