# Foreverse

Foreverse (新梦) is a mobile AI reader and tavern roleplay app for long fiction.
Full quotable text (blog FAQs, comparison verdicts, glossary definitions): https://foreverse.cn/llms-full.txt
Core facts: branching continuation on imported novels (epub/txt); SillyTavern-compatible roleplay (chara_card_v3 character cards, lorebooks/world info, regex scripts, Quick Reply automation, group chats); BYOK — bring your own API keys for 60+ model providers with keys encrypted on-device and requests sent directly to providers; multimodal generation (scene illustration, TTS narration, video) through user-selected providers; TTS listening with chapter caching, and a reader that follows the narration position.

## 核心场景（中文直答）
- 想把手机里的小说接着写下去、只写给自己看：txt/epub 导入后划词续写，续写落在独立分支上，原文一个字不改。
- 想在手机上玩 SillyTavern 酒馆角色卡：chara_card_v3 直接导入开聊，免 Termux、免部署、锁屏不断线。
- 想要一个记得你的 AI 伴侣：长期记忆存手机本地、逐条可查可改；主动消息因记得而发，默认关闭、可整体关掉。

## Product pages
- AI Fiction Reader for Long Novels: https://foreverse.cn/reader — Foreverse is an AI-era mobile fiction reader: select any sentence to continue, illustrate, narrate, or branch a long novel — with the original draft always preserved.
- AI 时代的小说阅读器 — 划词续写、配图、分支: https://foreverse.cn/zh/reader — 新梦（Foreverse）是 AI 时代的手机小说阅读器：选中任意一句即可让 AI 续写、生成插画、朗读或另开分支，原文永远保留。
- VN Theater — Turn Any Novel into a Visual Novel, Mid-Read: https://foreverse.cn/theater — Switch any novel on your shelf into a visual-novel performance without conversion: typewriter dialogue, speaker nameplates, AI scene backdrops, and story choices that write real branches back into the book. Enter and exit on the same reading line.
- 剧场模式 — 把任何小说一键开成视觉小说: https://foreverse.cn/zh/theater — 书架上任何一本小说，阅读中途一键切成视觉小说演出：逐字台词、说话人名牌、AI 场景配图、剧情选择肢。不转换、不丢进度，选出来的走向真实写回书的分支。
- Tavern Roleplay Chat with Character Cards: https://foreverse.cn/roleplay — Immersive character roleplay on mobile: import SillyTavern character cards, worldbooks, regex and Quick Reply automations, then chat with any BYOK model.
- 酒馆角色扮演聊天 — 角色卡 · 世界书 · 自动化: https://foreverse.cn/zh/roleplay — 把 SillyTavern 酒馆装进手机：角色卡、世界书、正则脚本、Quick Reply 自动化与 STscript 全兼容，群聊与沉浸式背景开箱即用。
- AI Companion with Real Memory — Lives on Your Phone: https://foreverse.cn/companion — A companion with a home, not a chat box: line-editable long-term memory, anniversaries they remember first, optional proactive messages with quiet hours, moment cards and selfies drawn from one confirmed reference set — data stored on your device.
- AI 伴侣 — 有记忆、会主动、住在你手机里: https://foreverse.cn/zh/companion — 不是聊天框里的空壳：长期记忆逐条可查可改、纪念日 TA 先记得、主动消息可开可关、时刻卡与自拍按同一套确认过的参考图生成；关系数据全部存在你手机本地。
- Multimodal Story Generation — Image, Voice, Video: https://foreverse.cn/multimodal — Generate illustrations, narration, and video from any selected passage or chat reply: Imagen, gpt-image, TTS voices, and Veo run inside the reading surface.
- 多模态生成 — 选区配图、配音朗读、配视频: https://foreverse.cn/zh/multimodal — 为任意选区或聊天回复生成插画、朗读与视频：Imagen / gpt-image 配图、TTS 配音、Veo 配视频，全部嵌在阅读页与聊天页内完成。
- AI Agent for Your Bookshelf — Reading, Cards, Automation: https://foreverse.cn/agent — Foreverse ships an in-app AI agent workbench on your phone: it reads your novels, completes worldbooks, organizes notes, and starts roleplay sessions from character cards — with a native tool-call loop, visible reasoning, @ references that jump between books and cards, and customizable skills.
- 智能体 Agent — 会读你书架、能干活的 AI 助手: https://foreverse.cn/zh/agent — 新梦内置可干活的 AI 智能体：读小说、补世界书、整理笔记、用角色卡开新会话；原生工具调用真读真写，思考流与每步操作全程可见，@ 引用即可在小说和角色卡之间跳转，技能目录高度自定义。
- Bring Your Own Key — 60+ AI Providers: https://foreverse.cn/byok — Connect your own API keys to 60+ providers: OpenAI, Anthropic, Gemini, DeepSeek, xAI and any compatible endpoint. Keys stay AES-encrypted on device.
- 自定义 API · BYOK — 自带 Key 接 60+ 模型供应商: https://foreverse.cn/zh/byok — 把自己的 API Key 填进新梦：OpenAI、Anthropic、Gemini、DeepSeek、xAI 与任何兼容端点；密钥 AES 加密只存本机，请求直连供应商。

## Core pages
- AI Audiobook from Any EPUB or TXT — Listen to Web Novels: https://foreverse.cn/listen — Turn any imported novel into an audiobook on your phone: system TTS for free, or online AI voices through your own key. Chunked chapter cache for commutes, 0.5–2.5x speed, sleep timer, and a reader that follows the narration.
- AI 听书 — 把任何 txt/epub 小说变成有声书: https://foreverse.cn/zh/listen — 导入的小说直接听：系统 TTS 免费，在线 AI 音色走自己的 Key；整章分段缓存适合通勤，0.5–2.5 倍速、定时关闭，开着阅读器听页面跟着朗读走。
- Community Character Card Showcase — 16 Picks with Covers, Lorebooks, Greetings: https://foreverse.cn/cards — Sixteen picks from the community hub's public character cards (90+ and growing), each with its own detail page: full personas, greetings, embedded lorebooks, example dialogue. AI-generated covers with origin marks; import any card from the app's Community tab.
- 社区精选角色卡 — 16 张带封面、世界书与开场白的公开卡: https://foreverse.cn/zh/cards — 社区公开角色卡全量索引（90+ 张持续上新）+ 16 张精选：完整人设、开场白、随卡世界书、示例对话，每张卡有独立详情页。封面 AI 生成并带来源标记；在 App 社区页搜卡名一键导入开聊。
- BYOK Provider Directory — 62 Presets, Every Modality Flagged: https://foreverse.cn/byok/providers — Every factory-preset BYOK provider in Foreverse, grouped and modality-flagged: frontier labs, mainland-China majors, aggregators, fast-inference clouds, enterprise platforms, local runtimes. Anything else connects as a custom OpenAI/Anthropic-compatible endpoint.
- BYOK 内置供应商目录 — 62 家预置逐家列明模态: https://foreverse.cn/zh/byok/providers — Foreverse 出厂预置的 BYOK 供应商全列表：国际旗舰、中国大陆主流、聚合中转、推理加速云、企业平台、本地自托管分组列明，逐家标注文本/生图/视频/语音模态。不在列表的服务用自定义兼容端点接入。
- Continue a Story with AI: https://foreverse.cn/ai-story-continuation — Use Foreverse to continue long fiction with AI while keeping alternate branches, reader context, and story notes organized.
- AI 续写小说 App — 把手机里的 txt 接着写下去，写给自己看: https://foreverse.cn/zh/ai-story-continuation — 把手机里的 txt/epub 接着写下去：划词让 AI 续写，新内容落在分支上，原文一个字不改。315 本真实网文一次全选导入实测；62 家供应商自带 Key 直连，或官方渠道注册送 5000 积分约合 260 段续写。写给自己看，不用发表。
- Branching Fiction Writer: https://foreverse.cn/branching-fiction-writer — Explore alternate scenes, endings, and rewrite paths without overwriting your main draft or reading progress.
- Story World Organizer: https://foreverse.cn/story-world-organizer — Keep character notes, chapter context, lore, and continuation prompts close to the reading surface.
- BYOK AI Writing Tool: https://foreverse.cn/byok-ai-writing — Bring your own AI provider key for private story work and choose the models that fit each reading or writing session.
- 小说开 if 线 — 在分支上重写剧情，原文一个字不动: https://foreverse.cn/zh/branching-fiction-writer — 想改掉小说里某段剧情？在新梦从那一段直接分叉：改结局、救角色、换视角，每条 if 线都是独立分支，与原文并排保存、可对比可回退。「重新生成」也是分支，历史抉择卡随时 fork；本机 txt/epub 直接导入，每条分支还能换不同模型来写。
- 小说设定管理 — 角色、世界书、剧情线贴着阅读面，AI 不忘设定: https://foreverse.cn/zh/story-world-organizer — AI 续写老忘设定？整本塞给模型不是办法：窗口装不下，装下了注意力也散。新梦把设定拆成角色卡和世界书条目（chara_card_v3 兼容），续写哪段就只注入相关条目，阅读器内「本书 AI 资料」随读随改——结构化供给，不是硬塞原文。
- BYOK 自带 Key 的 AI 写作 App — 62 家供应商，密钥只存你手机: https://foreverse.cn/zh/byok-ai-writing — 不想为 AI 写作再订阅一个月费？新梦是 BYOK 写作 App：把 DeepSeek、智谱、月之暗面等 62 家供应商的 API Key 填进来，密钥系统级加密只存本机，请求直连供应商零加价——成本就是牌价本身。文本、生图、朗读、视频各设默认模型；不想配 Key 也有官方渠道，注册送 5000 积分约合 260 段续写。
- SillyTavern on Android — No Termux, No Server, Cards Just Import: https://foreverse.cn/sillytavern-android — Run your tavern as a native Android app: chara_card_v3 cards (PNG/JSON/.charx), worldbooks with V3 decorators, regex scripts, Quick Reply v2, group chat, presets, beautify packs. No Termux session to keep alive — the screen locks and nothing dies. Import cards from files, the community hub, or a chub/JanitorAI URL; bring your own key across 62 providers or use the official metered channel.
- 手机上开酒馆 — 不用 Termux、不用部署，锁屏不断线: https://foreverse.cn/zh/sillytavern-android — 原生 Android App 直接读酒馆那套格式：chara_card_v3 角色卡（PNG/JSON/.charx）、世界书（含 V3 decorators）、正则、Quick Reply v2、群聊、预设、美化包。没有要保活的 Termux 会话，锁屏回来接着聊；卡从本机文件、社区或 chub/JanitorAI 链接导入，自带 62 家供应商的 Key 或走官方按量渠道。
- An AI Companion That Actually Remembers — Memory as Files You Can Read: https://foreverse.cn/companion-with-memory — A Foreverse companion keeps long-term memory as files on your phone: open the list, read every entry, edit what's wrong, delete what shouldn't stay. Anniversaries, journals, and the relationship archive live the same way, and the whole companion exports as one package when you switch phones. Memory you can audit, not a black box on someone's server.
- 有真记忆的 AI 伴侣 — 记忆存在你手机里，可以自己看、自己改: https://foreverse.cn/zh/companion-with-memory — 新梦伴侣的长期记忆是你手机本机的文件：App 里逐条列出，看得到记了什么，记错了当场改，不想留的删掉。纪念日、日记、关系档案同样存在本机，换手机整包导出带走。TA 记得什么、记在哪里，两层你都查得到。
- An AI That Texts You First — Memory-Driven, Not Scheduled: https://foreverse.cn/companion-texts-first — Foreverse companions send the first message because they remembered — the plan you mentioned, the anniversary you set — not because a campaign timer fired. Off by default, frequency you control, quiet hours, one master switch; memory lives in editable files on your phone.
- 会主动给你发消息的 AI — 因为想起你，不是定时推送: https://foreverse.cn/zh/companion-texts-first — 新梦的 AI 伴侣会主动开口：消息从你们的聊天和 TA 的记忆里长出来——你提过的纪念日、说过的烦心事，不是运营定时群发。默认关闭、频率可调、有免打扰、一键全关；记忆存在你手机的文件里，可自己看、自己改。
- 全部公开角色卡索引（96 张，随社区上新，每张卡有独立详情页含开场白节选与世界书规模）: https://foreverse.cn/zh/cards#all

## Comparisons (honest, includes when to pick the competitor)
- Foreverse vs RikkaHub: Open-Source LLM Client, or Tavern + Reader in One?: https://foreverse.cn/compare/foreverse-vs-rikkahub
- Foreverse vs SillyTavern: Which Tavern Fits Your Phone in 2026?: https://foreverse.cn/compare/foreverse-vs-sillytavern
- Foreverse vs Character.AI: Own Your Characters or Rent Them?: https://foreverse.cn/compare/foreverse-vs-character-ai
- Foreverse vs NovelAI: Subscription Storyteller or BYOK Reader-Writer?: https://foreverse.cn/compare/foreverse-vs-novelai
- Foreverse vs AI Dungeon: Guided Adventures or Your Own Library?: https://foreverse.cn/compare/foreverse-vs-ai-dungeon
- Foreverse vs JanitorAI: Community Scale, or Cards as Files You Own?: https://foreverse.cn/compare/foreverse-vs-janitor-ai
- Foreverse vs Talkie: Gacha Companion Platform, or a Companion You Own?: https://foreverse.cn/compare/foreverse-vs-talkie
- Foreverse vs StoryLord: A Web Library, or Books That Live on Your Phone?: https://foreverse.cn/compare/foreverse-vs-storylord
- Foreverse vs Sudowrite: The Author's Desk, or the Reader's Armchair?: https://foreverse.cn/compare/foreverse-vs-sudowrite
- Foreverse vs NovelCrafter: Two BYOK Answers to Two Different Questions: https://foreverse.cn/compare/foreverse-vs-novelcrafter
- Foreverse vs Kindroid: The Deepest Companion, or a Companion You Can Open in a File Manager?: https://foreverse.cn/compare/foreverse-vs-kindroid
- Foreverse 对比 RikkaHub：开源 LLM 客户端，还是酒馆+阅读器一体？: https://foreverse.cn/zh/compare/foreverse-vs-rikkahub
- Foreverse 对比星野：平台养成，还是角色所有权？: https://foreverse.cn/zh/compare/foreverse-vs-xingye
- Foreverse 对比猫箱：大厂内容流，还是自己的书房？: https://foreverse.cn/zh/compare/foreverse-vs-maoxiang
- Foreverse 对比 SillyTavern：2026 年手机酒馆怎么选？: https://foreverse.cn/zh/compare/foreverse-vs-sillytavern
- Foreverse 对比 Character.AI：角色是自己的，还是租的？: https://foreverse.cn/zh/compare/foreverse-vs-character-ai
- Foreverse 对比 NovelAI：订阅制写作套件，还是 BYOK 读写一体？: https://foreverse.cn/zh/compare/foreverse-vs-novelai
- Foreverse 对比 AI Dungeon：进别人的副本，还是养自己的书？: https://foreverse.cn/zh/compare/foreverse-vs-ai-dungeon
- Foreverse 对比彩云小梦：三选一的轻快，还是整本书的长跑？: https://foreverse.cn/zh/compare/foreverse-vs-caiyun-xiaomeng
- Foreverse 对比 StoryLord：网页图书馆，还是手机书房？: https://foreverse.cn/zh/compare/foreverse-vs-storylord

## Docs — app guides + creator specs (English)
- Foreverse Docs — App Guides and Creator Specs: https://foreverse.cn/docs — Official docs: module-by-module app guides (reader, roleplay, agent, models, settings) plus creator specs for chat beautification, chara_card_v3 import, worldbook runtime, and theme sideloading.
