wan-2-7

作者: agentspace-so

我们要求翻译一段文本,目标语言是简体中文。需要保留产品名、协议名、URL、数字、技术术语。不要添加声明、解释、Markdown、项目符号、链接、标签、前缀或额外评论。只翻译<text>内的内容,不包括名称除非在源文本中出现。不要添加"description"等标签。 源文本是英文,描述了一个agent skill,关于使用Wan 2.7生成文本到视频。需要翻译成中文,保留"Wan 2.7"、"RunComfy"、"HappyHorse 1.0"、"Seedance 2.0"、"Kling"、"LTX 2"、"audio_url"、"runcomfy run wan-ai/wan-2-7/text-to-video"等专有名词和技术术语。注意"wan-2-7"是名称,但源文本中出现了,所以保留。 翻译要准确,保持原意。注意"multi-reference conditioning"翻译为"多参考条件","audio-driven lip-sync"翻译

npx skills add https://github.com/agentspace-so/runcomfy-agent-skills --skill wan-2-7

Wan 2.7 — Pro Pack on RunComfy

runcomfy.com · Text-to-video · GitHub

Wan-AI's Wan 2.7 — flagship video model with multi-reference conditioning and audio-driven lip-sync — hosted on the RunComfy Model API.

npx skills add agentspace-so/runcomfy-skills --skill wan-2-7 -g

When to pick this model (vs siblings)

You wantUse
Lip-sync video to an audio track you supplyWan 2.7 (audio_url)
Multi-reference fine motion controlWan 2.7
Smooth transitions, accurate motion physicsWan 2.7
Currently-#1 blind-vote video modelHappyHorse 1.0
Multi-modal cinematic with image+video+audio refs + in-pass voice generationSeedance 2.0 Pro
Cinematic motion editing on existing footageKling Video O1
Ultra-fast iterationLTX 2

If the user said "Wan" / "Wan 2.7" / "wan-ai" / "alibaba video" explicitly, route here regardless.

Prerequisites

  1. RunComfy CLInpm i -g @runcomfy/cli
  2. RunComfy accountruncomfy login opens a browser device-code flow.
  3. CI / containers — set RUNCOMFY_TOKEN=<token> instead of runcomfy login.

Endpoints + input schema

wan-ai/wan-2-7/text-to-video

FieldTypeRequiredDefaultNotes
promptstringyesUp to ~5000 chars / ~1500 tokens.
audio_urlstringnoWAV/MP3, 3–30s, ≤15MB. Drives lip-sync. Omit → background music auto-generated.
aspect_ratioenumno16:916:9, 9:16, 1:1, 4:3, 3:4.
resolutionenumno1080p720p or 1080p.
durationenumno52–15 (whole seconds).
negative_promptstringnoUp to 500 chars. Concrete issues to avoid.
enable_prompt_expansionboolnotrueAuto-rewrites short prompts. Disable for literal control.
seedintno0..2^31-1. Reuse for variants.

How to invoke

Default (5s 1080p 16:9, prompt-expanded):

runcomfy run wan-ai/wan-2-7/text-to-video \
  --input '{"prompt": "<user prompt>"}' \
  --output-dir <absolute/path>

Audio-driven lip-sync (your own track):

runcomfy run wan-ai/wan-2-7/text-to-video \
  --input '{
    "prompt": "Medium close-up of the spokesperson, warm key light, locked tripod, slight breathing motion.",
    "audio_url": "https://.../voiceover.mp3",
    "duration": 12,
    "aspect_ratio": "9:16"
  }' \
  --output-dir <absolute/path>

Literal control (no auto-expansion):

runcomfy run wan-ai/wan-2-7/text-to-video \
  --input '{
    "prompt": "<exactly what you want, verbatim>",
    "enable_prompt_expansion": false,
    "negative_prompt": "no subtitles, no flicker, no distorted hands"
  }' \
  --output-dir <absolute/path>

Prompting — what actually works

Camera + motion in plain English. "Slow dolly in", "locked tripod, low angle", "handheld follow", "crane move from above". Front-load the shot.

One primary action per clip. Don't pile up multiple competing actions. Pick the beat: "she turns, then smiles" not "she turns AND smiles AND a bus passes AND...".

