如何在单行代码中初始化任何模型

许多 LLM 应用程序允许最终用户指定他们希望应用程序使用的模型提供者和模型。这需要编写一些逻辑来根据用户配置初始化不同的 ChatModels。initChatModel() 辅助方法使初始化许多不同的模型集成变得容易，而无需担心导入路径和类名。请记住，此功能仅适用于聊天模型。

先决条件

本指南假设你熟悉以下概念

• 聊天模型

• LangChain 表达式语言 (LCEL)

• 工具调用

兼容性

此功能仅适用于 Node 环境。在非 Node 环境或使用打包器中使用此功能不能保证工作且不受官方支持。

initChatModel 需要 langchain>=0.2.11。有关升级时需要考虑的一些因素，请参阅 本指南。

有关支持的集成列表，请参阅 initChatModel() API 参考。

确保已安装你想要支持的任何模型提供者的集成包。例如，你需要安装 @langchain/openai 来初始化 OpenAI 模型。

基本使用

import { initChatModel } from "langchain/chat_models/universal";

// Returns a @langchain/openai ChatOpenAI instance.
const gpt4o = await initChatModel("gpt-4o", {
  modelProvider: "openai",
  temperature: 0,
});
// Returns a @langchain/anthropic ChatAnthropic instance.
const claudeOpus = await initChatModel("claude-3-opus-20240229", {
  modelProvider: "anthropic",
  temperature: 0,
});
// Returns a @langchain/google-vertexai ChatVertexAI instance.
const gemini15 = await initChatModel("gemini-1.5-pro", {
  modelProvider: "google-vertexai",
  temperature: 0,
});

// Since all model integrations implement the ChatModel interface, you can use them in the same way.
console.log(`GPT-4o: ${(await gpt4o.invoke("what's your name")).content}\n`);
console.log(
  `Claude Opus: ${(await claudeOpus.invoke("what's your name")).content}\n`
);
console.log(
  `Gemini 1.5: ${(await gemini15.invoke("what's your name")).content}\n`
);

/*
GPT-4o: I'm an AI language model created by OpenAI, and I don't have a personal name. You can call me Assistant or any other name you prefer! How can I help you today?

Claude Opus: My name is Claude. It's nice to meet you!

Gemini 1.5: I don't have a name. I am a large language model, and I am not a person. I am a computer program that can generate text, translate languages, write different kinds of creative content, and answer your questions in an informative way.
*/

API 参考

• initChatModel 来自 langchain/chat_models/universal

推断模型提供者

对于常见且不同的模型名称，initChatModel() 将尝试推断模型提供者。有关推断行为的完整列表，请参阅 API 参考。例如，任何以 gpt-3... 或 gpt-4... 开头的模型都将被推断为使用模型提供者 openai。

import { initChatModel } from "langchain/chat_models/universal";

const gpt4o = await initChatModel("gpt-4o", {
  temperature: 0,
});
const claudeOpus = await initChatModel("claude-3-opus-20240229", {
  temperature: 0,
});
const gemini15 = await initChatModel("gemini-1.5-pro", {
  temperature: 0,
});

API 参考

• initChatModel 来自 langchain/chat_models/universal

创建可配置模型

你还可以通过指定 configurableFields 来创建运行时可配置的模型。如果你没有指定 model 值，则默认情况下，“model”和“modelProvider”将可配置。

import { initChatModel } from "langchain/chat_models/universal";

const configurableModel = await initChatModel(undefined, { temperature: 0 });

const gpt4Res = await configurableModel.invoke("what's your name", {
  configurable: { model: "gpt-4o" },
});
console.log("gpt4Res: ", gpt4Res.content);
/*
gpt4Res:  I'm an AI language model created by OpenAI, and I don't have a personal name. You can call me Assistant or any other name you prefer! How can I assist you today?
*/

const claudeRes = await configurableModel.invoke("what's your name", {
  configurable: { model: "claude-3-5-sonnet-20240620" },
});
console.log("claudeRes: ", claudeRes.content);
/*
claudeRes:  My name is Claude. It's nice to meet you!
*/

