forked from Archives/langchain
705431aecc
Co-authored-by: Ankush Gola <ankush.gola@gmail.com>
647 B
647 B
Qdrant
This page covers how to use the Qdrant ecosystem within LangChain. It is broken into two parts: installation and setup, and then references to specific Qdrant wrappers.
Installation and Setup
- Install the Python SDK with
pip install qdrant-client
Wrappers
VectorStore
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.vectorstores import Qdrant
For a more detailed walkthrough of the Qdrant wrapper, see this notebook