fix(core): repair FTS half of hybrid search for natural-language queries

Hybrid search was silently running vector-only on natural-language
queries — the FTS branch contributed zero candidates. Two causes in the
SQLite (and parallel Postgres) FTS query preparation:

1. Sentence punctuation forced phrase matching. A question like
   "When did Melanie paint a sunrise?" reached FTS5 as the exact phrase
   '"When did Melanie paint a sunrise?"*', which matches no document.
   The FTS5 tokenizer ignores this punctuation in the index, so
   stripping it from word edges loses nothing — but leaving it disabled
   the entire FTS contribution. _prepare_single_term now strips
   ?!.,;: from word edges of multi-word queries (interior characters —
   hyphens, slashes in permalinks/paths — untouched).

2. No relaxation when strict all-terms-AND matched nothing. Questions
   rarely have every word in one document, so even after (1) the
   strict AND returned zero rows. The hybrid path now retries once with
   an OR-joined, stopword-filtered, content-term query when the strict
   query is empty. bm25/ts_rank still rank multi-term matches first, and
   fusion with the vector branch keeps relaxed lexical candidates from
   dominating precision.

The relaxation is gated behind a new allow_relaxed=False parameter on
SearchRepositoryBase.search; only _search_hybrid opts in. Strict FTS
behavior (search_type=text, title, permalink, link resolution) is
unchanged — the service layer keeps its own conservative fallback.
No config flag, default-safe.

Discovered via the benchmark harness: two different fusion algorithms
produced byte-identical rankings across 1,986 queries (impossible with
two live sources), and instrumentation confirmed fts=0 on 40/40
sampled LoCoMo queries.

Benchmark impact (corrected LoCoMo, 1,986 queries, same index,
retrieval metrics — every category improves, no regression):
  recall@5  0.745 -> 0.823  (+7.9)
  MRR       0.618 -> 0.718  (+10.0)
  headline  r5 0.734 -> 0.801, MRR 0.621 -> 0.706
Largest gains on open_domain (+0.10 r5) and adversarial (+0.12 r5);
smallest on temporal (+0.003 r5 / +0.02 MRR).

Tests: punctuation no longer phrase-quotes; relaxation builds the
expected OR query and respects boolean/quoted/short-query intent; the
hybrid opt-in surfaces a partial-overlap document while the default
strict path still returns empty. Parallel coverage for Postgres. Full
SQLite unit suite green (2968 passed); ty + ruff clean.

Signed-off-by: Drew Cain <groksrc@gmail.com>

src/basic_memory/repository/postgres_search_repository.py

@@ -18,6 +18,7 @@ from basic_memory.repository.search_index_row import SearchIndexRow
 from basic_memory.repository.search_repository_base import (
     SearchRepositoryBase,
     VectorChunkState,
+    relaxed_query_words,
 )
 from basic_memory.repository.metadata_filters import parse_metadata_filters
 from basic_memory.repository.semantic_errors import SemanticDependenciesMissingError
@@ -176,6 +177,14 @@ class PostgresSearchRepository(SearchRepositoryBase):
         # For non-Boolean queries, prepare single term
         return self._prepare_single_term(term, is_prefix)
 
+    @staticmethod
+    def _relaxed_tsquery_text(search_text: Optional[str]) -> Optional[str]:
+        """OR-relaxed tsquery expression for a failed strict query, or None."""
+        words = relaxed_query_words(search_text)
+        if not words:
+            return None
+        return " | ".join(f"{word}:*" for word in words)
+
     def _prepare_boolean_query(self, query: str) -> str:
         """Convert Boolean query to tsquery format.
 
@@ -234,6 +243,14 @@ class PostgresSearchRepository(SearchRepositoryBase):
         for char in special_chars:
             cleaned_term = cleaned_term.replace(char, " ")
 
