Reply Extraction

{
  "message_id": "msg_9kL2xYw1pQm3",
  "from": "customer@company.com",
  "to": ["agent@daimon.email"],
  "subject": "Re: Support ticket #1234",

  "text_body": "Thanks for the quick fix!\n\nOn March 15, 2026 at 2:30 PM, Agent <agent@daimon.email> wrote:\n> Hi,\n> I've resolved the issue. Please try again.\n> Best,\n> Agent",

  "reply_body": "Thanks for the quick fix!",

  "html_body": "<div>Thanks for the quick fix!</div><div class='gmail_quote'>On March 15, 2026 at 2:30 PM, Agent &lt;agent@daimon.email&gt; wrote:<blockquote>Hi,<br>I've resolved the issue...</blockquote></div>"
}

app.post('/webhooks/daimon', async (req, res) => {
  const event = req.body;

  if (event.type === 'message.received') {
    const message = event.data;

    // ✅ Use reply_body for AI processing
    const sentiment = await analyzeSentiment(message.reply_body);
    const intent = await classifyIntent(message.reply_body);

    console.log('Customer replied:', message.reply_body);
    console.log('Sentiment:', sentiment); // "positive"
    console.log('Intent:', intent); // "gratitude"

    // Generate response based on clean reply
    const response = await generateResponse(message.reply_body);

    await client.inboxes.send(message.inbox_id, {
      to: message.from,
      subject: `Re: ${message.subject}`,
      text: response,
      thread_id: message.thread_id,
    });
  }

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

@app.route('/webhooks/daimon', methods=['POST'])
def handle_webhook():
    event = request.json

    if event['type'] == 'message.received':
        message = event['data']

        # ✅ Use reply_body for AI processing
        sentiment = analyze_sentiment(message['reply_body'])
        intent = classify_intent(message['reply_body'])

        print(f"Customer replied: {message['reply_body']}")
        print(f"Sentiment: {sentiment}")
        print(f"Intent: {intent}")

        # Generate response
        response = generate_response(message['reply_body'])

        client.inboxes.send(
            inbox_id=message['inbox_id'],
            to=message['from'],
            subject=f"Re: {message['subject']}",
            text=response,
            thread_id=message['thread_id']
        )

    return {'received': True}

{
  "message_id": "msg_9kL2xYw1pQm3",
  "from": "noreply@service.com",
  "subject": "Verify your email address",

  "reply_body": "Click here to verify: https://service.com/verify?token=abc123xyz\n\nIf you didn't request this, ignore this email.",

  "links": [
    "https://service.com/verify?token=abc123xyz"
  ],

  "cta_links": [
    {
      "url": "https://service.com/verify?token=abc123xyz",
      "type": "verification",
      "confidence": 0.95
    }
  ]
}

// Handle verification email
app.post('/webhooks/daimon', async (req, res) => {
  const event = req.body;

  if (event.type === 'message.received') {
    const message = event.data;

    // Check for verification links
    const verifyLink = message.cta_links.find(
      link => link.type === 'verification'
    );

    if (verifyLink) {
      console.log('Verification link detected:', verifyLink.url);

      // Agent can automatically click verification links
      await fetch(verifyLink.url, { method: 'GET' });
      console.log('Email verified automatically');
    }
  }

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

@app.route('/webhooks/daimon', methods=['POST'])
def handle_webhook():
    event = request.json

    if event['type'] == 'message.received':
        message = event['data']

        # Check for verification links
        verify_links = [
            link for link in message['cta_links']
            if link['type'] == 'verification'
        ]

        if verify_links:
            verify_url = verify_links[0]['url']
            print(f"Verification link detected: {verify_url}")

            # Agent can auto-click verification
            requests.get(verify_url)
            print('Email verified automatically')

    return {'received': True}

// Fetch message
const message = await client.inboxes.getMessage(inboxId, messageId);

console.log('=== FULL TEXT ===');
console.log(message.text_body);

console.log('\n=== EXTRACTED REPLY ===');
console.log(message.reply_body);

console.log('\n=== LINKS ===');
console.log(message.links);

console.log('\n=== CTA LINKS ===');
console.log(message.cta_links);

# Fetch message
message = client.inboxes.get_message(inbox_id, message_id)

print('=== FULL TEXT ===')
print(message['text_body'])

print('\n=== EXTRACTED REPLY ===')
print(message['reply_body'])

print('\n=== LINKS ===')
print(message['links'])

print('\n=== CTA LINKS ===')
print(message['cta_links'])

import Anthropic from '@anthropic-ai/sdk';

const anthropic = new Anthropic({ apiKey: process.env.ANTHROPIC_API_KEY });

async function extractReplyWithLLM(fullText: string): Promise<string> {
  const response = await anthropic.messages.create({
    model: 'claude-3-5-sonnet-20241022',
    max_tokens: 1024,
    messages: [{
      role: 'user',
      content: `Extract only the fresh reply text from this email, excluding any quoted history, signatures, or disclaimers:\n\n${fullText}`,
    }],
  });

  return response.content[0].text;
}

// Use custom extraction
const customReply = await extractReplyWithLLM(message.text_body);
console.log('LLM-extracted reply:', customReply);

import anthropic

client = anthropic.Anthropic(api_key=os.environ['ANTHROPIC_API_KEY'])

def extract_reply_with_llm(full_text: str) -> str:
    response = client.messages.create(
        model='claude-3-5-sonnet-20241022',
        max_tokens=1024,
        messages=[{
            'role': 'user',
            'content': f"Extract only the fresh reply text from this email, excluding any quoted history, signatures, or disclaimers:\n\n{full_text}"
        }]
    )

    return response.content[0].text

# Use custom extraction
custom_reply = extract_reply_with_llm(message['text_body'])
print(f"LLM-extracted reply: {custom_reply}")