nobodywho

nobodywho-oooEUPL-1.2活跃维护

跨平台本地大模型推理引擎,支持 Godot、Flutter、Expo 等客户端,让 LLM 在任意设备上高效离线运行。

NobodyWho is an inference engine that lets you run LLMs locally and efficiently on any device.

nobodywho-swift-v6.0.0发布于 2026-10-29 14:59 UTC1,675star +4 / 7 天101fork同步于 2026-11-11 11:46 UTC

怎么上手

由 README 提炼,执行前请确认
pip install nobodywho
from nobodywho import Chat
chat = Chat('hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M')
print(chat.ask('What is the capital of Denmark?').completed())
硬件要求按 README 说明

桌面端需 64 位 Linux/macOS/Windows(Windows 仅 x86_64),macOS 走 Metal,Linux/Windows 需 Vulkan 驱动否则回退 CPU;空闲内存约为模型文件的 1.5 倍,8GB 起步。iOS 需 iPhone 11 及以上、4GB 内存;Android 需骁龙 855/Adreno 640/6GB 内存以上。显存不足时按可用 VRAM 卸载部分层,其余跑 CPU。

需要 CUDA
下载:源码 zip·GitHub Releases(安装包)本站不镜像安装包

项目说明

由 README 自动翻译提炼

Rust 编写的本地 LLM 推理引擎,让手机、桌面和游戏引擎都能离线跑 GGUF 模型

跨平台本地大模型推理引擎,支持 Godot、Flutter、Expo 等客户端,让 LLM 在任意设备上高效离线运行。

核心能力

  • 基于 llama.cpp 推理任意 GGUF 格式聊天模型
  • 按函数签名自动生成结构化语法实现类型安全工具调用
  • 支持图像音频多模态输入与 Whisper 语音转文字
  • 内置 Kokoro 等后端本地合成 WAV 语音并做 VAD
  • 提供 Kotlin Swift Flutter React Native Python Godot 绑定

容易踩的坑

模型首次使用会从 Hugging Face 或 URL 下载并缓存,需联网;Godot 不支持 iOS 导出,Windows ARM64 和 Web 导出均不支持;本地服务器为实验性功能,默认监听 127.0.0.1:8888。

内容由模型根据 README 生成,可能不完整或不准确,以官方文档为准。看原文 README

最近发版

5 个版本nobodywho-swift-v6.0.0
  1. nobodywho-swift-v6.0.0最新正式版2026-10-29 · 2026-10-29 14:59 UTC

    6.0.0

    Added

    • Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.

    • Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.

      In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.

    Changed

    • Breaking: Several changes to how tool calls are read from a model's output:

      • With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
      • A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
      • Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given 10 received the number 10 instead of "10".
      • A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
      • A block of tool calls that can't be read is now streamed as text, not only returned in the response.
    • ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.

    Fixed

    • Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
    • A Hugging Face model path without a file name, such as hf://owner/repo, now fails with an error that shows the expected hf://owner/repo/filename.gguf format instead of a raw parser error.
  2. nobodywho-react-native-v6.0.02026-10-29 · 2026-10-29 14:04 UTC
    查看更新说明

    6.0.0

    Added

    • Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.

    • Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.

      In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.

    Changed

    • Breaking: Several changes to how tool calls are read from a model's output:

      • With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
      • A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
      • Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given 10 received the number 10 instead of "10".
      • A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
      • A block of tool calls that can't be read is now streamed as text, not only returned in the response.
    • ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.

    Fixed

    • Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
    • A Hugging Face model path without a file name, such as hf://owner/repo, now fails with an error that shows the expected hf://owner/repo/filename.gguf format instead of a raw parser error.
    • Added missing proguard-rules.pro, which should allow enabling R8 on Android.
  3. nobodywho-kotlin-v6.0.02026-10-29 · 2026-10-29 13:16 UTC
    查看更新说明

    6.0.0

    Added

    • Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.

    • Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.

      In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.

