# AI use cases for Open WebUI (open-webui/open-webui) Repo: [open-webui/open-webui](https://github.com/open-webui/open-webui) | Use cases: 3 | Page: https://dedupedai.com/use-cases/open-webui-open-webui/ Open WebUI is a self-hosted AI platform with a chat interface for Ollama and OpenAI-compatible APIs that can run entirely offline. It adds local RAG over your documents with hybrid search, web search from many providers, custom models and agents with tools and knowledge, voice and video calls, role-based access control for teams, and SQLite or PostgreSQL storage. It installs with pip, Docker or Kubernetes. This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL. - Run a private ChatGPT-style app for your local models: https://dedupedai.com/use-cases/open-webui-open-webui/run-a-private-chatgpt-style-ui-for-local-models/ - Chat with your own documents using local RAG: https://dedupedai.com/use-cases/open-webui-open-webui/chat-with-your-documents-using-local-rag/ - Share one AI workspace with your team, with roles and groups: https://dedupedai.com/use-cases/open-webui-open-webui/share-one-ai-workspace-with-your-team/ ## How to run a private ChatGPT-style app for your local models with Open WebUI Repo: [open-webui/open-webui](https://github.com/open-webui/open-webui) | Difficulty: Beginner | Time: 10 minutes | Basis: From the README Start Open WebUI with Docker or pip and chat with Ollama models in the browser. **Who it is for:** Someone running Ollama who wants a proper chat app instead of the terminal. **The problem:** Local models are hard to use day to day without a good interface. **The outcome:** A browser chat app at localhost:3000 talking to your local models, offline if you want. ### Steps 1. With Docker: `docker run -d -p 3000:8080 --add-host=host.docker.internal:host-gateway -v open-webui:/app/backend/data --name open-webui --restart always ghcr.io/open-webui/open-webui:main` 2. Or with Python: `pip install open-webui`, then `open-webui serve` 3. Open http://localhost:3000 and create the admin account 4. Pick an Ollama model, or add an OpenAI-compatible API in settings ### Prompt to paste into your agent ```text Install open-webui/open-webui with Docker on this machine, connect it to my local Ollama, and confirm I can chat with . Tell me where chats are stored and how to back them up. ``` ### Caveat Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/open-webui-open-webui/run-a-private-chatgpt-style-ui-for-local-models/ ## How to chat with your own documents using local RAG with Open WebUI Repo: [open-webui/open-webui](https://github.com/open-webui/open-webui) | Difficulty: Beginner | Time: 20 minutes | Basis: From the README Load documents into a chat or your library and ask questions answered from them. **Who it is for:** A researcher or small team that wants answers grounded in their own files without a cloud service. **The problem:** Cloud document chat tools require uploading private files. **The outcome:** Answers drawn from your documents with hybrid search and reranking, on your server. ### Steps 1. Upload documents to the library or a chat 2. Pull them into a conversation with the # command 3. Ask questions; retrieval uses hybrid BM25 and vector search with reranking 4. Add web search from a provider such as SearXNG if you want fresh results too ### Prompt to paste into your agent ```text In my open-webui/open-webui, create a knowledge collection from , then answer citing which document each point came from. ``` ### Caveat Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/open-webui-open-webui/chat-with-your-documents-using-local-rag/ ## How to share one AI workspace with your team, with roles and groups with Open WebUI Repo: [open-webui/open-webui](https://github.com/open-webui/open-webui) | Difficulty: Intermediate | Time: 1 hour | Basis: From the README Run Open WebUI on a server and give each person the models and tools their role needs. **Who it is for:** A small company that wants one internal AI chat with access control. **The problem:** Everyone using their own personal AI accounts means no control and duplicated cost. **The outcome:** One shared instance with user groups, per-group model access and custom agents. ### Steps 1. Deploy with Docker or Kubernetes on a team server 2. Use PostgreSQL instead of SQLite for a larger team 3. Create user groups and roles with granular RBAC 4. Build custom models and agents with instructions, tools and knowledge, and limit them per group ### Prompt to paste into your agent ```text Plan an open-webui/open-webui deployment for people on : storage choice, groups and roles for , and which models each group gets. Then give me the Docker command. ``` ### Caveat Risk, credentials: Admin access controls every user's chats and connected API keys; protect the admin account. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/open-webui-open-webui/share-one-ai-workspace-with-your-team/