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feat: show reranker info in hybrid search explain plan (#3006)

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Closes #3000

The hybrid search `explain_plan` now shows the reranker as the top-level
node with
the vector and FTS sub-plans indented underneath, instead of just
listing them
separately with no reranker context.

**Before:**
```
Vector Search Plan:
ProjectionExec: ...
FTS Search Plan:
ProjectionExec: ...
```

**After:**
```
RRFReranker(K=60)
  Vector Search Plan:
  ProjectionExec: ...
  FTS Search Plan:
  ProjectionExec: ...
```

Other rerankers display similarly ; e.g.
`LinearCombinationReranker(weight=0.7, fill=1.0)`,
`MRRReranker(weight_vector=0.5, weight_fts=0.5)`,
`CohereReranker(model_name=name)`.

---------

Signed-off-by: dask-58 <googldhruv@gmail.com>
Co-authored-by: Will Jones <willjones127@gmail.com>
This commit is contained in:
Dhruv
2026-02-11 01:15:39 +05:30
committed by GitHub
parent bd3dd6a8e5
commit 4323ca0147
12 changed files with 67 additions and 36 deletions
Download Patch File Download Diff File Expand all files Collapse all files

63
python/python/lancedb/query.py
View File

@@ -2118,19 +2118,17 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
""" # noqa: E501
self._create_query_builders()
results = ["Vector Search Plan:"]
results.append(
self._table._explain_plan(
self._vector_query.to_query_object(), verbose=verbose
)
reranker_label = str(self._reranker) if self._reranker else "No reranker"
vector_plan = self._table._explain_plan(
self._vector_query.to_query_object(), verbose=verbose
)
results.append("FTS Search Plan:")
results.append(
self._table._explain_plan(
self._fts_query.to_query_object(), verbose=verbose
)
fts_plan = self._table._explain_plan(
self._fts_query.to_query_object(), verbose=verbose
)
return "\n".join(results)
# Indent sub-plans under the reranker
indented_vector = "\n".join(" " + line for line in vector_plan.splitlines())
indented_fts = "\n".join(" " + line for line in fts_plan.splitlines())
return f"{reranker_label}\n {indented_vector}\n {indented_fts}"
def analyze_plan(self):
"""Execute the query and display with runtime metrics.
@@ -3164,23 +3162,20 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
... plan = await table.query().nearest_to([1.0, 2.0]).nearest_to_text("hello").explain_plan(True)
... print(plan)
>>> asyncio.run(doctest_example()) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
Vector Search Plan:
ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
Take: columns="vector, _rowid, _distance, (text)"
CoalesceBatchesExec: target_batch_size=1024
GlobalLimitExec: skip=0, fetch=10
FilterExec: _distance@2 IS NOT NULL
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
KNNVectorDistance: metric=l2
LanceRead: uri=..., projection=[vector], ...
<BLANKLINE>
FTS Search Plan:
ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
Take: columns="_rowid, _score, (vector), (text)"
CoalesceBatchesExec: target_batch_size=1024
GlobalLimitExec: skip=0, fetch=10
MatchQuery: column=text, query=hello
<BLANKLINE>
RRFReranker(K=60)
ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
Take: columns="vector, _rowid, _distance, (text)"
CoalesceBatchesExec: target_batch_size=1024
GlobalLimitExec: skip=0, fetch=10
FilterExec: _distance@2 IS NOT NULL
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST, _rowid@1 ASC NULLS LAST], preserve_partitioning=[false]
KNNVectorDistance: metric=l2
LanceRead: uri=..., projection=[vector], ...
ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
Take: columns="_rowid, _score, (vector), (text)"
CoalesceBatchesExec: target_batch_size=1024
GlobalLimitExec: skip=0, fetch=10
MatchQuery: column=text, query=hello
Parameters
----------
@@ -3192,12 +3187,12 @@ class AsyncHybridQuery(AsyncStandardQuery, AsyncVectorQueryBase):
plan : str
""" # noqa: E501
results = ["Vector Search Plan:"]
results.append(await self._inner.to_vector_query().explain_plan(verbose))
results.append("FTS Search Plan:")
results.append(await self._inner.to_fts_query().explain_plan(verbose))
return "\n".join(results)
vector_plan = await self._inner.to_vector_query().explain_plan(verbose)
fts_plan = await self._inner.to_fts_query().explain_plan(verbose)
# Indent sub-plans under the reranker
indented_vector = "\n".join(" " + line for line in vector_plan.splitlines())
indented_fts = "\n".join(" " + line for line in fts_plan.splitlines())
return f"{self._reranker}\n {indented_vector}\n {indented_fts}"
async def analyze_plan(self):
"""

