Instructions here: https://github.com/ghobs91/Self-GPT
If you’ve ever wanted a ChatGPT-style assistant but fully self-hosted and open source, Self-GPT is a handy script that bundles Open WebUI (chat interface front end) with Ollama (LLM backend).
- Privacy & Control: Unlike ChatGPT, everything runs locally, so your data stays with you—great for those concerned about data privacy.
- Cost: Once set up, self-hosting avoids monthly subscription fees. You’ll need decent hardware (ideally a GPU), but there’s a range of model sizes to fit different setups.
- Flexibility: Open WebUI and Ollama support multiple models and let you switch between them easily, so you’re not locked into one provider.
whats great is that with ollama and webui, you can as easily run it all on one computer locally using the open-webui pip package or in a remote server using the container version of open-webui.
Ive run both and the webui is really well done. It offers a number of advanced options, like the system prompt but also memory features, documents for RAG and even a built in python ide for when you want to execute python functions. You can even enable web browsing for your model.
I’m personally very pleased with open-webui and ollama and they both work wonders together. Hoghly recommend it! And the latest llama3.1 (in 8 and 70B variants) and llama3.2 (in 1 and 3B variants) work very well, even on CPU only, for the latter! Give it a shot, it is so easy to set up :)
What are your PC specifications for running Ollama3.1:70B smoothly?
I wish I could. I have an RTX 3060 12GB, I run mostly llama3.1 8B versions in fp8, at 30-35 tokens/s.
I can confirm that it does not run (at least not smoothly) with an Nvidia 4080 12Gb. However, gemma2:27B runs pretty well. Do you think if we add another graphical card, a modest one, maybe the llama3.1:70B could run?
No, but you can run Qwen 2.5 34B with 24GB total.
Host it in TabbyAPI instead of ollama too. Use its native tensor parallelism and Q4 cache, it will fly.