curl --location --request POST 'https://dashboard.laburen.com/api/agents/<agentId>/follow-up/query' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer <API_KEY>' \
--data-raw '{
    "messages": [
        { "from": "human", "text": "Hi, how much is the Wave?" },
        { "from": "agent", "text": "Hello! It is $120. Do you want the 40cm or the 52cm one?" },
        { "from": "human", "text": "The 52cm. Do you ship to Cordoba?" },
        { "from": "agent", "text": "Yes, it takes 3 business days. Should I reserve one for you?" }
    ]
}'

const apiUrl = 'https://dashboard.laburen.com/api';
const apiKey = '<API_KEY>';
const agentId = '<agentId>';

const response = await fetch(`${apiUrl}/agents/${agentId}/follow-up/query`, {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json',
    'Authorization': `Bearer ${apiKey}`,
  },
  body: JSON.stringify({
    // Run the follow-up over an existing conversation
    conversationId: 'clxxxxxxxxxxxxxxxxx',
    // Optional: try a prompt variant without editing the agent
    // prompt: 'Be brief, one sentence, and offer to schedule a call.',
    // Optional: skip the classification step
    // skipFilter: true,
  }),
});

const data = await response.json();
console.log(data.answer);
console.log(data.filter); // { verdict: 'follow_up_conversation', wouldSend: true }

import requests

api_url = "https://dashboard.laburen.com/api"
api_key = "<API_KEY>"
agent_id = "<agentId>"

response = requests.post(
    f"{api_url}/agents/{agent_id}/follow-up/query",
    headers={
        "Content-Type": "application/json",
        "Authorization": f"Bearer {api_key}",
    },
    json={
        # Run the follow-up over an existing conversation
        "conversationId": "clxxxxxxxxxxxxxxxxx",
        # Optional: try a prompt variant without editing the agent
        # "prompt": "Be brief, one sentence, and offer to schedule a call.",
        # Optional: skip the classification step
        # "skipFilter": True,
    },
)

data = response.json()
print(data["answer"])
print(data["filter"])

{
  "answer": "Should I reserve the 52cm Wave for you? Happy to jump on a quick call to confirm the shipping to Cordoba.",
  "filter": {
    "verdict": "follow_up_conversation",
    "wouldSend": true
  },
  "prompt": "Be brief, one sentence, and offer to schedule a call.",
  "promptSource": "request",
  "conversationId": "clxxxxxxxxxxxxxxxxx",
  "messageId": null,
  "model": "gpt-4.1-mini",
  "usage": {
    "inputTokens": 343,
    "outputTokens": 83
  }
}