8
python/python/lancedb/rerankers/answerdotai.py
View File

@@ -42,10 +42,18 @@ class AnswerdotaiRerankers(Reranker):
rerankers = attempt_import_or_raise(
"rerankers"
) # import here for faster ops later
self.model_name = model_name
self.model_type = model_type
self.reranker = rerankers.Reranker(
model_name=model_name, model_type=model_type, **kwargs
)
def __str__(self):
return (
f"AnswerdotaiRerankers(model_type={self.model_type}, "
f"model_name={self.model_name})"
)
def _rerank(self, result_set: pa.Table, query: str):
result_set = self._handle_empty_results(result_set)
if len(result_set) == 0:

3
python/python/lancedb/rerankers/base.py
View File

@@ -40,6 +40,9 @@ class Reranker(ABC):
if ARROW_VERSION.major <= 13:
self._concat_tables_args = {"promote": True}
def __str__(self):
return self.__class__.__name__
def rerank_vector(
self,
query: str,

3
python/python/lancedb/rerankers/cohere.py
View File

@@ -44,6 +44,9 @@ class CohereReranker(Reranker):
self.top_n = top_n
self.api_key = api_key
def __str__(self):
return f"CohereReranker(model_name={self.model_name})"
@cached_property
def _client(self):
cohere = attempt_import_or_raise("cohere")

3
python/python/lancedb/rerankers/cross_encoder.py
View File

@@ -50,6 +50,9 @@ class CrossEncoderReranker(Reranker):
if self.device is None:
self.device = "cuda" if torch.cuda.is_available() else "cpu"
def __str__(self):
return f"CrossEncoderReranker(model_name={self.model_name})"
@cached_property
def model(self):
sbert = attempt_import_or_raise("sentence_transformers")

3
python/python/lancedb/rerankers/jinaai.py
View File

@@ -45,6 +45,9 @@ class JinaReranker(Reranker):
self.top_n = top_n
self.api_key = api_key
def __str__(self):
return f"JinaReranker(model_name={self.model_name})"
@cached_property
def _client(self):
import requests

3
python/python/lancedb/rerankers/linear_combination.py
View File

@@ -38,6 +38,9 @@ class LinearCombinationReranker(Reranker):
self.weight = weight
self.fill = fill
def __str__(self):
return f"LinearCombinationReranker(weight={self.weight}, fill={self.fill})"
def rerank_hybrid(
self,
query: str, # noqa: F821

6
python/python/lancedb/rerankers/mrr.py
View File

@@ -54,6 +54,12 @@ class MRRReranker(Reranker):
self.weight_vector = weight_vector
self.weight_fts = weight_fts
def __str__(self):
return (
f"MRRReranker(weight_vector={self.weight_vector}, "
f"weight_fts={self.weight_fts})"
)
def rerank_hybrid(
self,
query: str, # noqa: F821

3
python/python/lancedb/rerankers/openai.py
View File

@@ -43,6 +43,9 @@ class OpenaiReranker(Reranker):
self.column = column
self.api_key = api_key
def __str__(self):
return f"OpenaiReranker(model_name={self.model_name})"
def _rerank(self, result_set: pa.Table, query: str):
result_set = self._handle_empty_results(result_set)
if len(result_set) == 0:

3
python/python/lancedb/rerankers/rrf.py
View File

@@ -36,6 +36,9 @@ class RRFReranker(Reranker):
super().__init__(return_score)
self.K = K
def __str__(self):
return f"RRFReranker(K={self.K})"
def rerank_hybrid(
self,
query: str, # noqa: F821

3
python/python/lancedb/rerankers/voyageai.py
View File

@@ -52,6 +52,9 @@ class VoyageAIReranker(Reranker):
self.api_key = api_key
self.truncation = truncation
def __str__(self):
return f"VoyageAIReranker(model_name={self.model_name})"
@cached_property
def _client(self):
voyageai = attempt_import_or_raise("voyageai")

2
python/python/tests/test_hybrid_query.py
View File

@@ -163,9 +163,7 @@ async def test_explain_plan(table: AsyncTable):
table.query().nearest_to_text("dog").nearest_to([0.1, 0.1]).explain_plan(True)
)
assert "Vector Search Plan" in plan
assert "KNNVectorDistance" in plan
assert "FTS Search Plan" in plan
assert "LanceRead" in plan