Stop the reranker fetch reading text it discards

Collapsing the caption text into `get_pictures_grouped` served the enrichment
path, which uses it, but the multimodal reranker discards the second return value
while still paying to read the column. That is the widest fan-out in the codebase,
`limit * 10` candidates, and it previously projected self_ref and picture_data
alone.

`with_text` is opt-in and off by default, so the cheap projection is what a caller
gets unless it asks for more. The reranker test asserts the projection as well as
the query count, since a count alone would not notice the column coming back.

CHANGELOG.md

@@ -11,7 +11,7 @@
 
 ### Changed
 
-- Search enrichment, the multimodal reranker's picture fetch, and context expansion each issue a fixed number of `document_items` queries regardless of how many documents a result set spans, instead of one set per document. `expand_with_items` takes the items to expand from rather than fetching them, and `DocumentItemRepository` gains `resolve_refs_grouped`, `get_items_in_ranges`, `get_pictures_grouped` and `get_caption_picture_refs_grouped`. The superseded methods are removed: `resolve_refs`, `get_items_in_range`, `get_caption_picture_refs`, `get_text_for_refs` and `get_all_items_grouped`. `get_pictures_grouped` returns the text alongside the bytes.
+- Search enrichment, the multimodal reranker's picture fetch, and context expansion each issue a fixed number of `document_items` queries regardless of how many documents a result set spans, instead of one set per document. `expand_with_items` takes the items to expand from rather than fetching them, and `DocumentItemRepository` gains `resolve_refs_grouped`, `get_items_in_ranges`, `get_pictures_grouped` and `get_caption_picture_refs_grouped`. The superseded methods are removed: `resolve_refs`, `get_items_in_range`, `get_caption_picture_refs`, `get_text_for_refs` and `get_all_items_grouped`. `get_pictures_grouped` returns each picture's text alongside its bytes under `with_text`, off by default so the reranker's blob fetch does not read a column it discards.
 - Eval judge pinned to `qwen3.8`: `DEFAULT_JUDGE_MODEL` is `ollama:qwen3.8`, and the reference configs use `Inferact/Qwen3.8-27B-NVFP4` with `extra_body.chat_template_kwargs.reasoning_effort: low`. Results in `docs/benchmarks.md` were judged by `Qwen3.6-35B-A3B-NVFP4` and are not re-judged.
 - `create_capability(rag=...)` lends a capability an open client rather than having it open its own; `client.ask`/`client.analyze` now pass theirs.
 - The MCP server opens one database client for its lifetime instead of one per tool call, and fails at startup if the database cannot be opened. `delete_document` no longer opens its own connection with `skip_validation=True`, so the server no longer opts out of embedding-config validation: drift that validation rejects (any `vector_dim` mismatch, or identity drift on a writable server) now fails MCP startup instead of serving a delete-only server. Use the CLI to delete under drift.

haiku_rag_slim/haiku/rag/client/search.py

@@ -184,7 +184,9 @@ async def _populate_image_data(client: "HaikuRAG", results: list[SearchResult])
     if not wanted:
         return
 
-    bytes_by_document, captions_by_document = await repo.get_pictures_grouped(wanted)
+    bytes_by_document, captions_by_document = await repo.get_pictures_grouped(
+        wanted, with_text=True
+    )
     if not bytes_by_document:
         return
 

haiku_rag_slim/haiku/rag/store/repositories/document_item.py

@@ -260,21 +260,28 @@ class DocumentItemRepository:
         return " OR ".join(clauses) if clauses else None
 
     async def get_pictures_grouped(
-        self, refs_by_document: "Mapping[str, list[str]]"
+        self,
+        refs_by_document: "Mapping[str, list[str]]",
+        *,
+        with_text: bool = False,
     ) -> tuple[dict[str, dict[str, bytes]], dict[str, dict[str, str]]]:
-        """Picture bytes and their text, across documents, in one query.
+        """Picture bytes across documents in one query.
 
