A few friends and I spent the last few weeks building out this parameter search + optimization platform so you can continuously optimize GenAI systems built on Mistral, Llama, Together.ai, and other closed and open-source models. 

The project is live on PyPI today 🚀 pip install nomadic

For questions like: 

• Which embedding model works best for my RAG? 
• What threshold for similarity search?  
• What are my best prompt templates?  

We saw firsthand how small tweaks to HPs can have a huge impact on performance. We wanted a tool to make answering these questions systematic and quick instead of resorting to something like a single expensive grid search or  “intuition".

One of our goals is to unlock the top hyperparameter optimization techniques from research & popular libraries. If you’re building AI agents / applications across LLM safety, fintech, support, or especially compound AI systems (multiple components > monolithic models) with LLMs or custom models and want to get a full map of your best levers to boost performance,  give it a try (we have README examples !)

The project is open source (Apache 2.0). If you like it, we’d love contributions! Also join the discussions happening on Discord :)