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@langchain/mistralai

v0.1.1

Published

MistralAI integration for LangChain.js

Downloads

139,301

Readme

@langchain/mistralai

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

Installation

npm install @langchain/mistralai @langchain/core

This package, along with the main LangChain package, depends on @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:

{
  "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

yarn install

Build the package

yarn build

Or from the repo root:

yarn 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:

$ yarn test
$ yarn test:int

Lint & Format

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

yarn lint && yarn 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 entrypoints field in the config variable located inside langchain.config.js and run yarn build to generate the new entrypoint.