morpheus.service.vdb.milvus_vector_db_service.MilvusVectorDBService

Bases: <a href="morpheus.service.vdb.vector_db_service.VectorDBService.html#morpheus.service.vdb.vector_db_service.VectorDBService">morpheus.service.vdb.vector_db_service.VectorDBService</a>

Service class for Milvus Vector Database implementation. This class provides functions for interacting with a Milvus vector database.

Parameters

host

The hostname or IP address of the Milvus server.

port

The port number for connecting to the Milvus server.

alias

Alias for the Milvus connection, by default “default”.

truncate_long_strings

When true, truncate strings values that are longer than the max length of the field

**kwargs

Additional keyword arguments specific to the Milvus connection configuration.

Methods

close()[source]

Close the connection to the Milvus vector database.

This method disconnects from the Milvus vector database by removing the connection.

count(name, **kwargs)[source]

Returns number of rows/entities in the given collection.

Parameters

name

Name of the collection.

**kwargs

Additional keyword arguments for the count operation.

Returns

int

Returns number of entities in the collection.

create(name, overwrite=False, **kwargs)[source]

Create a collection in the Milvus vector database with the specified name and configuration. This method creates a new collection in the Milvus vector database with the provided name and configuration options. If the collection already exists, it can be overwritten if the overwrite parameter is set to True.

Parameters

name

Name of the collection to be created.

overwrite

If True, the collection will be overwritten if it already exists, by default False.

**kwargs

Additional keyword arguments containing collection configuration.

Raises

ValueError

If the provided schema fields configuration is empty.

create_from_dataframe(name, df, overwrite=False, **kwargs)[source]

Create collections in the vector database.

Parameters

name

Name of the collection.

df

The dataframe to create the collection from.

overwrite

Whether to overwrite the collection if it already exists. Default is False.

**kwargs

Extra keyword arguments specific to the vector database implementation.

delete(name, expr, **kwargs)[source]

Delete vectors from the collection using expressions.

Parameters

name

Name of the collection.

expr

Delete expression.

**kwargs

Extra keyword arguments specific to the vector database implementation.

Returns

dict[str, typing.Any]

Returns result of the given keys that are delete from the collection.

delete_by_keys(name, keys, **kwargs)[source]

Delete vectors by keys from the collection.

Parameters

name

Name of the collection.

keys

Primary keys to delete vectors.

**kwargs

Extra keyword arguments specific to the vector database implementation.

Returns

typing.Any

Returns result of the given keys that are delete from the collection.

describe(name, **kwargs)[source]

Describe the collection in the vector database.

Parameters

name

Name of the collection.

**kwargs

Additional keyword arguments specific to the Milvus vector database.

Returns

dict

Returns collection information.

drop(name, **kwargs)[source]

Drop a collection, index, or partition in the Milvus vector database.

This method allows you to drop a collection, an index within a collection, or a specific partition within a collection in the Milvus vector database.

Parameters

name

Name of the collection, index, or partition to be dropped.

**kwargs

Additional keyword arguments for specifying the type and partition name (if applicable).

Raises

ValueError

If mandatory arguments are missing or if the provided ‘collection’ value is invalid.

classmethod get_collection_lock(name)[source]

Get a lock for a given collection name.

Parameters

name

Name of the collection for which to acquire the lock.

Returns

threading.Lock

A thread lock specific to the given collection name.

has_store_object(name)[source]

Check if a collection exists in the Milvus vector database.

Parameters

name

Name of the collection to check.

Returns

bool

True if the collection exists, False otherwise.

insert(name, data, **kwargs)[source]

Insert a collection specific data in the Milvus vector database.

Parameters

name

Name of the collection to be inserted.

data

Data to be inserted in the collection.

**kwargs

Additional keyword arguments containing collection configuration.

Returns

dict

Returns response content as a dictionary.

Raises

RuntimeError

If the collection not exists exists.

insert_dataframe(name, df, **kwargs)[source]

Converts dataframe to rows and insert to a collection in the Milvus vector database.

Parameters

name

Name of the collection to be inserted.

df

Dataframe to be inserted in the collection.

**kwargs

Additional keyword arguments containing collection configuration.

Returns

dict

Returns response content as a dictionary.

Raises

RuntimeError

If the collection not exists exists.

list_store_objects(**kwargs)[source]

List the names of all collections in the Milvus vector database.

Returns

list[str]

A list of collection names.

query(name, query=None, **kwargs)[source]

Query data in a collection in the Milvus vector database.

This method performs a search operation in the specified collection/partition in the Milvus vector database.

Parameters

name

Name of the collection to search within.

query

The search query, which can be a filter expression.

**kwargs

Additional keyword arguments for the search operation.

Returns

typing.Any

The search result, which can vary depending on the query and options.

release_resource(name)[source]

Release a loaded collection from the memory.

Parameters

name

Name of the collection to release.

retrieve_by_keys(name, keys, **kwargs)[source]

Retrieve the inserted vectors using their primary keys from the Collection.

Parameters

name

Name of the collection.

keys

Primary keys to get vectors for. Depending on pk_field type it can be int or str or a list of either.

**kwargs

Additional keyword arguments for the retrieval operation.

Returns

list[typing.Any]

Returns result rows of the given keys from the collection.

async similarity_search(name, **kwargs)[source]

Perform a similarity search within the collection.

Parameters

name

Name of the collection.

**kwargs

Extra keyword arguments specific to the vector database implementation.

Returns

list[dict]

Returns a list of dictionaries representing the results of the similarity search.

transform(data, **kwargs)[source]

Transform data according to the specific vector database implementation.

Parameters

data

Data to be updated in the resource.

**kwargs

Extra keyword arguments specific to the vector database implementation.

Returns

typing.Any

Returns transformed data as per the implementation.

update(name, data, **kwargs)[source]

Update data in the vector database.

Parameters

name

Name of the collection.

data

Data to be updated in the collection.

**kwargs

Extra keyword arguments specific to upsert operation.

Returns

dict[str, typing.Any]

Returns result of the updated operation stats.