copy clips

Copy clips from one timeline to another, or from one place on a timeline to another: named clips, every clip starting in a span, or the whole source. The earliest lands at at_seconds (the end of this timeline when omitted) and the rest keep their offsets. Everything travels: trim, speed, framing, keyframes, grade, effects, fades, transitions, volume, text style, layout slot, label, and a linked partner. A source at another frame rate is re-timed so its seconds hold. Each clip lands on track_id when it fits, else on this timeline’s lane of the same kind at the same stack position, else on a new lane. These are copies; to follow the source as it changes, nest it (addClip with timeline_id). A nested clip that would play this timeline is left out and named. Free.

POST

/

tools

/

copy_clips

copy clips

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

import requests

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

payload = {
    "timeline_id": "<string>",
    "from_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>', from_timeline_id: '<string>'})
};

fetch('https://eversince.ai/api/v1/tools/copy_clips', 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.

from_timeline_id

string

required

The timeline the clips are read from; this timeline's own id to duplicate a stretch of it elsewhere on it.

clip_ids

string[]

Clips of the source, by id.

range

object

Every clip of the source that starts inside this span, on any track.

Show child attributes

at_seconds

number

Where the earliest copied clip lands on this timeline. Omitted: after the last clip here.

Required range: x >= 0

track_id

string

A lane of this timeline for the copies of its kind; the rest land by the usual rule.

if_revision

The revision get_timeline returned. A stale one fails with revision_conflict instead of applying; so does no revision once a user edited the timeline in the app since this connection last read it.

context

string

Optional: one sentence shown to the user beside this action.

Maximum string length: 600

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[]

copy clips

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

import requests

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

payload = {
    "timeline_id": "<string>",
    "from_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>', from_timeline_id: '<string>'})
};

fetch('https://eversince.ai/api/v1/tools/copy_clips', 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>"
    }
  }
}