Add awesome webui, update readme. (#1211)

* apply basic typescript webui to the repo (to be modified).

* fix backend bugs.

* fix several bugs.

* change folder name.

* fix name change bugs.

* fix gitignore.

* fix tec report url, remove pdf file.

* Update inference WebUI.

* Update READMEs.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fix jsonc problems.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

README.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -70,14 +70,14 @@ Here are the official documents for Fish Audio S2, follow the instructions to ge
 Install and configure Fish-Audio S2 by following the instructions here: https://speech.fish.audio/install/
 ```
 
-## Fish Audio S2  
-**Best text-to-speech system among both open source and closed source**
+## Fish Audio S2 Pro
+**State-of-the-art multilingual text-to-speech (TTS) system, redefining the boundaries of voice generation.**
 
-Fish Audio S2 is the latest model developed by [Fish Audio](https://fish.audio/). Trained on over 10 million hours of audio across approximately 50 languages, S2 combines reinforcement learning alignment with a Dual-Autoregressive architecture to generate speech that sounds natural, realistic, and emotionally rich.
+Fish Audio S2 Pro is the most advanced multimodal model developed by [Fish Audio](https://fish.audio/). Trained on over **10 million hours** of audio data covering more than **80 languages**, S2 Pro combines a **Dual-Autoregressive (Dual-AR)** architecture with reinforcement learning (RL) alignment to generate speech that is exceptionally natural, realistic, and emotionally rich, leading the competition among both open-source and closed-source systems.
 
-S2 supports fine-grained inline control of prosody and emotion using natural-language tags like `[laugh]`, `[whispers]`, and `[super happy]`, as well as native multi-speaker and multi-turn generation.
+The core strength of S2 Pro lies in its support for **sub-word level** fine-grained control of prosody and emotion using natural language tags (e.g., `[whisper]`, `[excited]`, `[angry]`), while natively supporting multi-speaker and multi-turn conversation generation.
 
-Visit the [Fish Audio website](https://fish.audio/) for live playground. Read the [blog post](https://fish.audio/blog/fish-audio-open-sources-s2/) and [technical report](https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf) for more details.
+Visit the [Fish Audio website](https://fish.audio/) for a live playground, or read our [technical report](https://arxiv.org/abs/2603.08823) and [blog post](https://fish.audio/blog/fish-audio-open-sources-s2/) for more details.
 
 ### Model Variants
 
@@ -108,55 +108,57 @@ On Seed-TTS Eval, S2 achieves the lowest WER among all evaluated models includin
 
 ### Fine-Grained Inline Control via Natural Language
 
-S2 enables localized control over speech generation by embedding natural-language instructions directly at specific word or phrase positions within the text. Rather than relying on a fixed set of predefined tags, S2 accepts free-form textual descriptions — such as `[whisper in small voice]`, `[professional broadcast tone]`, or `[pitch up]` — allowing open-ended expression control at the word level.
+S2 Pro brings unprecedented "soul" to speech. Using simple `[tag]` syntax, you can precisely embed emotional instructions at any position in the text.
+- **15,000+ Unique Tags Supported**: Not limited to fixed presets; S2 supports **free-form text descriptions**. Try `[whisper in small voice]`, `[professional broadcast tone]`, or `[pitch up]`.
+- **Rich Emotion Library**:
+  `[pause]` `[emphasis]` `[laughing]` `[inhale]` `[chuckle]` `[tsk]` `[singing]` `[excited]` `[laughing tone]` `[interrupting]` `[chuckling]` `[excited tone]` `[volume up]` `[echo]` `[angry]` `[low volume]` `[sigh]` `[low voice]` `[whisper]` `[screaming]` `[shouting]` `[loud]` `[surprised]` `[short pause]` `[exhale]` `[delight]` `[panting]` `[audience laughter]` `[with strong accent]` `[volume down]` `[clearing throat]` `[sad]` `[moaning]` `[shocked]`
 
-### Dual-Autoregressive Architecture
+### Innovative Dual-Autoregressive (Dual-AR) Architecture
 
-S2 builds on a decoder-only transformer combined with an RVQ-based audio codec (10 codebooks, ~21 Hz frame rate). The Dual-AR architecture splits generation into two stages:
+S2 Pro adopts a master-slave Dual-AR architecture consisting of a decoder-only transformer and an RVQ audio codec (10 codebooks, ~21 Hz):
 
-- **Slow AR** operates along the time axis and predicts the primary semantic codebook.
-- **Fast AR** generates the remaining 9 residual codebooks at each time step, reconstructing fine-grained acoustic detail.
+- **Slow AR (4B parameters)**: Operates along the time axis, predicting the primary semantic codebook.
+- **Fast AR (400M parameters)**: Generates the remaining 9 residual codebooks at each time step, reconstructing exquisite acoustic details.
 
-This asymmetric design — 4B parameters along the time axis, 400M parameters along the depth axis — keeps inference efficient while preserving audio fidelity.
+This asymmetric design achieves peak audio fidelity while significantly boosting inference speed.
 
-### Reinforcement Learning Alignment
+### Reinforcement Learning (RL) Alignment
 
-S2 uses Group Relative Policy Optimization (GRPO) for post-training alignment. The same models used to filter and annotate training data are directly reused as reward models during RL — eliminating distribution mismatch between pre-training data and post-training objectives. The reward signal combines semantic accuracy, instruction adherence, acoustic preference scoring, and timbre similarity.
+S2 Pro utilizes **Group Relative Policy Optimization (GRPO)** for post-training alignment. We use the same model suite for data cleaning and annotation directly as Reward Models, perfectly resolving the distribution mismatch between pre-training data and post-training objectives.
+- **Multi-Dimensional Reward Signals**: Comprehensively evaluates semantic accuracy, instruction adherence, acoustic preference scoring, and timbre similarity to ensure every second of generated speech feels intuitive to humans.
 
-### Production Streaming via SGLang
+### Extreme Streaming Performance (Powered by SGLang)
 
-Because the Dual-AR architecture is structurally isomorphic to standard autoregressive LLMs, S2 directly inherits all LLM-native serving optimizations from SGLang — including continuous batching, paged KV cache, CUDA graph replay, and RadixAttention-based prefix caching.
+As the Dual-AR architecture is structurally isomorphic to standard LLMs, S2 Pro natively supports all SGLang inference acceleration features, including Continuous Batching, Paged KV Cache, CUDA Graph, and RadixAttention-based Prefix Caching.
 
-On a single NVIDIA H200 GPU:
+**Performance on a single NVIDIA H200 GPU:**
+- **Real-Time Factor (RTF)**: 0.195
+- **Time-to-First-Audio (TTFA)**: ~100 ms
+- **Extreme Throughput**: 3,000+ acoustic tokens/s while maintaining RTF < 0.5
 
-- **Real-Time Factor (RTF):** 0.195
-- **Time-to-first-audio:** ~100 ms
-- **Throughput:** 3,000+ acoustic tokens/s while maintaining RTF below 0.5
+### Robust Multilingual Support
 
-### Multilingual Support
+S2 Pro supports over 80 languages without requiring phonemes or language-specific preprocessing:
 
-S2 supports high-quality multilingual text-to-speech without requiring phonemes or language-specific preprocessing. Including:
-
-**English, Chinese, Japanese, Korean, Arabics, German, French...**
-
-**AND MORE!**
-
-The list is constantly expanding, check [Fish Audio](https://fish.audio/) for the latest releases.
+- **Tier 1**: Japanese (ja), English (en), Chinese (zh)
+- **Tier 2**: Korean (ko), Spanish (es), Portuguese (pt), Arabic (ar), Russian (ru), French (fr), German (de)
+- **Global Coverage**: sv, it, tr, no, nl, cy, eu, ca, da, gl, ta, hu, fi, pl, et, hi, la, ur, th, vi, jw, bn, yo, xsl, cs, sw, nn, he, ms, uk, id, kk, bg, lv, my, tl, sk, ne, fa, af, el, bo, hr, ro, sn, mi, yi, am, be, km, is, az, sd, br, sq, ps, mn, ht, ml, sr, sa, te, ka, bs, pa, lt, kn, si, hy, mr, as, gu, fo, etc.
 
 ### Native Multi-Speaker Generation
 
 <img src="./docs/assets/chattemplate.png" width=200%>
 
-Fish Audio S2 allows users to upload reference audio with multi-speaker, the model will deal with every speaker's feature via `<|speaker:i|>` token. Then you can control the model's performance with the speaker id token, allowing a single generation to include multiple speakers. You no longer need to upload reference audio separately for each speaker.
+Fish Audio S2 allows users to upload reference audio containing multiple speakers, and the model processes each speaker's features via the `<|speaker:i|>` token. You can then control the model's performance via speaker ID tokens, enabling a single generation to include multiple speakers. There is no longer a need to upload separate reference audio for each individual speaker.
 
 ### Multi-Turn Generation
 
-Thanks to the expansion of the model context, our model can now use previous information to improve the expressiveness of subsequent generated content, thereby increasing the naturalness of the content.
+Thanks to the expansion of the model context, our model can now leverage previous information to improve the expressiveness of subsequent generated content, thereby increasing the naturalness of the dialogue.
 
 ### Rapid Voice Cloning
 
-Fish Audio S2 supports accurate voice cloning using a short reference sample (typically 10–30 seconds). The model captures timbre, speaking style, and emotional tendencies, producing realistic and consistent cloned voices without additional fine-tuning.
-Please refer to [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md) to use the SGLang server.
+Fish Audio S2 supports accurate voice cloning using short reference samples (typically 10-30 seconds). The model captures timbre, speaking style, and emotional tendencies, producing realistic and consistent cloned voices without additional fine-tuning.
+For SGLang Server usage, please refer to the [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md).
+
 ---
 
 ## Credits

awesome_webui/.gitignore

@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

awesome_webui/README.md

@@ -0,0 +1,73 @@
+# React + TypeScript + Vite
+
+This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.
+
+Currently, two official plugins are available:
+
+- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Babel](https://babeljs.io/) (or [oxc](https://oxc.rs) when used in [rolldown-vite](https://vite.dev/guide/rolldown)) for Fast Refresh
+- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/) for Fast Refresh
+
+## React Compiler
+
+The React Compiler is currently not compatible with SWC. See [this issue](https://github.com/vitejs/vite-plugin-react/issues/428) for tracking the progress.
+
+## Expanding the ESLint configuration
+
+If you are developing a production application, we recommend updating the configuration to enable type-aware lint rules:
+
+```js
+export default defineConfig([
+  globalIgnores(['dist']),
+  {
+    files: ['**/*.{ts,tsx}'],
+    extends: [
+      // Other configs...
+
+      // Remove tseslint.configs.recommended and replace with this
+      tseslint.configs.recommendedTypeChecked,
+      // Alternatively, use this for stricter rules
+      tseslint.configs.strictTypeChecked,
+      // Optionally, add this for stylistic rules
+      tseslint.configs.stylisticTypeChecked,
+
+      // Other configs...
+    ],
+    languageOptions: {
+      parserOptions: {
+        project: ['./tsconfig.node.json', './tsconfig.app.json'],
+        tsconfigRootDir: import.meta.dirname,
+      },
+      // other options...
+    },
+  },
+])
+```
+
+You can also install [eslint-plugin-react-x](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-x) and [eslint-plugin-react-dom](https://github.com/Rel1cx/eslint-react/tree/main/packages/plugins/eslint-plugin-react-dom) for React-specific lint rules:
+
+```js
+// eslint.config.js
+import reactX from 'eslint-plugin-react-x'
+import reactDom from 'eslint-plugin-react-dom'
+
+export default defineConfig([
+  globalIgnores(['dist']),
+  {
+    files: ['**/*.{ts,tsx}'],
+    extends: [
+      // Other configs...
+      // Enable lint rules for React
+      reactX.configs['recommended-typescript'],
+      // Enable lint rules for React DOM
+      reactDom.configs.recommended,
+    ],
+    languageOptions: {
+      parserOptions: {
+        project: ['./tsconfig.node.json', './tsconfig.app.json'],
+        tsconfigRootDir: import.meta.dirname,
+      },
+      // other options...
+    },
+  },
+])
+```

awesome_webui/eslint.config.js

@@ -0,0 +1,23 @@
+import js from '@eslint/js'
+import globals from 'globals'
+import reactHooks from 'eslint-plugin-react-hooks'
+import reactRefresh from 'eslint-plugin-react-refresh'
+import tseslint from 'typescript-eslint'
+import { defineConfig, globalIgnores } from 'eslint/config'
+
+export default defineConfig([
+  globalIgnores(['dist']),
+  {
+    files: ['**/*.{ts,tsx}'],
+    extends: [
+      js.configs.recommended,
+      tseslint.configs.recommended,
+      reactHooks.configs.flat.recommended,
+      reactRefresh.configs.vite,
+    ],
+    languageOptions: {
+      ecmaVersion: 2020,
+      globals: globals.browser,
+    },
+  },
+])

awesome_webui/index.html

@@ -0,0 +1,15 @@
+<!doctype html>
+<html lang="en">
+
+<head>
+  <meta charset="UTF-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
+  <title>Awesome WebUI</title>
+</head>
+
+<body>
+  <div id="root"></div>
+  <script type="module" src="/src/main.tsx"></script>
+</body>
+
+</html>

awesome_webui/package-lock.json

@@ -0,0 +1,4476 @@
+{
+  "name": "awesome_webui",
+  "version": "0.0.0",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {
+    "": {
+      "name": "awesome_webui",
+      "version": "0.0.0",
+      "dependencies": {
+        "@radix-ui/react-collapsible": "^1.1.12",
+        "@radix-ui/react-dialog": "^1.1.15",
+        "@radix-ui/react-label": "^2.1.8",
+        "@radix-ui/react-scroll-area": "^1.2.10",
+        "@radix-ui/react-separator": "^1.1.8",
+        "@radix-ui/react-slider": "^1.3.6",
+        "@radix-ui/react-slot": "^1.2.4",
+        "@radix-ui/react-switch": "^1.2.6",
+        "@radix-ui/react-toggle-group": "^1.1.11",
+        "@tailwindcss/vite": "^4.2.1",
+        "class-variance-authority": "^0.7.1",
+        "clsx": "^2.1.1",
+        "lucide-react": "^0.577.0",
+        "react": "^19.2.0",
+        "react-dom": "^19.2.0",
+        "tailwind-merge": "^3.5.0",
+        "tailwindcss": "^4.2.1"
+      },
+      "devDependencies": {
+        "@eslint/js": "^9.39.1",
+        "@types/node": "^24.10.1",
+        "@types/react": "^19.2.7",
+        "@types/react-dom": "^19.2.3",
+        "@vitejs/plugin-react-swc": "^4.2.2",
+        "eslint": "^9.39.1",
+        "eslint-plugin-react-hooks": "^7.0.1",
+        "eslint-plugin-react-refresh": "^0.4.24",
+        "globals": "^16.5.0",
+        "typescript": "~5.9.3",
+        "typescript-eslint": "^8.48.0",
+        "vite": "^7.3.1"
+      }
+    },
+    "node_modules/@babel/code-frame": {
+      "version": "7.29.0",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/helper-validator-identifier": "^7.28.5",
+        "js-tokens": "^4.0.0",
+        "picocolors": "^1.1.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/compat-data": {
+      "version": "7.29.0",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/core": {
+      "version": "7.29.0",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/code-frame": "^7.29.0",
+        "@babel/generator": "^7.29.0",
+        "@babel/helper-compilation-targets": "^7.28.6",
+        "@babel/helper-module-transforms": "^7.28.6",
+        "@babel/helpers": "^7.28.6",
+        "@babel/parser": "^7.29.0",
+        "@babel/template": "^7.28.6",
+        "@babel/traverse": "^7.29.0",
+        "@babel/types": "^7.29.0",
+        "@jridgewell/remapping": "^2.3.5",
+        "convert-source-map": "^2.0.0",
+        "debug": "^4.1.0",
+        "gensync": "^1.0.0-beta.2",
+        "json5": "^2.2.3",
+        "semver": "^6.3.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      },
+      "funding": {
+        "type": "opencollective",
+        "url": "https://opencollective.com/babel"
+      }
+    },
+    "node_modules/@babel/generator": {
+      "version": "7.29.1",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/parser": "^7.29.0",
+        "@babel/types": "^7.29.0",
+        "@jridgewell/gen-mapping": "^0.3.12",
+        "@jridgewell/trace-mapping": "^0.3.28",
+        "jsesc": "^3.0.2"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-compilation-targets": {
+      "version": "7.28.6",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/compat-data": "^7.28.6",
+        "@babel/helper-validator-option": "^7.27.1",
+        "browserslist": "^4.24.0",
+        "lru-cache": "^5.1.1",
+        "semver": "^6.3.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-globals": {
+      "version": "7.28.0",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-module-imports": {
+      "version": "7.28.6",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/traverse": "^7.28.6",
+        "@babel/types": "^7.28.6"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helper-module-transforms": {
+      "version": "7.28.6",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/helper-module-imports": "^7.28.6",
+        "@babel/helper-validator-identifier": "^7.28.5",
+        "@babel/traverse": "^7.28.6"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      },
+      "peerDependencies": {
+        "@babel/core": "^7.0.0"
+      }
+    },
+    "node_modules/@babel/helper-string-parser": {
+      "version": "7.27.1",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=6.9.0"
+      }
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+      "version": "7.28.5",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=6.9.0"
+      }
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+    "node_modules/@babel/helper-validator-option": {
+      "version": "7.27.1",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/helpers": {
+      "version": "7.28.6",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/template": "^7.28.6",
+        "@babel/types": "^7.28.6"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/parser": {
+      "version": "7.29.0",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/types": "^7.29.0"
+      },
+      "bin": {
+        "parser": "bin/babel-parser.js"
+      },
+      "engines": {
+        "node": ">=6.0.0"
+      }
+    },
+    "node_modules/@babel/template": {
+      "version": "7.28.6",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/code-frame": "^7.28.6",
+        "@babel/parser": "^7.28.6",
+        "@babel/types": "^7.28.6"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/traverse": {
+      "version": "7.29.0",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/code-frame": "^7.29.0",
+        "@babel/generator": "^7.29.0",
+        "@babel/helper-globals": "^7.28.0",
+        "@babel/parser": "^7.29.0",
+        "@babel/template": "^7.28.6",
+        "@babel/types": "^7.29.0",
+        "debug": "^4.3.1"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@babel/types": {
+      "version": "7.29.0",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "@babel/helper-string-parser": "^7.27.1",
+        "@babel/helper-validator-identifier": "^7.28.5"
+      },
+      "engines": {
+        "node": ">=6.9.0"
+      }
+    },
+    "node_modules/@esbuild/aix-ppc64": {
+      "version": "0.27.3",
+      "resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.27.3.tgz",
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+      "cpu": [
+        "ppc64"
+      ],
+      "license": "MIT",
+      "optional": true,
+      "os": [
+        "aix"
+      ],
+      "engines": {
+        "node": ">=18"
+      }
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+    "node_modules/@esbuild/android-arm": {
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+        "@rollup/rollup-openbsd-x64": "4.59.0",
+        "@rollup/rollup-openharmony-arm64": "4.59.0",
+        "@rollup/rollup-win32-arm64-msvc": "4.59.0",
+        "@rollup/rollup-win32-ia32-msvc": "4.59.0",
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+    },
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+      "dev": true,
+      "license": "ISC",
+      "bin": {
+        "semver": "bin/semver.js"
+      }
+    },
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+      "version": "2.0.0",
+      "dev": true,
+      "license": "MIT",
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+        "shebang-regex": "^3.0.0"
+      },
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+      }
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+    },
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+      "dev": true,
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+      "dev": true,
+      "license": "Apache-2.0",
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+        "tsserver": "bin/tsserver"
+      },
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+      }
+    },
+    "node_modules/typescript-eslint": {
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+      "license": "MIT",
+      "dependencies": {
+        "@typescript-eslint/eslint-plugin": "8.56.1",
+        "@typescript-eslint/parser": "8.56.1",
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+      "version": "7.16.0",
+      "devOptional": true,
+      "license": "MIT"
+    },
+    "node_modules/update-browserslist-db": {
+      "version": "1.2.3",
+      "dev": true,
+      "funding": [
+        {
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+          "url": "https://opencollective.com/browserslist"
+        },
+        {
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+          "url": "https://tidelift.com/funding/github/npm/browserslist"
+        },
+        {
+          "type": "github",
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+        }
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+      },
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+        }
+      }
+    },
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+      "license": "MIT",
+      "dependencies": {
+        "detect-node-es": "^1.1.0",
+        "tslib": "^2.0.0"
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+      },
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+          "optional": true
+        }
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+    },
+    "node_modules/vite": {
+      "version": "7.3.1",
+      "license": "MIT",
+      "dependencies": {
+        "esbuild": "^0.27.0",
+        "fdir": "^6.5.0",
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+        "postcss": "^8.5.6",
+        "rollup": "^4.43.0",
+        "tinyglobby": "^0.2.15"
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+      },
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+      },
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+        "url": "https://github.com/vitejs/vite?sponsor=1"
+      },
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+      },
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+        "jiti": ">=1.21.0",
+        "less": "^4.0.0",
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+        "terser": "^5.16.0",
+        "tsx": "^4.8.1",
+        "yaml": "^2.4.2"
+      },
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+          "optional": true
+        },
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+        },
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+        },
+        "lightningcss": {
+          "optional": true
+        },
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+        },
+        "sass-embedded": {
+          "optional": true
+        },
+        "stylus": {
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+        },
+        "sugarss": {
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+        },
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+        },
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+        }
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+    },
+    "node_modules/which": {
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+      "dev": true,
+      "license": "ISC",
+      "dependencies": {
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+      },
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+      }
+    },
+    "node_modules/word-wrap": {
+      "version": "1.2.5",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=0.10.0"
+      }
+    },
+    "node_modules/yallist": {
+      "version": "3.1.1",
+      "dev": true,
+      "license": "ISC"
+    },
+    "node_modules/yocto-queue": {
+      "version": "0.1.0",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=10"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
+    "node_modules/zod": {
+      "version": "4.3.6",
+      "dev": true,
+      "license": "MIT",
+      "funding": {
+        "url": "https://github.com/sponsors/colinhacks"
+      }
+    },
+    "node_modules/zod-validation-error": {
+      "version": "4.0.2",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">=18.0.0"
+      },
+      "peerDependencies": {
+        "zod": "^3.25.0 || ^4.0.0"
+      }
+    }
+  }
+}

awesome_webui/package.json

@@ -0,0 +1,45 @@
+{
+  "name": "awesome_webui",
+  "private": true,
+  "version": "0.0.0",
+  "type": "module",
+  "scripts": {
+    "dev": "vite",
+    "build": "tsc -b && vite build",
+    "lint": "eslint .",
+    "preview": "vite preview"
+  },
+  "dependencies": {
+    "@radix-ui/react-collapsible": "^1.1.12",
+    "@radix-ui/react-dialog": "^1.1.15",
+    "@radix-ui/react-label": "^2.1.8",
+    "@radix-ui/react-scroll-area": "^1.2.10",
+    "@radix-ui/react-separator": "^1.1.8",
+    "@radix-ui/react-slider": "^1.3.6",
+    "@radix-ui/react-slot": "^1.2.4",
+    "@radix-ui/react-switch": "^1.2.6",
+    "@radix-ui/react-toggle-group": "^1.1.11",
+    "@tailwindcss/vite": "^4.2.1",
+    "class-variance-authority": "^0.7.1",
+    "clsx": "^2.1.1",
+    "lucide-react": "^0.577.0",
+    "react": "^19.2.0",
+    "react-dom": "^19.2.0",
+    "tailwind-merge": "^3.5.0",
+    "tailwindcss": "^4.2.1"
+  },
+  "devDependencies": {
+    "@eslint/js": "^9.39.1",
+    "@types/node": "^24.10.1",
+    "@types/react": "^19.2.7",
+    "@types/react-dom": "^19.2.3",
+    "@vitejs/plugin-react-swc": "^4.2.2",
+    "eslint": "^9.39.1",
+    "eslint-plugin-react-hooks": "^7.0.1",
+    "eslint-plugin-react-refresh": "^0.4.24",
+    "globals": "^16.5.0",
+    "typescript": "~5.9.3",
+    "typescript-eslint": "^8.48.0",
+    "vite": "^7.3.1"
+  }
+}

awesome_webui/public/vite.svg

@@ -0,0 +1 @@
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>

awesome_webui/src/App.tsx

@@ -0,0 +1,1185 @@
+import { useEffect, useRef, useState } from 'react'
+import {
+  AudioLines,
+  ChevronDown,
+  CircleAlert,
+  Copy,
+  Download,
+  FileText,
+  Info,
+  LoaderCircle,
+  Plus,
+  Settings2,
+  Upload,
+} from 'lucide-react'
+
+import { Alert, AlertDescription, AlertTitle } from '@/components/ui/alert'
+import { Badge } from '@/components/ui/badge'
+import { Button } from '@/components/ui/button'
+import {
+  Card,
+  CardContent,
+  CardDescription,
+  CardHeader,
+  CardTitle,
+} from '@/components/ui/card'
+import {
+  Collapsible,
+  CollapsibleContent,
+  CollapsibleTrigger,
+} from '@/components/ui/collapsible'
+import {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+} from '@/components/ui/dialog'
+import { Label } from '@/components/ui/label'
+import { ScrollArea } from '@/components/ui/scroll-area'
+import { Separator } from '@/components/ui/separator'
+import { Slider } from '@/components/ui/slider'
+import { Switch } from '@/components/ui/switch'
+import { Textarea } from '@/components/ui/textarea'
+import { ToggleGroup, ToggleGroupItem } from '@/components/ui/toggle-group'
+
+type AudioFormat = 'mp3' | 'wav' | 'pcm' | 'opus'
+type LatencyMode = 'normal' | 'balanced'
+
+const defaultInputText = `[excited, joyful tone] We're going to DISNEY WORLD! [squeal of delight] I've been saving for [emphasis] three years [breathless] and finally, FINALLY we can go! The look on your face right now is worth every extra shift I worked!
+[angry] After everything we've been through [break] I can't believe you would [emphasize] betray me like this. I gave you EVERYTHING! And now I'm left with nothing but memories and broken promises!`
+
+
+type ControlsState = {
+  chunkLength: number
+  maxNewTokens: number
+  temperature: number
+  topP: number
+  repetitionPenalty: number
+  normalize: boolean
+  format: AudioFormat
+  latency: LatencyMode
+}
+
+type Metrics = {
+  textLength: number
+  ttftMs: number
+  receivedKb: number
+}
+
+type StatusState = {
+  tone: 'error' | 'info'
+  message: string
+}
+
+type ReferenceItem = {
+  id: number
+  name: string
+  audio: ArrayBuffer
+  text: string
+  previewUrl: string
+}
+
+type SpeakerGroup = {
+  id: number
+  references: ReferenceItem[]
+}
+
+type PendingReference = {
+  mode: 'create' | 'edit'
+  speakerId: number
+  referenceId?: number
+  name: string
+  audio?: ArrayBuffer
+  text: string
+}
+
+const initialControls: ControlsState = {
+  chunkLength: 1000,
+  maxNewTokens: 2048,
+  temperature: 0.9,
+  topP: 0.9,
+  repetitionPenalty: 1.05,
+  normalize: false,
+  format: 'mp3',
+  latency: 'normal',
+}
+
+const formatMimeMap: Record<AudioFormat, string> = {
+  mp3: 'audio/mpeg',
+  wav: 'audio/wav',
+  pcm: 'audio/pcm',
+  opus: 'audio/opus',
+}
+
+function createId() {
+  return Date.now() + Math.floor(Math.random() * 100000)
+}
+
+function arrayBufferToBase64(buffer: ArrayBuffer): string {
+  const bytes = new Uint8Array(buffer)
+  let binary = ''
+  for (let i = 0; i < bytes.byteLength; i++) {
+    binary += String.fromCharCode(bytes[i])
+  }
+  return btoa(binary)
+}
+
+function createSpeakerGroup(): SpeakerGroup {
+  return {
+    id: createId(),
+    references: [],
+  }
+}
+
+const initialSpeakerGroup = createSpeakerGroup()
+
+function buildReferencesPayload(
+  speakerGroups: SpeakerGroup[],
+  includeBinaryAudio: boolean,
+) {
+  return speakerGroups.flatMap((speakerGroup) =>
+    speakerGroup.references.map((reference) => ({
+      text: reference.text,
+      audio: includeBinaryAudio
+        ? arrayBufferToBase64(reference.audio)
+        : '<audio binary data>',
+    })),
+  )
+}
+
+function buildPreviewPayload(
+  inputText: string,
+  controls: ControlsState,
+  speakerGroups: SpeakerGroup[],
+) {
+  return {
+    text: inputText,
+    chunk_length: controls.chunkLength,
+    max_new_tokens: controls.maxNewTokens,
+    format: controls.format,
+    latency: controls.latency,
+    normalize: controls.normalize,
+    references: buildReferencesPayload(speakerGroups, false),
+    temperature: controls.temperature,
+    top_p: controls.topP,
+    repetition_penalty: controls.repetitionPenalty,
+  }
+}
+
+function buildRequestPayload(
+  inputText: string,
+  controls: ControlsState,
+  speakerGroups: SpeakerGroup[],
+) {
+  return {
+    text: inputText,
+    chunk_length: controls.chunkLength,
+    max_new_tokens: controls.maxNewTokens,
+    format: controls.format,
+    latency: controls.latency,
+    normalize: controls.normalize,
+    references: buildReferencesPayload(speakerGroups, true),
+    temperature: controls.temperature,
+    top_p: controls.topP,
+    repetition_penalty: controls.repetitionPenalty,
+  }
+}
+
+function createFileName(inputText: string) {
+  const safePrefix = inputText.trim().replace(/\s+/g, '-').slice(0, 24) || 'tts'
