Skip to main content

AI-powered Jupyter Notebook

Vizly Notebook is a Jupyter alternative that integrates an AI copilot into your Jupyter Notebook editing experience.

Best of all, Vizly Notebook runs locally and can be used for free with Ollama or your own API key. To start:

pip install vizly-notebook

To start vizly-notebook, run the following

vizly-notebook

or

jupyter vizly-notebook

or

jupyter thread

Key features

1. Familiar Jupyter Notebook editing experience

SameEditorExperience

2. Natural language code edits

CellEditing

3. Generate cells to answer natural language questions

ThreadGenerateMode

4. Ask questions in a context aware chat sidebar

ThreadChatDemo480

5. Automatically explain or fix errors

image

Demo

https://github.com/squaredtechnologies/vizly-notebook/assets/18422723/b0ef0d7d-bae5-48ad-b293-217b940385fb

ThreadIntro

Feature Roadmap

These are some of the features we are hoping to launch in the next few month. If you have any suggestions or would like to see a feature added, please don't hesitate to open an issue or reach out to us via email or discord.

  • Add co-pilot style inline code suggestions
  • Data warehouse + SQL support
  • No code data exploration
  • UI based chart creation
  • Ability to collaborate on notebooks
  • Publish notebooks as shareable webapps
  • Add support for Jupyter Widgets
  • Add file preview for all file types

Cloud

Eventually we hope to integrate Vizly Notebook into a cloud platform that can support collaboration features as well hosting of notebooks as web application. If this sounds interesting to you, we are looking for enterprise design partners to partner with and customize the solution for. If you're interested, please reach out to us via email or join our waitlist.

Development instructions

To run the repo in development mode, you need to run two terminal commands. One will run Jupyter Server, the other will run the NextJS front end.

To begin, run:

yarn install

Then in one terminal, run:

sh ./run_dev.sh

And in another, run:

yarn dev

Navigate to localhost:3000/vizly-notebook and you should see your local version of Vizly Notebook running.

If you would like to develop with the AI features, navigate to the proxy folder and run:

yarn install

Then:

yarn dev --port 5001

Using Vizly Notebook with Ollama

You can use Ollama for a fully offline AI experience. To begin, install and run vizly-notebook using the commands above.

Once you have run vizly-notebook, in the bottom left, select the Settings icon:

image

Next, select the Model Settings setting:

image

This is what you will see:

image

Navigate to Ollama and enter your model details:

image

Use Ctrl / Cmd + K and try running a query to see how it looks!

Metadata

Release files for vizly-notebook 0.1.28

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for vizly-notebook 0.1.28
File Size Uploaded
vizly_notebook-0.1.28.tar.gz 15.0 MB Details

Built distribution (wheel)

Table of built distributions (wheels) for vizly-notebook 0.1.28
File Interpreter ABI Platform
vizly_notebook-0.1.28-py3-none-any.whl Python 3 none any Details

Total release size: 30.1 MB

Release files / vizly_notebook-0.1.28.tar.gz

Download URL vizly_notebook-0.1.28.tar.gz
Size 15.0 MB
Tags Source
SHA-256 checksum
How to use checksums
17b9ca7381e83ffdf4d150d8254e4342b06b2bc9c7bb6c2c69570815d53777e7
BLAKE2b-256 checksum
How to use checksums
d9237616d26b7e4844aa808dbd8851be2fad64015e7a2510fe7b87f68899069d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.0 CPython/3.11.9

Release files / vizly_notebook-0.1.28-py3-none-any.whl

Download URL vizly_notebook-0.1.28-py3-none-any.whl
Size 15.2 MB
Tags Python 3
SHA-256 checksum
How to use checksums
81bbb49945dfc5073f9601ec91ed0295dfe7cd3be559b4fcb88bc7af95353da4
BLAKE2b-256 checksum
How to use checksums
8aef6c3a724291ece2aabacaae528bdd61758165c9593dea8adea7696b79b63b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.0 CPython/3.11.9

Release history Release notifications | RSS feed

This release

0.1.28 This release

2 release files

0.1.27

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page