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Will Jones bcfc93cc88 fix(python): various fixes for async query builders (#2048 )

This includes several improvements and fixes to the Python Async query
builders:

1. The API reference docs show all the methods for each builder
2. The hybrid query builder now has all the same setter methods as the
vector search one, so you can now set things like `.distance_type()` on
a hybrid query.
3. Re-rankers are now properly hooked up and tested for FTS and vector
search. Previously the re-rankers were accidentally bypassed in unit
tests, because the builders overrode `.to_arrow()`, but the unit test
called `.to_batches()` which was only defined in the base class. Now all
builders implement `.to_batches()` and leave `.to_arrow()` to the base
class.
4. The `AsyncQueryBase` and `AsyncVectoryQueryBase` setter methods now
return `Self`, which provides the appropriate subclass as the type hint
return value. Previously, `AsyncQueryBase` had them all hard-coded to
`AsyncQuery`, which was unfortunate. (This required bringing in
`typing-extensions` for older Python version, but I think it's worth
it.)

2025-01-20 16:14:34 -08:00

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Python API Reference

This section contains the API reference for the Python API. There is a synchronous and an asynchronous API client.

The general flow of using the API is:

Use [lancedb.connect][] or [lancedb.connect_async][] to connect to a database.
Use the returned [lancedb.DBConnection][] or [lancedb.AsyncConnection][] to create or open tables.
Use the returned [lancedb.table.Table][] or [lancedb.AsyncTable][] to query or modify tables.

Installation

pip install lancedb

The following methods describe the synchronous API client. There is also an asynchronous API client.

Connections (Synchronous)

::: lancedb.connect

::: lancedb.db.DBConnection

Tables (Synchronous)

::: lancedb.table.Table

Querying (Synchronous)

::: lancedb.query.Query

::: lancedb.query.LanceQueryBuilder

::: lancedb.query.LanceVectorQueryBuilder

::: lancedb.query.LanceFtsQueryBuilder

::: lancedb.query.LanceHybridQueryBuilder

Embeddings

::: lancedb.embeddings.registry.EmbeddingFunctionRegistry

::: lancedb.embeddings.base.EmbeddingFunctionConfig

::: lancedb.embeddings.base.EmbeddingFunction

::: lancedb.embeddings.base.TextEmbeddingFunction

::: lancedb.embeddings.sentence_transformers.SentenceTransformerEmbeddings

::: lancedb.embeddings.openai.OpenAIEmbeddings

::: lancedb.embeddings.open_clip.OpenClipEmbeddings

::: lancedb.embeddings.utils.with_embeddings

Context

::: lancedb.context.contextualize

::: lancedb.context.Contextualizer

Full text search

::: lancedb.fts.create_index

::: lancedb.fts.populate_index

::: lancedb.fts.search_index

Utilities

::: lancedb.schema.vector

::: lancedb.merge.LanceMergeInsertBuilder

Integrations

Pydantic

::: lancedb.pydantic.pydantic_to_schema

::: lancedb.pydantic.vector

::: lancedb.pydantic.LanceModel

Reranking

::: lancedb.rerankers.linear_combination.LinearCombinationReranker

::: lancedb.rerankers.cohere.CohereReranker

::: lancedb.rerankers.colbert.ColbertReranker

::: lancedb.rerankers.cross_encoder.CrossEncoderReranker

::: lancedb.rerankers.openai.OpenaiReranker

Connections (Asynchronous)

Connections represent a connection to a LanceDb database and can be used to create, list, or open tables.

::: lancedb.connect_async

::: lancedb.db.AsyncConnection

Tables (Asynchronous)

Table hold your actual data as a collection of records / rows.

::: lancedb.table.AsyncTable

Indices (Asynchronous)

Indices can be created on a table to speed up queries. This section lists the indices that LanceDb supports.

::: lancedb.index.BTree

::: lancedb.index.Bitmap

::: lancedb.index.LabelList

::: lancedb.index.FTS

::: lancedb.index.IvfPq

::: lancedb.index.HnswPq

::: lancedb.index.HnswSq

::: lancedb.index.IvfFlat

Querying (Asynchronous)

Queries allow you to return data from your database. Basic queries can be created with the [AsyncTable.query][lancedb.table.AsyncTable.query] method to return the entire (typically filtered) table. Vector searches return the rows nearest to a query vector and can be created with the [AsyncTable.vector_search][lancedb.table.AsyncTable.vector_search] method.

::: lancedb.query.AsyncQuery options: inherited_members: true

::: lancedb.query.AsyncVectorQuery options: inherited_members: true

::: lancedb.query.AsyncFTSQuery options: inherited_members: true

::: lancedb.query.AsyncHybridQuery options: inherited_members: true

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