Open Web UI
User-friendly AI interface. Supports Ollama and OpenAI API.
Open the official app on openwebui.com
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Use it free
Open the official tool or demo — no account needed.
Self-host it
Run the open-source version on your own infrastructure.
What is Open Web UI?
Open WebUI is an open-source web tool designed to provide users with full control over AI model deployment and data management. As a self-hosted platform, it enables individuals and organizations to run AI applications on their own infrastructure, whether local or cloud-based, without relying on third-party services. The project's primary purpose is to offer a flexible interface for connecting to various AI models, extending functionality through code, and maintaining data sovereignty. It caters to developers, enterprises, and privacy-conscious users who seek to avoid vendor lock-in and ensure compliance with data regulations. By allowing models to be hosted privately, the tool addresses the challenge of balancing AI utility with security and control, particularly in regulated industries or environments where data residency is critical.
How it works
Open WebUI is a self-hosted AI platform built on the BSD-3-Clause license, offering a web interface to manage and deploy AI models. It emphasizes sovereignty by allowing users to host models, data, and applications on their own servers or private networks. The tool's purpose is to provide a unified interface for interacting with diverse AI models, such as Ollama, OpenAI, and Anthropic, while enabling customization through Python scripting. It prioritizes security and compliance, supporting features like role-based access control (RBAC) and data residency for regulated environments. Open WebUI connects to local or cloud-based AI models, supports Python extensions for custom logic, and integrates with tools like Ollama and OpenAI APIs. It includes features such as single sign-on (SSO), audit logging, and air-gapped deployment options for secure, on-premises use.
How to use it
- 1Clone the Open WebUI repository from GitHub. 2. Install dependencies, including Python and web server components. 3. Configure model connections via API keys or local endpoints. 4. Deploy using Docker, cloud platforms, or manual setup. Practical tips include using Docker for simplicity and ensuring compatible model versions are installed.
What it can do
- AI Tools
Use cases
Assumptions and limitations
Assumptions
- source: https://github.com/open-webui
- license: BSD-3-Clause — free to use
- privacy: Opens an external demo
Limitations
- Thin documentation may require advanced technical knowledge for setup.
- Limited out-of-the-box support for non-Python model integrations.
- Security configuration demands expertise in RBAC and network isolation.
- Scalability requires manual optimization for high-traffic deployments.
- Community-driven support may lack enterprise-grade SLA guarantees.
Understanding the result
User-friendly AI interface. Supports Ollama and OpenAI API.
Tool details
- Clearly flagged when a network request is needed.
- No account, no sign-up, and no tracking of your content.
- Powered by open-webui (BSD-3-Clause).
- Built with
- open-webui (https://github.com/open-webui)
- License
- BSD-3-Clause
- Runs locally
- No — requires a network request
- Verification
- Not yet verified
- Input
- Text
- Output
- Output
Built with https://github.com/open-webui. OpenToolVault provides the discovery and browser interface while crediting the original project maintainers.
- Built with
- open-webui
- License
- BSD-3-Clause
Open-source project
OpenToolVault is an independent directory. We are not affiliated with or endorsed by this project.
References
- /open-webui — GitHub Repository
Upstream project · GitHub
- BSD-3-Clause License
Upstream project
Frequently asked
What is Open WebUI and how does it differ from other AI tools?
Open WebUI is a self-hosted AI platform that prioritizes data sovereignty by allowing users to run models on their own infrastructure. Unlike hosted solutions like Streamlit or Gradio, it requires local or cloud deployment and offers features like RBAC and data residency. It differs from alternatives like LangChain by focusing on a unified interface for model management rather than workflow orchestration.
How does Open WebUI handle model compatibility and integration?
The tool connects to AI models via standard APIs, supporting frameworks like Ollama, OpenAI, and Anthropic. Users configure model endpoints and authentication keys in the settings. Python extensions enable custom logic for preprocessing, postprocessing, or model selection, though non-Python models may require additional adapters or API wrappers.
How do I deploy Open WebUI on a private server?
Clone the repository, install dependencies using pip, configure model connections in the config.yaml file, and deploy via Docker or a web server. For example, run 'docker-compose up' to start the service, then access the interface via the server's IP address. Ensure firewall rules allow traffic on the specified port and that models are accessible via their API endpoints.
How does Open WebUI compare to alternatives like Streamlit or Gradio?
Open WebUI is designed for full control over AI infrastructure, requiring self-hosting, while Streamlit and Gradio are hosted platforms with simpler setup. Open WebUI supports advanced security features like SSO and air-gapped deployments, whereas Streamlit focuses on rapid prototyping. Gradio excels in lightweight model demos but lacks Open WebUI's enterprise-grade compliance tools.
What should I do if my model fails to load?
Check the model's API endpoint URL and authentication credentials in the config file. Ensure the model is compatible with Open WebUI's supported APIs. Verify network connectivity to the model's server and review logs for error messages. If using a local model, confirm it's running and accessible via the specified port.