Show HN: I made a self-hosted ChatGPT UI

However, sophisticated readers familiar with ChatGPT will know the model and weights haven't been released and absent a leak/hack/release by OpenAI a completely self-hosted ChatGPT solution is impossible. Eventually we'll almost certainly see a "Completely self-hosted ChatGPT equivalent" (similar to Dall-E vs Stable Diffusion) but that's another thread for another time.

Based on my native speaker parsing of English "Self-hosted ChatGPT UI" is accurate and I'm not sure how else I would write it to disambiguate between a self-hosted UI and a completely self-hosted ChatGPT with a UI.

Integrating with Alpaca, Llama, ChatGLM, OpenChatBox and whatever comes next should be straightforward once people figure out reliable and fast methods to run the models locally.

Assuming the model was available, how big are the models and what kind of hardware is necessary to run the instance?

Edit i think the title name was changed. Dang can you please show revision history otherwise i cant dicuss properly

https://twitter.com/LeapJosh/status/1635735318665068549

https://old.reddit.com/r/OpenAI/comments/11k19en/i_made_an_a...

    function __summarize(api_key) {
        var selection = window.getSelection().toString();
        if (selection.length == 0) return;
    
        var xhr = new XMLHttpRequest();
        xhr.open("POST", "https://api.openai.com/v1/chat/completions");
        xhr.setRequestHeader('Content-Type', 'application/json');
        xhr.setRequestHeader('Authorization', 'Bearer ' + api_key);
        window.scrollTo({top: 0})
        document.body.innerHTML = 'asking...'
        document.body.style.backgroundColor = "white";
        document.body.style.color = "black";
        document.body.style.fontFamily = 'monospace'
        document.body.style.fontSize = "16px"
        document.body.style.margin = "auto"
        document.body.style.padding = "1rem"
        document.body.style.maxWidth = "60rem"
        xhr.onreadystatechange = function() {
            if (xhr.readyState == 4) {
                if (xhr.status == 200) {
                    var response = JSON.parse(xhr.responseText);
                    var summary = response.choices[0].message.content;
                    document.body.innerHTML = summary
                } else {
                    try {
                        var e = JSON.parse(xhr.responseText);
                        document.body.innerHTML = e.error.message
                    } catch(e) {
                        document.body.innerHTML = 'error asking.. check the console'
                        console.log(xhr)
                    }
                }
            }
        }
    
        var data = JSON.stringify({
            "model": "gpt-3.5-turbo",
            "messages": [
                {"role": "system", "content": "Summarize the following text as if you are Richard Feynman"},
                {"role": "user", "content": selection}
            ]
        });
        xhr.send(data);
    }

[0]: https://platform.openai.com/docs/guides/chat/introduction

That way it works in any app automatically. Seamless system wide clipboard read is a big ask though, so ideally you'd want a self hosted model like llama.cpp

I guess you could also try to tack on an extra layer before the actual API call, and make your own system that includes key bits of info to the prompt from a more specific data set. But I'd guess at this rate of new releases from OpenAI, it might be a safe bet to wait the couple of weeks until they update the fine-tune API.

https://dev.to/dhanushreddy29/fine-tune-gpt-3-on-custom-data...

True, and the free version does it lot, almost on purpose.

The paid version is a lot faster and doesn’t break as often, but it still breaks (eg. For the last two days, the chat list on the sidebar disappeared and it showed a message saying “don’t worry, your chats will show up eventually”).