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Uncensored AI Studio

A premium, zero-configuration local AI studio and offline GUI for Stable Diffusion (Image Generation), LLMs (Chat), Whisper (Speech-to-Text), and Kokoro (Text-to-Speech). Powered by hardware-accelerated GPU and NPU execution on Windows, Linux, and macOS.

100% Offline Platforms License

Uncensored AI Studio Video Tutorial

📖 Table of Contents

📖 What is Uncensored AI Studio?

Uncensored AI Studio is a completely offline, zero-setup, self-contained AI studio for Windows, Linux, and macOS. Unlike cloud-based AI systems, it runs entirely on your own hardware with no censorship, tracking, subscriptions, or login requirements.

It unifies four major local AI capabilities into one high-performance desktop interface:

  1. 🎨 Image Generation (Stable Diffusion): Generate and edit high-quality images offline using .safetensors, .gguf, or .ckpt model weights.
  2. 💬 Text Chat (LLMs): Converse privately with open-source language models (GGUF format) powered by official, high-performance llama.cpp backends.
  3. 🎙️ Speech-to-Text (Whisper): Transcribe voice recordings and speech to text in real-time with an integrated whisper.cpp engine.
  4. 🗣️ Text-to-Speech (Kokoro TTS): Convert text outputs into highly natural, lifelike vocal audio offline using the Kokoro-82M ONNX model.

🌟 Key Features

  • 100% Offline & Private: Run inferences locally. No internet, telemetry, cloud logging, or API keys required.
  • Zero-Install Portability: Entire runtime (Node.js, models, GPU backends) is self-contained. Zero global system environment changes.
  • Auto-Configured Acceleration: Auto-detects hardware specs to load CUDA (Nvidia), ROCm (AMD), Vulkan (Intel/AMD/NVIDIA), Metal (macOS), or OpenVINO (Intel NPU) backends.
  • Integrated Model Manager: Paste any Hugging Face model-page or direct-file link (the studio resolves it to the right file and folder automatically), drag-and-drop local weights to import them, or batch-download any number of library models in one go — image and text models download in parallel (up to 3 at once) for maximum speed, with live per-model progress. The built-in catalog includes uncensored and vision models.
  • Smart Hugging Face Import: Paste any huggingface.co/.../resolve/main/... URL — the studio detects the model type from the file extension (GGUF → chat, safetensors → image, bin → speech) and saves it into the right folder automatically.
  • Live Performance Monitor: Track CPU, RAM, GPU, and VRAM utilization in real-time directly inside the web UI.
  • Local Output Gallery: Saves generated images side-by-side with prompt parameters and metadata JSON files.
  • 🕵️ Uncensored Model Library: One-click curated uncensored text models (Gemma 2 Abliterated, Gemma 4 Heretic, Qwen 3.5 9B, NemoMix 12B, Dolphin, Mistral…) and uncensored image checkpoints (Pony Diffusion V6 XL…).
  • 🤖 AI Agents (CLI): Install and run real coding agents — Qwen Code, Aider, OpenCode, Claude Code, Codex — from the web UI, with a live output console. One-click auto-install (no terminal) installs the agent and connects it to your local llama.cpp server automatically once the install finishes, for fully offline coding.
  • 🖥️ Server Tab: Launch, stop and diagnose the local runtimes (llama.cpp, Stable Diffusion, whisper, Kokoro) — live status, ports, the exact model-loading error, and a live in-memory log tail.
  • ⌨️ Terminal Tab: A real, persistent web terminal that runs shell commands on the local server (in the project folder) — uses Git Bash on Windows so Unix commands (ls, pwd, grep, tar) work, and keeps your session state (cd, export, current folder) alive between commands. Install tools or fix models without leaving the browser.
  • 🎬 Video Generation: Generate videos from text via external APIs (MiniMax H3 and any OpenAI-compatible video endpoint), with task tracking and a saved-video gallery.
  • 🗣️ Voice Chat: Talk to your models — press the mic, speak in 10+ languages, the reply is read aloud. Multi-language voice input and output.
  • 🌐 Web Search in Chat: Optional live web search (DuckDuckGo) so local models can answer with up-to-date sources.
  • 🧩 Core Features + Real External Plugins: Every built-in feature (image/text/voice generation, chat, model downloads, history…) is a core system capability — always installed, always on, never a toggleable plugin. Optional third-party plugins live in the plugins/ folder (see plugins/README.md): drop a folder with a plugin.json (+ optional run.cjs script), refresh the Plugins tab, and enable/disable or even run them from the UI.
  • 🌗 Appearance Themes: Switch the whole UI between light, dark, high-contrast and AMOLED looks.
  • 🖥️ Desktop Launcher: One click creates a launcher shortcut on your desktop.
  • 🗃️ Model Load History: See every model you've loaded in Text/Image/Speech/TTS with timestamps.
  • 🌍 Multi-language TTS: 50+ Kokoro voices across 9 languages — French is on by default (Kokoro ff_siwis voice) — plus one-click system-voice playback for French, Spanish, German, Italian, Portuguese, Japanese, Chinese and more.