+  return safePrefix
+}
+
+function getErrorMessage(error: unknown) {
+  return error instanceof Error ? error.message : 'Unknown error'
+}
+
+function waitForSourceBuffer(sourceBuffer: SourceBuffer) {
+  if (!sourceBuffer.updating) {
+    return Promise.resolve()
+  }
+
+  return new Promise<void>((resolve) => {
+    const handleUpdateEnd = () => {
+      sourceBuffer.removeEventListener('updateend', handleUpdateEnd)
+      resolve()
+    }
+
+    sourceBuffer.addEventListener('updateend', handleUpdateEnd)
+  })
+}
+
+function canUseStreamingPlayback(format: AudioFormat) {
+  const mime = formatMimeMap[format]
+  return typeof window.MediaSource !== 'undefined' && MediaSource.isTypeSupported(mime)
+}
+
+type SettingSliderProps = {
+  label: string
+  value: number
+  min: number
+  max: number
+  step?: number
+  onValueChange: (value: number) => void
+  formatValue?: (value: number) => string
+}
+
+function SettingSlider({
+  label,
+  value,
+  min,
+  max,
+  step = 1,
+  onValueChange,
+  formatValue,
+}: SettingSliderProps) {
+  return (
+    <div className="space-y-3">
+      <div className="flex items-center justify-between gap-4">
+        <Label>{label}</Label>
+        <span className="text-sm text-muted-foreground">
+          {formatValue ? formatValue(value) : value}
+        </span>
+      </div>
+      <Slider
+        value={[value]}
+        min={min}
+        max={max}
+        step={step}
+        onValueChange={(nextValue) => {
+          const current = nextValue[0]
+          if (typeof current === 'number') {
+            onValueChange(current)
+          }
+        }}
+      />
+    </div>
+  )
+}
+
+function App() {
+  const [inputText, setInputText] = useState(defaultInputText)
+  const [controls, setControls] = useState(initialControls)
+  const [speakerGroups, setSpeakerGroups] = useState<SpeakerGroup[]>([initialSpeakerGroup])
+  const [pendingReference, setPendingReference] = useState<PendingReference | null>(null)
+  const [openSpeakerIds, setOpenSpeakerIds] = useState<number[]>([initialSpeakerGroup.id])
+  const [metrics, setMetrics] = useState<Metrics | null>(null)
+  const [isGenerating, setIsGenerating] = useState(false)
+  const [copyLabel, setCopyLabel] = useState('Copy')
+  const [isRequestPreviewOpen, setIsRequestPreviewOpen] = useState(false)
+  const [statusMessage, setStatusMessage] = useState<StatusState | null>(null)
+  const [downloadUrl, setDownloadUrl] = useState<string | null>(null)
+  const [downloadName, setDownloadName] = useState('generated-audio.mp3')
+
+  const audioRef = useRef<HTMLAudioElement | null>(null)
+  const fileInputRef = useRef<HTMLInputElement | null>(null)
+  const speakerGroupsRef = useRef<SpeakerGroup[]>([])
+  const uploadTargetSpeakerIdRef = useRef<number | null>(null)
+  const downloadUrlRef = useRef<string | null>(null)
+  const mediaSourceUrlRef = useRef<string | null>(null)
+
+  speakerGroupsRef.current = speakerGroups
+
+  useEffect(() => {
+    return () => {
+      speakerGroupsRef.current.forEach((speakerGroup) => {
+        speakerGroup.references.forEach((reference) => {
+          URL.revokeObjectURL(reference.previewUrl)
+        })
+      })
+
+      if (downloadUrlRef.current) {
+        URL.revokeObjectURL(downloadUrlRef.current)
+      }
+
+      if (mediaSourceUrlRef.current) {
+        URL.revokeObjectURL(mediaSourceUrlRef.current)
+      }
+    }
+  }, [])
+
+  function addSpeaker() {
+    const nextSpeaker = createSpeakerGroup()
+    setSpeakerGroups((current) => [...current, nextSpeaker])
+    setOpenSpeakerIds((current) => [...current, nextSpeaker.id])
+  }
+
+  function removeSpeaker(speakerId: number) {
+    setSpeakerGroups((current) => {
+      const targetSpeaker = current.find((speakerGroup) => speakerGroup.id === speakerId)
+      if (targetSpeaker) {
+        targetSpeaker.references.forEach((reference) => {
+          URL.revokeObjectURL(reference.previewUrl)
+        })
+      }
+
+      const next = current.filter((speakerGroup) => speakerGroup.id !== speakerId)
+      return next.length > 0 ? next : [createSpeakerGroup()]
+    })
+    setOpenSpeakerIds((current) => current.filter((currentSpeakerId) => currentSpeakerId !== speakerId))
+
+    if (pendingReference?.speakerId === speakerId) {
+      setPendingReference(null)
+    }
+  }
+
+  function addReference(speakerId: number, name: string, audio: ArrayBuffer, text: string) {
+    const previewUrl = URL.createObjectURL(new Blob([audio], { type: formatMimeMap.mp3 }))
+
+    setSpeakerGroups((current) =>
+      current.map((speakerGroup) =>
+        speakerGroup.id === speakerId
+          ? {
+              ...speakerGroup,
+              references: [
+                ...speakerGroup.references,
+                {
+                  id: createId(),
+                  name,
+                  audio,
+                  text,
+                  previewUrl,
+                },
+              ],
+            }
+          : speakerGroup,
+      ),
+    )
+  }
+
+  function removeReference(speakerId: number, referenceId: number) {
+    setSpeakerGroups((current) =>
+      current.map((speakerGroup) => {
+        if (speakerGroup.id !== speakerId) {
+          return speakerGroup
+        }
+
+        return {
+          ...speakerGroup,
+          references: speakerGroup.references.filter((reference) => {
+            if (reference.id === referenceId) {
+              URL.revokeObjectURL(reference.previewUrl)
+              return false
+            }
+
+            return true
+          }),
+        }
+      }),
+    )
+  }
+
+  function updateReferenceText(speakerId: number, referenceId: number, text: string) {
+    setSpeakerGroups((current) =>
+      current.map((speakerGroup) =>
+        speakerGroup.id === speakerId
+          ? {
+              ...speakerGroup,
+              references: speakerGroup.references.map((reference) =>
+                reference.id === referenceId ? { ...reference, text } : reference,
+              ),
+            }
+          : speakerGroup,
+      ),
+    )
+  }
+
+  function clearDownloadUrl() {
+    if (downloadUrlRef.current) {
+      URL.revokeObjectURL(downloadUrlRef.current)
+      downloadUrlRef.current = null
+    }
+
+    setDownloadUrl(null)
+  }
+
+  function clearMediaSourceUrl() {
+    if (mediaSourceUrlRef.current) {
+      URL.revokeObjectURL(mediaSourceUrlRef.current)
+      mediaSourceUrlRef.current = null
+    }
+  }
+
+  async function handleReferenceUpload(event: React.ChangeEvent<HTMLInputElement>) {
+    const file = event.target.files?.[0]
+    const speakerId = uploadTargetSpeakerIdRef.current
+    event.target.value = ''
+    uploadTargetSpeakerIdRef.current = null
+
+    if (!file || typeof speakerId !== 'number') {
+      return
+    }
+
+    const audio = await file.arrayBuffer()
+    setPendingReference({
+      mode: 'create',
+      speakerId,
+      name: file.name,
+      audio,
+      text: '',
+    })
+  }
+
+  function savePendingReference() {
+    if (!pendingReference) {
+      return
+    }
+
+    if (pendingReference.mode === 'create' && pendingReference.audio) {
+      addReference(
+        pendingReference.speakerId,
+        pendingReference.name,
+        pendingReference.audio,
+        pendingReference.text,
+      )
+    }
+
+    if (pendingReference.mode === 'edit' && typeof pendingReference.referenceId === 'number') {
+      updateReferenceText(
+        pendingReference.speakerId,
+        pendingReference.referenceId,
+        pendingReference.text,
+      )
+    }
+
+    setPendingReference(null)
+    setStatusMessage(null)
+  }
+
+  async function copyRequestPreview() {
+    const requestPreview = JSON.stringify(
+      buildPreviewPayload(inputText, controls, speakerGroups),
+      null,
+      2,
+    )
+
+    try {
+      await navigator.clipboard.writeText(requestPreview)
+      setCopyLabel('Copied')
+      window.setTimeout(() => setCopyLabel('Copy'), 2000)
+    } catch (error) {
+      setStatusMessage({
+        tone: 'error',
+        message: `Failed to copy request preview: ${getErrorMessage(error)}`,
+      })
+    }
+  }
+
+  async function handleGenerateAudio() {
+    const audioElement = audioRef.current
+    if (!audioElement) {
+      return
+    }
+
+    const mime = formatMimeMap[controls.format]
+    const useStreamingPlayback = canUseStreamingPlayback(controls.format)
+
+    clearDownloadUrl()
+    clearMediaSourceUrl()
+    setMetrics(null)
+    setStatusMessage(null)
+    setIsGenerating(true)
+
+    try {
+      const response = await fetch('/v1/tts', {
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json',
+        },
+        body: JSON.stringify(buildRequestPayload(inputText, controls, speakerGroups)),
+      })
+
+      if (!response.ok || !response.body) {
+        throw new Error('Failed to generate audio')
+      }
+
+      const reader = response.body.getReader()
+      let mediaSource: MediaSource | null = null
+
+      if (useStreamingPlayback) {
+        mediaSource = new MediaSource()
+        const streamUrl = URL.createObjectURL(mediaSource)
+        mediaSourceUrlRef.current = streamUrl
+        audioElement.src = streamUrl
+      } else {
+        audioElement.removeAttribute('src')
+        audioElement.load()
+      }
+
+      const allChunks: ArrayBuffer[] = []
+      const playQueue: ArrayBuffer[] = []
+      let sourceBuffer: SourceBuffer | null = null
+      let readingDone = false
+      let receivedLength = 0
+      let ttftMs = -1
+      const startTime = performance.now()
+
+      if (mediaSource) {
+        const sourceReady = new Promise<void>((resolve, reject) => {
+          mediaSource.addEventListener(
+            'sourceopen',
+            () => {
+              try {
+                sourceBuffer = mediaSource.addSourceBuffer(mime)
+
+                const processQueue = async () => {
+                  if (!sourceBuffer || !mediaSource) {
+                    return
+                  }
+
+                  while (true) {
+                    if (readingDone && playQueue.length === 0) {
+                      await waitForSourceBuffer(sourceBuffer)
+                      if (mediaSource.readyState === 'open') {
+                        mediaSource.endOfStream()
+                      }
+                      break
+                    }
+
+                    const chunk = playQueue.shift()
+                    if (!chunk) {
+                      await new Promise<void>((resolveSleep) => {
+                        window.setTimeout(resolveSleep, 50)
+                      })
+                      continue
+                    }
+
+                    await waitForSourceBuffer(sourceBuffer)
+                    sourceBuffer.appendBuffer(chunk)
+                    await waitForSourceBuffer(sourceBuffer)
+                  }
+                }
+
+                void processQueue()
+                resolve()
+              } catch (error) {
+                reject(error)
+              }
+            },
+            { once: true },
+          )
+        })
+
+        await sourceReady
+      }
+
+      while (true) {
+        const { done, value } = await reader.read()
+        if (done) {
+          readingDone = true
+          break
+        }
+
+        receivedLength += value.byteLength
+
+        if (ttftMs < 0) {
+          ttftMs = performance.now() - startTime
+        }
+
+        setMetrics({
+          textLength: inputText.length,
+          ttftMs,
+          receivedKb: Math.round(receivedLength / 1024),
+        })
+
+        const chunk = value.buffer.slice(value.byteOffset, value.byteOffset + value.byteLength)
+        playQueue.push(chunk)
+        allChunks.push(chunk)
+
+        if (useStreamingPlayback && audioElement.paused) {
+          void audioElement.play().catch(() => undefined)
+        }
+      }
+
+      const audioBlob = new Blob(allChunks, { type: mime })
+      const nextDownloadUrl = URL.createObjectURL(audioBlob)
+      downloadUrlRef.current = nextDownloadUrl
+      setDownloadUrl(nextDownloadUrl)
+      setDownloadName(`${createFileName(inputText)}.${controls.format}`)
+
+      if (!useStreamingPlayback) {
+        audioElement.src = nextDownloadUrl
+        audioElement.load()
+        setStatusMessage({
+          tone: 'info',
+          message: `Format "${controls.format}" is not supported for in-browser playback. The file is ready to download after generation completes.`,
+        })
+      }
+    } catch (error) {
+      setStatusMessage({
+        tone: 'error',
+        message: `Audio generation failed: ${getErrorMessage(error)}`,
+      })
+    } finally {
+      setIsGenerating(false)
+    }
+  }
+
+  const requestPreview = JSON.stringify(
+    buildPreviewPayload(inputText, controls, speakerGroups),
+    null,
+    2,
+  )
+
+  const totalReferenceCount = speakerGroups.reduce(
+    (count, speakerGroup) => count + speakerGroup.references.length,
+    0,
+  )
+
+  return (
+    <main className="min-h-screen bg-zinc-50">
+      <div className="mx-auto max-w-[1600px] px-3 py-3 sm:px-4 lg:px-5">
+        <div className="grid gap-4 xl:h-[calc(100vh-1.5rem)] xl:grid-cols-[minmax(0,1fr)_460px]">
+          <section className="grid gap-4 xl:min-h-0 xl:grid-rows-[minmax(0,1fr)_auto]">
+            <Card className="rounded-xl border-zinc-200 bg-white shadow-none xl:min-h-0 xl:flex xl:flex-col">
+              <CardHeader className="space-y-1 border-b border-zinc-100 px-4 py-4">
+                <div className="flex items-center gap-2 text-zinc-700">
+                  <FileText className="size-4" />
+                  <CardTitle>Input</CardTitle>
+                </div>
+                <CardDescription>
+                  Enter the text to synthesize and inspect the outgoing request payload.
+                </CardDescription>
+              </CardHeader>
+              <CardContent className="space-y-4 px-4 pt-4 xl:min-h-0 xl:flex-1 xl:overflow-y-auto">
+                <div className="space-y-2">
+                  <Label htmlFor="inputText">Input Text</Label>
+                  <Textarea
+                    id="inputText"
+                    value={inputText}
+                    onChange={(event) => setInputText(event.target.value)}
+                    placeholder="Enter text to synthesize"
+                    className="min-h-[220px] resize-y rounded-xl border-zinc-200 bg-white p-3 text-sm shadow-none focus-visible:ring-zinc-300 xl:min-h-[260px]"
+                  />
+                </div>
+
+                <Collapsible open={isRequestPreviewOpen} onOpenChange={setIsRequestPreviewOpen}>
+                  <div className="rounded-xl border border-zinc-200 bg-zinc-50">
+                    <div className="flex flex-col gap-2 p-3 sm:flex-row sm:items-center sm:justify-between">
+                      <div>
+                        <div className="text-sm font-medium text-zinc-900">Request Preview</div>
+                        <div className="text-xs text-zinc-500">
+                          Live snapshot of the payload sent to the backend.
+                        </div>
+                      </div>
+                      <div className="flex items-center gap-2">
+                        <Button
+                          type="button"
+                          variant="ghost"
+                          size="sm"
+                          className="border border-zinc-200 bg-white text-zinc-700 hover:bg-zinc-100"
+                          onClick={copyRequestPreview}
+                        >
+                          <Copy className="size-3.5" />
+                          {copyLabel}
+                        </Button>
+                        <CollapsibleTrigger asChild>
+                          <Button
+                            type="button"
+                            variant="ghost"
+                            size="sm"
+                            className="border border-zinc-200 bg-white text-zinc-700 hover:bg-zinc-100"
+                          >
+                            {isRequestPreviewOpen ? 'Collapse' : 'Expand'}
+                            <ChevronDown
+                              className={`size-4 transition-transform ${
+                                isRequestPreviewOpen ? 'rotate-180' : ''
+                              }`}
+                            />
+                          </Button>
+                        </CollapsibleTrigger>
+                      </div>
+                    </div>
+                    <CollapsibleContent>
+                      <Separator className="bg-zinc-200" />
+                      <div className="p-3 pt-3">
+                        <ScrollArea className="h-56 min-w-0 rounded-lg border border-zinc-200 bg-white">
+                          <pre className="max-w-full whitespace-pre-wrap break-all p-3 text-xs leading-5 text-zinc-700">
+                            {requestPreview}
+                          </pre>
+                        </ScrollArea>
+                      </div>
+                    </CollapsibleContent>
+                  </div>
+                </Collapsible>
+
+                <div className="space-y-4">
+                  <Button
+                    type="button"
+                    size="lg"
+                    className="h-11 rounded-lg bg-zinc-900 text-white hover:bg-zinc-800"
+                    onClick={handleGenerateAudio}
+                    disabled={isGenerating}
+                  >
+                    {isGenerating ? (
+                      <LoaderCircle className="size-4 animate-spin" />
+                    ) : (
+                      <AudioLines className="size-4" />
+                    )}
+                    {isGenerating ? 'Generating Audio...' : 'Generate Audio'}
+                  </Button>
+
+                  {statusMessage ? (
+                    <Alert
+                      variant={statusMessage.tone === 'error' ? 'destructive' : 'warning'}
+                      className="rounded-lg"
+                    >
+                      <div className="flex items-start gap-3">
+                        {statusMessage.tone === 'error' ? (
+                          <CircleAlert className="mt-0.5 size-4 shrink-0" />
+                        ) : (
+                          <Info className="mt-0.5 size-4 shrink-0" />
+                        )}
+                        <div>
+                          <AlertTitle>
+                            {statusMessage.tone === 'error' ? 'Error' : 'Notice'}
+                          </AlertTitle>
+                          <AlertDescription>{statusMessage.message}</AlertDescription>
+                        </div>
+                      </div>
+                    </Alert>
+                  ) : null}
+                </div>
+              </CardContent>
+            </Card>
+
+            <Card className="rounded-xl border-zinc-200 bg-white shadow-none">
+              <CardHeader className="space-y-1 border-b border-zinc-100 px-4 py-4">
+                <div className="flex items-center gap-2 text-zinc-700">
+                  <AudioLines className="size-4" />
+                  <CardTitle>Output</CardTitle>
+                </div>
+                <CardDescription>
+                  Stream the result when supported, then preview or download the final file.
+                </CardDescription>
+              </CardHeader>
+              <CardContent className="space-y-3 px-4 pt-4">
+                <audio
+                  ref={audioRef}
+                  controls
+                  className="w-full rounded-lg border border-zinc-200 bg-white"
+                />
+
+                <div className="flex flex-wrap gap-2">
+                  {metrics ? (
+                    <>
+                      <Badge variant="outline" className="border-zinc-200 bg-white text-zinc-700">
+                        Text length: {metrics.textLength}
+                      </Badge>
+                      <Badge variant="outline" className="border-zinc-200 bg-white text-zinc-700">
+                        TTFT: {metrics.ttftMs.toFixed(2)} ms
+                      </Badge>
+                      <Badge variant="outline" className="border-zinc-200 bg-white text-zinc-700">
+                        Received: {metrics.receivedKb} KB
+                      </Badge>
+                    </>
+                  ) : (
+                    <Badge variant="outline" className="border-zinc-200 bg-white text-zinc-500">
+                      No output yet
+                    </Badge>
+                  )}
+                </div>
+
+                <div className="flex justify-end">
+                  {downloadUrl ? (
+                    <Button
+                      asChild
+                      variant="outline"
+                      className="border-zinc-200 bg-white text-zinc-800 hover:bg-zinc-100"
+                    >
+                      <a href={downloadUrl} download={downloadName}>
+                        <Download className="size-4" />
+                        Download
+                      </a>
+                    </Button>
+                  ) : null}
+                </div>
+              </CardContent>
+            </Card>
+          </section>
+
+          <aside className="grid gap-4 xl:min-h-0 xl:grid-rows-[minmax(0,1fr)_auto]">
+            <Card className="rounded-xl border-zinc-200 bg-white shadow-none xl:min-h-0 xl:flex xl:flex-col">
+              <CardHeader className="space-y-1 border-b border-zinc-100 px-4 py-4">
+                <div className="flex items-center gap-2 text-zinc-700">
+                  <Upload className="size-4" />
+                  <CardTitle>Reference Audio</CardTitle>
+                </div>
+                <CardDescription>
+                  Build one or more speaker groups. Each speaker can have multiple reference clips.
+                </CardDescription>
+              </CardHeader>
+              <CardContent className="space-y-3 px-4 pt-4 xl:min-h-0 xl:flex xl:flex-1 xl:flex-col">
+                <div className="flex flex-wrap items-center justify-between gap-2">
+                  <div className="flex items-center text-sm text-zinc-500">
+                    {speakerGroups.length} speaker{speakerGroups.length === 1 ? '' : 's'} /{' '}
+                    {totalReferenceCount} reference{totalReferenceCount === 1 ? '' : 's'}
+                  </div>
+                  <Button
+                    type="button"
+                    variant="outline"
+                    className="border-zinc-200 bg-white hover:bg-zinc-100"
+                    onClick={addSpeaker}
+                  >
+                    <Plus className="size-4" />
+                    Add Speaker
+                  </Button>
+                  <input
+                    ref={fileInputRef}
+                    type="file"
+                    accept="audio/*"
+                    className="hidden"
+                    onChange={handleReferenceUpload}
+                  />
+                </div>
+
+                <ScrollArea className="min-h-0 rounded-md xl:h-full xl:flex-1">
+                  <div className="space-y-2">
+                    {speakerGroups.length > 0 ? (
+                      speakerGroups.map((speakerGroup, speakerIndex) => (
+                        <Collapsible
+                          key={speakerGroup.id}
+                          open={openSpeakerIds.includes(speakerGroup.id)}
+                          onOpenChange={(open) => {
+                            setOpenSpeakerIds((current) =>
+                              open
+                                ? [...current, speakerGroup.id]
+                                : current.filter(
+                                    (currentSpeakerId) => currentSpeakerId !== speakerGroup.id,
+                                  ),
+                            )
+                          }}
+                        >
+                          <div className="rounded-lg border border-zinc-200 bg-white">
+                            <div className="flex flex-col gap-2 px-3 py-3 sm:flex-row sm:items-center sm:justify-between">
+                              <div className="min-w-0">
+                                <div className="text-sm font-medium text-zinc-900">
+                                  Speaker {speakerIndex}
+                                </div>
+                                <div className="text-xs text-zinc-500">
+                                  {speakerGroup.references.length} reference
+                                  {speakerGroup.references.length === 1 ? '' : 's'}
+                                </div>
+                              </div>
+                              <div className="flex flex-wrap gap-2">
+                                <Button
+                                  type="button"
+                                  variant="outline"
+                                  size="sm"
+                                  className="h-8 border-zinc-200 bg-white px-2.5 hover:bg-zinc-100"
+                                  onClick={() => {
+                                    uploadTargetSpeakerIdRef.current = speakerGroup.id
+                                    fileInputRef.current?.click()
+                                  }}
+                                >
+                                  <Upload className="size-4" />
+                                  Upload
+                                </Button>
+                                {speakerGroups.length > 1 ? (
+                                  <Button
+                                    type="button"
+                                    variant="ghost"
+                                    size="sm"
+                                    className="h-8 px-2.5 text-zinc-500 hover:bg-zinc-100 hover:text-zinc-900"
+                                    onClick={() => removeSpeaker(speakerGroup.id)}
+                                  >
+                                    Remove
+                                  </Button>
+                                ) : null}
+                                <CollapsibleTrigger asChild>
+                                  <Button
+                                    type="button"
+                                    variant="ghost"
+                                    size="sm"
+                                    className="h-8 px-2 text-zinc-500 hover:bg-zinc-100 hover:text-zinc-900"
+                                  >
+                                    <ChevronDown
+                                      className={`size-4 transition-transform ${
+                                        openSpeakerIds.includes(speakerGroup.id) ? 'rotate-180' : ''
+                                      }`}
+                                    />
+                                  </Button>
+                                </CollapsibleTrigger>
+                              </div>
+                            </div>
+
+                            <CollapsibleContent>
+                              <Separator className="bg-zinc-200" />
+                              <div className="space-y-2 px-3 py-2.5">
+                                {speakerGroup.references.length > 0 ? (
+                                  speakerGroup.references.map((reference) => (
+                                    <div
+                                      key={reference.id}
+                                      className="flex flex-col gap-2 rounded-md border border-zinc-200 bg-zinc-50 p-2 sm:flex-row sm:items-center"
+                                    >
+                                      <audio
+                                        controls
+                                        src={reference.previewUrl}
+                                        className="h-9 w-full min-w-0 rounded-md border border-zinc-200 bg-white sm:flex-1"
+                                      />
+                                      <div className="flex gap-2 sm:shrink-0">
+                                        <Button
+                                          type="button"
+                                          variant="ghost"
+                                          size="sm"
+                                          className="h-8 border border-zinc-200 bg-white px-2.5 text-zinc-600 hover:bg-zinc-100 hover:text-zinc-900"
+                                          onClick={() =>
+                                            setPendingReference({
+                                              mode: 'edit',
+                                              speakerId: speakerGroup.id,
+                                              referenceId: reference.id,
+                                              name: reference.name,
+                                              text: reference.text,
+                                            })
+                                          }
+                                        >
+                                          Edit Text
+                                        </Button>
+                                        <Button
+                                          type="button"
+                                          variant="ghost"
+                                          size="sm"
+                                          className="h-8 border border-zinc-200 bg-white px-2.5 text-zinc-500 hover:bg-zinc-100 hover:text-zinc-900"
+                                          onClick={() =>
+                                            removeReference(speakerGroup.id, reference.id)
+                                          }
+                                        >
+                                          Remove
+                                        </Button>
+                                      </div>
+                                    </div>
+                                  ))
+                                ) : (
+                                  <div className="px-1 py-3 text-sm text-zinc-500">
+                                    No references yet.
+                                  </div>
+                                )}
+                              </div>
+                            </CollapsibleContent>
+                          </div>
+                        </Collapsible>
+                      ))
+                    ) : (
+                      <div className="rounded-lg border border-dashed border-zinc-300 bg-white p-4 text-sm text-zinc-500">
+                        No speaker groups configured yet.
+                      </div>
+                    )}
+                  </div>
+                </ScrollArea>
+              </CardContent>
+            </Card>
+
+            <Card className="rounded-xl border-zinc-200 bg-white shadow-none">
+              <CardHeader className="space-y-1 border-b border-zinc-100 px-4 py-4">
+                <div className="flex items-center gap-2 text-zinc-700">
+                  <Settings2 className="size-4" />
+                  <CardTitle>Generation Settings</CardTitle>
+                </div>
+                <CardDescription>Adjust sampling and output parameters.</CardDescription>
+              </CardHeader>
+              <CardContent className="space-y-4 px-4 pt-4">
+                <div className="space-y-2">
+                  <Label>Latency Mode</Label>
+                  <ToggleGroup
+                    type="single"
+                    value={controls.latency}
+                    className="grid grid-cols-2 gap-2"
+                    onValueChange={(value) => {
+                      if (value) {
+                        setControls((current) => ({
+                          ...current,
