技能 编程开发 Glean SDK 最佳实践指南

Glean SDK 最佳实践指南

v20260423
glean-sdk-patterns
本模块提供了针对Glean企业搜索平台的生产级SDK模式。它包含了类型化的客户端,用于实现搜索和文档索引功能。核心最佳实践包括单例模式、批量分页处理、健壮的错误处理(如重试机制),以及提供了一个流畅的请求构建器,确保API调用稳定可靠。
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概览

Glean SDK Patterns

Overview

Production-ready patterns for the Glean enterprise search platform. Glean uses POST-based REST endpoints for both search and indexing. Search queries go to the Client API while document ingestion uses the Indexing API. A structured client centralizes token management, enforces batch pagination for bulk indexing, and provides typed responses for search results.

Singleton Client

let _client: GleanClient | null = null;
export function getClient(): GleanClient {
  if (!_client) {
    const domain = process.env.GLEAN_DOMAIN, key = process.env.GLEAN_API_KEY;
    if (!domain || !key) throw new Error('GLEAN_DOMAIN and GLEAN_API_KEY must be set');
    _client = new GleanClient(domain, key);
  }
  return _client;
}
class GleanClient {
  private base: string; private h: Record<string, string>;
  constructor(domain: string, key: string) {
    this.base = `https://${domain}/api`;
    this.h = { 'Authorization': `Bearer ${key}`, 'Content-Type': 'application/json' };
  }
  async search(query: string, opts: { pageSize?: number; datasource?: string } = {}) {
    const r = await fetch(`${this.base}/client/v1/search`, { method: 'POST',
      headers: { ...this.h, 'X-Glean-Auth-Type': 'BEARER' },
      body: JSON.stringify({ query, pageSize: opts.pageSize ?? 20,
        requestOptions: opts.datasource ? { datasourceFilter: opts.datasource } : undefined }) });
    if (!r.ok) throw new GleanError(r.status, await r.text()); return r.json() as Promise<GleanSearchResponse>;
  }
  async indexDocuments(datasource: string, docs: GleanDocument[]): Promise<void> {
    const r = await fetch(`${this.base}/index/v1/indexdocuments`, {
      method: 'POST', headers: this.h, body: JSON.stringify({ datasource, documents: docs }) });
    if (!r.ok) throw new GleanError(r.status, await r.text());
  }
  async bulkIndex(ds: string, docs: GleanDocument[], batch = 100): Promise<void> {
    for (let i = 0; i < docs.length; i += batch) await this.indexDocuments(ds, docs.slice(i, i + batch));
  }
}

Error Wrapper

export class GleanError extends Error {
  constructor(public status: number, message: string) { super(message); this.name = 'GleanError'; }
}
export async function safeCall<T>(operation: string, fn: () => Promise<T>): Promise<T> {
  try { return await fn(); }
  catch (err: any) {
    if (err instanceof GleanError && err.status === 429) { await new Promise(r => setTimeout(r, 3000)); return fn(); }
    if (err instanceof GleanError && err.status === 401) throw new GleanError(401, 'Invalid GLEAN_API_KEY');
    throw new GleanError(err.status ?? 0, `${operation} failed: ${err.message}`);
  }
}

Request Builder

class GleanSearchBuilder {
  private body: Record<string, any> = {};
  query(q: string) { this.body.query = q; return this; }
  datasource(ds: string) { this.body.requestOptions = { datasourceFilter: ds }; return this; }
  pageSize(n: number) { this.body.pageSize = Math.min(n, 100); return this; }
  cursor(token: string) { this.body.cursor = token; return this; }
  facets(fields: string[]) { this.body.facetFilters = fields; return this; }
  build() { return this.body; }
}
// Usage: new GleanSearchBuilder().query('onboarding docs').datasource('confluence').pageSize(10).build();

Response Types

interface GleanDocument {
  id: string; title: string; url: string;
  body: { mimeType: string; textContent: string };
  author?: { email: string }; updatedAt?: string;
}
interface GleanSearchResponse {
  results: Array<{ document: GleanDocument; snippets: string[]; score: number }>;
  totalResults: number; cursor?: string;
}
interface GleanDatasource { name: string; displayName: string; documentCount: number; lastCrawledAt: string; }

Testing Utilities

export function mockDocument(o: Partial<GleanDocument> = {}): GleanDocument {
  return { id: 'doc-001', title: 'Onboarding Guide', url: 'https://wiki.example.com/onboarding',
    body: { mimeType: 'text/plain', textContent: 'Welcome to the team...' },
    author: { email: 'hr@example.com' }, updatedAt: '2025-03-01T00:00:00Z', ...o };
}
export function mockSearchResponse(n = 3): GleanSearchResponse {
  return { results: Array.from({ length: n }, (_, i) => ({
    document: mockDocument({ id: `doc-${i}` }), snippets: ['...match...'], score: 0.95 - i * 0.1 })), totalResults: n };
}

Error Handling

Pattern When to Use Example
safeCall wrapper All search and index calls Structured error with operation context
Retry on 429 Bulk indexing pipelines 3s delay before retry
Batch pagination Indexing > 100 documents bulkIndex with batch tracking
Auth validation Client init Fail fast on missing GLEAN_API_KEY

Resources

Next Steps

Apply patterns in glean-core-workflow-a.

信息
Category 编程开发
Name glean-sdk-patterns
版本 v20260423
大小 5.23KB
更新时间 2026-04-26
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