fix(workspace-search): repair wedged search indexing - #712
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Migrate the delete queue to add the `attempts` column when it predates the schema, and retry transient Workers AI embedding errors in-process. The delete queue survives version resets, so `CREATE TABLE IF NOT EXISTS` never adds `attempts` to an object whose table was created earlier. flushVectorDeletes is the first statement in processBatch and queries `WHERE attempts < ...`, so an affected object throws "no such column: attempts" on every alarm tick and never indexes anything. Add a pragma-guarded ALTER TABLE. Also wrap ai.run in bounded retry with backoff for retryable AiErrors (3xxx internal and 5xx-class upstream) so a transient hiccup like 3043 no longer burns an index attempt or opens an error-tracking issue. Generated-By: PostHog Code Task-Id: 6c0075cb-ea15-438c-8391-1a37c875860b
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React Doctor found 1 new issue in 1 file · 1 warning · score 92 / 100 (Great) · 1 fixed · vs 1 warning
Reviewed by React Doctor for commit |
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| const output = await runEmbeddingWithRetry(ai, batch, options); |
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React Doctor · react-doctor/async-await-in-loop (warning)
This makes the for…of loop slow because each await runs one after another, so collect the independent calls & run them together with await Promise.all(items.map(...))
Fix → Collect the items, then use await Promise.all(items.map(...)) so independent work runs at the same time
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Problem
kernel_search_vector_deletesis created withCREATE TABLE IF NOT EXISTSoutside the version-reset drop set, because its rows reference vectors still live in Vectorize and must survive resets. A Durable Object whose table was created by an earlier iteration of the schema never gains theattemptscolumn —IF NOT EXISTSis a no-op and the reset never touches it.flushVectorDeletesis the first statement inWorkspaceSearchIndexer.processBatchand queriesWHERE attempts < …, so an affected object throwsSqlError: no such column: attemptson every alarm tick and dies before indexing a single item — forever, with no self-healing path.embedWorkspaceSearchTextscallsai.run("@cf/baai/bge-m3", …)with no retry, so a single transientAiError: 3043burns one of the five index attempts and opens a fresh error-tracking issue.Changes
initializeWorkspaceSearchStorage:PRAGMA table_infocheck, thenALTER TABLE kernel_search_vector_deletes ADD COLUMN attempts INTEGER NOT NULL DEFAULT 0when absent. Chosen over moving the table into the reset drop set — a drop would discard queued deletes and orphan their vectors in Vectorize.ai.run: retryableAiErrors (3xxx internal, 5xx-class upstream) are retried in-process (4 attempts, exponential backoff capped at 2s); permanent client/validation codes fail fast. A transient hiccup no longer consumes an index attempt or pages anyone.Note
Failed items are already visible via the lexical fallback —
searchKeywordincludesvector_status = 'failed'andgetStatusreportspartial— so exhausted items keep surfacing in keyword results rather than vanishing.Tests
workspace-search-embeddings.test.ts: retryable-vs-permanent classification, retry-then-succeed, attempt-budget exhaustion, and fail-fast on permanent errors.Why
Restore a brand-new flagship surface (hybrid workspace search) that is silently, permanently broken for any affected workspace, with no client-visible error and no recovery short of a code fix.
Created with PostHog Desktop from this inbox report.
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