+                          latency: value as LatencyMode,
+                        }))
+                      }
+                    }}
+                  >
+                    <ToggleGroupItem value="balanced" className="w-full">
+                      balanced
+                    </ToggleGroupItem>
+                    <ToggleGroupItem value="normal" className="w-full">
+                      normal
+                    </ToggleGroupItem>
+                  </ToggleGroup>
+                  <p className="text-xs text-zinc-500">
+                    Low uses incremental local decode for faster first audio. Normal waits for the
+                    full LLM result, then decodes once.
+                  </p>
+                </div>
+
+                <div className="space-y-2">
+                  <Label>Format</Label>
+                  <ToggleGroup
+                    type="single"
+                    value={controls.format}
+                    className="grid grid-cols-4 gap-2"
+                    onValueChange={(value) => {
+                      if (value) {
+                        setControls((current) => ({
+                          ...current,
+                          format: value as AudioFormat,
+                        }))
+                      }
+                    }}
+                  >
+                    <ToggleGroupItem value="mp3" className="w-full">
+                      mp3
+                    </ToggleGroupItem>
+                    <ToggleGroupItem value="wav" className="w-full">
+                      wav
+                    </ToggleGroupItem>
+                    <ToggleGroupItem value="pcm" className="w-full">
+                      pcm
+                    </ToggleGroupItem>
+                    <ToggleGroupItem value="opus" className="w-full">
+                      opus
+                    </ToggleGroupItem>
+                  </ToggleGroup>
+                </div>
+
+                <div className="flex items-center justify-between rounded-lg border border-zinc-200 bg-zinc-50 px-3 py-2.5">
+                  <div className="space-y-1">
+                    <Label htmlFor="normalize">Normalize</Label>
+                    <p className="text-xs text-zinc-500">
+                      Normalize text before synthesis to keep input formatting consistent.
+                    </p>
+                  </div>
+                  <Switch
+                    id="normalize"
+                    checked={controls.normalize}
+                    onCheckedChange={(checked) =>
+                      setControls((current) => ({
+                        ...current,
+                        normalize: checked,
+                      }))
+                    }
+                  />
+                </div>
+
+                <Separator className="bg-zinc-200" />
+
+                <SettingSlider
+                  label="Chunk Length"
+                  value={controls.chunkLength}
+                  min={100}
+                  max={1000}
+                  onValueChange={(value) =>
+                    setControls((current) => ({
+                      ...current,
+                      chunkLength: value,
+                    }))
+                  }
+                />
+                <SettingSlider
+                  label="Max New Tokens"
+                  value={controls.maxNewTokens}
+                  min={256}
+                  max={2048}
+                  onValueChange={(value) =>
+                    setControls((current) => ({
+                      ...current,
+                      maxNewTokens: value,
+                    }))
+                  }
+                />
+                <SettingSlider
+                  label="Temperature"
+                  value={controls.temperature}
+                  min={0.8}
+                  max={1}
+                  step={0.01}
+                  formatValue={(value) => value.toFixed(2)}
+                  onValueChange={(value) =>
+                    setControls((current) => ({
+                      ...current,
+                      temperature: value,
+                    }))
+                  }
+                />
+                <SettingSlider
+                  label="Top P"
+                  value={controls.topP}
+                  min={0.8}
+                  max={1}
+                  step={0.01}
+                  formatValue={(value) => value.toFixed(2)}
+                  onValueChange={(value) =>
+                    setControls((current) => ({
+                      ...current,
+                      topP: value,
+                    }))
+                  }
+                />
+                <SettingSlider
+                  label="Repetition Penalty"
+                  value={controls.repetitionPenalty}
+                  min={1}
+                  max={1.2}
+                  step={0.01}
+                  formatValue={(value) => value.toFixed(2)}
+                  onValueChange={(value) =>
+                    setControls((current) => ({
+                      ...current,
+                      repetitionPenalty: value,
+                    }))
+                  }
+                />
+              </CardContent>
+            </Card>
+          </aside>
+        </div>
+      </div>
+
+      <Dialog open={pendingReference !== null} onOpenChange={(open) => !open && setPendingReference(null)}>
+        <DialogContent className="border-zinc-200 bg-white">
+          <DialogHeader>
+            <DialogTitle>
+              {pendingReference?.mode === 'create' ? 'Save Reference Text' : 'Edit Reference Text'}
+            </DialogTitle>
+            <DialogDescription>
+              {pendingReference
+                ? `Speaker ${speakerGroups.findIndex(
+                    (speakerGroup) => speakerGroup.id === pendingReference.speakerId,
+                  )}`
+                : ''}
+            </DialogDescription>
+          </DialogHeader>
+          <div className="space-y-3">
+            <div className="text-sm font-medium text-zinc-900">{pendingReference?.name}</div>
+            <Textarea
+              value={pendingReference?.text ?? ''}
+              onChange={(event) =>
+                setPendingReference((current) =>
+                  current
+                    ? {
+                        ...current,
+                        text: event.target.value,
+                      }
+                    : current,
+                )
+              }
+              placeholder="Enter reference text"
+              className="min-h-40 rounded-lg border-zinc-200 bg-white shadow-none focus-visible:ring-zinc-300"
+            />
+          </div>
+          <DialogFooter>
+            <Button type="button" variant="ghost" onClick={() => setPendingReference(null)}>
+              Cancel
+            </Button>
+            <Button
+              type="button"
+              variant="outline"
+              className="border-zinc-200 bg-white hover:bg-zinc-100"
+              onClick={savePendingReference}
+            >
+              Save
+            </Button>
+          </DialogFooter>
+        </DialogContent>
+      </Dialog>
+    </main>
+  )
+}
+
+export default App

awesome_webui/src/components/ui/alert.tsx

@@ -0,0 +1,35 @@
+import * as React from 'react'
+import { cva, type VariantProps } from 'class-variance-authority'
+
+import { cn } from '@/lib/utils'
+
+const alertVariants = cva('relative w-full rounded-lg border px-4 py-3 text-sm', {
+  variants: {
+    variant: {
+      default: 'bg-card text-card-foreground',
+      destructive: 'border-destructive/20 bg-destructive/5 text-destructive',
+      warning: 'border-amber-200 bg-amber-50 text-amber-900',
+    },
+  },
+  defaultVariants: {
+    variant: 'default',
+  },
+})
+
+function Alert({
+  className,
+  variant,
+  ...props
+}: React.ComponentProps<'div'> & VariantProps<typeof alertVariants>) {
+  return <div role="alert" className={cn(alertVariants({ variant }), className)} {...props} />
+}
+
+function AlertTitle({ className, ...props }: React.ComponentProps<'h5'>) {
+  return <h5 className={cn('mb-1 font-medium leading-none tracking-tight', className)} {...props} />
+}
+
+function AlertDescription({ className, ...props }: React.ComponentProps<'div'>) {
+  return <div className={cn('text-sm [&_p]:leading-relaxed', className)} {...props} />
+}
+
+export { Alert, AlertDescription, AlertTitle }

awesome_webui/src/components/ui/badge.tsx

@@ -0,0 +1,31 @@
+/* eslint-disable react-refresh/only-export-components */
+import * as React from 'react'
+import { cva, type VariantProps } from 'class-variance-authority'
+
+import { cn } from '@/lib/utils'
+
+const badgeVariants = cva(
+  'inline-flex items-center rounded-md border px-2 py-0.5 text-xs font-medium transition-colors',
+  {
+    variants: {
+      variant: {
+        default: 'border-transparent bg-primary text-primary-foreground',
+        secondary: 'border-transparent bg-secondary text-secondary-foreground',
+        outline: 'text-foreground',
+      },
+    },
+    defaultVariants: {
+      variant: 'default',
+    },
+  },
+)
+
+function Badge({
+  className,
+  variant,
+  ...props
+}: React.ComponentProps<'div'> & VariantProps<typeof badgeVariants>) {
+  return <div className={cn(badgeVariants({ variant }), className)} {...props} />
+}
+
+export { Badge, badgeVariants }

awesome_webui/src/components/ui/button.tsx

@@ -0,0 +1,44 @@
+/* eslint-disable react-refresh/only-export-components */
+import * as React from 'react'
+import { Slot } from '@radix-ui/react-slot'
+import { cva, type VariantProps } from 'class-variance-authority'
+
+import { cn } from '@/lib/utils'
+
+const buttonVariants = cva(
+  'inline-flex items-center justify-center gap-2 whitespace-nowrap rounded-md text-sm font-medium transition-colors disabled:pointer-events-none disabled:opacity-50 outline-none focus-visible:ring-2 focus-visible:ring-ring/70 focus-visible:ring-offset-2 focus-visible:ring-offset-background',
+  {
+    variants: {
+      variant: {
+        default: 'bg-primary text-primary-foreground hover:bg-primary/90',
+        destructive: 'bg-destructive text-destructive-foreground hover:bg-destructive/90',
+        outline: 'border bg-card hover:bg-accent hover:text-accent-foreground',
+        secondary: 'bg-secondary text-secondary-foreground hover:bg-secondary/80',
+        ghost: 'hover:bg-accent hover:text-accent-foreground',
+      },
+      size: {
+        default: 'h-9 px-4 py-2',
+        sm: 'h-8 rounded-md px-3 text-xs',
+        lg: 'h-11 rounded-md px-6',
+        icon: 'size-9',
+      },
+    },
+    defaultVariants: {
+      variant: 'default',
+      size: 'default',
+    },
+  },
+)
+
+type ButtonProps = React.ComponentProps<'button'> &
+  VariantProps<typeof buttonVariants> & {
+    asChild?: boolean
+  }
+
+function Button({ className, variant, size, asChild = false, ...props }: ButtonProps) {
+  const Comp = asChild ? Slot : 'button'
+
+  return <Comp className={cn(buttonVariants({ variant, size, className }))} {...props} />
+}
+
+export { Button, buttonVariants }

awesome_webui/src/components/ui/card.tsx

@@ -0,0 +1,31 @@
+import * as React from 'react'
+
+import { cn } from '@/lib/utils'
+
+function Card({ className, ...props }: React.ComponentProps<'div'>) {
+  return (
+    <div
+      data-slot="card"
+      className={cn('rounded-xl border bg-card text-card-foreground shadow-sm', className)}
+      {...props}
+    />
+  )
+}
+
+function CardHeader({ className, ...props }: React.ComponentProps<'div'>) {
+  return <div className={cn('flex flex-col space-y-1.5 p-6', className)} {...props} />
+}
+
+function CardTitle({ className, ...props }: React.ComponentProps<'div'>) {
+  return <div className={cn('text-base font-semibold leading-none tracking-tight', className)} {...props} />
+}
+
+function CardDescription({ className, ...props }: React.ComponentProps<'div'>) {
+  return <div className={cn('text-sm text-muted-foreground', className)} {...props} />
+}
+
+function CardContent({ className, ...props }: React.ComponentProps<'div'>) {
+  return <div className={cn('p-6 pt-0', className)} {...props} />
+}
+
+export { Card, CardContent, CardDescription, CardHeader, CardTitle }

awesome_webui/src/components/ui/collapsible.tsx

@@ -0,0 +1,7 @@
+import * as CollapsiblePrimitive from '@radix-ui/react-collapsible'
+
+const Collapsible = CollapsiblePrimitive.Root
+const CollapsibleTrigger = CollapsiblePrimitive.CollapsibleTrigger
+const CollapsibleContent = CollapsiblePrimitive.CollapsibleContent
+
+export { Collapsible, CollapsibleContent, CollapsibleTrigger }

awesome_webui/src/components/ui/dialog.tsx

@@ -0,0 +1,86 @@
+import * as React from 'react'
+import * as DialogPrimitive from '@radix-ui/react-dialog'
+import { X } from 'lucide-react'
+
+import { cn } from '@/lib/utils'
+
+const Dialog = DialogPrimitive.Root
+const DialogTrigger = DialogPrimitive.Trigger
+const DialogPortal = DialogPrimitive.Portal
+const DialogClose = DialogPrimitive.Close
+
+function DialogOverlay({
+  className,
+  ...props
+}: React.ComponentProps<typeof DialogPrimitive.Overlay>) {
+  return (
+    <DialogPrimitive.Overlay
+      className={cn('fixed inset-0 z-50 bg-black/40', className)}
+      {...props}
+    />
+  )
+}
+
+function DialogContent({
+  className,
+  children,
+  ...props
+}: React.ComponentProps<typeof DialogPrimitive.Content>) {
+  return (
+    <DialogPortal>
+      <DialogOverlay />
+      <DialogPrimitive.Content
+        className={cn(
+          'fixed left-1/2 top-1/2 z-50 grid w-full max-w-lg -translate-x-1/2 -translate-y-1/2 gap-4 rounded-xl border bg-background p-6 shadow-lg duration-200',
+          className,
+        )}
+        {...props}
+      >
+        {children}
+        <DialogClose className="absolute right-4 top-4 rounded-sm opacity-70 transition-opacity hover:opacity-100 focus-visible:ring-2 focus-visible:ring-ring/70">
+          <X className="size-4" />
+          <span className="sr-only">Close</span>
+        </DialogClose>
+      </DialogPrimitive.Content>
+    </DialogPortal>
+  )
+}
+
+function DialogHeader({ className, ...props }: React.ComponentProps<'div'>) {
+  return <div className={cn('flex flex-col space-y-1.5 text-left', className)} {...props} />
+}
+
+function DialogFooter({ className, ...props }: React.ComponentProps<'div'>) {
+  return <div className={cn('flex flex-col-reverse gap-2 sm:flex-row sm:justify-end', className)} {...props} />
+}
+
+function DialogTitle({ className, ...props }: React.ComponentProps<typeof DialogPrimitive.Title>) {
+  return (
+    <DialogPrimitive.Title
+      className={cn('text-lg font-semibold leading-none tracking-tight', className)}
+      {...props}
+    />
+  )
+}
+
+function DialogDescription({
+  className,
+  ...props
+}: React.ComponentProps<typeof DialogPrimitive.Description>) {
+  return (
+    <DialogPrimitive.Description
+      className={cn('text-sm text-muted-foreground', className)}
+      {...props}
+    />
+  )
+}
+
+export {
+  Dialog,
+  DialogContent,
+  DialogDescription,
+  DialogFooter,
+  DialogHeader,
+  DialogTitle,
+  DialogTrigger,
+}

awesome_webui/src/components/ui/label.tsx

@@ -0,0 +1,15 @@
+import * as React from 'react'
+import * as LabelPrimitive from '@radix-ui/react-label'
+
+import { cn } from '@/lib/utils'
+
+function Label({ className, ...props }: React.ComponentProps<typeof LabelPrimitive.Root>) {
+  return (
+    <LabelPrimitive.Root
+      className={cn('text-sm font-medium leading-none', className)}
+      {...props}
+    />
+  )
+}
+
+export { Label }

awesome_webui/src/components/ui/scroll-area.tsx

@@ -0,0 +1,43 @@
+import * as React from 'react'
+import * as ScrollAreaPrimitive from '@radix-ui/react-scroll-area'
+
+import { cn } from '@/lib/utils'
+
+function ScrollArea({
+  className,
+  children,
+  ...props
+}: React.ComponentProps<typeof ScrollAreaPrimitive.Root>) {
+  return (
+    <ScrollAreaPrimitive.Root className={cn('relative overflow-hidden', className)} {...props}>
+      <ScrollAreaPrimitive.Viewport className="h-full w-full rounded-[inherit]">
+        {children}
+      </ScrollAreaPrimitive.Viewport>
+      <ScrollBar />
+      <ScrollAreaPrimitive.Corner />
+    </ScrollAreaPrimitive.Root>
+  )
+}
+
+function ScrollBar({
+  className,
+  orientation = 'vertical',
+  ...props
+}: React.ComponentProps<typeof ScrollAreaPrimitive.ScrollAreaScrollbar>) {
+  return (
+    <ScrollAreaPrimitive.ScrollAreaScrollbar
+      orientation={orientation}
+      className={cn(
+        'flex touch-none select-none p-px transition-colors',
+        orientation === 'vertical' && 'h-full w-2.5 border-l border-l-transparent',
+        orientation === 'horizontal' && 'h-2.5 flex-col border-t border-t-transparent',
+        className,
+      )}
+      {...props}
+    >
+      <ScrollAreaPrimitive.ScrollAreaThumb className="relative flex-1 rounded-full bg-border" />
+    </ScrollAreaPrimitive.ScrollAreaScrollbar>
+  )
+}
+
+export { ScrollArea, ScrollBar }

awesome_webui/src/components/ui/separator.tsx

@@ -0,0 +1,26 @@
+import * as React from 'react'
+import * as SeparatorPrimitive from '@radix-ui/react-separator'
+
+import { cn } from '@/lib/utils'
+
+function Separator({
+  className,
+  orientation = 'horizontal',
+  decorative = true,
+  ...props
+}: React.ComponentProps<typeof SeparatorPrimitive.Root>) {
+  return (
+    <SeparatorPrimitive.Root
+      decorative={decorative}
+      orientation={orientation}
+      className={cn(
+        'shrink-0 bg-border',
+        orientation === 'horizontal' ? 'h-px w-full' : 'h-full w-px',
+        className,
+      )}
+      {...props}
+    />
+  )
+}
+
+export { Separator }

awesome_webui/src/components/ui/slider.tsx

@@ -0,0 +1,23 @@
+import * as React from 'react'
+import * as SliderPrimitive from '@radix-ui/react-slider'
+
+import { cn } from '@/lib/utils'
+
+function Slider({
+  className,
+  ...props
+}: React.ComponentProps<typeof SliderPrimitive.Root>) {
+  return (
+    <SliderPrimitive.Root
+      className={cn('relative flex w-full touch-none select-none items-center', className)}
+      {...props}
+    >
+      <SliderPrimitive.Track className="relative h-1.5 w-full grow overflow-hidden rounded-full bg-muted">
+        <SliderPrimitive.Range className="absolute h-full bg-primary" />
+      </SliderPrimitive.Track>
+      <SliderPrimitive.Thumb className="block size-4 rounded-full border border-primary/20 bg-background shadow-sm transition-colors focus-visible:ring-2 focus-visible:ring-ring/70 focus-visible:ring-offset-2 focus-visible:ring-offset-background disabled:pointer-events-none disabled:opacity-50" />
+    </SliderPrimitive.Root>
+  )
+}
+
+export { Slider }

awesome_webui/src/components/ui/switch.tsx

@@ -0,0 +1,27 @@
+import * as React from 'react'
+import * as SwitchPrimitive from '@radix-ui/react-switch'
+
+import { cn } from '@/lib/utils'
+
+function Switch({
+  className,
+  ...props
+}: React.ComponentProps<typeof SwitchPrimitive.Root>) {
+  return (
+    <SwitchPrimitive.Root
+      className={cn(
+        'peer inline-flex h-6 w-11 shrink-0 cursor-pointer items-center rounded-full border border-transparent bg-input shadow-xs transition-colors outline-none focus-visible:ring-2 focus-visible:ring-ring/70 focus-visible:ring-offset-2 focus-visible:ring-offset-background data-[state=checked]:bg-primary data-[state=unchecked]:bg-muted-foreground/30 disabled:cursor-not-allowed disabled:opacity-50',
+        className,
+      )}
+      {...props}
+    >
+      <SwitchPrimitive.Thumb
+        className={cn(
+          'pointer-events-none block size-5 rounded-full bg-background shadow-sm ring-0 transition-transform data-[state=checked]:translate-x-5 data-[state=unchecked]:translate-x-0',
+        )}
+      />
+    </SwitchPrimitive.Root>
+  )
+}
+
+export { Switch }

awesome_webui/src/components/ui/textarea.tsx

@@ -0,0 +1,17 @@
+import * as React from 'react'
+
+import { cn } from '@/lib/utils'
+
+function Textarea({ className, ...props }: React.ComponentProps<'textarea'>) {
+  return (
+    <textarea
+      className={cn(
+        'flex min-h-16 w-full rounded-lg border border-input bg-background px-3 py-2 text-sm shadow-xs outline-none transition-[color,box-shadow] placeholder:text-muted-foreground focus-visible:ring-2 focus-visible:ring-ring/70 disabled:cursor-not-allowed disabled:opacity-50',
+        className,
+      )}
+      {...props}
+    />
+  )
+}
+
+export { Textarea }

awesome_webui/src/components/ui/toggle-group.tsx

@@ -0,0 +1,49 @@
+import * as React from 'react'
+import * as ToggleGroupPrimitive from '@radix-ui/react-toggle-group'
+import { cva, type VariantProps } from 'class-variance-authority'
+
+import { cn } from '@/lib/utils'
+
+const toggleGroupItemVariants = cva(
+  'inline-flex items-center justify-center rounded-md text-sm font-medium transition-colors hover:bg-accent hover:text-accent-foreground focus-visible:ring-2 focus-visible:ring-ring/70 focus-visible:ring-offset-2 focus-visible:ring-offset-background disabled:pointer-events-none disabled:opacity-50 data-[state=on]:bg-primary data-[state=on]:text-primary-foreground border border-border bg-card',
+  {
+    variants: {
+      size: {
+        default: 'h-9 px-3',
+        sm: 'h-8 px-2.5 text-xs',
+        lg: 'h-10 px-4',
+      },
+    },
+    defaultVariants: {
+      size: 'default',
+    },
+  },
+)
+
+function ToggleGroup({
+  className,
+  ...props
+}: React.ComponentProps<typeof ToggleGroupPrimitive.Root>) {
+  return (
+    <ToggleGroupPrimitive.Root
+      className={cn('flex items-center gap-2', className)}
+      {...props}
+    />
+  )
+}
+
+function ToggleGroupItem({
+  className,
+  size,
+  ...props
+}: React.ComponentProps<typeof ToggleGroupPrimitive.Item> &
+  VariantProps<typeof toggleGroupItemVariants>) {
+  return (
+    <ToggleGroupPrimitive.Item
+      className={cn(toggleGroupItemVariants({ size }), className)}
+      {...props}
+    />
+  )
+}
+
+export { ToggleGroup, ToggleGroupItem }

awesome_webui/src/index.css

@@ -0,0 +1,71 @@
+@import "tailwindcss";
+
+:root {
+  --background: 0 0% 96%;
+  --foreground: 240 10% 3.9%;
+  --card: 0 0% 100%;
+  --card-foreground: 240 10% 3.9%;
+  --popover: 0 0% 100%;
+  --popover-foreground: 240 10% 3.9%;
+  --primary: 240 5.9% 10%;
+  --primary-foreground: 0 0% 98%;
+  --secondary: 240 4.8% 95.9%;
+  --secondary-foreground: 240 5.9% 10%;
+  --muted: 240 4.8% 95.9%;
+  --muted-foreground: 240 3.8% 46.1%;
+  --accent: 240 4.8% 95.9%;
+  --accent-foreground: 240 5.9% 10%;
+  --destructive: 0 72.2% 50.6%;
+  --destructive-foreground: 0 0% 98%;
+  --border: 240 5.9% 88%;
+  --input: 240 5.9% 88%;
+  --ring: 240 5% 64.9%;
+  --radius: 0.75rem;
+}
+
+@theme inline {
+  --color-background: hsl(var(--background));
+  --color-foreground: hsl(var(--foreground));
+  --color-card: hsl(var(--card));
+  --color-card-foreground: hsl(var(--card-foreground));
+  --color-popover: hsl(var(--popover));
+  --color-popover-foreground: hsl(var(--popover-foreground));
+  --color-primary: hsl(var(--primary));
+  --color-primary-foreground: hsl(var(--primary-foreground));
+  --color-secondary: hsl(var(--secondary));
+  --color-secondary-foreground: hsl(var(--secondary-foreground));
+  --color-muted: hsl(var(--muted));
+  --color-muted-foreground: hsl(var(--muted-foreground));
+  --color-accent: hsl(var(--accent));
+  --color-accent-foreground: hsl(var(--accent-foreground));
+  --color-destructive: hsl(var(--destructive));
+  --color-destructive-foreground: hsl(var(--destructive-foreground));
+  --color-border: hsl(var(--border));
+  --color-input: hsl(var(--input));
+  --color-ring: hsl(var(--ring));
+  --radius-sm: calc(var(--radius) - 4px);
+  --radius-md: calc(var(--radius) - 2px);
+  --radius-lg: var(--radius);
+  --radius-xl: calc(var(--radius) + 4px);
+}
+
+@layer base {
+  * {
+    @apply border-border;
+  }
+
+  html {
+    min-width: 320px;
+  }
+
+  body {
+    @apply bg-background text-foreground antialiased;
+    font-family: "Inter", "Avenir Next", "Segoe UI", sans-serif;
+  }
+
+  button,
+  input,
+  textarea {
+    font: inherit;
+  }
+}

awesome_webui/src/lib/utils.ts

@@ -0,0 +1,6 @@
+import { clsx, type ClassValue } from "clsx"
+import { twMerge } from "tailwind-merge"
+
+export function cn(...inputs: ClassValue[]) {
+    return twMerge(clsx(inputs))
+}

awesome_webui/src/main.tsx

@@ -0,0 +1,10 @@
+import { StrictMode } from 'react'
+import { createRoot } from 'react-dom/client'
+import './index.css'
+import App from './App.tsx'
+
+createRoot(document.getElementById('root')!).render(
+  <StrictMode>
+    <App />
+  </StrictMode>,
+)

awesome_webui/tsconfig.app.json

@@ -0,0 +1,38 @@
+{
+  "compilerOptions": {
+    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
+    "target": "ES2022",
+    "useDefineForClassFields": true,
+    "lib": [
+      "ES2022",
+      "DOM",
+      "DOM.Iterable"
+    ],
+    "module": "ESNext",
+    "types": [
+      "vite/client"
+    ],
+    "skipLibCheck": true,
+    "baseUrl": ".",
+    "paths": {
+      "@/*": [
+        "./src/*"
+      ]
+    },
+    "moduleResolution": "bundler",
+    "allowImportingTsExtensions": true,
+    "verbatimModuleSyntax": true,
+    "moduleDetection": "force",
+    "noEmit": true,
+    "jsx": "react-jsx",
+    "strict": true,
+    "noUnusedLocals": true,
+    "noUnusedParameters": true,
+    "erasableSyntaxOnly": true,
+    "noFallthroughCasesInSwitch": true,
+    "noUncheckedSideEffectImports": true
+  },
+  "include": [
+    "src"
+  ]
+}

awesome_webui/tsconfig.json

@@ -0,0 +1,7 @@
+{
+  "files": [],
+  "references": [
+    { "path": "./tsconfig.app.json" },
+    { "path": "./tsconfig.node.json" }
+  ]
+}

awesome_webui/tsconfig.node.json

@@ -0,0 +1,34 @@
+{
+  "compilerOptions": {
+    "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
+    "target": "ES2023",
+    "lib": [
+      "ES2023"
+    ],
+    "module": "ESNext",
+    "types": [
+      "node"
+    ],
+    "skipLibCheck": true,
+    "baseUrl": ".",
+    "paths": {
+      "@/*": [
+        "./src/*"
+      ]
+    },
+    "moduleResolution": "bundler",
+    "allowImportingTsExtensions": true,
+    "verbatimModuleSyntax": true,
+    "moduleDetection": "force",
+    "noEmit": true,
+    "strict": true,
+    "noUnusedLocals": true,
+    "noUnusedParameters": true,
+    "erasableSyntaxOnly": true,
+    "noFallthroughCasesInSwitch": true,
+    "noUncheckedSideEffectImports": true
+  },
+  "include": [
+    "vite.config.ts"
+  ]
+}

awesome_webui/vite.config.ts

@@ -0,0 +1,113 @@
+import fs from 'node:fs'
+import { defineConfig, type Plugin } from 'vite'
+import react from '@vitejs/plugin-react-swc'
+import tailwindcss from '@tailwindcss/vite'
+import path from 'node:path'
+
+function inlineEntryAssets(): Plugin {
+  let resolvedOutDir = ''
+
+  return {
+    name: 'inline-entry-assets',
+    apply: 'build',
+    configResolved(config) {
+      resolvedOutDir = path.resolve(config.root, config.build.outDir)
+    },
+    closeBundle() {
+      const indexHtmlPath = path.join(resolvedOutDir, 'index.html')
+      if (!fs.existsSync(indexHtmlPath)) {
+        return
+      }
+
+      const filesToDelete = new Set<string>()
+      const escapeInlineScript = (code: string) => code.replace(/<\/script/gi, '<\\/script')
+      const escapeInlineStyle = (code: string) => code.replace(/<\/style/gi, '<\\/style')
+      const normalizeFileName = (assetPath: string) =>
+        assetPath.replace(/^\//, '').replace(/^\.\//, '')
+      const readBuiltAsset = (assetPath: string) => {
+        const fileName = normalizeFileName(assetPath)
+        const absolutePath = path.join(resolvedOutDir, fileName)
+        if (!fs.existsSync(absolutePath)) {
+          return null
+        }
+
+        filesToDelete.add(absolutePath)
+        return fs.readFileSync(absolutePath, 'utf8')
+      }
+
+      let html = fs.readFileSync(indexHtmlPath, 'utf8')
+
+      html = html.replace(
+        /<link rel="modulepreload"[^>]+href="([^"]+)"[^>]*>/g,
+        (_fullMatch, href: string) => {
+          const absolutePath = path.join(resolvedOutDir, normalizeFileName(href))
+          if (fs.existsSync(absolutePath)) {
+            filesToDelete.add(absolutePath)
+          }
+          return ''
+        },
+      )
+
+      html = html.replace(
+        /<link rel="stylesheet"[^>]+href="([^"]+)"[^>]*>/g,
+        (fullMatch, href: string) => {
+          const assetSource = readBuiltAsset(href)
+          if (!assetSource) {
+            return fullMatch
+          }
+
+          return `<style>${escapeInlineStyle(assetSource)}</style>`
+        },
+      )
+
+      html = html.replace(
+        /<script type="module"[^>]+src="([^"]+)"[^>]*><\/script>/g,
+        (fullMatch, src: string) => {
+          const chunkCode = readBuiltAsset(src)
+          if (!chunkCode) {
+            return fullMatch
+          }
+
+          return `<script type="module">${escapeInlineScript(chunkCode)}</script>`
+        },
+      )
+
+      fs.writeFileSync(indexHtmlPath, html)
+
+      for (const filePath of filesToDelete) {
+        fs.rmSync(filePath, { force: true })
+      }
+
+      fs.rmSync(path.join(resolvedOutDir, 'vite.svg'), { force: true })
+      fs.rmSync(path.join(resolvedOutDir, 'assets'), { recursive: true, force: true })
+    },
+  }
+}
+
+// https://vite.dev/config/
+export default defineConfig({
+  plugins: [react(), tailwindcss(), inlineEntryAssets()],
+  publicDir: false,
+  resolve: {
+    alias: {
+      '@': path.resolve(__dirname, './src'),
+    },
+  },
+  build: {
+    assetsInlineLimit: Number.MAX_SAFE_INTEGER,
+    cssCodeSplit: false,
+    modulePreload: false,
+    rollupOptions: {
+      output: {
+        inlineDynamicImports: true,
+      },
+    },
+  },
+  server: {
+    proxy: {
+      '/v1': 'http://localhost:8888',
+      '/v2': 'http://localhost:8888',
+      '/health': 'http://localhost:8888',
+    },
+  },
+})

docs/README.ar.md

@@ -36,127 +36,129 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
 
 > [!IMPORTANT]
 > **إشعار الترخيص**
-> يتم إصدار هذا المشروع وأوزان النماذج المرتبطة به بموجب رخصة **[FISH AUDIO RESEARCH LICENSE](../LICENSE)**. يرجى الرجوع إلى [LICENSE](../LICENSE) لمزيد من التفاصيل.
+> يتم إصدار قاعدة الأكواد هذه وأوزان النماذج المرتبطة بها تحت **[FISH AUDIO RESEARCH LICENSE](../LICENSE)**. يرجى الرجوع إلى ملف [LICENSE](../LICENSE) لمزيد من التفاصيل.
+
 
 > [!WARNING]
 > **إخلاء المسؤولية القانونية**
-> نحن لا نتحمل أي مسؤولية عن أي استخدام غير قانوني لهذا المشروع. يرجى الرجوع إلى القوانين المحلية المتعلقة بحقوق الطبع والنشر الرقمية (DMCA) والقوانين الأخرى ذات الصلة.
+> نحن لا نتحمل أي مسؤولية عن أي استخدام غير قانوني لقاعدة الأكواد. يرجى الرجوع إلى القوانين المحلية المتعلقة بـ DMCA والقوانين الأخرى ذات الصلة.
 
-## البدء السريع
+## البداية السريعة
 
-### ابدأ من الوثائق
+### روابط التوثيق
 
-هذه هي الوثائق الرسمية لـ Fish Audio S2، ويمكنك البدء مباشرة عبر الروابط التالية:
+هذا هو التوثيق الرسمي لـ Fish Audio S2، يرجى اتباع التعليمات للبدء بسهولة.
 
 - [التثبيت](https://speech.fish.audio/ar/install/)
-- [الاستدلال عبر سطر الأوامر](https://speech.fish.audio/ar/inference/)
-- [استدلال WebUI](https://speech.fish.audio/ar/inference/)
-- [الاستدلال عبر الخادم](https://speech.fish.audio/ar/server/)
-- [إعداد Docker](https://speech.fish.audio/ar/install/)
+- [الاستدلال عبر خط الأوامر](https://speech.fish.audio/ar/inference/)
+- [الاستدلال عبر واجهة الويب](https://speech.fish.audio/ar/inference/)
+- [استدلال الخادم](https://speech.fish.audio/ar/server/)
+- [نشر Docker](https://speech.fish.audio/ar/install/)
 
 > [!IMPORTANT]
-> **بالنسبة لخادم SGLang، راجع [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md).**
+> **إذا كنت ترغب في استخدام خادم SGLang، فيرجى الرجوع إلى [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md).**
 
-### دليل وكلاء LLM
+### دليل وكيل LLM
 
