AI 大模型接入 + 自动化测试（手动/AI/定时三种触发）
- 自动化测试核心（packages/core/src/testing.ts）：
- JSONPath 求值（$.a.b[0].c）、断言评估（状态码/耗时/Header/Body × 10 种操作）
- 变量提取（响应 → 当前环境，{{var}} 链式传值）、Markdown 报告导出
- 用例模型：场景用例 = 有序步骤（引用 HTTP 接口 + 断言 + 提取），失败后继续可选
- 执行器 testRunner + 定时调度器 scheduler（应用运行期间按间隔自动执行）
- TestingView：用例列表 / 步骤编排 / 断言与提取编辑器 / 报告（统计卡+断言明细+过滤+再次运行+导出）
- AI 助手：OpenAI 兼容客户端（DeepSeek/智谱/Kimi/OpenAI/Ollama 预设）
- 设置 → AI 助手：供应商 CRUD + 测试连接 + 当前使用切换
- AI 生成场景用例：读取集合接口清单 → 编排步骤/断言/提取 → 预览保存
- 入口：侧栏底部「自动化测试」+ ⋯ 菜单；文档新增 /docs/testing /docs/ai
- 新增 11 个引擎单测（总 48 前端用例全绿）；本地 E2E：运行通过+断言通过+petId 提取验证
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/**
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* AI 助手：OpenAI 兼容 Chat Completions 客户端 + 用例生成。
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* 供应商配置保存在工作区设置（本地 localStorage），不经任何第三方中转。
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*/
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import type {
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AiProvider,
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Collection,
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HttpRequestData,
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RequestNode,
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TestAssertion,
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TestCase,
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TestStep,
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} from "@opsxapi/core";
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import { newTestCase, suggestAssertions } from "@opsxapi/core";
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/** 常见供应商预设（均为 OpenAI 兼容协议） */
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export const AI_PROVIDER_PRESETS: { name: string; baseUrl: string; model: string; hint: string }[] = [
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{ name: "DeepSeek", baseUrl: "https://api.deepseek.com/v1", model: "deepseek-chat", hint: "性价比高，推荐" },
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{ name: "智谱 GLM", baseUrl: "https://open.bigmodel.cn/api/paas/v4", model: "glm-4-flash", hint: "新用户有免费额度" },
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{ name: "Moonshot Kimi", baseUrl: "https://api.moonshot.cn/v1", model: "moonshot-v1-8k", hint: "" },
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{ name: "OpenAI", baseUrl: "https://api.openai.com/v1", model: "gpt-4o-mini", hint: "" },
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{ name: "Ollama 本地", baseUrl: "http://127.0.0.1:11434/v1", model: "qwen2.5:7b", hint: "无需 API Key" },
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];
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export function newAiProvider(preset?: (typeof AI_PROVIDER_PRESETS)[number]): AiProvider {
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return {
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id: `ai-${Math.random().toString(36).slice(2, 10)}`,
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name: preset?.name ?? "自定义供应商",
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baseUrl: preset?.baseUrl ?? "",
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apiKey: "",
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model: preset?.model ?? "",
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enabled: true,
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};
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}
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type ChatMessage = { role: "system" | "user" | "assistant"; content: string };
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/** 调用 Chat Completions（非流式），失败抛 Error */
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export async function chatComplete(provider: AiProvider, messages: ChatMessage[], timeoutMs = 60000): Promise<string> {
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if (!provider.baseUrl.trim()) throw new Error("未配置 Base URL");
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const url = `${provider.baseUrl.trim().replace(/\/+$/, "")}/chat/completions`;
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const ctrl = new AbortController();
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const timer = setTimeout(() => ctrl.abort(), timeoutMs);
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try {
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const res = await fetch(url, {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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...(provider.apiKey.trim() ? { Authorization: `Bearer ${provider.apiKey.trim()}` } : {}),
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},
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body: JSON.stringify({
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model: provider.model.trim() || "gpt-4o-mini",
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messages,
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temperature: 0.2,
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stream: false,
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}),
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signal: ctrl.signal,
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});
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if (!res.ok) {
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const text = await res.text().catch(() => "");
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throw new Error(`HTTP ${res.status}${text ? `：${text.slice(0, 200)}` : ""}`);
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}
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const data = (await res.json()) as {
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choices?: { message?: { content?: string } }[];
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};
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const content = data.choices?.[0]?.message?.content;
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if (!content) throw new Error("模型未返回内容");
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return content;
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} catch (e) {
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if (e instanceof DOMException && e.name === "AbortError") throw new Error("请求超时");
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throw e instanceof Error ? e : new Error(String(e));
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}
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}
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/** 连接测试：问一句并要求简答 */
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export async function testProviderConnection(provider: AiProvider): Promise<string> {
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const reply = await chatComplete(
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provider,
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[
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{ role: "system", content: "你是连通性测试助手，只输出：OK" },
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{ role: "user", content: "ping" },
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],
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20000,
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);
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return reply.trim().slice(0, 60) || "OK";
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}
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/* ---------------- AI 生成场景用例 ---------------- */
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/** 汇总集合中的 HTTP 接口给模型看 */
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function summarizeNodes(nodes: { node: RequestNode; path: string }[]): string {
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return nodes
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.map(({ node, path }) => {
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if (node.kind !== "http") return null;
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const d = node.data as HttpRequestData;
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const lines = [
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`- id: ${node.id} | ${d.method} ${d.url} | 名称: ${node.name}${path ? ` | 目录: ${path}` : ""}`,
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];
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if (d.bodyMode === "json" && d.bodyRaw.trim()) {
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lines.push(` body 示例: ${d.bodyRaw.replace(/\s+/g, " ").slice(0, 160)}`);
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}
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return lines.join("\n");
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})
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.filter(Boolean)
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.join("\n");
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}
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const GEN_SYSTEM_PROMPT = `你是 API 自动化测试专家。根据给定的接口清单设计一个可执行的"场景用例"（按业务顺序编排多个接口步骤）。
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只输出一个 JSON 代码块（\`\`\`json ... \`\`\`），不要输出其他解释文字。JSON 结构：
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{
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"name": "用例名称（中文，简短）",