    Changed

    • Breaking: Several changes to how tool calls are read from a model's output:

      • With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
      • A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
      • Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given 10 received the number 10 instead of "10".
      • A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
      • A block of tool calls that can't be read is now streamed as text, not only returned in the response.
    • ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.

    Fixed

    • Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
    • A Hugging Face model path without a file name, such as hf://owner/repo, now fails with an error that shows the expected hf://owner/repo/filename.gguf format instead of a raw parser error.
  4. nobodywho-godot-v13.0.02026-10-29 · 2026-10-29 12:34 UTC
    查看更新说明

    13.0.0

    Added

    • Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.

    • Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.

      In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.

    Changed

    • Breaking: Several changes to how tool calls are read from a model's output:

      • With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
      • A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
      • Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given 10 received the number 10 instead of "10".
      • A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
      • A block of tool calls that can't be read is now streamed as text, not only returned in the response.
    • ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.

    Fixed

    • Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
    • A Hugging Face model path without a file name, such as hf://owner/repo, now fails with an error that shows the expected hf://owner/repo/filename.gguf format instead of a raw parser error.
  5. nobodywho-python-v5.0.02026-10-29 · 2026-10-29 10:35 UTC
    查看更新说明

    5.0.0

    Added

    • Add support for Laya decision model inference, with choices, Boolean judgments, ordinal scores, and answer probabilities.

    • Updated llama.cpp version from v0.5.0 (roughly) to v0.8.0.

      In particular, this adds support for GLM-5.3-Flash, EmbeddingGemma 2 and LiquidAI LFM3.

    Changed

    • Breaking: Several changes to how tool calls are read from a model's output:

      • With tools, a chat now fails to start if the model's vocabulary doesn't have its format's tool call markers as single special tokens. All supported models have them.
      • A tool call cut off by stopping the generation or by the token limit is now kept as text and never runs. An LFM2 call could run before.
      • Qwen3.5, Qwen3.6 and FunctionGemma tool calls now pass an argument to the tool with the type its schema gives. Previously anything that parsed as JSON was converted, so a string parameter given 10 received the number 10 instead of "10".
      • A tool call marker a model writes inside its reasoning is now part of the reasoning, and no longer starts a tool call.
      • A block of tool calls that can't be read is now streamed as text, not only returned in the response.
    • ONNX Runtime, used for speech-to-text, text-to-speech and voice activity detection, is updated from 1.28 to 1.31.

    Fixed

    • Conversation history as rendered to the LLM now matches exactly what the model saw and wrote. Previously some special tokens and whitespace could be added or lost. This can change output, but probably won't do so much.
    • A Hugging Face model path without a file name, such as hf://owner/repo, now fails with an error that shows the expected hf://owner/repo/filename.gguf format instead of a raw parser error.

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    README 原文

    未翻译

    Discord Matrix Mastodon Pub.dev Version PyPI Version npm Version Godot Engine Contributor Covenant Docs


    Features

    • Run locally, offline — no API keys needed or hidden fees
    • Run any chat LLM — Gemma, Qwen, Mistral and more
    • Fast, type-safe tool calling — automatically generates structured grammars from your function signatures, no schema writing needed
    • Multimodal input — provide image and audio information to your LLM
    • Text-to-speech — synthesize local WAV audio with Kokoro, Pocket TTS and Supertonic backends
    • Speech-to-text — transcribe audio into text with Whisper
    • Voice Activity Detection — know when to stop listening and start transcribing with Silero
    • Model downloading — load models directly from Hugging Face or any URL

    Under the Hood

    flowchart TD
        FL["Flutter"]:::lang
        PY["Python"]:::lang
        GO["Godot"]:::lang
        K["Kotlin"]:::lang
        S["Swift"]:::lang
        RN["React Native"]:::lang
    
        FRB["flutter_rust_bridge"]:::glue
        P3["PyO3"]:::glue
        GX["gdext"]:::glue
        U["UniFFI"]:::glue
    
        FL --> FRB
        PY --> P3
        GO --> GX
        K --> U
        S --> U
        RN --> U
    
        CORE["NobodyWho · Rust<br/>chat · templates · grammars · sampling · context shifting"]:::core
    