 ```
-قم بتثبيت وإعداد Fish Audio S2 باتباع التعليمات في https://speech.fish.audio/ar/install/ .
+يرجى قراءة https://speech.fish.audio/ar/install/ أولاً، وتثبيت وتكوين Fish Audio S2 وفقاً للوثائق.
 ```
 
-## Fish Audio S2
-**أفضل نظام لتحويل النص إلى كلام بين الأنظمة مفتوحة المصدر ومغلقة المصدر**
+## Fish Audio S2 Pro
+**نظام تحويل النص إلى كلام (TTS) متعدد اللغات الرائد في الصناعة، والذي يعيد تعريف حدود توليد الصوت.**
 
-Fish Audio S2 هو أحدث نموذج من [Fish Audio](https://fish.audio/). تم تدريبه على أكثر من 10 ملايين ساعة صوتية عبر نحو 50 لغة، ويجمع بين المواءمة بالتعلم المعزز وبنية Dual-Autoregressive لإنتاج كلام طبيعي وواقعي وغني بالتعبير العاطفي.
+Fish Audio S2 Pro هو أحدث طراز متعدد الوسائط تم تطويره بواسطة [Fish Audio](https://fish.audio/). تم تدريبه على أكثر من **10 ملايين ساعة** من البيانات الصوتية الهائلة، التي تغطي أكثر من **80 لغة** حول العالم. من خلال بنية **ثنائية الانحدار الذاتي (Dual-AR)** المبتكرة وتقنية توافق التعلم التعزيزي (RL)، يمكن لـ S2 Pro توليد كلام يتمتع بإحساس طبيعي وواقعي وعمق عاطفي كبير، مما يجعله رائداً في المنافسة بين الأنظمة المفتوحة والمغلقة المصدر.
 
-يدعم S2 التحكم الدقيق في النبرة والعاطفة داخل النص نفسه باستخدام وسوم باللغة الطبيعية مثل `[laugh]` و`[whispers]` و`[super happy]`، كما يدعم بشكل أصيل توليد متحدثين متعددين وحوارات متعددة الأدوار.
+تكمن القوة الضاربة لـ S2 Pro في دعمه للتحكم الدقيق للغاية في النبرة والعاطفة على مستوى **ما دون الكلمة (Sub-word Level)** من خلال وسوم اللغة الطبيعية (مثل `[whisper]` و `[excited]` و `[angry]`) ، مع دعم أصلي لتوليد متحدثين متعددين وحوارات متعددة الجولات بسياق طويل جداً.
 
-يمكنك تجربة النموذج مباشرة عبر [موقع Fish Audio](https://fish.audio/)، وقراءة المزيد في [منشور المدونة](https://fish.audio/blog/fish-audio-open-sources-s2/).
+تفضل بزيارة [موقع Fish Audio الرسمي](https://fish.audio/) الآن لتجربة العرض المباشر، أو اقرأ [تقريرنا الفني](https://arxiv.org/abs/2603.08823) و[مقال المدونة](https://fish.audio/blog/fish-audio-open-sources-s2/) للتعرف على المزيد.
 
-### إصدارات النموذج
+### متغيرات النموذج
 
 | النموذج | الحجم | التوفر | الوصف |
 |------|------|-------------|-------------|
-| S2-Pro | 4B معلمة | [HuggingFace](https://huggingface.co/fishaudio/s2-pro) | نموذج رائد كامل الميزات بأعلى مستوى من الجودة والاستقرار |
+| S2-Pro | 4 مليار معلمة | [HuggingFace](https://huggingface.co/fishaudio/s2-pro) | النموذج الرائد كامل الميزات، مع أعلى جودة واستقرار |
 
-يمكن العثور على مزيد من التفاصيل في [التقرير التقني](https://arxiv.org/abs/2411.01156).
+لمزيد من التفاصيل حول النماذج، يرجى مراجعة [التقرير الفني](https://arxiv.org/abs/2411.01156).
 
-## نتائج القياس المعياري
+## نتائج الاختبارات المرجعية (Benchmarks)
 
-| المعيار | Fish Audio S2 |
+| الاختبار | Fish Audio S2 |
 |------|------|
 | Seed-TTS Eval — WER (الصينية) | **0.54%** (الأفضل إجمالاً) |
 | Seed-TTS Eval — WER (الإنجليزية) | **0.99%** (الأفضل إجمالاً) |
-| Audio Turing Test (مع التعليمات) | **0.515** المتوسط البعدي |
+| Audio Turing Test (مع التعليمات) | **0.515** متوسط خلفي (Posterior mean) |
 | EmergentTTS-Eval — معدل الفوز | **81.88%** (الأعلى إجمالاً) |
 | Fish Instruction Benchmark — TAR | **93.3%** |
 | Fish Instruction Benchmark — الجودة | **4.51 / 5.0** |
-| متعدد اللغات (MiniMax Testset) — أفضل WER | **11 من 24** لغة |
-| متعدد اللغات (MiniMax Testset) — أفضل SIM | **17 من 24** لغة |
+| متعدد اللغات (MiniMax Testset) — أفضل WER | **11** لغة من أصل **24** |
+| متعدد اللغات (MiniMax Testset) — أفضل SIM | **17** لغة من أصل **24** |
 
-في Seed-TTS Eval، حقق S2 أقل WER بين جميع النماذج التي تم تقييمها، بما في ذلك الأنظمة المغلقة: Qwen3-TTS ‏(0.77/1.24)، وMiniMax Speech-02 ‏(0.99/1.90)، وSeed-TTS ‏(1.12/2.25). وفي Audio Turing Test، تفوقت قيمة 0.515 على Seed-TTS ‏(0.417) بنسبة 24% وعلى MiniMax-Speech ‏(0.387) بنسبة 33%. وفي EmergentTTS-Eval، حقق S2 نتائج قوية بشكل خاص في الخصائص شبه اللغوية (91.61%)، والأسئلة (84.41%)، والتعقيد النحوي (83.39%).
+في تقييم Seed-TTS، حقق S2 أقل معدل خطأ في الكلمات (WER) بين جميع النماذج التي تم تقييمها (بما في ذلك الأنظمة مغلقة المصدر): Qwen3-TTS (0.77/1.24)، و MiniMax Speech-02 (0.99/1.90)، و Seed-TTS (1.12/2.25). وفي اختبار Audio Turing Test، سجل S2 قيمة 0.515 بزيادة قدرها 24% مقارنة بـ Seed-TTS (0.417) و 33% مقارنة بـ MiniMax-Speech (0.387). وفي EmergentTTS-Eval، تميز S2 بشكل خاص في أبعاد مثل اللغويات المصاحبة (معدل فوز 91.61%)، والجمل الاستفهامية (84.41%)، والتعقيد النحوي (83.39%).
 
 ## أبرز المميزات
 
 <img src="./assets/totalability.png" width=200%>
 
-### تحكم مضمّن دقيق عبر اللغة الطبيعية
-
-يتيح Fish Audio S2 تحكمًا موضعيًا في توليد الكلام من خلال تضمين تعليمات باللغة الطبيعية مباشرة عند مواقع كلمات أو عبارات محددة داخل النص. وبدلًا من الاعتماد على مجموعة ثابتة من الوسوم المُعرّفة مسبقًا، يقبل S2 أوصافًا نصية حرة مثل [whisper in small voice] أو [professional broadcast tone] أو [pitch up]، مما يتيح تحكمًا مفتوحًا في التعبير على مستوى الكلمة.
-
-### بنية Dual-Autoregressive
+### تحكم دقيق للغاية عبر اللغة الطبيعية
 
-يعتمد S2 على Transformer أحادي الاتجاه (Decoder-only) مع مُرمّز صوتي قائم على RVQ (عدد 10 codebooks وبمعدل إطارات يقارب 21 هرتز). وتُقسّم بنية Dual-AR عملية التوليد إلى مرحلتين:
+يمنح S2 Pro الصوت "روحاً" لا مثيل لها. من خلال صيغة `[tag]` البسيطة، يمكنك تضمين تعليمات عاطفية بدقة في أي موضع من النص.
+- **دعم أكثر من 15,000 وسم فريد**: لا يقتصر على الإعدادات المسبقة الثابتة، بل يدعم **أوصاف النص الحر**. يمكنك تجربة `[whisper in small voice]` (همس بصوت منخفض)، أو `[professional broadcast tone]` (نبرة إذاعية احترافية)، أو `[pitch up]` (رفع طبقة الصوت).
+- **مكتبة عواطف غنية**:
+  `[pause]` `[emphasis]` `[laughing]` `[inhale]` `[chuckle]` `[tsk]` `[singing]` `[excited]` `[laughing tone]` `[interrupting]` `[chuckling]` `[excited tone]` `[volume up]` `[echo]` `[angry]` `[low volume]` `[sigh]` `[low voice]` `[whisper]` `[screaming]` `[shouting]` `[loud]` `[surprised]` `[short pause]` `[exhale]` `[delight]` `[panting]` `[audience laughter]` `[with strong accent]` `[volume down]` `[clearing throat]` `[sad]` `[moaning]` `[shocked]`
 
-- **Slow AR** يعمل على المحور الزمني ويتنبأ بالـ semantic codebook الأساسي.
-- **Fast AR** يولّد الـ 9 residual codebooks المتبقية في كل خطوة زمنية لإعادة بناء التفاصيل الصوتية الدقيقة.
+### بنية مبتكرة ثنائية الانحدار الذاتي (Dual-Autoregressive)
 
-هذا التصميم غير المتماثل (4B معلمة على المحور الزمني و400M على محور العمق) يرفع كفاءة الاستدلال مع الحفاظ على جودة الصوت.
+يعتمد S2 Pro بنية Dual-AR بنظام "رئيسي-تابع"، تتكون من Decoder-only Transformer وترميز صوتي RVQ (10 قواميس أكواد، بمعدل إطارات يبلغ حوالي 21 هرتز):
 
-### المواءمة بالتعلم المعزز
+- **Slow AR (4 مليار معلمة)**: يعمل على طول المحور الزمني، ويتنبأ بقاموس الأكواد الدلالي الأساسي.
+- **Fast AR (400 مليون معلمة)**: يولد الـ 9 قواميس المتبقية في كل خطوة زمنية، لاستعادة أدق التفاصيل الصوتية ببراعة.
 
-يستخدم S2 خوارزمية Group Relative Policy Optimization (GRPO) للمواءمة بعد التدريب. ويتم إعادة استخدام نفس النماذج التي استُخدمت لتصفية بيانات التدريب وتعليقها كنماذج مكافأة في التعلم المعزز مباشرة، مما يلغي عدم تطابق التوزيع بين بيانات ما قبل التدريب وأهداف ما بعد التدريب. وتجمع إشارة المكافأة بين الدقة الدلالية، والالتزام بالتعليمات، وتقييم التفضيل الصوتي، وتشابه النبرة.
+يحقق هذا التصغير غير المتماثل أقصى درجات الدقة الصوتية مع زيادة سرعة الاستدلال بشكل كبير.
 
-### البث الإنتاجي عبر SGLang
+### توافق التعلم التعزيزي (RL Alignment)
 
-لأن بنية Dual-AR متماثلة بنيويًا مع نماذج LLM autoregressive القياسية، فإن S2 يرث مباشرة تحسينات الخدمة الأصلية في SGLang، بما في ذلك: continuous batching، وpaged KV cache، وCUDA graph replay، وprefix caching المعتمد على RadixAttention.
+يستخدم S2 Pro تقنية **Group Relative Policy Optimization (GRPO)** للتوافق بعد التدريب. نستخدم نفس مجموعة النماذج المستخدمة في تنظيف البيانات وتصنيفها مباشرة كنماذج مكافأة (Reward Model)، مما يحل بشكل مثالي مشكلة عدم التطابق بين توزيع بيانات ما قبل التدريب وأهداف ما بعد التدريب.
+- **إشارات مكافأة متعددة الأبعاد**: تقييم شامل للدقة الدلالية، والقدرة على اتباع التعليمات، وتسجيل التفضيل الصوتي، وتماثل نبرة الصوت، لضمان أن كل ثانية من الكلام المولد تتوافق مع الحدس البشري.
 
-على بطاقة NVIDIA H200 واحدة:
+### أداء استدلال تدفقي فائق (يعتمد على SGLang)
 
-- **عامل الزمن الحقيقي (RTF):** 0.195
-- **الزمن حتى أول مقطع صوتي:** حوالي 100 مللي ثانية
-- **معدل المعالجة:** أكثر من 3,000 acoustic tokens/s مع الحفاظ على RTF أقل من 0.5
+نظراً لأن بنية Dual-AR تتماثل هيكلياً مع بنية LLM القياسية، فإن S2 Pro يدعم أصلاً جميع ميزات تسريع الاستدلال في SGLang، بما في ذلك الدفعات المستمرة (Continuous Batching)، و Paged KV Cache، و CUDA Graph، والتخزين المؤقت للبادئة القائم على RadixAttention.
 
-### دعم لغات متعددة
+**أداء وحدة معالجة رسومات NVIDIA H200 واحدة:**
+- **عامل الوقت الحقيقي (RTF)**: 0.195
+- **تأخر الصوت الأول (TTFA)**: حوالي 100 مللي ثانية
+- **إنتاجية فائقة السرعة**: تصل إلى 3000+ وسم صوتي/ثانية مع الحفاظ على RTF < 0.5
 
-يدعم Fish Audio S2 تحويل النص إلى كلام بجودة عالية ولغات متعددة دون الحاجة إلى رموز صوتية أو معالجة مسبقة خاصة بكل لغة. بما في ذلك:
+### دعم قوي للغات المتعددة
 
-**الإنجليزية، الصينية، اليابانية، الكورية، العربية، الألمانية، الفرنسية...**
+يدعم S2 Pro أكثر من 80 لغة، مما يتيح تركيباً عالياً الجودة دون الحاجة إلى وحدات صوتية (phonemes) أو معالجة محددة لكل لغة:
 
-**وأكثر من ذلك بكثير!**
+- **المستوى الأول (Tier 1)**: اليابانية (ja)، الإنجليزية (en)، الصينية (zh)
+- **المستوى الثاني (Tier 2)**: الكورية (ko)، الإسبانية (es)، البرتغالية (pt)، العربية (ar)، الروسية (ru)، الفرنسية (fr)، الألمانية (de)
+- **تغطية عالمية**: sv, it, tr, no, nl, cy, eu, ca, da, gl, ta, hu, fi, pl, et, hi, la, ur, th, vi, jw, bn, yo, xsl, cs, sw, nn, he, ms, uk, id, kk, bg, lv, my, tl, sk, ne, fa, af, el, bo, hr, ro, sn, mi, yi, am, be, km, is, az, sd, br, sq, ps, mn, ht, ml, sr, sa, te, ka, bs, pa, lt, kn, si, hy, mr, as, gu, fo والمزيد.
 
-القائمة في توسع مستمر، تحقق من [Fish Audio](https://fish.audio/) لمعرفة أحدث الإصدارات.
-
-### توليد أصلي لمتحدثين متعددين
+### توليد متحدثين متعددين أصلي
 
 <img src="./assets/chattemplate.png" width=200%>
 
-يسمح Fish Audio S2 للمستخدمين برفع صوت مرجعي يحتوي على متحدثين متعددين، وسيتعامل النموذج مع ميزات كل متحدث عبر رمز `<|speaker:i|>`. يمكنك بعد ذلك التحكم في أداء النموذج باستخدام رمز معرف المتحدث، مما يسمح بتوليد واحد يتضمن متحدثين متعددين. لم تعد بحاجة لرفع ملفات مرجعية منفصلة لكل متحدث.
+يسمح Fish Audio S2 للمستخدمين بتحميل عينة مرجعية تحتوي على متحدثين متعددين، وسيقوم النموذج بمعالجة ميزات كل متحدث عبر وسم `<|speaker:i|>`. بعد ذلك، يمكنك التحكم في أداء النموذج عبر وسم معرف المتحدث، مما يتيح لتوليد واحد أن يتضمن متحدثين متعددين. لم تعد هناك حاجة لتحميل عينة مرجعية منفصلة وتوليد صوت لكل متحدث على حدة كما كان في السابق.
 
-### توليد حوارات متعددة الأدوار
+### توليد حوارات متعددة الجولات
 
-بفضل توسيع سياق النموذج، يمكن لنموذجنا الآن استخدام المعلومات السابقة لتحسين التعبير في المحتوى المولد لاحقاً، مما يزيد من طبيعية المحتوى.
+بفضل توسيع سياق النموذج، يمكن لنموذجنا الآن الاستفادة من المعلومات السابقة لتحسين التعبير في المحتوى المولد لاحقاً، مما يعزز من طبيعية المحتوى.
 
-### استنساخ صوت سريع
+### استنساخ الصوت السريع
 
-يدعم Fish Audio S2 استنساخ الصوت بدقة باستخدام عينة مرجعية قصيرة (عادةً 10-30 ثانية). يلتقط النموذج نبرة الصوت، وأسلوب التحدث، والميول العاطفية، مما ينتج أصواتاً مستنسخة واقعية ومتسقة دون الحاجة إلى ضبط دقيق إضافي.
-لاستخدام خادم SGLang، راجع [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md) .
+يدعم Fish Audio S2 استنساخاً دقيقاً للصوت باستخدام عينات مرجعية قصيرة (عادةً 10-30 ثانية). يلتقط النموذج نبرة الصوت وأسلوب الكلام والميول العاطفية، مما يولد أصواتاً مستنسخة واقعية ومتسقة دون الحاجة إلى ضبط دقيق إضافي.
+لاستخدام خادم SGLang، يرجى الرجوع إلى [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md).
 
 ---
 
@@ -170,7 +172,8 @@ Fish Audio S2 هو أحدث نموذج من [Fish Audio](https://fish.audio/).
 - [GPT-SoVITS](https://github.com/RVC-Boss/GPT-SoVITS)
 - [Qwen3](https://github.com/QwenLM/Qwen3)
 
-## التقرير التقني
+## التقرير الفني
+
 ```bibtex
 @misc{fish-speech-v1.4,
       title={Fish-Speech: Leveraging Large Language Models for Advanced Multilingual Text-to-Speech Synthesis},

