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 filterA 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.
Method for adding documents to the RedisVectorStore. It first converts the documents to texts and then adds them as vectors.
The documents to add.
Optional options: RedisAddOptionsOptional parameters for adding the documents.
A promise that resolves when the documents have been added.
Method for adding vectors to the RedisVectorStore. It checks if the index exists and creates it if it doesn't, then adds the vectors in batches.
The vectors to add.
The documents associated with the vectors.
A promise that resolves when the vectors have been added.
Optional kOrFields: number | Partial<VectorStoreRetrieverInput<RedisVectorStore>>Optional filter: RedisVectorStoreFilterTypeOptional callbacks: CallbacksOptional tags: string[]Optional metadata: Record<string, unknown>Optional verbose: booleanMethod for dropping an index from the RedisVectorStore.
Optional deleteDocuments: booleanOptional boolean indicating whether to drop the associated documents.
A promise that resolves to a boolean indicating whether the index was dropped.
Method for performing a similarity search in the RedisVectorStore. It returns the documents and their scores.
The query vector.
The number of nearest neighbors to return.
Optional filter: RedisVectorStoreFilterTypeOptional filter to apply to the search.
A promise that resolves to an array of documents and their scores.
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 fromStatic method for creating a new instance of RedisVectorStore from documents. It adds the documents to the RedisVectorStore.
The documents to add.
The embeddings to use.
The configuration for the RedisVectorStore.
A promise that resolves to a new instance of RedisVectorStore.
Static fromStatic method for creating a new instance of RedisVectorStore from texts. It creates documents from the texts and metadata, then adds them to the RedisVectorStore.
The texts to add.
The metadata associated with the texts.
The embeddings to use.
The configuration for the RedisVectorStore.
A promise that resolves to a new instance of RedisVectorStore.
Static lc_Generated using TypeDoc
Class representing a RedisVectorStore. It extends the VectorStore class and includes methods for adding documents and vectors, performing similarity searches, managing the index, and more.