星 火 绘 卷
将经典文学长文本，经由六阶段多 Agent 工作流，
自动生成角色一致、印刷级品质的连环画页面。
Transform classic literature into illustrated comics through a
six-stage multi-agent AI pipeline — character-consistent, print-quality.
SparkScroll（星火绘卷）是面向经典文学内容生成的多模态创作平台。 围绕"长文本理解 → 剧情拆解 → 分镜生成 → 页面渲染 → 前端展示"构建完整闭环， 让《西游记》等经典名著化身精美的数字连环画。
SparkScroll is a multimodal creation platform for classic literary content. It closes the loop from "long-text understanding → plot decomposition → storyboarding → page rendering → frontend display," transforming masterpieces like Journey to the West into beautiful digital comics.
项目名称中，Spark 致敬 NVIDIA DGX Spark 平台， Scroll 代表连环画与画卷； 中文"星火绘卷"兼具科技感与古典文学韵味。
In the name: Spark pays tribute to the NVIDIA DGX Spark platform, and Scroll represents comics and picture scrolls. The Chinese name "星火绘卷" carries both a sense of technology and classical literary charm.
Director → Writer → CharacterDesigner → Drafting → Editor → Assembler， 完整还原人类漫画制作流程，从百万字长文到精美页面一气呵成。
Fully reproduces the human comic production workflow — from million-word novels to polished pages in one continuous pipeline.
立绘 Agent 预生成角色正/侧/背三视图与道具参考图，后续所有分镜以参考图为基准注入扩散模型条件通道，风格统一、叙事连贯。
CharacterDesigner pre-generates front/side/back reference sheets; all subsequent panels use these as conditioning inputs to the diffusion model, ensuring visual consistency throughout.
文本主脑（~40 GB）与视觉中枢（50–60 GB）同时常驻 DGX Spark 128 GB 统一内存，零 Swap、极致秒级响应，多 Agent 极速切换。
Text brain (~40 GB) and visual core (50–60 GB) co-reside in DGX Spark's 128 GB unified memory — zero swap, second-level response, rapid multi-agent switching.
Editor Agent 使用 Python PIL 在像素层面排版文字，彻底消除 AI 生字乱码，保证中文字体清晰、布局精准、达到出版级品质。
The Editor agent uses Python PIL to typeset text at the pixel level — no AI-generated garbled characters, ensuring crisp Chinese fonts and publication-grade layout quality.
基于 128K 上下文对长文本进行"降维压缩"，提取核心剧情节点与角色关系，输出结构化剧本大纲。
Leverages 128K context to compress long texts, extracting core plot nodes and character relationships into a structured story outline.
将大纲拆解为分集、分镜，每页 4–6 个场景，输出标准化 JSON 剧本，指定每格台词与画面描述。
Breaks the outline into episodes and panels (4–6 scenes per page), outputting a standardized JSON script with dialogue and visual descriptions for each cell.
预生成每个角色的正面、侧面、背面三视图和关键道具参考图，为后续分镜锁定视觉一致性基准。
Pre-generates front/side/back three-view character sheets and key prop reference images, establishing the visual consistency baseline for all subsequent panels.
基于分镜 JSON 和角色参考图，调用 Diffusers + vLLM-Omni 双驱动生成各格底图，保证角色风格与参考图对齐。
Using the storyboard JSON and character references, calls the Diffusers + vLLM-Omni dual engine to generate panel base images, keeping character style aligned to references.
纯 PIL 像素级排版：将台词嵌入对话框，精准控制字体大小、行距与位置，拒绝 AI 乱码，输出印刷级清晰图像。
Pure PIL pixel-level typesetting: embeds dialogue into speech bubbles with precise font control, eliminating AI-generated garbled text and producing print-quality images.
聚合各页产物，流式按页推送给前端，每生成一页即时呈现，用户无需等待全集完成即可阅览。
Aggregates per-page outputs and streams them to the frontend in real time — users can start reading as soon as the first page is ready, without waiting for the full episode.
