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    "sections": [
      {
        "title": "Validation",
        "body": "mkdir -p output/alicloud-ai-video-wan-r2v\npython -m py_compile skills/ai/video/alicloud-ai-video-wan-r2v/scripts/prepare_r2v_request.py && echo \"py_compile_ok\" > output/alicloud-ai-video-wan-r2v/validate.txt\n\nPass criteria: command exits 0 and output/alicloud-ai-video-wan-r2v/validate.txt is generated."
      },
      {
        "title": "Output And Evidence",
        "body": "Save reference input metadata, request payloads, and task outputs in output/alicloud-ai-video-wan-r2v/.\nKeep at least one polling result snapshot.\n\nUse Wan R2V for reference-to-video generation. This is different from i2v (single image to video)."
      },
      {
        "title": "Critical model names",
        "body": "Use one of these exact model strings:\n\nwan2.6-r2v-flash\nwan2.6-r2v"
      },
      {
        "title": "Prerequisites",
        "body": "Install SDK in a virtual environment:\n\npython3 -m venv .venv\n. .venv/bin/activate\npython -m pip install dashscope\n\nSet DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials."
      },
      {
        "title": "Request",
        "body": "prompt (string, required)\nreference_video (string | bytes, required)\nreference_image (string | bytes, optional)\nduration (number, optional)\nfps (number, optional)\nsize (string, optional)\nseed (int, optional)"
      },
      {
        "title": "Response",
        "body": "video_url (string)\ntask_id (string, when async)\nrequest_id (string)"
      },
      {
        "title": "Async handling",
        "body": "Prefer async submission for production traffic.\nPoll task result with 15-20s intervals.\nStop polling when SUCCEEDED or terminal failure status is returned."
      },
      {
        "title": "Local helper script",
        "body": "Prepare a normalized request JSON and validate response schema:\n\n.venv/bin/python skills/ai/video/alicloud-ai-video-wan-r2v/scripts/prepare_r2v_request.py \\\n  --prompt \"Generate a short montage with consistent character style\" \\\n  --reference-video \"https://example.com/reference.mp4\""
      },
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        "title": "Output location",
        "body": "Default output: output/alicloud-ai-video-wan-r2v/videos/\nOverride base dir with OUTPUT_DIR."
      },
      {
        "title": "Workflow",
        "body": "Confirm user intent, region, identifiers, and whether the operation is read-only or mutating.\nRun one minimal read-only query first to verify connectivity and permissions.\nExecute the target operation with explicit parameters and bounded scope.\nVerify results and save output/evidence files."
      },
      {
        "title": "References",
        "body": "references/sources.md"
      }
    ],
    "body": "Category: provider\n\nModel Studio Wan R2V\nValidation\nmkdir -p output/alicloud-ai-video-wan-r2v\npython -m py_compile skills/ai/video/alicloud-ai-video-wan-r2v/scripts/prepare_r2v_request.py && echo \"py_compile_ok\" > output/alicloud-ai-video-wan-r2v/validate.txt\n\n\nPass criteria: command exits 0 and output/alicloud-ai-video-wan-r2v/validate.txt is generated.\n\nOutput And Evidence\nSave reference input metadata, request payloads, and task outputs in output/alicloud-ai-video-wan-r2v/.\nKeep at least one polling result snapshot.\n\nUse Wan R2V for reference-to-video generation. This is different from i2v (single image to video).\n\nCritical model names\n\nUse one of these exact model strings:\n\nwan2.6-r2v-flash\nwan2.6-r2v\nPrerequisites\nInstall SDK in a virtual environment:\npython3 -m venv .venv\n. .venv/bin/activate\npython -m pip install dashscope\n\nSet DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.\nNormalized interface (video.generate_reference)\nRequest\nprompt (string, required)\nreference_video (string | bytes, required)\nreference_image (string | bytes, optional)\nduration (number, optional)\nfps (number, optional)\nsize (string, optional)\nseed (int, optional)\nResponse\nvideo_url (string)\ntask_id (string, when async)\nrequest_id (string)\nAsync handling\nPrefer async submission for production traffic.\nPoll task result with 15-20s intervals.\nStop polling when SUCCEEDED or terminal failure status is returned.\nLocal helper script\n\nPrepare a normalized request JSON and validate response schema:\n\n.venv/bin/python skills/ai/video/alicloud-ai-video-wan-r2v/scripts/prepare_r2v_request.py \\\n  --prompt \"Generate a short montage with consistent character style\" \\\n  --reference-video \"https://example.com/reference.mp4\"\n\nOutput location\nDefault output: output/alicloud-ai-video-wan-r2v/videos/\nOverride base dir with OUTPUT_DIR.\nWorkflow\nConfirm user intent, region, identifiers, and whether the operation is read-only or mutating.\nRun one minimal read-only query first to verify connectivity and permissions.\nExecute the target operation with explicit parameters and bounded scope.\nVerify results and save output/evidence files.\nReferences\nreferences/sources.md"
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    "owner": "cinience",
    "version": "1.0.1",
    "license": null,
    "verificationStatus": "Indexed source record"
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