initChatModel

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

const gpt4 = await initChatModel("openai:gpt-4", {
  temperature: 0.25,
});
const gpt4Result = await gpt4.invoke("what's your name");

const claude = await initChatModel("anthropic:claude-3-opus-20240229", {
  temperature: 0.25,
});
const claudeResult = await claude.invoke("what's your name");

const gemini = await initChatModel("gemini-1.5-pro", {
  modelProvider: "google-vertexai",
  temperature: 0.25,
});
const geminiResult = await gemini.invoke("what's your name");

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

const configurableModel = await initChatModel(undefined, {
  temperature: 0,
  configurableFields: ["model", "apiKey"],
});

const gpt4Result = await configurableModel.invoke("what's your name", {
  configurable: {
    model: "gpt-4",
  },
});

const claudeResult = await configurableModel.invoke("what's your name", {
  configurable: {
    model: "claude-sonnet-4-5-20250929",
  },
});

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

const configurableModelWithDefault = await initChatModel("gpt-4", {
  modelProvider: "openai",
  configurableFields: "any",
  configPrefix: "foo",
  temperature: 0,
});

const openaiResult = await configurableModelWithDefault.invoke(
  "what's your name",
  {
    configurable: {
      foo_apiKey: process.env.OPENAI_API_KEY,
    },
  }
);

const claudeResult = await configurableModelWithDefault.invoke(
  "what's your name",
  {
    configurable: {
      foo_model: "claude-sonnet-4-5-20250929",
      foo_modelProvider: "anthropic",
      foo_temperature: 0.6,
      foo_apiKey: process.env.ANTHROPIC_API_KEY,
    },
  }
);

import { initChatModel } from "langchain/chat_models/universal";
import { z } from "zod/v3";
import { tool } from "@langchain/core/tools";

const getWeatherTool = tool(
  (input) => {
    // Do something with the input
    return JSON.stringify(input);
  },
  {
    schema: z
      .object({
        location: z
          .string()
          .describe("The city and state, e.g. San Francisco, CA"),
      })
      .describe("Get the current weather in a given location"),
    name: "GetWeather",
    description: "Get the current weather in a given location",
  }
);

const getPopulationTool = tool(
  (input) => {
    // Do something with the input
    return JSON.stringify(input);
  },
  {
    schema: z
      .object({
        location: z
          .string()
          .describe("The city and state, e.g. San Francisco, CA"),
      })
      .describe("Get the current population in a given location"),
    name: "GetPopulation",
    description: "Get the current population in a given location",
  }
);

const configurableModel = await initChatModel("gpt-4", {
  configurableFields: ["model", "modelProvider", "apiKey"],
  temperature: 0,
});

const configurableModelWithTools = configurableModel.bindTools([
  getWeatherTool,
  getPopulationTool,
]);

const configurableToolResult = await configurableModelWithTools.invoke(
  "Which city is hotter today and which is bigger: LA or NY?",
  {
    configurable: {
      apiKey: process.env.OPENAI_API_KEY,
    },
  }
);

const configurableToolResult2 = await configurableModelWithTools.invoke(
  "Which city is hotter today and which is bigger: LA or NY?",
  {
    configurable: {
      model: "claude-sonnet-4-5-20250929",
      apiKey: process.env.ANTHROPIC_API_KEY,
    },
  }
);

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

const model = await initChatModel("gpt-4o-mini", {
  profile: {
    maxInputTokens: 100000,
  },
});

@description
This function initializes a ChatModel based on the provided model name and provider.
It supports various model providers and allows for runtime configuration of model parameters.

Security Note: Setting `configurableFields` to "any" means fields like apiKey, baseUrl, etc.
can be altered at runtime, potentially redirecting model requests to a different service/user.
Make sure that if you're accepting untrusted configurations, you enumerate the
`configurableFields` explicitly.

The function will attempt to infer the model provider from the model name if not specified.
Certain model name prefixes are associated with specific providers:
- gpt-3... or gpt-4... -> openai
- claude... -> anthropic
- amazon.... -> bedrock
- gemini... -> google-vertexai
- command... -> cohere
- accounts/fireworks... -> fireworks

@since 0.2.11
@version 0.2.11