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## Description Add `Dashvector` vectorstore for langchain - [dashvector quick start](https://help.aliyun.com/document_detail/2510223.html) - [dashvector package description](https://pypi.org/project/dashvector/) ## How to use ```python from langchain.vectorstores.dashvector import DashVector dashvector = DashVector.from_documents(docs, embeddings) ``` --------- Co-authored-by: smallrain.xuxy <smallrain.xuxy@alibaba-inc.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
25 lines
1.1 KiB
Plaintext
25 lines
1.1 KiB
Plaintext
# DashVector
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> [DashVector](https://help.aliyun.com/document_detail/2510225.html) is a fully-managed vectorDB service that supports high-dimension dense and sparse vectors, real-time insertion and filtered search. It is built to scale automatically and can adapt to different application requirements.
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This document demonstrates to leverage DashVector within the LangChain ecosystem. In particular, it shows how to install DashVector, and how to use it as a VectorStore plugin in LangChain.
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It is broken into two parts: installation and setup, and then references to specific DashVector wrappers.
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## Installation and Setup
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Install the Python SDK:
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```bash
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pip install dashvector
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```
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## VectorStore
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A DashVector Collection is wrapped as a familiar VectorStore for native usage within LangChain,
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which allows it to be readily used for various scenarios, such as semantic search or example selection.
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You may import the vectorstore by:
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```python
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from langchain.vectorstores import DashVector
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```
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For a detailed walkthrough of the DashVector wrapper, please refer to [this notebook](/docs/integrations/vectorstores/dashvector.html)
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