Changelog

Version 4.5.4

This patch version includes:

  • Fix parsing of creation/update time from old weaviate versions that write them in ns instead of ms

  • Support video_fields in multi2vec-palm which was added in Weaviate 1.24.4:

Version 4.5.3

This patch version includes:

  • Fix bug with hybrid searches without vector.

  • Support for new modules in Weaviate 1.24.2: - text2vec-voyageai - generative-mistral - Support new parameters for interference URLs in text2vec-transformers and multi2vec-clip

  • Support for new modules in Weaviate 1.24.3: - multi2vec-palm

Version 4.5.2

This patch version includes:

  • Fixes endpoint parameter for text2vec-palm

  • Adds support for GSE and TRIGRAM tokenizers

Version 4.5.1

This patch version includes:

  • Implements an extension to the filtering syntax allowing to pass lists of filters
    • Filter.all_of([f1, f2]]) is a shortcut for f1 & f2

    • Filter.any_of([f1, f2]]) is a shortcut for f1 | f2

    • Can all be chained and mixed together to create dynamic and complex filters

  • Introduces weaviate.classes.init.Timeout class allowing to define the timeout used when performing client init checks, in addition to connect and query

  • Fixes a bug when performing contains_any/contains_all filtering using an empty list

  • Adds the ability to limit the top_occurences return when performing aggregation queries

  • Allows for defining gRPC proxying of the client and fixes the parsing of http and https proxies

  • Allow None as a query value in BM25 and hybrid queries

  • Fix missing named vectors support in data.update and data.replace

  • Reimplement support for updating named vector configurations alongside the patched 1.24.1 server version

Version 4.5.0

This minor version includes:

  • Full support for the new named vectors feature available in the Weaviate 1.24 release.

  • Bugfixes to passing of Weaviate schema objects as collection configurations in certain edge cases.

  • Support use of Sagemaker when vectorizing with the text2vec-aws module.

  • Allow creation of collections that use the hnsw index with the bq quantizing strategy.

  • Allow specifying dimensions when vectorizing with the text2vec-openai module.

  • Python in-memory performance improvements when making queries .

Version 4.4.4

This patch version includes:

  • A fix to the validation logic of the apiEndpoint field of GenerativePaLMConfig object.

Version 4.4.3

This patch version includes

  • Fixes batching with references. Under some circumstances a reference could be added before its from-object and the reference would be lost.

  • Fixes readthedocs page

  • Small performance improvements for queries

Version 4.4.2

This patch version includes

  • Fixes client.is_ready().

  • Adds option to skip input parameter validation if you need to squeeze out some extra performance.

  • All functions that accept vectors now also accept numpy arrays, tensorflow arrays and pandas/polars dataframes as input.

  • Hybrid search accepts None as query for a pure vector search.

  • Adds FilterValue to weaviate.outputs.

  • Allows group_by: str in aggregation queries.

Version 4.4.1

This patch version includes

  • Allows strings as input for groupBy arguments for aggregation.

  • Fixes for rate limit batching.

Version 4.4.0

This version is the first full release for the Python v4 client and _requires_ weaviate versions >= 1.23.7.

Since the previous RC, there have been a number of improvements and final bug fixes. - The type of object.vector has changed from Optional[Dict[str, List[float]]] to Dict[str, List[float]] so that object.vector is never None. - Exporting and importing of collections has been tidied up and improved. - A number of methods have had input validation added to them. - Most exceptions are now unified under a few common classes.

For more information around the new client, see here: https://weaviate.io/developers/weaviate/client-libraries/python

Version 4.4.rc1

This version is a release candidate for the python v4 client.

There is a significant breaking change in this version in anticipation of the named vectors functionality of future Weaviate versions. - The vector property of Object has had its type changed from Optional[List[float]] to Optional[Dict[str, List[float]]]. - Accessing of the vector property has changed from object.vector to object.vector["default"]. - When using the client with future releases, other named vectors will be accessible as object.vector["name"].

Newly created (as of 15:00UTC 01/30/24) WCS sandbox instances are now capable of handling gRPC connections and so the client has been updated accordingly in its connect_to_wcs method. If you are using an old sandbox, make a new one and use the new one instead.

Minor bugfixes are also included.

Version 4.4.rc0

This version is a release candidate for the python v4 client.

All backward compatibility code is being removed and _requires_ weaviate versions >= 1.23.5.

All deprecated code has been removed. Check the migration guide (https://www.weaviate.io/developers/weaviate/client-libraries/python#migration-guides) how to update your code.

Improvements include: - Input validation - Embedded weaviate shows an error when the chosen port(s) are already occupied

Fixes include: - Filter chained references by reference count - Various bug with filtered aggregation - Aggregation with move to/away_from objects - Timeouts also apply to GRPC calls

Version 4.4.b9

This beta version has breaking changes, a migration guide is available at https://www.weaviate.io/developers/weaviate/client-libraries/python#migration-guides:

  • The batching algorithm has been streamlined and improved in its implementation and API surface.
    • There are now three types of batching that can be performed:
      • client.batch.dynamic() where the algorithm will automatically determine the optimal batch size and number of concurrent requests.

