Video generation: Seedance 2.0

Seedance 2.0 (ByteDance) is a multimodal video generation model. It supports four input types — text-to-video, image-to-video, first-last frame, and reference-video — and the output includes synced audio by default. RuAPI exposes an OpenAI-compatible async video API: submit a task → poll status → download the video. Billed in USDT, no foreign card required.

Audio is on by default — Seedance 2.0 videos come with a synced audio track (dialogue / ambient / SFX), no extra parameters needed.

Generated videos are kept for 7 days only. Download and save them right after generation; the link stops working once it expires.

Available models

Model ID	Description
`doubao-seedance-2.0-fast`	Faster and cheaper, the default choice
`doubao-seedance-2.0`	Full version with higher quality
`doubao-seedance-2.0-mini`	The cheapest option — for drafts and tests

For exact prices, see the pricing page (video is billed per token).

URLs & auth

Base URL: https://www.ruapi.ai/v1
Auth: header Authorization: Bearer sk-YOUR_KEY (create one in the console under “API Keys”)

Generation is async, in three steps:

Submit a task

POST /v1/videos → returns a task id

Poll the status

GET /v1/videos/{id} → until status becomes completed

Download the video

GET /v1/videos/{id}/content → get the MP4

Step 1. Submit a task (text-to-video)

curl https://www.ruapi.ai/v1/videos \
  -H "Authorization: Bearer sk-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-2.0-fast",
    "prompt": "Night city, neon reflecting on wet streets, cyberpunk style, camera slowly pushing in",
    "seconds": "5",
    "metadata": { "resolution": "720p", "ratio": "16:9" }
  }'

import requests

resp = requests.post(
    "https://www.ruapi.ai/v1/videos",
    headers={"Authorization": "Bearer sk-YOUR_KEY"},
    json={
        "model": "doubao-seedance-2.0-fast",
        "prompt": "Night city, neon reflecting on wet streets, cyberpunk style, camera slowly pushing in",
        "seconds": "5",
        "metadata": {"resolution": "720p", "ratio": "16:9"},
    },
)
task_id = resp.json()["id"]
print("Task submitted:", task_id)

const resp = await fetch("https://www.ruapi.ai/v1/videos", {
  method: "POST",
  headers: {
    Authorization: "Bearer sk-YOUR_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    model: "doubao-seedance-2.0-fast",
    prompt: "Night city, neon reflecting on wet streets, cyberpunk style, camera slowly pushing in",
    seconds: "5",
    metadata: { resolution: "720p", ratio: "16:9" },
  }),
});
const { id } = await resp.json();
console.log("Task submitted:", id);

Response (id is the task number, used in the next two steps):

{
  "id": "task_guXmm9BZpLpYaxfky7mkR2kSlRtgDSe9",
  "object": "video",
  "model": "doubao-seedance-2.0-fast",
  "status": "queued",
  "progress": 0,
  "created_at": 1783579686
}

Step 2. Poll the status

Query the GET /v1/videos/{id} route about every 5 seconds. status goes through queued → in_progress → completed.

curl https://www.ruapi.ai/v1/videos/task_YOUR_TASK_ID \
  -H "Authorization: Bearer sk-YOUR_KEY"

import requests

r = requests.get(
    f"https://www.ruapi.ai/v1/videos/{task_id}",
    headers={"Authorization": "Bearer sk-YOUR_KEY"},
).json()
print(r["status"], r.get("progress"))

Once complete (metadata.url is the download link):

{
  "id": "task_guXmm9BZpLpYaxfky7mkR2kSlRtgDSe9",
  "object": "video",
  "status": "completed",
  "progress": 100,
  "metadata": {
    "url": "https://www.ruapi.ai/v1/videos/task_guXmm9BZpLpYaxfky7mkR2kSlRtgDSe9/content"
  }
}

Step 3. Download the video

curl -L https://www.ruapi.ai/v1/videos/task_YOUR_TASK_ID/content \
  -H "Authorization: Bearer sk-YOUR_KEY" \
  -o seedance.mp4

video = requests.get(
    f"https://www.ruapi.ai/v1/videos/{task_id}/content",
    headers={"Authorization": "Bearer sk-YOUR_KEY"},
)
with open("seedance.mp4", "wb") as f:
    f.write(video.content)
print("Saved seedance.mp4")

Full example: the whole flow in one script

Copy-paste and run, replacing sk-YOUR_KEY with your own key:

