A path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.
Optional
autoOptional
numA map of aliases for constructor args. Keys are the attribute names, e.g. "foo". Values are the alias that will replace the key in serialization. This is used to eg. make argument names match Python.
A map of additional attributes to merge with constructor args. Keys are the attribute names, e.g. "foo". Values are the attribute values, which will be serialized. These attributes need to be accepted by the constructor as arguments.
The final serialized identifier for the module.
A map of secrets, which will be omitted from serialization. Keys are paths to the secret in constructor args, e.g. "foo.bar.baz". Values are the secret ids, which will be used when deserializing.
Adds documents to the Milvus database.
Array of Document instances to be added to the database.
Promise resolving to void.
Adds vectors to the Milvus database.
Array of vectors to be added to the database.
Array of Document instances associated with the vectors.
Promise resolving to void.
Optional
kOrFields: number | Partial<VectorStoreRetrieverInput<Milvus>>Optional
filter: stringOptional
callbacks: CallbacksOptional
tags: string[]Optional
metadata: Record<string, unknown>Optional
verbose: booleanCreates a collection in the Milvus database.
Array of vectors to be added to the new collection.
Array of Document instances to be added to the new collection.
Promise resolving to void.
Ensures that a collection exists in the Milvus database.
Optional
vectors: number[][]Optional array of vectors to be used if a new collection needs to be created.
Optional
documents: Document<Record<string, any>>[]Optional array of Document instances to be used if a new collection needs to be created.
Promise resolving to void.
Searches for vectors in the Milvus database that are similar to a given vector.
Vector to compare with the vectors in the database.
Number of similar vectors to return.
Optional
filter: stringOptional filter to apply to the search.
Promise resolving to an array of tuples, each containing a Document instance and a similarity score.
Optional
maxReturn documents selected using the maximal marginal relevance. Maximal marginal relevance optimizes for similarity to the query AND diversity among selected documents.
Text to look up documents similar to.
Static
fromCreates a Milvus instance from a set of Document instances.
Array of Document instances to be added to the database.
Embeddings instance used to generate vector embeddings for the documents.
Optional
dbConfig: MilvusLibArgsOptional configuration for the Milvus database.
Promise resolving to a new Milvus instance.
Static
fromCreates a Milvus instance from an existing collection in the Milvus database.
Embeddings instance used to generate vector embeddings for the documents in the collection.
Configuration for the Milvus database.
Promise resolving to a new Milvus instance.
Static
fromCreates a Milvus instance from a set of texts and their associated metadata.
Array of texts to be added to the database.
Array of metadata objects associated with the texts.
Embeddings instance used to generate vector embeddings for the texts.
Optional
dbConfig: MilvusLibArgsOptional configuration for the Milvus database.
Promise resolving to a new Milvus instance.
Static
lc_Generated using TypeDoc
Class for interacting with a Milvus database. Extends the VectorStore class.