      • client.batch.fixed_size() where the user can specify the batch size and number of concurrent requests.

      • client.batch.rate_limit() where the user specifies the number of requests per minute that their third-party vectorization API can support.

    • If an exception is thrown in the background batching thread then this is surfaced to the main thread and re-raised in order to stop the batch.
      • Previously, this would silently error.

  • Enforces that all optional arguments to queries must be supplied as keyword arguments.

  • Adds runtime validation to all queries.

  • Renaming of prop to name in Filter.by_property.

  • Moving of the timeout argument in weaviate.connect_to_x methods into new argument additional_config: Optional[AdditionalConfig].

Improvements include: - Introduction of the .by_ref_count() method on Filter to filter on the number of references present in a reference property of an object.

  • This was previously achievable with Filter([refProp]).greater_than(0) but is now more explicit using the chaining syntax.

  • The syntax for sorting now feels similar to the new filtering syntax.
    • Supports method chaining like Sort.by_property(prop).by_creation_time() which will apply the sorting in the order they are chained, i.e., this chain

    is equivalent to the previous syntax of [Sort(prop), Sort("_creationTimeUnix")].

Fixes include: - The potential for deadlocks and data races when batching has been reduced. - Fixes a number of missing properties and poor docstrings in weaviate.connect_to_x methods. - Adds the missing offset parameter to all queries.

Version 4.4.b8

This beta version has breaking changes, a migration guide is available at https://www.weaviate.io/developers/weaviate/client-libraries/python#migration-guides:

  • Filters have been reworked and have a new syntax.
    • Coming from <=4.4.b6 you can replace:
      • Filter(path=property) with Filter.by_property(property)

      • Filter(path=["ref","target_class", "target_property"]) with Filter.by_ref("ref").by_property("target_property")

      • FilterMetadata.ByXX``with ``Filter.by_id/creation_time/update_time()

    • Coming from =4.4b7 you can replace:
      • Filter.by_ref().link_on("ref").by_property("target_property") with Filter.by_ref("ref").by_property("target_property")

Bugfixes include: - Error message when creating the client directly without calling connect_to_XXX. - Fix deadlock in new batching algorithm. - Fix skip_init_checks=True resulting in compatibility with Weaviate 1.22 only.

Version 4.4.b7

This beta version has breaking changes, a migration guide is available at https://www.weaviate.io/developers/weaviate/client-libraries/python#migration-guides:

  • For client.batch the add_reference method was revised. The to_object_collection parameter was removed and the other parameters were harmonized with collection.batch. Available parameters are now: from_uuid, from_collection, from_property, to and tenant.

  • It is no longer possible to use client.batch directly, you must use it as a context manager (with client.batch as batch)

  • Manual batch mode has been removed.

  • Dynamic batching (for batch_size and number of concurrent requests) is now default. Fixed-size batching can be configured with batch.configure_fixed_size(..).

  • Filters have been reworked and have a new syntax. You can replace:
    • Filter(path=property) with Filter.by_property(property)

    • Filter(path=["ref","target_class", "target_property"]) with Filter.by_ref().link_on("ref").by_property("target_property")

    • FilterMetadata.ByXX``with ``Filter.by_id/creation_time/update_time()

  • Importing directly from weaviate has been deprecated. Use import weaviate.classes as wvc instead and import from there.

  • Multi-target references functions have been moved to:
    • ReferenceProperty.MultiTarget

    • DataReference.MultiTarget

    • QueryReference.MultiTarget

  • Exception names are now compatible with PEP8, old names are still available but deprecated.

  • References can now be provided directly as UUIDs, str and Reference.XXX() has been deprecated. For multi-target references use ReferenceToMulti.

New functionality includes: - New batching algorithm that supports dynamic scaling of batch-size and number of concurrent requests. - New filter syntax that also supports structured filtering on references for normal properties and metadata. - All reference functions have unified input formats and now accept UUID, str and (where applicable) List[str], List[UUID]. - Returned types are now available in weaviate.output. - Add missing classes to weaviate.classes. - Add missing parameters to connect_to_XXX, all functions should support skipping of init checks and auth. - The client can now be used in a context manager with connect_to_XX(..) as client and all connections will be closed when exiting the manager. - New close function client.close() that needs to be called when not using a context manager to avoid stale connections and potential memory leaks. - Support for Phonenumber datatype. - Referenced objects now contain the name of their collection. - Adds collection.config.update_shards().

Bugfixes include: - object.reference is empty instead of None, if an object does not have a reference. - Fixes creating backups on weaviate master. - Add missing classes to wvc.

