FAISS

import Icon from "@site/src/components/icon"; import PartialParams from '@site/docs/_partial-hidden-params.mdx'; import PartialConditionalParams from '@site/docs/_partial-conditional-params.mdx'; import PartialVectorSearchResults from '@site/docs/_partial-vector-search-results.mdx'; import PartialVectorStoreInstance from '@site/docs/_partial-vector-store-instance.mdx';

<Icon name="Blocks" aria-hidden="true" /> Bundles contain custom components that support specific third-party integrations with Langflow.

This page describes the components that are available in the FAISS bundle.

FAISS vector store

The FAISS component provides access to the Facebook AI Similarity Search (FAISS) library through an instance of FAISS vector store.

<details> <summary>About vector store instances</summary> <PartialVectorStoreInstance /> </details> <PartialVectorSearchResults />

FAISS vector store parameters

You can inspect a vector store component's parameters to learn more about the inputs it accepts, the features it supports, and how to configure it.

<PartialParams /> <PartialConditionalParams />

For information about accepted values and functionality, see the FAISS documentation or inspect component code.

Name	Type	Description
index_name	String	Input parameter. The name of the FAISS index. Default: "langflow_index".
persist_directory	String	Input parameter. Path to save the FAISS index. It is relative to where Langflow is running.
search_query	String	Input parameter. The query to search for in the vector store.
ingest_data	Data	Input parameter. The list of data to ingest into the vector store.
allow_dangerous_deserialization	Boolean	Input parameter. Set to True to allow loading pickle files from untrusted sources. Default: True.
embedding	Embeddings	Input parameter. The embedding function to use for the vector store.
number_of_results	Integer	Input parameter. Number of results to return from the search. Default: 4.