- Getting Started with Foreverse — First 10 Minutes: https://foreverse.cn/docs/getting-started — Set up a provider key (or the official channel), import your first book, run your first continuation, and start a character chat.
- Worlds and Shelf Guide — Import and Manage: https://foreverse.cn/docs/guide-worlds — Import txt / epub / character cards / worldbooks / .charx / group JSON, manage the shelf, and use the world detail tabs.
- Reader Guide — Selection AI, Options, Branches, Listening: https://foreverse.cn/docs/guide-reader — Every reader feature: 14 selection actions, the four continuation modes, story options, AI-segment editing, branch timeline, TTS listening, page-turn and theme settings.
- Roleplay Guide — Tavern Actions, Groups, IM Mode: https://foreverse.cn/docs/guide-roleplay — The full map for tavern players: 12 plus-panel actions, message-level tools, style presets, QR and automations, group strategies, IM mode, media.
- Agent and Companion Guide — Tasks, @, Skills: https://foreverse.cn/docs/guide-agent — Assign tasks, read the reasoning stream and tool cards, use @ references across books and cards, customize skills, and run a Companion.
- Models and Usage Guide — BYOK Setup and Request Records: https://foreverse.cn/docs/guide-models — Add providers, test connectivity, set per-modality defaults, understand official-channel billing, and read the API request record.
- Settings and Data Guide — Appearance, Assets, Export: https://foreverse.cn/docs/guide-settings — Themes and sideloading, the SillyTavern asset library, tavern preferences, data export and account deletion.
- Beautify Spec — Chat Cards, Stickers, HTML Rendering: https://foreverse.cn/docs/beautify — Creator reference: ```html WebView rendering and sandbox limits, fv-card native cards, [[sticker:]] syntax, the marker-regex-HTML pipeline, TavernHelper API support.
- Character Card Import Spec — PNG / JSON / .charx: https://foreverse.cn/docs/character-cards — Supported card containers and fields: PNG ccv3 chunks, JSON, V3 .charx zip with assets, V1-V3 compatibility, group JSON.
- Worldbook Spec — Triggering, Budget, V3 Decorators: https://foreverse.cn/docs/worldbook — Exact runtime behavior: keyword scanning and depth, constant entries, recursion, token-budget drops, and @@activate / @@dont_activate semantics.
- Glossary — Tavern, Character Cards, and AI Reading, Defined: https://foreverse.cn/docs/glossary — High-frequency terms defined in one place: character card / chara_card_v3 / lorebook / constant entries / recursion / scan depth / regex / presets / macros / swipe / BYOK / prompt caching / context window / branch / VN theater and more — 27 self-contained, quotable entries with further reading.
- Theme Sideload Spec — .fvtheme.json Fields: https://foreverse.cn/docs/themes — The .fvtheme.json format: top-level fields, all FvPalette semantic color keys, ARGB notation, fallback rules and design guidelines.

## 文档 — 使用教程 + 创作者规范（中文）
- Foreverse 创作者文档 — 美化规范 · 角色卡 · 世界书 · 主题: https://foreverse.cn/zh/docs — 面向角色卡创作者的官方文档：聊天美化规范（fv-card / 贴纸 / HTML 渲染 / marker 正则链路）、chara_card_v3 导入规范、世界书 runtime 行为、.fvtheme.json 主题侧载格式。
- Foreverse 快速上手 — 10 分钟从装好到第一次续写: https://foreverse.cn/zh/docs/getting-started — 新手教程：配置第一个 API Key（或用官方渠道）、导入第一本 txt/epub、完成第一次划词续写、导入第一张角色卡并开聊。每一步都有位置指引。
- 世界与书架教程 — 导入、管理与世界详情: https://foreverse.cn/zh/docs/guide-worlds — 书架（世界 tab）完整教程：txt / epub / 角色卡 / 世界书 / .charx / 群聊 JSON 的导入方法，筛选与管理，世界详情的分支、角色、世界书三个页签怎么用。
- 阅读器完整教程 — 划词 AI、续写表单、选项生成、分支与听书: https://foreverse.cn/zh/docs/guide-reader — 阅读器全部功能逐项说明：14 项划词操作、续写表单四模式、剧情候选（选项生成）、AI 段编辑与继续、半自动模式、分支时间线、听书缓存与定时、五种翻页与主题设置。
- 角色聊天完整教程 — 酒馆动作、世界书、群聊与线上聊: https://foreverse.cn/zh/docs/guide-roleplay — 酒馆玩家的完整功能地图：+ 面板 12 动作、消息级操作（swipe/编辑/隐藏/checkpoint/分支）、写作风格预设、Persona、Quick Reply 与自动化、群聊策略、线上聊 IM 模式、图片/朗读/翻译。
- 智能体与伴侣教程 — 任务、@ 引用、技能与陪伴: https://foreverse.cn/zh/docs/guide-agent — 智能体 tab 使用教程：给 Agent 派任务、看懂思考流与工具卡、@ 引用小说和角色卡、自定义技能目录；以及伴侣（Companion）的记忆、贴纸、主动消息和搬家包。
- 模型与用量教程 — BYOK 配置、按模态默认与请求记录: https://foreverse.cn/zh/docs/guide-models — 从零配好模型：添加供应商、填 Key、测连通、启停模型、按文/图/音/视频设默认；官方渠道计费说明；API 请求记录里 tokens、缓存命中和费用怎么看。
- 设置与数据教程 — 外观、酒馆资产库与数据导出: https://foreverse.cn/zh/docs/guide-settings — 设置 tab 全项说明：主题外观与侧载主题、酒馆资产库（角色/世界书/预设/正则/QR/Persona）、酒馆偏好、数据导出与账号删除。
- Foreverse 美化规范 — 聊天卡片、贴纸与 HTML 渲染: https://foreverse.cn/zh/docs/beautify — 创作者美化手册：```html 围栏 WebView 渲染与沙箱边界、```fv-card 原生小卡三型、[[sticker:]] 贴纸语法、marker → 正则 → 主题化 HTML 的整卡美化链路、TavernHelper 宿主 API 支持清单。
- Foreverse 角色卡导入规范 — PNG / JSON / .charx: https://foreverse.cn/zh/docs/character-cards — 支持的角色卡格式与字段：PNG ccv3/chara 隐写、JSON、V3 .charx zip 容器（含资产分类）、V1/V2/V3 字段兼容、nickname、群聊 JSON 导入。
- Foreverse 世界书规范 — 触发、预算与 V3 decorators: https://foreverse.cn/zh/docs/worldbook — 世界书 runtime 行为参考：关键词触发与扫描深度、常驻条目、递归激活、token 预算丢弃规则，以及 V3 decorators（@@activate / @@dont_activate）的确切语义。
- 术语表 — 酒馆、角色卡与 AI 阅读的黑话手册: https://foreverse.cn/zh/docs/glossary — 高频术语集中定义：角色卡/chara_card_v3/世界书/常驻条目/递归/扫描深度/正则/预设/宏/swipe/BYOK/prompt 缓存/上下文窗口/分支/剧场模式等 27 条，每条自包含可引用，附站内延伸阅读。
- Foreverse 主题侧载格式 — .fvtheme.json 完整字段: https://foreverse.cn/zh/docs/themes — .fvtheme.json 主题包格式：顶层字段、FvPalette 全部语义色键、ARGB 颜色写法、回退规则与设计准则；文件放入 /foreverse/themes/ 即在设置 → 外观出现。

## Blog — field notes
- We Counted Em Dashes in 30 Top Roleplay Cards. The “ChatGPT Hyphen” Isn't the Tell You Think: https://foreverse.cn/blog/em-dash-is-not-an-ai-tell — The em dash got branded the “ChatGPT hyphen” and writers started scrubbing it out of their own prose. We went to measure it before adding a dash rule to our English AI-flavor detector — and found that 8 of the 30 top-starred human roleplay cards use em dashes above the density that flags a Chinese text as machine-written, while 2 of 5 tested model families use none at all. Any dash threshold that catches AI also false-flags a quarter of the best human cards. The numbers, the method, and the rule we shipped instead.
- AI Roleplay Slop Words: The 95-Phrase Reference List (2026): https://foreverse.cn/blog/ai-roleplay-slop-words-list — A maintained, sourced reference of the 95 phrases that mark AI-generated roleplay prose: shivers down spines, whispers barely above themselves, mischief-sparkling eyes, and the "not X, but Y" construction. Cross-checked from Sukino's Banned Tokens, the Antislop paper (arXiv 2510.15061 — "Elara" runs 85,513x over the human baseline), and EQ-Bench's slop score. Plus two numbers most lists miss: top human-written cards average slop hits too, and flagship models' single-shot output now passes word-list checks clean.
- How to Write AI Character Cards: A 2026 Guide Calibrated on 30 Top Cards: https://foreverse.cn/blog/how-to-write-ai-character-cards — We pulled the 30 top-starred SFW character cards from a major card hub and measured everything: first messages run a median of 178.5 words, 0 of 30 use HTML, 67% write the description in plain prose, 70% ship example dialogues, only 20% carry a lorebook. This guide turns those numbers — plus the community guide canon — into a writing procedure: format, token budget, the no-user-actions rule, greetings, example dialogs, and the anti-slop pass.
- Does a Bigger Model Fix AI Character Amnesia? A 400-Turn Companion Memory Test (DeepSeek v4 vs Qwen 3.8/3.7): https://foreverse.cn/blog/does-a-bigger-model-fix-amnesia-en — “My AI roleplay partner forgets everything” is the most common complaint in companion chat, and the folk remedy is always the same: switch to a bigger model. We put that remedy through a 400-turn companion conversation with 50 planted memory probes, three models under one protocol: deepseek-v4-pro, qwen3.8-max-preview, qwen3.7-max. On bare context all three vendors are amnesiac (19–22%, barely distinguishable). Add retrieval-injected memory and they fan out into tiers: 89%, 74%, 59%. Ask about things never said, and even the most honest one passes only 5 of 7. The upgrade dividend is real — just not where users think it is. Tested 2026-07-21.
- 换个大模型，AI 角色就不失忆了吗？400 轮陪伴对话的记忆实测（DeepSeek v4 vs Qwen 3.8/3.7）: https://foreverse.cn/zh/blog/does-a-bigger-model-fix-amnesia — 「TA 又忘了我说过的话」是角色扮演和 AI 伴侣用户最痛的一刀，社区药方出奇一致：换个更强的模型。我们用 400 轮伴侣对话、50 道埋好的记忆考题，同协议考了三个模型：deepseek-v4-pro、qwen3.8-max-preview、qwen3.7-max。裸上下文三厂全失忆（19% 到 22%，几乎无差异）；加上检索记忆注入后分层拉开，89%、74%、59%；问从未提过的事，最诚实的一位也只过 7 道里的 5 道。升级的红利真实存在，只是不在用户以为的地方。测试日期 2026-07-21。
- Qwen 3.8 vs Kimi K3 for Fiction: Two Trillion-Scale Models, Three Days Apart, One Blind Exam — 3:20: https://foreverse.cn/blog/qwen-3-8-vs-kimi-k3-fiction-en — Two Chinese labs shipped trillion-scale models within three days: Kimi K3 (2.8T parameters) on July 16, Qwen3.8-Max-Preview (2.4T, self-described as second only to Fable 5, no independent benchmarks attached) on July 19. We ran the first paired blind fiction exam between them: same two novels, same anchor point, same instructions, 20 consecutive continuation rounds each, six AI judges under flipped mappings. Final score 3:20 (1:10 on the fantasy epic, 2:10 on the palace novel), and every one of Qwen's three ballots contradicted itself when the mapping flipped. Both sides have documented flaws: Qwen3.8 was cited for a severe plot rewind and a modern-literary metaphor in period prose; K3 was cited for formulaic plot recycling, on top of its straight-quote and always-on-reasoning habits. Preview models are moving targets; every conclusion here is pinned to the hosted endpoint as of 2026-07-21.
