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想在本地运行 Mistral 的模型?查看我们的 Ollama 集成
您当前页面介绍的是将 Mistral 模型用作文本补全模型。Mistral 上提供的许多流行模型都是聊天补全模型您可能在寻找此页面
Mistral AI 是一个平台,为他们强大的开源模型提供托管服务。 这将帮助您开始使用 LangChain 的 MistralAI 补全模型(LLMs)。有关 MistralAI 功能和配置选项的详细文档,请参阅 API 参考

概览

集成详情

类别本地可序列化PY 支持下载量版本
MistralAI@langchain/mistralaiNPM - DownloadsNPM - Version

设置

要访问 MistralAI 模型,您需要创建一个 MistralAI 账户,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。完成后,设置 MISTRAL_API_KEY 环境变量
export MISTRAL_API_KEY="your-api-key"
如果您想获取模型调用的自动化跟踪,您还可以通过取消注释下方来设置您的 LangSmith API 密钥
# export LANGSMITH_TRACING="true"
# export LANGSMITH_API_KEY="your-api-key"

安装

LangChain MistralAI 集成位于 @langchain/mistralai 包中
npm install @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完成
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.

挂钩

Mistral AI 支持三个事件的自定义钩子:beforeRequest、requestError 和 response。每种钩子类型的函数签名示例如下所示
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
};
要将这些钩子添加到聊天模型,可以将其作为参数传递,它们会自动添加
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...
});
或者在实例化后手动分配和添加
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();
`addAllHooksToHttpClient` 方法会清除所有当前添加的钩子,然后分配整个更新后的钩子列表,以避免钩子重复。 钩子可以一次移除一个,或者一次性从模型中清除所有钩子。
model.removeHookFromHttpClient(beforeRequestHook);

model.removeAllHooksFromHttpClient();

API 参考

有关所有 MistralAI 功能和配置的详细文档,请访问 API 参考
以编程方式连接这些文档到 Claude、VSCode 等,通过 MCP 获取实时答案。
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