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.
  • The Hobbyist@lemmy.zipEnglish
    3·
    10 days ago

    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 :)

      • The Hobbyist@lemmy.zipEnglish
        0·
        10 days ago

        I wish I could. I have an RTX 3060 12GB, I run mostly llama3.1 8B versions in fp8, at 30-35 tokens/s.

        • camilobotero@feddit.dkEnglish
          0·
          9 days ago

          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?

          • brucethemoose@lemmy.worldEnglish
            1·
            9 days ago

            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.

  • Nickm8@lemmy.worldEnglish
    2·
    8 days ago

    Have been using it a while now, I recommend using something like Tailscale so you can access it from anywhere on your phone. I also have a raspberry pi that can wake up my main machine when I need it.

  • Aeri@lemmy.worldEnglish
    2·
    10 days ago

    I just want one that won’t just be like “I"m sowwy miss I can’t talk about that 🥺”

  • rsolva@lemmy.worldEnglish
    1·
    10 days ago

    I have been running this for a year on my old HP EliteDesk 800 SFF (G2) with 64GB RAM, and it performes great on the smallest models (up til 8B) only on CPU. I run Ollama and OpenWebUI in containers/LXC in Proxmox. It’s not as smart as ChatGPT, but it can be suprisingly capable for everyday tasks!

  • Nexy@lemmy.sdf.orgEnglish
    0·
    9 days ago

    I didnt use any AI until I was able to host it localy. I hate the idea of training a model or how that data centers consumes so much water and resouses. Also I dont use any AI generative of images. Is not etic for me. But I’m trying to find a way to make ollama a tool I can use somehow, and not just a thing to talk sometimes for fun.

    • Gumus@lemmy.worldEnglish
      2·
      8 days ago

      You realize the models you’re running locally had to be trained the same way as the proprietary ones, right?

  • Player2@lemm.eeEnglish
    0·
    10 days ago

    Wish I could accelerate these models with an Intel Arc card, unfortunately Ollama seems to only support Nvidia

    • Possibly linux@lemmy.zipEnglish
      1·
      10 days ago

      And AMD

      You should be able to get llama.cpp to run on Arc but I’m not sure what performance you will get. It may not be worth it.