包详细信息

@langchain/mistralai

langchain-ai602.8kMIT1.0.2

MistralAI integration for LangChain.js

自述文件

@langchain/mistralai

This package contains the LangChain.js integrations for Mistral through their SDK.

Installation

```bash npm2yarn npm install @langchain/mistralai @langchain/core


This package, along with the main LangChain package, depends on [`@langchain/core`](https://npmjs.com/package/@langchain/core/).
If you are using this package with other LangChain packages, you should make sure that all of the packages depend on the same instance of @langchain/core.
You can do so by adding appropriate field to your project's `package.json` like this:

```json
{
  "name": "your-project",
  "version": "0.0.0",
  "dependencies": {
    "@langchain/core": "^0.3.0",
    "@langchain/mistralai": "^0.0.0"
  },
  "resolutions": {
    "@langchain/core": "^0.3.0"
  },
  "overrides": {
    "@langchain/core": "^0.3.0"
  },
  "pnpm": {
    "overrides": {
      "@langchain/core": "^0.3.0"
    }
  }
}

The field you need depends on the package manager you're using, but we recommend adding a field for the common yarn, npm, and pnpm to maximize compatibility.

Chat Models

This package contains the ChatMistralAI class, which is the recommended way to interface with the Mistral series of models.

To use, install the requirements, and configure your environment.

export MISTRAL_API_KEY=your-api-key

Then initialize

import { ChatMistralAI } from "@langchain/mistralai";

const model = new ChatMistralAI({
  apiKey: process.env.MISTRAL_API_KEY,
  modelName: "mistral-small",
});
const response = await model.invoke(new HumanMessage("Hello world!"));

Streaming

import { ChatMistralAI } from "@langchain/mistralai";

const model = new ChatMistralAI({
  apiKey: process.env.MISTRAL_API_KEY,
  modelName: "mistral-small",
});
const response = await model.stream(new HumanMessage("Hello world!"));

Embeddings

This package also adds support for Mistral's embeddings model.

import { MistralAIEmbeddings } from "@langchain/mistralai";

const embeddings = new MistralAIEmbeddings({
  apiKey: process.env.MISTRAL_API_KEY,
});
const res = await embeddings.embedQuery("Hello world");

Development

To develop the Mistral package, you'll need to follow these instructions:

Install dependencies

pnpm install

Build the package

pnpm build

Or from the repo root:

pnpm build --filter @langchain/mistralai

Run tests

Test files should live within a tests/ file in the src/ folder. Unit tests should end in .test.ts and integration tests should end in .int.test.ts:

$ pnpm test
$ pnpm test:int

Lint & Format

Run the linter & formatter to ensure your code is up to standard:

pnpm lint && pnpm format

Adding new entrypoints

If you add a new file to be exported, either import & re-export from src/index.ts, or add it to the exports field in the package.json file and run pnpm build to generate the new entrypoint.

更新日志

@langchain/mistralai

1.0.2

Patch Changes

1.0.1

Patch Changes

1.0.0

This release updates the package for compatibility with LangChain v1.0. See the v1.0 release notes for details on what's new.

0.2.3

Patch Changes

  • 5d24ff1: roll back toolCall and response pairing

0.2.2

Patch Changes

  • 9eb78b7: Added logic to ensure toolCalls have corresponding toolResponses when sending messages to the Mistral API