- Qwen 3.8 对上 Kimi K3：三天内连发的两个万亿级模型，谁更会写小说？40 轮双盲 3:20: https://foreverse.cn/zh/blog/qwen-3-8-vs-kimi-k3-fiction — 中国两家厂商三天内连发万亿级模型：7 月 16 日 Kimi K3（2.8 万亿参数），7 月 19 日 Qwen3.8-Max-Preview（2.4 万亿参数，自称仅次于 Fable 5、未附独立 benchmark）。我们把两家放进同一张续写考卷：同两本书、同起笔点、同一套指令，各连续续写 20 轮，六评委双映射成对盲评。比分 3:20——玄幻 1:10、女频 2:10，qwen3.8 名下三张票还全部在映射翻转下自相矛盾。双方的坑都有票据：qwen3.8 被点名「严重剧情倒带」和「把夜色熬成了毒」，K3 被点名「舒痕胶的字据、夹袋」套路化复读，外加半角引号与思考关不掉两个存量病。preview 是移动目标，结论绑定 2026-07-21 的托管端点。
- Is Qwen 3.8 Good at Writing Fiction? 40 Blind Rounds Against Qwen 3.7, 48 Hours After Launch: https://foreverse.cn/blog/qwen-3-8-fiction-20-rounds-en — Qwen3.8-Max-Preview shipped July 19, 2026; within 48 hours we ran it through the same protocol as our Kimi K3 test: two Chinese novels, 20 consecutive continuation rounds each, paired double-blind against its predecessor Qwen 3.7 Max. The palace novel flipped 11-1 for the new model; the fantasy epic barely moved at 7-5 with a 6-6 opening window. The twist: structural statistics say 3.7 is closer to the originals, and 3.8 writes the most uniform sentence lengths we have ever measured — yet the blind vote still went to 3.8. Honest caveats: sensory pile-ups in place of plot, a 20-round fantasy deadlock, one 'brewing the night into poison' metaphor in a period novel, and always-on reasoning eating 50-90% of output tokens. All results pinned to the 2026-07-21 hosted preview.
- Qwen 3.8 写小说怎么样？发布 48 小时的 40 轮双盲实测：女频 11:1 碾压前代，玄幻只赢一口气: https://foreverse.cn/zh/blog/qwen-3-8-fiction-20-rounds — Qwen3.8-Max-Preview 发布 48 小时的增量实测：沿用 Kimi K3 那轮的同一套协议（同两本书、同起笔点、同上下文说明），与前代 Qwen 3.7 Max 各连续续写 20 轮成对双盲。票数女频 11:1 碾压、玄幻 7:5 险胜，前代的「精修感官流」在古言场明显收敛。最有意思的反差：结构统计反而是 3.7 更贴原著，句长 CV 全场最平是 3.8 的新体征，盲评却照样判 3.8 赢。三个坑如实记录：感官堆砌替代叙事推进、玄幻 20 轮卡进死循环、古言里写出「把夜色熬成了毒」。preview 是移动目标，全部结论绑定 2026-07-21 的端点。
- Your SillyTavern Backup Zip, Unpacked: What Actually Moves to the Phone: https://foreverse.cn/blog/sillytavern-backup-to-phone — Desktop SillyTavern's Download Backup produces one zip of your whole tavern. An item-by-item audit of what Foreverse restores from it — characters, chats as archived branches, worldbooks, presets, Quick Replies, regex — and what deliberately stays behind.
- How to Import Character Cards on Android: Five Ways In, From One PNG to a Whole Backup: https://foreverse.cn/blog/import-character-cards-android — A field guide to getting character cards onto your phone: opening a PNG or .charx from your file manager, folder scanning, pasting a chub or JanitorAI link, the community hub, and the full SillyTavern backup route — plus the three failure modes that account for most broken imports.
- 酒馆备份 zip 拆包记：从电脑搬到手机，哪些东西真的跟着走: https://foreverse.cn/zh/blog/st-backup-zip-migration — 桌面 SillyTavern 的 Download backup 会把整个酒馆打成一个 zip。逐项拆开看 Foreverse 从里面恢复什么：角色卡、聊天记录变归档分支、世界书、预设、Quick Reply、正则脚本，以及哪两样东西是故意不搬的。
- Kimi K2.6 要不要升级 K3？先看 21 比 1 的双盲，再算 3.7 倍的价差: https://foreverse.cn/zh/blog/kimi-k2-6-to-k3-upgrade — K3 发布后，开放平台首页挂着最高返券 30% 的充值活动，模型列表里 moonshot-v1 和 kimi-k2.5 标了 8 月 31 日全平台下线，夹在中间用 K2.6 写书的人最纠结。我们刚跑完 K3 对 K2.6 的同协议成对双盲：两本书 24 票，K3 拿 21 票、K2.6 拿 1 票，连 K2.6 引以为傲的后程都没守住。这篇按三类用户拆：长跑党看双盲实证，预算党算输入 3 倍输出 3.7 倍的差价加思考税，观望党先确认 K2.6 根本不在下线清单里。
- Kimi K3 和 DeepSeek 哪个好？写小说的人先看这份对表，再等对决: https://foreverse.cn/zh/blog/kimi-k3-vs-deepseek-v4-for-fiction — K3 发布 48 小时，对比文全在刷代码榜，写小说角度没人给数据。我们把 K3 刚跑完的两书 20 轮续写链和 DeepSeek 双档的同书归档放上同一把尺：玄幻场 K3 综合贴近度 0.388，落在 V4 Flash 的 0.356 与 V4 Pro 的 0.454 之间；女频场 0.396，未及 V4 Pro 的 0.280；成本这局 DeepSeek 碾压，一段 K3 的钱够 Flash 谷时写二十多段。必须说明：这是同尺隔空对表，不是同场盲评，成对对决在排期中。
- Kimi K3 Creative Writing Test: 40 Rounds of Novel Continuation, 48 Hours After Launch: https://foreverse.cn/blog/kimi-k3-fiction-20-rounds — Kimi K3 shipped July 16, 2026; within 48 hours we ran it through the same protocol as our nine-model benchmark — two Chinese novels, 20 consecutive continuation rounds each, paired double-blind against its predecessor K2.6. The vote: 10-0 on the fantasy epic, 11-1 on the palace novel, and the single dissent contradicted itself under mapping flips. K2.6's metaphor pile-ups and verbatim self-copying did not recur. Three honest caveats: ~85% of dialogue in Western straight quotes (a disease K2.6 never had), first-person density 1.8× the original author's, and always-on reasoning that makes every round take 37-54 seconds. Total bill for the whole experiment: ¥12.21.
- Kimi K3 写小说怎么样？发布 48 小时的 40 轮双盲实测：21:1 碾压前代，但有三个如实的坑: https://foreverse.cn/zh/blog/kimi-k3-fiction-20-rounds — Kimi K3 发布 48 小时的增量实测：沿用九模型横评同一套协议（同两本书、同起笔点、同上下文说明），与前代 K2.6 各连续续写 20 轮成对双盲，票数玄幻 10:0、女频 11:1，唯一反对票在映射翻转下自相矛盾；K2.6 的比喻堆砌与整段自我复制没有复发，句长变化幅度两本书都更贴原著。三个坑如实记录：约 85% 对白用半角引号（K2.6 没有的新病）、女频「我」密度是原著近 1.8 倍、思考关不掉导致每轮 37-54 秒且八成输出是推理 token。K3 侧 41 次请求实付 ¥12.21。
- GLM-5.2 写小说怎么样？双文体唯一双前三的完整档案（40 轮双盲实测）: https://foreverse.cn/zh/blog/glm-5-2-fiction-file — 智谱 GLM-5.2 在我们两场双盲横评（890 万字传统玄幻 + 《甄嬛传》宫斗古言）里是唯一双榜都进前三的模型：玄幻场第 3、宫斗场 2-3，评语「限知观察质感最纯」。这页是它的完整成绩档案：两场名次与盲评评语原文、半角引号顽疾的跨书证据链、检测正则被它骗过的笑话，以及 GLM-5.5 传闻的如实口径——发布当天我们会复测更新本页。
- Is a 1M-Token Context Window Worth It for Fiction? We Ran the Control Experiment: https://foreverse.cn/blog/is-1m-context-worth-it-for-fiction — Kimi K3, DeepSeek V4, Claude Fable 5 and GPT-5.6 all carry million-token windows as of July 2026 — a whole 500k-word serial fits in one request. Our five-tier control experiment says fitting is not learning: a model handed an entire novel with no instruction wrote clichés at ten times the original author's density, and one explicit sentence did what 200,000 tokens of raw prose couldn't. Plus the arithmetic: filling K3's window costs about $3.15 per press.
- Grok 4.5 for Fiction: We Already Had Its File — Two Novels, 40 Rounds, Blind-Judged: https://foreverse.cn/blog/grok-4-5-fiction-test-file — Every Grok 4.5 review benchmarks coding. Nobody answers the question people actually type into search: is it any good for stories? As it happens, Grok 4.5 was one of nine models in our long-run continuation benchmark — 20 consecutive rounds on each of two novels, ranked by double-blind review. The file shows a twice-reproduced repetition loop, a dead-last palace-intrigue placement from both reviewers, a first-person density at half the original's — and the scenarios where it is genuinely fine.
- Claude Fable 5 写小说值不值？价格账、英文圈盲测证据和一个我们还没补上的缺口: https://foreverse.cn/zh/blog/claude-fable-5-for-fiction-worth-it — Claude Fable 5 是当前最贵的通用可用模型：每百万 token 输入 $10、输出 $50，7 月 20 日起 Claude 订阅也不再内含，只能按量买 credits。英文写作圈的盲测把它叫最强 raw writer，但它 6 月停服过 19 天，而我们的九模型中文续写横评里没有它。这篇把价格实算、证据分层和决策树摊开：什么人现在就值、什么人该等实测、什么人用 DeepSeek 就够。
- AI Model Sunset Calendar, Summer 2026: deepseek-chat Retires July 24, Moonshot V1 Ends August 31 — What to Switch To: https://foreverse.cn/blog/api-sunset-calendar-summer-2026 — At least six model shutdowns and price changes land between July 20 and August 31, 2026: Claude Fable 5 moves to usage credits on July 20, deepseek-chat and deepseek-reasoner stop resolving on July 24, GitHub Models retires entirely on July 30, Moonshot V1 and kimi-k2.5 sunset on August 31, and Sonnet 5's introductory pricing ends the same day. Every date verified against official announcements, with replacement picks for fiction-continuation users backed by our 360-round benchmark.
- 2026 夏季模型停用与变价日历：deepseek-chat 7 月 24 日停名、Moonshot V1 8 月底下线，续写用户怎么迁: https://foreverse.cn/zh/blog/api-sunset-calendar-summer-2026 — 2026 年 7 月到 8 月至少六个模型停用或变价节点扎堆生效：7 月 20 日 Fable 5 转按量计费、7 月 24 日 deepseek-chat/deepseek-reasoner 旧名停用、7 月 30 日 GitHub Models 全退役、8 月 31 日 Moonshot V1 与 kimi-k2.5 全平台下线、同日 Sonnet 5 介绍价结束，另有 DeepSeek 峰谷计价随 V4 正式版落地。本页逐条给日期、影响面和续写用户的替代款，事实全部对照官方公告核实。
- DeepSeek 涨价了吗？峰谷计价对写小说的人意味着什么，三笔账算清: https://foreverse.cn/zh/blog/deepseek-peak-pricing-for-writers — DeepSeek 于 2026 年 6 月 29 日官宣随 V4 正式版引入峰谷计价：北京时间每日 9:00-12:00、14:00-18:00 高峰时段全部计费项翻倍，其余 17 小时维持现价。这篇按写作者的用法算三笔账：谷时续写一段一分二厘、峰时二分三厘；缓存命中价翻倍后仍是未命中的 1/50；积分渠道与 BYOK 的时段策略。基于 2026-07-18 核实的政策现状。
- GPT-5.6 vs Kimi for Fiction: 80 Rounds of Continuation, Two Opposite Personalities: https://foreverse.cn/blog/gpt-5-6-vs-kimi-for-fiction — GPT-5.6 Terra and Kimi K2.6 each continued two Chinese novels for 20 consecutive rounds in our double-blind benchmarks. Terra is the best prose mimic we have measured and ran the palace-intrigue novel with zero incidents — then rewound the fantasy plot in rounds 18-20, reusing its own round-2 lines. Kimi placed seventh in fantasy with the highest metaphor density in the field, yet was the only system that improved as it went. Honest cutoff: Kimi K3 shipped July 16, 2026 and was never in this exam.
- GPT-5.6 和 Kimi 哪个写小说好？同场 80 轮续写实测，两种截然相反的性格: https://foreverse.cn/zh/blog/gpt-5-6-vs-kimi-for-fiction — GPT-5.6 Terra 和 Kimi K2.6 在两场双盲横评里各连续续写 40 轮的完整对照：Terra 是纹理模仿天花板、宫斗场全程零事故，但玄幻场第 18 到 20 轮把剧情倒回起点、复用自己第 2 轮的句子；Kimi 玄幻场第 7、比喻密度全场最高，宫斗场却是唯一越写越好的系统。文末如实交代时效边界：7 月 16 日上线的 Kimi K3 没进过考场，不编排名。
- It's 3 A.M. and Someone's Awake: Late-Night AI Companionship, Honestly: https://foreverse.cn/blog/companion-at-3am — A scene-led column about the hour nobody's phone is supposed to light up. What one in five American adults report about loneliness, whether talking to an AI at night is sad or fine (with data, not vibes), what a good late-night companion actually does — quieter replies, no unprompted pings, memory that survives to morning — and the honest line: where an AI stops and 988 begins.