⚙️ Workspace & Engine Architecture

To avoid exhausting system RAM or VRAM, text and image engines are mutually exclusive by default. You can switch between workspaces inside the UI:

  • Image Generation Workspace: Uses a dedicated stable-diffusion.cpp backend node. Model weights are stored in app/models/.
  • Text Chat Workspace: Uses a portable llama.cpp server backend. Model weights (.gguf) are stored in app/llm-models/. A small Qwen2.5 Coder starter model can be downloaded directly from the Text Chat panel.
  • Speech Worker (Whisper): Runs a localized whisper-cli process to convert your vocal input to text.
  • Audio Output (Kokoro TTS): Utilizes kokoro-js locally on the server side to read responses in natural voices.

Supported Models

The app is designed around single-file local models that can be loaded directly by the bundled backend engines.

Image generation

Model type Supported Put files in Notes
Stable Diffusion 1.5 checkpoints Yes app/models/ Best compatibility. Use .safetensors or .ckpt files.
SDXL checkpoints Yes app/models/ Supported as single-file checkpoints. Requires more RAM/VRAM than SD 1.5.
Single-file SD/SDXL GGUF checkpoints Limited app/models/ Only complete single-file checkpoints are supported.
OpenVINO image model folders Intel NPU only app/openvino-models/ Download from the Model Manager after running the OpenVINO setup.
CoreML image models Apple Silicon only app/models/ Requires macOS on Apple Silicon and the CoreML setup path.
Flux, HiDream, Hunyuan, Wan, Qwen Image, Z-Image workflows No N/A These usually require separate diffusion, VAE, and text encoder files and are not one-click checkpoint loads in this app.
LoRA, ControlNet, VAE-only, text-encoder-only, or diffusion-only files No N/A Companion files are not loaded as standalone image models.

Known-good image models available from the Model Manager:

Name Filename Type Approx. size Recommended use
Juggernaut XL v9 Lightning Juggernaut_RunDiffusionPhoto2_Lightning_4Steps.safetensors SDXL 6.6 GB High-quality photorealism on mid/high tier machines.
DreamShaper XL Lightning DreamShaperXL_Lightning.safetensors SDXL 6.6 GB General SDXL images, fantasy, renders, and illustration.
RealVisXL V5.0 RealVisXL_V5.0_fp16.safetensors SDXL 6.9 GB Top-tier photorealistic SDXL portraits & scenes.
Stable Diffusion XL Base 1.0 sd_xl_base_1.0.safetensors SDXL 6.9 GB The official SDXL base model.
Animagine XL 3.1 animagine-xl-3.1.safetensors SDXL 6.9 GB Premium anime / illustration SDXL model.
DreamShaper 8 DreamShaper_8_pruned.safetensors SD 1.5 2.1 GB Faster, lower-memory image generation.
CyberRealistic V8 CyberRealistic_V8_FP16.safetensors SD 1.5 2.0 GB Realistic SD 1.5 images and lower-memory systems.
Rev Animated rev-animated-v1-2-2.safetensors SD 1.5 2.0 GB Stylized/anime SD 1.5 images.
Realistic Vision V5.1 Realistic_Vision_V5.1_fp16-no-ema.safetensors SD 1.5 2.1 GB One of the most popular realistic SD 1.5 models.
Deliberate v2 Deliberate_v2.safetensors SD 1.5 2.1 GB Versatile fantasy / semi-realistic SD 1.5 model.
Counterfeit V3.0 Counterfeit-V3.0_fix_fp16.safetensors SD 1.5 2.1 GB High-quality anime / illustration SD 1.5 model.
LCM DreamShaper OpenVINO OpenVINO/LCM_Dreamshaper_v7-fp16-ov OpenVINO 2.7 GB Intel Core Ultra NPU test model.

