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Documentation Index

Fetch the complete documentation index at: https://langchain.idochub.dev/llms.txt

Use this file to discover all available pages before exploring further.

Qdrant (read: quadrant) is a vector similarity search engine. It provides a production-ready service with a convenient API to store, search, and manage points - vectors with an additional payload. Qdrant is tailored to extended filtering support.

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Installation and Setup

Install the Python partner package: 
pip install langchain-qdrant

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Embedding models

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FastEmbedSparse

from langchain_qdrant import FastEmbedSparse

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SparseEmbeddings

from langchain_qdrant import SparseEmbeddings

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Vector Store

There exists a wrapper around Qdrant indexes, allowing you to use it as a vectorstore, whether for semantic search or example selection. To import this vectorstore: 
from langchain_qdrant import QdrantVectorStore
For a more detailed walkthrough of the Qdrant wrapper, see this notebook