publish to feed

Put a timeline or a canvas on the workspace feed as one post, drawn live with nothing rendered: a timeline plays where it sits, its versions (create with parent) as tiles after it, a project of clips as its clips, a canvas as its slides. The post follows every later edit. A clip’s or version’s id publishes its project’s post (version names the tile); one alone: copy it out (manage_timelines create with from, no parent), publish the copy. One already up returns its post, already_up: true. unpublish: true takes it off; publishing again restores it. Free.

POST

tools

publish_to_feed

publish to feed

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

import requests

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

payload = {
    "timeline_id": "<string>",
    "canvas_id": "<string>",
    "unpublish": True,
    "context": "<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>',
    canvas_id: '<string>',
    unpublish: true,
    context: '<string>'
  })
};

fetch('https://eversince.ai/api/v1/tools/publish_to_feed', 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,
      "charged_minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "held_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,
      "charged_minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "held_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 default: for a key or a connected agent, one of the workspaces the user allowed it.

Body

application/json

timeline_id

string

The timeline. Give this or canvas_id.

canvas_id

string

The canvas. Give this or timeline_id.

unpublish

boolean

Take the post off the feed instead of publishing. The work stays.

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).

any

required

data

object

required

meta

object

required

Show child attributes

media

object[]

publish to feed

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

import requests

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

payload = {
    "timeline_id": "<string>",
    "canvas_id": "<string>",
    "unpublish": True,
    "context": "<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>',
    canvas_id: '<string>',
    unpublish: true,
    context: '<string>'
  })
};

fetch('https://eversince.ai/api/v1/tools/publish_to_feed', 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,
      "charged_minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "held_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,
      "charged_minutes": 123,
      "queued_minutes": 123,
      "left_minutes": 123,
      "held_minutes": 123,
      "bought_minutes": 123,
      "note": "<string>"
    }
  }
}

Discovery

Timeline

Workspace

Library

Canvas

Generation

Research

Account

Models

Uploads

Webhooks

publish to feed

Authorizations

Headers

Body

Response