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.
A 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 documents to the Xata database. Maps the page content of each document, embeds the documents using the embeddings, and adds the vectors to the database.
Array of documents to be added.
Optional options: { Optional object containing an array of ids.
Optional ids?: string[]Promise resolving to an array of ids of the added documents.
Method to add vectors to the Xata database. Maps each vector to a row with the document's content, embedding, and metadata. Creates or replaces these rows in the Xata database.
Array of vectors to be added.
Array of documents corresponding to the vectors.
Optional options: { Optional object containing an array of ids.
Optional ids?: string[]Promise resolving to an array of ids of the added vectors.
Optional kOrFields: number | Partial<VectorStoreRetrieverInput<XataVectorSearch<XataClient>>>Optional filter: objectOptional callbacks: CallbacksOptional tags: string[]Optional metadata: Record<string, unknown>Optional verbose: booleanMethod to perform a similarity search in the Xata database. Returns the k most similar documents along with their scores.
Query vector for the similarity search.
Number of most similar documents to return.
Optional filter: objectOptional filter for the search.
Promise resolving to an array of tuples, each containing a Document and its 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 fromStatic lc_Generated using TypeDoc
Class for interacting with a Xata database as a VectorStore. Provides methods to add documents and vectors to the database, delete entries, and perform similarity searches.