get timeline

Read a timeline: settings, caption style, tracks, clips with stable ids, markers, gaps, caption-group summaries and the revision. response_format detailed adds everything updateClip can set (fades, transitions, grade, effects, text styling, a graphic’s knobs); a clip’s spoken text and a graphic’s source code come only when fields names them. A read stops at about 60,000 characters of clips, whole tracks first, says so in cut_short, and next_cursor reads on; time_range, tracks and fields narrow it. local_only marks a clip the cloud cannot render until its media syncs. history is the revision log undo takes; media the items and documents the timeline works with. Ids come back shortened and are passed back as received. Free.

POST

/

tools

/

get_timeline

get timeline

curl --request POST \
  --url https://eversince.ai/api/v1/tools/get_timeline \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "timeline_id": "<string>"
}
'

import requests

url = "https://eversince.ai/api/v1/tools/get_timeline"

payload = { "timeline_id": "<string>" }
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({timeline_id: '<string>'})
};

fetch('https://eversince.ai/api/v1/tools/get_timeline', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

{
  "ok": true,
  "data": {},
  "meta": {
    "request_id": "<string>",
    "cost": {},
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  },
  "media": [
    {}
  ]
}

{
  "ok": false,
  "error": {
    "code": "<string>",
    "message": "<string>",
    "retryable": true,
    "suggested_action": "<string>",
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  }
}

Authorizations

Authorization

string

header

required

An API key (es_live_…) from Settings, under API keys, or an OAuth access token.

Headers

Idempotency-Key

string

Retry a paid dispatch safely: the same key returns the job already dispatched instead of charging again.

x-workspace-id

string

The workspace this one call acts in, when it is not the key's own.

Body

application/json

timeline_id

string

required

The timeline id.

time_range

tuple

[start, end] in frames; only clips overlapping this window.

Show child attributes

tracks

string[]

Only these track ids.

fields

string[]

Only these clip fields in the response.

response_format

enum<string>

concise (default): every track and clip with key fields. detailed: everything updateClip can set (fades, transitions, grade, effects, text styling, a graphic's knobs), for matching a look or patching a clip whole. A clip's spoken text and a graphic's source code come only when fields names them.

Available options:

concise,

detailed

history

integer

Include this many recent revisions, newest first.

Required range: 1 <= x <= 50

media

boolean

Include how many library items the timeline works with and its documents by title. timeline_media reads and changes the whole set.

limit

integer

At most this many clips. Default: as many as fit the read.

Required range: 1 <= x <= 2000

cursor

string

next_cursor from the answer before, with the other fields the same: the rest of a timeline a read cut short.

Response

Done, or a job started for work that runs longer (follow it with get_jobs).

ok

any

required

data

object

required

meta

object

required

Show child attributes

media

object[]

get timeline

curl --request POST \
  --url https://eversince.ai/api/v1/tools/get_timeline \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "timeline_id": "<string>"
}
'

import requests

url = "https://eversince.ai/api/v1/tools/get_timeline"

payload = { "timeline_id": "<string>" }
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({timeline_id: '<string>'})
};

fetch('https://eversince.ai/api/v1/tools/get_timeline', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

{
  "ok": true,
  "data": {},
  "meta": {
    "request_id": "<string>",
    "cost": {},
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  },
  "media": [
    {}
  ]
}

{
  "ok": false,
  "error": {
    "code": "<string>",
    "message": "<string>",
    "retryable": true,
    "suggested_action": "<string>",
    "cloud_processing": {
      "ran_on": "cloud",
      "minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  }
}