关于 ChatPod Studio

产品定位

ChatPod 从 Studio 开始做图、视频和页面；对话用来聊模型和知识，不是第二条创作首页。用户可以从自然语言描述、参考图片或预设技能开始，并在Studio 工作台中继续编辑和管理生成结果。工作台强调「可见状态」：真实生成、排队中、演示结果与不可用能力应被清楚区分，避免把模拟结果当成线上能力。

ChatPod Studio is an integrated AI creation workbench for images, video, and website concepts. It keeps prompts, references, canvas annotations, and generation history in one place so teams can iterate without jumping across disconnected tools.

主要能力

当前工作流覆盖图片生成、视频生成、网站方案、参考素材管理、画布标注、项目保存与生成历史。设计类技能适合海报、社媒卡片、产品主图和品牌贴纸；视频类技能覆盖分镜、运镜参考与短片节奏探索；网站类能力用于快速形成结构与视觉方向。具体能力取决于部署环境中启用的模型和第三方服务。

Typical scenes include brand design drafts, social content packs, ecommerce visuals, product explainers, creative proposals, and storyboard-driven video exploration. Operators choose which model providers, galleries, and storage backends are available in each deployment.

工作方式

用户通常先在 Studio 首页用一句话或技能模板启动任务，再进入无限画布整理参考、标注重点、并发生成与对比版本。项目可保存以便继续迭代；失败与限流会通过界面反馈，而不是静默重试或伪造成功。需要从参考图切入时，也可从灵感页进入同一套画布。

产品原则

界面应明确区分真实生成、演示结果与不可用功能；涉及外部服务、内容上传和数据处理时，应向用户提供可理解的状态与错误反馈。有关数据范围请阅读隐私说明，使用生成内容前请阅读使用条款。正式运营方还应公布服务商清单、支持渠道与适用地区要求。

Who it is for

Designers, marketers, and small product teams use the workbench to turn a brief into visual drafts quickly: campaign stills, short-form video boards, landing-page concepts, and reusable reference boards. The goal is not to replace final art direction or legal review; it is to shorten the path from intent to editable assets that can be compared, annotated, and handed off.

If you already chat with models in ChatPod, this surface is where you ship visuals. Conversation remains the place for research and Q&A; generation, canvas layout, and project history live here. Learn more about the broader product entry at chatpod.online.

Before production launch, operators should confirm which models are enabled, how projects are stored, how quotas are enforced, and how users request support or data deletion. Those deployment choices determine the exact experience beyond what this open codebase demonstrates. Keep a short internal runbook for model outages, quota exhaustion, and content-safety escalations so creators are not left guessing when a task fails.

The interface also encourages honest copy: disabled skills should look disabled, mock generation should be labeled, and empty states should explain the next useful action. That clarity is part of the product, not an afterthought for documentation alone. When something fails, the message should help the user retry or switch models instead of hiding the failure behind a spinner.