        FRB --> CORE
        P3 --> CORE
        GX --> CORE
        U --> CORE
    
        CORE --> LCPP["llama.cpp<br/>text · vision · embeddings · reranking"]:::engine
        CORE --> ORT["ONNX Runtime<br/>speech-to-text · text-to-speech · VAD"]:::engine
    
        LCPP --> HW["Hardware<br/>Vulkan · Metal · CUDA · GPU · CPU"]:::hw
        ORT --> HW
    
        classDef lang fill:#e8eefc,stroke:#5b7bd5,color:#11204a
        classDef glue fill:#f3f0fb,stroke:#8b7bd5,color:#2a1f4a
        classDef core fill:#eaf6ee,stroke:#4fa46a,color:#0f3b1f
        classDef engine fill:#fdf0e3,stroke:#d58f3b,color:#4a2d0b
        classDef hw fill:#f0eeea,stroke:#a09a90,color:#3a352e
    
    • GPU-accelerated inference via Vulkan or Metal — runs fast on any OS
    • Compatible with thousands of pre-trained LLMs — use any LLM in the GGUF format
    • Powered by the wonderful llama.cpp

    You can test our inference engine on iOS, Android, Vision Pro and Apple Watch.


    Platforms

    BindingInstallRuns onDocumentation
    KotlinMaven CentralDesktop, Androiddocs.nobodywho.ooo/kotlin
    SwiftSPMmacOS, iOS, visionOS, watchOSdocs.nobodywho.ooo/swift
    React Native / ExponpmDesktop, Android, iOSdocs.nobodywho.ooo/js
    Flutterpub.devDesktop, Android, iOSdocs.nobodywho.ooo/flutter
    PythonPyPIDesktopdocs.nobodywho.ooo/python
    GodotAssetLibDesktop, Androiddocs.nobodywho.ooo/godot

    Desktop means Linux, macOS and Windows throughout. Three gaps worth knowing before you start:

    • Godot has no iOS export. Use the Flutter, React Native or Swift binding on iOS.
    • Windows ARM64 is not supported yet.
    • There is no web export. It is tracked in issue #111.

    ⭐ Useful to you? Star the repo, it's the easiest way to say thanks.

    Requirements

    Inference uses the GPU where available and CPU where not. The real constraint is memory.

    Desktop

    • Hardware — any 64-bit Linux, macOS or Windows machine. Windows is x86_64 only, there are no ARM64 Windows builds. macOS accelerates through Metal out of the box, Linux and Windows need a GPU driver with Vulkan support and fall back to CPU without one.
    • Memory — roughly 1.5× the model file in free RAM, or 2× on a machine that's already busy. 8 GB is a comfortable floor for models up to ~2 GB; 16 GB or more above that.
    • Discrete GPUs — NobodyWho offloads as many layers as fit in free VRAM and runs the rest on the CPU, so a model larger than your VRAM still works, just slower. If barely any of it fits, it skips the GPU and stays on CPU. It uses one GPU, the card with the most free memory.

    Mobile

    • iOS — iPhone 11 or newer, 4 GB RAM or more.
    • Android — Snapdragon 855 / Adreno 640 / 6 GB RAM or better.
    • Rule of thumb — the device needs roughly twice the model file size in available RAM. iOS reserves around 2 GB, Android 2 to 4 GB depending on vendor. Models under 1 GB run smoothly on any phone.

    Models

    Any model in the GGUF format works. Pass a hf:owner/repo:QUANT reference, an HTTPS URL, or a local path anywhere a model path is expected; remote models are downloaded and cached on first use. Pass "auto" to fit one to available memory.

    Start with Qwen3 0.6B: it is small enough for any phone and good enough to tell whether the integration works.


    Quick Start

    pip install nobodywho
    
    from nobodywho import Chat
    
    chat = Chat('hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M')
    response = chat.ask('What is the capital of Denmark?')
    print(response.completed()) # The capital of Denmark is Copenhagen.
    