         Returns `(bytes_by_document, text_by_document)`, each
         `{document_id: {self_ref: value}}` and each omitting refs whose value is
-        empty. The text comes from the same rows as the bytes, so asking for it
-        separately would be a second read of rows already in hand.
+        empty. `with_text` adds each picture's text to the projection, which is
+        free in queries because it is on the same rows, but not in bytes: the
+        text column is dead weight for a caller that only scores pixels.
         """
         predicate = self._per_document_predicate(refs_by_document, "self_ref")
         if predicate is None:
             return {}, {}
+        columns = ["document_id", "self_ref", "picture_data"]
+        if with_text:
+            columns.append("text")
         rows = await (
             self.store.document_items_table.query()
-            .select(["document_id", "self_ref", "picture_data", "text"])
+            .select(columns)
             .where(predicate)
             .to_list()
         )

tests/store/test_document_item_grouped.py

@@ -54,7 +54,7 @@ async def test_pictures_grouped_keeps_documents_apart(temp_db_path, item_queries
 
         item_queries["n"] = 0
         blobs, texts = await repo.get_pictures_grouped(
-            {"doc-a": ["#/pictures/0"], "doc-b": ["#/pictures/0"]}
+            {"doc-a": ["#/pictures/0"], "doc-b": ["#/pictures/0"]}, with_text=True
         )
 
         assert item_queries["n"] == 1
@@ -156,3 +156,18 @@ async def test_caption_picture_refs_grouped_ignores_non_picture_predecessors(
         )
 
         assert got == {}
+
+
+@pytest.mark.asyncio
+async def test_pictures_grouped_omits_text_unless_asked(temp_db_path, item_queries):
+    """Text is dead weight for a caller that only scores pixels."""
+    async with Store(temp_db_path, create=True) as store:
+        repo = DocumentItemRepository(store)
+        await _seed(repo, "doc-a")
+
+        item_queries["n"] = 0
+        blobs, texts = await repo.get_pictures_grouped({"doc-a": ["#/pictures/0"]})
+
+        assert item_queries["n"] == 1
+        assert blobs == {"doc-a": {"#/pictures/0": b"bytes-doc-a"}}
+        assert texts == {}

tests/test_enrichment_batching.py

@@ -1,4 +1,5 @@
 import lancedb
+import lancedb.query
 import pytest
 
 from haiku.rag.client import HaikuRAG
@@ -35,6 +36,21 @@ async def _seed(rag: HaikuRAG, document_ids: list[str]) -> None:
         )
 
 
+@pytest.fixture
+def item_projections(monkeypatch):
+    """Columns each document_items query projects."""
+    projections: list[list[str]] = []
+    select = lancedb.query.AsyncQuery.select
+
+    def recording(self, columns):
+        if isinstance(columns, list):
+            projections.append([str(c) for c in columns])
+        return select(self, columns)
+
+    monkeypatch.setattr(lancedb.query.AsyncQuery, "select", recording)
+    return projections
+
+
 @pytest.fixture
 def item_queries(monkeypatch):
     tally = {"n": 0}
@@ -223,7 +239,7 @@ def _picture_chunk(document_id: str) -> Chunk:
 
 @pytest.mark.asyncio
 async def test_reranker_blob_fetch_is_one_query_for_any_document_count(
-    temp_db_path, item_queries
+    temp_db_path, item_queries, item_projections
 ):
     """This path runs over `limit * 10` candidates, so per-document fetching
     costs the most here."""
@@ -239,6 +255,10 @@ async def test_reranker_blob_fetch_is_one_query_for_any_document_count(
             assert all(c._picture_data for c in chunks)
 
     assert counts == [1, 1], counts
+    # The reranker scores pixels, so `text` has no business in the projection.
+    picture_projections = [p for p in item_projections if "picture_data" in p]
+    assert picture_projections, "no picture query observed"
+    assert all("text" not in p for p in picture_projections), picture_projections
 
 
 @pytest.mark.asyncio