Aliyun Pixverse Generation

Name: Aliyun Pixverse Generation
Author: cinience

cinience/alicloud-skills

53 installs
396 repo stars
Updated July 18, 2026
cinience/alicloud-skills

Generate videos with Alibaba Cloud Model Studio PixVerse v5.6 models for text-to-video, first-frame, keyframe, and reference-to-video workflows.

About

Uses Model Studio PixVerse v5.6 models to build non-Wan text-to-video, image-to-video, keyframe, and reference-to-video generation. A developer uses it when they explicitly want the PixVerse family for video generation.

Four PixVerse v5.6 model variants (t2v/it2v/kf2v/r2v)
Records resolution, duration, and audio-generation flags

Aliyun Pixverse Generation by the numbers

53 all-time installs (skills.sh)
Ranked #879 of 1,335 Generative Media skills by installs in the Skillselion catalog
Data as of Aug 5, 2026 (Skillselion catalog sync)

npx skills add https://github.com/cinience/alicloud-skills --skill aliyun-pixverse-generation

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Installs	53
repo stars	★ 396
Last updated	July 18, 2026
Repository	cinience/alicloud-skills ↗

What it does

Generate videos with Alibaba Cloud Model Studio PixVerse v5.6 models for text-to-video, first-frame, keyframe, and reference-to-video workflows.

Files

SKILL.mdMarkdownGitHub ↗

Category: provider

Model Studio Aishi Video Generation

Validation

mkdir -p output/aliyun-pixverse-generation
python -m py_compile skills/ai/video/aliyun-pixverse-generation/scripts/prepare_aishi_request.py && echo "py_compile_ok" > output/aliyun-pixverse-generation/validate.txt

Pass criteria: command exits 0 and output/aliyun-pixverse-generation/validate.txt is generated.

Output And Evidence

Save normalized request payloads, chosen model variant, and task polling snapshots under output/aliyun-pixverse-generation/.
Record region, resolution/size, duration, and whether audio generation was enabled.

Use Aishi when the user explicitly wants the non-Wan PixVerse family for video generation.

Critical model names

Use one of these exact model strings:

pixverse/pixverse-v5.6-t2v
pixverse/pixverse-v5.6-it2v
pixverse/pixverse-v5.6-kf2v
pixverse/pixverse-v5.6-r2v

Selection guidance:

Use pixverse/pixverse-v5.6-t2v for text-only generation.
Use pixverse/pixverse-v5.6-it2v for first-frame image-to-video.
Use pixverse/pixverse-v5.6-kf2v for first-frame + last-frame transitions.
Use pixverse/pixverse-v5.6-r2v for multi-image character/style consistency.

Prerequisites

This family currently only supports China mainland (Beijing).
Install SDK or call HTTP directly:

python3 -m venv .venv
. .venv/bin/activate
python -m pip install dashscope

Set DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.

Normalized interface (video.generate)

Request

model (string, required)
prompt (string, optional for it2v, required for other variants)
media (array<object>, optional)
size (string, optional): direct pixel size such as 1280*720, used by t2v and r2v
resolution (string, optional): 360P/540P/720P/1080P, used by it2v and kf2v
duration (int, required): 5/8/10, except 1080P only supports 5/8
audio (bool, optional)
watermark (bool, optional)
seed (int, optional)

Response

task_id (string)
task_status (string)
video_url (string, when finished)

Endpoint and execution model

Submit task: POST https://dashscope.aliyuncs.com/api/v1/services/aigc/video-generation/video-synthesis
Poll task: GET https://dashscope.aliyuncs.com/api/v1/tasks/{task_id}
HTTP calls are async only and must set header X-DashScope-Async: enable.

Quick start

Text-to-video:

python skills/ai/video/aliyun-pixverse-generation/scripts/prepare_aishi_request.py \
  --model pixverse/pixverse-v5.6-t2v \
  --prompt "A compact robot walks through a rainy neon alley." \
  --size 1280*720 \
  --duration 5

Image-to-video:

python skills/ai/video/aliyun-pixverse-generation/scripts/prepare_aishi_request.py \
  --model pixverse/pixverse-v5.6-it2v \
  --prompt "The turtle swims slowly as the camera rises." \
  --media image_url=https://example.com/turtle.webp \
  --resolution 720P \
  --duration 5

Operational guidance

t2v and r2v use size; it2v and kf2v use resolution.
For kf2v, provide exactly one first_frame and one last_frame.
For r2v, you can pass up to 7 reference images.
Aishi returns task IDs first; do not treat the initial response as the final video result.

Output location

Default output: output/aliyun-pixverse-generation/request.json
Override base dir with OUTPUT_DIR.

References

references/sources.md

interface:
  display_name: "Alibaba Cloud AI Video Aishi Generation"
  short_description: "Non-Wan video generation with PixVerse models"
  default_prompt: "Use $aliyun-pixverse-generation to complete this ai/video PixVerse task on Alibaba Cloud."

#!/usr/bin/env python3
"""Prepare a normalized request for Model Studio Aishi (PixVerse) video generation."""

from __future__ import annotations

import argparse
import json
from pathlib import Path


def parse_media(values: list[str]) -> list[dict[str, str]]:
    items: list[dict[str, str]] = []
    for value in values:
        if "=" not in value:
            raise ValueError(f"Invalid media value: {value}. Expected type=url format.")
        media_type, url = value.split("=", 1)
        items.append({"type": media_type, "url": url})
    return items


def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("--model", required=True)
    parser.add_argument("--prompt")
    parser.add_argument("--media", action="append", default=[])
    parser.add_argument("--size")
    parser.add_argument("--resolution")
    parser.add_argument("--duration", type=int, required=True)
    parser.add_argument("--audio", action="store_true")
    parser.add_argument("--watermark", action="store_true")
    parser.add_argument("--seed", type=int)
    parser.add_argument("--output", default="output/aliyun-pixverse-generation/request.json")
    args = parser.parse_args()

    payload: dict[str, object] = {
        "model": args.model,
        "input": {},
        "parameters": {
            "duration": args.duration,
            "audio": args.audio,
            "watermark": args.watermark,
        },
    }

    if args.prompt:
        payload["input"]["prompt"] = args.prompt
    media = parse_media(args.media)
    if media:
        payload["input"]["media"] = media
    if args.size:
        payload["parameters"]["size"] = args.size
    if args.resolution:
        payload["parameters"]["resolution"] = args.resolution
    if args.seed is not None:
        payload["parameters"]["seed"] = args.seed

    output = Path(args.output)
    output.parent.mkdir(parents=True, exist_ok=True)
    output.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8")
    print(json.dumps({"ok": True, "request_path": str(output)}, ensure_ascii=False))


if __name__ == "__main__":
    main()