docs/README.ja.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -45,13 +45,14 @@
 > **ライセンス注意事項**
 > このコードベースおよび関連するモデルウェイトは **[FISH AUDIO RESEARCH LICENSE](../LICENSE)** の下でリリースされています。詳細については [LICENSE](../LICENSE) をご参照ください。
 
+
 > [!WARNING]
 > **法的免責事項**
 > 私たちはコードベースの不法な使用について一切の責任を負いません。DMCA 及びその他の関連法律について、現地の法律をご参照ください。
 
 ## クイックスタート
 
-### まずはドキュメントから
+### ドキュメント入口
 
 Fish Audio S2 の公式ドキュメントです。以下からすぐに始められます。
 
@@ -59,31 +60,31 @@ Fish Audio S2 の公式ドキュメントです。以下からすぐに始めら
 - [コマンドライン推論](https://speech.fish.audio/ja/inference/)
 - [WebUI 推論](https://speech.fish.audio/ja/inference/)
 - [サーバー推論](https://speech.fish.audio/ja/server/)
-- [Docker セットアップ](https://speech.fish.audio/ja/install/)
+- [Docker デプロイ](https://speech.fish.audio/ja/install/)
 
 > [!IMPORTANT]
 > **SGLang サーバーについては [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md) を参照してください。**
 
-### LLM Agent 向け
+### LLM Agent 指南
 
 ```
 https://speech.fish.audio/ja/install/ の手順に従って、Fish Audio S2 をインストール・設定してください。
 ```
 
-## Fish Audio S2
-**オープンソースおよびクローズドソースの中で最も優れたテキスト読み上げシステム**
+## Fish Audio S2 Pro
+**業界最先端の多言語テキスト読み上げ (TTS) システム。音声生成の限界を再定義します。**
 
-Fish Audio S2 は [Fish Audio](https://fish.audio/) が開発した最新モデルです。約 50 言語・1,000 万時間超の音声データで学習され、強化学習アラインメントと Dual-Autoregressive アーキテクチャを組み合わせることで、自然でリアルかつ感情表現豊かな音声を生成します。
+Fish Audio S2 Pro は [Fish Audio](https://fish.audio/) が開発した最高峰のマルチモーダルモデルです。世界 **80 言語以上**、**1,000 万時間** を超える膨大な音声データで学習されています。革新的な **二重自己回帰 (Dual-AR)** アーキテクチャと強化学習 (RL) アライメント技術を組み合わせることで、極めて自然でリアル、かつ感情豊かな音声を生成し、オープンソースおよびクローズドソースの双方でリーダーシップを発揮しています。
 
-S2 は `[laugh]`、`[whispers]`、`[super happy]` といった自然言語タグで、韻律や感情を文中の任意位置で細かく制御できます。さらに、マルチスピーカー生成とマルチターン生成にもネイティブ対応しています。
+S2 Pro の最大の特徴は、自然言語タグ（例：`[whisper]`、`[excited]`、`[angry]`）による韻律や感情の **サブワードレベル (Sub-word Level)** での極めて細やかなインライン制御が可能である点です。また、マルチスピーカー生成や長文コンテキストのマルチターン対話生成にもネイティブ対応しています。
 
-ライブデモは [Fish Audio ウェブサイト](https://fish.audio/) から、詳細は [ブログ記事](https://fish.audio/blog/fish-audio-open-sources-s2/) をご覧ください。
+今すぐ [Fish Audio 公式サイト](https://fish.audio/) でプレイグラウンドを体験するか、[技術レポート](https://arxiv.org/abs/2603.08823) や [ブログ記事](https://fish.audio/blog/fish-audio-open-sources-s2/) を読んで詳細を確認してください。
 
 ### モデルバリアント
 
 | モデル | サイズ | 利用可能性 | 説明 |
 |------|------|-------------|-------------|
-| S2-Pro | 4B パラメータ | [HuggingFace](https://huggingface.co/fishaudio/s2-pro) | 品質と安定性を最大化したフル機能のフラッグシップモデル |
+| S2-Pro | 4B パラメータ | [HuggingFace](https://huggingface.co/fishaudio/s2-pro) | 品質と安定性を最大化した、フル機能のフラッグシップモデル |
 
 モデルの詳細は[技術レポート](https://arxiv.org/abs/2411.01156)をご参照ください。
 
@@ -108,59 +109,60 @@ Seed-TTS Eval では、S2 はクローズドソースを含む全評価モデル
 
 ### 自然言語による細粒度インライン制御
 
-Fish Audio S2 では、テキスト内の特定の単語やフレーズ位置に自然言語の指示を直接埋め込むことで、音声生成を局所的に制御できます。固定の事前定義タグに依存するのではなく、S2 は [whisper in small voice]、[professional broadcast tone]、[pitch up] のような自由形式のテキスト記述を受け付け、単語レベルで表現をオープンエンドに制御できます。
-
-### 二重自己回帰（Dual-Autoregressive）アーキテクチャ
-
-S2 はデコーダー専用 Transformer と RVQ ベースの音声コーデック（10 codebooks、約 21 Hz）を組み合わせています。Dual-AR は生成を 2 段階に分割します。
+S2 Pro は音声にこれまでにない「魂」を宿らせます。シンプルな `[tag]` 構文を使用して、テキスト内の任意の場所に感情の指示を正確に埋め込むことができます。
+- **1万5,000以上のユニークタグに対応**：固定のプリセットに限定されず、**自由形式のテキスト記述** をサポートします。`[whisper in small voice]` (ささやき声で), `[professional broadcast tone]` (プロのナレーション風), `[pitch up]` (ピッチを上げる) などを試してみてください。
+- **豊富な感情ライブラリ**:
+  `[pause]` `[emphasis]` `[laughing]` `[inhale]` `[chuckle]` `[tsk]` `[singing]` `[excited]` `[laughing tone]` `[interrupting]` `[chuckling]` `[excited tone]` `[volume up]` `[echo]` `[angry]` `[low volume]` `[sigh]` `[low voice]` `[whisper]` `[screaming]` `[shouting]` `[loud]` `[surprised]` `[short pause]` `[exhale]` `[delight]` `[panting]` `[audience laughter]` `[with strong accent]` `[volume down]` `[clearing throat]` `[sad]` `[moaning]` `[shocked]`
 