New client usage: - Client as a context manager:

  • Client without a context manager:

Version 4.4.b6

This beta version includes:

  • A fix to the _Property dataclass returned within collection.config.get() to include any nested_properties of object and object[] type properties

  • Fix batch inserts with empty lists

Version 4.4.b5

This beta version includes:

  • fetch_object_by_id with Weaviate 1.22 returned None for non-existing references

  • empty strings in returned objects caused a panic with weaviate 1.22

  • Support for nodes/cluster API

  • Speed up client creation when connecting to WCS using connect_to_wcs

  • Checks GRPC availability of Weaviate instance and return an error if it is not supported yet

  • Adds skip_init_checks to connect_to_wcs

With the next Weaviate version (1.23.1) this beta version supports: - Blob properties - Reranker

Version 4.4.b4

This beta version fixes an issue with being unable to disable PQ once enabled

Version 4.4.b3

This beta version fixes a naming issue: - All instances of quantitizer have been renamed to quantizer

Version 4.4.b2

This version works best with Weaviate 1.23 which was released on 2023-12-18.

This beta version has breaking changes, a migration guide is available at https://www.weaviate.io/developers/weaviate/client-libraries/python#migration-guides:

  • Refactor weaviate.classes structure

  • Rename various classes and methods:
    • In all vectorizer configuration methods: vectorize_class_name => vectorize_collection_name

    • object.metadata.creation_time_unix => object.metadata.creation_time which is now a datetime

    • object.metadata.last_update_time_unix => object.metadata.last_update_time which is now a datetime

    • MetadataQuery(creation_time_unix=.., last_update_time_unix= ..) => MetadataQuery(creation_time=.., last_update_time=..)

    • FromReference => QueryReference when querying references

  • Splits out references from properties when creating, changing and querying collections

  • UUID and UUID_ARRAY properties are now returned as typed UUID objects

  • DATE and DATE_ARRAY properties are now returned as typed datetime objects

  • vector_index_type``has been remove from ``collection.create() and is now determined automatically

  • Configure.vector_index() has been moved to Configure.VectorIndex.hnsw()

  • PQ can now be configured using Configure.VectorIndex.hnsw(quantitizer=Configure.VectorIndex.Quantitizer.pq(..options..))

  • object.metadata.vector was moved to object.vector and can be requested by using include_vector=True/False when querying

  • object.metadata.uuid was moved to object.uuid and is always available

  • Order of arguments in .data.update() and .replace() changed to accommodate not providing properties when updating.

  • In .data.reference_add, .reference_delete and .reference_replace the ref keyword was renamed to to

  • In collections.create() and .get() the keyword to provide generics was renamed from data_model to data_model_properties

New functionality includes:

  • Adds backup functionality to v4 client (client.backup) and directly to the collection (collection.backup)

  • Adds support for FLAT vector index

  • Adds binary quantization for FLAT vector index

  • Adds text2vec_jinaai static method to Configure.Vectorizer

  • Adds anyscale static method to Configure.Generative

  • Adds collection.batch for uploading to a single collection in batches

  • Adds methods for creating a collection from dict and exporting a collection config as dict

  • Adds support for geo-coordinates

  • Adds metadata filtering with FilterMetadata

  • Adds client.graphql_raw_query to use Weaviate features that are not directly supported.

  • Adds DataReferenceOneToMany which allows to add multiple references at once.

  • Adds validation of input parameters for non-mypy users.

  • Various performance improvements and bugfixes

Version 4.4.b1

This patch beta version includes:

  • Performance improvements when making queries

Version 4.4.b0

This minor beta version includes:

  • Adds support for connecting to WCS using the connect_to_wcs helper function

  • Changes default num_workers in client.batch from 1 to Python’s ThreadPoolExecutor default

  • Adds text2vec-aws and generative-aws static methods to Configure.Vectorizer and Configure.Generative

  • Tidy up stale docstrings

  • Add missing class exports

Version 4.3.b2

This patch beta version includes:

  • Fixes to the dataclass types returned by aggregate queries

Version 4.3.b1

This patch beta version includes:

  • Bump default Weaviate embedded version

Version 4.3.b0

This minor beta version includes:

  • Refactoring of the _Object class
    • _Object.metadata.uuid moved to _Object.uuid and is not Optional

    • _Object.metadata.vector moved to _Object.vector

  • Addition of include_vector argument to all queries
    • include_vector is False by default

  • return_metadata in queries is now Optional and defaults to None
    • _Object.metadata is now Optional as a result

  • Addition of include_vector to FromReference

  • Addition of ReferenceAnnotation for use when defining generic annotated cross references

Version 4.2.b2

This patch beta version includes:

  • Allow None when batch inserting using DataObject and BatchObject

Version 4.2.b1

This patch beta version includes:

  • Bug fix of the default alpha argument to query.hybrid

  • Extend the Configure.Vectorizer.multi2vec_ methods to accept lists of strings

  • Correctly export StopwordsPreset from weaviate.classes

  • Add generative_config and vectorizer_config to _CollectionConfig

  • Add skip_vectorization and vectorize_class_name to _PropertyConfig

Version 4.2.b0

This minor beta version includes:

  • A refactoring of the collection.aggregate namespace methods

  • Change Metrics to no longer accept the type_ argument

  • Instead, Metrics has multiple methods, e.g. .text(), for each type of metric

  • Allow return_metrics to be a single metric object or a list of metric objects in each aggregate query

