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feat: update readme (#10)
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README.md

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- Upload large videos (1080p/4K) beyond 8MB with auto compression
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- Support using natural language to make Nova Canvas generate images, remove backgrounds, replace backgrounds, and
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create images in similar styles.
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- Support LaTeX formula rendering for Amazon Nova.
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- Support LaTeX formula rendering (inline and display modes) for Amazon Nova.
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The image below demonstrates SwiftChat rich markdown content support. We redesigned the UI with optimized font sizes and
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line spacing for a more elegant and clean presentation.
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We redesigned the UI with optimized font sizes and line spacing for a more elegant and clean presentation. The image
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below demonstrates SwiftChat rich markdown content support (Paragraph, Code Blocks, Tables, LaTeX and more)
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![](assets/markdown.png)
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- [x] Check detailed token usage and image generation count in Settings
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- [x] In-app upgrade notifications (Android & macOS)
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We have optimized the layout for landscape mode. As shown below, you can comfortably view table and code contents in
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landscape orientation.
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We have optimized the layout for landscape mode. As shown below, you can comfortably view table contents in landscape
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orientation.
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![](assets/landscape.png)
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![](assets/landscape_code.png)
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## What Makes SwiftChat Really "Swift"?
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README_CN.md

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- 支持直接在安卓和 iOS 设备上录制最长 30 秒的视频供 Nova 分析
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- 支持自动压缩上传超过 8MB 的高清视频(1080p/4K)
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- 支持通过自然语言让 Nova Canvas 生成图片,去除背景,替换背景,以及生成类似风格的图片
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- 支持 Amazon Nova 系列渲染 LaTeX 公式
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- 支持 Amazon Nova 系列 LaTeX 公式渲染(行内混排和单独显示模式)
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下图展示了 SwiftChat 支持丰富的 Markdown 内容渲染,其中我们从头设计了 UI,例如字号,行间距。使其展示更加美观简洁。
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其中我们从新设计了 UI,例如字号行间距等,使其展示更加美观简洁。下图展示了 SwiftChat 支持丰富的 Markdown 内容渲染(段落、代码块、表格、LaTeX
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公式等)。
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![](assets/markdown.png)
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你所看到的这些内容都可以在所有支持的平台上以原生 UI 的形式很好的呈现
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你所看到的这些内容都可以在所有支持的平台上以原生 UI 的形式很好地呈现
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## 架构
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- [x] 在设置中查看详细的 token 使用情况和图片生成数量
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- [x] 应用内升级提示(Android 和 macOS)
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我们针对横屏做了相应优化,下图展示了通过横屏模式您可以很好的阅读代码及表格内容
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我们针对横屏做了相应优化,下图展示了通过横屏模式您可以很好地阅读表格内容
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![](assets/landscape_zh.png)
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![](assets/landscape_code_zh.png)
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## 是什么让 SwiftChat 如此"迅速"?
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server/README.md

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## SwiftChat Backend API
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The SwiftChat backend API is implemented using Python language and the FastAPI framework. It is packaged as a Docker image using [aws-lambda-adapter](https://github.com/awslabs/aws-lambda-web-adapter) and deployed to both AWS App Runner and AWS Lambda for execution.
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The SwiftChat backend API is implemented using Python language and the FastAPI framework. It is packaged as a Docker image using [aws-lambda-adapter](https://github.com/awslabs/aws-lambda-web-adapter) and deployed to AWS App Runner or AWS Lambda for execution.
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## API Reference
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