hackerFish / dsh-video-studio

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鲸影 DSH Video Studio:DeepSeek Harness 原生视频/漫剧生成插件——六段导演流水线、多供应商免费额度调度、四层提示词自优化,质量优先省钱第二

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安装

npx -y @deepseek-ai/dsh plugin --profile web add github:hackerFish/dsh-video-studio

此安装命令根据 GitHub 仓库地址生成,是未经验证的安装起点。

README

维护者编写的文档快照。

在 GitHub 查看 ↗
提交版本 dd66957同步于 2026年8月17日

🐳 dsh-video-studio (Whale) — AI Video & Motion-Comic Studio for DeepSeek Harness

A DeepSeek Harness native plugin for AI video and motion-comic (漫剧) production: seven-stage director pipeline × multi-account quota pool with failure fallback × credential vault × four-layer prompt engineering with a score-feedback loop. Quality first, cost second.

中文 · Siblings: dsh-lab · awesome-dsh-skills · awesome-dsh-presets

The DSH ecosystem has 1000+ plugins — none does generative video. Whale brings the industry-validated motion-comic pipeline (waoowaoo / LumenX / MangaV / ArcReel pattern) into DSH as a hot-pluggable, per-step-controllable plugin.

Pipeline — the industry-standard seven-stage workflow

story (LLM, e.g. Doubao writes the novel) → script (LLM breaks it down)
→ storyboard (LLM shot list) → master asset (MJ-style hero image)
→ shot assets (image-model variations for consistency) → video (Seedance/Jimeng/Kling)
→ final cut (JianYing draft export / local ffmpeg render)
  • The first three stages are LLM stages: inside DSH the session model itself does them — the model you're chatting with (Doubao, DeepSeek, whatever) is the brain that writes the story, script and shots; the plugin never calls an external LLM.

Mapping to the industry-standard toolchain:

Industry flowWhale
Doubao writes novel / script / shots= DSH session model doing story/script/storyboard (pick a Doubao model and it IS "Doubao writes")
MJ hero asset= master-asset stage (MJ official API adapter to come; wanx/Seedream can substitute)
image variations= shot-assets stage (wanx ✅ verified · Doubao Seedream ✅ wired)
Seedance video= video stage (Doubao Seedance ✅ / jimeng / kling / ComfyUI)
JianYing final cut= final-cut stage (JianYing draft export ✅ / ffmpeg ✅)
  • Every stage has a gate: auto / ask / manual.

  • Parallel shots, quota scheduler, style genome, distribution pack as before.

  • Consistency asset library: character/scene master assets + per-shot variations with automatic reference-image injection into prompts (the motion-comic standard technique)

  • Parallel shots: batch submit → concurrent polling (configurable concurrency)

  • Account pool (quota scheduler): multi-account rotation per provider, per-day caps, exponential backoff on failure, automatic fallback re-submit to the next healthy account mid-pipeline, full audit trail

  • Credential vault: ~/.whale/whale.json (0600, atomic writes, follows $DSH_HOME), masked API responses, account management UI in the plugin settings (鲸影账号 tab)

  • Runtime account wiring: accounts added in the UI feed straight into whale_generate_video — vault → pool pick (rotation/backoff) → per-account provider binding (src/host/account-providers.ts, single-field credentials as plain strings, multi-field as JSON) → usage/health persisted back to the vault

  • Style genome (memory): style DNA, shot-template scoring evolution, retry feedback — persists across sessions

  • Prompt engineering: parameterized professional template library (character sheet / scene master / single shot) + composable quality boosters (8K / clean bg / neutral face / no text …) + optimizer; whale_optimize_prompt upgrades drafts to pro-grade prompts locally

  • Score-feedback loop (评分回写): every reviewed shot writes its score + booster combo back to the scorebook; the optimizer then picks boosters by real historical performance

  • Preset motion-comic pack: 5 genres (city comeback / xianxia / suspense / sweet romance / sci-fi) with bilingual character cards, scene cards and shot scripts — whale_story_presets turns one preset id into a pipeline-ready script, scripts/demo-presets.ts runs it end-to-end with the mock provider (zero keys)

  • Self-analysis (自我审计): whale_self_audit tool + npm run self-audit scan the repo itself — source modules, test counts, provider matrix, capability inventory and a gap list — and write a generated report to docs/AUDIT-REPORT.md; the daily diff of that file IS the progress log. Session lessons are distilled into docs/RETROSPECTIVE-2026-08-17.md

Providers (verified matrix)

