## Problem
When applying hard filters that result in zero matches, hybrid search
crashes with `IndexError: list index out of range` during reranking.
This happens because empty result tables are passed through the full
reranker pipeline, which expects at least one result.
Traceback from the issue:
```
lancedb/query.py: in _combine_hybrid_results
results = reranker.rerank_hybrid(fts_query, vector_results, fts_results)
lancedb/rerankers/answerdotai.py: in rerank_hybrid
combined_results = self._rerank(combined_results, query)
...
IndexError: list index out of range
```
## Fix
Added an early return in `_combine_hybrid_results` when both vector and
FTS results are empty. Instead of passing empty tables through
normalization, reranking, and score restoration (which can fail in
various ways), we now build a properly-typed empty result table with the
`_relevance_score` column and return it directly.
## Test
Added `test_empty_hybrid_result_reranker` that exercises
`_combine_hybrid_results` directly with empty vector and FTS tables,
verifying:
- Returns empty table with correct schema
- Includes `_relevance_score` column
- Respects `with_row_ids` flag
Closes#2425
The basic idea of MRR is this -
https://www.evidentlyai.com/ranking-metrics/mean-reciprocal-rank-mrr
I've implemented a weighted version for allowing user to set weightage
between vector and fts.
The gist is something like this
### Scenario A: Document at rank 1 in one set, absent from another
```
# Assuming equal weights: weight_vector = 0.5, weight_fts = 0.5
vector_rr = 1.0 # rank 1 → 1/1 = 1.0
fts_rr = 0.0 # absent → 0.0
weighted_mrr = 0.5 × 1.0 + 0.5 × 0.0 = 0.5
```
### Scenario B: Document at rank 1 in one set, rank 2 in another
```
# Same weights: weight_vector = 0.5, weight_fts = 0.5
vector_rr = 1.0 # rank 1 → 1/1 = 1.0
fts_rr = 0.5 # rank 2 → 1/2 = 0.5
weighted_mrr = 0.5 × 1.0 + 0.5 × 0.5 = 0.5 + 0.25 = 0.75
```
And so with `return_score="all"` the result looks something like this
(this is from the reranker tests).
Because this is a weighted rank based reranker, some results might have
the same score
```
text vector _distance _rowid _score _relevance_score
0 I am your father [-0.010703234, 0.069315575, 0.030076642, 0.002... 8.149148e-13 8589934598 10.978719 1.000000
1 the ground beneath my feet [-0.09500901, 0.00092102867, 0.0755851, 0.0372... 1.376896e+00 8589934604 NaN 0.250000
2 I find your lack of faith disturbing [0.07525753, -0.0100010475, 0.09990541, 0.0209... NaN 8589934595 3.483394 0.250000
3 but I don't wanna die [0.033476487, -0.011235877, -0.057625435, -0.0... 1.538222e+00 8589934610 1.130355 0.238095
4 if you strike me down I shall become more powe... [0.00432201, 0.030120496, 5.3317923e-05, 0.033... 1.381086e+00 8589934594 0.715157 0.216667
5 I see a salty message written in the eves [-0.04213107, 0.0016004723, 0.061052393, -0.02... 1.638301e+00 8589934603 1.043785 0.133333
6 but his son was mortal [0.012462767, 0.049041674, -0.057339743, -0.04... 1.421566e+00 8589934620 NaN 0.125000
7 I've got a bad feeling about this [-0.06973199, -0.029960092, 0.02641632, -0.031... NaN 8589934596 1.043785 0.125000
8 now that's a name I haven't heard in a long time [-0.014374257, -0.013588792, -0.07487557, 0.03... 1.597573e+00 8589934593 0.848772 0.118056
9 he was a god [-0.0258895, 0.11925236, -0.029397793, 0.05888... 1.423147e+00 8589934618 NaN 0.100000
10 I wish they would make another one [-0.14737535, -0.015304729, 0.04318139, -0.061... NaN 8589934622 1.043785 0.100000
11 Kratos had a son [-0.057455737, 0.13734367, -0.03537109, -0.000... 1.488075e+00 8589934617 NaN 0.083333
12 I don't wanna live like this [-0.0028891307, 0.015214227, 0.025183653, 0.08... NaN 8589934609 1.043785 0.071429
13 I see a mansard roof through the trees [0.052383978, 0.087759204, 0.014739997, 0.0239... NaN 8589934602 1.043785 0.062500
14 great kid don't get cocky [-0.047043696, 0.054648954, -0.008509666, -0.0... 1.618125e+00 8589934592 NaN 0.055556
```
Previously `return_score="all"` was supported only for the default
reranker (RRF) and not the model based rerankers.
