Reframe

Product ID: reframe · Billing: Beeble Cloud credits

Before you start

Create an API key for an organization with this product enabled.
Prepare your media as Beeble URIs, authorized CDN URLs, public/presigned HTTPS URLs, or base64 data URIs.
Select an available model below; complete any required consent in Beeble Cloud.

Models and inputs

Set BEEBLE_API_KEY and, for internal teams, BEEBLE_TEAM_ID.

curl --fail-with-body "https://api.beeble.ai/v1/products/reframe/models" \
  -H "x-api-key: $BEEBLE_API_KEY" \
  -H "X-Beeble-Team-Id: ${BEEBLE_TEAM_ID:-}"

import json
import os
import requests

headers = {"x-api-key": os.environ["BEEBLE_API_KEY"]}
if team_id := os.environ.get("BEEBLE_TEAM_ID"):
    headers["X-Beeble-Team-Id"] = team_id

response = requests.get(
    "https://api.beeble.ai/v1/products/reframe/models",
    headers=headers,
    timeout=30,
)
response.raise_for_status()
print(json.dumps(response.json(), indent=2))

const headers = { "x-api-key": process.env.BEEBLE_API_KEY }
if (process.env.BEEBLE_TEAM_ID) {
  headers["X-Beeble-Team-Id"] = process.env.BEEBLE_TEAM_ID
}
const response = await fetch(
  "https://api.beeble.ai/v1/products/reframe/models",
  {
    headers,
    signal: AbortSignal.timeout(30_000),
  },
)
if (!response.ok) throw new Error(await response.text())
console.log(JSON.stringify(await response.json(), null, 2))

Response (200): models contains each model’s id, name, input_schema, and any requires_consent value. Use the selected model’s input_schema for required inputs, types, defaults, and supported values. Request parameters and response schema Set the new canvas dimensions and the source rectangle together. A reference image is required to guide newly revealed areas; a prompt is optional. The example assumes a 960 × 720 source placed on a 1280 × 720 canvas.

Submit a job

Schemas: Request body · Response. The inputs object follows your selected model’s input_schema above. Save as request.json with your media URIs. The Beeble URIs below can be replaced with any supported single-file media input. Use a unique idempotency_key for each new job; keep it unchanged on retries.

{
  "model_id": "reframe-1",
  "billing_unit": "credits",
  "idempotency_key": "reframe-example-001",
  "inputs": {
    "source": "beeble://uploads/your-upload-id/source.png",
    "reference_image": "beeble://uploads/your-reference-upload-id/reference.png",
    "generation_type": "image",
    "prompt": "Extend the surrounding studio",
    "max_resolution": 720,
    "canvas_width": 1280,
    "canvas_height": 720,
    "source_x": 160,
    "source_y": 0,
    "source_width": 960,
    "source_height": 720
  }
}

Python requires requests; JavaScript examples run in Node.js.

curl --fail-with-body https://api.beeble.ai/v1/products/reframe/jobs \
  -H "x-api-key: $BEEBLE_API_KEY" \
  -H "X-Beeble-Team-Id: ${BEEBLE_TEAM_ID:-}" \
  -H "Content-Type: application/json" \
  --data-binary @request.json

import json
import os
from pathlib import Path

import requests

headers = {"x-api-key": os.environ["BEEBLE_API_KEY"]}
if team_id := os.environ.get("BEEBLE_TEAM_ID"):
    headers["X-Beeble-Team-Id"] = team_id

response = requests.post(
    "https://api.beeble.ai/v1/products/reframe/jobs",
    headers=headers,
    json=json.loads(Path("request.json").read_text()),
    timeout=120,
)
response.raise_for_status()
job_id = response.json()["id"]
print(job_id)

import { readFile } from "node:fs/promises"

const headers = {
  "x-api-key": process.env.BEEBLE_API_KEY,
  "Content-Type": "application/json",
}
if (process.env.BEEBLE_TEAM_ID) {
  headers["X-Beeble-Team-Id"] = process.env.BEEBLE_TEAM_ID
}

const response = await fetch("https://api.beeble.ai/v1/products/reframe/jobs", {
  method: "POST",
  headers,
  body: await readFile("request.json", "utf8"),
  signal: AbortSignal.timeout(120_000),
})
if (!response.ok) throw new Error(await response.text())
const { id: jobId } = await response.json()
console.log(jobId)

Response (202, abbreviated):

{
  "id": "dap_example",
  "status": "processing",
  "outputs": {}
}

Results and constraints

Supply canvas_width, canvas_height, source_x, source_y, source_width, and source_height together, in pixels. Canvas and placement dimensions must be positive. These values describe your desired layout and are not inferred from the source. The server measures source media metadata; you can omit generation_type and frame_count. See Billing & credits for spending caps and refunds.

Completed response

Poll the job using the returned id until status is success. Stop on failed, cancelled, or credit_required. Example response (200, success; abbreviated): URLs are illustrative. Available outputs depend on the model and input media.

{
  "id": "dap_example",
  "product": "reframe",
  "status": "success",
  "outputs": {
    "render": "https://cdn.beeble.ai/example/render.png?signed-parameters",
    "source": "https://cdn.beeble.ai/example/source.png?signed-parameters"
  }
}

Download outputs.render for the reframed image or video.

Get started

Products

Core concepts

Integrations

Before you start

Models and inputs

Submit a job

Results and constraints

Completed response

​Before you start

​Models and inputs

​Submit a job

​Results and constraints

​Completed response

Before you start

Models and inputs

Submit a job

Results and constraints

Completed response