Python

import time
import requests

BASE = "https://www.ruapi.ai/v1"
HEADERS = {"Authorization": "Bearer sk-YOUR_KEY"}

# 1) Submit a task
resp = requests.post(
    f"{BASE}/videos",
    headers=HEADERS,
    json={
        "model": "doubao-seedance-2.0-fast",
        "prompt": "Night city, neon reflecting on wet streets, cyberpunk style, camera slowly pushing in",
        "seconds": "5",
        "metadata": {"resolution": "720p", "ratio": "16:9"},
    },
)
resp.raise_for_status()
task_id = resp.json()["id"]
print("Task submitted:", task_id)

# 2) Poll until done (usually 1-3 minutes)
while True:
    r = requests.get(f"{BASE}/videos/{task_id}", headers=HEADERS).json()
    print("Status:", r.get("status"), r.get("progress"))
    if r.get("status") == "completed":
        break
    if r.get("status") == "failed":
        raise RuntimeError(f"Generation failed: {r.get('error')}")
    time.sleep(5)

# 3) Download (result is kept 7 days — save it promptly)
video = requests.get(f"{BASE}/videos/{task_id}/content", headers=HEADERS)
with open("seedance.mp4", "wb") as f:
    f.write(video.content)
print("Saved seedance.mp4")

The same with curl

One command for macOS, Linux and Windows (Git Bash / WSL): it submits the task, waits until it is ready (usually 1–3 minutes) and saves seedance.mp4. Put your key on the first line. If anything goes wrong, it prints the API response with the reason.

KEY="sk-YOUR_KEY"

ID=$(curl -sS https://www.ruapi.ai/v1/videos \
  -H "Authorization: Bearer $KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-2.0-fast",
    "prompt": "A night city, neon reflecting on wet asphalt, cyberpunk, slow camera push-in",
    "seconds": "5",
    "metadata": { "resolution": "720p", "ratio": "16:9" }
  }' | tee resp.json | grep -o '"id": *"[^"]*"' | head -n 1 | cut -d'"' -f4)
echo "Task: $ID"

while [ -n "$ID" ]; do
  STATUS=$(curl -sS "https://www.ruapi.ai/v1/videos/$ID" -H "Authorization: Bearer $KEY" \
    | tee resp.json | grep -o '"status": *"[^"]*"' | head -n 1 | cut -d'"' -f4)
  echo "Status: $STATUS"
  if [ "$STATUS" = "completed" ]; then
    curl -sSL "https://www.ruapi.ai/v1/videos/$ID/content" -H "Authorization: Bearer $KEY" -o seedance.mp4 \
      && echo "Saved: seedance.mp4"
    break
  fi
  if [ "$STATUS" = "failed" ] || [ -z "$STATUS" ]; then cat resp.json; break; fi
  sleep 5
done
[ -z "$ID" ] && cat resp.json

Parameters

Top-level fields:

Field	Type	Description
`model`	string	`doubao-seedance-2.0-fast`, `doubao-seedance-2.0` or `doubao-seedance-2.0-mini`
`prompt`	string	Required. Text description of the scene
`seconds`	string	Duration (sec), 4–15, e.g. `"5"`, `"10"`
`metadata`	object	Resolution, aspect ratio, image/video inputs — see below

Fields inside metadata:

Field	Type	Description
`resolution`	string	`"480p"` / `"720p"` / `"1080p"`
`ratio`	string	Aspect ratio, e.g. `"16:9"`, `"9:16"`, `"1:1"`
`input_type`	string	Input type (usually omit — auto-detected): `text_to_video` / `first_last_frame` / `reference`
`images`	string[]	Array of image URLs (for image-to-video)
`videos`	string[]	Array of video URLs (for reference-video)

Higher resolution and longer duration use more tokens and cost more. If unsure, start with 480p / 5 seconds, then tune.

The four input modes

input_type usually doesn’t need to be set — it’s inferred from the number of images/videos; you can also set it explicitly via metadata.input_type.

Mode	How to pass input	Inferred `input_type`
Text-to-video	`prompt` only	`text_to_video`
Image-to-video	`metadata.images` — 1 image	`reference`
First-last frame	`metadata.images` — 2 images	`first_last_frame`
Reference-video	`metadata.videos` — 1 video	`reference`

Images / videos must be publicly reachable URLs (the server has to download them); images support JPG / PNG / WebP, videos support MP4. base64 inline is not supported (an oversized request body will fail).

Below, each mode shows only step 1 “Submit”; steps 2 (poll) and 3 (download) are identical for all modes.