Version 4.1.b2

This patch beta version includes:

  • Correctly exporting weaviate.collections.classes.aggregate.Metrics from weaviate.classes

Version 4.1.b1

This patch beta version includes:

  • Bumping the default embedded version to Weaviate latest

  • Adding the version argument to weaviate.connect_to_embedded to allow users to specify the embedded version

Version 4.1.b0

This minor beta version includes:

  • Makes total_count=True the default in aggregation queries to avoid unintentional GraphQL errors

  • Catches empty GraphQL errors in aggregation queries in case of user error

  • Renames class_name to collections within the collections.batch namespace

  • Adds get_vector to the collections.data namespace so that users can supply numpy and pytorch vectors

  • Adds __str__ magic method to Collections class so that print(collection) outputs the collection’s schema as pretty JSON

Version 4.0.b5

This patch beta version includes:

  • Update changelog

Version 4.0.b4

This patch beta version includes:

  • A small bug fix to remove a redundant print

  • Raising an exception from connect_to_wcs as gRPC support is not ready

  • Making _Collection a public class as Collection to be used in type hinting

Version 4.0.b3

This patch beta version includes:

  • Addition of batch_size to client.batch.configure for users who want automatic non-dynamic batching

  • Renaming of ConfigureUpdate to Reconfigure

  • Fixing of missing arguments to Configure.Vectorizer.text2vec_ methods

Version 4.0.b2

This patch beta version includes:

  • Fixes to the readthedocs documentation appearance

Version 4.0.b1

This beta version includes:

  • Introduction of the new beta Python collections client API
    • Streamlined and simplified client API for mutating and querying your data

    • Full support for gRPC batching and searching

    • End-to-end generics support for type safety

    • Python-native dataclasses for easy data manipulation

    • No more builder methods or raw dictionaries

  • Join the discussion and contribute your feedback here

Version 3.26.2

This patch version includes

  • Adds a timeout to wait_for_weaviate startup check

Version 3.26.1

This patch version includes

  • Fix backup creation with current weaviate master

Version 3.26.0

This minor version includes:

  • Support for Weaviate 1.23

  • Bump of the default version for Weaviate Embedded DB to v1.23.0

  • Adds support for nodes api verbosity option

Version 3.25.3

This patch version includes

  • Bump of the default version for Weaviate Embedded DB to v1.22.3

Version 3.25.2

This patch version includes

  • Fixes to the codebase naming convention and directory structure to prevent collision with Google’s proto-plus library

  • Fixes to the build method so that readthedocs.io builds the documentation correctly again

Version 3.25.1

This patch version includes:

  • Bump default embedded version to 1.22.0

Version 3.25.0

This minor version includes:

  • Support for new Weaviate nested objects on insert and query
    • client.data_object.create() now supports nested objects

    • client.query.get() now supports nested objects

  • Updates to use Weaviate’s v1 gRPC API

  • Support for batching with Weaviate>1.22.0 version and async vector indexing

  • Addition of the client.batch.wait_for_async_indexing() method to force block until async indexing is complete

  • Add tests for Python 3.12 to ensure compatibility

Version 3.24.2

This patch version includes:

  • Small fix to the batching process to ensure that failed multi-tenant objects are re-added to the batch with their tenant attached

Version 3.24.1

This patch version updates the changelog.rst that became stale over the last few releases

Version 3.24.0

This minor version includes:

  • Small fixes and improvements throughout the codebase:
    • Catching and reraising of JsonDecodeException for users to catch

    • Client-wide mypy error fixing and type hinting improvements

    • Fix for where filter operands in batch.delete_objects

    • Removal of buggy client-side schema validation

    • Package dependency updates

Version 3.23.2

This patch version includes:

  • Enforcing class name capitalization throughout the client

  • Further fixes to where filtering with ContainsAny/All

Version 3.23.1

This patch version includes:

  • Enabling of rerank-cohere module in EmbeddedWeaviate

  • Fixes for where filtering between query.get over GraphQL and batch.delete_objects over REST

Version 3.23.0

This minor version updates the client to work with Weaviate’s 1.21 version and includes:

  • Adds support for near<Media> filters when using the new multi2vec-bind module for neural searching on different media types
    • client.query.get().with_near_audio()

    • client.query.get().with_near_depth()

    • client.query.get().with_near_image() (unchanged from previous versions but usable by the module)

    • client.query.get().with_near_imu()

    • client.query.get().with_near_thermal()

    • client.query.get().with_near_video()

  • Deprecates configuring client.batch using client.batch() in favour of using client.batch.configure()
    • client.batch() will be removed in a future version

    • client.batch.configure() will return None in a future version

    • with client.batch as batch should be the standard way to initiate a batch

  • Adds support for new ContainsAny and ContainsAll filters when using .with_where

  • Adds support for updating individual tenants within a multi-tenancy class configuration: client.schema.update_class_tenants

  • Improves client.batch algorithm to choose batch size dynamically maximizing throughput

