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MistralAI

提示

想在本地运行 Mistral 的模型吗？查看我们的 Ollama 集成。

注意

您当前所在的页面记录了 Mistral 模型作为 文本补全模型 的使用情况。Mistral 上许多流行的模型是 聊天补全模型。

您可能正在寻找 此页面。

Mistral AI 是一个提供其强大 开源模型 托管的平台。

这将帮助您开始使用 LangChain 使用 MistralAI 补全模型 (LLM)。有关 MistralAI 功能和配置选项的详细文档，请参阅 API 参考。

概述​

集成详细信息​

类包本地可序列化PY 支持包下载包最新
MistralAI@langchain/mistralai❌✅❌NPM - DownloadsNPM - Version

设置​

要访问 MistralAI 模型，您需要创建一个 MistralAI 帐户，获取 API 密钥，并安装 @langchain/mistralai 集成包。

凭据​

前往 console.mistral.ai 注册 MistralAI 并生成 API 密钥。完成此操作后，设置 MISTRAL_API_KEY 环境变量

export MISTRAL_API_KEY="your-api-key"

如果您想获得对模型调用的自动跟踪，您还可以通过取消下面的注释来设置您的 LangSmith API 密钥

# export LANGCHAIN_TRACING_V2="true"
# export LANGCHAIN_API_KEY="your-api-key"

安装​

LangChain MistralAI 集成位于 @langchain/mistralai 包中

提示

请参阅 本节了解有关安装集成包的一般说明。

yarn add @langchain/mistralai @langchain/core

实例化​

现在我们可以实例化我们的模型对象并生成聊天补全

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

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

调用​

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.

链接​

我们可以将我们的补全模型与提示模板 链接，如下所示

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."

由于 Mistral LLM 是一个补全模型，它们还允许您在提示中插入 suffix。后缀可以通过调用模型时传递的调用选项传递，如下所示

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');
```

如第一个示例所示，该模型生成了请求的 console.log('hello world') 代码片段，但也包含了额外的不需要的文本。通过添加后缀，我们可以限制模型仅在后缀之前完成提示（在本例中，为三个反引号）。这使我们能够轻松解析补全并仅使用自定义输出解析器提取所需响应，而无需后缀。

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');

API 参考​

有关所有 MistralAI 功能和配置的详细文档，请前往 API 参考：https://api.js.langchain.com/classes/langchain_mistralai.MistralAI.html

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您也可以在 GitHub 上留下详细的反馈 GitHub.