ChatGroq 集成

使用 LangChain JavaScript 集成 ChatGroq chat model。

Groq is a company that offers fast AI inference, powered by LPU™ AI inference technology which delivers fast, affordable, and energy efficient AI.

This will help you getting started with Groq chat models. For detailed documentation of all ChatGroq features and configurations head to the API reference.

概述

集成详情

Class	Package	Serializable	PY support	Downloads	Version
ChatGroq	@langchain/groq	❌	✅

模型功能

请参阅下表标题中的链接，了解如何使用特定功能。

Tool calling	Structured output	Image input	Audio input	Video input	Token-level streaming	Token usage	Logprobs
✅	✅	❌	❌	❌	✅	✅	✅

设置

要访问 ChatGroq models，你需要create a Groq account, get an API key, and install the @langchain/groq integration package.

凭证

In order to use the Groq API you’ll need an API key. Sign up for a Groq account and create an API key. Then, you can set the API key as an environment variable in your terminal:

export GROQ_API_KEY="your-api-key"

如果你想要自动追踪模型调用，还可以设置你的 LangSmith API 密钥，取消注释以下内容：

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

安装

LangChain 的 ChatGroq 集成位于 @langchain/groq 包中：

npm

npm install @langchain/groq @langchain/core

实例化

现在我们可以实例化模型对象并生成聊天补全：

import { ChatGroq } from "@langchain/groq"

const llm = new ChatGroq({
    model: "llama-3.3-70b-versatile",
    temperature: 0,
    maxTokens: undefined,
    maxRetries: 2,
    // 其他参数...
})

调用

const aiMsg = await llm.invoke([
    {
      role: "system",
      content: "You are a helpful assistant that translates English to French. Translate the user sentence.",
    },
    { role: "user", content: "I love programming." },
])
aiMsg

AIMessage {
  "content": "I enjoy programming. (The French translation is: \"J'aime programmer.\")\n\nNote: I chose to translate \"I love programming\" as \"J'aime programmer\" instead of \"Je suis amoureux de programmer\" because the latter has a romantic connotation that is not present in the original English sentence.",
  "additional_kwargs": {},
  "response_metadata": {
    "tokenUsage": {
      "completionTokens": 73,
      "promptTokens": 31,
      "totalTokens": 104
    },
    "finish_reason": "stop"
  },
  "tool_calls": [],
  "invalid_tool_calls": []
}

console.log(aiMsg.content)

I enjoy programming. (The French translation is: "J'aime programmer.")

Note: I chose to translate "I love programming" as "J'aime programmer" instead of "Je suis amoureux de programmer" because the latter has a romantic connotation that is not present in the original English sentence.

Json invocation

const messages = [
  {
    role: "system",
    content: "You are a math tutor that handles math exercises and makes output in json in format { result: number }.",
  },
  { role: "user",  content: "2 + 2 * 2" },
];

const aiInvokeMsg = await llm.invoke(messages, { response_format: { type: "json_object" } });

// if you want not to pass response_format in every invoke, you can bind it to the instance
const llmWithResponseFormat = llm.bind({ response_format: { type: "json_object" } });
const aiBindMsg = await llmWithResponseFormat.invoke(messages);

// they are the same
console.log({ aiInvokeMsgContent: aiInvokeMsg.content, aiBindMsg: aiBindMsg.content });

{
  aiInvokeMsgContent: '{\n"result": 6\n}',
  aiBindMsg: '{\n"result": 6\n}'
}

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API 参考

有关所有 ChatGroq 功能和配置的详细文档，请前往 API 参考。

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