Text, speech, and TTS

Workspace Supported model files Put files in Notes
Text Chat .gguf llama.cpp models app/llm-models/ Use single-file GGUF chat/instruct models. Vision models may also require a matching mmproj file.
Speech-to-Text whisper.cpp .bin models app/speech-models/ Use Whisper GGML/whisper.cpp model files.
Text-to-Speech Kokoro .json manifests and model assets app/tts-models/ / app/tts-runtime/ Use the built-in Kokoro setup and Model Manager entries.

Note

Linux release binaries are built for Ubuntu 24.04-era systems and require glibc 2.38+ plus GLIBCXX_3.4.32+. On older Ubuntu/Debian VMs, a model such as CyberRealistic may be valid but the backend can still fail before loading it. Upgrade the VM OS or build the backend from source.

📁 Folder Architecture

Uncensored-AI-Studio/
├── windows.bat                # Windows Launcher (Double-click entrypoint)
├── linux.sh                   # Linux Launcher (Terminal entrypoint)
├── mac.sh                     # macOS Launcher (Terminal entrypoint)
├── LICENSE                    # MIT Open Source License
├── .gitignore                 # Excludes models and output images from version control
├── README.md                  # Detailed system documentation
├── scripts/
│   ├── setup/                 # Platform setup and backend installers
│   ├── reset/                 # Clean install & environment repair
│   ├── server/                # UI web server and backend lifecycle manager
│   ├── workers/               # Local worker processes
│   ├── build/                 # Optional source build helpers
│   └── config/                # Runtime configuration catalogs
└── app/
    ├── frontend/              # UI source code (Vite + React)
    ├── models/                # Place image weights here (.safetensors, .gguf, .ckpt)
    ├── llm-models/            # Place text GGUF weights here
    └── outputs/               # Saved images and parameters metadata

🚀 Getting Started

Ensure you have a modern web browser installed. Follow the quick guide below for your platform:

Windows Setup

  1. Launch: Double-click windows.bat.

    [!NOTE] On the first run, the script will automatically download a portable Node.js runtime and configure pre-compiled GPU/CPU backend binaries.

  2. Add Models: Drop .safetensors, .gguf, or .ckpt weights into app/models/ (or download them via the Model Manager tab in the UI).
  3. Generate: Open http://localhost:1420 in your browser, select your model, and write a prompt.

Linux Setup

  1. Make executable: Open a terminal in the project folder and make the script executable: 
    chmod +x linux.sh
  2. Launch: Run ./linux.sh.
    • NVIDIA GPU Users: You will be prompted to set up the high-performance CUDA backend (downloads prebuilt or automatically compiles from source as a fallback).
    • AMD Radeon Performance: Run with ./linux.sh --max-perf to add the ROCm backend (~1.3 GB download).
    • Intel Core Ultra NPU: Run with ./linux.sh --setup-openvino to configure Intel NPU support (requires Intel Linux NPU driver).
  3. Add Models: Drop your weights into app/models/ or download them via the Model Manager tab.
  4. Generate: Open http://localhost:1420 in your browser.

macOS Setup

  1. Make executable: Open a terminal in the project folder and make the script executable: 
    chmod +x mac.sh
  2. Launch: Run ./mac.sh.

    [!IMPORTANT] The prebuilt macOS backend is optimized for Apple Silicon (M1 or newer) and uses Metal GPU acceleration. (macOS Intel hardware is completely unsupported).

  3. Add Models: Drop your weights into app/models/ or download them via the Model Manager tab.
  4. Generate: Open http://localhost:1420 in your browser.

🖥️ Hardware Compatibility & Acceleration

Windows

GPU Vendor Tech Status Notes
Nvidia CUDA ✅ Native Maps sd-cuda.exe with Nvidia SDK 12 optimizations.
AMD Radeon Vulkan ✅ Native Maps sd-vulkan.exe with Vulkan API acceleration.
Intel Arc Vulkan ✅ Native Maps sd-vulkan.exe for Intel hardware.
Integrated / None CPU ⚠️ Fallback Runs on logical CPU threads (slow).

