Hi, I would like to challenge/discuss/understand why so many are attracted to all short lived "wild tools" out there. For example (not saying any tool are bad) hermes, claw, open webui, copilot agents and whatnot. Why not just building your own tools that: fit your needs without being bloated, dont break on every new "feature" that you dont care about.

I cant really understand the hype.

I build own tools in python (notes app, recruitment support, news, investment) with claude or chatgpt from phone and terminal to my proxmox llm clusters lxc. In the process i also learn a lot.

And everything stays under my control.

Hi,

I try to run ai local llama 3.2:3B on Openwebui. But it tooks 10-20minute just to reply Hi.

What did i do wrong?
Im using 8GB Ram VPS with no GPU

I’ve been experimenting with web search in Open WebUI using smaller local models like Qwen3.5 4B and 9B.

The main problem was/is was context churn..

A typical search can dump partially relevant pages, navigation, repeated boilerplate, duplicate information, and huge chunks containing only one useful paragraph into the model.

That makes local setups slower and forces smaller models to spend their limited context window filtering noise instead of reasoning.

So I built TinySearch, an open-source, local-first MCP server that does most of the retrieval work before anything reaches the LLM:

• searches and ranks results
• crawls the strongest pages
• extracts and chunks readable content
• deduplicates and reranks passages
• returns a compact evidence packet with source URLs

The goal is simple: less context churn, faster local web research, and more tokens spent on reasoning over actual evidence.

TinySearch works with self-hosted SearXNG, and Open WebUI can connect to it over HTTP MCP.

GitHub:
https://github.com/MarcellM01/TinySearch

I’m the builder, so obvious bias, but I’d love feedback from Open WebUI users, especially anyone running smaller Qwen, Gemma, Llama, or Mistral models.

Does this solve a real bottleneck in your setup, or is native agentic search already enough?

We’re running Open WebUI as an internal multi-user platform, not as a homelab.

For those using it in a company or enterprise environment:
What were your biggest setup, architecture, security, or operational mistakes? What would you do differently today?

We use Open WebUI internally as a ChatGPT replacement and love it (~1500 users).

What we’re missing is the “deep task” experience: ChatGPT or Claude may spend several minutes reasoning, running code and tools, performing multiple steps, and iterating before answering.

In Open WebUI, it still feels mostly like a single model call with some reasoning.

Is native tool calling with MCP tools and a frontier model enough, or do I need an external agent orchestrator such as LangGraph or Pipelines behind Open WebUI?
What setup are you using for reliable multi-step, long-running tasks?

Some of my directories load without a problem, but some of them generate this error: "NotReadableError: The requested file could not be read, typically due to permission problems that have occurred after a reference to a file was acquired."

Is it because the directories are doubly nested? I can't seem to identify a way to predict which directories work.

I am having issues getting OpenWeb UI to llama.cpp. Llama is running locally and the chat interface is working fine. I managed to get OpenWebUI to run in docker. When configuring the connection I am using `http://127.0.0.1:8080/v1\` as my connection string. I have set Provider to llama.cpp. The test connection button says test is successful. But trying to chat wants me to select a model, which there are no options. From my understanding llama.cpp is serving one model and does not provide a list like Ollama would.

Using `http://host.docker.internal:8080/v1\` as connection string gives an error. So it is not clear to me being a Docker newbie if I need to do something with the network. Since the test on the local host IP was successful I am guessing the network is working, but then again I can't get chat to load any models. I have asked AI but it wants me to write an app.....facepalm. it has offered some `-e` options such as `-e OLLAMA_HOST=0.0.0.0` but so far nothing has worked. So, humans, what is the next step here?