Use negative_prompt for concrete issues. Good: "no subtitles, no watermark, no flicker". Bad (vague): "no bad lighting".

Prompt expansion is on by default. Short prompts get auto-rewritten by the model. For terse / literal prompts (e.g. brand-strict ad copy), disable with enable_prompt_expansion: false.

Audio specs matter. audio_url must be 3–30s, ≤15MB, WAV/MP3. Out-of-range files reject. Match audio length to clip duration.

Iterate seeds. Reuse the same seed when you want consistent output across variants of the same prompt. Change seed for genuine variety.

Anti-patterns:

  • Static-frame descriptions → motion will be vague.
  • Vague negatives ("no bad colors") → ignored.
  • Audio outside the 3–30s / 15MB / WAV-MP3 spec → rejected.
  • Prompts > 5000 chars / 1500 tokens → degraded output.

Where it shines

Use caseWhy Wan 2.7
Lip-synced ads with custom voiceoveraudio_url accepts your track
Multi-language dub variantsSame prompt, different audio_url per language
Multi-reference motion controlUp to 5 reference media (image / video / voice)
Smooth transitions + motion physicsStrong physics-aware motion priors
Negative-prompted clean outputTargeted issue exclusion

Sample prompts (verified to produce strong results)

Page example (product showcase):

Cinematic medium shot of a product on a marble surface, soft studio
lighting, slow subtle camera push-in, shallow depth of field, premium
commercial look, crisp 1080p detail

Lip-synced spokesperson (with audio_url):

Medium close-up of a confident spokesperson in a softly-lit recording
booth, leaning slightly toward the camera, locked tripod, shallow depth
of field, warm key light from camera-left.

Vertical platform-native:

9:16 vertical short. A barista pulls a single espresso shot, steam
rising into morning sun, rich crema slowly forming. Close-up handheld,
shallow DOF, warm cafe ambience.

Limitations

  • Duration cap 15s. For longer narratives, stitch multiple calls.
  • No native 4K — 1080p ceiling.
  • Aspect ratios — only the 5 documented values.
  • Audio specs — 3–30s, ≤15MB, WAV/MP3 only.
  • Reference media cap 5 (image + video + voice combined).
  • For in-pass voice generation (no separate audio track), use Seedance 2.0 Pro — Wan accepts audio rather than generating it.

Exit codes

codemeaning
0success
64bad CLI args
65bad input JSON / schema mismatch
69upstream 5xx
75retryable: timeout / 429
77not signed in or token rejected

Full reference: docs.runcomfy.com/cli/troubleshooting.

How it works

The skill invokes runcomfy run wan-ai/wan-2-7/text-to-video with a JSON body matching the schema. The CLI POSTs to https://model-api.runcomfy.net/v1/models/wan-ai/wan-2-7/text-to-video, polls the request, fetches the result, and downloads any .runcomfy.net/.runcomfy.com URL into --output-dir. Ctrl-C cancels the remote request before exit.

Security & Privacy

  • Token storage: runcomfy login writes the API token to ~/.config/runcomfy/token.json with mode 0600 (owner-only read/write). Set RUNCOMFY_TOKEN env var to bypass the file entirely in CI / containers.
  • Input boundary: the user prompt is passed as a JSON string to the CLI via --input. The CLI does NOT shell-expand the prompt; it transmits the JSON body directly to the Model API over HTTPS. No shell injection surface from prompt content.
  • Third-party content: image / mask / video URLs you pass are fetched by the RunComfy model server, not by the CLI on your machine. Treat external URLs as untrusted; image-based prompt injection is a known risk for any image-edit / video-edit model.
  • Outbound endpoints: only model-api.runcomfy.net (request submission) and *.runcomfy.net / *.runcomfy.com (download whitelist for generated outputs). No telemetry, no callbacks.
  • Generated-file size cap: the CLI aborts any single download > 2 GiB to prevent disk-fill from a malicious or runaway model output.