Linux

GPU Vendor Primary Fallback Notes
NVIDIA CUDA / Vulkan Vulkan / CPU Auto-detects NVIDIA. Prompt-driven CUDA setup downloads prebuilt or compiles from source. Falls back to Vulkan for GTX.
AMD Radeon ROCm Vulkan ROCm provides best AMD performance when host ROCm drivers are available.
Intel Arc / integrated Vulkan CPU Cross-vendor Vulkan support.
Intel Core Ultra NPU OpenVINO NPU CPU Requires the Intel Linux NPU driver, kernel 6.6+, Python 3, and ./linux.sh --setup-openvino.
Integrated / None CPU — Runs on logical CPU threads (slow).

macOS

Hardware Primary Fallback Notes
Apple Silicon (M1 or newer) Metal CPU Uses the official Darwin arm64 stable-diffusion.cpp backend.

Important

System Requirements & Notes:

  • 64-bit Windows 10 or Windows 11 is required for the portable Node.js 22 runtime used by the Windows launcher.
  • glibc 2.38 or newer is required for the prebuilt Linux backends (Ubuntu 24.04, Fedora 40+, etc.). The setup script will warn you if your glibc is older.
  • Linux runtime libraries: The prebuilt backends require libgomp.so.1; Vulkan additionally requires libvulkan.so.1 and a working GPU driver. The setup script now checks these before installing a backend and prints the exact distro package command when one is missing.
  • Linux OpenVINO NPU: Intel Core Ultra, x86_64 Linux, kernel 6.6+, a working /dev/accel/accel0 device, Python 3 with venv, and the Intel Linux NPU driver are required.

🛠️ Troubleshooting & FAQ

Reset Environment: If a build fails or you want to clear dependencies

Run scripts/reset/reset.ps1 (Windows) or scripts/reset/reset.sh (Linux/macOS). This will clear temporary compilation and package caches to repair your environment. (Note: This preserves your model weights and generated output images).

Linux backends fail to start with GLIBC_2.38 not found

The prebuilt binaries require glibc 2.38+ (e.g. Ubuntu 24.04). If your distribution uses an older glibc version, you can upgrade your operating system or compile the backend from source (see the Building From Source guide below).

Port Conflicts: Default port address already busy

The web user interface runs on port 1420 by default. The GPU backend manager attempts to bind to port 8080 first, then automatically detects and falls back to a free system port if 8080 is already occupied.

Linux ROCm not loading for AMD Radeon GPUs

Ensure your AMD GPU hardware and host kernel are fully compatible with ROCm 7.13. If ROCm fails to initialize correctly, the application will automatically fall back to Vulkan acceleration.

Linux uses the integrated GPU instead of the discrete GPU

On dual-GPU Linux systems, Vulkan device order can put the integrated Intel GPU at vulkan0 and the discrete AMD/NVIDIA GPU at vulkan1. The launcher now tries to prefer a discrete Vulkan device when vulkaninfo --summary is available. To force a device manually, start the app with SD_VULKAN_DEVICE=vulkan1 ./linux.sh or use another index such as vulkan0/vulkan2.

Windows exits with code 3221225781 (0xC0000135)

This code means Windows could not locate a required backend DLL:

  • For AMD/Intel Vulkan: Update your GPU driver to one with full Vulkan runtime support, then rerun the setup script to restore app/backend/win/vulkan/.
  • For NVIDIA CUDA: Install or update your NVIDIA graphics driver, then rerun the setup script to restore the CUDA runtime DLLs.
Generation shows "server is not responding or crashed"

This indicates that the local backend engine process terminated. Check your launch terminal (where you executed windows.bat, ./linux.sh, or ./mac.sh) for the exact console error. Common causes include glibc version mismatches, missing Vulkan drivers, or system out-of-memory (OOM) issues.