This adds support for keeping all scores in the base reranker so that
all model based rerankers can use it. Its a slower path than keeping
just the relevance score but can be useful in debugging
I found some edge cases while running experiments that - depending on
the base reranking libraries, some of them don't handle empty lists
well. This PR manually checks if the result set to be reranked is empty
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **Bug Fixes**
- Enhanced search result processing by ensuring that reordering only
occurs when valid, non-empty results are available, thereby preventing
unnecessary operations and potential errors.
- **Tests**
- Added automated tests to verify that empty search result sets are
handled correctly, ensuring consistent behavior across various
rerankers.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
@wjones127 is there a standard way you guys setup your virtualenv? I can
either relist all the dependencies in the pyright precommit section, or
specify a venv, or the user has to be in the virtual environment when
they run git commit. If the venv location was standardized or a python
manager like `uv` was used it would be easier to avoid duplicating the
pyright dependency list.
Per your suggestion, in `pyproject.toml` I added in all the passing
files to the `includes` section.
For ruff I upgraded the version and removed "TCH" which doesn't exist as
an option.
I added a `pyright_report.csv` which contains a list of all files sorted
by pyright errors ascending as a todo list to work on.
I fixed about 30 issues in `table.py` stemming from str's being passed
into methods that required a string within a set of string Literals by
extracting them into `types.py`
Can you verify in the rust bridge that the schema should be a property
and not a method here? If it's a method, then there's another place in
the code where `inner.schema` should be `inner.schema()`
``` python
class RecordBatchStream:
@property
def schema(self) -> pa.Schema: ...
```
Also unless the `_lancedb.pyi` file is wrong, then there is no
`__anext__` here for `__inner` when it's not an `AsyncGenerator` and
only `next` is defined:
``` python
async def __anext__(self) -> pa.RecordBatch:
return await self._inner.__anext__()
if isinstance(self._inner, AsyncGenerator):
batch = await self._inner.__anext__()
else:
batch = await self._inner.next()
if batch is None:
raise StopAsyncIteration
return batch
```
in the else statement, `_inner` is a `RecordBatchStream`
```python
class RecordBatchStream:
@property
def schema(self) -> pa.Schema: ...
async def next(self) -> Optional[pa.RecordBatch]: ...
```
---------
Co-authored-by: Will Jones <willjones127@gmail.com>
BREAKING CHANGE: embedding function implementations in Node need to now
call `resolveVariables()` in their constructors and should **not**
implement `toJSON()`.
This tries to address the handling of secrets. In Node, they are
currently lost. In Python, they are currently leaked into the table
schema metadata.
This PR introduces an in-memory variable store on the function registry.
It also allows embedding function definitions to label certain config
values as "sensitive", and the preprocessing logic will raise an error
if users try to pass in hard-coded values.
Closes#2110Closes#521
---------
Co-authored-by: Weston Pace <weston.pace@gmail.com>
Fixes#2031
When we do hybrid search, we normalize the scores. We do this
calculation in-place, because the Rerankers expect the `_distance` and
`_score` columns to be the normalized ones. So I've changed the logic so
that we restore the original distance and scores by matching on row ids.
related to #2014
this fixes:
- linear reranker may lost some results if the merging consumes all
vector results earlier than fts results
- linear reranker inverts the fts score but only vector distance can be
inverted
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
- Enforce all rerankers always return _relevance_score. This was already
loosely done in tests before but based on user feedback its better to
always have _relevance_score present in all reranked results
- Deprecate LinearCombinationReranker in docs. And also fix a case where
it would not return _relevance_score if one result set was missing
Currently, the only documented way of performing hybrid search is by
using embedding API and passing string queries that get automatically
embedded. There are use cases where users might like to pass vectors and
text manually instead.
