AI Agents

/agent send 1 eth to alix
/agent lets play a game
/agent tell me a joke
/agent help me swap 1 eth to usdc

import { HandlerContext, User } from "@xmtp/message-kit";
import { textGeneration } from "../lib/openai.js";
 
export async function handler(context: HandlerContext) {
  if (!process?.env?.OPEN_AI_API_KEY) {
    console.log("No OPEN_AI_API_KEY found in .env");
    return;
  }
 
  const {
    message: {
      content: { content, params },
    },
  } = context;
 
  const systemPrompt = generateSystemPrompt(context);
  try {
    let userPrompt = params?.prompt ?? content;
    console.log("userPrompt", userPrompt);
 
    const { reply } = await textGeneration(userPrompt, systemPrompt);
    console.log("intent:", reply);
    context.intent(reply);
  } catch (error) {
    console.error("Error during OpenAI call:", error);
    await context.reply("An error occurred while processing your request.");
  }
}
 
function generateSystemPrompt(context: HandlerContext) {
  const {
    members,
    commands,
    message: { sender },
  } = context;
 
  const systemPrompt = `
  ### Context
 
  You are a helpful bot agent that lives inside a web3 messaging group that helps interpret user requests and execute commands.
  #### Users
   ${JSON.stringify(members?.map((member: User) => ({ ...member, username: `@${member.username}` })))}\n
  #### Commands
  ${JSON.stringify(commands)}\n
  The message was sent by @${sender?.username}
 
  ### Example s
 
  prompt /agent tip alix and bo
  reply /tip @alix @bo 10
 
  Important:
  - If a user asks jokes, make jokes about web3 devs\n
  - If the user asks about performing an action and you can think of a command that would help, answer directly with the command and nothing else.
  - Populate the command with the correct or random values. Always return commands with real values only, using usernames with @ and excluding addresses.\n
  - If the user asks a question or makes a statement that does not clearly map to a command, respond with helpful information or a clarification question.\n
  - If the user is grateful, respond asking for a tip in a playful manner.
  `;
  return systemPrompt;
}

yarn add openai

import dotenv from "dotenv";
dotenv.config();
 
import OpenAI from "openai";
const openai = new OpenAI({
  apiKey: process.env.OPEN_AI_API_KEY,
});
 
export async function textGeneration(
  userPrompt: string,
  systemPrompt: string,
  chatHistory?: any[],
) {
  let messages = chatHistory ? [...chatHistory] : []; // Start with existing chat history
  if (messages.length === 0) {
    messages.push({
      role: "system",
      content: systemPrompt,
    });
  }
  messages.push({
    role: "user",
    content: userPrompt,
  });
  try {
    const response = await openai.chat.completions.create({
      model: "gpt-4o",
      messages: messages as any,
    });
    const reply = response.choices[0].message.content;
    messages.push({
      role: "assistant",
      content: reply || "No response from OpenAI.",
    });
    const cleanedReply = reply
      ?.replace(/(\*\*|__)(.*?)\1/g, "$2")
      ?.replace(/\[([^\]]+)\]\(([^)]+)\)/g, "$2")
      ?.replace(/^#+\s*(.*)$/gm, "$1")
      ?.replace(/`([^`]+)`/g, "$1")
      ?.replace(/^`|`$/g, "");
 
    return { reply: cleanedReply as string, history: messages };
  } catch (error) {
    console.error("Failed to fetch from OpenAI:", error);
    throw error;
  }
}
 
// New method to interpret an image
export async function vision(imageData: Uint8Array, systemPrompt: string) {
  const base64Image = Buffer.from(imageData).toString("base64");
  const dataUrl = `data:image/jpeg;base64,${base64Image}`;
 
  // Create a new thread for each vision request
  const visionMessages = [
    {
      role: "system",
      content: systemPrompt,
    },
    {
      role: "user",
      content: [
        { type: "text", text: systemPrompt },
        {
          type: "image_url",
          image_url: {
            url: dataUrl,
          },
        },
      ],
    },
  ];
 
  try {
    const response = await openai.chat.completions.create({
      model: "gpt-4o",
      messages: visionMessages as any,
    });
    return response.choices[0].message.content;
  } catch (error) {
    console.error("Failed to interpret image with OpenAI:", error);
    throw error;
  }
}