Example: Support Agent

import express from 'express';
import { CommuneClient } from 'commune-ai';
import OpenAI from 'openai';

const app = express();
const commune = new CommuneClient({ apiKey: process.env.COMMUNE_API_KEY });
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });

// Step 1: Handle inbound emails
app.post('/webhook/email', express.json(), async (req, res) => {
  const { message, extractedData, security } = req.body;

  // Step 2: Check security
  if (security?.spam?.flagged) {
    console.log('Spam detected, skipping');
    return res.json({ ok: true });
  }

  if (security?.prompt_injection?.risk_level === 'critical') {
    console.log('Prompt injection detected, skipping');
    return res.json({ ok: true });
  }

  const sender = message.participants.find(
    (p: any) => p.role === 'sender'
  )?.identity;
  const subject = message.metadata.subject;
  const content = message.content;

  // Step 3: Use extracted data for routing
  const intent = extractedData?.intent || 'general';
  const urgency = extractedData?.urgency || 'medium';
  const orderNumber = extractedData?.order_number;

  console.log(`New ${urgency} ${intent} ticket from ${sender}`);
  if (orderNumber) console.log(`Order: ${orderNumber}`);

  // Step 4: Generate reply with LLM
  const completion = await openai.chat.completions.create({
    model: 'gpt-4o',
    messages: [
      {
        role: 'system',
        content: `You are a helpful customer support agent for Acme Corp. 
Be concise, empathetic, and solution-oriented. 
If you don't have enough info to resolve the issue, ask a specific follow-up question.
Never make up order statuses or tracking numbers.`,
      },
      {
        role: 'user',
        content: `Customer email:
Subject: ${subject}
From: ${sender}
Intent: ${intent}
Urgency: ${urgency}
${orderNumber ? `Order: ${orderNumber}` : ''}

Message:
${content}`,
      },
    ],
  });

  const reply = completion.choices[0].message.content;

  // Step 5: Send reply in the same thread
  await commune.messages.send({
    to: sender,
    subject: `Re: ${subject}`,
    html: `<p>${reply.replace(/\n/g, '<br>')}</p>`,
    text: reply,
    thread_id: message.thread_id,
  });

  console.log(`Replied to ${sender} in thread ${message.thread_id}`);

  res.json({ ok: true });
});

app.listen(3000, () => console.log('Support agent running on :3000'));

from flask import Flask, request
from commune import CommuneClient
from openai import OpenAI

app = Flask(__name__)
commune_client = CommuneClient(api_key="comm_...")
openai_client = OpenAI(api_key="sk-...")


@app.route("/webhook/email", methods=["POST"])
def handle_email():
    data = request.json
    message = data["message"]
    extracted = data.get("extractedData", {})
    security = data.get("security", {})

    # Check security
    if security.get("spam", {}).get("flagged"):
        return {"ok": True}
    if security.get("prompt_injection", {}).get("risk_level") == "critical":
        return {"ok": True}

    sender = next(
        p["identity"] for p in message["participants"] if p["role"] == "sender"
    )
    subject = message["metadata"]["subject"]
    content = message["content"]
    intent = extracted.get("intent", "general")
    urgency = extracted.get("urgency", "medium")
    order_number = extracted.get("order_number")

    # Generate reply
    completion = openai_client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {
                "role": "system",
                "content": (
                    "You are a helpful customer support agent for Acme Corp. "
                    "Be concise, empathetic, and solution-oriented."
                ),
            },
            {
                "role": "user",
                "content": f"Subject: {subject}\nFrom: {sender}\n"
                f"Intent: {intent}, Urgency: {urgency}\n"
                f"{'Order: ' + order_number if order_number else ''}\n\n"
                f"{content}",
            },
        ],
    )

    reply = completion.choices[0].message.content

    # Send reply in thread
    commune_client.messages.send(
        to=sender,
        subject=f"Re: {subject}",
        html=f"<p>{reply}</p>",
        text=reply,
        thread_id=message["thread_id"],
    )

    return {"ok": True}


if __name__ == "__main__":
    app.run(port=3000)