> ## Documentation Index
> Fetch the complete documentation index at: https://docs.langchain.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Modelscope integrations

> Integrate with Modelscope using LangChain Python.

> [ModelScope](https://www.modelscope.cn/home) is a big repository of the models and datasets.

This page covers how to use the modelscope ecosystem within LangChain.
It is broken into two parts: installation and setup, and then references to specific modelscope wrappers.

## Installation

<CodeGroup>
  ```bash pip theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  pip install -U langchain-modelscope-integration
  ```

  ```bash uv theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  uv add langchain-modelscope-integration
  ```
</CodeGroup>

Head to [ModelScope](https://modelscope.cn/) to sign up to ModelScope and generate an [SDK token](https://modelscope.cn/my/myaccesstoken). Once you've done this set the `MODELSCOPE_SDK_TOKEN` environment variable:

```bash theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
export MODELSCOPE_SDK_TOKEN=<your_sdk_token>
```

## Chat models

`ModelScopeChatEndpoint` class exposes chat models from ModelScope. See [available models in the ModelScope API documentation](https://www.modelscope.cn/docs/model-service/API-Inference/intro).

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_modelscope import ModelScopeChatEndpoint

llm = ModelScopeChatEndpoint(model="Qwen/Qwen2.5-Coder-32B-Instruct")
llm.invoke("Sing a ballad of LangChain.")
```

## Embeddings

`ModelScopeEmbeddings` class exposes embeddings from ModelScope.

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_modelscope import ModelScopeEmbeddings

embeddings = ModelScopeEmbeddings(model_id="damo/nlp_corom_sentence-embedding_english-base")
embeddings.embed_query("What is the meaning of life?")
```

## LLMs

`ModelScopeEndpoint` class exposes LLMs from ModelScope.

```python theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
from langchain_modelscope import ModelScopeEndpoint

llm = ModelScopeEndpoint(model="Qwen/Qwen2.5-Coder-32B-Instruct")
llm.invoke("The meaning of life is")
```

***

<div className="source-links">
  <Callout icon="terminal-2">
    [Connect these docs](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers.
  </Callout>

  <Callout icon="edit">
    [Edit this page on GitHub](https://github.com/langchain-ai/docs/edit/main/src/oss/python/integrations/providers/modelscope.mdx) or [file an issue](https://github.com/langchain-ai/docs/issues/new/choose).
  </Callout>
</div>