I built Sequence-LLM because I kept running into the same friction while working with local models. I was switching between different models for different tasks, one for reasoning, another for coding, sometimes another for general chat. Every switch meant stopping one server, starting another, changing ports, and breaking my workflow. It felt unnecessary and slow, especially when the whole point of local AI is control and speed. The core problem I wanted to solve was simple: treat multiple models like interchangeable tools instead of separate environments. I wanted a single interface where I could move between them instantly using commands, while the system handled process management, configuration, and health checks in the background. During development, the approach evolved quite a bit. Initially it was just a small script to start and stop llama.cpp servers. Then I realized this could become a proper developer tool with profiles, configuration files, and cross platform support. I also leaned heavily into rapid iteration with AI assisted engineering, where I focused on architecture, testing, and validation while letting AI help generate and refine implementation details. That process actually shaped the project as much as the technical goals did. The result is a lightweight CLI that orchestrates local LLM workflows without locking users into a specific backend. My goal is to keep improving it based on real usage and feedback from people who rely on local models daily.

Sequence-LLM

Manage multiple local LLMs with simple commands.

Manage multiple local LLMs with simple commands.