This ticket contains more information and historical context -
https://github.com/lancedb/lancedb/issues/937
This breaks a undocumented pathway that allowed passing (vector, text)
tuple queries which was intended to be temporary, so this is marked as a
breaking change. For all practical purposes, this should not really
impact most users
### usage
```
results = table.search(query_type="hybrid")
.vector(vector_query)
.text(text_query)
.limit(5)
.to_pandas()
```
This PR:
- Adds missing license headers
- Integrates with answerdotai Rerankers package
- Updates ColbertReranker to subclass answerdotai package. This is done
to keep backwards compatibility as some users might be used to importing
ColbertReranker directly
- Set `trust_remote_code` to ` True` by default in CrossEncoder and
sentence-transformer based rerankers
- Update ColBertReranker architecture: The current implementation
doesn't use the right arch. This PR uses the implementation in Rerankers
library. Fixes https://github.com/lancedb/lancedb/issues/1546
Benchmark diff (hit rate):
Hybrid - 91 vs 87
reranked vector - 85 vs 80
- Reranking in FTS is basically disabled in main after last week's FTS
updates. I think there's no blocker in supporting that?
- Allow overriding accelerators: Most transformer based Rerankers and
Embedding automatically select device. This PR allows overriding those
settings by passing `device`. Fixes:
https://github.com/lancedb/lancedb/issues/1487
---------
Co-authored-by: BubbleCal <bubble-cal@outlook.com>
Lance now supports FTS, so add it into lancedb Python, TypeScript and
Rust SDKs.
For Python, we still use tantivy based FTS by default because the lance
FTS index now misses some features of tantivy.
For Python:
- Support to create lance based FTS index
- Support to specify columns for full text search (only available for
lance based FTS index)
For TypeScript:
- Change the search method so that it can accept both string and vector
- Support full text search
For Rust
- Support full text search
The others:
- Update the FTS doc
BREAKING CHANGE:
- for Python, this renames the attached score column of FTS from "score"
to "_score", this could be a breaking change for users that rely the
scores
---------
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
Currently targeting the following usage:
```
from lancedb.rerankers import CrossEncoderReranker
reranker = CrossEncoderReranker()
query = "hello"
res1 = table.search(query, vector_column_name="vector").limit(3)
res2 = table.search(query, vector_column_name="text_vector").limit(3)
res3 = table.search(query, vector_column_name="meta_vector").limit(3)
reranked = reranker.rerank_multivector(
[res1, res2, res3],
deduplicate=True,
query=query # some reranker models need query
)
```
- This implements rerank_multivector function in the base reranker so
that all rerankers that implement rerank_vector will automatically have
multivector reranking support
- Special case for RRF reranker that just uses its existing
rerank_hybrid fcn to multi-vector reranking.
---------
Co-authored-by: Weston Pace <weston.pace@gmail.com>
SDK
Python
Description
Exposes pyarrow batch api during query execution - relevant when there
is no vector search query, dataset is large and the filtered result is
larger than memory.
---------
Co-authored-by: Ishani Ghose <isghose@amazon.com>
Co-authored-by: Chang She <759245+changhiskhan@users.noreply.github.com>
solves https://github.com/lancedb/lancedb/issues/1086
Usage Reranking with FTS:
```
retriever = db.create_table("fine-tuning", schema=Schema, mode="overwrite")
pylist = [{"text": "Carson City is the capital city of the American state of Nevada. At the 2010 United States Census, Carson City had a population of 55,274."},
{"text": "The Commonwealth of the Northern Mariana Islands is a group of islands in the Pacific Ocean that are a political division controlled by the United States. Its capital is Saipan."},
{"text": "Charlotte Amalie is the capital and largest city of the United States Virgin Islands. It has about 20,000 people. The city is on the island of Saint Thomas."},
{"text": "Washington, D.C. (also known as simply Washington or D.C., and officially as the District of Columbia) is the capital of the United States. It is a federal district. "},
{"text": "Capital punishment (the death penalty) has existed in the United States since before the United States was a country. As of 2017, capital punishment is legal in 30 of the 50 states."},
{"text": "North Dakota is a state in the United States. 672,591 people lived in North Dakota in the year 2010. The capital and seat of government is Bismarck."},
]
retriever.add(pylist)
retriever.create_fts_index("text", replace=True)
query = "What is the capital of the United States?"