  • Provides sensible defaults to client.batch that do not cause unexpected damaging consequences like infinite batch sizes

  • Fixes bugs when using .with_where with valueText, valueString, and valueGeoRange types

Version 3.22.1

This patch version includes:

  • Fix “is client outdated”-check in air-gaped environments

  • Add tenant to batch delete

Version 3.22.0

This minor version includes:

  • Multi-tenancy

  • Aggregate with limit

  • Autocut

  • Fusion type for hybrid search

  • Client emits a warning when it is outdated (three minor version behind last release on pypi)

  • Increase default embedded version to 1.19.12

Version 3.21.0

This minor version includes: - Weaviate Embedded supports MacOs

Version 3.20.1

This patch version includes:

  • Fix imports without GRPC package

  • Improve shutdown handling with Weaviate Embedded

Version 3.20.0

This minor version includes:

  • Increase maximum version of request library to 2.31.0. This also updates to urllib 2.0. This may contain minor breaking changes if you use urllib in other projects in the same virtual environment.

  • Add licensing information to pypi package

  • Increase default embedded version to 1.19.7

Version 3.19.2

This patch version includes:

  • Add custom headers to all requests

  • Support properties field in generative groupedResult field

Version 3.19.1

This patch version includes:

  • Fixes imports of of weaviate_pb2.

Version 3.19.0

This minor version includes:

  • Increases default embedded version to 1.19.3

  • Clients emits warning if used weaviate version is too old (3 versions behind latest minor version)

  • Adds native support for querying reference properties
    result = client.query.get(
      "Article", ["title", "url", "wordCount", LinkTo(link_on="caller", linked_class="Person", properties=["name"])]
         )
    
  • Adds dataclasses to easier access to additional properties
    query = client.query.get("Test").with_additional(
                weaviate.AdditionalProperties(
                    uuid=True,
                    vector=True,
                    creationTimeUnix=True,
                    lastUpdateTimeUnix=True,
                    distance=True,
                )
            )
    
  • Typing fixes

  • Expand support for experimental GRPC API and add support for
    • BM25 and hybrid search

    • Additional properties (via dataclass shown above)

    • Querying reference properties (via dataclass shown above)

Version 3.18.0

This minor version includes:

  • Add support for properties with hybrid search

  • Fixes documentation publishing on readthedocs

Version 3.17.1

This patch version includes:

  • Fix schemas with new property keys indexFilterable and indexSearchable.

Version 3.17.0

This minor version includes:

  • Add support for groupBy to group objects:
    .with_group_by(properties=["caller"], groups=2, objects_per_group=3)
    
  • Add support for uuid and uuid[] datatypes.

  • Add schema.exists(class).

  • Add support for Support GQL Get{} tunable consistency
    resp = (
        client.query.get("Article", ["name"])
        .with_additional("isConsistent")
        .with_consistency_level(ConsistencyLevel.ALL)
        .do()
    )
    

Version 3.16.2

This patch version includes:

  • Fix url containing username and password.

Version 3.16.1

This patch version includes:

  • Fixes timeout error in detection of grpc.

Version 3.16.0

This minor version includes:

  • Experimental support for GRPC.
    • Can by enabled by installing the client with pip install weaviate-client[GRPC] or install the grpcio package manually.

    • To disable uninstall the grpcio package.

    • This will speed up certain GraphQL queries: Get with NearObject or NearVector if only non-reference queries are retrieved and no other options are set.

  • Removal of python 3.7 support. Minimum supported version is python 3.8

  • Removal of the WCS module. Note that the module was used to administrate old WCS instances and does not work anymore.

Version 3.15.6

This patch version includes:

  • Fix multi-line queries for BM25 and hybrid search.

Version 3.15.5

This patch version includes:

  • EmbeddedDB now supports latest and versions (eg 1.18.3) as version argument.

  • Removed cluster_hostname from EmbeddedOptions. It can still be set by using additional_env_vars.

  • Fix multi-line queries for generative search.

Version 3.15.4

This patch version includes:

  • Fix imports of EmbeddedDB on Mac. It now properly raises an exception that MacOS is currently unsupported.

Version 3.15.3

This patch version includes:

  • Improve embedded weaviate: Better folder structures, add support for env variables and support multiple versions.

  • Fix edge case for timeout retries: When all objects have been added, no empty batch will be send.

  • Fix authentication via additional_headers

Version 3.15.2

This patch version includes:

  • Fixes API keys with Weaviate setups that do not have OIDC enabled.

Version 3.15.1

This patch version includes:

  • Fixes refreshing of OIDC tokens on unstable connections

Version 3.15.0

This minor version includes:

  • GraphQL Multiple queries and aliases support
    client.query.multi_get(
            [
               client.query.get("Ship", ["name"]).with_alias("one"),
               client.query.get("Ship", ["size"]).with_alias("two"),
               client.query.get("Person", ["name"])
            ]
    
  • Adds support for embedded weaviate version
    from weaviate import Client
    from weaviate.embedded import EmbeddedOptions
    
    # Create the embedded client which automatically launches a Weaviate database in the background
    client = Client(embedded_options=EmbeddedOptions())
    

Version 3.14.0

This minor version includes:

  • Support for API-Keys
    client = weaviate.Client(url, auth_client_secret=AuthApiKey(api_key="my-secret-key"))
    

Version 3.13.0

This minor version includes:

  • Extend CRUD operations for single data objects and reference with consistency level.