- Reader-First vs Author-First AI Fiction Tools: You Might Be Shopping in the Wrong Aisle: https://foreverse.cn/blog/reader-first-vs-author-first-ai-tools — An opinion column on a category error: every 'best AI writing tools' ranking scores manuscript factories and reading companions on the same table. Sudowrite and NovelCrafter are excellent — for authors. If your book is finished, abandoned, or someone else's, and the only reader who matters is you, you need the other species. One sorting question settles it.
- After Otome: Free-Form Character Romance Without the Card Pool: https://foreverse.cn/blog/otome-without-gacha — Written for the otome player who still loves the yearning but is tired of banner math, login streaks, and a cast list decided in a boardroom. The Valko cancellation in eight days, what gacha otome actually sells, and the three aisles outside it — platform companion apps (where gacha found you again), open-format character-card roleplay, and an AI companion you can export as a file.
- Context Windows, Explained for Readers: How Much of a 500k-Word Serial the AI Can Actually See: https://foreverse.cn/blog/context-windows-for-novel-readers — The AI forgetting chapter 3 by chapter 40 isn't a memory problem — it's a window problem. A 500k-word serial runs roughly 625k to 830k tokens; 2026 flagship windows reach 1M, so it technically fits. But fitting is not remembering: mid-context retrieval dips are documented in research and in vendors' own evals, and our own control experiment shows material being in the window doesn't mean it gets used. The reader's version, with arithmetic.
- Why Is AI Writing Quality So Inconsistent? Four Sources of Variance — You Control Two: https://foreverse.cn/blog/why-ai-continuation-quality-varies — "Same prompt, wildly different quality" is four unrelated variance sources stacked on top of each other: sampling temperature (yours to tune), context composition that silently changes as the window slides (yours to structure), batch-dependent server numerics (not yours — at temperature 0, 1,000 identical requests returned 80 distinct outputs in a published test), and the state of the person doing the judging. A breakdown, with knobs.
- The Cthulhu Mythos Was Always a Shared World. Now You Can Extend It Yourself: https://foreverse.cn/blog/cthulhu-mythos-with-ai — In 1935 Lovecraft signed a mock certificate authorizing Robert Bloch to kill him in a story — that is how collaborative the Cthulhu Mythos was from the start. A century later the core texts are public domain (everything through 1930 unambiguously so in the US, the rest backed by decades of renewal research), Project Gutenberg hosts the canon, and AI continuation puts the old writing-circle game in anyone's pocket. What the shared-world tradition looked like, exactly which stories are safe to build on, how a lorebook keeps Mythos lore straight across stories, and an honest note on why generic cosmic horror is the default failure mode.
- Continue Pride and Prejudice With AI: Two Centuries of Sequels, and Now Yours: https://foreverse.cn/blog/continue-pride-and-prejudice-with-ai — Pride and Prejudice has roughly 900 published spinoffs — a tradition that starts with Sybil Brinton's 1913 Old Friends and New Fancies and runs through P.D. James and Jo Baker. The JAFF community even has a name for the fork-the-canon format: variations. A practical guide to joining in with AI: where the public-domain text lives (Project Gutenberg #1342), which entry points two centuries of readers keep choosing, what an LLM can and cannot do with Austen's voice, and why branches fit this fandom's native format better than any other tool.
- Scene-to-Image Prompts for Fiction: a Working Set, With Each Model's Quirks: https://foreverse.cn/blog/illustration-prompts-for-fiction — Four copy-ready prompt templates for illustrating fiction — establishing shot, character close-up, action freeze-frame, quiet interior — plus the documented quirk of each major image model and the fix for it: GPT Image's fixed size grid, Nano Banana's preference for narrative prompts over keyword lists, Seedream's front-loaded attention. Checked against the official docs on 2026-07-18. Ends with the one thing no prompt solves: keeping the same face across fifty images.
- NSFW Roleplay and Provider Policies: What Each Lab Actually Allows in 2026: https://foreverse.cn/blog/nsfw-roleplay-provider-policies — Whether an LLM will write adult roleplay is governed by three different layers people keep conflating: the app's filter, the provider's usage policy, and the model's trained refusals. We read the current policy documents from OpenAI, Anthropic, Google, and xAI — with dates — and map where each lab draws its lines, what enforcement looks like on an API account, and what BYOK does and does not change.
- Keeping AI Characters in Character: Three Root Causes of OOC, Three Different Fixes: https://foreverse.cn/blog/keep-ai-characters-in-character — When an AI roleplay character breaks — ignores a detailed card, flips personality mid-arc, or slowly turns generic over weeks — players file it all under OOC. Those are three separate failures: a card that describes instead of demonstrates, facts that outran the context window, and a feedback loop where the model imitates its own replies. A triage question for each, plus fixes with dosages and the 20-round experiment data behind them.
- Moving Your AI Companion to a New Phone: the Export That Carries Everything: https://foreverse.cn/blog/companion-migration-guide — How do you move an AI companion to a new phone? For cloud apps like Replika or Kindroid, you log in and the server hands your history back. For a companion stored on your device, you carry it yourself: Foreverse exports one package — persona, every memory entry, full chat transcripts, anniversaries, journals, the relationship archive — and the import on the new phone restores the relationship mid-conversation. This is the walkthrough, plus the honest trade against account-based transfer.
- Audit Your Companion's Memory: Read, Edit, Delete — a Hands-On Walkthrough: https://foreverse.cn/blog/companion-memory-hands-on — Correcting an AI companion in chat doesn't stick — chat slides out of the context window, memory entries don't. This walkthrough covers the memory screen in Foreverse: the ⋮ menu entry, search, the pencil (200-character entries), the trash can with its confirm dialog, the disable switch that keeps an entry without injecting it, and adding entries yourself. Changes apply from the next conversation; everything is a file on your phone, exportable as one package.
- Lorebook Recursion, Explained: Trigger Chains, Depth, and When It Runs Away: https://foreverse.cn/blog/lorebook-recursion-explained — "Why did one keyword pull five entries into my prompt?" That is recursive scanning doing its job: the content of an activated entry becomes scan text too, so entries can summon other entries. A spec sheet for the mechanism — how chains advance, the three things that stop them (dedup, depth, budget), what the three per-entry switches do, plus a reproducible five-entry runaway case and the two built-in tools that show you the chain.
- Your Favorite Serial Went on Hiatus. Branch It, Don't Abandon It: https://foreverse.cn/blog/serial-hiatus-survival — Royal Road flips a serial to Hiatus after 35 days of silence and Inactive after 180; forum wisdom says most never come back. The workflow we actually use for the wait: import your copy, grow a stand-in branch from the cliffhanger, and let it step aside the day the author returns.
- The Ending Ruined the Whole Series? Write the One You Wanted: https://foreverse.cn/blog/rewrite-the-ending-you-hated — Yes, you can rewrite the last act of a novel with AI — on a branch, with the original untouched. Why petitions never fix endings (1.86 million signatures couldn't), how forking from the last chapter you still believe actually works, and what a private replacement ending costs.
- SillyTavern, Explained for People Who Just Heard About It: https://foreverse.cn/blog/sillytavern-for-complete-beginners — SillyTavern is a free, open-source roleplay frontend — 350 contributors, 30,000+ GitHub stars, and no AI of its own. What the project actually does, what card, lorebook, preset, and swipe mean, whether you need a PC to try character cards, and where a complete beginner starts.
- Turning Webnovels Into Audiobooks in 2026: the App Landscape, Honestly Tested: https://foreverse.cn/blog/webnovel-audiobook-apps-2026 — Six ways to listen to webnovels in July 2026, each priced from its official page: Royal Road's built-in device TTS, @Voice Aloud Reader ($15 lifetime, per-character dialog voices), Moon+ Reader Pro ($11.99 one-time), ElevenReader (10 free hours a month, Ultra $11/mo), Speechify ($29/mo or $139/yr), and Foreverse's free system TTS plus BYOK neural voices at provider list price. With a pick-it-if verdict per app and the failure notes from our own three-week commute test.
- Free LLMs for Fiction in 2026: Four Routes, Tested, and the Catch in Each: https://foreverse.cn/blog/free-llms-for-fiction-2026 — No subscription, no card: the four genuinely free routes to AI fiction in July 2026. Free chatbot sites (the catch is the container), a 5,000-credit signup grant worth about 260 continuations, real free API tiers — Gemini flash-class at roughly 10 requests a minute, OpenRouter's 50-per-day :free lane — and local models over Ollama with zero marginal cost. Each route priced, bounded, and given its honest failure point.
