AI-powered Jupyter notebook platform
An open-source notebook environment where AI is a first-class citizen. It understands your full context, generates and runs code, manages cells, and works across multiple LLM providers — all in isolated, containerized workspaces.
Choose from Gemini, OpenAI, Anthropic, or run fully local with Ollama. Switch providers per cell or conversation. No vendor lock-in on your AI backend.
Live Python kernel with streaming output. Write code, run it, see results instantly. AI can execute and test code in an isolated sandbox before affecting your kernel.
AI reads, writes, inserts, and executes notebook cells on your behalf. It understands the full context of your notebook — code, output, and markdown.
Every project runs in its own Docker container. Full isolation for security and reproducibility. Automatic dependency installation when packages are missing.
The AI sees your entire notebook state — all cells above, your code, outputs, and notes. It gives targeted help, not generic answers.
Full .ipynb notebook format support. Import existing Jupyter notebooks, export your work. Dark, Light, and Monokai themes. File operations within isolated workspaces.
AI-Notebook follows a microservices architecture with isolated execution environments. Each project gets its own Docker container with a dedicated Python kernel and LLM integration.
# AI-Notebook in action
In [1]: import pandas as pd
df = pd.read_csv("sales.csv")
df.describe()
AI: I see your dataset has 3 outliers
in the revenue column. Let me clean
that and create a visualization...
In [2]: # AI-generated cellWhether you're a data scientist, researcher, or developer — AI-Notebook puts an intelligent copilot right inside your workflow.
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