API 参考

• initChatModel 来自 langchain/chat_models/universal

具有默认值的可配置模型

我们可以创建一个具有默认模型值的可配置模型，指定哪些参数是可配置的，并将前缀添加到可配置的参数

import { initChatModel } from "langchain/chat_models/universal";

const firstLlm = await initChatModel("gpt-4o", {
  temperature: 0,
  configurableFields: ["model", "modelProvider", "temperature", "maxTokens"],
  configPrefix: "first", // useful when you have a chain with multiple models
});

const openaiRes = await firstLlm.invoke("what's your name");
console.log("openaiRes: ", openaiRes.content);
/*
openaiRes:  I'm an AI language model created by OpenAI, and I don't have a personal name. You can call me Assistant or any other name you prefer! How can I assist you today?
*/

const claudeRes = await firstLlm.invoke("what's your name", {
  configurable: {
    first_model: "claude-3-5-sonnet-20240620",
    first_temperature: 0.5,
    first_maxTokens: 100,
  },
});
console.log("claudeRes: ", claudeRes.content);
/*
claudeRes:  My name is Claude. It's nice to meet you!
*/

API 参考

• initChatModel 来自 langchain/chat_models/universal

以声明方式使用可配置模型

我们可以对可配置模型调用 bindTools、withStructuredOutput、withConfig 等声明性操作，并将可配置模型以与我们通常实例化聊天模型对象相同的方式链接。

import { z } from "zod";
import { tool } from "@langchain/core/tools";
import { initChatModel } from "langchain/chat_models/universal";

const GetWeather = z
  .object({
    location: z.string().describe("The city and state, e.g. San Francisco, CA"),
  })
  .describe("Get the current weather in a given location");
const weatherTool = tool(
  (_) => {
    // do something
    return "138 degrees";
  },
  {
    name: "GetWeather",
    schema: GetWeather,
  }
);

const GetPopulation = z
  .object({
    location: z.string().describe("The city and state, e.g. San Francisco, CA"),
  })
  .describe("Get the current population in a given location");
const populationTool = tool(
  (_) => {
    // do something
    return "one hundred billion";
  },
  {
    name: "GetPopulation",
    schema: GetPopulation,
  }
);

const llm = await initChatModel(undefined, { temperature: 0 });
const llmWithTools = llm.bindTools([weatherTool, populationTool]);

const toolCalls1 = (
  await llmWithTools.invoke("what's bigger in 2024 LA or NYC", {
    configurable: { model: "gpt-4o" },
  })
).tool_calls;
console.log("toolCalls1: ", JSON.stringify(toolCalls1, null, 2));
/*
toolCalls1:  [
  {
    "name": "GetPopulation",
    "args": {
      "location": "Los Angeles, CA"
    },
    "type": "tool_call",
    "id": "call_DXRBVE4xfLYZfhZOsW1qRbr5"
  },
  {
    "name": "GetPopulation",
    "args": {
      "location": "New York, NY"
    },
    "type": "tool_call",
    "id": "call_6ec3m4eWhwGz97sCbNt7kOvC"
  }
]
*/

const toolCalls2 = (
  await llmWithTools.invoke("what's bigger in 2024 LA or NYC", {
    configurable: { model: "claude-3-5-sonnet-20240620" },
  })
).tool_calls;
console.log("toolCalls2: ", JSON.stringify(toolCalls2, null, 2));
/*
toolCalls2:  [
  {
    "name": "GetPopulation",
    "args": {
      "location": "Los Angeles, CA"
    },
    "id": "toolu_01K3jNU8jx18sJ9Y6Q9SooJ7",
    "type": "tool_call"
  },
  {
    "name": "GetPopulation",
    "args": {
      "location": "New York City, NY"
    },
    "id": "toolu_01UiANKaSwYykuF4hi3t5oNB",
    "type": "tool_call"
  }
]
*/

API 参考

• 工具 来自 @langchain/core/tools
• initChatModel 来自 langchain/chat_models/universal