🧭 The New Tabs & Features

Beyond the classic four workspaces, the studio now ships a full plugin ecosystem:

Tab What it does
Install & History Shows install status of every component (Node, llama.cpp, whisper, Kokoro, SD backend), model counts, free disk space, and a log of every model you've loaded.
AI Agents Install & run local coding agents (Qwen Code, Aider, OpenCode, Claude Code, Codex) with a live output console. Works with your local GGUF models or cloud APIs.
Video Generator Three providers: Local animated GIF (offline, no API key — frames from your SD model), MiniMax H3 (768P/2K), or any OpenAI-compatible endpoint. Tasks are tracked and videos land in app/videos/.
Plugins A 33-plugin library in 5 categories (Generation, Conversation & Agents, Internet & Models, Hardware & Backends, Interface & UX) — including Batch Model Downloads, One-Click Agent Install and Connect Local Server to Agents. Disabling a gated plugin hides its feature from the UI.
Text Chat extras 🌐 Web search toggle, 🎤 voice input (10+ languages), 🔊 spoken replies (voice-chat mode), DeepThink reasoning.
TTS 50+ Kokoro voices across 9 languages (incl. French Siwis) + one-click system-voice playback for many more languages.

Voice Chat: In the Text Chat tab, press the 🎤 Voice button, pick a language (FR, EN, ES, DE…), and speak. Your words are transcribed, answered by the local LLM, and the reply is read aloud automatically when Talk mode is on.

AI Agents: Open the AI Agents tab → pick an agent (e.g. Qwen Code) → press ⚡ Auto-install (or follow the one-line install command in a terminal) → press Refresh → optionally press Connect local to run it against your loaded local model → write a prompt and press Run. Output streams into the on-screen console.

HF URL Import: In the Model Manager, paste any https://huggingface.co/<org>/<repo> model page link (or a direct /resolve/... file link) — the studio resolves it to the best downloadable file, detects the model kind from the extension, and downloads it into the correct folder automatically. Tick several library models and press Download selected to fetch them in parallel.

📚 Documentation

🔨 Building From Source

The setup script (scripts/setup/setup.sh) now automates building and setting up the CUDA backend from source when selected. If you want to manually build all backends (CPU, Vulkan, and CUDA) at once, you can run the included scripts/build/build_from_source.sh script.

For macOS, the included scripts/build/build_from_source.sh builds the Metal backend and copies it to app/backend/mac/sd.

Requirements

  • git, cmake, make (or ninja), and a C++17 compiler (g++ / clang++).
  • For CUDA: the NVIDIA CUDA toolkit (nvcc) must be on your PATH.
  • For Vulkan: the Vulkan SDK / loader, a compatible driver, and glslc (Ubuntu/Debian package: glslc).
  • For ROCm: AMD ROCm development libraries.
  • For macOS Metal: Apple Command Line Tools or Xcode.

Build commands

# 1. Clone upstream
git clone https://github.com/leejet/stable-diffusion.cpp.git
cd stable-diffusion.cpp
mkdir build && cd build

# 2. Configure for your backend (pick ONE)
# CPU only
cmake .. -DSD_BUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release

# CUDA
cmake .. -DSD_CUDA=ON -DSD_BUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release

# Vulkan
cmake .. -DSD_VULKAN=ON -DSD_BUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release

# ROCm
cmake .. -DSD_HIPBLAS=ON -DSD_BUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release

# macOS Metal
cmake .. -DSD_METAL=ON -DSD_BUILD_SHARED_LIBS=ON -DCMAKE_BUILD_TYPE=Release

# 3. Build
cmake --build . --config Release -j$(getconf _NPROCESSORS_ONLN 2>/dev/null || sysctl -n hw.ncpu)

# 4. Copy the binaries into this project
cp bin/sd* /path/to/Uncensored-AI-Studio/app/backend/linux/<backend>/

After copying, rename the server binary to match what scripts/server/serve.cjs expects:

  • Vulkan: sd → sd-vulkan
  • ROCm: sd → sd-rocm

Then restart the app with ./linux.sh (Linux) or ./mac.sh (macOS).

📝 License

This project is licensed under the MIT License - see the LICENSE file. Bundles stable-diffusion.cpp (MIT License). Model weights are subject to their respective creators' licenses.

About

Portable AI Studio — your complete local AI studio that runs entirely from a USB stick. Uncensored text & image generation, video (MiniMax H3 + local GIFs), 50+ multilingual TTS voices, voice chat, web search, coding agents, Hugging Face import, 30 plugins. 100% offline & private.

Topics

aiaiderclaude-codecodexcoremlhuggingfacellmlocal-aioffline-aiopenvinoportable-appprivacyqwenstable-diffusiontext-to-speechttsuncensored-aiusbvideo-generationvoicechat

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