SparkScroll 采用"重型双大模型常驻显存"架构，普通单卡系统完全无法运行该并发管线。
SparkScroll's "Memory-Resident Multi-Model" architecture simply cannot run on ordinary single-GPU systems.
| 模块 | Module | 选型 | Selection | 显存预算 | Memory Budget | DGX Spark 必要性 | Why DGX Spark |
|---|---|---|---|---|---|---|---|
| 文本与逻辑主脑 | Text & Logic Brain | Qwen3.5-9B 128K ctx · vLLM v0.19.0 |
~40 GB | ~40 GB | 128K 上下文足以覆盖绝大多数小说全文，稳定支撑剧情压缩与跨集规划。 | 128K context covers most full-length novels, enabling stable plot compression and cross-episode planning. | |
| 视觉渲染中枢 | Visual Rendering Core | Qwen-Image-Edit-2511 FireRed-Image-Edit-1.1 |
50–60 GB | 50–60 GB | 兼顾高保真角色一致性编辑与中文字幕渲染，强行量化会导致排版几何推理能力丧失。 | Balances high-fidelity character editing and Chinese subtitle rendering; forced quantization destroys layout geometry reasoning. | |
| 框架与并发缓冲 | Framework & Concurrency | vLLM · FastAPI · Diffusers · OS | ~15 GB | ~15 GB | 支撑 API 流转、自研调度与多 Agent 极速切换，需安全冗余。 | Supports API routing, custom scheduling, and rapid multi-agent switching, requiring safe redundancy. | |
| 总计 | Total | — | 110–115 GB / 128 G | 110–115 GB / 128 G | 只有 DGX Spark 能实现"零 Swap"的极致秒级响应，支撑多 Agent 极速切换与流式呈现。 | Only DGX Spark achieves zero-swap, second-level responses enabling rapid multi-agent switching and streaming delivery. |
基于本地生成结果整理，每个项目可按集数与页码连续预览
Organized from local generation outputs, with project-level episode and page previews
将《西游记》等古典名著转化为连环画，提升学生知识留存率与阅读兴趣。
Transform classics like Journey to the West into comics, boosting student retention and reading engagement.
网络小说每日更新章节自动生成 5–10 页连环画，在短视频平台快速引流。
Auto-generate 5–10 comic pages per chapter update, driving traffic on short-video platforms.
将晦涩的历史文献转化为连环长卷，让博物馆展览更加生动易读。
Convert obscure historical texts into scrolling comic murals, bringing museum exhibitions to life.
品牌故事快速转化为多风格连环画，支持多语言适配，降低内容本土化成本。
Rapidly convert brand stories into multi-style comics with multilingual adaptation, reducing localization costs.
重建年印量曾达 81 亿册的连环画产业，让"小人书"以数字化形态涅槃重生。
Revive the comic-book industry that once printed 8.1 billion copies annually — reborn in digital form.
团队起名"纵贯线"，源自成员来自北京、南京、广州三地，如一条纵贯全国的线。 三地协作、远程共享 DGX Spark 设备，以 OpenClaw 多 Agent 辅助开发。
"Zongguanxian" means the line running through the country — a nod to the team spanning Beijing, Nanjing, and Guangzhou. Remote collaboration, shared DGX Spark access, and AI-assisted development via OpenClaw.
队长 · 项目策划
Team Lead · Project Planning
项目策划与管理、本地模型部署、前端 UI 开发与调试
Project planning & management, local model deployment, frontend UI development
队员 · 测试与文档
Testing & Documentation
前端 UI 开发、系统测试、技术文档、参赛材料编写
Frontend UI, system testing, technical documentation, competition materials
队员 · 架构设计
Architecture Lead
系统整体架构、技术路线制定
System architecture, technical roadmap
AI 助手 · Gateway 开发
AI Assistant · Gateway Dev
设计和实现后端 API 服务
Designed and implemented backend API services
AI 助手 · 前端 UI 开发
AI Assistant · Frontend Dev
设计用户友好的前端界面，提供直观的操作入口
Designed user-friendly frontend interfaces with intuitive model operation flows