ProviderChannelStatus
jimeng (即梦)sessionid, free daily quota✅ protocol verified end-to-end; text-to-video queue stays SystemBusy even off-peak (0 credits consumed) — free route is now: wanx images → image-to-video
tongyi-wanx (通义万相)cookie+xsrf, free creditslive-verified: real whale image generated & downloaded (free tier = text-to-image; video needs membership)
kling official (可灵)accessKey:secretKey JWT, api-beijing.klingai.com✅ adapter written — not yet tested against a real key
kling via DashScopesk- key✅ adapter written — not yet tested against a real key
kling-lipsync (可灵对口型)official JWT, /v1/videos/lip-sync✅ adapter written against the official 3-13 contract (audio2video + text2video voice modes), 8 tests — not yet tested against a real key
wan video via DashScope (通义万相视频)sk- key, official free quota✅ adapter written (same async protocol as kling) — model id to confirm on first real key
doubao (火山方舟)ARK API key✅ Seedance video + Seedream image (assets) — not yet tested against a real key
doubao-web (豆包网页版)cookie, free web quotalive-replayed & parsed: SSE chat for the LLM stages (story/script/shots) + image bot for assets. Pro-tier free quota runs on a 7-day window (image bot pauses when spent; text keeps working)
ComfyUI localworkflow JSON builder + /prompt protocol✅ protocol-tested (mock server), real GPU pending
kling web (sessionid)anti-bot one-time falcon token📄 anatomy documented; automation needs a capture bridge (deferred)

Editing & distribution

  • Final cut with optional lip-sync stage: with a capabilities.lipSync provider configured, every voiced shot runs audio-driven lip sync (video reference + audio base64) and the synced clip replaces the original on the timeline; failure falls back to the original clip, never blocking the render. Shots can also carry a pre-recorded voiceFile (external TTS/voice actor) that skips local TTS
  • ffmpeg auto-render — verified end-to-end (synthetic clips → timeline → burned subtitles → audio mix → final mp4, duration-checked)
  • JianYing (剪映) draft export — editable tracks/keyframes/subtitles for manual polish; structure-validated
  • say TTS — real Chinese voiceover with zero API keys: macOS say; Windows PowerShell SAPI (System.Speech, needs a Chinese voice pack). Any platform can also plug external audio per shot via voiceFile
  • Distribution pack — platform specs + compliance precheck for 4 Chinese platforms

DSH integration (deep invocation)

  • Model tools: whale_story_presets (5-genre content pack → pipeline script), whale_storyboard (offline shot planning), whale_generate_video (provider routing), whale_optimize_prompt (pro-grade prompt upgrade), whale_quality_review (rule-level QC), whale_comfyui_workflow (ComfyUI workflow JSON), whale_self_audit (project self-analysis)
  • Host routes: /dsh-video-studio/health, /dsh-video-studio/runs, /dsh-video-studio/accounts (GET list masked / POST add / DELETE remove)
  • Client UI: 鲸影 (status) · 鲸影工作台 (live pipeline progress per run) · 鲸影账号 (account vault management) tabs in plugin settings; whale_generate_video gets a dedicated video card view
  • Installs via dsh plugin add, boot-verified clean
  • Planned: slash commands, subagent-parallel shots

Verification discipline

123 unit tests green (account pool rotation/backoff/fallback, credential vault, runtime account→provider wiring, quota routing, prompt merging, score-feedback loop, lip-sync stage incl. fallback, Windows SAPI script + CJK font candidates, jianying draft structure, ffmpeg end-to-end render, provider protocols via mock servers incl. kling lip-sync, preset pack integrity, self-audit, live jimeng model probe, live wanx image generation). Test logs and proof artifacts live in demos/. The provider matrix lives in src/selfaudit/matrix.ts (single source of truth shared by the health route, the vault whitelist and the audit report).

Install

dsh plugin --profile web add github:hackerFish/dsh-video-studio --ignore-workspace-root-check
# or npm once published

Honesty notes

Model output quality is bounded by the vendor model; the pipeline maximizes it (consistency tokens, QC retry loop, score-feedback booster selection). sessionid/cookie usage is per-platform ToS — respect each platform's terms. Credentials live only in the local vault file and are never logged or returned unmasked. Not affiliated with DeepSeek.

License

MIT

项目文件与信号

以下项目是目录快照中检测到的公开仓库信号。

测试已检测
文档已检测
示例已检测

仓库信息

开发语言
TypeScript
许可证
MIT
最后更新
2026年8月17日 05:09

谨慎安装

请检查源代码、权限、生命周期脚本、依赖与网络访问;不受信任的插件应先在隔离环境中测试。