CRM Timeline

curl -X POST https://vibecode.bitrix24.com/v1/timeline-logs \
  -H "X-Api-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "entityTypeId": 2,
    "entityId": 100,
    "title": "AI agent processed the request",
    "text": "Client data analyzed. Recommendation: offer the Enterprise plan."
  }'

{
  "success": true,
  "data": {
    "id": 5012,
    "created": "2026-04-27T10:00:00+00:00",
    "authorId": 1,
    "title": "AI agent processed the request",
    "text": "Client data analyzed. Recommendation: offer the Enterprise plan.",
    "iconCode": ""
  }
}

curl -X POST https://vibecode.bitrix24.com/v1/timeline-logs/5012/pin \
  -H "X-Api-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "entityTypeId": 2, "entityId": 100 }'

curl -X POST https://vibecode.bitrix24.com/v1/timeline-logs/5012/note \
  -H "X-Api-Key: YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{ "entityTypeId": 2, "entityId": 100, "text": "The client usually responds within 2 days." }'

const VIBE_KEY = process.env.VIBE_KEY
const BASE = 'https://vibecode.bitrix24.com/v1'

async function api(method, path, body = null) {
  const opts = { method, headers: { 'X-Api-Key': VIBE_KEY } }
  if (body) {
    opts.headers['Content-Type'] = 'application/json'
    opts.body = JSON.stringify(body)
  }
  const res = await fetch(`${BASE}${path}`, opts)
  return res.json()
}

const dealId = 100
const contactId = 50
const companyId = 10

// 1. Record that work has started
const start = await api('POST', '/timeline-logs', {
  entityTypeId: 2,
  entityId: dealId,
  title: 'AI agent started processing',
  text: 'Client data analysis, credit-limit check, quote preparation.',
})
const startId = start.data.id

// 2. Bind the entry to the contact and the company — managers of both will see
//    the same event in their timelines
await api('POST', `/timeline-logs/${startId}/bind`, { entityTypeId: 3, entityId: contactId })
await api('POST', `/timeline-logs/${startId}/bind`, { entityTypeId: 4, entityId: companyId })

// ... the AI agent does its work ...

// 3. Record the result as a separate log entry
const result = await api('POST', '/timeline-logs', {
  entityTypeId: 2,
  entityId: dealId,
  title: 'AI agent finished processing',
  text: [
    '[b]Analysis results:[/b]',
    '- Credit limit: OK (500,000 USD)',
    '- Recommended plan: Enterprise',
    '- Discount: 10% (returning client)',
    '- Quote generated and sent by email',
  ].join('\n'),
})
const resultId = result.data.id

// 4. Pin the final entry at the top of the timeline
await api('POST', `/timeline-logs/${resultId}/pin`, { entityTypeId: 2, entityId: dealId })

// 5. Leave an internal note for the manager
await api('POST', `/timeline-logs/${resultId}/note`, {
  entityTypeId: 2,
  entityId: dealId,
  text: 'The client usually responds within 2 days. Remind the manager if there is no reply.',
})

console.log('AI agent finished, all actions logged')