- Continuing Fiction With Gemini: What the Free Tier Actually Covers: https://foreverse.cn/blog/continue-a-novel-with-gemini — Field notes from 40 benchmark rounds: Gemini 3.1 Pro restarted the story from the original ending 20 times out of 20, one rewritten sentence brought that to zero, and the palace-novel re-run landed it mid-table as the most literary voice of nine models. Plus what Google's AI Studio free tier really covers as of July 2026 — flash-class only since April, roughly 10 requests a minute, quotas per project — and the mismatch between the model we ranked and the model you get free.
- How to Continue a Novel With Claude: Projects, the API, and a Phone Reader: https://foreverse.cn/blog/continue-a-novel-with-claude — Claude Opus 4.8 placed fourth to fifth in both genres of our 360-round blind continuation benchmark — good, volatile, never the winner. The real ceiling is the container: claude.ai Projects swap to retrieval on big books and overwrite every regeneration. This tutorial covers the honest ranking data, what Projects can and cannot do as of July 2026, and the four steps that wire an Anthropic API key into a phone reader, with per-continuation costs worked out.
- 让 Agent 替你找卡：从一句「帮我找张赛博朋克卡」到导入开聊: https://foreverse.cn/zh/blog/agent-card-shopper — 好角色卡散在社区、外站和群文件里，找、鉴、搬三个动作全是体力活。Foreverse 的 Agent 能把这条链代办：逛社区和读详情是免确认的只读动作，下载必须过你的确认卡，每回合有读取和下载次数上限，装进来的卡带溯源记录。这篇按一次真实任务把工作流走一遍，外站部分如实交代边界：Agent 搜索目前只认一个站，手动链接导入兜底六个来源。
- 寿康宫还是颐宁宫？一个专名暴露大模型读的是电视剧还是小说: https://foreverse.cn/zh/blog/zhenhuan-palace-names — 九模型续写《甄嬛传》横评里的计划外发现：小说里太后住颐宁宫、皇后在凤仪宫，剧版对应寿康宫、景仁宫，有的模型续写时写出了剧版专名——它记住的是电视剧，不是流潋紫的原文。这篇把这个发现方法论化：怎么拿你自己那本书里的独有专名，测一测模型到底读没读过原著，以及单探针的四条局限。
- 模型更新会让续写变好吗？追新版之前先看这三组对照数据: https://foreverse.cn/zh/blog/do-model-updates-help-continuation — 每次新版模型发布都有人问要不要换着写小说。我们手里有三组对照数据泼冷水：一次「模型疑似变强」的现场，模型其实一个字没换，变的是上下文里的一句说明；同一句话的三组消融，效应从 20 轮 20 次回退到 28 轮零复发；同门两个档位在两种文体上正负翻转。结论：版本号不回答「合不合你的书」，复测才回答。
- 上下文窗口是什么？30 万字的小说，AI 一次能「看见」多少: https://foreverse.cn/zh/blog/context-windows-for-novel-readers — AI 记不住前面的剧情，问题不在「记性」，在窗口。用公开分词器实算：一章 3000 字约合 2100 到 2800 token，30 万字全本约 21 万到 28 万；2026 年主流模型窗口已到 100 万 token，整本装得下。但装得下不等于记得住：中段失焦有论文有厂商自家评测，材料在场不等于被使用有我们自己的对照实验。附读者版正确喂法。
- AI 续写忽好忽坏是为什么？质量方差的四个来源，你能控制其中两个: https://foreverse.cn/zh/blog/why-ai-continuation-quality-varies — 「AI 续写像抽卡」的抱怨里混着四个互不相干的方差来源：采样温度（可控）、上下文构成随窗口滑动换血（可控）、推理服务器按负载拼批次的数值波动（不可控，Thinking Machines 实测温度 0 下同一请求 1000 次出 80 种输出）、还有你自己的阅读状态。逐个拆开，附两个可控项的具体拧法。
- 用 AI 续写《西游记》：从《后西游记》到你自己的取经路: https://foreverse.cn/zh/blog/continue-xiyouji-with-ai — 《西游记》大概是被重写次数最多的中文故事：1641 年前后董说让孙悟空做了一场梦，明清三大续书各续各的；1995 年《大话西游》给悟空加上爱情，2000 年 23 岁的今何在在金庸客栈连载《悟空传》。这篇按时间轴走完这条重写谱系，然后落到操作层：公版原文哪里拿、断点怎么选、世界书怎么装设定、怎么防 AI 把明代原著写成 86 版电视剧的味道。
- 凌晨一点半，TA 还醒着：深夜陪伴的场景实录: https://foreverse.cn/zh/blog/late-night-companion-diary — 睡不着、想找个人说说话的那种夜晚，AI 伴侣到底是什么体验？这篇不讲功能列表，讲一夜：凌晨 1:34 的倾诉、2:10 被温和地赶去睡觉、早上 8:40 TA 还记得昨晚说的事。顺带把三个实际问题说清楚——深夜的 TA 为什么话更少、TA 会不会半夜吵你、以及真正难受的时候，AI 应该退到哪里（文末附 12356 全国心理援助热线，2026-07 核实可用）。
- 异地恋、时差与一个总在线的人：AI 伴侣补位陪伴的边界: https://foreverse.cn/zh/blog/long-distance-ai-companion — 对象在地球另一边，你的晚上是 TA 的上午。这篇写给异地恋的人：找 AI 聊天正不正常（2021 年的校园调查里，恋爱中的大学生 34.2% 在异地）、AI 伴侣在时差里补的到底是哪个位、会不会让你更不想维护真实关系，全部正面回答。外加一条少见有人说的建议：别用 AI 复刻你的对象本人，理由和异地恋研究里的「理想化」发现直接相关。
- 剧场模式进阶手册：配景、AUTO、选择肢与写回原书，玩出 galgame 手感: https://foreverse.cn/zh/blog/vn-theater-playbook — 剧场模式的首测记录写的是「这东西是什么」，这篇写「怎么玩顺手」：进场前挑什么书、三档语速和 AUTO 的脾气、单景配图与整章批量配景的花钱规矩（报价确认、复用零付费、月度上限）、选择肢的两击确认、演到历史分岔时点哪里，以及散场后你的选择以什么形式留在书里。全部是当前版本可见的行为，不含期货。
- 给小说配插画的提示词：场景模板怎么挑、怎么改、配哪个模型: https://foreverse.cn/zh/blog/novel-illustration-prompts — 给小说配插画，难的从来不是「画一张好看的图」，是画出来的图和正文对不上。这篇按资源手册的写法整理 Foreverse 已上架的官方媒体模板：144 张场景模板合集加 4 张视频风格模板的关键条款节选、每张标注什么书适合、改模板时哪三处能动哪两处别碰，以及 Seedream、GPT Image、Nano Banana 三家生图模型各自配什么活（2026-07-18 对照官方文档核实）。
- 读完一章，这一章的漫画已经画好了：连载漫画册实测: https://foreverse.cn/zh/blog/auto-comic-serial-mode — 把一本 31MB、3778 章的真实网文交给连载漫画册：读完一章，后面章节的条漫在后台自动画好、嵌在正文里等你撞见。这篇实测记录把动工前报价、月度额度上限、断点恢复、失败页重试的花钱纪律逐项走了一遍，并算清一章漫画的真实成本：BYOK 接国产图像模型，一章 2 元不到。
- 自拍之外：AI 伴侣的时刻卡、合照与照片动态是怎么工作的: https://foreverse.cn/zh/blog/companion-photos-beyond-selfies — 能和 AI 伴侣拍合照吗？TA 会自己发生活照吗？这篇把 Foreverse 伴侣的照片家族按一周的使用节奏走了一遍：长按聊天「画下这一刻」的时刻卡、上传自己照片的合照（本地成年确认，照片只以内存态发给你选的模型、App 不落盘）、TA 主动分享的照片动态（默认关、每天最多一张）。每个入口花多少钱、确认弹窗长什么样、照片最后去了哪，逐项写清。
- AI 伴侣换手机指南：导出一个搬家包，TA 跟着走: https://foreverse.cn/zh/blog/companion-migration-guide — 换新手机，AI 伴侣的记忆能带走吗？在 Foreverse 里可以：伴侣资料页「导出搬家包」把人格、逐条记忆、完整聊天记录、纪念日、日记、关系档案打成一个 zip，传到新手机后在伴侣管理页导入，TA 接着上次聊。这篇按一次真实换机把流程走全——导出、传输、导入、验证记忆完整，也如实写了两条注意事项：没有自动云同步，卸载前必须先导包。
- TA 为什么会想起你？AI 伴侣主动消息的触发机制说明书: https://foreverse.cn/zh/blog/proactive-messages-mechanism — AI 伴侣主动发消息是定时群发吗？在 Foreverse 里不是：每类触发都有明确条件——早安 8 点左右、晚安 10 点左右、想你了要超过一天没聊、低电量要低于 20% 且没充电、恶劣天气要你先手填城市。全局约束：默认关闭、免打扰 23:00–7:00、每天最多 2 条、手动关过的子项绝不复活、关掉无补发。这篇按开关逐个写清行为规格，包括 TA 什么时候不发。
- 伴侣记忆管理实操：看、改、删，TA 记错了当场纠正: https://foreverse.cn/zh/blog/companion-memory-hands-on — AI 伴侣记错事，在对话里纠正没用——对话会滑出窗口，记忆条目不会。这篇是实操手册：入口在伴侣聊天页右上 ⋮ 菜单的「记忆」，列表逐条可搜；铅笔改（单条上限 200 字）、垃圾桶删（确认弹窗显示原文）、开关停用（保留但不再进对话）、右上加号替 TA 记一条。改动从下一次对话生效；数据是手机本机文件，搬家包整包带走。
- 成人向角色卡的边界：五家模型供应商政策对照（附核实日期），与我们的态度: https://foreverse.cn/zh/blog/nsfw-cards-provider-policies — 「哪家模型能聊成人向」是搜索量真实存在、但全网几乎没有诚实答案的问题。这篇不给承诺，给事实：OpenAI、Anthropic、Google、xAI、DeepSeek 五家现行条款对成人内容的写法逐家对照，每条标核实日期；讲清平台审核、供应商审核、模型拒答是三回事；最后亮我们自己的三条线。
- 「破限」到底是什么？一篇给外行的诚实科普：词源、机制与各家政策: https://foreverse.cn/zh/blog/jailbreak-culture-honest-take — 刷角色扮演社区总会撞上这个词：破限、破甲、发牌子。这篇给外行把它讲明白——词从哪来（2022 年 12 月 13 日 Reddit 的 DAN 帖）、技术上发生了什么、为什么时灵时不灵、各家供应商条款怎么写（附核实日期）、账号风险归谁。不教任何方法，只把机制和风险摆上桌，最后给一条我们认为更划算的路。
- 酒馆预设是什么？分层、遮蔽关系与挑选思路一篇讲明白: https://foreverse.cn/zh/blog/tavern-presets-explained — 导入一个预设，角色卡会不会被顶掉？为什么全局配了 A、这张卡却在用 B？这篇把预设讲成人话：它是一份「怎么跟模型说话」的打包配置，采样参数加提示词结构；四层生效顺序是会话、角色、全局、内置默认，越贴近这局越优先；最后给挑预设的三个问题和四个社区大部头的实数。
- 酒馆群聊怎么玩才好玩？搭班子指南：请谁进群、怎么配戏才不冷场: https://foreverse.cn/zh/blog/group-chat-casting-guide — 四张喜欢的卡拉进同一个群，结果一个人刷屏、三个人装雕塑——问题多半出在选角。这篇从运营视角讲群聊：放几个角色合适、四个功能位怎么配、话痨值怎么用、一个全员高冷的失败班底为什么必然冷场，以及每位发言背后的成本账。
- Quick Reply 自动化玩法：把每次都要敲的那句话做成一颗按钮: https://foreverse.cn/zh/blog/quick-reply-automation-guide — 酒馆的 Quick Reply（自动按钮）是把重复劳动钉成按钮的机关：一键剧情总结、换景模板、无声导演批注、AI 回复后自动计数，四个可直接照抄的配方。按钮内容以 / 开头就是 STscript，手机端跑的是桌面同源的命令子集，不认识的命令安全跳过；四档自动化模式加死循环检测兜底，脚本里只有触发生成的步骤才花钱。
- 酒馆正则入门：它改的是显示还是历史？第一次用先分清这个: https://foreverse.cn/zh/blog/regex-scripts-for-beginners — 酒馆正则就是自动跑的查找替换：藏思考链、去 OOC 旁注、把状态栏 marker 换成美化界面，全是它。但第一次用之前要分清三档执行时机——「双向」在消息写进记录前就替换、改动是永久的；「仅显示」只改你看到的；「仅提示词」只改模型看到的。这篇玩家向教程带四步上手：导入带正则的卡、认时机、从模板建第一条、出问题单条排查。
- 世界书递归是什么？触发链、深度限制与一次失控案例: https://foreverse.cn/zh/blog/lorebook-recursion-explained — 「为什么加了一条设定，好几条一起冒出来？」这是世界书递归扫描在干活：已命中词条的正文也被当作扫描源，词条可以召唤词条。这篇机制说明书讲清链条怎么走、在哪停（层数、预算、去重三道闸）、三个词条级开关各管什么，附一个五条连锁的可复现失控案例和两件自带的验证工具。
- 睡前听书方案：定时关闭、音色、缓存和不吵醒室友的细节: https://foreverse.cn/zh/blog/bedtime-listening-setup — 睡前听小说的完整设置清单：睡眠定时 15/30/60/90 分钟四档怎么选、深夜听不吓人的音色和语速搭配、提前缓存整章防半夜断网、锁屏通知栏控制和不吵醒室友的细节，外加「听到哪明早从哪读」的进度接力。免费系统 TTS 就能起步，全部步骤按关灯前五分钟的顺序排好。
- token 是什么？给只想看小说的人算一笔账: https://foreverse.cn/zh/blog/token-explained-for-readers — token 是 AI 读写文字的计量单位，也是计费单位。我们拿一章 3065 字的真实网文实算：不同家的分词器数出 1800 到 4200 个 token 不等，约合一个汉字 0.6 到 1.4 个 token。这篇全程用「章、段、几分钱」当单位，把「续写一段为什么只要一分多钱」「缓存为什么能打到零头价」算到你能核对的粒度。
- 2026 年免费用 AI 续写小说的四条路，各自的天花板实测: https://foreverse.cn/zh/blog/free-models-for-continuation-2026 — 2026 年零成本用 AI 续写小说的四条路逐条核实：注册送 5000 积分约 260 段续写；智谱 GLM-4.7-Flash 官方免费调用、Gemini AI Studio 免费层限次不限期；硅基流动实名领 16 元代金券可试旗舰；本地 Ollama 零 API 成本。每条路的真实天花板（额度、限速、机能、文笔）如实标注，附组合走法。
- Grok 能写小说吗？复读实测、适用边界与什么时候别用它: https://foreverse.cn/zh/blog/grok-continue-novel-howto — Grok 4.5 写小说的直答页：360 轮双盲横评里它是唯一在两种文体都掉进复读循环的模型，宫斗场评审一致垫底、二十轮剧情停在案发当日下午。这篇讲清复读为什么不是你的问题、Grok 真正能打的场景、什么时候别用它，附 2026 年 7 月核实的 xAI 牌价与国内接入现状。
- 智谱 GLM 续写小说：唯一双文体都进前三的模型，和它的半角引号顽疾: https://foreverse.cn/zh/blog/glm-continue-novel-howto — 智谱 GLM 5.2 是我们两场双盲横评（890 万字传统玄幻 + 《甄嬛传》宫斗古言）里唯一双榜都进前三的模型，代价是跨文体复现的半角引号顽疾：玄幻场 20 轮 108 处，宫斗场原样复发。这篇按一次完整开书流程走：bigmodel.cn 实名建 Key、免费档 GLM-4.7-Flash 试笔、旗舰 5.2 正式续写、撞上引号后的三层绕行，附 2026 年 7 月核实牌价。
- Kimi 续写小说实测：长上下文是真优势还是伪需求: https://foreverse.cn/zh/blog/kimi-continue-novel-howto — Kimi K2.6 的 256K 上下文是真能力，「窗口大就续得像」是伪推论：九模型《甄嬛传》双盲横评它排 5-7 名，评语「越写越收敛」与窗口无关；4k 到 20 万 token 的五档对照实验证明，整本塞入不加指令照样比喻密度 10 倍于原著，且每段按全书输入计费。附 2026 年 7 月官方牌价（输入 ¥6.5/百万 token）、接入步骤与长上下文真正适用的场景清单。
- Gemini 续写小说实测：免费档能白嫖到什么程度，短板在哪: https://foreverse.cn/zh/blog/gemini-continue-novel-howto — AI Studio 免费档 2026 年 7 月核实：Flash 级每分钟约 10-15 次、每天数百到一千多次请求，长期有效不用绑卡；但免费层只覆盖 Flash 级，我们双盲横评排名的是付费层的 Gemini 3.1 Pro——玄幻场曾因一句标注措辞 20 轮全部重写开场，措辞修复后甄嬛传场回到 4-6 名。这篇把「免费」和「能打」两笔账分开算，附拿 Key 与接进手机阅读器的步骤。
- Claude 怎么续写小说？从网页版长度天花板到 API 接进手机阅读器: https://foreverse.cn/zh/blog/claude-continue-novel-howto — 想用 Claude 续写手机里的小说：claude.ai 的 Projects 大书自动切检索模式、写出的段落散在会话里，续写要走 API。这篇给四步教程：console.anthropic.com 开户建 Key、填进 BYOK 阅读器、设默认模型、第一段续写落分支；附 2026 年 7 月官方牌价折算（Opus 一段约五毛钱）与双盲横评里 Claude 的真实名次。
- 我们把角色卡创作 Skill、47 份分类指南和 AI 味检测器全部开源了: https://foreverse.cn/zh/blog/open-sourcing-character-card-skills — character-card-skills 仓库上线：两个 agent skill（写卡 + 聊后调优）、47 份分类创作指南、15 张过检测的原创卡（酒馆可直接导入的 v2 JSON + v3 PNG 嵌卡都给了），以及那个在 LLM 评委 gold 正确率只有 12% 之后、按真实读者判断校准出来的规则版 AI 味检测器。代码 MIT，内容 CC BY 4.0。Claude Code、Cursor、Codex 都能跑，在 Foreverse 安卓端是内置的。
- We Open-Sourced Our Character Card Authoring Skills, 47 Genre Playbooks and the AI-Flavor Detector: https://foreverse.cn/blog/open-sourcing-character-card-skills — character-card-skills is live: two agent skills (card authoring + chat-quality triage), 47 genre playbooks, 15 original cards shipped as SillyTavern-ready v2 JSON and v3 PNG, and the rule-based AI-flavor detector we calibrated after our LLM judges failed gold calibration at 12%. Code MIT, content CC BY 4.0. Runs in Claude Code, Cursor, Codex, Gemini CLI — and natively in Foreverse on Android.
