I Built a tool to stop manually swapping models on my 8GB GPU,chains a small Prompter and a large Coder into one pipeline with automatic VRAM swap

Reddit r/LocalLLaMA Tools
open-source model-chaining vram-management gpu streamlit prompt-engineering coding-assistant

Summary

The author built Prompt-Chain, a Streamlit app that chains a small prompter model and a large coder model with automatic VRAM swapping, enabling efficient code generation on an 8GB GPU.

While trying out different LLMs I noticed that giving them precise, detailed prompts produced way better results than typing a one line sentence. To get those detailed prompts I'd use a smaller, faster model first - but with only 8GB VRAM I can't keep two models loaded at once, so switching between them was a constant pain for me . So I built Prompt-Chain to automate the whole thing. It's a Streamlit app that chains two models into a single pipeline: You type a rough idea (e.g. "make a snake game in React") A small, fast Prompter (e.g. Phi-4 Mini) rewrites it into a detailed prompt You review and optionally edit the refined prompt VRAM is automatically swapped — Prompter unloads, Coder loads A larger, code-focused model (e.g. Qwen 2.5 Coder 14B) generates the code Output streams to screen and saves to file The main benefit is you stop wasting time manually unloading/loading models and stop wasting tokens (or money if you use cloud APIs) on poorly-worded prompts hitting a big model. Other features: - Mix backends per role: LM Studio, Ollama, OpenAI, Claude, Gemini chosen independently for Prompter and Coder - Auto model detection from the server - 25 built-in presets (Web Dev, Games, Data, CLI,etc..) - Refine-in-place: follow-up instructions edit the code without regenerating from scratch - Run history that persists across restarts - Smart file output with auto language detection and timestamped saves GitHub: https://github.com/atharva557/Prompt-Chaining Would appreciate any feedback, especially from people running similar setups!
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