KB injection tuning: pgvector substrate + retrieval telemetry + title-first auto-inject #74

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bvandeusen merged 4 commits from dev into main 2026-06-22 20:56:15 -04:00

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+1037 -32

4 Commits

Author	SHA1	Message	Date
bvandeusenandClaude Opus 4.8	eec241d3c0	feat(plugin): sharpen the recall-before-acting reflex in static context ... Turn the SessionStart static guidance into a concrete recall trigger — search Scribe before answering about the operator projects/people/places/decisions or starting a task, and pass the active project id to scope results — instead of a vague "search for related work". Step 4 (pull-path sharpening); the cross-encoder rerank half is deferred until auto_inject telemetry shows precision is the bottleneck. Scribe: project 2, milestone 93, task 1034. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Xz4j1H7pjYSjKsEpgcNH5E	2026-06-22 20:39:54 -04:00
bvandeusenandClaude Opus 4.8	8126db3203	feat(plugin): knowledge auto-inject (Path A) — title-first per-turn awareness ... New UserPromptSubmit hook (scribe_autoinject.sh) + GET /api/plugin/retrieve that surface the TITLES (never bodies) of the few notes clearing four anti-bloat gates: a per-user confidence threshold (stricter than pull search), a margin gate, per-session dedup (exclude_ids), and a top-k ceiling. Each retrieval is logged to retrieval_logs as source=auto_inject so the threshold can be tuned from data. Per-user config (enable / threshold / top-k) is DB-backed via /api/settings with a Settings UI card; defaults enabled, threshold 0.55, top-k 3 (conservative — tune once auto_inject telemetry accrues). Scribe: project 2, milestone 93, task 1033. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Xz4j1H7pjYSjKsEpgcNH5E	2026-06-22 20:31:07 -04:00
bvandeusenandClaude Opus 4.8	807f478cac	feat(search): retrieval telemetry — log every semantic retrieval ... Add retrieval_logs (migration 0068) + services/retrieval_telemetry with a fire-and-forget record_retrieval(), wired into the MCP search tool (source=mcp_search) and the REST search route (source=rest_search). Captures query, effective params, and the per-result score distribution so KB-injection thresholds can be tuned from data rather than guessed. Scribe: project 2, milestone 93, task 1032. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Xz4j1H7pjYSjKsEpgcNH5E	2026-06-22 20:10:15 -04:00
bvandeusenandClaude Opus 4.8	513019786e	feat(search): pgvector substrate — vector(384) + HNSW for semantic search ... Move semantic_search_notes off the full-table Python cosine scan onto a native pgvector column: indexed ORDER BY embedding <=> :q LIMIT k (HNSW, cosine). Migration 0067 enables the extension, converts the JSONB embedding column to vector(384) (stale-dim rows dropped and regenerated by the startup backfill), and builds the HNSW cosine index. Postgres image moves postgres:16-alpine -> pgvector/pgvector:pg17 across prod, quickstart, and CI. Scribe: project 2, milestone 93, task 1031. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Xz4j1H7pjYSjKsEpgcNH5E	2026-06-22 20:10:15 -04:00