AI Agents: The Future of Automation 

# Simple Chatbot AI Agent
import random

class ChatAgent:
    def __init__(self):
        self.knowledge = {
            "hello": "Hi there! How can I help you today?",
            "how are you": "I'm an AI agent, so I don't have feelings, but thanks for asking!",
            "bye": "Goodbye! Have a great day!"
        }

    def observe(self, user_input):
        return user_input.lower()

    def decide(self, observation):
        for key in self.knowledge:
            if key in observation:
                return self.knowledge[key]
        return "Sorry, I don't understand. Can you rephrase?"

    def act(self, response):
        print(response)

agent = ChatAgent()
print("🤖 ChatAgent is ready! Type 'bye' to exit.")

while True:
    user_input = input("You: ")
    observation = agent.observe(user_input)
    response = agent.decide(observation)
    agent.act(response)
    if "bye" in observation:
        break

import OpenAI from "openai";
import fetch from "node-fetch";

const client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const memory = [];

async function webSearch(query) {
  const res = await fetch(`https://api.duckduckgo.com/?q=${encodeURIComponent(query)}&format=json`);
  const data = await res.json();
  return data.AbstractText || "No result found";
}

async function runAgent(goal) {
  const resp = await client.chat.completions.create({
    model: "gpt-4o-mini",
    messages: [{ role: "user", content: "Break the goal into steps and solve it:\n" + goal }]
  });

  const steps = JSON.parse(resp.choices[0].message.content);
  for (const step of steps) {
    if (step.tool === "webSearch") {
      const result = await webSearch(step.input);
      memory.push({ step, result });
    }
  }
  return memory;
}

runAgent("Find AI news today").then(console.log);