Notebook LLM

Notebook LLM is designed to bridge the gap between code notebooks (like Jupyter) and modern LLM capabilities. Instead of sending data to the cloud, users can install models locally using frameworks like Ollama or LM Studio and interact with them through a notebook interface that supports:

• Markdown + code blocks + LLM cells
• Multimodal input (text, code, files)
• Prompt chaining and structured memory
• Integration with local vector databases
• Full offline operation and user control

It is lightweight, user-friendly, and ideal for privacy-sensitive environments like research labs, data-secure institutions, or edge computing projects.