MistralAI

<Tip>
**Want to run Mistral's models locally? Check out our [Ollama integration](/oss/javascript/integrations/chat/ollama).**

:::

</Tip>caution
You are currently on a page documenting the use of Mistral models as text completion models. Many popular models available on Mistral are [chat completion models](/oss/javascript/langchain/models).

You may be looking for [this page instead](/oss/javascript/integrations/chat/mistral/).
:::

export MISTRAL_API_KEY="your-api-key"

# export LANGSMITH_TRACING="true"
# export LANGSMITH_API_KEY="your-api-key"

import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
<IntegrationInstallTooltip></IntegrationInstallTooltip>

<Npm2Yarn>
  @langchain/mistralai @langchain/core
</Npm2Yarn>

import { MistralAI } from "@langchain/mistralai"

const llm = new MistralAI({
  model: "codestral-latest",
  temperature: 0,
  maxTokens: undefined,
  maxRetries: 2,
  // other params...
})

const inputText = "MistralAI is an AI company that "

const completion = await llm.invoke(inputText)
completion

 has developed Mistral 7B, a large language model (LLM) that is open-source and available for commercial use. Mistral 7B is a 7 billion parameter model that is trained on a diverse and high-quality dataset, and it has been fine-tuned to perform well on a variety of tasks, including text generation, question answering, and code interpretation.

MistralAI has made Mistral 7B available under a permissive license, allowing anyone to use the model for commercial purposes without having to pay any fees. This has made Mistral 7B a popular choice for businesses and organizations that want to leverage the power of large language models without incurring high costs.

Mistral 7B has been trained on a diverse and high-quality dataset, which has enabled it to perform well on a variety of tasks. It has been fine-tuned to generate coherent and contextually relevant text, and it has been shown to be capable of answering complex questions and interpreting code.

Mistral 7B is also a highly efficient model, capable of processing text at a fast pace. This makes it well-suited for applications that require real-time responses, such as chatbots and virtual assistants.

Overall, Mistral 7B is a powerful and versatile large language model that is open-source and available for commercial use. Its ability to perform well on a variety of tasks, its efficiency, and its permissive license make it a popular choice for businesses and organizations that want to leverage the power of large language models.

import { PromptTemplate } from "@langchain/core/prompts"

const prompt = PromptTemplate.fromTemplate("How to say {input} in {output_language}:\n")

const chain = prompt.pipe(llm);
await chain.invoke(
  {
    output_language: "German",
    input: "I love programming.",
  }
)

I love programming.

Ich liebe Programmieren.

In German, the phrase "I love programming" is translated as "Ich liebe Programmieren." The word "programming" is translated to "Programmieren," and "I love" is translated to "Ich liebe."

const suffixResponse = await llm.invoke(
  "You can print 'hello world' to the console in javascript like this:\n\`\`\`javascript", {
    suffix: "\`\`\`"
  }
);
console.log(suffixResponse);

console.log('hello world');
\`\`\`

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

const llmForFillInCompletion = new MistralAI({
  model: "codestral-latest",
  temperature: 0,
});

const suffix = "\`\`\`";

const customOutputParser = (input: string) => {
  if (input.includes(suffix)) {
    return input.split(suffix)[0];
  }
  throw new Error("Input does not contain suffix.")
};

const resWithParser = await llmForFillInCompletion.invoke(
  "You can print 'hello world' to the console in javascript like this:\n\`\`\`javascript", {
    suffix,
  }
);

console.log(customOutputParser(resWithParser));

console.log('hello world');

const beforeRequestHook = (req: Request): Request | void | Promise<Request | void> => {
    // Code to run before a request is processed by Mistral
};

const requestErrorHook = (err: unknown, req: Request): void | Promise<void> => {
    // Code to run when an error occurs as Mistral is processing a request
};

const responseHook = (res: Response, req: Request): void | Promise<void> => {
    // Code to run before Mistral sends a successful response
};

import { ChatMistralAI } from "@langchain/mistralai"

const modelWithHooks = new ChatMistralAI({
    model: "mistral-large-latest",
    temperature: 0,
    maxRetries: 2,
    beforeRequestHooks: [ beforeRequestHook ],
    requestErrorHooks: [ requestErrorHook ],
    responseHooks: [ responseHook ],
    // other params...
});

import { ChatMistralAI } from "@langchain/mistralai"

const model = new ChatMistralAI({
    model: "mistral-large-latest",
    temperature: 0,
    maxRetries: 2,
    // other params...
});

model.beforeRequestHooks = [ ...model.beforeRequestHooks, beforeRequestHook ];
model.requestErrorHooks = [ ...model.requestErrorHooks, requestErrorHook ];
model.responseHooks = [ ...model.responseHooks, responseHook ];

model.addAllHooksToHttpClient();

model.removeHookFromHttpClient(beforeRequestHook);

model.removeAllHooksFromHttpClient();