feat(llm): 大模型双协议(OpenAI+Anthropic)接入 + SSH凭证修复 + 容量预测AI解读
后端双协议: 新增 anthropic.go(Complete/Stream/工具转换) + client.go 工厂按 Protocol 路由; llm.Client 加 Stream; llm_chat 三方法收敛复用 llm.Client; resolveProtocol 按 provider 路由; Agent CLI 注入协议。编码套餐(GLM-5.2/Kimi/MiMo/Anthropic)走 Anthropic /v1/messages。 SSH凭证修复: applyCredential 正确解析凭证 JSON 的 private_key(旧实现把整个 JSON 当私钥 → ssh.ParsePrivateKey 失败 → ssh-key 登录不通); AssignCredential/批量导入/单台 CRUD 三处统一; 单台补齐 credential_id 字段(原被忽略)。 容量预测: 新增 AI 深度解读(buildCapacityInsightPrompt + PredictiveCapacityTab 按钮, 复用 aiApi.chat)。 其他: DeepSeek 模型名更新为 deepseek-v4-flash/pro; 智能助手去掉重复模型配置按钮; LLMConfig 精简生成参数(Claude Code 式)。 Co-Authored-By: Claude <noreply@anthropic.com>
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@@ -27,16 +27,6 @@ import {
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} from 'lucide-react';
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import type { JsonData } from '@/types/common';
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// LLM 提供商列表（OpenAI 兼容接口） // Logan.Li
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const LLM_PROVIDERS: { id: string; name: string; defaultEndpoint: string; models: string[] }[] = [
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{ id: 'openai', name: 'OpenAI', defaultEndpoint: 'https://api.openai.com/v1', models: ['gpt-4o-mini', 'gpt-4o', 'gpt-4-turbo'] },
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{ id: 'deepseek', name: 'DeepSeek', defaultEndpoint: 'https://api.deepseek.com/v1', models: ['deepseek-chat', 'deepseek-reasoner'] },
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{ id: 'qwen', name: '通义千问 (DashScope)', defaultEndpoint: 'https://dashscope.aliyuncs.com/compatible-mode/v1', models: ['qwen-plus', 'qwen-turbo', 'qwen-max'] },
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{ id: 'moonshot', name: 'Moonshot 月之暗面', defaultEndpoint: 'https://api.moonshot.cn/v1', models: ['moonshot-v1-8k', 'moonshot-v1-32k'] },
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{ id: 'ollama', name: 'Ollama 本地', defaultEndpoint: 'http://localhost:11434/v1', models: ['qwen2.5:7b', 'llama3.2', 'deepseek-r1:7b'] },
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{ id: 'custom', name: '自定义 (OpenAI 兼容)', defaultEndpoint: '', models: [] },
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];
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const defaultConfig: LLMConfigData = {
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provider: 'openai',
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model: 'gpt-4o-mini',
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@@ -323,15 +313,6 @@ export function AIOpsAssistant() {
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{config.model}
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</Badge>
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) : null}
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<Button
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variant="outline"
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size="sm"
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className="border-slate-700 text-slate-300 hover:text-purple-400"
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onClick={() => navigate('/ai-llm-config')}
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>
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<Settings className="h-4 w-4 mr-1" />
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模型配置
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</Button>
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</div>
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</div>
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@@ -13,19 +13,27 @@ import { toast } from 'sonner';
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import { Loader2, Save, Wifi, KeyRound, Brain } from 'lucide-react';
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import { aiApi, type LLMConfigData } from '@/api';
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// OpenAI 兼容提供商列表 // Logan.Li
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// 提供商列表（后端按 provider 自动路由协议） // Logan.Li
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// Anthropic 协议（glm-coding / anthropic）：端点不含 /v1，后端拼 /v1/messages。
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// OpenAI 协议（其余）：端点含 /v1，后端拼 /chat/completions。
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const PROVIDERS = [
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{ id: 'openai', name: 'OpenAI', endpoint: 'https://api.openai.com/v1', models: 'gpt-4o-mini, gpt-4o' },
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{ id: 'deepseek', name: 'DeepSeek', endpoint: 'https://api.deepseek.com/v1', models: 'deepseek-chat, deepseek-reasoner' },
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{ id: 'openai', name: 'OpenAI', endpoint: 'https://api.openai.com/v1', models: 'gpt-4o-mini, gpt-4o, gpt-4.1' },
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{ id: 'deepseek', name: 'DeepSeek', endpoint: 'https://api.deepseek.com/v1', models: 'deepseek-v4-flash, deepseek-v4-pro' },
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{ id: 'glm', name: '智谱 GLM (通用)', endpoint: 'https://open.bigmodel.cn/api/paas/v4', models: 'glm-4.6, glm-4.5, glm-4-flash' },
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{ id: 'glm-coding', name: '智谱 GLM (编码套餐)', endpoint: 'https://open.bigmodel.cn/api/anthropic', models: 'GLM-5.2' },
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{ id: 'qwen', name: '通义千问 (DashScope)', endpoint: 'https://dashscope.aliyuncs.com/compatible-mode/v1', models: 'qwen-plus, qwen-turbo, qwen-max' },
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{ id: 'moonshot', name: 'Moonshot 月之暗面', endpoint: 'https://api.moonshot.cn/v1', models: 'moonshot-v1-8k, moonshot-v1-32k' },
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{ id: 'moonshot', name: 'Moonshot (Kimi)', endpoint: 'https://api.moonshot.cn/v1', models: 'kimi-latest, moonshot-v1-8k, moonshot-v1-32k' },
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{ id: 'kimi', name: 'Kimi 编码套餐', endpoint: 'https://api.kimi.com/coding/v1', models: 'kimi-for-coding' },
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{ id: 'mimo', name: '小米 MiMo', endpoint: 'https://api.mimo.mi.com/v1', models: 'mimo-v2-flash, mimo-v2' },
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{ id: 'anthropic', name: 'Anthropic Claude', endpoint: 'https://api.anthropic.com', models: 'claude-sonnet-4-6, claude-opus-4-8, claude-haiku-4-5' },
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{ id: 'ollama', name: 'Ollama 本地', endpoint: 'http://localhost:11434/v1', models: 'qwen2.5:7b, llama3.2' },
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{ id: 'custom', name: '自定义 (OpenAI 兼容)', endpoint: '', models: '' },
