Class AzureChatOpenAI

import { AzureChatOpenAI } from '@langchain/openai';

const llm = new AzureChatOpenAI({
  azureOpenAIApiKey: process.env.AZURE_OPENAI_API_KEY, // In Node.js defaults to process.env.AZURE_OPENAI_API_KEY
  azureOpenAIApiInstanceName: process.env.AZURE_OPENAI_API_INSTANCE_NAME, // In Node.js defaults to process.env.AZURE_OPENAI_API_INSTANCE_NAME
  azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME, // In Node.js defaults to process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME
  azureOpenAIApiVersion: process.env.AZURE_OPENAI_API_VERSION, // In Node.js defaults to process.env.AZURE_OPENAI_API_VERSION
  temperature: 0,
  maxTokens: undefined,
  timeout: undefined,
  maxRetries: 2,
  // apiKey: "...",
  // baseUrl: "...",
  // other params...
});
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const messages = [
  {
    type: "system" as const,
    content: "You are a helpful translator. Translate the user sentence to French.",
  },
  {
    type: "human" as const,
    content: "I love programming.",
  },
];
const result = await llm.invoke(messages);
console.log(result);
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for await (const chunk of await llm.stream(messages)) {
  console.log(chunk);
}
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import { AIMessageChunk } from '@langchain/core/messages';
import { concat } from '@langchain/core/utils/stream';

const stream = await llm.stream(messages);
let full: AIMessageChunk | undefined;
for await (const chunk of stream) {
  full = !full ? chunk : concat(full, chunk);
}
console.log(full);
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import { z } from 'zod';

const GetWeather = {
  name: "GetWeather",
  description: "Get the current weather in a given location",
  schema: z.object({
    location: z.string().describe("The city and state, e.g. San Francisco, CA")
  }),
}

const GetPopulation = {
  name: "GetPopulation",
  description: "Get the current population in a given location",
  schema: z.object({
    location: z.string().describe("The city and state, e.g. San Francisco, CA")
  }),
}

const llmWithTools = llm.bindTools([GetWeather, GetPopulation]);
const aiMsg = await llmWithTools.invoke(
  "Which city is hotter today and which is bigger: LA or NY?"
);
console.log(aiMsg.tool_calls);
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import { z } from 'zod';

const Joke = z.object({
  setup: z.string().describe("The setup of the joke"),
  punchline: z.string().describe("The punchline to the joke"),
  rating: z.number().optional().describe("How funny the joke is, from 1 to 10")
}).describe('Joke to tell user.');

const structuredLlm = llm.withStructuredOutput(Joke);
const jokeResult = await structuredLlm.invoke("Tell me a joke about cats");
console.log(jokeResult);
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const jsonLlm = llm.bind({ response_format: { type: "json_object" } });
const jsonLlmAiMsg = await jsonLlm.invoke(
  "Return a JSON object with key 'randomInts' and a value of 10 random ints in [0-99]"
);
console.log(jsonLlmAiMsg.content);
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import { HumanMessage } from '@langchain/core/messages';

const imageUrl = "https://example.com/image.jpg";
const imageData = await fetch(imageUrl).then(res => res.arrayBuffer());
const base64Image = Buffer.from(imageData).toString('base64');

const message = new HumanMessage({
  content: [
    { type: "text", text: "describe the weather in this image" },
    {
      type: "image_url",
      image_url: { url: `data:image/jpeg;base64,${base64Image}` },
    },
  ]
});

const imageDescriptionAiMsg = await llm.invoke([message]);
console.log(imageDescriptionAiMsg.content);
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const aiMsgForMetadata = await llm.invoke(messages);
console.log(aiMsgForMetadata.usage_metadata);
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const logprobsLlm = new ChatOpenAI({ logprobs: true });
const aiMsgForLogprobs = await logprobsLlm.invoke(messages);
console.log(aiMsgForLogprobs.response_metadata.logprobs);
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const aiMsgForResponseMetadata = await llm.invoke(messages);
console.log(aiMsgForResponseMetadata.response_metadata);
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