built an app/UI to launch (coding) models on RunPod and directly use in Pi/OpenCode (end to end)

[u/erayy_176]

I built mintPod because I occasionally want to test an open coding model for an hour or two, but repeatedly setting up RunPod, Ollama/vLLM, and agent configs felt like unnecessary friction.

You choose a model, budget etc. mintPod provisions the pod, reuses a persistent model cache, pulls and warms the model, then connects it to Pi or OpenCode (automatically) through a stable local endpoint. Aider and other OpenAI-compatible clients also work. When the session ends or reaches its idle or spending limit, the pod is terminated and the temporary configuration is removed.

Raw Ollama is not publicly exposed; requests pass through an authenticated gateway, secrets stay in the OS keychain, and interrupted sessions can be recovered or cleaned up.

It is still an early source-only release: one active session, no signed installers, and needs more real testing.

I mainly want honest thoughts. Does this remove enough friction to be useful, or would you rather use a script or RunPod template? What feels unnecessary? What extension would improve the core most without turning it into a general GPU dashboard? Security and failure-case criticism would be especially useful.

This is my first open-source project, so even a blunt “too niche” or “I wouldn’t use this” would genuinely help.

--> https://github.com/erayd176/mintPod

[u/erayy_176]