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]>
28 lines
954 B
TypeScript
28 lines
954 B
TypeScript
import BunSQLite from "@moduletrace/bun-sqlite";
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import { AppData } from "@/src/data/app-data";
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type Params = {
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job_id: number | string;
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/**
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* Unix ms before which the job can't be claimed again.
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*/
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until: number;
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};
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/**
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* Puts a claimed ingest job back to wait, giving back the attempt it
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* used: every embedding model was resting, so nothing was tried. Capped
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* at `AppData.HarnessMaxCooldownMs` from now.
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*/
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export default async function deferIngestJob({ job_id, until }: Params) {
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const now = Date.now();
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const at = Math.min(Math.max(until, now + AppData.HarnessCooldownMs), now + AppData.HarnessMaxCooldownMs);
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await BunSQLite.sql({
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sql: `UPDATE file_ingest_queue SET status = 'pending', locked_at = NULL, locked_by = NULL,
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attempts = MAX(attempts - 1, 0), available_at = ?, updated_at = ?
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WHERE id = ? AND status = 'processing'`,
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values: [at, now, job_id],
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});
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}
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