mirror of
https://github.com/hwchase17/langchain
synced 2024-10-29 17:07:25 +00:00
66 lines
2.6 KiB
Markdown
66 lines
2.6 KiB
Markdown
|
# MyScale
|
||
|
|
|
||
|
|
This page covers how to use MyScale vector database within LangChain.
|
||
|
|
It is broken into two parts: installation and setup, and then references to specific MyScale wrappers.
|
||
|
|
|
||
|
|
With MyScale, you can manage both structured and unstructured (vectorized) data, and perform joint queries and analytics on both types of data using SQL. Plus, MyScale's cloud-native OLAP architecture, built on top of ClickHouse, enables lightning-fast data processing even on massive datasets.
|
||
|
|
|
||
|
|
## Introduction
|
||
|
|
|
||
|
|
[Overview to MyScale and High performance vector search](https://docs.myscale.com/en/overview/)
|
||
|
|
|
||
|
|
You can now register on our SaaS and [start a cluster now!](https://docs.myscale.com/en/quickstart/)
|
||
|
|
|
||
|
|
If you are also interested in how we managed to integrate SQL and vector, please refer to [this document](https://docs.myscale.com/en/vector-reference/) for further syntax reference.
|
||
|
|
|
||
|
|
We also deliver with live demo on huggingface! Please checkout our [huggingface space](https://huggingface.co/myscale)! They search millions of vector within a blink!
|
||
|
|
|
||
|
|
## Installation and Setup
|
||
|
|
- Install the Python SDK with `pip install clickhouse-connect`
|
||
|
|
|
||
|
|
### Setting up envrionments
|
||
|
|
|
||
|
|
There are two ways to set up parameters for myscale index.
|
||
|
|
|
||
|
|
1. Environment Variables
|
||
|
|
|
||
|
|
Before you run the app, please set the environment variable with `export`:
|
||
|
|
`export MYSCALE_URL='<your-endpoints-url>' MYSCALE_PORT=<your-endpoints-port> MYSCALE_USERNAME=<your-username> MYSCALE_PASSWORD=<your-password> ...`
|
||
|
|
|
||
|
|
You can easily find your account, password and other info on our SaaS. For details please refer to [this document](https://docs.myscale.com/en/cluster-management/)
|
||
|
|
Every attributes under `MyScaleSettings` can be set with prefix `MYSCALE_` and is case insensitive.
|
||
|
|
|
||
|
|
2. Create `MyScaleSettings` object with parameters
|
||
|
|
|
||
|
|
|
||
|
|
```python
|
||
|
|
from langchain.vectorstores import MyScale, MyScaleSettings
|
||
|
|
config = MyScaleSetting(host="<your-backend-url>", port=8443, ...)
|
||
|
|
index = MyScale(embedding_function, config)
|
||
|
|
index.add_documents(...)
|
||
|
|
```
|
||
|
|
|
||
|
|
## Wrappers
|
||
|
|
supported functions:
|
||
|
|
- `add_texts`
|
||
|
|
- `add_documents`
|
||
|
|
- `from_texts`
|
||
|
|
- `from_documents`
|
||
|
|
- `similarity_search`
|
||
|
|
- `asimilarity_search`
|
||
|
|
- `similarity_search_by_vector`
|
||
|
|
- `asimilarity_search_by_vector`
|
||
|
|
- `similarity_search_with_relevance_scores`
|
||
|
|
|
||
|
|
### VectorStore
|
||
|
|
|
||
|
|
There exists a wrapper around MyScale database, allowing you to use it as a vectorstore,
|
||
|
|
whether for semantic search or similar example retrieval.
|
||
|
|
|
||
|
|
To import this vectorstore:
|
||
|
|
```python
|
||
|
|
from langchain.vectorstores import MyScale
|
||
|
|
```
|
||
|
|
|
||
|
|
For a more detailed walkthrough of the MyScale wrapper, see [this notebook](../modules/indexes/vectorstores/examples/myscale.ipynb)
|