fix: crash in AnswerdotaiRerankers/ColbertReranker for return_score="all" (#3671)

## What

`AnswerdotaiRerankers(return_score="all").rerank_hybrid(...)` (and
`ColbertReranker`, which subclasses it without overriding
`rerank_hybrid`) raises:

```
pyarrow.lib.ArrowInvalid: Invalid sort key column: No match for FieldRef.Name(_relevance_score) in _rowid: int64 ...
```

## Why

```python
combined_results = self.merge_results(vector_results, fts_results)
combined_results = self._rerank(combined_results, query)
if self.score == "relevance":
    combined_results = self._keep_relevance_score(combined_results)
elif self.score == "all":
    combined_results = self._merge_and_keep_scores(vector_results, fts_results)
```

When `score == "all"`, `combined_results` is unconditionally overwritten
by `_merge_and_keep_scores(vector_results, fts_results)` **after**
`_rerank()` already computed and appended `_relevance_score` —
discarding it. The following `sort_by("_relevance_score", ...)` then has
nothing to sort on.

Every sibling reranker that supports `return_score="all"`
(`cross_encoder`, `openai`, `cohere`, `jinaai`, `voyageai`, `watsonx`)
instead calls `_merge_and_keep_scores()` **before** `_rerank()`. This
file is the one place the ordering got inverted when `"all"` support was
added (#2509) — a copy/paste inconsistency across the six files that PR
touched. Fix mirrors the pattern already used (and tested) by the other
five rerankers.

Also drops the now-stale `"Only 'relevance' is supported for now"`
docstring line on both classes, left over from before `"all"` support
existed.

## Testing

Added `test_answerdotai_reranker_return_all`, mirroring the existing
`test_cross_encoder_reranker_return_all`. Verified locally with the real
built Rust extension: red (reproduces the exact `ArrowInvalid` above) →
green, using the actual `rerank_hybrid`/`_rerank`/`base.py` code path
with the model call mocked out — my local environment's
`rerankers==0.10.0` fails to load the real ColBERT model against the
available `transformers` version (`AttributeError: 'ColBERTModel' object
has no attribute 'all_tied_weights_keys'`), which I confirmed also
breaks the **pre-existing**, unmodified
`test_colbert_reranker`/`test_answerdotai_reranker` baseline tests
identically — an unrelated local dependency-version issue, not a
regression from this change. `ruff check`/`ruff format` clean; full
`test_rerankers.py` run: 9 passed / 8 skipped / 3 failed (the 3 failures
are exactly those two pre-existing tests plus my new one, all failing at
model-loading time for the same unrelated reason before reaching the
changed code).

---
Disclosure: this PR was drafted with AI assistance (Claude); I reviewed,
tested, and take responsibility for the change.

Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>

python/python/lancedb/rerankers/answerdotai.py

@@ -23,7 +23,7 @@ class AnswerdotaiRerankers(Reranker):
     column : str, default "text"
         The name of the column to use as input to the cross encoder model.
     return_score : str, default "relevance"
-        options are "relevance" or "all". Only "relevance" is supported for now.
+        options are "relevance" or "all".
     **kwargs
         Additional keyword arguments to pass to the model. For example, 'device'.
         See AnswerDotAI/rerankers for more information.
@@ -77,12 +77,13 @@ class AnswerdotaiRerankers(Reranker):
         vector_results: pa.Table,
         fts_results: pa.Table,
     ):
-        combined_results = self.merge_results(vector_results, fts_results)
+        if self.score == "all":
+            combined_results = self._merge_and_keep_scores(vector_results, fts_results)
+        else:
+            combined_results = self.merge_results(vector_results, fts_results)
         combined_results = self._rerank(combined_results, query)
         if self.score == "relevance":
             combined_results = self._keep_relevance_score(combined_results)
-        elif self.score == "all":
-            combined_results = self._merge_and_keep_scores(vector_results, fts_results)
         combined_results = combined_results.sort_by(
             [("_relevance_score", "descending")]
         )

python/python/lancedb/rerankers/colbert.py

@@ -16,7 +16,7 @@ class ColbertReranker(AnswerdotaiRerankers):
     column : str, default "text"
         The name of the column to use as input to the cross encoder model.
     return_score : str, default "relevance"
-        options are "relevance" or "all". Only "relevance" is supported for now.
+        options are "relevance" or "all".
     **kwargs
         Additional keyword arguments to pass to the model, for example, 'device'.
         See AnswerDotAI/rerankers for more information.

python/python/tests/test_rerankers.py

@@ -644,6 +644,21 @@ def test_cross_encoder_reranker_return_all(tmp_path):
     assert "_distance" in result.column_names
 
 
+def test_answerdotai_reranker_return_all(tmp_path):
+    pytest.importorskip("rerankers")
+    reranker = AnswerdotaiRerankers(return_score="all")
+    table, schema = get_test_table(tmp_path)
+    query = "single player experience"
+    result = (
+        table.search(query, query_type="hybrid", vector_column_name="vector")
+        .rerank(reranker=reranker)
+        .to_arrow()
+    )
+    assert "_relevance_score" in result.column_names
+    assert "_score" in result.column_names
+    assert "_distance" in result.column_names
+
+
 # ---------------------------------------------------------------------------
 # Regression tests for LinearCombinationReranker scoring bugs (issue #3154)
 # ---------------------------------------------------------------------------