What is pico-jarvis?

Pico Jarvis is a lightweight chatbot that can answer questions by reasoning through them step by step, looking up information from documents you give it, and even checking live weather data. Think of it as a tiny version of the AI assistants you see on bigger platforms, but running on your own machine with open-source components. The project demonstrates a technique called Retrieval-Augmented Generation, or RAG. In plain terms, that means the chatbot doesn't just rely on what it already knows, it can search through a document (like a PDF about the solar system) to find specific facts before answering. It also breaks down questions into smaller reasoning steps, which helps it give more accurate answers. To run it, you need a local AI model serving as the "brain," plus Node.js to run the web interface. You open a browser, type questions, and get answers back. The main audience is developers or tinkerers who want to understand how RAG works in practice, without signing up for a pricey API or wrestling with a complex setup. A founder exploring AI features for their product could use it as a reference implementation, a working example of how a chatbot can combine general knowledge, custom documents, and live external data (like weather) into one conversation. The included sample questions cover trivia, solar system facts from a PDF, and weather queries, so you can see all three modes in action quickly. What's notable is the emphasis on keeping things small. The project pairs with Phi 2, a compact language model that can run on modest hardware, rather than requiring a massive model or cloud service. There's a tradeoff: smaller models are faster and cheaper to run but may be less accurate, and the README notes that you can swap in a larger model if you want better precision at the cost of speed.