mirror of
https://github.com/hwchase17/langchain.git
synced 2025-10-02 10:51:33 +00:00
fa5d49f2c1
ran ```bash g grep -l "langchain.vectorstores" | xargs -L 1 sed -i '' "s/langchain\.vectorstores/langchain_community.vectorstores/g" g grep -l "langchain.document_loaders" | xargs -L 1 sed -i '' "s/langchain\.document_loaders/langchain_community.document_loaders/g" g grep -l "langchain.chat_loaders" | xargs -L 1 sed -i '' "s/langchain\.chat_loaders/langchain_community.chat_loaders/g" g grep -l "langchain.document_transformers" | xargs -L 1 sed -i '' "s/langchain\.document_transformers/langchain_community.document_transformers/g" g grep -l "langchain\.graphs" | xargs -L 1 sed -i '' "s/langchain\.graphs/langchain_community.graphs/g" g grep -l "langchain\.memory\.chat_message_histories" | xargs -L 1 sed -i '' "s/langchain\.memory\.chat_message_histories/langchain_community.chat_message_histories/g" gco master libs/langchain/tests/unit_tests/*/test_imports.py gco master libs/langchain/tests/unit_tests/**/test_public_api.py ```
25 lines
1.1 KiB
Plaintext
25 lines
1.1 KiB
Plaintext
# DashVector
|
|
|
|
> [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.
|
|
|
|
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.
|
|
It is broken into two parts: installation and setup, and then references to specific DashVector wrappers.
|
|
|
|
## Installation and Setup
|
|
Install the Python SDK:
|
|
```bash
|
|
pip install dashvector
|
|
```
|
|
|
|
## VectorStore
|
|
|
|
A DashVector 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:
|
|
```python
|
|
from langchain_community.vectorstores import DashVector
|
|
```
|
|
|
|
For a detailed walkthrough of the DashVector wrapper, please refer to [this notebook](/docs/integrations/vectorstores/dashvector)
|