reranker = CohereReranker(return_score="all")
print(retriever.search(query, query_type="fts").limit(10).to_pandas())
print(retriever.search(query, query_type="fts").rerank(reranker=reranker).limit(10).to_pandas())
```
Result
```
text vector score
0 Capital punishment (the death penalty) has exi... [0.099975586, 0.047943115, -0.16723633, -0.183... 0.729602
1 Charlotte Amalie is the capital and largest ci... [-0.021255493, 0.03363037, -0.027450562, -0.17... 0.678046
2 The Commonwealth of the Northern Mariana Islan... [0.3684082, 0.30493164, 0.004600525, -0.049407... 0.671521
3 Carson City is the capital city of the America... [0.13989258, 0.14990234, 0.14172363, 0.0546569... 0.667898
4 Washington, D.C. (also known as simply Washing... [-0.0090408325, 0.42578125, 0.3798828, -0.3574... 0.653422
5 North Dakota is a state in the United States. ... [0.55859375, -0.2109375, 0.14526367, 0.1634521... 0.639346
text vector score _relevance_score
0 Washington, D.C. (also known as simply Washing... [-0.0090408325, 0.42578125, 0.3798828, -0.3574... 0.653422 0.979977
1 The Commonwealth of the Northern Mariana Islan... [0.3684082, 0.30493164, 0.004600525, -0.049407... 0.671521 0.299105
2 Capital punishment (the death penalty) has exi... [0.099975586, 0.047943115, -0.16723633, -0.183... 0.729602 0.284874
3 Carson City is the capital city of the America... [0.13989258, 0.14990234, 0.14172363, 0.0546569... 0.667898 0.089614
4 North Dakota is a state in the United States. ... [0.55859375, -0.2109375, 0.14526367, 0.1634521... 0.639346 0.063832
5 Charlotte Amalie is the capital and largest ci... [-0.021255493, 0.03363037, -0.027450562, -0.17... 0.678046 0.041462
```
## Vector Search usage:
```
query = "What is the capital of the United States?"
reranker = CohereReranker(return_score="all")
print(retriever.search(query).limit(10).to_pandas())
print(retriever.search(query).rerank(reranker=reranker, query=query).limit(10).to_pandas()) # <-- Note: passing extra string query here
```
Results
```
text vector _distance
0 Capital punishment (the death penalty) has exi... [0.099975586, 0.047943115, -0.16723633, -0.183... 39.728973
1 Washington, D.C. (also known as simply Washing... [-0.0090408325, 0.42578125, 0.3798828, -0.3574... 41.384884
2 Carson City is the capital city of the America... [0.13989258, 0.14990234, 0.14172363, 0.0546569... 55.220200
3 Charlotte Amalie is the capital and largest ci... [-0.021255493, 0.03363037, -0.027450562, -0.17... 58.345654
4 The Commonwealth of the Northern Mariana Islan... [0.3684082, 0.30493164, 0.004600525, -0.049407... 60.060867
5 North Dakota is a state in the United States. ... [0.55859375, -0.2109375, 0.14526367, 0.1634521... 64.260544
text vector _distance _relevance_score
0 Washington, D.C. (also known as simply Washing... [-0.0090408325, 0.42578125, 0.3798828, -0.3574... 41.384884 0.979977
1 The Commonwealth of the Northern Mariana Islan... [0.3684082, 0.30493164, 0.004600525, -0.049407... 60.060867 0.299105
2 Capital punishment (the death penalty) has exi... [0.099975586, 0.047943115, -0.16723633, -0.183... 39.728973 0.284874
3 Carson City is the capital city of the America... [0.13989258, 0.14990234, 0.14172363, 0.0546569... 55.220200 0.089614
4 North Dakota is a state in the United States. ... [0.55859375, -0.2109375, 0.14526367, 0.1634521... 64.260544 0.063832
5 Charlotte Amalie is the capital and largest ci... [-0.021255493, 0.03363037, -0.027450562, -0.17... 58.345654 0.041462
```
This changes `lancedb` from a "pure python" setuptools project to a
maturin project and adds a rust lancedb dependency.
The async python client is extremely minimal (only `connect` and
`Connection.table_names` are supported). The purpose of this PR is to
get the infrastructure in place for building out the rest of the async
client.
Although this is not technically a breaking change (no APIs are
changing) it is still a considerable change in the way the wheels are
built because they now include the native shared library.