    Python documentation · PyPI

    // Android
    implementation("ai.nobodywho:nobodywho-android:<version>")
    
    // Desktop JVM (Linux, macOS, Windows)
    implementation("ai.nobodywho:nobodywho:<version>")
    

    Use the version from the Maven Central badge above.

    import ai.nobodywho.Chat
    
    val chat = Chat.fromPath(
        modelPath = "hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M"
    )
    
    val response = chat.ask("What is the capital of Denmark?").completed()
    println(response) // The capital of Denmark is Copenhagen.
    

    Kotlin documentation

    Add via Swift Package Manager:

    https://github.com/nobodywho-ooo/nobodywho-swift.git
    
    import NobodyWho
    
    let chat = try await Chat.fromPath(
        modelPath: "hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M"
    )
    
    let response = try await chat.ask("What is the capital of Denmark?").completed()
    print(response) // The capital of Denmark is Copenhagen.
    

    Swift documentation · GitHub · starter app

    # React Native
    npm install react-native-nobodywho
    
    # Expo
    npx expo install react-native-nobodywho
    
    import { Chat } from "react-native-nobodywho";
    
    const chat = await Chat.fromPath({
      modelPath: "hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M",
    });
    
    const msg = await chat.ask("What is the capital of Denmark?").completed();
    console.log(msg); // The capital of Denmark is Copenhagen.
    

    RN / Expo documentation · NPM · RN starter app · Expo starter app

    flutter pub add nobodywho
    
    import 'package:nobodywho/nobodywho.dart' as nobodywho;
    
    void main() async {
      await nobodywho.NobodyWho.init();
    
      final chat = await nobodywho.Chat.fromPath(
        modelPath: 'hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M',
      );
    
      final msg = await chat.ask('What is the capital of Denmark?').completed();
      print(msg); // The capital of Denmark is Copenhagen.
    }
    

    Flutter documentation · pub.dev · starter app

    Install NobodyWho from inside the editor:

    1. In Godot 4.5+, open the AssetLib tab and search for NobodyWho.
    2. Download and import it, making sure Ignore asset root is ticked in the import dialogue.
    3. Reload the project.

    You can also grab a specific version from the releases page and import the zip the same way.

    Godot documentation

    NobodyWho provides an experimental local server that implements the OpenAI Chat Completions API.

    Start the server :

    uvx --from 'git+https://github.com/nobodywho-ooo/nobodywho.git#subdirectory=nobodywho/server' nobodywho-server --model hf:NobodyWho/Qwen_Qwen3-0.6B-GGUF:Q4_K_M --name qwen
    

    It listens on http://127.0.0.1:8888 and serves /v1/models and /v1/chat/completions. See the docs for more info.


    Documentation

    The documentation has everything you might want to know: https://docs.nobodywho.ooo/

    Working with a coding agent? Point it at llms.txt or llms-full.txt, or install the NobodyWho skill so your agent can look up the current APIs and documentation:

    npx skills add https://github.com/nobodywho-ooo/nobodywho --skill nobodywho

    Community

    ⭐ Star the repo if NobodyWho is useful to you. It is how people find us.

    License

    NobodyWho is licensed under the EUPL-1.2. You may use it in proprietary and commercial projects, free of charge. There has been some confusion about this, so to be precise:

    Linking two programs or linking an existing software with your own work does not – at least under European law – produce a derivative or extend the coverage of the linked software licence to your own work. [1]

    If you distribute modified versions of the code in this repo, you must open source those changes.

    Feel free to make proprietary projects using NobodyWho, but don't make a proprietary fork of NobodyWho.

    The Kokoro text-to-speech backend converts text to phonemes with espeak-ng, which is licensed under GPL-3.0-or-later. It is compiled in through the kokoro Cargo feature, which is on by default, so the prebuilt packages include it. If you don't need Kokoro, you can build without it, for example with cargo build -p nobodywho-godot --release --no-default-features in the nobodywho/ directory. Supertonic and Pocket TTS work either way.