-- **Slow AR** は時間軸方向に動作し、主となる semantic codebook を予測。
-- **Fast AR** は各時刻で残り 9 個の residual codebook を生成し、細かな音響ディテールを復元。
+### 革新的な二重自己回帰 (Dual-Autoregressive) アーキテクチャ
 
-この非対称設計（時間軸 4B パラメータ、深さ軸 400M パラメータ）により、音質を保ちながら推論効率を高めています。
+S2 Pro は、Decoder-only Transformer と RVQ オーディオコーデック（10 コードブック、約 21 Hz）で構成されるマスター・スレーブ型の Dual-AR アーキテクチャを採用しています：
 
-### 強化学習アラインメント
+- **Slow AR (4B パラメータ)**: 時間軸方向に動作し、核となるセマンティックコードブックを予測。
+- **Fast AR (400M パラメータ)**: 各時間ステップで残り 9 個の残差コードブックを生成し、極めて繊細な音響ディテールを復元。
 
-S2 は後学習アラインメントに Group Relative Policy Optimization（GRPO）を採用しています。学習データのフィルタリングとアノテーションに使った同一モデル群を、そのまま RL の報酬モデルとして再利用することで、事前学習データ分布と事後学習目的のミスマッチを抑制しています。報酬信号には、意味的正確性、指示追従性、音響的選好スコア、音色類似度が含まれます。
+この非対称設計により、究極のオーディオ忠実度を維持しながら、推論速度を大幅に向上させています。
 
-### SGLang による本番向けストリーミング
+### 強化学習 (RL) アライメント
 
-Dual-AR は構造的に標準的な自己回帰 LLM と同型のため、S2 は SGLang の LLM 向け最適化をそのまま活用できます。たとえば continuous batching、paged KV cache、CUDA graph replay、RadixAttention ベースの prefix caching です。
+S2 Pro は、事後学習アライメントに **Group Relative Policy Optimization (GRPO)** 技術を採用しています。データのクリーニングとアノテーションに使用したモデルセットをそのまま報酬モデル (Reward Model) として使用することで、事前学習データの分布と事後学習の目標との間のミスマッチを完璧に解決しました。
+- **多次元の報酬信号**: 意味の正確性、指示追従性、音響的な好み、音色の類似性を総合的に評価し、生成される一秒一秒の音声が人間の直感に沿うようにしています。
 
-単一の NVIDIA H200 GPU での実測:
+### SGLang による究極のストリーミング推論性能
 
-- **RTF（Real-Time Factor）:** 0.195
-- **初回音声出力までの時間:** 約 100 ms
-- **スループット:** RTF 0.5 未満を維持しつつ 3,000+ acoustic tokens/s
+Dual-AR アーキテクチャは標準的な LLM 構造と同型であるため、S2 Pro は SGLang のすべての推論加速機能をネイティブにサポートしています。これには、Continuous Batching、Paged KV Cache、CUDA Graph、RadixAttention ベースの Prefix Caching が含まれます。
 
-### 多言語サポート
+**NVIDIA H200 GPU 1枚でのパフォーマンス表現:**
+- **リアルタイム係数 (RTF)**: 0.195
+- **初回音声出力までの時間 (TTFA)**: 約 100 ms
+- **極速スループット**: RTF < 0.5 を維持しつつ 3,000+ acoustic tokens/s
 
-Fish Audio S2 は、音素や言語固有の前処理を必要とせずに、高品質な多言語テキスト読み上げをサポートします。以下を含みます：
+### 強力な多言語サポート
 
-**英語、中国語、日本語、韓国語、アラビア語、ドイツ語、フランス語...**
+S2 Pro は 80 以上の言語をサポートしており、音素や特定の言語に対する前処理なしで高品質な合成を実現します：
 
-**さらに多く！**
-
-リストは常に拡大しています。最新のリリースについては [Fish Audio](https://fish.audio/) を確認してください。
+- **第1層 (Tier 1)**: 日本語 (ja), 英語 (en), 中国語 (zh)
+- **第2層 (Tier 2)**: 韓国語 (ko), スペイン語 (es), ポルトガル語 (pt), アラビア語 (ar), ロシア語 (ru), フランス語 (fr), ドイツ語 (de)
+- **グローバルカバレッジ**: sv, it, tr, no, nl, cy, eu, ca, da, gl, ta, hu, fi, pl, e!t, hi, la, ur, th, vi, jw, bn, yo, xsl, cs, sw, nn, he, ms, uk, id, kk, bg, lv, my, tl, sk, ne, fa, af, el, bo, hr, ro, sn, mi, yi, am, be, km, is, az, sd, br, sq, ps, mn, ht, ml, sr, sa, te, ka, bs, pa, lt, kn, si, hy, mr, as, gu, fo など。
 
 ### ネイティブなマルチスピーカー生成
 
 <img src="./assets/chattemplate.png" width=200%>
 
-Fish Audio S2 では、ユーザーが複数のスピーカーを含む参照オーディオをアップロードでき、モデルは `<|speaker:i|>` トークンを介して各スピーカーの特徴を処理します。その後、スピーカーIDトークンを使用してモデルのパフォーマンスを制御し、1回の生成で複数のスピーカーを含めることができます。以前のように各スピーカーに対して個別に参照オーディオをアップロードして音声を生成する必要はもうありません。
+Fish Audio S2 では、複数のスピーカーを含む参照オーディオをアップロードでき、モデルは `<|speaker:i|>` トークンを介して各スピーカーの特徴を処理します。スピーカー ID トークンを使用してモデルの出力を制御することで、1回の生成に複数のスピーカーを混在させることが可能です。個別のスピーカーごとに参照オーディオをアップロードし直す手間はもう不要です。
 
 ### マルチターン対話生成
 
-モデルのコンテキストの拡張により、以前の情報を使用して後続の生成されたコンテンツの表現力を向上させ、コンテンツの自然さを高めることができるようになりました。
+コンテキストの拡張により、以前のターンの情報を利用して後続の生成内容の表現力を高めることができ、対話としての自然さが大幅に向上しました。
 
 ### 高速音声クローニング
 
-Fish Audio S2 は、短い参照サンプル（通常10〜30秒）を使用した正確な音声クローニングをサポートしています。モデルは音色、話し方、感情的な傾向を捉え、追加の微調整なしでリアルで一貫したクローン音声を生成します。
-SGLang サーバーの利用については [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md) を参照してください。
+Fish Audio S2 は、短い参照サンプル（通常 10〜30 秒）を使用した正確な音声クローニングをサポートしています。モデルは音色、話し方、感情を捉え、追加の微調整なしでリアルで一貫したクローン音声を生成します。
+SGLang サーバーの利用については、[SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md) を参照してください。
 
 ---
 
-## クレジット
+## 謝辞
 
 - [VITS2 (daniilrobnikov)](https://github.com/daniilrobnikov/vits2)
 - [Bert-VITS2](https://github.com/fishaudio/Bert-VITS2)
@@ -171,6 +173,7 @@ SGLang サーバーの利用については [SGLang-Omni README](https://github.
 - [Qwen3](https://github.com/QwenLM/Qwen3)
 
 ## 技術レポート
+
 ```bibtex
 @misc{fish-speech-v1.4,
       title={Fish-Speech: Leveraging Large Language Models for Advanced Multilingual Text-to-Speech Synthesis},

docs/README.ko.md

@@ -36,131 +36,133 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
 
 > [!IMPORTANT]
-> **라이선스 고지사항**
-> 이 코드베이스 및 관련 모델 가중치는 **[FISH AUDIO RESEARCH LICENSE](../LICENSE)** 하에 릴리스됩니다. 자세한 내용은 [LICENSE](../LICENSE)를 참조하세요.
+> **라이선스 고지**
+> 이 코드베이스 및 관련 모델 가중치는 **[FISH AUDIO RESEARCH LICENSE](../LICENSE)** 에 따라 배포됩니다. 자세한 내용은 [LICENSE](../LICENSE)를 참조하십시오.
+
 
 > [!WARNING]
-> **법적 면책조항**
-> 저희는 코드베이스의 불법적인 사용에 대해 어떠한 책임도 지지 않습니다. DMCA 및 기타 관련 법률에 대한 현지 법률을 참조하세요.
+> **법적 면책 조항**
+> 당사는 코드베이스의 불법적인 사용에 대해 어떠한 책임도 지지 않습니다. 해당 지역의 DMCA 및 기타 관련 법률을 참조하십시오.
 
 ## 빠른 시작
 
-### 문서로 바로 시작하기
+### 문서 입구
 
-Fish Audio S2 공식 문서입니다. 아래 링크에서 바로 시작할 수 있습니다.
+Fish Audio S2의 공식 문서입니다. 지침에 따라 쉽게 시작하십시오.
 
 - [설치](https://speech.fish.audio/ko/install/)
-- [커맨드라인 추론](https://speech.fish.audio/ko/inference/)
+- [명령줄 추론](https://speech.fish.audio/ko/inference/)
 - [WebUI 추론](https://speech.fish.audio/ko/inference/)
 - [서버 추론](https://speech.fish.audio/ko/server/)
-- [Docker 설정](https://speech.fish.audio/ko/install/)
+- [Docker 배포](https://speech.fish.audio/ko/install/)
 
 > [!IMPORTANT]
-> **SGLang 서버는 [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md)를 참고하세요.**
+> **SGLang 서버를 사용하려면 [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md)를 참조하십시오.**
 
 ### LLM Agent 가이드
 
 ```
-https://speech.fish.audio/ko/install/ 문서를 따라 Fish Audio S2를 설치하고 구성하세요.
+먼저 https://speech.fish.audio/ko/install/ 을 읽고 문서에 따라 Fish Audio S2를 설치 및 구성하십시오.
 ```
 
-## Fish Audio S2
-**오픈 소스와 클로즈드 소스 모두에서 가장 뛰어난 텍스트 음성 변환 시스템**
+## Fish Audio S2 Pro
+**음성 생성의 경계를 재정의하는 업계 최고의 다국어 텍스트 음성 변환(TTS) 시스템.**
 
-Fish Audio S2는 [Fish Audio](https://fish.audio/)가 개발한 최신 모델입니다. 약 50개 언어, 1,000만 시간 이상의 오디오 데이터로 학습되었고, 강화학습 정렬과 Dual-Autoregressive 아키텍처를 결합해 자연스럽고 사실적이며 감정 표현이 풍부한 음성을 생성합니다.
+Fish Audio S2 Pro는 [Fish Audio](https://fish.audio/)에서 개발한 최첨단 멀티모달 모델입니다. 전 세계 **80개 이상의 언어**를 아우르는 **1,000만 시간** 이상의 방대한 오디오 데이터로 학습되었습니다. 혁신적인 **이중 자기회귀(Dual-AR)** 아키텍처와 강화 학습(RL) 정렬 기술을 통해 S2 Pro는 극도로 자연스럽고 사실적이며 감정이 풍부한 음성을 생성하며, 오픈 소스와 클ローズ드 소스 경쟁 모두에서 선두를 달리고 있습니다.
 
-S2는 `[laugh]`, `[whispers]`, `[super happy]` 같은 자연어 태그를 사용해 운율과 감정을 문장 내부에서 세밀하게 제어할 수 있으며, 멀티 화자/멀티 턴 생성도 네이티브로 지원합니다.
+S2 Pro의 핵심 강점은 자연어 태그(예: `[whisper]`, `[excited]`, `[angry]`)를 통해 운율과 감정을 **하위 단어 수준(Sub-word Level)**에서 매우 세밀하게 인라인 제어할 수 있다는 점입니다. 또한 다중 화자 생성 및 긴 컨텍스트의 다중 턴 대화 생성을 기본적으로 지원합니다.
 
-실시간 데모는 [Fish Audio 웹사이트](https://fish.audio/)에서, 자세한 내용은 [블로그 글](https://fish.audio/blog/fish-audio-open-sources-s2/)에서 확인할 수 있습니다.
+지금 바로 [Fish Audio 공식 웹사이트](https://fish.audio/)에서 온라인 데모를 체험하거나, [기술 보고서](https://arxiv.org/abs/2603.08823) 및 [블로그 게시물](https://fish.audio/blog/fish-audio-open-sources-s2/)을 통해 자세히 알아보십시오.
 
-### 모델 변형
+### 모델 변체
 
 | 모델 | 크기 | 가용성 | 설명 |
 |------|------|-------------|-------------|
-| S2-Pro | 4B 매개변수 | [HuggingFace](https://huggingface.co/fishaudio/s2-pro) | 최고 수준의 품질과 안정성을 제공하는 풀기능 플래그십 모델 |
+| S2-Pro | 4B 파라미터 | [HuggingFace](https://huggingface.co/fishaudio/s2-pro) | 최고의 품질과 안정성을 갖춘 모든 기능을 갖춘 플래그십 모델 |
 
-모델 상세는 [기술 보고서](https://arxiv.org/abs/2411.01156)를 참고하세요.
+모델에 대한 자세한 내용은 [기술 보고서](https://arxiv.org/abs/2411.01156)를 참조하십시오.
 
 ## 벤치마크 결과
 
 | 벤치마크 | Fish Audio S2 |
 |------|------|
-| Seed-TTS Eval — WER (중국어) | **0.54%** (전체 최고) |
-| Seed-TTS Eval — WER (영어) | **0.99%** (전체 최고) |
-| Audio Turing Test (지시 포함) | **0.515** 사후 평균 |
+| Seed-TTS Eval — WER(중국어) | **0.54%** (전체 최고) |
+| Seed-TTS Eval — WER(영어) | **0.99%** (전체 최고) |
+| Audio Turing Test (지침 포함) | **0.515** 후험 평균 |
 | EmergentTTS-Eval — 승률 | **81.88%** (전체 최고) |
 | Fish Instruction Benchmark — TAR | **93.3%** |
 | Fish Instruction Benchmark — 품질 | **4.51 / 5.0** |
 | 다국어 (MiniMax Testset) — 최고 WER | **24개 언어 중 11개** |
 | 다국어 (MiniMax Testset) — 최고 SIM | **24개 언어 중 17개** |
 
-Seed-TTS Eval에서 S2는 클로즈드 소스 시스템을 포함한 전체 비교 모델 중 가장 낮은 WER를 기록했습니다: Qwen3-TTS (0.77/1.24), MiniMax Speech-02 (0.99/1.90), Seed-TTS (1.12/2.25). Audio Turing Test에서는 0.515를 기록해 Seed-TTS (0.417) 대비 24%, MiniMax-Speech (0.387) 대비 33% 높았습니다. EmergentTTS-Eval에서는 파라언어 표현(91.61%), 의문문(84.41%), 구문 복잡도(83.39%)에서 특히 강한 성능을 보였습니다.
+Seed-TTS Eval에서 S2는 클ローズ드 소스 시스템을 포함한 모든 평가 모델 중 가장 낮은 WER을 달성했습니다: Qwen3-TTS (0.77/1.24), MiniMax Speech-02 (0.99/1.90), Seed-TTS (1.12/2.25). Audio Turing Test에서 S2의 0.515는 Seed-TTS (0.417) 대비 24%, MiniMax-Speech (0.387) 대비 33% 향상된 수치입니다. EmergentTTS-Eval에서 S2는 부차 언어학(91.61% 승률), 의문문(84.41%), 구문 복잡성(83.39%) 등의 측면에서 특히 두드러진 성과를 보였습니다.
 
-## 주요 특징
+## 하이라이트
 
 <img src="./assets/totalability.png" width=200%>
 
-### 자연어 기반 세밀한 인라인 제어
-
-Fish Audio S2는 텍스트의 특정 단어 또는 구문 위치에 자연어 지시를 직접 삽입해 음성 생성을 국소적으로 제어할 수 있습니다. 고정된 사전 정의 태그에 의존하는 대신, S2는 [whisper in small voice], [professional broadcast tone], [pitch up] 같은 자유 형식 텍스트 설명을 받아 단어 수준의 개방형 표현 제어를 지원합니다.
-
-### Dual-Autoregressive 아키텍처
+### 자연어를 통한 초미세 인라인 제어
 
-S2는 decoder-only Transformer와 RVQ 기반 오디오 코덱(10 codebooks, 약 21 Hz 프레임레이트)을 결합합니다. Dual-AR은 생성 과정을 두 단계로 나눕니다.
+S2 Pro는 음성에 전례 없는 "영혼"을 부여합니다. 간단한 `[tag]` 구문을 사용하여 텍스트의 어느 위치에나 감정 지침을 정확하게 삽입할 수 있습니다.
+- **15,000개 이상의 고유 태그 지원**: 고정된 사전 설정에 국한되지 않고 **자유 형식의 텍스트 설명**을 지원합니다. `[whisper in small voice]` (작은 목소리로 속삭임), `[professional broadcast tone]` (전문 방송 톤), `[pitch up]` (음높이 높임) 등을 시도해 보십시오.
+- **풍부한 감정 라이브러리**:
+  `[pause]` `[emphasis]` `[laughing]` `[inhale]` `[chuckle]` `[tsk]` `[singing]` `[excited]` `[laughing tone]` `[interrupting]` `[chuckling]` `[excited tone]` `[volume up]` `[echo]` `[angry]` `[low volume]` `[sigh]` `[low voice]` `[whisper]` `[screaming]` `[shouting]` `[loud]` `[surprised]` `[short pause]` `[exhale]` `[delight]` `[panting]` `[audience laughter]` `[with strong accent]` `[volume down]` `[clearing throat]` `[sad]` `[moaning]` `[shocked]`
 
-- **Slow AR**: 시간축을 따라 동작하며 주 semantic codebook을 예측
-- **Fast AR**: 각 시점에서 나머지 9개 residual codebook을 생성해 세밀한 음향 디테일을 복원
+### 혁신적인 이중 자기회귀 (Dual-Autoregressive) 아키텍처
 
-이 비대칭 설계(시간축 4B 파라미터, 깊이축 400M 파라미터)는 음질을 유지하면서 추론 효율을 높입니다.
+S2 Pro는 Decoder-only Transformer와 RVQ 오디오 코덱(10개 코드북, 약 21Hz 프레임 속도)으로 구성된 마스터-슬레이브 방식의 Dual-AR 아키텍처를 채택했습니다.
 
-### 강화학습 정렬
+- **Slow AR (4B 파라미터)**: 시간 축을 따라 작동하며 핵심 의미 코드북을 예측합니다.
+- **Fast AR (400M 파라미터)**: 각 타임스텝에서 나머지 9개의 잔차 코드북을 생성하여 극도로 정교한 음향 세부 사항을 복원합니다.
 
-S2는 후학습 정렬을 위해 Group Relative Policy Optimization(GRPO)을 사용합니다. 학습 데이터 필터링/라벨링에 쓰인 동일한 모델을 RL 보상 모델로 재사용해, 사전학습 데이터 분포와 후학습 목표 간의 분포 불일치를 줄였습니다. 보상 신호는 의미 정확도, 지시 준수도, 음향 선호 점수, 음색 유사도를 함께 반영합니다.
+이러한 비대칭 설계는 오디오의 최고 충실도를 보장하는 동시에 추론 속도를 대폭 향상시킵니다.
 
-### SGLang 기반 프로덕션 스트리밍
+### 강화 학습 (RL) 정렬
 
-Dual-AR 구조는 표준 자기회귀 LLM과 구조적으로 동형이기 때문에, S2는 SGLang의 LLM 서빙 최적화를 그대로 활용합니다. 예: continuous batching, paged KV cache, CUDA graph replay, RadixAttention 기반 prefix caching.
+S2 Pro는 사후 학습 정렬을 위해 **Group Relative Policy Optimization (GRPO)** 기술을 채택했습니다. 데이터 정제 및 주석 처리에 사용된 것과 동일한 모델 세트를 보상 모델(Reward Model)로 직접 사용함으로써 사전 학습 데이터 분포와 사후 학습 목표 간의 불일치 문제를 완벽하게 해결했습니다.
+- **다차원 보상 신호**: 의미 체계의 정확성, 지침 준수 능력, 음향 선호도 점수 및 음색 유사성을 종합적으로 평가하여 생성된 음성의 매초가 인간의 직관에 부합하도록 보장합니다.
 
-NVIDIA H200 단일 GPU 기준:
+### SGLang 기반의 극한 스트리밍 추론 성능
 
-- **실시간 계수(RTF):** 0.195
-- **첫 오디오 출력까지 시간:** 약 100 ms
-- **처리량:** RTF 0.5 미만 유지 시 3,000+ acoustic tokens/s
+Dual-AR 아키텍처는 표준 LLM 구조와 동형이므로 S2 Pro는 Continuous Batching, Paged KV Cache, CUDA Graph 및 RadixAttention 기반 Prefix Caching을 포함한 SGLang의 모든 추론 가속 기능을 기본적으로 지원합니다.
 
-### 다국어 지원
+**단일 NVIDIA H200 GPU 성능 지표:**
+- **실시간 계수 (RTF)**: 0.195
+- **첫 음성 지연 (TTFA)**: 약 100 ms
+- **초고속 처리량**: RTF < 0.5 유지 시 처리량 3,000+ acoustic tokens/s 달성
 
-Fish Audio S2는 음소나 언어별 전처리 없이 고품질 다국어 텍스트 음성 변환을 지원합니다. 포함 사항:
+### 강력한 다국어 지원
 
-**영어, 중국어, 일본어, 한국어, 아랍어, 독일어, 프랑스어...**
+S2 Pro는 음소나 특정 언어 처리가 필요 없는 고품질 합성을 80개 이상의 언어에서 지원합니다.
 
-**그리고 더 많이!**
+- **1계층 (Tier 1)**: 일본어 (ja), 영어 (en), 중국어 (zh)
+- **2계층 (Tier 2)**: 한국어 (ko), 스페인어 (es), 포르투갈어 (pt), 아랍어 (ar), 러시아어 (ru), 프랑스어 (fr), 독일어 (de)
+- **글로벌 커버리지**: sv, it, tr, no, nl, cy, eu, ca, da, gl, ta, hu, fi, pl, et, hi, la, ur, th, vi, jw, bn, yo, xsl, cs, sw, nn, he, ms, uk, id, kk, bg, lv, my, tl, sk, ne, fa, af, el, bo, hr, ro, sn, mi, yi, am, be, km, is, az, sd, br, sq, ps, mn, ht, ml, sr, sa, te, ka, bs, pa, lt, kn, si, hy, mr, as, gu, fo 등.
 
-목록은 계속 확장되고 있습니다. 최신 릴리스는 [Fish Audio](https://fish.audio/)를 확인하세요.
-
-### 네이티브 멀티 화자 생성
+### 네이티브 다중 화자 생성
 
 <img src="./assets/chattemplate.png" width=200%>
 
-Fish Audio S2는 사용자가 여러 화자가 포함된 참조 오디오를 업로드할 수 있도록 하며, 모델은 `<|speaker:i|>` 토큰을 통해 각 화자의 특징을 처리합니다. 그런 다음 화자 ID 토큰으로 모델의 성능을 제어하여 한 번의 생성으로 여러 화자를 포함할 수 있습니다. 이전처럼 각 화자마다 별도로 참조 오디오를 업로드하고 음성을 생성할 필요가 없습니다.
+Fish Audio S2를 사용하면 사용자가 여러 화자가 포함된 참조 오디오를 업로드할 수 있으며, 모델은 `<|speaker:i|>` 토큰을 통해 각 화자의 특징을 처리합니다. 이후 화자 ID 토큰을 사용하여 모델의 표현을 제어함으로써 한 번의 생성에 여러 화자를 포함할 수 있습니다. 더 이상 화자마다 별도의 참조 오디오를 업로드하고 음성을 생성할 필요가 없습니다.
 
-### 멀티 턴 대화 생성
+### 다중 턴 대화 생성
 
-모델 컨텍스트의 확장 덕분에 이제 이전 정보를 활용하여 후속 생성 콘텐츠의 표현력을 높이고 콘텐츠의 자연스러움을 향상시킬 수 있습니다.
+모델 컨텍스트 확장에 힘입어 이제 이전 정보의 도움을 받아 후속 생성 내용의 표현력을 높이고 콘텐츠의 자연스러움을 향상시킬 수 있습니다.
 
-### 빠른 음성 복제
+### 고속 음성 복제
 
-Fish Audio S2는 짧은 참조 샘플(일반적으로 10-30초)을 사용하여 정확한 음성 복제를 지원합니다. 모델은 음색, 말하기 스타일 및 감정적 경향을 캡처하여 추가 미세 조정 없이 사실적이고 일관된 복제 음성을 생성합니다.
-SGLang 서버 사용은 [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md) 를 참고하세요.
+Fish Audio S2는 짧은 참조 샘플(보통 10-30초)을 사용한 정확한 음성 복제를 지원합니다. 모델은 음색, 말하기 스타일 및 감정적 경향을 포착하여 추가적인 미세 조정 없이도 사실적이고 일관된 복제 음성을 생성합니다.
+SGLang 서버 사용에 대해서는 [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md)를 참조하십시오.
 
 ---
 
-## 크레딧
+## 감사의 말
 
 - [VITS2 (daniilrobnikov)](https://github.com/daniilrobnikov/vits2)
 - [Bert-VITS2](https://github.com/fishaudio/Bert-VITS2)
@@ -171,6 +173,7 @@ SGLang 서버 사용은 [SGLang-Omni README](https://github.com/sgl-project/sgla
 - [Qwen3](https://github.com/QwenLM/Qwen3)
 
 ## 기술 보고서
+
 ```bibtex
 @misc{fish-speech-v1.4,
       title={Fish-Speech: Leveraging Large Language Models for Advanced Multilingual Text-to-Speech Synthesis},

docs/README.pt-BR.md

@@ -36,131 +36,133 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
 
 > [!IMPORTANT]
 > **Aviso de Licença**
-> Este repositório e os pesos de modelo associados são lançados sob a **[FISH AUDIO RESEARCH LICENSE](../LICENSE)**. Consulte [LICENSE](../LICENSE) para obter mais detalhes.
+> Este repositório de código e seus pesos de modelo associados são lançados sob a **[FISH AUDIO RESEARCH LICENSE](../LICENSE)**. Consulte [LICENSE](../LICENSE) para obter mais detalhes.
+
 