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"description": "一句话说明场景",
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"steps": [
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{
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"nodeId": "必须使用清单中的接口 id",
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"reason": "为什么这一步",
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"assertions": [
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{ "target": "status|timeMs|header|body", "locator": "header名或JSONPath（其余为空）", "op": "eq|neq|lt|gt|contains|not_contains|exists|not_exists|jsonpath_eq|jsonpath_contains", "expected": "期望值" }
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],
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"extracts": [ { "jsonpath": "$.data.id", "varName": "petId" } ]
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}
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]
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}
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要求：步骤顺序符合业务依赖（如 先创建 → 再查询 → 再删除）；每步至少 1 条断言；跨步骤传值用 extracts 提取变量并在后续 URL/Body 用 {{变量名}}（如果原接口里已有 {{xxx}} 占位则沿用）；断言 4-8 条为宜，聚焦关键业务字段。`;
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export type AiCaseDraft = { name: string; description?: string; steps: TestStep[]; notes: string[] };
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/** 从模型回复中提取 JSON（容错：代码块 / 首尾杂文） */
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export function extractJsonBlock(text: string): unknown {
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const fenced = /```(?:json)?\s*([\s\S]*?)```/.exec(text);
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const raw = fenced ? fenced[1] : text.slice(text.indexOf("{"), text.lastIndexOf("}") + 1);
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return JSON.parse(raw.trim());
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}
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export async function aiGenerateTestCase(
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provider: AiProvider,
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collection: Collection,
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instruction?: string,
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): Promise<AiCaseDraft> {
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const nodes: { node: RequestNode; path: string }[] = [];
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const walk = (children: Collection["children"], path: string): void => {
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for (const n of children) {
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if (n.type === "folder") walk(n.children, path ? `${path}/${n.name}` : n.name);
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else if (n.kind === "http") nodes.push({ node: n, path });
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}
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};
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walk(collection.children, "");
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if (nodes.length === 0) throw new Error("集合中没有 HTTP 接口可供编排");
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const user = [
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`接口清单（共 ${nodes.length} 个）：`,
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summarizeNodes(nodes),
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instruction?.trim() ? `\n用户要求：${instruction.trim()}` : "",
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"\n请输出场景用例 JSON。",
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]
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.filter(Boolean)
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.join("\n");
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const reply = await chatComplete(provider, [
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{ role: "system", content: GEN_SYSTEM_PROMPT },
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{ role: "user", content: user },
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]);
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const parsed = extractJsonBlock(reply) as {
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name?: string;
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description?: string;
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steps?: {
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nodeId?: string;
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reason?: string;
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assertions?: { target?: string; locator?: string; op?: string; expected?: string }[];
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extracts?: { jsonpath?: string; varName?: string }[];
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}[];
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};
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const notes: string[] = [];
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const steps: TestStep[] = [];
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const validIds = new Set(nodes.map((n) => n.node.id));
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const nodeById = new Map(nodes.map((n) => [n.node.id, n.node]));
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for (const s of parsed.steps ?? []) {
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if (!s.nodeId) continue;
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if (!validIds.has(s.nodeId)) {
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notes.push(`已跳过未知接口：${s.nodeId}`);
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continue;
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}
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const node = nodeById.get(s.nodeId)!;
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const assertions: TestAssertion[] = (s.assertions ?? []).map((a) => ({
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id: `as-${Math.random().toString(36).slice(2, 10)}`,
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enabled: true,
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target: (["status", "timeMs", "header", "body"].includes(a.target ?? "") ? a.target : "status") as TestAssertion["target"],
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locator: a.locator ?? "",
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op: ([
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"eq", "neq", "lt", "gt", "contains", "not_contains", "exists", "not_exists", "jsonpath_eq", "jsonpath_contains",
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].includes(a.op ?? "") ? a.op : "eq") as TestAssertion["op"],
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expected: a.expected ?? "",
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}));
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if (assertions.length === 0) {
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assertions.push(...suggestAssertions(node.data as HttpRequestData));
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if (s.reason) notes.push(`「${node.name}」未给断言，已补默认断言`);
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}
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steps.push({
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id: `st-${Math.random().toString(36).slice(2, 10)}`,
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enabled: true,
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nodeId: s.nodeId,
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assertions,
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extracts: (s.extracts ?? [])
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.filter((e) => e.jsonpath && e.varName)
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.map((e) => ({ id: `ex-${Math.random().toString(36).slice(2, 10)}`, jsonpath: e.jsonpath!, varName: e.varName! })),
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});
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}
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if (steps.length === 0) throw new Error("模型未生成有效步骤，请重试或补充要求");
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return {
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name: parsed.name?.trim() || `${collection.name} · AI 用例`,
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description: parsed.description?.trim(),
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steps,
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notes,
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};
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}
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/** 把 AI 草稿转成正式用例 */
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export function draftToTestCase(draft: AiCaseDraft): TestCase {
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const tc = newTestCase(draft.name);
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tc.description = draft.description;
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tc.steps = draft.steps;
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return tc;
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}
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