# oobabooga/text-generation-webui: The Premier Local LLM Interface

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oobabooga/text-generation-webui is a powerful and versatile web UI for running large language models (LLMs) locally. It offers a 100% offline and private environment for text generation, vision, tool-calling, and even training, all accessible through an intuitive interface and API.

GitHub: https://github.com/oobabooga/text-generation-webui
OSRepos URL: https://osrepos.com/repo/oobabooga-text-generation-webui

## Summary

oobabooga/text-generation-webui is a powerful and versatile web UI for running large language models (LLMs) locally. It offers a 100% offline and private environment for text generation, vision, tool-calling, and even training, all accessible through an intuitive interface and API.

## Topics

- Python
- LLM
- AI
- Text Generation
- Local Inference
- Machine Learning
- Open Source
- Web UI

## Repository Information

Last analyzed by OSRepos: Fri May 01 2026 20:04:28 GMT+0100 (Western European Summer Time)
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GitHub clicks: 3

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## Content

## Introduction

oobabooga/text-generation-webui is recognized as the original and leading local interface for Large Language Models (LLMs). This project provides a comprehensive solution for interacting with LLMs, offering capabilities such as text generation, vision integration, tool-calling, and model training. Designed for complete privacy and offline operation, it features both a user-friendly web UI and a robust API. With over 46,914 stars and 5,970 forks, it stands as a highly popular choice for local AI experimentation and development.

## Installation

Getting started with oobabooga/text-generation-webui is designed to be straightforward, offering several installation methods to suit different user needs.

### Portable Builds

For the quickest setup, portable builds are available. These require zero setup: simply download, unzip, and run. They include all dependencies and are compatible with GGUF (llama.cpp) models.

[Download Portable Builds](https://github.com/oobabooga/textgen/releases){:target="_blank"}

### One-Click Installer

For users requiring additional backends (like ExLlamaV3, Transformers), training capabilities, image generation, or extensions, the one-click installer is recommended. This method simplifies the setup process, handling dependencies like PyTorch automatically.

1.  Clone the repository or [download its source code](https://github.com/oobabooga/textgen/archive/refs/heads/main.zip){:target="_blank"} and extract it.
2.  Run the startup script for your OS: `start_windows.bat`, `start_linux.sh`, or `start_macos.sh`.
3.  Follow the prompts to select your GPU vendor.

### Manual Portable Install with venv

For those who prefer a manual setup within a Python virtual environment, follow these steps:

bash
# Clone repository
git clone https://github.com/oobabooga/textgen
cd textgen

# Create virtual environment
python -m venv venv

# Activate virtual environment (example for macOS/Linux)
source venv/bin/activate

# Install dependencies (choose appropriate file under requirements/portable)
pip install -r requirements/portable/requirements.txt --upgrade

# Launch server
python server.py --portable --api --auto-launch


For detailed instructions and other installation methods, including Conda and Docker, please refer to the [official documentation](https://github.com/oobabooga/textgen/wiki){:target="_blank"}.

## Examples

The web UI provides a rich set of features for interacting with LLMs:

*   **Chat & Generation**: Engage with models in `instruct` mode for instruction-following, `chat-instruct`/`chat` for custom characters, or use the `notebook` tab for free-form text generation.
*   **Multimodal Capabilities**: Attach images to messages for visual understanding and upload text, PDF, or .docx documents to discuss their contents.
*   **Flexible Backends**: Seamlessly switch between various LLM backends, including `llama.cpp`, `Transformers`, `ExLlamaV3`, and `TensorRT-LLM`, without restarting the application.
*   **OpenAI/Anthropic-compatible API**: Utilize a local API that mimics OpenAI/Anthropic endpoints, complete with tool-calling support, making it a drop-in replacement for many applications.
*   **Tool-Calling**: Enable models to execute custom functions, such as web search or math operations, defined as simple Python files.
*   **Training & Image Generation**: Fine-tune LoRAs on datasets and generate images using `diffusers` models like Z-Image-Turbo, all within the same interface.

## Why Use It

oobabooga/text-generation-webui stands out for several compelling reasons:

*   **Complete Privacy**: Operates 100% offline with zero telemetry, ensuring your data and interactions remain private.
*   **Versatility**: Supports a wide array of LLM backends, multimodal inputs, tool-calling, and even training and image generation, making it a comprehensive AI toolkit.
*   **Ease of Use**: Offers portable builds and a one-click installer for quick setup, alongside a user-friendly web interface.
*   **Active Community**: Benefits from a vibrant community, providing support and contributing to its continuous development.

## Links

*   **GitHub Repository**: [oobabooga/text-generation-webui](https://github.com/oobabooga/textgen){:target="_blank"}
*   **Documentation**: [TextGen Wiki](https://github.com/oobabooga/textgen/wiki){:target="_blank"}
*   **Community**: [r/Oobabooga on Reddit](https://www.reddit.com/r/Oobabooga/){:target="_blank"}