  • Extend batch operations with consistency level.

  • Add Cursor api.

  • Add support for azure backup module.

Version 3.12.0

This minor version includes:

  • Adds with_generate in GetBuilder() which allows to use the generative openai module. Needs Weaviate with version >=v1.17.3.

  • Fix for empty OIDC scopes

  • New startup_period parameter in Client(). The client will wait for the given timeout for Weaviate to start. By default 5 seconds.

  • Improved error messages for where filters and authentication.

Version 3.11.0

This minor version includes:

  • New status code attribute for UnexpectedStatusCodeException that can be accessed like this:

    try:
        # your code
    except weaviate.UnexpectedStatusCodeException as err:
        print(err.status_code)
    
  • Fix for get_meta().

  • Caches server version at Client initialization. This improves batch reference creation performance.

  • Changes accepted data types for arguments from_object_uuid and to_object_uuid of the method add_reference() to str and uuid.UUID.

  • Adds automatic retry for failed objects. It can be configured using the weaviate_error_retries argument for the configure() or __call__(), and should be an instance of WeaviateErrorRetryConf. It can be used like this:
    • All errors:

      from weaviate import WeaviateErrorRetryConf
      
      with client.batch(
          weaviate_error_retries=WeaviateErrorRetryConf(number_retries=3),
      ) as batch:
          # Your code
      
    • Exclude errors, all the other errors will be retried:

      from weaviate import WeaviateErrorRetryConf
      
      with client.batch(
          weaviate_error_retries=WeaviateErrorRetryConf(number_retries=3, errors_to_exclude=["Ignore me", "other error to ignore"]),
      ) as batch:
          # Your code
      
    • Include errors, all the other errors will be ignored:

      from weaviate import WeaviateErrorRetryConf
      
      with client.batch(
          weaviate_error_retries=WeaviateErrorRetryConf(number_retries=3, errors_to_include=["error to retry", "other error to test again"]),
      ) as batch:
          # Your code
      
  • Adds new arguments sort and offset for get().

Version 3.10.0

This minor version includes:

  • Improves error message for error "413: Payload Too Large"

  • Adds new Client credential OIDC flow method:
    client_credentials_config = weaviate.AuthClientCredentials(
        client_secret = "client_secret",
        scope = "scope1 scope2" # optional, depends on the configuration of your identity provider
    )
    client = weaviate.Client("https://localhost:8080", auth_client_secret=client_credentials_config)
    
  • Improves size of batches on dynamic batching.

  • New limit argument to get() method of the DataObject client attribute.

  • Bump minimum version of request to 2.28.0

  • Adds support for node_name and consistency_level for both get() and get_by_id() of the DataObject client attribute. This can be used ONLY with Weaviate Server v1.17.0 or later.
  • Adds support for replication factor in schema. This can be used ONLY with Weaviate Server v1.17.0 or later. This can be configured in class schema like this:
    my_class = {
        "class": "MyClass",
        ...,
        "replicationConfig": {
            "factor": 1
        }
    }
    
  • Adds support for Bm25 for Get queries, with_bm25(). This can be used ONLY with Weaviate Server v1.17.0 or later.

  • Adds support for with_hybrid for Get queries, with_hybrid(). This can be used ONLY with Weaviate Server v1.17.0 or later.

Version 3.9.0

This minor version includes:

  • Authentication using Bearer token, by adding additional_headers to the Client initialization:
    client = weaviate.Client(
        url='http://localhost:8080',
        additional_headers={
            {"authorization": "Bearer <MY_TOKEN>"}
        }
    )
    
  • Multi-threading Batch import:
    • Now it is possible to import data using multi-threading. The number of threads can be set using the new argument num_workers in configure() and __call__(), defaults to 1 ( Use with care to not overload your weaviate instance.).
    • New argument connection_error_retries to retry on ConnectionError that can be set in configure() and __call__() or using the property getter/setter: client.batch.connection_error_retries to get the value and client.batch.connection_error_retries = 5 to set the value.
    • New method start() to create a BatchExecutor (ThreadExecutor). This method does NOT need to be called if using the Batch in a context manager (with). Also it is idempotent.
    • New method shutdown() to shutdown the existing BatchExecutor (ThreadExecutor) to release any resources that it is holding once the batch import is done. This method does NOT need to be called if using the Batch in a context manager (with). Also it is idempotent.
  • New Client attribute Cluster to check the status of the cluster nodes.
    • The method get_nodes_status() returns the status of each node as a list of dictionaries.
      client.cluster.get_nodes_status()
      
  • Fix for replace() and update() when using with Weaviate server >=v1.14.0.

