morpheus.service.vdb.milvus_vector_db_service.MilvusVectorDBResourceService

(Latest Version)
class MilvusVectorDBResourceService(name, client)[source]

Bases: morpheus.service.vdb.vector_db_service.VectorDBResourceService

Represents a service for managing resources in a Milvus Vector Database.

Parameters
name

Name of the resource.

client

An instance of the MilvusClient for interaction with the Milvus Vector Database.

Methods

count(**kwargs) Returns number of rows/entities.
delete(expr, **kwargs) Delete vectors from the collection using expressions.
delete_by_keys(keys, **kwargs) Delete vectors by keys from the collection.
describe(**kwargs) Provides a description of the collection.
drop(**kwargs) Drop a collection, index, or partition in the Milvus vector database.
insert(data, **kwargs) Insert data into the vector database.
insert_dataframe(df, **kwargs) Insert a dataframe entires into the vector database.
query(query, **kwargs) Query data in a collection in the Milvus vector database.
retrieve_by_keys(keys, **kwargs) Retrieve the inserted vectors using their primary keys.
similarity_search(embeddings[, k]) Perform a similarity search within the collection.
update(data, **kwargs) Update data in the collection.
count(**kwargs)[source]

Returns number of rows/entities.

Parameters
**kwargs

Additional keyword arguments for the count operation.

Returns
int

Returns number of entities in the collection.

delete(expr, **kwargs)[source]

Delete vectors from the collection using expressions.

Parameters
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 deleted from the collection.

delete_by_keys(keys, **kwargs)[source]

Delete vectors by keys from the collection.

Parameters
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 deleted from the collection.

describe(**kwargs)[source]

Provides a description of the collection.

Parameters
**kwargs

Extra keyword arguments specific to the vector database implementation.

Returns
dict

Returns response content as a dictionary.

drop(**kwargs)[source]

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

This function allows you to drop a collection.

Parameters
**kwargs

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

insert(data, **kwargs)[source]

Insert data into the vector database.

Parameters
data

Data to be inserted into the collection.

**kwargs

Extra keyword arguments specific to the vector database implementation.

Returns
dict

Returns response content as a dictionary.

insert_dataframe(df, **kwargs)[source]

Insert a dataframe entires into the vector database.

Parameters
df

Dataframe to be inserted into the collection.

**kwargs

Extra keyword arguments specific to the vector database implementation.

Returns
dict

Returns response content as a dictionary.

query(query, **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
query

The search query, which can be a filter expression, by default None.

**kwargs

Additional keyword arguments for the search operation.

Returns
typing.Any

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

Raises
RuntimeError

If an error occurs during the search operation. If query argument is None and data keyword argument doesn’t exist. If data keyword arguement is None.

retrieve_by_keys(keys, **kwargs)[source]

Retrieve the inserted vectors using their primary keys.

Parameters
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.

Perform a similarity search within the collection.

Parameters
embeddings

Embeddings for which to perform the similarity search.

k

The number of nearest neighbors to return, by default 4.

**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.

update(data, **kwargs)[source]

Update data in the collection.

Parameters
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.

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