+        # Sentence punctuation carries no lexical signal in tsquery either;
+        # strip it from word edges so question-form queries produce clean
+        # lexemes (parity with the SQLite FTS5 preparation).
+        if " " in cleaned_term:
+            cleaned_term = " ".join(
+                word.strip("?!.,;") for word in cleaned_term.split() if word.strip("?!.,;")
+            )
+
         # Handle multi-word queries
         if " " in cleaned_term:
             words = [w for w in cleaned_term.split() if w.strip()]
@@ -908,6 +925,7 @@ class PostgresSearchRepository(SearchRepositoryBase):
         min_similarity: Optional[float] = None,
         limit: int = 10,
         offset: int = 0,
+        allow_relaxed: bool = False,
     ) -> List[SearchIndexRow]:
         """Search across all indexed content using PostgreSQL tsvector."""
         # --- Dispatch vector / hybrid modes (shared logic) ---
@@ -982,6 +1000,20 @@ class PostgresSearchRepository(SearchRepositoryBase):
             async with db.scoped_session(self.session_maker) as session:
                 result = await session.execute(text(sql), params)
                 rows = result.fetchall()
+                # Trigger: multi-word natural-language query matched nothing
+                # under the default all-terms-AND tsquery semantics.
+                # Why: questions rarely have every word in one document;
+                # without relaxation the FTS half of hybrid search contributes
+                # zero candidates (parity with the SQLite path).
+                # Outcome: one retry with OR-joined prefix lexemes; ts_rank
+                # still ranks multi-term matches first.
+                relaxed = (
+                    self._relaxed_tsquery_text(search_text) if allow_relaxed and not rows else None
+                )
+                if relaxed and params.get("text"):
+                    params["text"] = relaxed
+                    result = await session.execute(text(sql), params)
+                    rows = result.fetchall()
         except Exception as e:
             if self._is_tsquery_syntax_error(e):
                 logger.warning(f"tsquery syntax error for search term: {search_text}, error: {e}")

src/basic_memory/repository/search_repository_base.py

@@ -40,6 +40,36 @@ BULLET_PATTERN = re.compile(r"^[\-\*]\s+")
 OVERSIZED_ENTITY_VECTOR_SHARD_SIZE = 256
 _SQLITE_MAX_PREPARE_WINDOW = 8
 
+# Interrogative/function words contribute lexical noise when a strict
+# full-text query is relaxed: "when OR did OR a" matches loud wrong documents
+# that displace genuine results from the ranking window.
+RELAXATION_STOPWORDS = frozenset(
+    "a an and are as at be but by did do does for from had has have how i in is it of on "
+    "or that the their they this to was we were what when where which who whom whose why "
+    "will with you your".split()
+)
+
+
+def relaxed_query_words(search_text: Optional[str]) -> Optional[list[str]]:
+    """Content-bearing words for OR-relaxing a strict full-text query.
+
+    Returns None when relaxation must not apply: empty input, quoted phrases,
+    or explicit boolean queries (user intent is not second-guessed).
+    """
+    if not search_text:
+        return None
+    stripped = search_text.strip()
+    if '"' in stripped or any(op in f" {stripped} " for op in (" AND ", " OR ", " NOT ")):
+        return None
+    words = [word.strip("?!.,;:") for word in stripped.split()]
+    words = [
+        word
+        for word in words
+        if word and word.isalnum() and word.lower() not in RELAXATION_STOPWORDS
+    ]
+    return words or None
+
+
 # Entity, observation, and relation rows in search_index carry ids from independent
 # auto-increment sequences, so a bare id is ambiguous across row types. Every map in
 # the vector/hybrid retrieval path must key rows by (type, id) to avoid collisions.
@@ -229,6 +259,7 @@ class SearchRepositoryBase(ABC):
         min_similarity: Optional[float] = None,
         limit: int = 10,
         offset: int = 0,
+        allow_relaxed: bool = False,
     ) -> List[SearchIndexRow]:
         """Search across all indexed content.
 
@@ -2174,6 +2205,9 @@ class SearchRepositoryBase(ABC):
         query_start = time.perf_counter()
         candidate_limit = max(self._semantic_vector_k, (limit + offset) * 10)
         fts_start = time.perf_counter()
+        # allow_relaxed: question-form queries rarely AND-match, and a dead FTS
+        # branch silently degrades hybrid to vector-only ranking. Fusion plus
+        # bm25 keep relaxed lexical candidates from dominating precision.
         fts_results = await self.search(
             search_text=search_text,
             permalink=permalink,
@@ -2187,6 +2221,7 @@ class SearchRepositoryBase(ABC):
             retrieval_mode=SearchRetrievalMode.FTS,
             limit=candidate_limit,
             offset=0,
+            allow_relaxed=True,
         )
         fts_ms = (time.perf_counter() - fts_start) * 1000
         vector_start = time.perf_counter()

