A some time ago I shipped a desktop app to generate LLM fine-tuning datasets. It worked: my Qwen2.5-Coder-7B fine-tune jumped from 55.5% → 72.3% on HumanEval . Whole pipeline ran on OpenRouter — pick a model, click Generate, get JSONL. v1.0.3-beta ships multi-provider LLM support — Ollama, LM Studio, llama.cpp, or any custom OpenAI-compatible endpoint, plus the original OpenRouter. Mix and match: generate on your local Qwen3-14B, judge on a cheap cloud model. Or stay fully offline. Here's what shipped, what was harder than I expected, and what I learned along the way. What's new in v1.0.3-beta One-click local LLM . Open Settings → Providers → "Auto-detect local". The app probes localhost:11434 (Ollama), 1234 (LM Studio), 8080 (llama.cpp). Anything that answers gets a one-click "Add" button. Onboarding for an offline-first user takes ~30 seconds. Mixed mode . Each category can use its own provider. Gen on local Qwen2.5-Coder:14B, judge on cloud example GPT-4-mini.…