 > [!WARNING]
-> **Isenção de Responsabilidade Legal**
-> Não nos responsabilizamos por qualquer uso ilegal do repositório. Consulte as leis locais sobre DMCA e outras leis relacionadas.
+> **Aviso Legal**
+> Não nos responsabilizamos por qualquer uso ilegal deste repositório. Consulte as leis locais sobre DMCA e outras regulamentações relevantes.
 
 ## Início Rápido
 
-### Comece pela documentação
+### Links da Documentação
 
-Esta é a documentação oficial do Fish Audio S2. Você pode começar por aqui:
+Esta é a documentação oficial do Fish Audio S2, siga as instruções para começar facilmente.
 
-- [Instalação](https://speech.fish.audio/pt/install/)
-- [Inferência por Linha de Comando](https://speech.fish.audio/pt/inference/)
-- [Inferência WebUI](https://speech.fish.audio/pt/inference/)
-- [Inferência via Servidor](https://speech.fish.audio/pt/server/)
-- [Configuração Docker](https://speech.fish.audio/pt/install/)
+- [Instalação](https://speech.fish.audio/install/)
+- [Inferência por Linha de Comando](https://speech.fish.audio/inference/)
+- [Inferência por WebUI](https://speech.fish.audio/inference/)
+- [Inferência por Servidor](https://speech.fish.audio/server/)
+- [Implantação Docker](https://speech.fish.audio/install/)
 
 > [!IMPORTANT]
-> **Para servidor com SGLang, consulte o [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md).**
+> **Caso deseje utilizar o SGLang Server, consulte o [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md).**
 
-### Guia para agentes LLM
+### Guia para Agentes de LLM
 
 ```
-Instale e configure o Fish Audio S2 seguindo as instruções em https://speech.fish.audio/pt/install/ .
+Leia primeiro https://speech.fish.audio/install/ e siga a documentação para instalar e configurar o Fish Audio S2.
 ```
 
-## Fish Audio S2
-**O melhor sistema de conversão de texto em fala entre código aberto e código fechado**
+## Fish Audio S2 Pro
+**O sistema de conversão de texto em fala (TTS) multilíngue líder do setor, redefinindo as fronteiras da geração de voz.**
 
-O Fish Audio S2 é o modelo mais recente da [Fish Audio](https://fish.audio/). Treinado com mais de 10 milhões de horas de áudio em cerca de 50 idiomas, o S2 combina alinhamento por reforço com uma arquitetura Dual-Autoregressive para gerar fala natural, realista e emocionalmente expressiva.
+Fish Audio S2 Pro é o modelo multimodal mais avançado desenvolvido pela [Fish Audio](https://fish.audio/). Treinado em mais de **10 milhões de horas** de dados de áudio massivos, cobrindo mais de **80 idiomas** globais. Através de uma arquitetura inovadora de **Dual-Autoregressive (Dual-AR)** e tecnologia de alinhamento por aprendizado por reforço (RL), o S2 Pro é capaz de gerar fala com um senso de naturalidade, realismo e riqueza emocional extremos, liderando tanto em competições de código aberto quanto proprietário.
 
-O S2 permite controle fino de prosódia e emoção dentro da própria frase com tags em linguagem natural, como `[laugh]`, `[whispers]` e `[super happy]`, além de oferecer suporte nativo a múltiplos falantes e múltiplos turnos.
+O grande diferencial do S2 Pro reside em seu suporte para controle inline de granularidade ultra-fina de prosódia e emoção ao nível de **sub-palavra (Sub-word Level)** via tags de linguagem natural (como `[whisper]`, `[excited]`, `[angry]`), além de suporte nativo para múltiplos falantes e geração de diálogos de múltiplos turnos com contexto ultra-longo.
 
-Acesse o [site da Fish Audio](https://fish.audio/) para testar ao vivo e leia o [post no blog](https://fish.audio/blog/fish-audio-open-sources-s2/) para mais detalhes.
+Visite agora o [site oficial da Fish Audio](https://fish.audio/) para experimentar a demonstração online, ou leia nosso [relatório técnico](https://arxiv.org/abs/2603.08823) e [artigo no blog](https://fish.audio/blog/fish-audio-open-sources-s2/) para saber mais.
 
-### Variantes do Modelo
+### Variantes de Modelo
 
 | Modelo | Tamanho | Disponibilidade | Descrição |
 |------|------|-------------|-------------|
-| S2-Pro | 4B parâmetros | [HuggingFace](https://huggingface.co/fishaudio/s2-pro) | Modelo carro-chefe completo com máxima qualidade e estabilidade |
+| S2-Pro | 4B parâmetros | [HuggingFace](https://huggingface.co/fishaudio/s2-pro) | Modelo flagship completo, com máxima qualidade e estabilidade |
 
-Mais detalhes podem ser encontrados no [relatório técnico](https://arxiv.org/abs/2411.01156).
+Para mais detalhes sobre os modelos, consulte o [relatório técnico](https://arxiv.org/abs/2411.01156).
 
 ## Resultados de Benchmark
 
 | Benchmark | Fish Audio S2 |
 |------|------|
-| Seed-TTS Eval — WER (Chinês) | **0.54%** (melhor geral) |
-| Seed-TTS Eval — WER (Inglês) | **0.99%** (melhor geral) |
-| Audio Turing Test (com instrução) | **0.515** média a posteriori |
-| EmergentTTS-Eval — Taxa de vitória | **81.88%** (maior geral) |
+| Seed-TTS Eval — WER (Chinês) | **0.54%** (Melhor geral) |
+| Seed-TTS Eval — WER (Inglês) | **0.99%** (Melhor geral) |
+| Audio Turing Test (Com instrução) | **0.515** Média posterior |
+| EmergentTTS-Eval — Taxa de Vitória | **81.88%** (Maior geral) |
 | Fish Instruction Benchmark — TAR | **93.3%** |
 | Fish Instruction Benchmark — Qualidade | **4.51 / 5.0** |
 | Multilíngue (MiniMax Testset) — Melhor WER | **11 de 24** idiomas |
 | Multilíngue (MiniMax Testset) — Melhor SIM | **17 de 24** idiomas |
 
-No Seed-TTS Eval, o S2 obteve o menor WER entre todos os modelos avaliados, incluindo sistemas fechados: Qwen3-TTS (0.77/1.24), MiniMax Speech-02 (0.99/1.90) e Seed-TTS (1.12/2.25). No Audio Turing Test, o valor 0.515 supera o Seed-TTS (0.417) em 24% e o MiniMax-Speech (0.387) em 33%. No EmergentTTS-Eval, o S2 se destacou especialmente em paralinguística (91.61%), perguntas (84.41%) e complexidade sintática (83.39%).
+No Seed-TTS Eval, o S2 alcançou o menor WER entre todos os modelos avaliados (incluindo sistemas proprietários): Qwen3-TTS (0.77/1.24), MiniMax Speech-02 (0.99/1.90), Seed-TTS (1.12/2.25). No Audio Turing Test, o valor de 0.515 do S2 representa um aumento de 24% em relação ao Seed-TTS (0.417) e 33% em relação ao MiniMax-Speech (0.387). No EmergentTTS-Eval, o S2 destacou-se especialmente em dimensões como paralinguística (taxa de vitória de 91.61%), frases interrogativas (84.41%) e complexidade sintática (83.39%).
 
 ## Destaques
 
 <img src="./assets/totalability.png" width=200%>
 
-### Controle Inline Refinado via Linguagem Natural
-
-O Fish Audio S2 permite controle localizado da geração de fala ao incorporar instruções em linguagem natural diretamente em posições específicas de palavras ou frases no texto. Em vez de depender de um conjunto fixo de tags predefinidas, o S2 aceita descrições textuais livres, como [whisper in small voice], [professional broadcast tone] ou [pitch up], permitindo controle de expressão aberto no nível da palavra.
-
-### Arquitetura Dual-Autoregressive
+### Controle Inline de Granularidade Ultra-Fina via Linguagem Natural
 
-O S2 é baseado em um transformer apenas decodificador, combinado com um codec de áudio RVQ (10 codebooks, ~21 Hz de taxa de quadros). A arquitetura Dual-AR divide a geração em duas etapas:
+S2 Pro confere à voz uma "espiritualidade" sem precedentes. Através de uma sintaxe simples de `[tag]`, você pode inserir instruções emocionais precisamente em qualquer posição do texto.
+- **Suporte para mais de 15.000 tags únicas**: Não limitado a predefinições fixas, suporta **descrições textuais de formato livre**. Você pode tentar `[whisper in small voice]` (sussurrando), `[professional broadcast tone]` (tom de locução profissional) ou `[pitch up]` (aumentar o tom).
+- **Rica biblioteca de emoções**:
+  `[pause]` `[emphasis]` `[laughing]` `[inhale]` `[chuckle]` `[tsk]` `[singing]` `[excited]` `[laughing tone]` `[interrupting]` `[chuckling]` `[excited tone]` `[volume up]` `[echo]` `[angry]` `[low volume]` `[sigh]` `[low voice]` `[whisper]` `[screaming]` `[shouting]` `[loud]` `[surprised]` `[short pause]` `[exhale]` `[delight]` `[panting]` `[audience laughter]` `[with strong accent]` `[volume down]` `[clearing throat]` `[sad]` `[moaning]` `[shocked]`
 
-- **Slow AR** opera no eixo temporal e prevê o codebook semântico principal.
-- **Fast AR** gera os 9 codebooks residuais restantes em cada passo de tempo, reconstruindo detalhes acústicos finos.
+### Arquitetura Inovadora Dual-Autoregressive (Dual-AR)
 
-Esse desenho assimétrico (4B parâmetros no eixo temporal e 400M no eixo de profundidade) mantém a inferência eficiente sem sacrificar fidelidade de áudio.
+S2 Pro adota uma arquitetura Dual-AR mestre-escravo, consistindo de um Decoder-only Transformer e um codec de áudio RVQ (10 codebooks, cerca de 21 Hz de taxa de frames):
 
-### Alinhamento por Reforço
+- **Slow AR (4B parâmetros)**: Atua ao longo do eixo temporal, prevendo o codebook semântico central.
+- **Fast AR (400M parâmetros)**: Gera os 9 codebooks residuais restantes em cada passo de tempo, restaurando detalhes acústicos extremos com delicadeza.
 
-O S2 usa Group Relative Policy Optimization (GRPO) no pós-treinamento. Os mesmos modelos usados para filtrar e anotar dados de treino são reutilizados diretamente como modelos de recompensa no RL, eliminando o desalinhamento de distribuição entre os dados de pré-treinamento e os objetivos de pós-treinamento. O sinal de recompensa combina precisão semântica, aderência à instrução, preferência acústica e similaridade de timbre.
+Este design assimétrico garante fidelidade extrema ao áudio enquanto aumenta significativamente a velocidade de inferência.
 
-### Streaming em Produção com SGLang
+### Alinhamento por Aprendizado por Reforço (RL Alignment)
 
-Como a arquitetura Dual-AR é estruturalmente isomórfica a LLMs autoregressivos padrão, o S2 herda diretamente as otimizações nativas de serving do SGLang, incluindo continuous batching, paged KV cache, CUDA graph replay e prefix caching com RadixAttention.
+S2 Pro utiliza a tecnologia **Group Relative Policy Optimization (GRPO)** para o alinhamento pós-treinamento. Utilizamos o mesmo conjunto de modelos para limpeza e anotação de dados diretamente como modelos de recompensa (Reward Model), resolvendo perfeitamente o problema de descasamento entre a distribuição dos dados de pré-treinamento e os objetivos de pós-treinamento.
+- **Sinais de recompensa multidimensionais**: Avalia de forma abrangente a precisão semântica, a capacidade de seguir instruções, a pontuação de preferência acústica e a similaridade de timbre, garantindo que cada segundo de fala gerada esteja alinhado com a intuição humana.
 
-Em uma única NVIDIA H200:
+### Desempenho de Inferência de Streaming Extremo (Baseado em SGLang)
 
-- **RTF (Real-Time Factor):** 0.195
-- **Tempo até o primeiro áudio:** ~100 ms
-- **Throughput:** mais de 3.000 acoustic tokens/s mantendo RTF abaixo de 0.5
+Como a arquitetura Dual-AR é estruturalmente isomorfa à estrutura padrão de LLMs, o S2 Pro suporta nativamente todos os recursos de aceleração de inferência do SGLang, incluindo loteamento contínuo (Continuous Batching), Paged KV Cache, CUDA Graph e cache de prefixo baseado em RadixAttention.
 
-### Suporte Multilíngue
+**Desempenho em uma única GPU NVIDIA H200:**
+- **Fator em Tempo Real (RTF)**: 0.195
+- **Latência do Primeiro Áudio (TTFA)**: aprox. 100 ms
+- **Taxa de Transferência Ultrarrápida**: Alcance de 3.000+ acoustic tokens/s mantendo RTF < 0.5
 
-O Fish Audio S2 oferece suporte a conversão de texto em fala multilíngue de alta qualidade sem a necessidade de fonemas ou processamento específico de idioma. Incluindo:
+### Poderoso Suporte Multilíngue
 
-**Inglês, Chinês, Japonês, Coreano, Árabe, Alemão, Francês...**
+S2 Pro suporta mais de 80 idiomas, possibilitando síntese de alta qualidade sem a necessidade de fonemas ou processamento específico por idioma:
 
-**E MUITO MAIS!**
+- **Tier 1**: Japonês (ja), Inglês (en), Chinês (zh)
+- **Tier 2**: Coreano (ko), Espanhol (es), Português (pt), Árabe (ar), Russo (ru), Francês (fr), Alemão (de)
+- **Cobertura Global**: sv, it, tr, no, nl, cy, eu, ca, da, gl, ta, hu, fi, pl, et, hi, la, ur, th, vi, jw, bn, yo, xsl, cs, sw, nn, he, ms, uk, id, kk, bg, lv, my, tl, sk, ne, fa, af, el, bo, hr, ro, sn, mi, yi, am, be, km, is, az, sd, br, sq, ps, mn, ht, ml, sr, sa, te, ka, bs, pa, lt, kn, si, hy, mr, as, gu, fo, etc.
 
-A lista está em constante expansão, verifique o [Fish Audio](https://fish.audio/) para os lançamentos mais recentes.
-
-### Geração Nativa de Múltiplos Falantes
+### Geração Nativa Multi-falante
 
 <img src="./assets/chattemplate.png" width=200%>
 
-O Fish Audio S2 permite enviar um áudio de referência com vários falantes; o modelo processa as características de cada voz por meio do token `<|speaker:i|>`. Depois, você controla o comportamento do modelo com o token de ID do falante, permitindo incluir várias vozes em uma única geração. Assim, não é mais necessário subir um áudio de referência separado para cada falante.
+O Fish Audio S2 permite que os usuários enviem áudio de referência contendo múltiplos falantes, e o modelo processará as características de cada falante via o token `<|speaker:i|>`. Em seguida, você pode controlar o desempenho do modelo através do token de ID do falante, permitindo incluir múltiplos falantes em uma única geração. Não é mais necessário enviar áudios de referência separadamente para cada falante.
 
-### Geração de Múltiplos Turnos
+### Geração de Diálogos Multiturnos
 
-Graças à extensão do contexto do modelo, nosso modelo agora pode usar informações anteriores para melhorar a expressividade e a naturalidade dos conteúdos gerados subsequentemente.
+Graças à expansão do contexto do modelo, nosso modelo agora pode aproveitar as informações prévias para aumentar a expressividade dos conteúdos gerados subsequentemente, elevando assim a naturalidade dos diálogos.
 
 ### Clonagem de Voz Rápida
 
-O Fish Audio S2 suporta clonagem de voz precisa usando uma pequena amostra de referência (tipicamente de 10 a 30 segundos). O modelo captura o timbre, o estilo de fala e as tendências emocionais, produzindo vozes clonadas realistas e consistentes sem ajuste fino adicional.
-Para usar o servidor SGLang, consulte [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md) .
+O Fish Audio S2 suporta clonagem de voz precisa usando curtas amostras de referência (normalmente 10-30 segundos). O modelo captura o timbre, o estilo de fala e as tendências emocionais, gerando vozes clonadas realistas e consistentes sem necessidade de ajustes finos adicionais.
+Caso deseje utilizar o SGLang Server, consulte o [SGLang-Omni README](https://github.com/sgl-project/sglang-omni/blob/main/sglang_omni/models/fishaudio_s2_pro/README.md).
 
