모델

const model = await initChatModel(
    "anthropic:claude-sonnet-4-5",
    { temperature: 0.7, timeout: 30, max_tokens: 1000 }
)

const response = await model.invoke("Why do parrots have colorful feathers?");
console.log(response);

const conversation = [
  { role: "system", content: "You are a helpful assistant that translates English to French." },
  { role: "user", content: "Translate: I love programming." },
  { role: "assistant", content: "J'adore la programmation." },
  { role: "user", content: "Translate: I love building applications." },
];

const response = await model.invoke(conversation);
console.log(response);  // AIMessage("J'adore créer des applications.")

import { HumanMessage, AIMessage, SystemMessage } from "langchain";

const conversation = [
  new SystemMessage("You are a helpful assistant that translates English to French."),
  new HumanMessage("Translate: I love programming."),
  new AIMessage("J'adore la programmation."),
  new HumanMessage("Translate: I love building applications."),
];

const response = await model.invoke(conversation);
console.log(response);  // AIMessage("J'adore créer des applications.")

let full: AIMessageChunk | null = null;
for await (const chunk of stream) {
  full = full ? full.concat(chunk) : chunk;
  console.log(full.text);
}

// The
// The sky
// The sky is
// The sky is typically
// The sky is typically blue
// ...

console.log(full.contentBlocks);
// [{"type": "text", "text": "The sky is typically blue..."}]

const responses = await model.batch([
  "Why do parrots have colorful feathers?",
  "How do airplanes fly?",
  "What is quantum computing?",
  "Why do parrots have colorful feathers?",
  "How do airplanes fly?",
  "What is quantum computing?",
]);
for (const response of responses) {
  console.log(response);
}

import { tool } from "langchain";
import * as z from "zod";
import { ChatOpenAI } from "@langchain/openai";

const getWeather = tool(
  (input) => `It's sunny in ${input.location}.`,
  {
    name: "get_weather",
    description: "Get the weather at a location.",
    schema: z.object({
      location: z.string().describe("The location to get the weather for"),
    }),
  },
);

const model = new ChatOpenAI({ model: "gpt-4o" });
const modelWithTools = model.bindTools([getWeather]);  

const response = await modelWithTools.invoke("What's the weather like in Boston?");
const toolCalls = response.tool_calls || [];
for (const tool_call of toolCalls) {
  // View tool calls made by the model
  console.log(`Tool: ${tool_call.name}`);
  console.log(`Args: ${tool_call.args}`);
}

const response = await model.invoke("Create a picture of a cat");
console.log(response.contentBlocks);
// [
//   { type: "text", text: "Here's a picture of a cat" },
//   { type: "image", data: "...", mimeType: "image/jpeg" },
// ]

const response = await model.invoke(
    "Tell me a joke",
    {
        runName: "joke_generation",      // Custom name for this run
        tags: ["humor", "demo"],          // Tags for categorization
        metadata: {"user_id": "123"},     // Custom metadata
        callbacks: [my_callback_handler], // Callback handlers
    }
)