cb6d6d46ab
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.
129 lines
4.8 KiB
Python
129 lines
4.8 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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def test_sanitize_fts_query_never_crashes_on_fts5_specials():
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"""Queries with FTS5 operator characters must not produce malformed SQL."""
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problematic = [
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'test " query',
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"test * query",
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"test (a OR b) query",
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"test^2 query",
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"test:colon query",
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"test-hyphen query",
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"a" * 1000, # long query
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]
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for q in problematic:
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result = FactRetriever._sanitize_fts_query(q)
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# We just need it to return a string without raising
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assert isinstance(result, str)
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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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def test_prefetch_single_keyword_still_works(retriever_with_facts):
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"""Single-term queries (pre-fix working case) remain working."""
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results = retriever_with_facts.search("compaction")
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assert len(results) >= 1
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assert "Compaction" in results[0]["content"] or "compaction" in results[0]["content"].lower()
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def test_prefetch_stopword_only_query_empty(retriever_with_facts):
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"""Pure stopword queries return zero results but don't crash."""
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# Pass to _sanitize_fts_query directly first so we know what happens
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assert FactRetriever._sanitize_fts_query("the and of") == "the and of"
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# search() handles the likely-zero-hit case gracefully
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results = retriever_with_facts.search("the and of")
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# Either zero results or it errored-gracefully to [] — both are fine
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assert isinstance(results, list)
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