mirror of
https://github.com/garrytan/gbrain.git
synced 2026-07-30 11:22:34 +00:00
b44a31cc0defe418b2ea9ec2d4cfcf5658d9c8a9
3
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
|
699db50a3d |
fix(extract+migrate): kill N+1 hang + v0.12.0 migration timeout (v0.12.1) (#198)
* feat(engine): add addLinksBatch + addTimelineEntriesBatch via unnest()
Multi-row INSERT...SELECT FROM unnest() JOIN pages ON CONFLICT DO NOTHING
RETURNING 1. 4 array-typed bound parameters (links) or 5 (timeline)
regardless of batch size, sidesteps Postgres's 65535-parameter cap.
Returns count of rows actually inserted (excluding ON CONFLICT no-ops
and JOIN-dropped rows whose slugs don't exist).
Per-row addLink / addTimelineEntry signatures and SQL behavior unchanged.
All 10 existing call sites compile and behave identically.
Tests: 11 PGLite cases (empty batch, missing optionals, within-batch dedup,
JOIN drops missing slug, half-existing batch, batch of 100) + 9 E2E
postgres-engine cases against real Postgres+pgvector.
* fix(migrate): pre-create btree helper in v8 + v9 dedup; bump phaseASchema timeout
Production bug: v0.12.0 schema migration timed out at Supabase Management API's
60s ceiling on brains with 80K+ duplicate timeline rows. The DELETE...USING
self-join was O(n²) without an index on the dedup columns.
Fix: pre-create idx_links_dedup_helper / idx_timeline_dedup_helper on the
dedup columns BEFORE the DELETE, drop after. Turns O(n²) into O(n log n).
On 80K+ rows the migration completes in <1s instead of timing out.
Also bumps the v0.12.0 orchestrator's phaseASchema timeout 60s -> 600s as
belt-and-suspenders for unforeseen slowness.
Exports MIGRATIONS for structural test assertions.
Tests: 2 structural assertions (helper-index DDL must appear in v8/v9 SQL
in the right order — catches regression even at 0-row scale) + 2 behavioral
regression tests (1000-row dedup completes <5s).
* perf(extract): kill N+1 dedup pre-load; switch to batched writes
Production bug: gbrain extract hung 10+ minutes producing zero output on
47K-page brains. The pre-load loop called engine.getLinks(slug) (or
getTimeline) once per page across engine.listPages({limit: 100000}) — 47K
serial round-trips over the Supabase pooler before the first file was read.
Both engines already enforced uniqueness at the SQL layer
(UNIQUE(from, to, link_type) on links, idx_timeline_dedup on timeline_entries).
The in-memory dedup Set was redundant insurance that became the bottleneck.
Fix: delete the pre-load entirely. Buffer 100 candidates per file walk,
flush via engine.addLinksBatch / engine.addTimelineEntriesBatch. ~99% fewer
DB round-trips per re-extract.
Also fixes counter accuracy: 'created' now counts rows actually inserted
(via batch RETURNING 1 row count). Re-run on a fully-extracted brain
prints 'Done: 0 links' instead of lying.
Dry-run mode keeps a per-run dedup Set so duplicate candidates from N
markdown files print exactly once, not N times.
Batch errors are visible in BOTH json and human modes — silent loss of
100 rows is worse than per-row error visibility.
Tests: extract-fs.test.ts (idempotency + truthful counter + dry-run dedup
+ perf regression guard <2s).
* chore: bump version + changelog (v0.12.1)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* docs: update CLAUDE.md for v0.12.1 (batch engine API, test counts)
Reflect what shipped in v0.12.1:
- New engine methods addLinksBatch + addTimelineEntriesBatch (PGLite via
unnest() + manual $N, postgres-engine via INSERT...SELECT FROM
unnest($1::text[], ...) JOIN pages ON CONFLICT DO NOTHING).
- extract.ts no longer pre-loads dedup set; candidates are buffered 100
at a time and flushed via the new batch methods.
- v0.12.0 orchestrator phaseASchema timeout bumped 60s to 600s.
- Test counts 1297 unit / 105 E2E to 1412 unit / 119 E2E.
- New test/extract-fs.test.ts covers the N+1 regression guard.