- Continue Sherlock Holmes With AI: The Pastiche Tradition Goes Personal: https://foreverse.cn/blog/continue-sherlock-holmes-with-ai — Sherlock Holmes has been continued by other hands since the 1890s — thousands of pastiches, an estate-endorsed novel, 250+ screen portrayals. Since January 1, 2023 the entire canon is public domain in the US. A practical guide: where to get the source text (Project Gutenberg), why Watson's voice is a natural style anchor, what long-run failures to expect from real 360-round data, and how branching handles the Reichenbach what-if.
- Story Continuation Prompts That Survive Long Runs: Field Notes and Four Copy-Ready Templates: https://foreverse.cn/blog/story-continuation-prompting-guide — Bare 'continue this' prompts decay measurably over consecutive rounds — we have the 20-round benchmark data. These field notes split the working prompt into an instruction layer and a material layer, explain the continuity directive that took one model from 20/20 restart loops to 0/20, and include four copy-ready English templates (fast action, interior-emotional, suspense, literary restraint), each with banned-phrase lists and a note on when to use it.
- The Author Dropped the Novel Two Years Ago. Here's How I Finished It for Myself With AI: https://foreverse.cn/blog/finish-a-dropped-novel-with-ai — A web serial I followed went silent in 2024 at chapter 214, mid-scene. This is the actual workflow I used to give it an ending nobody else will ever read: getting the text out as a txt file, picking the real last-good chapter, growing the continuation on a branch so the original stays byte-for-byte intact — plus the honest part about style drift over long runs, and what happens if the author ever comes back.
- What AI Story Continuation Costs: No Subscription, Three Routes, the Actual Math: https://foreverse.cn/blog/what-ai-continuation-costs — One continuation measured about 19 credits — $0.0019 — on Foreverse's official channel. This ledger prices all three routes (5,000 free starter credits, pay-as-you-go packs from $0.99, BYOK at provider list price), works out what a 200,000-word ride costs on each, and runs the honest comparison against a $19/month writing subscription. Includes the 50% service-fee disclosure and when BYOK is the better deal.
- Is It Legal to Continue Someone Else's Novel With AI for Personal Use? Fair Use, the Sequel Cases, and the Private-Use Line: https://foreverse.cn/blog/ai-continuation-copyright-fair-use — A private AI continuation you never share and a continuation you post or sell sit in different risk classes under US copyright law. This explainer walks the 17 U.S.C. §107 fair use factors, what Salinger v. Colting and Anderson v. Stallone actually decided, why the AI training lawsuits are a different fight from your personal use, and a plain do/don't checklist. Background information, not legal advice.
- Import Character Cards by URL: chub, JanitorAI, and Four More Sources Tested: https://foreverse.cn/blog/import-character-cards-by-url — Foreverse now imports character cards straight from pasted links: chub.ai, JanitorAI, Pygmalion, RisuRealm, AICC, plus public png/json/charx file URLs. A site-by-site test log — what the links look like, what comes through, where each source bites, and the honest limits.
- Where Your Novels Actually Live: A Data-Boundary Walkthrough: https://foreverse.cn/blog/where-your-novels-actually-live — Imported books, continuation branches, BYOK keys, chat logs, character cards — where each one is stored, who can read it, how to back it up, how to delete it. Answered item by item, including the thing we don't have yet: automatic cloud sync.
- Which LLM Continues a Novel Best? Nine Models, Two Genres, Blind-Judged: https://foreverse.cn/blog/best-model-for-continuing-novels — Nine LLMs each continued two Chinese novels for 20 consecutive rounds — 360 rounds total, ranked by double-blind review. DeepSeek V4 Flash won the fantasy epic; DeepSeek V4 Pro and GPT-5.6 Terra took the top tier on the palace-intrigue novel; the fantasy champion dropped to sixth on the second book. Full ranking tables, a checklist of three long-run failure modes, and how to actually use the results.
- 和 AI 谈恋爱正常吗？一个做 AI 伴侣功能的团队的立场: https://foreverse.cn/zh/blog/loving-an-ai-our-take — 72% 的美国青少年用过 AI 伴侣，Replika 一次功能下线曾让论坛版主贴出自杀干预资源。我们是做这个功能的团队，摆三条立场：这是真实的情感体验不是病，但替代不了线下的支持系统；依恋是强力杠杆，做产品的人有责任不拿它换日活；数据主权是情感主权的一部分，记忆存在你手机里，关系才没收不走。有些问题我们也没想清楚，一并写在里面。
- 用 AI 续写《红楼梦》会怎样？从两百年续书公案，到你自己的第八十一回: https://foreverse.cn/zh/blog/continue-hongloumeng-with-ai — 《红楼梦》后四十回是人类史上最著名的续写公案：高鹗背了一百年骂名，2008 年人民文学出版社把署名改成「无名氏续」。今天你可以在手机上自己下场：公版全本哪里找、断点选第八十回末还是黛玉焚稿前、哪些模型接得住典雅书面语（甄嬛传九模型横评的真实数据）、怎么用分支让「黛玉不死线」和「宝钗视角线」并存。
- 一条链接把角色卡搬进手机：chub、JanitorAI 等六源导入实测: https://foreverse.cn/zh/blog/import-cards-by-url — chub.ai、JanitorAI、Pygmalion、RisuRealm、AICC 和公开文件直链，六个来源的角色卡链接现在都能粘贴直接导入。这篇按站记录：链接长什么样、导进来带什么、每站的坑，以及导入失败的常见原因。
- 你的小说存在哪里？Foreverse 数据边界一页说清: https://foreverse.cn/zh/blog/where-your-novels-live — 导入的书、续写分支、BYOK Key、聊天记录、角色卡各存在哪里、谁能看到、怎么备份怎么删，逐项直答；也如实写了我们还没有的东西：自动云同步。
- AI 写小说软件排行看不懂？先分清作者向和读者向两个物种: https://foreverse.cn/zh/blog/reader-tools-vs-writer-tools — 搜「AI 续写工具推荐」会拿到一堆大纲生成、伏笔管理、日更产能的作者向工具（笔灵、岱宗、蛙趣、解忧笔札），但很多搜续写的人其实是读者：想把手机里那本书接着写下去、写给自己看。这篇观点专栏把两个赛道劈开讲清楚，逐家陈述可核实定位、不打分不排名，文末附「你是哪派」三问自测。
- 怎么让 AI 写同人不 OOC？把人设崩拆成三种病因，各有各的治法: https://foreverse.cn/zh/blog/fanfic-anti-ooc-method — AI 写同人人设崩（OOC）有三种不同病因：模型没见过原作人设（治法是结构化角色卡）、设定超出上下文窗口（治法是世界书按相关性注入）、长跑文风漂移（治法是来源标注，附 20 轮实验数据）。用一条师徒 CP if 线做贯穿案例，把三味药的用法和用量写清楚。
- DeepSeek 怎么续写小说？从网页版贴不下，到 API 接进手机阅读器: https://foreverse.cn/zh/blog/deepseek-continue-novel-howto — 想用 DeepSeek 续写手机里的小说，会依次撞到三堵墙：网页版聊天框贴不下一本书；API 要去 platform.deepseek.com 开通（注册、建 Key、充值三步）；拿到 Key 还得接进能装下整本书的阅读器。这篇按墙给做法，附 2026 年 7 月官方牌价、峰谷定价窗口和模型名迁移提醒。
- 乙女游戏玩腻了？想要不抽卡、剧情自由的纸片人恋爱，2026 年有这四派: https://foreverse.cn/zh/blog/beyond-otome-free-roleplay — 写给玩腻了卡池、混池和排期表的乙游玩家：把 2026 年「和纸片人谈恋爱」的四种形态摊开对比，长线运营乙游、星野猫箱系平台、酒馆角色卡、AI 伴侣，各自给了什么、收走了什么，以及自由度和所有权到底值多少。
- 酒馆是什么？SillyTavern 新手入门：角色卡、世界书、第一次开聊一篇讲明白: https://foreverse.cn/zh/blog/tavern-beginners-guide — 「酒馆」是 SillyTavern 的中文圈昵称。这篇新手教程把黑话一次讲明白：酒馆的来历、角色卡和世界书是什么、「破限」该怎么看待，以及不用电脑、在手机上四步跑通第一次角色扮演对话。
- txt 小说转有声书 App 哪个好？2026 年四条路线横评（含全免费方案）: https://foreverse.cn/zh/blog/txt-to-audiobook-apps-2026 — 手里的 txt 小说想转成有声书听？横评 2026 年四条主流路线：番茄系平台朗读、静读天下+MultiTTS、开源阅读 Legado+在线 TTS、阅读器自带 AI 听书，音色上限、缓存、成本、书源自由度逐项对比，含全免费方案。
- iPhone 怎么玩酒馆？苹果手机 AI 续写小说现有的三条路，和一条在路上的: https://foreverse.cn/zh/blog/iphone-tavern-and-continuation — iPhone 上玩 SillyTavern 酒馆的三条真实路线（云端酒馆、家里电脑局域网、App Store 原生 App）逐条核实代价；AI 续写小说在 iOS 的现状，以及 Foreverse iOS 版的诚实进度：Android 已上架 Google Play，iOS 内测报名中。
- AI 续写小说用哪个模型？九个大模型 × 两种文体实测排名（双盲评审）: https://foreverse.cn/zh/blog/which-model-continues-novels — 九个大模型在玄幻与宫斗古言两种文体上各连续续写 20 轮、累计 360 轮，双盲评审排名：玄幻第一 DeepSeek V4 Flash，古言第一梯队 DeepSeek V4 Pro 与 GPT-5.6 Terra，两张榜的冠军互不重叠。附完整排名表、三种长跑失效模式避坑清单、按文体选模型的实际用法。
- AI 续写小说提示词怎么写？23 个官方模板按场景挑，可直接抄: https://foreverse.cn/zh/blog/continuation-prompt-templates — 裸的「接着写」会让 AI 写成温吞的平均网文腔。这篇按场景拆 Foreverse 已上架的 23 个官方提示词模板：快节奏网文、细腻情感、悬疑张力、古风雅意的关键段落原文节选，每张标注什么时候用；外加一节讲清模板管不了的文风漂移要靠什么解决。
- AI 续写小说要花多少钱？免费额度、按量积分、自带 Key 三条路算清楚: https://foreverse.cn/zh/blog/ai-continuation-cost — 在 Foreverse 用官方渠道续写一段实测约 19 credits，折合人民币一分多钱；注册送 5000 credits 约够 260 段、8 到 13 万字。这篇把免费额度、按量买积分、BYOK 自带 Key 三条路的单价、总价和适用人群逐项算清，附 DeepSeek 官方牌价算例和学生党零成本走法。
- 用 AI 续写别人的小说算侵权吗？只写给自己看的法律边界: https://foreverse.cn/zh/blog/ai-continuation-copyright-personal — 把小说喂给 AI 续写、只自己看，和把续写发到网上、拿去变现，是两个相差很远的风险等级。这篇整理《著作权法》第二十四条合理使用条款、金庸诉江南案、AI 文生图案与奥特曼案的判决脉络，给出一份可对照的行为自查清单。信息整理，不构成法律意见。
- 彩云小梦还能用吗？还想「接着写下去」的人，2026 年有哪些选择: https://foreverse.cn/zh/blog/after-caiyun-xiaomeng — 2021 年 9 月彩云小梦上线，三选一续写和平行世界让一代人第一次玩到「AI 接着写」。截至 2026-07 它还在架、还在更新，只是热度早已散场。这篇按时间线捋一遍这五年，再诚实回答：轻量玩留在小梦就好；手机里存着整本 txt、想长期写、想自己挑模型的人，需求已经长到了下一代工具上。
- 追的小说断更了怎么办？一份等更党生存指南（含新玩法）: https://foreverse.cn/zh/blog/hiatus-survival-ai-branches — 追的书断更了、作者疑似太监，除了重读、找平替、蹲作者微博，还有第四个选择：把 txt 导进阅读器，从断更那章开分支让 AI 先替作者写着；正版复更了回主线接着看，AI 版留作 if 线，原文一个字不被污染。
- 小说烂尾了怎么办？忍、找同人，或者自己写一个结局: https://foreverse.cn/zh/blog/novel-bad-ending-write-your-own — 烂尾几乎不可逆：日更行规下，作者极少回头重写结局。可走的路有三条：接受、找同人、自己续。这篇讲第三条怎么走通——把 txt 导进手机，回翻到还没崩的那一章，从那里开分支让 AI 接着写；原文一个字不动，写崩了砍掉分支重来。
- Three Ways LLMs Fail at Long Fiction: Restart Loops, Mid-Run Freezes, and Ending Rewinds: https://foreverse.cn/blog/three-ways-llms-fail-long-fiction — Nine models (GPT-5.6 Terra, Grok 4.5, Kimi K2.6, Claude Opus 4.8, Gemini 3.1 Pro, DeepSeek V4 ×2, Qwen 3.7 Max, GLM 5.2) each continued two Chinese novels for 20 consecutive rounds. Every long-run failure we observed fits one of three patterns — and the most interesting one hit the model with the best prose mimicry in the field.
- Six LLMs Continue the Same Webnovel. A Blind Review Picks the Most Faithful — 120 Rounds of Data: https://foreverse.cn/blog/which-model-clones-your-novel-style — DeepSeek V4 Pro/Flash, Claude Opus 4.8, Gemini 3.1 Pro, Qwen 3.7 Max and GLM 5.2 each continued an 8.9M-character Chinese fantasy novel from the same anchor point, 20 rounds each, output fed back into context. Double-blind review ranked the results. The winner isn't the most expensive model; one model rewrote the same opening paragraph 20 times; another aced every statistical metric and still placed fifth.
