tbenandClaude Opus 5.5
e7b23b7454
Knowledgebases give bots RAG over documents, scoped like extensions: to particular bots, to a workspace, or to every bot, with their own button beside Tools in the composer. Documents are chunked and embedded by the file-ingest worker with the install's embedding model, which is now an install-wide setting rather than a per-bot one. - Word search runs on an FTS5 index ranked by BM25, with a scored LIKE fallback for scripts written without spaces. - Changing the embedding model re-indexes documents automatically. - Ingest jobs wait without spending attempts while every embedding model rests, fail at once on errors retrying can't fix, and keep passages searchable by words when the model refuses. - Settings > Knowledgebases shows each knowledgebase's and document's index state: spinner, warning, grey check (words only) or green check. Co-Authored-By: Claude Opus 5.5 <[email protected]>
22 lines
924 B
TypeScript
22 lines
924 B
TypeScript
import { describe, expect, test } from "bun:test";
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import knowledgebaseSummary from "./knowledgebase-summary";
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const empty = { document_count: 0, pending_count: 0, error_count: 0, stale_count: 0, size: 0 };
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describe("knowledgebaseSummary", () => {
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test("an empty knowledgebase says so", () => {
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expect(knowledgebaseSummary({ knowledgebase: empty })).toBe("No documents yet");
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});
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test("counts documents and names only the problems there are", () => {
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expect(knowledgebaseSummary({ knowledgebase: { ...empty, document_count: 1, size: 2048 } })).toBe(
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"1 document · 2.0 KB",
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);
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expect(
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knowledgebaseSummary({
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knowledgebase: { document_count: 3, pending_count: 1, error_count: 1, stale_count: 2, size: 2048 },
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}),
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).toBe("3 documents · 2.0 KB · 1 being read · 1 couldn't be read · 2 need re-indexing");
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});
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});
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