src/basic_memory/repository/sqlite_search_repository.py

@@ -23,7 +23,10 @@ from basic_memory.models.search import (
 from basic_memory.repository.embedding_provider import EmbeddingProvider
 from basic_memory.repository.embedding_provider_factory import create_embedding_provider
 from basic_memory.repository.search_index_row import SearchIndexRow
-from basic_memory.repository.search_repository_base import SearchRepositoryBase
+from basic_memory.repository.search_repository_base import (
+    SearchRepositoryBase,
+    relaxed_query_words,
+)
 from basic_memory.repository.metadata_filters import parse_metadata_filters, build_sqlite_json_path
 from basic_memory.repository.semantic_errors import SemanticDependenciesMissingError
 from basic_memory.schemas.search import SearchItemType, SearchRetrievalMode
@@ -255,6 +258,19 @@ class SQLiteSearchRepository(SearchRepositoryBase):
         if "*" in term and all(c.isalnum() or c in "*_-" for c in term):
             return term
 
+        # Natural-language queries arrive with sentence punctuation that FTS5
+        # treats as syntax ("When did Melanie paint a sunrise?"). The tokenizer
+        # ignores this punctuation in the INDEX, so stripping it from word
+        # edges loses nothing — but leaving it forces the whole question into
+        # an exact-phrase match that returns zero rows, silently disabling the
+        # FTS half of hybrid search. Interior characters (hyphens, slashes —
+        # permalinks and paths) are untouched.
+        if " " in term:
+            words = [word.strip("?!.,;:") for word in term.split()]
+            term = " ".join(word for word in words if word)
+            if not term:
+                return ""
+
         # Characters that can cause FTS5 syntax errors when used as operators
         # We're more conservative here - only quote when we detect problematic patterns
         problematic_chars = [
@@ -351,6 +367,14 @@ class SQLiteSearchRepository(SearchRepositoryBase):
         # For non-Boolean queries, use the single term preparation logic
         return self._prepare_single_term(term, is_prefix)
 
+    @staticmethod
+    def _relaxed_fts_text(search_text: Optional[str]) -> Optional[str]:
+        """OR-relaxed FTS5 expression for a failed strict query, or None."""
+        words = relaxed_query_words(search_text)
+        if not words:
+            return None
+        return " OR ".join(f"{word}*" for word in words)
+
     # ------------------------------------------------------------------
     # sqlite-vec extension loading (SQLite-specific)
     # ------------------------------------------------------------------
@@ -953,8 +977,15 @@ class SQLiteSearchRepository(SearchRepositoryBase):
         min_similarity: Optional[float] = None,
         limit: int = 10,
         offset: int = 0,
+        allow_relaxed: bool = False,
     ) -> List[SearchIndexRow]:
-        """Search across all indexed content using SQLite FTS5."""
+        """Search across all indexed content using SQLite FTS5.
+
+        ``allow_relaxed=True`` retries a zero-result strict multi-word query
+        with OR-joined content terms. Only the hybrid path opts in: its FTS
+        branch otherwise contributes nothing for question-form queries.
+        Service-level FTS searches keep their own conservative fallback.
+        """
         # --- Dispatch vector / hybrid modes (shared logic) ---
         dispatched = await self._dispatch_retrieval_mode(
             search_text=search_text,
@@ -1021,6 +1052,21 @@ class SQLiteSearchRepository(SearchRepositoryBase):
             async with db.scoped_session(self.session_maker) as session:
                 result = await session.execute(text(sql), params)
                 rows = result.fetchall()
+                # Trigger: multi-word natural-language query matched nothing
+                # under the default all-terms-AND semantics.
+                # Why: questions ("when did X do Y") rarely have every word in
+                # one document; without relaxation the FTS half of hybrid
+                # search contributes zero candidates and ranking degrades to
+                # vector-only.
+                # Outcome: one retry with OR-joined prefix terms; bm25 still
+                # ranks multi-term matches first.
+                relaxed = (
+                    self._relaxed_fts_text(search_text) if allow_relaxed and not rows else None
+                )
+                if relaxed and params.get("text"):
+                    params["text"] = relaxed
+                    result = await session.execute(text(sql), params)
+                    rows = result.fetchall()
         except Exception as e:
             # Handle FTS5 syntax errors and provide user-friendly feedback
             if self._is_fts5_syntax_error(e):  # pragma: no cover