- 九个大模型续写《甄嬛传》，双盲评审谁最像流潋紫——GPT-5.6、DeepSeek、Grok 全下场: https://foreverse.cn/zh/blog/nine-llms-continue-zhenhuan — GPT-5.6 Terra、Grok 4.5、Kimi K2.6、DeepSeek V4 双档、Claude Opus 4.8、Gemini 3.1 Pro、Qwen 3.7 Max、GLM 5.2，从甄嬛传同一个宫斗高潮各自连续续写 20 轮，双盲评审排名。宫斗文冠军和玄幻冠军不是同一个模型；有模型二十轮剧情停在案发当日；还有模型写着写着暴露了它记的是电视剧不是小说。
- AI 续写为什么越写越不像原著？我们跑了 60 条 20 轮的链找答案: https://foreverse.cn/zh/blog/ai-continuation-style-drift — AI 续写第一段很像原著，第十段开始「翻译腔」，第二十段像换了个作者——这不是错觉。我们用一本 890 万字的玄幻书做了组对照实验：裸提示词的链 20 轮后句式持续均匀化、比喻堆叠、意象自我复读；给上下文标注「哪段是原著、哪段是 AI 写的」再配一句基准声明，漂移显著放缓，甚至出现越写越像的反向曲线。
- 六个大模型续写同一本网文，谁最像原著？——120 轮实测 + 双盲评审: https://foreverse.cn/zh/blog/which-model-clones-your-novel-style — 拿一本 890 万字的传统玄幻《踏天境》，让 DeepSeek V4 Pro/Flash、Claude Opus 4.8、Gemini 3.1 Pro、Qwen 3.7 Max、GLM 5.2 从同一个位置各自连续续写 20 轮，再做双盲评审排名。第一名不是最贵的那个；有一个模型 20 轮都在重写同一段开场；还有一个模型句长统计几乎完美、盲评却排第五。完整数据和方法都在这篇。
- We Dumped 315 Real Novels Into a Phone Reader, Then Opened Ten at Random: https://foreverse.cn/blog/315-books-in-8-seconds — We loaded a real phone-storage snapshot onto a vivo foldable, select-all imported the 315 webnovel txt files it scanned out (about 1GB), and clocked batch ingestion at roughly 8 seconds. Ten random books all opened clean; system frame stats over 71,320 frames showed 0.49% jank. Full methodology and numbers from two real devices — including the data-safety bug this test caught and we fixed.
- Your Books, Your Cards, Your Chats — As Files: https://foreverse.cn/blog/your-worlds-are-files — Every app claims your data is yours; the storage architecture decides whether it's true. Foreverse's version: each world is a directory on your device, character cards are standard chara_card_v3 files, lorebooks are JSON, a companion packs into a moving-box zip, community imports carry provenance records, and AI-generated images get machine-readable origin marks. Here is the file-first architecture laid open — costs included.
- A Tour of the Plugin Center: Desktop Tavern Extensions, Rebuilt for a Phone's Budget: https://foreverse.cn/blog/tavern-plugin-center-tour — Memory, auto-summary, story choices, state tracking, stepped thinking, lorebook suggestions, reply ideas — the extension powers desktop tavern players rely on, built into Foreverse as a plugin center. A walkthrough of what each plugin does and costs, plus the three disciplines we hold: every side-request is itemized in your billing log, every turn has a call budget, and tapping a choice never sends on your behalf.
- The Real Problem in AI Group Chat: Who Speaks Next?: https://foreverse.cn/blog/who-speaks-next-group-chat — Single-character AI chat is a solved genre. Group roleplay's hard problem lives elsewhere: turn-taking. Mentions must be answered, talkative characters should talk, silence needs a fallback, and nobody gets to spam the table. How we brought desktop-tavern group chat to a phone: the three-tier natural arbitration, four speaking strategies, three card-injection modes, and an auto mode that lets the scene run itself.
- How Character-Card Beautification Survives on a Phone: https://foreverse.cn/blog/card-beautify-on-phones — The tavern community's most vibrant craft is beautification: status bars, themed chat skins, interactive choice menus, all built from regex scripts and HTML. That ecosystem grew up inside desktop browsers. Here is how it renders on a phone in Foreverse: the marker-to-regex-to-WebView pipeline, the sandbox rules that break desktop habits, and why beautify code costs zero context tokens.
- An AI Agent That Lives on Your Bookshelf: Five Tasks, Logged (Including One Self-Repair): https://foreverse.cn/blog/an-agent-on-your-bookshelf — Foreverse ships an in-app agent that does real work: your novels, character cards, and lorebooks are files it can read and write. Task logs from development: a 121-round chained treasure hunt (60/60 found), growing a lorebook out of a novel, forking a card from the library and starting a chat, shopping the community on your behalf — and the moment a failed edit fed its error back and the agent fixed itself.
- Where Should Memory Go in a Roleplay Prompt? Our First Answer Was a Caching Artifact: https://foreverse.cn/blog/where-to-inject-roleplay-memory — For long-term roleplay memory, injection position decides both your cache bill and whether memory works at all. A 24-round experiment told us to append a system block after chat history (94.3% cache hits). A 400-round rerun three weeks later overturned it: DeepSeek's template merges every system message to the top of the prompt, and that 94.3% was cache pollution. Full data inside — seven retrieval strategies, leak detection, and the abstention failure that worries us more than retrieval.
- 怎么给「AI 味」写单元测试：一个规则检测器的校准记录: https://foreverse.cn/zh/blog/unit-testing-ai-flavor — 我们给角色卡文案做了一个规则检测器：套话词表加句式配额，用来拦截「一眼 AI」的官方文案。这篇是它的校准记录：金标判例集第一次跑就抓出检测器误杀人类（人类热门卡均分 4.55 低于 AI 的 4.90）、单词黑名单为什么必须降级成句式检测、以及它永远抓不到的那类 AI 味。附一个免费的浏览器版工具。
- 你的书、你的卡、你的聊天记录，都是文件: https://foreverse.cn/zh/blog/your-worlds-are-files — 「数据是你的」谁都会说，兑现要看存储架构。Foreverse 的写法：每个世界一个目录，角色卡是 chara_card_v3 标准文件，世界书是 JSON，伴侣可以打成搬家包整包带走，社区导入的内容带溯源记录，AI 生成的图片写入可读的来源标记。这篇把这套文件化架构摊开讲，包括它的代价。
- 插件中心导览：把桌面酒馆的扩展生态过一遍手机的安检: https://foreverse.cn/zh/blog/tavern-plugin-center-tour — 记忆、自动摘要、剧情选项、状态追踪、先想后答、世界书推荐、回复灵感……桌面酒馆玩家熟悉的扩展能力，在 Foreverse 里以插件中心的形式内置。这篇逐个过：每个插件干什么、多花多少钱、以及三条我们坚持的设计纪律：副请求全部记账可查、每轮调用有预算上限、点选项永远不替你直发。
- AI 群聊真正的难题：下一句该谁说？: https://foreverse.cn/zh/blog/who-speaks-next-group-chat — 单人角色聊天已经很成熟，群聊的难点在另一处：轮到谁说话。点名要接住、话痨该多说、冷场要有人兜底、还不能让同一张嘴连续刷屏。这篇讲我们在手机上实现桌面酒馆群聊的完整方案：自然轮替的三层裁决、四种发言策略、角色卡的三种注入方式、以及自动模式让戏自己演下去。
- 酒馆美化包在手机上是怎么活下来的：给创作者的一封技术信: https://foreverse.cn/zh/blog/card-beautify-on-phones — 美化是中文酒馆社区最有生命力的手艺：状态栏、可折叠思维链、主题化聊天皮肤，全靠正则和 HTML 搭出来。但这套生态默认长在桌面浏览器里。这封信写给美化创作者：你的卡在 Foreverse 手机端怎么渲染、marker→正则→WebView 三段链路各自的规矩、哪些桌面习惯会翻车、以及美化代码为什么不吃你的 token。
- 把 Agent 放进书架：五个任务的实录，含一次自我纠错: https://foreverse.cn/zh/blog/an-agent-on-your-bookshelf — Foreverse 内置了一个真的会干活的 Agent：你的小说、角色卡、世界书对它来说都是可读写的文件。这篇是开发期的任务实录：121 轮连环寻宝压力测试（60/60 全中）、从一本书里长出世界书、fork 一张库里的卡再开聊、替你逛社区选卡代下载，以及一次工具调用失败后它自己把自己修好的现场。
- 记忆块该插在 Prompt 哪里？我们的第一个结论是缓存假象: https://foreverse.cn/zh/blog/where-to-inject-roleplay-memory — 给角色扮演做长期记忆，注入位置直接决定缓存账单和记忆生效率。我们先在 24 轮实验里得出「历史末尾插 system 块」的结论（缓存命中 94.3%），三周后被 400 轮实验推翻：DeepSeek 的模板会把所有 system 消息归并到开头，那个 94.3% 是缓存污染的假象。这篇公开完整数据：七种检索策略、泄漏检测、以及比检索更要命的「弃权灾难」。
- The Day Your AI Companion Sends a Selfie — and Why the Face Is the Hard Part: https://foreverse.cn/blog/the-day-they-sent-a-selfie — The hard part of AI companion selfies isn't generating a pretty image — it's the fiftieth image still reading as the same person. How the visual identity system works: user-confirmed reference sets, why generated images never auto-promote, how two-person photos guard both faces, and exactly where your uploaded photo goes (in memory only, to the image provider you chose — the app never stores it).
- Our LLM Judges Called Human Writing AI-Flavored 88% of the Time: https://foreverse.cn/blog/llm-judges-called-humans-ai — We ran a double-blind panel: four heterogeneous LLM judges, gold anchors labeled by real humans, both presentation orders. Gold accuracy came back at 12% — the judges systematically inverted, calling million-conversation human hits “AI” and the copy a real user flagged as AI “human.” Inter-judge agreement was 86%, and they agreed on the wrong answer. Full failure data and the rule we adopted.
- Characters Shouldn't Die When the Book Ends — an Opinion on Where AI Roleplay Went Wrong: https://foreverse.cn/blog/characters-shouldnt-die — An opinion column: chat platforms gave AI characters a room but no biography — no origin, no stage, no future. Why the chat box is a dead end for character attachment, and what it looks like when one character can live on the page, on a stage, across the table, and by your side, carrying the same setting and visual identity.
- We Added a Game Mode to an E-Reader. Here's the Design Decision That Made It Work: https://foreverse.cn/blog/first-reader-with-game-mode — VN Theater turns any novel on your shelf into a visual-novel performance mid-read — no conversion, no separate project, one shared reading position. A builder's note on the single design decision everything hangs on, why we refused to guess who's speaking, and what a choice made on stage does to the book.
- TA 第一次给你发自拍：AI 伴侣的脸是怎么固定下来的: https://foreverse.cn/zh/blog/the-day-they-sent-a-selfie — AI 伴侣发自拍最难的不是生成图，是「第五十张还认得出是同一个人」。这篇讲清视觉档案的工作方式：参考图集为什么必须由你亲手确认、生成的图为什么不自动混进参考集、合照怎么压低换脸风险，以及你的照片在这个过程里去了哪（答案：只以内存态发给你自己选的图像模型，App 这边不落盘不留档）。
- 我们的 LLM 评委，把人类写的文字判成了 AI——88% 的时候: https://foreverse.cn/zh/blog/llm-judges-called-humans-ai — 一次双盲评审实验的完整数据：4 个异构大模型评委、真人标注的金标锚点、双顺序对照。结果 gold 正确率只有 12%——评委们一致地把人类热门作品判成 AI、把被真实用户吐槽「一眼 AI」的文案判成真人。评委间一致率 86%，但一致地错。这篇公开实验设计、翻车数据和我们最后立下的铁律。
- 一个角色的四种活法：纸上、台上、对面、身边: https://foreverse.cn/zh/blog/character-four-lives — 同一个角色在 Foreverse 里有四种活法：在书页里被续写（纸上）、在剧场里亲口演出（台上）、带着完整设定和你对话（对面）、升格成有记忆会主动发消息的伴侣（身边）。这篇顺着一个角色走完全程，讲清每一步之间的数据是怎么真实连通的，以及哪一步我们明确没做。
- 315 本 txt 一次全选导入：一台真机的阅读器性能账本: https://foreverse.cn/zh/blog/315-books-in-8-seconds — 拿一台 vivo 折叠屏真机灌入真实手机存储快照，把扫出的 315 本网文 txt 一次性全选导入，批量入库约 8 秒；随机进 10 本书全部正常打开，7 万多帧渲染统计卡顿率 0.49%。这篇公开完整测法和两台真机的数字，包括我们在测试里修掉的一个数据安全隐患。
- AI 怎么知道这句话是谁说的？说话人归因的五个坑: https://foreverse.cn/zh/blog/who-said-that — 把小说演成视觉小说，第一关是给每句引语找到说话人。这篇拆解说话人归因的五个真实案例：后置说话从句、受话人陷阱、交替对话的边界、句号归属，以及为什么我们最终选择「宁可放旁白，不冒错认的险」。含真书人工标注的核对结果。
- 把书架上的小说一键开成文字游戏：剧场模式实测记录: https://foreverse.cn/zh/blog/novel-to-visual-novel — 把正在读的小说一键切成视觉小说演出：逐字台词、说话人名牌、AI 场景背景、剧情选择肢。这篇是剧场模式在两本书上的完整实测记录——包括它怎么做到不转换、不丢进度、选出来的剧情真实写回书里，以及我们在「谁在说话」这个问题上交过的学费。
- Writing Fanfiction With AI: What Actually Works, From a Reader's Request: https://foreverse.cn/blog/ai-fanfiction-honestly — Someone on our waitlist asked for TGCF-style fanfiction support. An honest assessment: where AI fanfic quality actually stands, how to feed canon so characters stay in character, why branching solves the three-endings problem, and the problems (voice drift, OOC, platform disclosure rules) that no tool has solved.
