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<!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit - **Documentation** - Expanded Python API reference with new entries for table metadata, tagging, remote client configuration, and index statistics. - Added documentation for new classes and modules in both synchronous and asynchronous sections, including `FragmentStatistics`, `FragmentSummaryStats`, `Tags`, `AsyncTags`, `IndexStatistics`, and remote configuration options. <!-- end of auto-generated comment: release notes by coderabbit.ai -->
3.7 KiB
Python API Reference
This section contains the API reference for the Python API of LanceDB. Both synchronous and asynchronous APIs are available.
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
::: lancedb.table.FragmentStatistics
::: lancedb.table.FragmentSummaryStats
::: lancedb.table.Tags
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
Remote configuration
::: lancedb.remote.ClientConfig
::: lancedb.remote.TimeoutConfig
::: lancedb.remote.RetryConfig
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
::: lancedb.table.AsyncTags
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
::: lancedb.table.IndexStatistics
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