@langchain/mistralai
v0.1.1
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MistralAI integration for LangChain.js
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@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.