LLM support

HyperAgent can run LLM models that extend the Langchain BaseChatModel class. You can see a list of supported models

All that is required is initializing the model with required parameters, and then passing that through the llm parameter in the HyperAgent constructor.

With OpenAI GPT-4o

import "dotenv/config";
import HyperAgent from "@hyperbrowser/agent";

import chalk from "chalk";
import { ChatOpenAI } from "@langchain/openai";

const TASK =
  "Go to hackernews, and find if there's any SHOW HN post up there. If it is, then tell me the title of the post.";

async function runEval() {
  const llm = new ChatOpenAI({
    apiKey: process.env.OPENAI_API_KEY,
    model: "gpt-4o",
  });

  const agent = new HyperAgent({
    llm: llm,
    debug: true,
  });

  console.log(`\n${chalk.green("Running agent with GPT-4o")}\n`);

  const result = await agent.executeTask(TASK, {
    debugOnAgentOutput: (agentOutput) => {
      console.log("\n" + chalk.cyan.bold("===== AGENT OUTPUT ====="));
      console.dir(agentOutput, { depth: null, colors: true });
      console.log(chalk.cyan.bold("===============") + "\n");
    },
    onStep: (step) => {
      console.log("\n" + chalk.cyan.bold(`===== STEP ${step.idx} =====`));
      console.dir(step, { depth: null, colors: true });
      console.log(chalk.cyan.bold("===============") + "\n");
    },
  });
  await agent.closeAgent();
  console.log(chalk.green.bold("\nResult:"));
  console.log(chalk.white(result.output));
  return result;
}

(async () => {
  await runEval();
})().catch((error) => {
  console.error(chalk.red("Error:"), error);
  process.exit(1);
});

With Anthropic Claude 3.7 Sonnet

import "dotenv/config";
import HyperAgent from "@hyperbrowser/agent";

import chalk from "chalk";
import { ChatAnthropic } from "@langchain/anthropic";

const TASK =
  "Go to hackernews, and find if there's any SHOW HN post up there. If it is, then tell me the title of the post.";

async function runEval() {
  const llm = new ChatAnthropic({
    apiKey: process.env.ANTHROPIC_API_KEY,
    model: "claude-3-7-sonnet-latest",
  });

  const agent = new HyperAgent({
    llm: llm,
  });

  console.log(`\n${chalk.green("Running agent with Claude Sonnet 3.7")}\n`);

  const result = await agent.executeTask(TASK, {
    debugOnAgentOutput: (agentOutput) => {
      console.log("\n" + chalk.cyan.bold("===== AGENT OUTPUT ====="));
      console.dir(agentOutput, { depth: null, colors: true });
      console.log(chalk.cyan.bold("===============") + "\n");
    },
    onStep: (step) => {
      console.log("\n" + chalk.cyan.bold(`===== STEP ${step.idx} =====`));
      console.dir(step, { depth: null, colors: true });
      console.log(chalk.cyan.bold("===============") + "\n");
    },
  });
  await agent.closeAgent();
  console.log(chalk.green.bold("\nResult:"));
  console.log(chalk.white(result.output));
  return result;
}

(async () => {
  await runEval();
})().catch((error) => {
  console.error(chalk.red("Error:"), error);
  process.exit(1);
});

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import "dotenv/config"; import HyperAgent from "@hyperbrowser/agent"; import chalk from "chalk"; import { ChatOpenAI } from "@langchain/openai"; const TASK = "Go to hackernews, and find if there's any SHOW HN post up there. If it is, then tell me the title of the post."; async function runEval() { const llm = new ChatOpenAI({ apiKey: process.env.OPENAI_API_KEY, model: "gpt-4o", }); const agent = new HyperAgent({ llm: llm, debug: true, }); console.log(`\n${chalk.green("Running agent with GPT-4o")}\n`); const result = await agent.executeTask(TASK, { debugOnAgentOutput: (agentOutput) => { console.log("\n" + chalk.cyan.bold("===== AGENT OUTPUT =====")); console.dir(agentOutput, { depth: null, colors: true }); console.log(chalk.cyan.bold("===============") + "\n"); }, onStep: (step) => { console.log("\n" + chalk.cyan.bold(`===== STEP ${step.idx} =====`)); console.dir(step, { depth: null, colors: true }); console.log(chalk.cyan.bold("===============") + "\n"); }, }); await agent.closeAgent(); console.log(chalk.green.bold("\nResult:")); console.log(chalk.white(result.output)); return result; } (async () => { await runEval(); })().catch((error) => { console.error(chalk.red("Error:"), error); process.exit(1); });

import "dotenv/config"; import HyperAgent from "@hyperbrowser/agent"; import chalk from "chalk"; import { ChatAnthropic } from "@langchain/anthropic"; const TASK = "Go to hackernews, and find if there's any SHOW HN post up there. If it is, then tell me the title of the post."; async function runEval() { const llm = new ChatAnthropic({ apiKey: process.env.ANTHROPIC_API_KEY, model: "claude-3-7-sonnet-latest", }); const agent = new HyperAgent({ llm: llm, }); console.log(`\n${chalk.green("Running agent with Claude Sonnet 3.7")}\n`); const result = await agent.executeTask(TASK, { debugOnAgentOutput: (agentOutput) => { console.log("\n" + chalk.cyan.bold("===== AGENT OUTPUT =====")); console.dir(agentOutput, { depth: null, colors: true }); console.log(chalk.cyan.bold("===============") + "\n"); }, onStep: (step) => { console.log("\n" + chalk.cyan.bold(`===== STEP ${step.idx} =====`)); console.dir(step, { depth: null, colors: true }); console.log(chalk.cyan.bold("===============") + "\n"); }, }); await agent.closeAgent(); console.log(chalk.green.bold("\nResult:")); console.log(chalk.white(result.output)); return result; } (async () => { await runEval(); })().catch((error) => { console.error(chalk.red("Error:"), error); process.exit(1); });