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Lucy Edit Pro is a state-of-the-art video editing model that produces studio-quality results in minutes, not weeks. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

video-to-video
Input

Idle

$0.1per run·~10 / $1

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ExamplesView all

Transform the woman's outfit into a regal medieval gown with flowing velvet fabric, intricate gold embroidery, and a jeweled crown, giving her the appearance of a queen.

Transform the woman's clothes in the video into sportswear.

Add a beard, hair, and sunglasses to the man in the video.

The woman in the video was dressed in high-tech mecha.

Change the woman's clothes in the video to blue.

Related Models

README

Lucy-edit-pro — High-Fidelity Text-Guided Video Editor

Lucy Edit Pro is a high-end, text-guided video editing model for precise, cinematic transformations. Provide a source video and a natural-language prompt, and the model redraws clothing, style, and scene details frame by frame while preserving motion, timing, and composition. Compared with the Dev edition, Pro prioritizes visual fidelity, temporal stability, and 720p output quality.

What Lucy Edit Pro does

  • Advanced prompt-based video editing Transform outfits, add props, restyle scenes, or change visual themes using simple text instructions.

  • Structure-preserving edits Keeps original camera motion, pacing, and blocking; only the requested elements are modified.

  • High temporal consistency Reduces flicker and frame-to-frame drift, especially on detailed clothing, hair, and accessories.

  • 720p-ready quality Designed for sharper, more detailed output suitable for social content, previews, and concept shots.

Inputs

  • video (required): The source clip to edit. The output duration matches the input duration (up to the maximum supported length).

  • prompt (required): A clear description of the desired edit, for example: “Transform the woman’s outfit into a regal medieval gown with a jeweled crown.” “Turn the kitchen into a futuristic laboratory with glowing panels.”

  • resolution

  • 480p

  • 720p

Pricing

ResolutionPrice per second
480p$0.100
720p$0.150

Maximum supported duration per request: 120 seconds.

How to use

  1. Upload or paste the URL of your source video.
  2. Choose the output resolution (480p for cheaper drafts, 720p for higher quality).
  3. Write a focused prompt describing exactly what should change and what should remain.
  4. Run the model and review the edited clip.
  5. Refine the prompt and rerun to iterate on details such as style, color, or accessories.

Tips for best results

  • Use well-lit, reasonably clean footage; extreme compression and heavy motion blur reduce quality.
  • Keep prompts specific (“Replace her clothes with a red sci-fi pilot suit with metallic details”) rather than vague.
  • When iterating, keep the core prompt stable and only adjust small parts to maintain consistency.
Note:This website uses AI models provided by third parties. Documentation prices are for reference and may be outdated. The Generate button shows an estimate; the final task charge prevails.

Lucy Edit Pro API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/decart/lucy-edit-pro with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Lucy Edit Pro below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "resolution": "720p"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/decart/lucy-edit-pro" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/decart/lucy-edit-pro";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
        "resolution": "720p"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
    "resolution": "720p"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/decart/lucy-edit-pro", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Lucy Edit Pro API — Frequently asked questions

What is the Lucy Edit Pro API?

Lucy Edit Pro is a Decart model for video editing, exposed as a REST API on WaveSpeedAI. Lucy Edit Pro is a state-of-the-art video editing model that produces studio-quality results in minutes, not weeks. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Lucy Edit Pro API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/decart/decart-lucy-edit-pro.

How much does Lucy Edit Pro cost per run?

Lucy Edit Pro starts at $0.10 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does Lucy Edit Pro accept?

Key inputs: `prompt`, `video`, `resolution`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/decart/decart-lucy-edit-pro.

How long does Lucy Edit Pro take to generate?

Median end-to-end generation time on WaveSpeedAI is around 129 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Lucy Edit Pro outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Decart). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Lucy Edit Pro | AI Video Editing API on WaveSpeedAI