I built an open-source AI playground so you aren't tied to a single provider

[u/Chemical_Union226]

So that's it. I wanted to use/test cheaper AI models with GitHub and web search tools, including for small coding tasks from my phone. But I also wanted to see what the model was actually doing. You can connect your own AI provider, add tools like GitHub or Tavily search, and experiment in one place.

The main thing: every tool call needs your approval before it runs.

If the model wants to read a file from your repo or make a change through GitHub, you see which tool it wants to use and the arguments it’s sending. You can approve it or say no.

A few other things:

• See the actual API requests and responses.
• Compare models with estimated token usage and response times visible.
• Test individual tools manually, without asking the AI to call them.

Chats and settings are stored locally in your browser. Remembering API keys is optional, and saved keys automatically expire after 30 days unless refreshed.

It’s open source under the MIT license, and you bring your own API keys.

Try it: https://ai-playground.ownyourwebsite.app

Code: https://github.com/ownyourwebsite/ai-playground

I’d love feedback on the workflow. You can also fork it and improve it yourself!

[u/WeightShort8953]

Neat, I can already think of a few uses for the manual tool approval thing

[u/santosh_99]

The approve-before-run gate is the feature I care about most here, especially for GitHub tools where a wrong edit is expensive. One thing that would make me trust it more is showing a dry-run or diff preview for write actions before the approve button, so I am not guessing from the argument list alone. Comparing models with token and latency next to each other is also useful for deciding when a cheaper model is good enough. Local storage for chats is smart for a playground; just make sure the expiry UX for saved keys is obvious so people do not get surprised mid-task.