Tools· AI Assistance & Agent Building

    Open WebUI

    Open WebUI is a self-hostable, offline-capable interface for local and remote language models, with Ollama integration, local RAG and enterprise features such as SSO and audit logs.

    conversationalexecutableOpen Source

    Description

    Strengths

    Universal provider connection
    Chat with Ollama, OpenAI, Anthropic or any OpenAI-compatible provider from a single interface, including file attachments, web search and code execution right inside the chat.
    Flexible installation
    Runs via Docker, Kubernetes, pip or bare metal, with dedicated images for Ollama and CUDA setups.
    Progressive Web App
    Installs without a separate download to a phone home screen, desktop taskbar or dock.
    Multi-user from day one
    Roles, user groups, per-model access control and integration with an existing identity provider, from a solo install to an organization with thousands of seats.
    Open REST API
    Over 200 environment variables and a full REST API authenticated via Bearer tokens or JWTs are available for custom automations.

    Assessment

    AI features

    • Knowledge base and RAG Upload files and build knowledge bases, choosing between vector search for large collections or full-content injection for precision, with native function calling letting models autonomously search and synthesize across the entire knowledge base.
    • Custom agents Agents such as a Python tutor, a meeting summarizer or a code reviewer are built as configuration wrappers from a base model with bound knowledge, tools and a system prompt.
    • Notes workspace A dedicated space for content outside individual conversations, with AI-assisted rewriting right in the editor and precise context injection into chats without chunking or vector search.
    • Computer connection A real computing environment where the AI writes code, executes it, reads the output, fixes errors and iterates, including file handling, package installation and running servers.
    • Tools and pipelines Custom Python tools run inside the chat, external services connect via OpenAPI or MCP, and pipelines filter, transform or route every message.

    Suitable for

    • Teams who want to run local language models via Ollama offline and without cloud dependency
    • Organizations with high data protection requirements that need an air-gapped or on-premises AI interface
    • Users who need local RAG features and custom model variants via the model builder alongside chat
    • Less suitable for Less suited to teams who want to get started immediately without hosting it themselves

    Limitations and notes

    • Operational effort The large feature set can mean more effort in setup and maintenance than with leaner alternatives, and operation rests entirely with your own team.
    • Configuration depth Over 200 environment variables control authentication, model routing, storage and logging, with a dedicated reference section to look them up.
    • No hosted cloud service Operation runs entirely on your own infrastructure, with costs arising from hosting and from any connected cloud models.
    • Reverse proxy and HTTPS on your own Production deployments require your own certificate handling, WebSocket support and a production-hardened reverse proxy configuration.

    Quick start

    1. Choose an installation path: Docker for the fastest start, Python via pip for a lightweight install, or Kubernetes for production.
    2. Connect a first model provider, such as Ollama or an OpenAI-compatible or Open Responses endpoint.
    3. Work through the Getting Started basics: plugins, what happens with long chats, the Task Model, RAG over your own documents, and Native Tool Calling.
    4. Add Open WebUI as a Progressive Web App to your home screen, taskbar or dock.
    5. For team use, set up roles, user groups and per-model access rights.

    Tips

    • Generate a personal access token for custom automations; each key inherits the permissions of the user who created it.
    • For errors in long chats, the documentation points to a filter that fixes the issue instead of restarting the chat.
    • Before going to production, review the reference sections on HTTPS configuration and reverse proxy setups.
    • Updates can be applied manually with a single Docker or pip command, or automated with Watchtower, WUD or Diun, including backup and restore procedures.
    • External AI agents with their own toolset for terminal, file operations or web search can connect to Open WebUI as a chat frontend, with the agent deciding on its own when to use a tool.

    Access

    Last reviewed: · Pricing, plans and features are a snapshot in time. Check the provider's own page before deciding.

    In the workshop this becomes your method.

    Whoever sees this process run once wants the agent behind it next. We build that in the workshop From Process to Agent.

    View workshops

    Related resources

    Browse all resources

    Conversation, not pitch

    Understand first, then decide. We take time for an initial conversation, without sales pressure, without obligation.

    Schedule a call