Mode 1. Text-to-video

Just a text prompt — generated entirely from the description.

curl https://www.ruapi.ai/v1/videos \
  -H "Authorization: Bearer sk-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-2.0-fast",
    "prompt": "Night city, neon reflecting on wet streets, cyberpunk style, camera slowly pushing in",
    "seconds": "5",
    "metadata": { "resolution": "720p", "ratio": "16:9" }
  }'

import requests

resp = requests.post(
    "https://www.ruapi.ai/v1/videos",
    headers={"Authorization": "Bearer sk-YOUR_KEY"},
    json={
        "model": "doubao-seedance-2.0-fast",
        "prompt": "Night city, neon reflecting on wet streets, cyberpunk style, camera slowly pushing in",
        "seconds": "5",
        "metadata": {"resolution": "720p", "ratio": "16:9"},
    },
)
print(resp.json()["id"])  # get the task id, then poll & download as in the full script above

Mode 2. Image-to-video (1 image)

Put 1 image URL in metadata.images; it’s used as the basis to animate. Describe the motion / camera in prompt.

curl https://www.ruapi.ai/v1/videos \
  -H "Authorization: Bearer sk-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-2.0-fast",
    "prompt": "The person in the image smiles and waves naturally, camera slowly pushing in",
    "seconds": "5",
    "metadata": {
      "resolution": "720p",
      "ratio": "16:9",
      "images": ["https://your-domain/portrait.jpg"]
    }
  }'

import requests

resp = requests.post(
    "https://www.ruapi.ai/v1/videos",
    headers={"Authorization": "Bearer sk-YOUR_KEY"},
    json={
        "model": "doubao-seedance-2.0-fast",
        "prompt": "The person in the image smiles and waves naturally, camera slowly pushing in",
        "seconds": "5",
        "metadata": {
            "resolution": "720p",
            "ratio": "16:9",
            "images": ["https://your-domain/portrait.jpg"],
        },
    },
)
print(resp.json()["id"])

Mode 3. First-last frame (2 images)

Put 2 images in metadata.images: the 1st = start frame, the 2nd = end frame. It generates a smooth transition from the first to the second.

curl https://www.ruapi.ai/v1/videos \
  -H "Authorization: Bearer sk-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-2.0-fast",
    "prompt": "Smooth transition from the first frame to the second, natural camera motion, cinematic",
    "seconds": "5",
    "metadata": {
      "resolution": "720p",
      "ratio": "16:9",
      "images": [
        "https://your-domain/first.jpg",
        "https://your-domain/last.jpg"
      ]
    }
  }'

import requests

resp = requests.post(
    "https://www.ruapi.ai/v1/videos",
    headers={"Authorization": "Bearer sk-YOUR_KEY"},
    json={
        "model": "doubao-seedance-2.0-fast",
        "prompt": "Smooth transition from the first frame to the second, natural camera motion, cinematic",
        "seconds": "5",
        "metadata": {
            "resolution": "720p",
            "ratio": "16:9",
            "images": [
                "https://your-domain/first.jpg",
                "https://your-domain/last.jpg",
            ],
        },
    },
)
print(resp.json()["id"])

Mode 4. Reference-video (1 video)

Put 1 short video URL in metadata.videos; the model reinterprets it while keeping the subject’s motion (e.g. restyle or change the scene).

curl https://www.ruapi.ai/v1/videos \
  -H "Authorization: Bearer sk-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-2.0-fast",
    "prompt": "Keep the person's motion from the video, restyle to a neon cyberpunk street",
    "seconds": "5",
    "metadata": {
      "resolution": "480p",
      "ratio": "9:16",
      "videos": ["https://your-domain/dance.mp4"]
    }
  }'

import requests

resp = requests.post(
    "https://www.ruapi.ai/v1/videos",
    headers={"Authorization": "Bearer sk-YOUR_KEY"},
    json={
        "model": "doubao-seedance-2.0-fast",
        "prompt": "Keep the person's motion from the video, restyle to a neon cyberpunk street",
        "seconds": "5",
        "metadata": {
            "resolution": "480p",
            "ratio": "9:16",
            "videos": ["https://your-domain/dance.mp4"],
        },
    },
)
print(resp.json()["id"])

Reference-video is picky about input: use a short clip that is ≤ 15 seconds with a clear subject (e.g. a person). Cartoons, clips without an obvious subject, or overly long videos often fail. It’s best if the reference’s aspect ratio matches your target ratio (e.g. a vertical source → 9:16).

