Qdrant

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 Qdrant bundle.

Qdrant vector store

The Qdrant component reads and writes to Qdrant vector stores using an instance of QdrantVectorStore.

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

:::tip For a tutorial using a vector database in a flow, see Create a vector RAG chatbot. :::

Qdrant 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 Qdrant documentation or inspect component code.

Name	Type	Description
collection_name	String	Input parameter. The name of the Qdrant collection.
host	String	Input parameter. The Qdrant server host.
port	Integer	Input parameter. The Qdrant server port.
grpc_port	Integer	Input parameter. The Qdrant gRPC port.
api_key	SecretString	Input parameter. The API key for Qdrant.
prefix	String	Input parameter. The prefix for Qdrant.
timeout	Integer	Input parameter. The timeout for Qdrant operations.
path	String	Input parameter. The path for Qdrant.
url	String	Input parameter. The URL for Qdrant.
distance_func	String	Input parameter. The distance function for vector similarity.
content_payload_key	String	Input parameter. The content payload key.
metadata_payload_key	String	Input parameter. The metadata payload key.
search_query	String	Input parameter. The query for similarity search.
ingest_data	JSON	Input parameter. The data to be ingested into the vector store.
embedding	Embeddings	Input parameter. The embedding function to use.
number_of_results	Integer	Input parameter. The number of results to return in search.