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];
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// 生成参数（温度/max_tokens/系统提示词）已按 Claude Code 模式精简：UI 不再暴露，走内置默认。 // Logan.Li
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const defaultCfg: LLMConfigData = {
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provider: 'deepseek', model: 'deepseek-chat', api_key: '',
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endpoint: 'https://api.deepseek.com/v1', temperature: 0.3, max_tokens: 4096,
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provider: 'deepseek', model: 'deepseek-v4-flash', api_key: '',
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endpoint: 'https://api.deepseek.com/v1', temperature: 0.7, max_tokens: 8192,
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system_prompt: '', enabled: false,
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};
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@@ -105,36 +113,11 @@ export default function LLMConfigPage() {
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</CardContent>
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</Card>
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<Card className="bg-slate-900/60 border-slate-800">
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<CardHeader><CardTitle className="text-slate-200 text-base">生成参数</CardTitle></CardHeader>
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<CardContent className="space-y-4">
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<div className="grid grid-cols-2 gap-4">
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<div className="space-y-1.5">
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<Label className="text-slate-300">温度（Temperature）</Label>
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<Input type="number" step="0.1" min="0" max="2" value={cfg.temperature}
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onChange={(e) => set('temperature', Number(e.target.value))}
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className="bg-slate-800 border-slate-700 text-slate-200" />
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</div>
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<div className="space-y-1.5">
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<Label className="text-slate-300">最大输出 Token</Label>
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<Input type="number" min="256" value={cfg.max_tokens}
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onChange={(e) => set('max_tokens', Number(e.target.value))}
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className="bg-slate-800 border-slate-700 text-slate-200" />
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</div>
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</div>
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<div className="space-y-1.5">
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<Label className="text-slate-300">系统提示词（可选，留空使用内置运维助手角色）</Label>
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<textarea value={cfg.system_prompt} onChange={(e) => set('system_prompt', e.target.value)} rows={3}
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className="w-full bg-slate-800 border border-slate-700 rounded-md px-3 py-2 text-sm text-slate-200 resize-none" />
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</div>
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<div className="flex items-center justify-between">
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<Label className="text-slate-300">启用 LLM 服务</Label>
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<Switch checked={cfg.enabled} onCheckedChange={(v) => set('enabled', v)} />
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</div>
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</CardContent>
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</Card>
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<div className="flex items-center gap-2">
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<div className="flex items-center gap-2 text-sm text-slate-300">
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<Switch checked={cfg.enabled} onCheckedChange={(v) => set('enabled', v)} />
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<span>启用 LLM 服务</span>
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</div>
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<Button onClick={save} disabled={saving} className="bg-blue-600 hover:bg-blue-700">
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{saving ? <Loader2 className="w-4 h-4 mr-1 animate-spin" /> : <Save className="w-4 h-4 mr-1" />} 保存配置
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</Button>
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@@ -1,7 +1,11 @@
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import { HardDrive, Database, Zap, Loader2 } from 'lucide-react';
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import { useState } from 'react';
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import { HardDrive, Database, Zap, Loader2, Sparkles } from 'lucide-react';
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import { Badge } from '@/components/ui/badge';
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import { Button } from '@/components/ui/button';
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import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
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import type { CapacityForecast } from './predictUtils';
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import { toast } from 'sonner';
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import { aiApi } from '@/api';
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import { buildCapacityInsightPrompt, type CapacityForecast } from './predictUtils';
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export function PredictiveCapacityTab({
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forecasts,
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@@ -10,6 +14,25 @@ export function PredictiveCapacityTab({
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forecasts: CapacityForecast[];
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loading: boolean;
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}) {
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const [insight, setInsight] = useState('');
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const [analyzing, setAnalyzing] = useState(false);
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// AI 深度解读：把容量预测硬数据喂给 LLM，生成综合风险评估与运维建议 // Logan.Li
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// 复用 aiApi.chat（双协议后自动支持 GLM-5.2 等）；失败仅 toast，下方逐条模板建议仍可读。
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const analyze = async () => {