 ---
 
-## Créditos
+## Agradecimentos
 
 - [VITS2 (daniilrobnikov)](https://github.com/daniilrobnikov/vits2)
 - [Bert-VITS2](https://github.com/fishaudio/Bert-VITS2)
@@ -171,6 +173,7 @@ Para usar o servidor SGLang, consulte [SGLang-Omni README](https://github.com/sg
 - [Qwen3](https://github.com/QwenLM/Qwen3)
 
 ## Relatório Técnico
+
 ```bibtex
 @misc{fish-speech-v1.4,
       title={Fish-Speech: Leveraging Large Language Models for Advanced Multilingual Text-to-Speech Synthesis},
@@ -184,7 +187,7 @@ Para usar o servidor SGLang, consulte [SGLang-Omni README](https://github.com/sg
 
 @misc{liao2026fishaudios2technical,
       title={Fish Audio S2 Technical Report}, 
-      author={Shijia Liao and Yuxuan Wang and Songting Liu and Yifan Cheng and Ruoyi Zhang and Tianyu Li and Shidong Li and Yisheng Zheng and Xingwei Liu and Qingzheng Wang and Zhizhuo Zhou and Jiahua Liu and Xin Chen and Dawei Han},
+      author={Shijia Liao and Yuxuan Wang racing Songting Liu and Yifan Cheng and Ruoyi Zhang and Tianyu Li and Shidong Li and Yisheng Zheng and Xingwei Liu and Qingzheng Wang and Zhizhuo Zhou and Jiahua Liu and Xin Chen and Dawei Han},
       year={2026},
       eprint={2603.08823},
       archivePrefix={arXiv},

docs/README.zh.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -71,14 +71,14 @@
 请先阅读 https://speech.fish.audio/zh/install/ ，并按文档安装和配置 Fish Audio S2。
 ```
 
-## Fish Audio S2
-**在开源与闭源方案中都处于领先水平的文本转语音系统**
+## Fish Audio S2 Pro
+**行业顶尖的多语言文本转语音 (TTS) 系统，重新定义声音生成的边界。**
 
-Fish Audio S2 是由 [Fish Audio](https://fish.audio/) 开发的最新模型。S2 在约 50 种语言、超过 1000 万小时音频数据上完成训练，并结合强化学习对齐与双自回归架构，能够生成自然、真实且情感丰富的语音。
+Fish Audio S2 Pro 是 [Fish Audio](https://fish.audio/) 开发的最先进的多模态模型。S2 Pro 训练自超过 **1000 万小时** 的海量音频数据，覆盖全球 **80 多种语言**。通过创新的 **双自回归 (Dual-AR)** 架构与强化学习 (RL) 对齐技术，S2 Pro 能生成极具自然感、真实感且情感饱满的语音，在开源与闭源竞争中均处于领先地位。
 
-S2 支持通过自然语言标签（如 `[laugh]`、`[whispers]`、`[super happy]`）对韵律和情绪进行细粒度行内控制，同时原生支持多说话人和多轮生成。
+S2 Pro 的杀手锏在于支持通过自然语言标签（如 `[whisper]`、`[excited]`、`[angry]`）对韵律与情绪进行 **亚词级（Sub-word Level）** 的极细粒度行内控制，同时原生支持多说话人与超长上下文的多轮对话生成。
 
-请访问 [Fish Audio 网站](https://fish.audio/) 体验在线演示，并阅读[博客文章](https://fish.audio/blog/fish-audio-open-sources-s2/)了解更多细节。
+立即访问 [Fish Audio 官网](https://fish.audio/) 体验在线演示，或阅读我们的[技术报告](https://arxiv.org/abs/2603.08823)与[博客文章](https://fish.audio/blog/fish-audio-open-sources-s2/)深入了解。
 
 ### 模型变体
 
@@ -107,42 +107,43 @@ S2 支持通过自然语言标签（如 `[laugh]`、`[whispers]`、`[super happy
 
 <img src="./assets/totalability.png" width=200%>
 
-### 通过自然语言进行细粒度行内控制
+### 通过自然语言进行极细粒度行内控制
 
-Fish Audio S2 支持在文本中的特定词或短语位置直接嵌入自然语言指令，从而对语音生成进行局部控制。与依赖固定预设标签不同，S2 接受自由形式的文本描述，例如 [whisper in small voice]、[professional broadcast tone] 或 [pitch up]，实现词级别的开放式表达控制。
+S2 Pro 赋予了语音前所未有的“灵性”。通过简单的 `[tag]` 语法，你可以在文本的任何位置精准嵌入情感指令。
+- **15,000+ 独特标签支持**：不局限于固定的预设，支持 **自由格式的文本描述**。你可以尝试 `[whisper in small voice]` (低声耳语), `[professional broadcast tone]` (专业播音腔), 或 `[pitch up]` (提高音调)。
+- **丰富的情绪库**：
+  `[pause]` `[emphasis]` `[laughing]` `[inhale]` `[chuckle]` `[tsk]` `[singing]` `[excited]` `[laughing tone]` `[interrupting]` `[chuckling]` `[excited tone]` `[volume up]` `[echo]` `[angry]` `[low volume]` `[sigh]` `[low voice]` `[whisper]` `[screaming]` `[shouting]` `[loud]` `[surprised]` `[short pause]` `[exhale]` `[delight]` `[panting]` `[audience laughter]` `[with strong accent]` `[volume down]` `[clearing throat]` `[sad]` `[moaning]` `[shocked]`
 
-### 双自回归架构（Dual-Autoregressive）
+### 创新的双自回归 (Dual-Autoregressive) 架构
 
-S2 基于仅解码器 Transformer，并结合 RVQ 音频编解码器（10 个码本，约 21 Hz 帧率）。Dual-AR 架构将生成拆分为两个阶段：
+S2 Pro 采用了主从式 Dual-AR 架构，由 Decoder-only Transformer 与 RVQ 音频编解码器（10 个码本，约 21 Hz 帧率）组成：
 
-- **Slow AR** 沿时间轴运行，预测主语义码本。
-- **Fast AR** 在每个时间步生成剩余 9 个残差码本，用于重建细粒度声学细节。
+- **Slow AR (4B 参数)**：沿时间轴工作，预测核心的语义码本。
+- **Fast AR (400M 参数)**：在每个时间步生成剩余 9 个残差码本，细腻还原极致的音频细节。
 
-这种非对称设计（时间轴 4B 参数、深度轴 400M 参数）在保持音频保真度的同时，提高了推理效率。
+这种非对称设计在保证音频极致保真度的同时，大幅提升了推理速度。
 
-### 强化学习对齐
+### 强化学习对齐 (RL Alignment)
 
-S2 使用 Group Relative Policy Optimization（GRPO）进行后训练对齐。用于过滤和标注训练数据的同一批模型被直接复用为 RL 的奖励模型，从而避免了预训练数据分布与后训练目标之间的不匹配。奖励信号综合了语义准确性、指令遵循、声学偏好评分与音色相似度。
+S2 Pro 采用了 **Group Relative Policy Optimization (GRPO)** 技术进行后训练对齐。我们将用于数据清洗与标注的同一套模型直接作为奖励模型 (Reward Model)，完美解决了预训练数据分布与后训练目标之间的不匹配问题。
+- **多维奖励信号**：综合评估语义准确性、指令遵循能力、声学偏好评分以及音色相似度，确保生成的每一秒语音都符合人类直觉。
 
-### 基于 SGLang 的生产级流式推理
+### 极致的流式推理性能 (基于 SGLang)
 
-由于 Dual-AR 架构在结构上与标准自回归 LLM 同构，S2 可以直接继承 SGLang 提供的 LLM 原生服务优化能力，包括连续批处理、分页 KV Cache、CUDA Graph Replay 与基于 RadixAttention 的前缀缓存。
+由于 Dual-AR 架构与标准 LLM 结构同构，S2 Pro 原生支持 SGLang 的所有推理加速特性，包括连续批处理 (Continuous Batching)、分页 KV Cache、CUDA Graph 与基于 RadixAttention 的前缀缓存。
 
-在单张 NVIDIA H200 GPU 上：
+**单张 NVIDIA H200 GPU 性能表现：**
+- **实时因子 (RTF)**：0.195
+- **首音延迟 (TTFA)**：约 100 ms
+- **极速吞吐**：在保持 RTF < 0.5 时，吞吐量达到 3,000+ acoustic tokens/s
 
-- **实时因子（RTF）：** 0.195
-- **首音频延迟：** 约 100 ms
-- **吞吐：** 在 RTF 低于 0.5 的情况下达到 3,000+ acoustic tokens/s
+### 强大的多语言支持
 
-### 多语言支持
+S2 Pro 支持 80 多种语言，无需音素或特定语言的处理即可实现高质量合成：
 
-Fish Audio S2 支持高质量的多语言文本转语音，无需音素或特定语言的预处理。包括：
-
-**英语、中文、日语、韩语、阿拉伯语、德语、法语...**
-
-**以及更多！**
-
-列表正在不断扩大，请查看 [Fish Audio](https://fish.audio/) 获取最新发布。
+- **第一梯队 (Tier 1)**：日语 (ja), 英语 (en), 中文 (zh)
+- **第二梯队 (Tier 2)**：韩语 (ko), 西班牙语 (es), 葡萄牙语 (pt), 阿拉伯语 (ar), 俄语 (ru), 法语 (fr), 德语 (de)
+- **全球覆盖**：sv, it, tr, no, nl, cy, eu, ca, da, gl, ta, hu, fi, pl, et, hi, la, ur, th, vi, jw, bn, yo, xsl, cs, sw, nn, he, ms, uk, id, kk, bg, lv, my, tl, sk, ne, fa, af, el, bo, hr, ro, sn, mi, yi, am, be, km, is, az, sd, br, sq, ps, mn, ht, ml, sr, sa, te, ka, bs, pa, lt, kn, si, hy, mr, as, gu, fo 等。
 
 ### 原生多说话人生成
 

docs/ar/index.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -75,7 +75,7 @@ Fish Audio S2 هو أحدث نموذج من [Fish Audio](https://fish.audio/).
 
 يدعم S2 التحكم الدقيق في النبرة والعاطفة داخل النص نفسه باستخدام وسوم باللغة الطبيعية مثل `[laugh]` و`[whispers]` و`[super happy]`، كما يدعم بشكل أصيل توليد متحدثين متعددين وحوارات متعددة الأدوار.
 
-يمكنك تجربة النموذج مباشرة عبر [موقع Fish Audio](https://fish.audio/)، وقراءة المزيد في [منشور المدونة](https://fish.audio/blog/fish-audio-open-sources-s2/).
+يمكنك تجربة النموذج مباشرة عبر [موقع Fish Audio](https://fish.audio/)، وقراءة المزيد في [منشور المدونة](https://fish.audio/blog/fish-audio-open-sources-s2/) و[التقرير التقني](https://arxiv.org/abs/2603.08823).
 
 ### إصدارات النموذج
 

docs/ar/inference.md

@@ -55,4 +55,44 @@ python fish_speech/models/dac/inference.py \
 
 ## استنتاج WebUI
 
-قيد التطوير.
+### 1. Gradio WebUI
+
+للحفاظ على التوافق، ما زلنا نحتفظ بواجهة Gradio WebUI السابقة.
+
+```bash
+python tools/run_webui.py # --compile إذا كنت بحاجة إلى تسريع
+```
+
+### 2. Awesome WebUI
+
+تعد Awesome WebUI واجهة ويب حديثة تعتمد على TypeScript، وتوفر ميزات أغنى وتجربة مستخدم أفضل.
+
+**بناء WebUI:**
+
+يجب أن يكون لديك Node.js و npm مثبتين على جهازك المحلي أو الخادم.
+
+1. ادخل إلى دليل `awesome_webui`:
+   ```bash
+   cd awesome_webui
+   ```
+2. تثبيت التبعيات:
+   ```bash
+   npm install
+   ```
+3. بناء WebUI:
+   ```bash
+   npm run build
+   ```
+
+**بدء تشغيل خادم الخلفية:**
+
+بعد بناء WebUI، عد إلى دليل جذر المشروع وقم بتشغيل خادم API:
+
+```bash
+python tools/api_server.py --listen 0.0.0.0:8888 --compile
+```
+
+**الوصول:**
+
+بمجرد تشغيل الخادم، يمكنك الوصول إليه عبر المتصفح على العنوان التالي:
+`http://localhost:8888/ui`

docs/en/index.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -75,7 +75,7 @@ Fish Audio S2 is the latest model developed by [Fish Audio](https://fish.audio/)
 
 S2 supports fine-grained inline control of prosody and emotion using natural-language tags like `[laugh]`, `[whispers]`, and `[super happy]`, as well as native multi-speaker and multi-turn generation.
 
-Visit the [Fish Audio website](https://fish.audio/) for live playground. Read the [blog post](https://fish.audio/blog/fish-audio-open-sources-s2/) for more details.
+Visit the [Fish Audio website](https://fish.audio/) for live playground. Read the [blog post](https://fish.audio/blog/fish-audio-open-sources-s2/) and [technical report](https://arxiv.org/abs/2603.08823) for more details.
 
 ### Model Variants
 

docs/en/inference.md

@@ -55,4 +55,44 @@ After that, you will get a `fake.wav` file.
 
 ## WebUI Inference
 
-Coming soon.
+### 1. Gradio WebUI
+
+For compatibility, we still maintain the Gradio WebUI.
+
+```bash
+python tools/run_webui.py # --compile if you need acceleration
+```
+
+### 2. Awesome WebUI
+
+Awesome WebUI is a modernized Web interface built with TypeScript, offering richer features and a better user experience.
+
+**Build WebUI:**
+
+You need to have Node.js and npm installed on your local machine or server.
+
+1. Enter the `awesome_webui` directory:
+   ```bash
+   cd awesome_webui
+   ```
+2. Install dependencies:
+   ```bash
+   npm install
+   ```
+3. Build the WebUI:
+   ```bash
+   npm run build
+   ```
+
+**Start Backend Server:**
+
+After building the WebUI, return to the project root and start the API server:
+
+```bash
+python tools/api_server.py --listen 0.0.0.0:8888 --compile
+```
+
+**Access:**
+
+Once the server is running, you can access it via your browser:
+`http://localhost:8888/ui`

docs/ja/index.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -75,7 +75,7 @@ Fish Audio S2 は [Fish Audio](https://fish.audio/) が開発した最新モデ
 
 S2 は `[laugh]`、`[whispers]`、`[super happy]` といった自然言語タグで、韻律や感情を文中の任意位置で細かく制御できます。さらに、マルチスピーカー生成とマルチターン生成にもネイティブ対応しています。
 
-ライブデモは [Fish Audio ウェブサイト](https://fish.audio/) から、詳細は [ブログ記事](https://fish.audio/blog/fish-audio-open-sources-s2/) をご覧ください。
+ライブデモは [Fish Audio ウェブサイト](https://fish.audio/) から、詳細は [ブログ記事](https://fish.audio/blog/fish-audio-open-sources-s2/) と [技術レポート](https://arxiv.org/abs/2603.08823) をご覧ください。
 
 ### モデルバリアント
 

docs/ja/inference.md

@@ -55,4 +55,44 @@ python fish_speech/models/dac/inference.py \
 
 ## WebUI 推論
 
-まもなく公開予定です。
+### 1. Gradio WebUI
+
+互換性を維持するため、以前の Gradio WebUI も引き続き利用可能です。
+
+```bash
+python tools/run_webui.py # 加速が必要な場合は --compile
+```
+
+### 2. Awesome WebUI
+
+Awesome WebUI は TypeScript で開発された、より豊富な機能と優れたユーザー体験を提供する最新の Web インターフェースです。
+
+**WebUI のビルド：**
+
+ローカルまたはサーバーに Node.js と npm がインストールされている必要があります。
+
+1. `awesome_webui` ディレクトリに移動します：
+   ```bash
+   cd awesome_webui
+   ```
+2. 依存関係をインストールします：
+   ```bash
+   npm install
+   ```
+3. WebUI をビルドします：
+   ```bash
+   npm run build
+   ```
+
+**バックエンドサーバーの起動：**
+
+WebUI のビルドが完了したら、プロジェクトのルートに戻り、API サーバーを起動します：
+
+```bash
+python tools/api_server.py --listen 0.0.0.0:8888 --compile
+```
+
+**アクセス：**
+
+サーバーが起動したら、ブラウザから以下のアドレスにアクセスして体験できます：
+`http://localhost:8888/ui`

docs/ko/index.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -75,7 +75,7 @@ Fish Audio S2는 [Fish Audio](https://fish.audio/)가 개발한 최신 모델입
 
 S2는 `[laugh]`, `[whispers]`, `[super happy]` 같은 자연어 태그를 사용해 운율과 감정을 문장 내부에서 세밀하게 제어할 수 있으며, 멀티 화자/멀티 턴 생성도 네이티브로 지원합니다.
 
-실시간 데모는 [Fish Audio 웹사이트](https://fish.audio/)에서, 자세한 내용은 [블로그 글](https://fish.audio/blog/fish-audio-open-sources-s2/)에서 확인할 수 있습니다.
+실시간 데모는 [Fish Audio 웹사이트](https://fish.audio/)에서, 자세한 내용은 [블로그 글](https://fish.audio/blog/fish-audio-open-sources-s2/)과 [기술 보고서](https://arxiv.org/abs/2603.08823)에서 확인할 수 있습니다.
 
 ### 모델 변형
 

docs/ko/inference.md

@@ -55,4 +55,44 @@ python fish_speech/models/dac/inference.py \
 
 ## WebUI 추론
 
-준비 중입니다.
+### 1. Gradio WebUI
+
+호환성을 유지하기 위해 기존의 Gradio WebUI를 보존하고 있습니다.
+
+```bash
+python tools/run_webui.py # 가속이 필요한 경우 --compile
+```
+
+### 2. Awesome WebUI
+
+Awesome WebUI는 TypeScript 기반으로 개발된 현대적인 웹 인터페이스로, 더 풍부한 기능과 향상된 사용자 경험을 제공합니다.
+
+**WebUI 빌드:**
+
+로컬 또는 서버에 Node.js와 npm이 설치되어 있어야 합니다.
+
+1. `awesome_webui` 디렉토리로 이동합니다:
+   ```bash
+   cd awesome_webui
+   ```
+2. 의존성 설치:
+   ```bash
+   npm install
+   ```
+3. WebUI 빌드:
+   ```bash
+   npm run build
+   ```
+
+**백엔드 서버 실행:**
+
+WebUI 빌드가 완료되면 프로젝트 루트로 돌아가 API 서버를 실행합니다:
+
+```bash
+python tools/api_server.py --listen 0.0.0.0:8888 --compile
+```
+
+**접속:**
+
+서버가 실행된 후 브라우저를 통해 다음 주소로 접속하면 체험할 수 있습니다:
+`http://localhost:8888/ui`

docs/pt/index.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -75,7 +75,7 @@ O Fish Audio S2 é o modelo mais recente da [Fish Audio](https://fish.audio/). T
 
 O S2 permite controle fino de prosódia e emoção dentro da própria frase com tags em linguagem natural, como `[laugh]`, `[whispers]` e `[super happy]`, além de oferecer suporte nativo a múltiplos falantes e múltiplos turnos.
 
-Acesse o [site da Fish Audio](https://fish.audio/) para testar ao vivo e leia o [post no blog](https://fish.audio/blog/fish-audio-open-sources-s2/) para mais detalhes.
+AcesVisite o [site da Fish Audio](https://fish.audio/) para demonstrações ao vivo. Leia a [postagem no blog](https://fish.audio/blog/fish-audio-open-sources-s2/) e o [relatório técnico](https://arxiv.org/abs/2603.08823) para mais detalhes.
 
 ### Variantes do Modelo
 

docs/pt/inference.md

@@ -55,4 +55,44 @@ Depois disso, você obterá um arquivo `fake.wav`.
 
 ## Inferência WebUI
 
-Em breve.
+### 1. Gradio WebUI
+
+Para manter a compatibilidade, mantemos a interface Gradio WebUI anterior.
+
+```bash
+python tools/run_webui.py # --compile se você precisar de aceleração
+```
+
+### 2. Awesome WebUI
+
+A Awesome WebUI é uma interface web moderna baseada em TypeScript, oferecendo funcionalidades mais ricas e uma melhor experiência do usuário.
+
+**Construir a WebUI:**
+
+Você precisa ter o Node.js e o npm instalados em seu computador local ou servidor.
+
+1. Entre no diretório `awesome_webui`:
+   ```bash
+   cd awesome_webui
+   ```
+2. Instale as dependências:
+   ```bash
+   npm install
+   ```
+3. Construa a WebUI:
+   ```bash
+   npm run build
+   ```
+
+**Iniciar o Servidor Backend:**
+
+Após a construção da WebUI, retorne ao diretório raiz do projeto e inicie o servidor API:
+
+```bash
+python tools/api_server.py --listen 0.0.0.0:8888 --compile
+```
+
+**Acesso:**
+
+Após o servidor ser iniciado, você pode acessá-lo através do navegador no seguinte endereço:
+`http://localhost:8888/ui`

docs/zh/index.md

@@ -36,7 +36,7 @@
     <a target="_blank" href="https://fish.audio/blog/fish-audio-open-sources-s2/">
         <img alt="Fish Audio Blog" src="https://img.shields.io/badge/Blog-Fish_Audio_S2-1f7a8c?style=flat-square&logo=readme&logoColor=white"/>
     </a>
-    <a target="_blank" href="https://github.com/fishaudio/fish-speech/blob/main/FishAudioS2TecReport.pdf">
+    <a target="_blank" href="https://arxiv.org/abs/2603.08823">
         <img alt="Paper | Technical Report" src="https://img.shields.io/badge/Paper-Technical_Report-b31b1b?style=flat-square"/>
     </a>
 </div>
@@ -75,7 +75,7 @@ Fish Audio S2 是由 [Fish Audio](https://fish.audio/) 开发的最新模型。S
 
 S2 支持通过自然语言标签（如 `[laugh]`、`[whispers]`、`[super happy]`）对韵律和情绪进行细粒度行内控制，同时原生支持多说话人和多轮生成。
 
-请访问 [Fish Audio 网站](https://fish.audio/) 体验在线演示，并阅读[博客文章](https://fish.audio/blog/fish-audio-open-sources-s2/)了解更多细节。
+请访问 [Fish Audio 网站](https://fish.audio/) 体验在线演示，并阅读[博客文章](https://fish.audio/blog/fish-audio-open-sources-s2/)和[技术报告](https://arxiv.org/abs/2603.08823)了解更多细节。
 
 ### 模型变体
 

docs/zh/inference.md

@@ -55,4 +55,44 @@ python fish_speech/models/dac/inference.py \
 
 ## WebUI 推理
 
-未完待续。
+### 1. Gradio WebUI
+
+为了保持兼容，我们保留了以往的Gradio WebUI。
+
+```bash
+python tools/run_webui.py # --compile 如果你需要加速的话
+```
+
+### 2. Awesome WebUI
+
+Awesome WebUI 是一个基于 TypeScript 开发的现代化 Web 界面，提供更丰富的功能和更好的交互体验。
+
+**构建 WebUI：**
+
+您需要先在本地或者服务器上安装 Node.js 和 npm。
+
+1. 进入 `awesome_webui` 目录：
+   ```bash
+   cd awesome_webui
+   ```
+2. 安装依赖：
+   ```bash
+   npm install
+   ```
+3. 构建 WebUI：
+   ```bash
+   npm run build
+   ```
+
+**启动后端服务器：**
+
+WebUI 构建完成后，返回项目根目录，启动 API 服务器：
+
+```bash
+python tools/api_server.py --listen 0.0.0.0:8888 --compile
+```
+
+**访问：**
+
+在服务器启动后，您可以通过浏览器访问以下地址体验：
+`http://localhost:8888/ui`

fish_speech/utils/schema.py

@@ -80,9 +80,11 @@ class ServeReferenceAudio(BaseModel):
 
 class ServeTTSRequest(BaseModel):
     text: str
-    chunk_length: Annotated[int, conint(ge=100, le=300, strict=True)] = 200
+    chunk_length: Annotated[int, conint(ge=100, le=1000, strict=True)] = 200
     # Audio format
-    format: Literal["wav", "pcm", "mp3"] = "wav"
+    format: Literal["wav", "pcm", "mp3", "opus"] = "wav"
+    # Latency mode (used by api.fish.audio; "normal" or "balanced")
+    latency: Literal["normal", "balanced"] = "normal"
     # References audios for in-context learning
     references: list[ServeReferenceAudio] = []
     # Reference id

tools/api_client.py

@@ -66,7 +66,7 @@ def parse_args():
         help="Whether to play audio after receiving data",
     )
     parser.add_argument(
-        "--format", type=str, choices=["wav", "mp3", "flac"], default="wav"
+        "--format", type=str, choices=["wav", "pcm", "mp3", "opus"], default="wav"
     )
     parser.add_argument(
         "--latency",
@@ -159,6 +159,7 @@ if __name__ == "__main__":
         ],
         "reference_id": idstr,
         "format": args.format,
+        "latency": args.latency,
         "max_new_tokens": args.max_new_tokens,
         "chunk_length": args.chunk_length,
         "top_p": args.top_p,

tools/server/api_utils.py

@@ -87,6 +87,8 @@ def get_content_type(audio_format):
         return "audio/flac"
     elif audio_format == "mp3":
         return "audio/mpeg"
+    elif audio_format == "opus":
+        return "audio/ogg"
     else:
         return "application/octet-stream"
 

tools/server/views.py

@@ -51,9 +51,27 @@ from tools.server.model_utils import (
 
 MAX_NUM_SAMPLES = int(os.getenv("NUM_SAMPLES", 1))
 
+_WEBUI_HTML = (
+    Path(__file__).parent.parent.parent / "awesome_webui" / "dist" / "index.html"
+)
+
 routes = Routes()
 
 
+@routes.http("/ui")
+class WebUI(HttpView):
+    @classmethod
+    async def get(cls):
+        from kui.asgi import HTMLResponse
+
+        if _WEBUI_HTML.exists():
+            return HTMLResponse(_WEBUI_HTML.read_text(encoding="utf-8"))
+        return JSONResponse(
+            {"error": "WebUI not built. Run: cd awesome_webui && npm run build"},
+            status_code=404,
+        )
+
+
 @routes.http("/v1/health")
 class Health(HttpView):
     @classmethod