- BrainEngine method count 37/38 to 40.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
|
||
|
|
81b3f7afac |
feat: knowledge graph layer — auto-link, typed relationships, graph-query (v0.10.3) (#188)
* feat(schema): graph layer migrations v5/v6/v7 + GraphPath/health types
Schema foundation for v0.10.3 knowledge graph layer:
- v5: links UNIQUE constraint widened to (from, to, link_type) so the same
person can both works_at AND advises the same company as separate rows.
Idempotent for fresh + upgrade (drops both old constraint names first).
- v6: timeline_entries gets UNIQUE index on (page_id, date, summary) for
ON CONFLICT DO NOTHING idempotency at DB level.
- v7: drops trg_timeline_search_vector trigger. Structured timeline entries
are now graph data, not search text. Markdown timeline still feeds search
via the pages trigger. Side benefit: extraction pagination is no longer
self-invalidating (trigger used to bump pages.updated_at on every insert).
Types: new GraphPath (edge-based traversal result), PageFilters.updated_after,
BrainHealth gets link_coverage / timeline_coverage / most_connected. Postgres
schema regenerated via build:schema.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(graph): auto-link on put_page + extract --source db + security hardening
Core graph layer wired into the operation surface:
- New src/core/link-extraction.ts: extractEntityRefs (canonical extractor used
by both backlinks.ts and the new graph code), extractPageLinks (combines
markdown refs + bare-slug scan + frontmatter source, dedups within-page),
inferLinkType (deterministic regex heuristics for attended/works_at/
invested_in/founded/advises/source/mentions), parseTimelineEntries (parses
multiple date format variants from page content), isAutoLinkEnabled
(engine config flag, defaults true, accepts false/0/no/off case-insensitive).
- put_page operation auto-link post-hook: extracts entity refs from freshly
written content, reconciles links table (adds new, removes stale). Returns
auto_links: { created, removed, errors } in response so MCP callers see
outcomes. Runs in a transaction so concurrent put_page on same slug can't
race the reconciliation. Default on; opt out with auto_link=false config.
- traverse_graph operation extended with link_type and direction params.
Returns GraphPath[] (edges) when filters set, GraphNode[] (nodes) for
backwards compat. Depth hard-capped at TRAVERSE_DEPTH_CAP=10 for remote
callers; without this, depth=1e6 from MCP burns memory on the recursive CTE.
- gbrain extract <links|timeline|all> --source db: walks pages from the
engine instead of from disk. Works for live brains with no local checkout
(MCP-driven Wintermute / OpenClaw). Filesystem mode (--source fs) is
unchanged. New --type and --since filters with date validation upfront
(invalid --since used to silently no-op the filter and reprocess everything).
- Security: auto-link skipped for ctx.remote=true (MCP). Bare-slug regex
matches `people/X` anywhere in page text including code fences and quoted
strings. Without this gate an untrusted MCP caller could plant arbitrary
outbound links by writing pages with intentional slug references; combined
with the new backlink boost, attacker-placed targets would surface higher
in search.
- Postgres orphan_pages aligned to PGLite definition (no inbound AND no
outbound). Comment used to claim alignment but code disagreed; engines
drifted silently when users migrated.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(cli): graph-query command + skill updates + v0.10.3 migration file
Agent-facing surface for the graph layer:
- New `gbrain graph-query <slug>` command with --type, --depth, --direction
in|out|both. Maps to traverse_graph operation with the new filters. Renders
the result as an indented edge tree.
- skills/migrations/v0.10.3.md: agent runs this post-upgrade to discover the
graph layer. Tells the agent to run `gbrain extract links --source db`,
then timeline, verify with stats, try graph-query, and lists the inferred
link types so they can be used in subsequent traversals.
- skills/brain-ops/SKILL.md Phase 2.5: documents that put_page now auto-links.
No more manual add_link calls in the Iron Law back-linking path.
- skills/maintain/SKILL.md: graph population phase. Shows the right command
to backfill links + timeline from existing pages.
- cli.ts: register graph-query in CLI_ONLY + handleCliOnly switch. Update help
text to describe `gbrain extract --source fs|db` and the new graph-query.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* test(graph): unit + e2e + 80-page A/B/C benchmark for graph layer
Coverage for the v0.10.3 graph layer (260+ new test assertions):
- test/link-extraction.test.ts (46 tests): extractEntityRefs both formats,
extractPageLinks dedup + frontmatter source, inferLinkType heuristics
(meeting/CEO/invested/founded/advises/default), parseTimelineEntries
multiple date formats + invalid date rejection, isAutoLinkEnabled
case-insensitive truthy/falsy parsing.
