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6b81590c55
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).
97 lines
3.4 KiB
Python
97 lines
3.4 KiB
Python
"""Tests for FactRetriever FTS5 query sanitization.
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These tests cover the fix where raw natural-language queries passed to
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FTS5 MATCH were AND-joined by default, dropping recall to zero on any
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multi-word prose query. The sanitizer drops stopwords and OR-joins the
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remaining content tokens as phrase literals.
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"""
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from __future__ import annotations
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import pytest
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pytest.importorskip("numpy") # retrieval module imports numpy indirectly
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from plugins.memory.holographic.retrieval import FactRetriever
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from plugins.memory.holographic.store import MemoryStore
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# ---------------------------------------------------------------------------
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# _sanitize_fts_query — unit tests (no DB required)
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# ---------------------------------------------------------------------------
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@pytest.mark.parametrize(
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"query,expected_tokens",
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[
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# stopwords dropped
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("what happened with the deployment rollback", {"happened", "deployment", "rollback"}),
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# single content word passes through
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("compaction", {"compaction"}),
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# all stopwords → falls back to raw
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("the and of", None), # None = sentinel for fallback-to-raw
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# empty string → empty output
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("", ""),
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# FTS5 operator characters stripped
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("context: length-probe", {"context", "lengthprobe"}),
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# trailing punctuation stripped by tokenizer
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("hello, world!", {"hello", "world"}),
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],
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)
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def test_sanitize_fts_query_extracts_content_tokens(query, expected_tokens):
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result = FactRetriever._sanitize_fts_query(query)
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if expected_tokens == "":
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assert result == ""
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return
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if expected_tokens is None:
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# Pathological case: all stopwords — should fall back to raw query
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assert result == query
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return
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# OR-joined phrase literals: `"tok1" OR "tok2" OR ...`
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# Extract the tokens between quotes, order-independent.
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import re
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matches = re.findall(r'"([^"]+)"', result)
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assert set(matches) == expected_tokens, f"got {result!r}"
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# ---------------------------------------------------------------------------
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# Integration test — actually run _fts_candidates against an in-memory DB
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# ---------------------------------------------------------------------------
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@pytest.fixture
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def retriever_with_facts(tmp_path):
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"""MemoryStore seeded with a few facts for retrieval tests."""
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db_path = tmp_path / "test_facts.db"
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store = MemoryStore(str(db_path))
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store.add_fact(
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content="The Thursday deployment rollback failed because of stale migration state.",
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category="project",
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)
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store.add_fact(
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content="Compaction settings tuned to 0.85 threshold.",
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category="tool",
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)
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store.add_fact(
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content="Venice.ai advertises availableContextTokens inside model_spec.",
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category="tool",
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)
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retriever = FactRetriever(store=store)
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yield retriever
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store.close()
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def test_prefetch_recovers_prose_query(retriever_with_facts):
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"""A natural-language query should now match the relevant fact.
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Before the sanitizer fix, 'what happened with the deployment rollback'
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returned zero hits because FTS5 required every token to co-occur.
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"""
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results = retriever_with_facts.search(
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"what happened with the deployment rollback"
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)
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assert len(results) >= 1
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# The top hit should be the deployment rollback fact
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assert "deployment rollback" in results[0]["content"].lower()
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