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Zvec is an open-source, in-process vector database — lightweight, lightning-fast, and designed to embed directly into applications. Built on Proxima (Alibaba’s battle-tested vector search engine), it delivers production-grade, low-latency, scalable similarity search with minimal setup
This document demonstrates to leverage Zvec within the LangChain ecosystem. In particular, it shows how to install Zvec, and how to use it as a VectorStore plugin in LangChain.

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Installation and setup

Install the Python SDK: 
pip install zvec

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Embedding models

from langchain_community.embeddings import DashScopeEmbeddings
See the use example.

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Vector store

A Zvec Collection is wrapped as a familiar VectorStore for native usage within LangChain, which allows it to be readily used for various scenarios, such as semantic search or example selection. You may import the vectorstore by: 
from langchain_community.vectorstores import Zvec
For a detailed walkthrough of the Zvec wrapper, please refer to this notebook
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