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 indexA 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 to add an array of documents to the Tigris database.
An array of Document instances to be added to the Tigris database.
Optional options: string[] | { Optional parameter that can either be an array of string IDs or an object with a property 'ids' that is an array of string IDs.
A Promise that resolves when the documents have been added to the Tigris database.
Method to add vectors to the Tigris database.
An array of vectors to be added to the Tigris database.
An array of Document instances corresponding to the vectors.
Optional options: string[] | { Optional parameter that can either be an array of string IDs or an object with a property 'ids' that is an array of string IDs.
A Promise that resolves when the vectors have been added to the Tigris database.
Optional kOrFields: number | Partial<VectorStoreRetrieverInput<TigrisVectorStore>>Optional filter: string | objectOptional callbacks: CallbacksOptional tags: string[]Optional metadata: Record<string, unknown>Optional verbose: booleanMethod to perform a similarity search in the Tigris database and return the k most similar vectors along with their similarity scores.
The query vector.
The number of most similar vectors to return.
Optional filter: objectOptional filter object to apply during the search.
A Promise that resolves to an array of tuples, each containing a Document and its 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 fromStatic method to create a new instance of TigrisVectorStore from an array of Document instances.
An array of Document instances to be added to the Tigris database.
An instance of Embeddings to be used for embedding the documents.
An instance of TigrisLibArgs to be used for configuring the Tigris database.
A Promise that resolves to a new instance of TigrisVectorStore.
Static fromStatic method to create a new instance of TigrisVectorStore from an existing index.
An instance of Embeddings to be used for embedding the documents.
An instance of TigrisLibArgs to be used for configuring the Tigris database.
A Promise that resolves to a new instance of TigrisVectorStore.
Static fromStatic method to create a new instance of TigrisVectorStore from an array of texts.
An array of texts to be converted into Document instances and added to the Tigris database.
Either an array of metadata objects or a single metadata object to be associated with the texts.
An instance of Embeddings to be used for embedding the texts.
An instance of TigrisLibArgs to be used for configuring the Tigris database.
A Promise that resolves to a new instance of TigrisVectorStore.
Static lc_Generated using TypeDoc
Class for managing and operating vector search applications with Tigris, an open-source Serverless NoSQL Database and Search Platform.