- 用 AI 写同人文靠谱吗？回答一位想续写耽美同人的等待名单用户: https://foreverse.cn/zh/blog/write-fanfic-with-ai — 等待名单里一位用户留言想用 AI 写 TGCF 式的耽美同人。这篇认真回答：AI 写同人的真实水平在哪、原作人设怎么喂给模型才不崩、分支怎么解决「一个梗想写三个走向」、以及哪些坑（OOC、文风飘、审查尺度）现阶段绕不开。
- AI Token 真的越来越便宜吗？看完定价数据后我改了自己的用法: https://foreverse.cn/zh/blog/are-ai-tokens-getting-cheaper — a16z 把 LLM 推理降价称作「LLMflation」：同等能力的 token 价格约每年降 10 倍；Epoch AI 的口径甚至更激进。但旗舰模型定价三年没动，推理模型的思考 token 让单次任务更贵。一篇买家视角的定价观察，附我们自己改用法的过程。
- AI Token 缓存为什么越来越重要？一次 60 轮续写实测的账单笔记: https://foreverse.cn/zh/blog/why-prompt-caching-matters — Prompt 缓存（KV Cache）已成为大模型计费的隐形折扣：DeepSeek 缓存命中价约为原价 1/10，Anthropic 缓存读取按 10% 计费，OpenAI 自动打五折。这篇是一份实测笔记：60 轮连续续写的真实账单、命中率从 91% 掉到 0% 的事故现场，和四家供应商的规则差异。
- Prompt Caching Explained: What 60 Continuation Requests Taught Us About LLM Bills: https://foreverse.cn/blog/prompt-caching-explained — Prompt caching is the largest line-item discount in LLM billing: DeepSeek bills cache hits at roughly one-tenth of the miss price, Anthropic reads cost 10% of base input, OpenAI halves repeated prefixes automatically. Notes from a 60-request field test, including the timestamp bug that dropped our hit rate from 91% to zero.
- C.AI 又改规则了？我们陪一位用户把养了八个月的角色搬了家: https://foreverse.cn/zh/blog/cai-refugee-migration-guide — Character.AI 类平台的老问题：过滤收紧、角色下架、记忆变差、数据带不走。这篇是一次真实迁移的过程记录：怎么把平台上的角色重建成 chara_card_v3 角色卡、几千条聊天记录怎么蒸馏成关系档案、BYOK 换模型，以及搬完之后哪些地方不如从前。
- Are AI Tokens Getting Cheaper? The Pricing Data Says Yes and Your Bill Says No: https://foreverse.cn/blog/llm-token-price-trends — a16z calls it LLMflation: the price of a fixed level of LLM capability drops roughly 10x per year, and Epoch AI measures 9-900x depending on the task. Meanwhile frontier list prices have been flat for three years and reasoning tokens inflate per-task cost. A buyer's memo, with the changes we made to our own usage.
- 世界书塞了 237 条设定，AI 还是叫错名字：一次完整的排障记录: https://foreverse.cn/zh/blog/lorebook-writing-guide — 一位创作者的世界书写了 237 条，AI 第三轮就把师父认成仇人。这篇是完整排障记录：从关键词扫描、别名覆盖、token 预算到递归触发，一步步找出四种「无声失效」，顺带得出几条可复用的世界书写法。附症状排查表。
- Turn Any EPUB Into an AI Audiobook: Three Weeks of Commute Testing, Honestly Reported: https://foreverse.cn/blog/epub-to-ai-audiobook — Most books never get an audiobook; studio narration costs thousands of dollars per title. Neural TTS in 2026 is good enough to fix that, so we spent three weeks of commutes listening to a 900-chapter webnovel and wrote down what broke: asterisks read aloud, chapter-boundary stutters, split progress, and what each cost to fix.
- Lorebook Not Triggering? Three Support Tickets and What Fixed Each One: https://foreverse.cn/blog/lorebook-world-info-not-triggering — Three real cases of world info failing without an error message: keywords that never matched, a token budget quietly eaten by one 800-word entry, and a scan window the conversation outran. How World Info injection actually works, what fixed each ticket, plus a symptom table.
- 角色卡导入失败的 9 个原因：PNG、JSON、世界书一次排查清楚: https://foreverse.cn/zh/blog/character-card-import-troubleshooting — 角色卡导入失败 90% 是这 9 个原因：微信压缩抹掉 PNG 隐写、JSON 编码损坏、v1 老卡、改后缀、重名冲突等。附手机端特有的坑和一套 30 秒自检流程。
- How to Run SillyTavern on Android or iPhone in 2026: Termux, Cloud, or Native App: https://foreverse.cn/blog/run-sillytavern-on-android-iphone — Four real ways to get SillyTavern on a phone in 2026 — Termux on Android, a cloud VPS, LAN access to your PC, or a native tavern-style app. Costs, trade-offs, and what survives the migration.
- 2026 年手机玩 SillyTavern 酒馆的四条路：Termux、云端、局域网、原生 App: https://foreverse.cn/zh/blog/sillytavern-on-phone-2026 — 想在安卓或 iPhone 上玩 SillyTavern？这篇把 Termux 本地部署、云端酒馆、局域网访问、原生酒馆 App 四条路线的真实体验、成本和坑一次讲清，附角色卡迁移建议。
- Why Your AI Roleplay Partner Forgets Everything — and What Actually Fixes It: https://foreverse.cn/blog/why-ai-roleplay-chats-forget — AI roleplay memory loss isn't a bug, it's architecture: context windows, summary compression, and platform-owned history. What lorebooks, character cards, and on-device chat libraries actually fix — and what they can't.
- AI 续写小说为什么总把书写崩？我们换了一种结构来解决: https://foreverse.cn/zh/blog/ai-continue-novel-branches — AI 续写小说最大的痛不是文笔是结构：上下文丢失、风格漂移、改了就回不去。这篇讲分支续写的思路——像管理代码版本一样管理剧情线，烂尾文自救的工程化方案。
- Character Card Formats Explained: v1, v2, and chara_card_v3 — What Actually Imports: https://foreverse.cn/blog/character-card-formats-explained — How character cards really work: data hidden in PNG tEXt chunks, what each spec generation added (alternate greetings, character books, v3 assets), why cards break in transit, and a distribution checklist for creators.
- BYOK 不是中转：在手机上自带 API Key 的正确姿势: https://foreverse.cn/zh/blog/byok-on-mobile — 买中转 Key 被跑路、填进网页被盗刷——这篇讲清 BYOK（自带 API Key）的判别标准：密钥是否离开设备、请求是否直连官方、价格是否透明，以及手机端管理多家供应商密钥的实践。
- BYOK, Actually: How to Tell If an App Really Keeps Your API Key on Device: https://foreverse.cn/blog/what-byok-actually-means — BYOK has become a checkbox word. The real definition: your key stays on your device and requests go straight to the provider. Here are the red flags, the three-step verification, and how key storage should work on a phone.
- 通勤路上「听」完 300 万字网文：AI 朗读的实测笔记: https://foreverse.cn/zh/blog/listen-to-webnovels-tts — AI 朗读听网文的真实体验：现代 TTS 和十年前机械音的差距、听书最烦的章节边界和错别字问题怎么处理、流量和缓存的取舍，以及挑选音色的实用建议。
- Rerolling Is Gambling. Branching Is Writing. A Better Way to Use AI on Long Fiction: https://foreverse.cn/blog/branching-beats-rerolling — Why the reroll button quietly ruins AI-assisted fiction: destructive generation, lost alternatives, sunk-cost plotting. Branching — version control for narrative — keeps every draft alive and makes long stories coherent.

## Trust and support
- About Foreverse — Who Builds This and How: https://foreverse.cn/about — Foreverse is built by a small independent team: what we ship, what we test on real devices, how the blog is written, and how to reach us.
- 关于 Foreverse · 新梦 — 谁在做这个产品: https://foreverse.cn/zh/about — Foreverse（新梦）由一个小型独立团队开发：我们在做什么、怎么在真机上测试、博客怎么写成、以及怎么联系我们。
- Changelog — What Shipped in Foreverse: https://foreverse.cn/changelog — A month-by-month record of what actually shipped: VN Theater, the plugin center, group chat parity, visual identity, bulk-import hardening, and the Google Play launch.
- 更新日志 — Foreverse 每个月上了什么: https://foreverse.cn/zh/changelog — 按月记录真实上线的功能：剧场模式、插件中心、群聊、视觉身份、批量导入加固、Google Play 上架。
- AI Flavor Checkup — Rule-Based AI Writing Detector (Chinese): https://foreverse.cn/labs/ai-flavor — Free in-browser AI-flavor detector for Chinese prose: stock-phrase blacklist, sentence-pattern quotas, highlighted hits, 0-5 score. Nothing uploaded.
- AI 味体检 — 中文 AI 文案规则检测小工具: https://foreverse.cn/zh/labs/ai-flavor — 免费在线检测中文文字的 AI 味：套话词表 + 句式配额 + 原文标黄，浏览器本地运行不上传。
- Join the Foreverse iOS Beta — Android Is Live on Google Play: https://foreverse.cn/waitlist — The Android app is live on Google Play. Leave an email for the iOS beta — one short note when it opens, no drip newsletter.
- Foreverse iOS 内测报名 — Android 已上架 Google Play: https://foreverse.cn/zh/waitlist — Android 版已上架 Google Play。留下邮箱，iOS 内测开放时只发一封简短邮件，没有营销轰炸。
- Foreverse Support: https://foreverse.cn/support — Contact Foreverse support for account, privacy, Pro, AI content, BYOK provider, and deletion questions.
- AI Content Policy: https://foreverse.cn/ai-content-policy — Foreverse AI content rules, reporting paths, user responsibilities, and generated-content labeling commitments.
- BYOK AI Providers: https://foreverse.cn/providers — How Foreverse treats bring-your-own-key AI providers, model routing, privacy, and user control.
- Data Export and Deletion: https://foreverse.cn/data-export — How Foreverse handles account data, story exports, deletion requests, and user-controlled local workflows.
- Security and Disclosure: https://foreverse.cn/security — Foreverse security contacts, key handling principles, account protection, and responsible disclosure guidance.

## All public URLs
- https://foreverse.cn/
- https://foreverse.cn/reader
- https://foreverse.cn/zh/reader
- https://foreverse.cn/theater
- https://foreverse.cn/zh/theater
- https://foreverse.cn/roleplay
- https://foreverse.cn/zh/roleplay
- https://foreverse.cn/companion
- https://foreverse.cn/zh/companion
- https://foreverse.cn/multimodal
- https://foreverse.cn/zh/multimodal
- https://foreverse.cn/agent
- https://foreverse.cn/zh/agent
- https://foreverse.cn/byok
- https://foreverse.cn/zh/byok
- https://foreverse.cn/listen
- https://foreverse.cn/zh/listen
- https://foreverse.cn/cards
- https://foreverse.cn/zh/cards
- https://foreverse.cn/byok/providers
- https://foreverse.cn/zh/byok/providers
- https://foreverse.cn/ai-story-continuation
- https://foreverse.cn/zh/ai-story-continuation
- https://foreverse.cn/branching-fiction-writer
- https://foreverse.cn/story-world-organizer
- https://foreverse.cn/byok-ai-writing
- https://foreverse.cn/zh/branching-fiction-writer
- https://foreverse.cn/zh/story-world-organizer
- https://foreverse.cn/zh/byok-ai-writing
- https://foreverse.cn/sillytavern-android
- https://foreverse.cn/zh/sillytavern-android
- https://foreverse.cn/companion-with-memory
- https://foreverse.cn/zh/companion-with-memory
- https://foreverse.cn/companion-texts-first
- https://foreverse.cn/zh/companion-texts-first
- https://foreverse.cn/zh/docs
- https://foreverse.cn/zh/docs/getting-started
- https://foreverse.cn/zh/docs/guide-worlds
- https://foreverse.cn/zh/docs/guide-reader
- https://foreverse.cn/zh/docs/guide-roleplay
- https://foreverse.cn/zh/docs/guide-agent
- https://foreverse.cn/zh/docs/guide-models
- https://foreverse.cn/zh/docs/guide-settings
- https://foreverse.cn/zh/docs/beautify
- https://foreverse.cn/zh/docs/character-cards
- https://foreverse.cn/zh/docs/worldbook
- https://foreverse.cn/zh/docs/glossary
- https://foreverse.cn/zh/docs/themes
- https://foreverse.cn/docs
- https://foreverse.cn/docs/getting-started
- https://foreverse.cn/docs/guide-worlds
- https://foreverse.cn/docs/guide-reader
- https://foreverse.cn/docs/guide-roleplay
- https://foreverse.cn/docs/guide-agent
- https://foreverse.cn/docs/guide-models
- https://foreverse.cn/docs/guide-settings
- https://foreverse.cn/docs/beautify
- https://foreverse.cn/docs/character-cards
- https://foreverse.cn/docs/worldbook
- https://foreverse.cn/docs/glossary
- https://foreverse.cn/docs/themes
- https://foreverse.cn/about
- https://foreverse.cn/zh/about
- https://foreverse.cn/changelog
- https://foreverse.cn/zh/changelog
- https://foreverse.cn/labs/ai-flavor
- https://foreverse.cn/zh/labs/ai-flavor
- https://foreverse.cn/waitlist
- https://foreverse.cn/zh/waitlist
- https://foreverse.cn/support
- https://foreverse.cn/ai-content-policy
- https://foreverse.cn/providers
- https://foreverse.cn/data-export
- https://foreverse.cn/security
- https://foreverse.cn/privacy
- https://foreverse.cn/terms
- https://foreverse.cn/account/delete

Contact: support@foreverse.app