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2 commits

Author SHA1 Message Date
Teknium
6b81590c55
test: prune low-value tests suite-wide (wave 1) — 46,820 → 28,106 test functions
Systematic prune per AGENTS.md test policy, one pass over every major
test tree (gateway, hermes_cli, tools, agent, run_agent, plugins, cli,
cron, tui_gateway, honcho/openviking, root-level):

- DELETE: source-reading tests (read_text/getsource on prod files),
  change-detector tests (exact catalog counts, model-name snapshots,
  config version literals), mock-echo tests (assert a mock returns what
  it was told), assertion-free/trivial tests, near-duplicate
  parametrizations (boundaries + one representative kept), async/sync
  twin duplicates, cosmetic within-file variations.
- KEEP (mandatory): security/redaction/approval guards, message-role
  alternation invariants, prompt-caching/deterministic-call-id
  invariants, issue-number regression tests (deduped), E2E tests.
- 6 test files deleted outright (script-style/no-assert or fully
  redundant); conftest.py, fakes/, fixtures/ untouched.
- tests/acp/conftest.py added: autouse fixture stubs the live
  models.dev/GitHub/Copilot/Anthropic inventory fetches that ACP server
  tests performed on every session create — test_server.py 147s → 3.4s,
  and the tests are now genuinely hermetic.
- Sleep-based slowness shrunk where safe (codex_ttfb_watchdog,
  compression_concurrent_fork, etc.); no wall-clock assertion tightened.

Verification: full hermetic suite via scripts/run_tests.sh —
2439 files, 31,130 tests passed, 0 failed, 0 flaky retries, 315s wall
(baseline: 583s wall, 13,564s subprocess CPU).
2026-07-29 13:10:23 -07:00
cyb3rwr3n
cb6d6d46ab fix(memory/holographic): sanitize FTS5 queries for natural-language recall
The FactRetriever's _fts_candidates passed the raw query string directly
to FTS5's MATCH operator. FTS5 defaults to AND-between-tokens, which
means any multi-word prose query like 'what happened with the deployment
rollback' required every single token to co-occur in a fact — dropping
recall to zero on the kind of queries agents actually issue via prefetch().

Fix: add _sanitize_fts_query() that:
- tokenizes the query and drops English stopwords
- strips FTS5 operator characters per token
- OR-joins the remaining content tokens as phrase literals

For pathological inputs (all stopwords, empty), falls back to the raw
query so the caller sees zero results instead of a SQL error.

This is a pure-retrieval-quality fix — the HRR + Jaccard reranking
stages still keep precision high. Ships with 10 tests covering the
sanitizer and retrieval integration.
2026-06-30 15:55:11 -07:00