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Aliyun Wan R2v

by @cinience

Use when generating reference-based videos with Alibaba Cloud Model Studio Wan R2V models (wan2.6-r2v-flash, wan2.6-r2v). Use when creating multi-shot videos...

Versionv1.0.0
Downloads397
TERMINAL
clawhub install aliyun-wan-r2v

πŸ“– About This Skill


name: aliyun-wan-r2v description: Use when generating reference-based videos with Alibaba Cloud Model Studio Wan R2V models (wan2.6-r2v-flash, wan2.6-r2v). Use when creating multi-shot videos from reference video/image material, preserving character style, or documenting reference-to-video request/response flows. version: 1.0.0

Category: provider

Model Studio Wan R2V

Validation

mkdir -p output/aliyun-wan-r2v
python -m py_compile skills/ai/video/aliyun-wan-r2v/scripts/prepare_r2v_request.py && echo "py_compile_ok" > output/aliyun-wan-r2v/validate.txt

Pass criteria: command exits 0 and output/aliyun-wan-r2v/validate.txt is generated.

Output And Evidence

  • Save reference input metadata, request payloads, and task outputs in output/aliyun-wan-r2v/.
  • Keep at least one polling result snapshot.
  • Use Wan R2V for reference-to-video generation. This is different from i2v (single image to video).

    Critical model names

    Use one of these exact model strings:

  • wan2.6-r2v-flash
  • wan2.6-r2v
  • Newer official releases may prefer the flash variant for lower latency and lower cost.

    Prerequisites

  • Install SDK in a virtual environment:
  • 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_reference)

    Request

  • prompt (string, required)
  • reference_video (string | bytes, required)
  • reference_image (string | bytes, optional)
  • duration (number, optional)
  • fps (number, optional)
  • size (string, optional)
  • seed (int, optional)
  • Response

  • video_url (string)
  • task_id (string, when async)
  • request_id (string)
  • Async handling

  • Prefer async submission for production traffic.
  • Poll task result with 15-20s intervals.
  • Stop polling when SUCCEEDED or terminal failure status is returned.
  • Local helper script

    Prepare a normalized request JSON and validate response schema:

    .venv/bin/python skills/ai/video/aliyun-wan-r2v/scripts/prepare_r2v_request.py \
      --prompt "Generate a short montage with consistent character style" \
      --reference-video "https://example.com/reference.mp4"
    

    Output location

  • Default output: output/aliyun-wan-r2v/videos/
  • Override base dir with OUTPUT_DIR.
  • Workflow

    1) Confirm user intent, region, identifiers, and whether the operation is read-only or mutating. 2) Run one minimal read-only query first to verify connectivity and permissions. 3) Execute the target operation with explicit parameters and bounded scope. 4) Verify results and save output/evidence files.

    References

  • references/sources.md
  • βš™οΈ Configuration

  • Install SDK in a virtual environment:
  • 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.
  • πŸ”’ Constraints

    mkdir -p output/aliyun-wan-r2v
    python -m py_compile skills/ai/video/aliyun-wan-r2v/scripts/prepare_r2v_request.py && echo "py_compile_ok" > output/aliyun-wan-r2v/validate.txt
    

    Pass criteria: command exits 0 and output/aliyun-wan-r2v/validate.txt is generated.