Glean sdk patterns
'Apply production-ready Glean API patterns with typed clients, batch indexing, pagination, and error handling.From its SKILL.md
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SKILL.md
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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: ${err.message}`);
}
}
Request Builder
class GleanSearchBuilder {
private body: Record<string, any> = {};
query(q: string) { this.body.query = q; return this; }
datasource(ds: string) { this.body.requestOptions = { datasourceFilter: ds }; return this; }
pageSize(n: number) { this.body.pageSize = Math.min(n, 100); return this; }
cursor(token: string) { this.body.cursor = token; return this; }
facets(fields: string[]) { this.body.facetFilters = fields; return this; }
build() { return this.body; }
}
// Usage: new GleanSearchBuilder().query('onboarding docs').datasource('confluence').pageSize(10).build();
Response Types
interface GleanDocument {
id: string; title: string; url: string;
body: { mimeType: string; textContent: string };
author?: { email: string }; updatedAt?: string;
}
interface GleanSearchResponse {
results: Array<{ document: GleanDocument; snippets: string[]; score: number }>;
totalResults: number; cursor?: string;
}
interface GleanDatasource { name: string; displayName: string; documentCount: number; lastCrawledAt: string; }
Testing Utilities
export function mockDocument(o: Partial<GleanDocument> = {}): GleanDocument {
return { id: 'doc-001', title: 'Onboarding Guide', url: 'https://wiki.example.com/onboarding',
body: { mimeType: 'text/plain', textContent: 'Welcome to the team...' },
author: { email: '[email protected]' }, updatedAt: '2025-03-01T00:00:00Z', ...o };
}
export function mockSearchResponse(n = 3): GleanSearchResponse {
return { results: Array.from({ length: n }, (_, i) => ({
document: mockDocument({ id: `doc-${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.
What ships with it
Read from the repository
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