  • New default timeout_config: (10, 60).

Version 3.8.0

This minor version includes:

  • Backup functionalities (Backup):
  • New Client attribute: backup to create, restore and get status of the backups. All backup operations MUST be done through Client.backup.

  • Added return value for add_data_object(), it now returns the UUID of the added object, if one was not set then an UUIDv4 will be generated.

Version 3.7.0

This minor version includes:

  • Adds rolling average (last 5 batches) for batch creation time used by Dynamic Batching method.

  • Adds ability to use get() without specifying any properties IF Additional Properties (with_additional()) are set before executing the query.

  • Adds base Weaviate Exception WeaviateBaseError.

  • Adds ability to set proxies. Can be set at Client initialization by using the new proxies or trust_env arguments.

  • Batch creates UUIDs (UUIDv4) for all added objects that do not have one at client side (fixes data duplication on Batch retries).

  • Adds new methods for WCS for instances that have authentication enabled:
    • get_users_of_cluster() to get users (emails) for all the users that have access to the created Weaviate instance.

    • add_user_to_cluster() to add users (email) to the created Weaviate instance.

    • remove_user_from_cluster() to remove user (email) from the created Weaviate instance.

Version 3.6.0

This minor version includes:

  • New function in check_batch_result() used to print errors from batch creation.

  • New function argument class_name for generate_local_beacon(), used ONLY with Weaviate Server version >= 1.14.0

    (defaults to None for backwards compatibility).

  • check_batch_result() is the default callback function for Batch (configure() and __call__()) (instead of None).
  • New method argument to_object_class_name for add_reference(), used ONLY with Weaviate Server version >= 1.14.0 (defaults to None for backwards compatibility).
  • Support for distance in GraphQL filters (only with Weaviate server >= 1.14.0).

  • For DataObject:
    • New method argument class_name for get_by_id(), get(), delete() exists(), used ONLY with Weaviate Server version >= 1.14.0 (defaults to None for backwards compatibility).
    • Deprecation Warning if Weaviate Server version >= 1.14.0 and class_name is None OR if Weaviate Server version < 1.14.0 and class_name is NOT None.

  • For Reference:
    • New method arguments from_class_name and to_class_name (to_class_names for update()) for add(), delete(), update(), used ONLY with Weaviate Server version >= 1.14.0 (defaults to None for backwards compatibility).
    • Deprecation Warning if Weaviate Server version >= 1.14.0 and class_name is None OR if Weaviate Server version < 1.14.0 and class_name is NOT None.

Version 3.5.1

This patch version fixes:

  • the rerank not being set bug in with_ask().
  • the bug when using double quotes() in question field in with_ask().
  • the bug where nearText filter checks for objects in moveXXX clause but never sets it.

Version 3.5.0

This minor version contains functionality for the new features introduced in Weaviate v1.13.0.

Version 3.4.2

This patch version fixes another bug in exists().

Version 3.4.1

This patch version fixes bug in exists().

Version 3.4.0

This minor version fixes the bug in setting the Schema’s invertedIndexConfig field.
New method get_class_shards() to get all shards configuration of a particular class.
New method update_class_shard() to update one/all shard/s configuration of a particular class.
Support for new Property field: tokenization.

Version 3.3.3

This patch version fixes the nearImage filter requests.

Version 3.3.2

This patch version allows using UUIDs in hex format for DataObject too i.e. UUIDs without hyphens.

Version 3.3.1

This patch version allows using UUIDs in hex format too i.e. UUIDs without hyphens.

Version 3.3.0

This minor version adds a new with_offset() for the Get queries. This method should be used with the with_limit(). This new feature (introduced in weaviate version 1.8.0) allows to use pagination functionality with the Get queries. The offset represents the start index of the objects to be returned, and the number of objects is specified by the with_limit() method.
For example, to list the first ten results, set limit: 10. Then, to “display the second page of 10”, set offset: 10, limit: 10 and so on. E.g. to show the 9th page of 10 results, set offset: 80, limit: 10 to effectively display results 81-90.

Version 3.2.5

This patch fixes the 'Batch' object is not callable error.

Version 3.2.4

All class_name and cross-refs dataType are implicitly capitalized. (This functionality is added because if class_name is not capitalized then Weaviate server does it for you, and this was leading to errors where the client and server have different configurations.)

Fixes/updates in Schema class:

  • This patch fixes the contains() to accept separate class schemas as argument i.e. it does not expect to have only this format: {"classes": [CLASS_1, CLASS_2, ...]}; now it is possible to pass just CLASS_X as well.

Version 3.2.3

This patch fixes the with_near_object(). It uses now explicit string literals for id/beacon in nearoOject clauses.

Version 3.2.2

This patch adds support for array data types: boolean[], date[].

Version 3.2.1

This patch adds support for array data types: int[], number[], text[], string[].

Version 3.2.0

Fixes/updates in WCS class:

  • Fixed progress bar for create(), it is being updated in Notebooks too, instead of printing each iteration on new line.

  • Method create() now prints the creation status above the bar.

