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Aether 👋

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Aether Banner

Aether is an extensible, feature-rich, and user-friendly self-hosted AI platform designed to operate entirely offline. It supports various LLM runners like Ollama and OpenAI-compatible APIs, with a built-in inference engine for RAG, making it a powerful AI deployment solution.

Key Features ⭐

  • 🚀 Effortless Setup: Install seamlessly using Docker or Kubernetes (kubectl, kustomize or helm) for a hassle-free experience with support for both :ollama and :cuda tagged images.

  • 🤝 Ollama/OpenAI API Integration: Effortlessly integrate OpenAI-compatible APIs for versatile conversations alongside Ollama models. Customize the OpenAI API URL to link with LMStudio, GroqCloud, Mistral, OpenRouter, and more.

  • 🛡️ Granular Permissions and User Groups: Administrators can create detailed user roles and permissions, ensuring a secure and customized user environment.

  • 📱 Responsive Design: Enjoy a seamless experience across Desktop PC, Laptop, and Mobile devices.

  • 📱 Progressive Web App (PWA) for Mobile: Enjoy a native app-like experience on your mobile device with offline access on localhost and a seamless user interface.

  • ✒️🔢 Full Markdown and LaTeX Support: Comprehensive Markdown and LaTeX capabilities for enriched interaction.

  • 🎤📹 Hands-Free Voice/Video Call: Seamless communication with integrated hands-free voice and video call features using multiple Speech-to-Text providers (Local Whisper, OpenAI, Deepgram, Azure) and Text-to-Speech engines (Azure, ElevenLabs, OpenAI, Transformers, WebAPI).

  • 🛠️ Model Builder: Easily create and customize models via the Web UI. Add custom characters/agents, customize chat elements, and import models effortlessly.

  • 🐍 Native Python Function Calling Tool: Enhance your LLMs with built-in code editor support. Add your own pure Python functions for seamless LLM integration.

  • 📚 Local RAG Integration: Groundbreaking Retrieval Augmented Generation (RAG) support using your choice of 9 vector databases and multiple content extraction engines (Tika, Docling, Document Intelligence, Mistral OCR). Load documents directly into chat using the # command before a query.

  • 🔍 Web Search for RAG: Perform web searches using 15+ providers including SearXNG, Google PSE, Brave Search, Tavily, Perplexity, DuckDuckGo, Bing, and more, injecting results directly into your chat experience.

  • 🌐 Web Browsing Capability: Integrate websites into your chat using the # command followed by a URL.

  • 🎨 Image Generation Integration: Generate images using multiple engines including OpenAI's DALL-E, Gemini, ComfyUI (local), and AUTOMATIC1111 (local).

  • ⚙️ Multi-Model Conversations: Engage with various models simultaneously, harnessing their unique strengths for optimal responses.

  • 🔐 Role-Based Access Control (RBAC): Secure access with restricted permissions — only authorized individuals can access your models, with exclusive creation/pulling rights reserved for administrators.

  • 🗄️ Flexible Database & Storage Options: Choose from SQLite, PostgreSQL, or configure cloud storage backends (S3, Google Cloud Storage, Azure Blob Storage).

  • 🌐 Multilingual Support: Experience Aether in your preferred language with full internationalization (i18n) support.

How to Install 🚀

Installation via Python pip 🐍

Ensure you're using Python 3.11 to avoid compatibility issues.

  1. Install Aether:

    pip install open-webui

  2. Run Aether:

    open-webui serve

Access Aether at http://localhost:8080.

Quick Start with Docker 🐳

Note: Include -v open-webui:/app/backend/data in your Docker command to ensure your database is properly mounted and data is not lost.

If Ollama is on your computer:

docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name aether --restart always ghcr.io/open-webui/open-webui:main

If Ollama is on a different server:

docker run -d -p 3000:8080 -e OLLAMA_BASE_URL=https://example.com -v open-webui:/app/backend/data --name aether --restart always ghcr.io/open-webui/open-webui:main

With Nvidia GPU support:

docker run -d -p 3000:8080 --gpus all --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name aether --restart always ghcr.io/open-webui/open-webui:cuda

OpenAI API only:

docker run -d -p 3000:8080 -e OPENAI_API_KEY=your_secret_key -v open-webui:/app/backend/data --name aether --restart always ghcr.io/open-webui/open-webui:main

Access Aether at http://localhost:3000.

Troubleshooting

If you experience connection issues inside Docker, use the --network=host flag:

docker run -d --network=host -v open-webui:/app/backend/data -e OLLAMA_BASE_URL=http://127.0.0.1:11434 --name aether --restart always ghcr.io/open-webui/open-webui:main

Note: with --network=host the port changes from 3000 to 8080.

License 📜

This project is based on code originally licensed under the BSD 3-Clause License. All new contributions are licensed under the MIT License. See LICENSE for details.

Support 💬

If you have any questions, suggestions, or need assistance, please open an issue on GitHub. 🤝