Skip to main content

ChatPerplexity

本指南将帮助你开始使用 Perplexity 聊天模型。如需了解 ChatPerplexity 所有功能和配置的详细文档，请访问 API 参考文档。

概览​

集成详情​

类别包本地支持可序列化Python 支持包下载量最新版本
ChatPerplexity@langchain/community❌beta✅NPM - 下载量NPM - 版本

模型特性​

有关如何使用特定特性的指南，请参见下表标题中的链接。

工具调用结构化输出JSON 模式图像输入音频输入视频输入逐 token 流式传输token 使用量对数概率
❌✅❌❌❌❌✅✅❌

请注意，在撰写本文时，Perplexity 仅在某些使用层级上支持结构化输出。

准备工作​

要访问 Perplexity 模型，你需要创建一个 Perplexity 账户，获取 API 密钥，并安装 @langchain/community 集成包。

凭据​

前往 https://perplexity.ai 注册 Perplexity 并生成一个 API 密钥。完成此操作后，请设置 PERPLEXITY_API_KEY 环境变量：

export PERPLEXITY_API_KEY="your-api-key"

如果你想自动追踪模型调用，也可以通过取消注释以下内容来设置你的 LangSmith API 密钥：

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

安装​

LangChain Perplexity 的集成位于 @langchain/community 包中：

:::提示 请参阅安装集成包的一般说明部分。 :::

yarn add @langchain/community @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 { ChatPerplexity } from "@langchain/community/chat_models/perplexity";

const llm = new ChatPerplexity({
  model: "sonar",
  temperature: 0,
  maxTokens: undefined,
  timeout: undefined,
  maxRetries: 2,
  // other params...
});

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 {
  "id": "run-71853938-aa30-4861-9019-f12323c09f9a",
  "content": "J'adore la programmation.",
  "additional_kwargs": {
    "citations": [
      "https://careersatagoda.com/blog/why-we-love-programming/",
      "https://henrikwarne.com/2012/06/02/why-i-love-coding/",
      "https://forum.freecodecamp.org/t/i-love-programming-but/497502",
      "https://ilovecoding.org",
      "https://thecodinglove.com"
    ]
  },
  "response_metadata": {
    "tokenUsage": {
      "promptTokens": 20,
      "completionTokens": 9,
      "totalTokens": 29
    }
  },
  "tool_calls": [],
  "invalid_tool_calls": []
}
console.log(aiMsg.content);
J'adore la programmation.

链式调用​

我们可以像这样将模型与提示模板链式调用：

import { ChatPromptTemplate } from "@langchain/core/prompts";

const prompt = ChatPromptTemplate.fromMessages([
  [
    "system",
    "You are a helpful assistant that translates {input_language} to {output_language}.",
  ],
  ["human", "{input}"],
]);

const chain = prompt.pipe(llm);
await chain.invoke({
  input_language: "English",
  output_language: "German",
  input: "I love programming.",
});
AIMessage {
  "id": "run-a44dc452-4a71-423d-a4ee-50a2d7c90abd",
  "content": "**English to German Translation:**\n\n\"I love programming\" translates to **\"Ich liebe das Programmieren.\"**\n\nIf you'd like to express your passion for programming in more detail, here are some additional translations:\n\n- **\"Programming is incredibly rewarding and fulfilling.\"** translates to **\"Das Programmieren ist unglaublich lohnend und erfüllend.\"**\n- **\"I enjoy solving problems through coding.\"** translates to **\"Ich genieße es, Probleme durch Codieren zu lösen.\"**\n- **\"I find the process of creating something from nothing very satisfying.\"** translates to **\"Ich finde den Prozess, etwas aus dem Nichts zu schaffen, sehr befriedigend.\"**",
  "additional_kwargs": {
    "citations": [
      "https://careersatagoda.com/blog/why-we-love-programming/",
      "https://henrikwarne.com/2012/06/02/why-i-love-coding/",
      "https://dev.to/dvddpl/coding-is-boring-why-do-you-love-coding-cl0",
      "https://forum.freecodecamp.org/t/i-love-programming-but/497502",
      "https://ilovecoding.org"
    ]
  },
  "response_metadata": {
    "tokenUsage": {
      "promptTokens": 15,
      "completionTokens": 149,
      "totalTokens": 164
    }
  },
  "tool_calls": [],
  "invalid_tool_calls": []
}

API 参考文档​

如需了解 ChatPerplexity 所有功能和配置的详细文档，请访问 API 参考页面: https://api.js.langchain.com/classes/\_langchain_community.chat_models_perplexity.ChatPerplexity.html

Was this page helpful?


You can also leave detailed feedback on GitHub.