来自 agentspace-so 的更多技能

ai-avatar-video
agentspace-so
We need to translate the given English text into Simplified Chinese. The instruction says to preserve product names, protocol names, URLs, numbers, and technical terms. The name "ai-avatar-video" is not in the text, so we don't include it. We must not add any labels or extra commentary. Just translate the text inside <text>. The text describes creating AI avatar videos using runcomfy CLI, mentioning various models: ByteDance OmniHuman, Wan-AI Wan 2-7, HappyHorse 1.0, Seedance v2 Pro. Also mentions user intents like UGC voiceover, virtual presenter, etc. We need to translate accurately, keeping technical terms and names as is. For example, "talking-head" might be translated as "说话头像" or keep as "talking-head"? Probably keep as "talking-head" or translate? The instruction says preserve technical terms, but "talking-head" is a common term. I'll translate it as "说话头像" but maybe keep English? Better to translate common terms
videocreativemedia
ai-music
agentspace-so
Generate AI music on RunComfy via the `runcomfy` CLI — a smart router across the music-model catalog. Routes to ElevenLabs AI Music Generation (premium 44.1 kHz stereo vocal tracks, 5 s–5 min, $0.0083/s) and ACE Step / ACE Step 1.5 (StepFun-AI open-weights, tag-driven composition, multilingual lyrics, $0.0002–0.0003/s, ~27× cheaper), plus ACE Step audio-inpaint (regenerate a time range inside an existing track) and ACE Step audio-outpaint (extend a track before or after). Picks the right...
creativeaudioapi
video-edit
agentspace-so
编辑RunComfy上的现有视频——此技能是一个智能路由器,将用户意图匹配到RunComfy目录中的正确编辑模型。选择Wan 2.7 Edit-Video(通用重风格化/背景替换/包装替换,保留身份+动作)、Kling 2.6 Pro Motion Control(将参考视频的精确动作迁移到目标角色)或Lucy Edit Restyle(轻量级身份稳定重风格化/服装替换)。整合每个模型记录的提示模式,使该技能...
videocreativemedia
relight
agentspace-so
Relight a still image — change the lighting setup, color temperature, direction, or mood — on RunComfy via the `runcomfy` CLI. Routes to Qwen Edit 2509's dedicated `relight` LoRA endpoint for purpose-built relighting, with fallback to identity-preserving edit endpoints (Nano Banana 2 Edit, GPT Image 2 Edit, FLUX Kontext Pro) when prose lighting language is enough. Use for product relighting (studio softbox → window light), portrait mood shift (overcast → golden hour), or color-grade change....
creativeimagemedia
kling-3-0
agentspace-so
RunComfy上的Kling 3.0视频生成。Kling 3.0(也称Kling V3.0)是快手科技第三代多镜头视频模型,具备原生同步音频和跨镜头一致的角色身份。该技能涵盖全部六个Kling 3.0端点,覆盖三种渲染等级(标准、专业、4K)和两种模式(文生视频、图生视频)。通过本地RunComfy CLI调用runcomfy run kling/kling-3.0/ /。触发词为"kling"、"kling 3.0"、"kling v3"、"kling pro"等。
creativevideomedia
runcomfy-cli
agentspace-so
Run any model on RunComfy from the command line. The `runcomfy` CLI is one binary, one auth, hundreds of model endpoints — image generation, image edit, video generation, image-to-video, lip-sync, face swap, video edit, inpainting, outpainting, extend, ControlNet, relight, upscale, LoRA training and more. Submit a request, poll for status, download the output. This skill teaches the agent how to install, authenticate, discover model schemas, invoke models, stream / poll / no-wait, script in...
creativemediaapi
happyhorse-1-0
agentspace-so
在RunComfy上使用HappyHorse 1.0生成文本到视频。介绍HappyHorse 1.0的优势(在Artificial Analysis Video Arena排名第一,原生1080p并同步音频,多镜头角色一致性,支持6种语言提示),时长/宽高比/分辨率方案,以及何时转向Wan
creativevideomedia
ai-image-generation
agentspace-so
Generate and edit images on RunComfy via the `runcomfy` CLI — a smart router across the full image-model catalog: FLUX 2 (Klein 9B/4B, Pro, Dev, Flash, Turbo, Max), Google Nano Banana 2 / Pro, OpenAI GPT Image 2, ByteDance Seedream 5 / 4-5 / 4-0 and Dreamina 4-0, Alibaba Qwen Image and Z-Image Turbo, Wan 2-7. Covers both text-to-image (t2i) and image-to-image / edit (i2i) endpoints — the skill picks the right model for the user's actual intent (typography precision, photoreal portraits,...
creativemediaimage