text_to_video.py

"""
Seedance 2.0 Text-to-Video – Basic Example
==========================================
Generate video from a text prompt using the Seedance 2.0 API on Atlas Cloud.

Get your API key: https://www.atlascloud.ai/seedance-2?utm_source=github&utm_campaign=free-seedance-2-api
API docs:         https://www.atlascloud.ai/models/bytedance/seedance-2.0/text-to-video?tab=api&utm_source=github&utm_campaign=free-seedance-2-api
"""

import os
import time
import requests

API_KEY = os.environ.get("ATLASCLOUD_API_KEY", "your_api_key_here")
BASE_URL = "https://api.atlascloud.ai"


def generate_video(
    prompt: str,
    model: str = "bytedance/seedance-2.0/text-to-video",
    width: int = 1280,
    height: int = 720,
    duration: int = 5,
    fps: int = 24,
    negative_prompt: str = "",
    seed: int | None = None,
) -> str:
    """
    Generate a video from a text prompt.

    Args:
        prompt: Description of the video to generate
        model: Model ID. Use 'text-to-video-fast' for cheaper, faster generation
        width: Output width in pixels
        height: Output height in pixels
        duration: Video duration in seconds (5–15)
        fps: Frames per second (24 or 30)
        negative_prompt: Things to avoid in the output
        seed: Random seed for reproducibility

    Returns:
        URL to the generated MP4 video file
    """
    headers = {
        "Content-Type": "application/json",
        "Authorization": f"Bearer {API_KEY}",
    }

    input_params = {
        "prompt": prompt,
        "width": width,
        "height": height,
        "duration": duration,
        "fps": fps,
    }
    if negative_prompt:
        input_params["negative_prompt"] = negative_prompt
    if seed is not None:
        input_params["seed"] = seed

    # Submit generation request
    response = requests.post(
        f"{BASE_URL}/api/v1/model/generateVideo",
        headers=headers,
        json={"model": model, "input": input_params},
        timeout=30,
    )
    response.raise_for_status()
    prediction_id = response.json()["data"]["id"]
    print(f"Generation started | ID: {prediction_id}")

    # Poll for completion
    poll_headers = {"Authorization": f"Bearer {API_KEY}"}
    poll_url = f"{BASE_URL}/api/v1/model/prediction/{prediction_id}"
    interval = 2

    while True:
        result = requests.get(poll_url, headers=poll_headers, timeout=15).json()["data"]
        status = result["status"]
        print(f"Status: {status}")

        if status in ("completed", "succeeded"):
            video_url = result["outputs"][0]
            predict_time = result.get("metrics", {}).get("predict_time", "?")
            print(f"Done in {predict_time}s → {video_url}")
            return video_url

        if status == "failed":
            raise RuntimeError(f"Generation failed: {result.get('error', 'unknown error')}")

        time.sleep(interval)
        interval = min(interval * 1.5, 10)  # Exponential backoff, max 10s


def download_video(url: str, output_path: str = "output.mp4") -> str:
    """Download a generated video to local disk."""
    response = requests.get(url, timeout=60, stream=True)
    response.raise_for_status()
    with open(output_path, "wb") as f:
        for chunk in response.iter_content(chunk_size=8192):
            f.write(chunk)
    print(f"Saved → {output_path}")
    return output_path


if __name__ == "__main__":
    # Example 1: Cinematic landscape
    video_url = generate_video(
        prompt=(
            "A cinematic drone shot gliding over snow-capped mountain peaks at golden hour, "
            "volumetric fog in the valleys, ultra HD, photorealistic"
        ),
        width=1920,
        height=1080,
        duration=10,
    )
    download_video(video_url, "mountain_landscape.mp4")

    # Example 2: Vertical format for social media
    video_url = generate_video(
        prompt=(
            "A barista expertly pouring latte art in slow motion, "
            "warm café lighting, bokeh background, commercial style"
        ),
        width=1080,
        height=1920,  # 9:16 vertical
        duration=5,
        model="bytedance/seedance-2.0/text-to-video-fast",  # Faster + cheaper
    )
    download_video(video_url, "latte_art.mp4")