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const prompt = buildCapacityInsightPrompt(forecasts);
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if (!prompt) return;
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setAnalyzing(true);
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try {
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const res = await aiApi.chat([{ role: 'user', content: prompt }]);
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setInsight(res?.content || '');
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} catch {
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toast.error('AI 解读失败，请检查大模型配置或稍后重试');
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} finally {
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setAnalyzing(false);
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}
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};
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return (
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<Card className="bg-slate-800 border-slate-700">
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<CardHeader className="pb-3">
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@@ -18,7 +41,22 @@ export function PredictiveCapacityTab({
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<HardDrive className="h-5 w-5 text-amber-400" />
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容量规划预警
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</CardTitle>
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<span className="text-xs text-slate-500">基于日均增长率推算阈值触及时间</span>
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{!loading && forecasts.length > 0 && (
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<Button
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variant="outline"
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size="sm"
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onClick={analyze}
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disabled={analyzing}
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className="border-purple-500/30 text-purple-300 hover:text-purple-200 h-7"
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>
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{analyzing ? (
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<Loader2 className="h-3.5 w-3.5 mr-1 animate-spin" />
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) : (
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<Sparkles className="h-3.5 w-3.5 mr-1" />
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)}
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AI 深度解读
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</Button>
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)}
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</div>
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</CardHeader>
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<CardContent>
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@@ -30,6 +68,16 @@ export function PredictiveCapacityTab({
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<div className="text-center py-12 text-slate-500">暂无容量数据</div>
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) : (
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<div className="space-y-4">
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{/* AI 深度解读结果（点击按钮后展示） */}
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{insight && (
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<div className="p-4 rounded-lg border border-purple-500/30 bg-purple-500/5">
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<div className="flex items-center gap-2 mb-2">
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<Sparkles className="h-4 w-4 text-purple-400" />
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<span className="text-sm font-medium text-purple-300">AI 深度解读</span>
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</div>
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<p className="text-sm text-slate-300 whitespace-pre-wrap break-words">{insight}</p>
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</div>
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)}
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{forecasts.map((forecast, idx) => (
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<div key={idx} className="p-4 rounded-lg border border-slate-700 bg-slate-800/50">
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<div className="flex items-center justify-between mb-3">
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@@ -319,3 +319,26 @@ export function trendColorClass(trend: string): string {
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return 'text-slate-400';
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}
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}
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/**
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* 构建容量预测「AI 深度解读」的 prompt —— 把硬数据序列化为结构化上下文喂给 LLM。 // Logan.Li
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* 纯函数，供 PredictiveCapacityTab 调 aiApi.chat 使用。无数据返回空串（调用方据此禁用按钮）。
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*/
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export function buildCapacityInsightPrompt(forecasts: CapacityForecast[]): string {
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if (forecasts.length === 0) return '';
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const lines = forecasts.map((f) => {
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const risk = f.daysUntilThreshold >= 999 ? '增长平缓，暂无触顶风险' : `${f.daysUntilThreshold} 天后触及阈值`;
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return `- ${f.resource}：当前 ${f.currentUsage}% → 7天后预测 ${f.predictedUsage}%（阈值 ${f.threshold}%），${risk}`;
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});
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return [
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'你是 AIOps 容量规划专家。基于以下服务器资源容量预测数据，给出综合风险评估与可执行的运维建议：',
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'',
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'【容量预测数据】',
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...lines,
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'',
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'要求：',
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'1. 指出最紧急的风险资源（触及阈值最快者优先）',
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'2. 给出针对性处置建议（扩容 / 清理 / 优化，具体到操作命令或步骤）',
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'3. 简洁中文，Markdown 无序列表，不超过 200 字',
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].join('\n');
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}
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