Advanced: multiple images / videos

images and videos are arrays — you can pass several references at once (both verified):

Multiple images: put 3 or more images in images (officially up to 9). The model combines subject / scene / style across them. With 3+ images, input_type is auto-detected as reference.
Multiple videos: put 2 or more clips in videos (officially up to 3, total duration ≤ 15 seconds).

curl https://www.ruapi.ai/v1/videos \
  -H "Authorization: Bearer sk-YOUR_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "doubao-seedance-2.0-fast",
    "prompt": "Combine the subject and style from these images into one coherent video, natural camera motion",
    "seconds": "5",
    "metadata": {
      "resolution": "720p",
      "ratio": "16:9",
      "images": [
        "https://your-domain/ref1.jpg",
        "https://your-domain/ref2.jpg",
        "https://your-domain/ref3.jpg"
      ]
    }
  }'

import requests

resp = requests.post(
    "https://www.ruapi.ai/v1/videos",
    headers={"Authorization": "Bearer sk-YOUR_KEY"},
    json={
        "model": "doubao-seedance-2.0-fast",
        "prompt": "Combine the subject and style from these images into one coherent video, natural camera motion",
        "seconds": "5",
        "metadata": {
            "resolution": "720p",
            "ratio": "16:9",
            "images": [
                "https://your-domain/ref1.jpg",
                "https://your-domain/ref2.jpg",
                "https://your-domain/ref3.jpg",
            ],
        },
    },
)
print(resp.json()["id"])

Same for videos: replace images with videos and pass several short clips (each ideally ≤ 7 seconds with a clear subject, ≤ 15 seconds total).

Task statuses

`status`	Meaning
`queued`	Queued
`in_progress`	Generating
`completed`	Done, `metadata.url` is the download link
`failed`	Failed, reason in the `error` field

Billing

Video is billed per token (resolution × duration). A pre-charge is held on submit, then recalculated by actual usage on completion — the difference is refunded. The final charge is what actually got deducted. See the pricing page.

FAQ

Model not available (503) or 404 error

Check two things: is the model name correct (e.g. doubao-seedance-2.0-fast) — otherwise you get a 503 with the code model_not_found; and is the address https://www.ruapi.ai/v1/videos (with /v1) — otherwise a 404.

Stuck on queued / in_progress

That’s normal. Generation usually takes 1–3 minutes; keep polling and don’t set the interval too short.

Downloaded file is empty / won't open

It’s likely been more than 7 days and the download link has expired. Download right after generation.

Reference-video task failed

This mode is picky about input. Make sure the reference video is ≤ 15 seconds, has a clear subject, and is a publicly reachable MP4. Cartoons or clips without an obvious subject often fail.

Which address do I poll?

Use the plural GET /v1/videos/{id}. It’s the OpenAI-compatible format, and metadata.url in the response is directly the download link.

Pricing & billing rules
Questions? support@ruapi.ai

Getting Started

Guides

API Reference

Model guides

Integrations

Capabilities

Recipes

Legal

Video generation: Seedance 2.0

Available models

URLs & auth

Step 1. Submit a task (text-to-video)

Step 2. Poll the status

Step 3. Download the video

Full example: the whole flow in one script

The same with curl

Parameters

The four input modes

Mode 1. Text-to-video

Mode 2. Image-to-video (1 image)

Mode 3. First-last frame (2 images)

Mode 4. Reference-video (1 video)

Advanced: multiple images / videos

Task statuses

Billing

FAQ

Next

​Available models

​URLs & auth

​Step 1. Submit a task (text-to-video)

​Step 2. Poll the status

​Step 3. Download the video

​Full example: the whole flow in one script

​The same with curl

​Parameters

​The four input modes

​Mode 1. Text-to-video

​Mode 2. Image-to-video (1 image)

​Mode 3. First-last frame (2 images)

​Mode 4. Reference-video (1 video)

​Advanced: multiple images / videos

​Task statuses

​Billing

​FAQ

​Next

Available models

URLs & auth

Step 1. Submit a task (text-to-video)

Step 2. Poll the status

Step 3. Download the video

Full example: the whole flow in one script

The same with curl

Parameters

The four input modes

Mode 1. Text-to-video

Mode 2. Image-to-video (1 image)

Mode 3. First-last frame (2 images)

Mode 4. Reference-video (1 video)

Advanced: multiple images / videos

Task statuses

Billing

FAQ

Next