- test/extract-db.test.ts (12 tests): `gbrain extract <links|timeline|all>
--source db` happy paths, --type filter, --dry-run JSON output,
idempotency via DB constraint, type inference from CEO context.
- test/graph-query.test.ts (5 tests): direction in/out/both, type filter,
non-existent slug, indented tree output.
- test/pglite-engine.test.ts (+26 tests): getAllSlugs, listPages
updated_after filter, multi-type links via v5 migration, removeLink with
and without linkType, addTimelineEntry skipExistenceCheck flag,
getBacklinkCounts for hybrid search boost, traversePaths in/out/both with
cycle prevention via visited array, getHealth graph metrics
(link_coverage / timeline_coverage / most_connected).
- test/e2e/graph-quality.test.ts (6 tests): full pipeline against PGLite
in-memory. Auto-link via put_page operation handler. Reconciliation
removes stale links on edit. auto_link=false config skip.
- test/benchmark-graph-quality.ts: A/B/C comparison on 80 fictional pages,
35 queries across 7 categories. Hard thresholds: link_recall > 90%,
link_precision > 95%, timeline_recall > 85%, type_accuracy > 80%,
relational_recall > 80%. Currently passing all 9.
Built test-first: benchmark caught WORKS_AT_RE matching "founder" inside
slug names (frank-founder), "worked at" past-tense missing from regex,
PGLite Date object vs ISO string comparison bug. All fixed before merge.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* chore: bump version and changelog (v0.10.3)
CHANGELOG: knowledge graph layer headline. Auto-link on every page write.
Typed relationships (works_at, attended, invested_in, founded, advises).
gbrain extract --source db. graph-query CLI. Backlink boost in hybrid search.
Schema migrations v5/v6/v7 applied automatically.
Security hardening caught during /ship adversarial review: traverse_graph
depth capped at 10 from MCP, auto-link skipped for ctx.remote=true, runAutoLink
reconciliation in transaction, --since validates dates upfront.
TODOS.md: 2 P2 follow-ups (auto-link redundant SQL on skipped writes;
extract --source db not gated on auto_link config).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* docs: sync CLAUDE.md with v0.10.3 graph layer
Updated key files list (extract.ts now describes --source fs|db, added
graph-query.ts and link-extraction.ts), test inventory (extract-db,
link-extraction, graph-query unit tests; e2e/graph-quality), and
test count (51 unit + 7 e2e, 1151 + 105 assertions).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* docs(v0.10.3): wire graph layer into install flow + README + benchmark
Existing brains upgrading to v0.10.3 had no clear path to backfill the new
links/timeline tables. New installs had no instruction to run extract --source db
after import. This wires the knowledge graph into every install touchpoint so the
v0.10.3 features actually reach the user.
- README: headline now sells self-wiring graph + 94% benchmark numbers; new
Knowledge Graph section between Knowledge Model and Search; LINKS+GRAPH command
block expanded; Benchmarks docs group added
- INSTALL_FOR_AGENTS.md: new Step 4.5 (graph backfill) + Upgrade section now runs
gbrain init + post-upgrade and points to migrations/v<N>.md
- skills/setup/SKILL.md Phase C: new step 5 for graph backfill (idempotent,
skip-if-empty); existing file migration becomes step 6
- src/commands/init.ts: post-init hint detects existing brain (page_count > 0)
and prints extract commands for both PGLite and Postgres engines
- docs/GBRAIN_VERIFY.md: new Check #7 (knowledge graph wired) with backfill
fallback + graph-query smoke test
- docs/benchmarks/2026-04-18-graph-quality.md: checked-in benchmark report
matching the existing search-quality format (94% recall, 100% precision,
100% relational recall, idempotent both ways)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* docs(claude): require PR descriptions to cover the whole branch
Adds a rule to CLAUDE.md so future PR bodies always cover the full diff
against the base branch, not just the most recent commit. Includes the
git log + gh pr view incantation to check what's actually in a PR.
This is a reaction to PR #189 being created with a body that described
only the last commit instead of the 7 commits it actually contained.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* feat(upgrade): post-upgrade prints full body + --execute mode + downstream skill upgrade doc
PR #188 review caught two install-flow gaps that this commit closes:
1. `gbrain post-upgrade` only printed the migration headline + description
from YAML frontmatter, never the markdown body that contains the
step-by-step backfill instructions. Agents saw "Knowledge graph layer —
your brain now wires itself" and had no idea to run `gbrain extract
links --source db`. Now prints the full body after the headline.