Updates in gql sub-package:

  • New key-value autocorrect: <bool> introduced for the NearText and Ask filters. The autocorrect is enabled only if Weaviate server has the text-spellcheck module enabled. If autocorrect is True the query is corrected before the query is made. Usage example:
# with 'nearText' filter
client.query\
    .get('Article', ['title', 'author'])\
    .near_text(
        {
            'concepts': ['Ecconomy'],
            'autocorrect': True
        }
    )
    # the concept should be corrected to 'Economy'
# with 'ask' filter
client.query\
    .get('Article', ['title', 'author'])\
    .with_ask(
        {
            'question': 'When was the last financial crysis?',
            'autocorrect': True
        }
    )
    # the question should be corrected to 'When was the last financial crisis?'
  • New method with_additional() is added to GET the _additional properties. Usage example:
# single additional property with this GraphQL query
'''
{
    Get {
        Article {
            title
            author
            _additional {
                id
            }
        }
    }
}
'''
client.query\
    .get('Article', ['title', 'author'])\
    .with_additional('id') # argument as `str`

# multiple additional property with this GraphQL query
'''
{
    Get {
        Article {
            title
            author
            _additional {
                id
                certainty
            }
        }
    }
}
'''
client.query\
    .get('Article', ['title', 'author'])\
    .with_additional(['id', 'certainty']) # argument as `List[str]`

# additional properties as clause with this GraphQL query
'''
{
    Get {
        Article {
            title
            author
            _additional {
                classification {
                    basedOn
                    classifiedFields
                    completed
                    id
                    scope
                }
            }
        }
    }
}
'''
client.query\
    .get('Article', ['title', 'author'])\
    .with_additional(
        {
            'classification' : [
                'basedOn',
                'classifiedFields',
                'completed',
                'id',
                'scope'
            ]
        }
    ) # argument as `Dict[str, List[str]]`

# or with this GraphQL query
'''
{
    Get {
        Article {
            title
            author
            _additional {
                classification {
                    completed
                }
            }
        }
    }
}
'''
client.query\
    .get('Article', ['title', 'author'])\
    .with_additional(
        {
            'classification' : 'completed'
        }
    ) # argument as `Dict[str, str]`

# additional properties as clause and clause settings with this GraphQL query
'''
{
    Get {
        Article {
            title
            author
            _additional {
                token (
                    properties: ["content"]
                    limit: 10
                    certainty: 0.8
                ) {
                    certainty
                    endPosition
                    entity
                    property
                    startPosition
                    word
                }
            }
        }
    }
}
'''
clause = {
    'token': [
        'certainty',
        'endPosition',
        'entity',
        'property',
        'startPosition',
        'word',
    ]
}
settings = {
    'properties': ["content"],  # is required
    'limit': 10,                # optional, int
    'certainty': 0.8            # optional, float
}
client.query\
    .get('Article', ['title', 'author'])\
    .with_additional(
        (clause, settings)
    ) # argument as `Tuple[Dict[str, List[str]], Dict[str, Any]]`

# if the desired clause does not match any example above, then the clause can always
# be converted to string before passing it to the `.with_additional` method

Version 3.1.1

  • Fixes in WCS class:
    • Make WCS’s methods’ argument cluster_name case insensitive (lowercased inside the method) to match Weaviate Cloud Service’ naming convention, this fixes the error when Weaviate Cloud Service lowercases the cluster_name but the users are not aware of this and get the exception KeyError.

Version 3.1.0

  • New Batch methods:
  • Fixes in WCS class:
    • Authentication only with AuthClientPassword.

    • The create() argument module is renamed to modules and can also be a list of modules to enable for the WCS cluster. The argument can be used on the PROD WCS too.
    • The get_cluster_config() does not raise an exception if the cluster does not exist but returns a empty configuration.

    • The delete_cluster() does not raise an exception if the cluster does not exist.

  • Add phoneNumber to the Weaviate’s primitive types. Thanks to GitHub user @cdpierse.

  • Bug fix in Connection.

  • Fix ConnectionError handling.

  • Optimization in weaviate.batch.requests and weaviate.connect.connection.

Version 3.0.0

  • weaviate.tools module is REMOVED.
    • Batcher class is REMOVED.

    • WCS class is moved from the weaviate.tools to the new module weaviate.wcs

    • weaviate.tools.generate_uuid is REMOVED.

  • weaviate.util.generate_uuid5() is ADDED.

  • New Batch class implementation to replace the old one. This implementation uses the BatchRequest objects under the hood, which means that there is no need to create BatchRequest’s anymore. This new class implementation allows 3 different batch creations methods: manual, auto-create and auto-create with dynamic batching. See the Batch documentation for more information.
  • BatchRequest classes (ObjectsBatchRequest and ReferenceBatchRequest) are hidden from the user and should not be used anymore. This is due to the new Batch class implementation.
  • New Schema field is ADDED, “shardingConfig”. It can bu used with Weaviate version >= 1.6.0.
  • New method update_config() used to update mutable schema configuration (like efConstruction, …).