2. New `--execute` flag reads a structured `auto_execute:` list from
migration frontmatter and runs the safe commands sequentially. Without
`--yes` it prints the plan only (preview mode). With `--yes` it actually
runs them. Stops on first failure with a clear error.
3. Downstream agents (Wintermute etc.) keep local skill forks that gbrain
can't push updates to. New `docs/UPGRADING_DOWNSTREAM_AGENTS.md` lists
the exact diffs each release needs applied to those forks. v0.10.3
diffs for brain-ops, meeting-ingestion, signal-detector, enrich.
Changes:
- src/commands/upgrade.ts:
- runPostUpgrade(args) accepts flags
- Prints full body via extractBody()
- Parses auto_execute: list via extractAutoExecute() (hand-rolled, no yaml dep)
- --execute previews, --execute --yes runs
- Fix cosmetic bug: `recipe: null` no longer prints "show null" message
- src/cli.ts: pass args to runPostUpgrade
- skills/migrations/v0.10.3.md:
- Add auto_execute: list (gbrain init + extract links/timeline + stats)
- Fix typo: completion record version was 0.10.1, now 0.10.3
- test/upgrade.test.ts: 5 new tests covering body printing, plan preview,
actual execution, no-auto_execute case, and --help output
- docs/UPGRADING_DOWNSTREAM_AGENTS.md: NEW
- CLAUDE.md: key files list updated
Test: 13 upgrade tests pass (was 8, +5 new). Full unit suite: 1078 pass,
zero regressions, 32 expected E2E skips (no DATABASE_URL).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* bench(graph): add Configuration A baseline (no graph) vs C comparison
Previous benchmark showed C numbers only (94.4% link recall, 100% relational
recall, etc.) but never quantified what a pre-v0.10.3 brain actually loses.
Reviewer caught this gap.
Adds measureBaselineRelational() that simulates a no-graph fallback:
- Outgoing queries: regex-extract entity refs from the seed page content
- Incoming queries: grep-style scan of all pages for the seed slug
This is what an agent without the structured links table can do today.
Honest result on the 5 relational queries in the benchmark:
- Recall: 100% A vs 100% C (+0%) — markdown contains the refs either way
- Precision: 58.8% A vs 100.0% C (+70%) — without typed links, you get the
right answers buried in 41% noise
Per-query breakdown shows the divergence is concentrated in INCOMING queries:
"Who works at startup-0?" returns 5 candidates without graph (2 employees +
3 noise pages that mention startup-0) vs exactly 2 with graph. For an LLM
agent, that's ~3x less reading work per relational question.
Also documented what the benchmark deliberately doesn't test (multi-hop,
search ranking with backlink boost, aggregate queries, type-disagreement
queries) so future benchmark work has a roadmap.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
* bench(graph): add 4 missing categories — multi-hop, aggregate, type-disagreement, ranking
The previous benchmark commit (
|
||
|
|
6c7d2ed30b |
feat: PGLite engine — local brain, zero infrastructure (v0.7.0) (#41)
* refactor: extract shared utils, add runMigration + getChunksWithEmbeddings to BrainEngine Extract validateSlug, contentHash, rowToPage, rowToChunk, rowToSearchResult from postgres-engine.ts into shared utils.ts. Add rowToChunk includeEmbedding parameter for migration support. Add two new methods to BrainEngine interface: - runMigration(version, sql) — replaces internal eng.sql access in migrate.ts - getChunksWithEmbeddings(slug) — returns chunks with embedding data for migration Replace 'sqlite' with 'pglite' in EngineConfig and GBrainConfig types. Fix loadConfig to infer engine from database_path. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: pluggable engine factory + hybridSearch keyword-only fallback Add createEngine() factory with dynamic imports so PGLite WASM is never loaded for Postgres users. Wire CLI to use factory instead of hardcoded PostgresEngine. Force workers=1 for PGLite imports (single-connection architecture). Fix hybridSearch to check OPENAI_API_KEY before calling embed(). When unset, returns keyword-only results instead of throwing. Critical for local PGLite users who don't need vector search. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: PGLiteEngine — embedded Postgres 17.5 via WASM, same SQL everywhere Full BrainEngine implementation (37 methods) using @electric-sql/pglite. Same SQL as PostgresEngine — tsvector triggers, pgvector HNSW, pg_trgm fuzzy matching, recursive CTEs, JSONB. Only the driver call syntax differs (parameterized queries instead of tagged templates). PGLite schema is the Postgres schema minus RLS, advisory locks, and remote auth tables (access_tokens, mcp_request_log, files). No server. No subscription. One directory. Works offline. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * feat: smart init (PGLite default) + bidirectional engine migration gbrain init now defaults to PGLite — brain ready in 2 seconds, no server needed. Scans target directory: <1000 .md files = PGLite, >=1000 = suggests Supabase. --supabase and --pglite flags override. gbrain migrate --to supabase/pglite transfers all data between engines with manifest-based resume. Copies pages, chunks (with embeddings), tags, timeline, raw data, links, and config. --force overwrites non-empty target. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * test: 60 new tests for PGLite engine, utils, and factory 41 PGLite engine tests covering all 37 BrainEngine methods: CRUD, tsvector keyword search, pg_trgm fuzzy matching, chunk upsert with COALESCE, graph traversal via recursive CTE, transactions, cascade deletes, stats/health, and embedding round-trip. 14 shared utility tests (validateSlug, contentHash, row mappers). 5 engine factory tests (dispatch, error messages). All run in-memory — zero Docker, zero DATABASE_URL, instant in CI. Add P0 TODO: submit Bun PR for WASM embedding in bun build --compile (oven-sh/bun#15032). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: bump version and changelog (v0.7.0) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update project documentation for v0.7.0 PGLite engine - CLAUDE.md: add PGLite key files, update architecture, add migrate command, add 3 test files - README.md: PGLite as default init, zero-config getting started, migration path to Supabase - docs/ENGINES.md: PGLiteEngine shipped (v0.7), capability matrix, migration docs - docs/SQLITE_ENGINE.md: marked superseded by PGLite Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: remove stale v0.4 README update prompt Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * chore: remove SQLITE_ENGINE.md (superseded by PGLite) PGLite uses the same SQL as Postgres, making a separate SQLite engine unnecessary. docs/ENGINES.md covers PGLiteEngine. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update README step 2 to default to PGLite Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add schema setup step and install-all-integrations step to README Step 3 now tells agents to read GBRAIN_RECOMMENDED_SCHEMA.md and set up the MECE directory structure before importing. Step 7 tells agents to install every available integration recipe, not just list them. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: update install goal to match full opinionated setup Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: add 'Need an AI agent first?' section with one-click deploy links New users who don't have OpenClaw or Hermes Agent get pointed to AlphaClaw on Render and the Hermes Agent Railway template. One click each. Claude Code mentioned for users who already have it. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * fix: add migrate to CLI_ONLY + help output, fix standalone example - migrate command was missing from CLI_ONLY set (errored as "Unknown command") - migrate now shows in --help under SETUP - init help line shows --pglite flag - standalone CLI example uses gbrain init (not --supabase) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: set realistic time expectation (~30 min to working brain) DB is 2 seconds. But schema + import + embeddings + integrations is 15-30 minutes. The agent does the work, you answer API key questions. Don't oversell time-to-value. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: fix AlphaClaw Render requirement (8GB+ RAM, not free tier) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: final README polish for launch - GOAL line: "Garry Tan's exact setup" (not Claude Code specific) - Remove markdown links from code block (won't render) - STEP 2 renamed from "START HERE" to "DATABASE" - Tighten Supabase fallback text Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: remove duplicate old install block from README The v0.5-era "With OpenClaw or Hermes Agent" paste block was superseded by the top-level "Start here" block. Having both confused users and the old one still said --supabase as step 2. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * docs: clean up README consistency and remove duplicated content - Remove duplicate "Try it" section (old 4-act walkthrough that repeated the install flow and contradicted "~30 min" with "90 sec") - Remove duplicate Setup section (third repetition of gbrain init) - Fix brain.db → brain.pglite (actual default path) - Fix "coming in v0.7" → "not yet implemented" (we ARE v0.7) - Remove "You don't need Postgres" (confusing since PGLite IS Postgres) - Deduplicate "competitive dynamics" query (appeared 3 times) - Collapse redundant standalone CLI section Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |