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Weave

Weave is a visual development environment designed for building AI-powered software. It is also an open-source, interactive analytics toolkit for performant data exploration.

Use Weave to:

  • Spend less time waiting for datasets to load and more time exploring data, deriving insights, and building powerful data analytics
  • Interactively explore your data. Work with your data visually and dynamically to discover patterns that static graphs can not reveal, without using complicated APIs.
  • Monitor AI applications and models in production with real-time metrics, customizable visualizations, and interactive analysis.
  • Generate Boards to address common use cases when monitoring production models and working with LLMs

For more information about Weave, see the Weave Github Repo.

How it worksโ€‹

Use Weave to view your dataframe in your notebook with only a few lines of code:

  1. First, install or update to the latest version of Weave with pip:
pip install weave --upgrade
  1. Load your dataframe into your notebook.
  2. View your dataframe with weave.show.
weave.ipynb
import weave
from sklearn.datasets import load_iris

# We load in the iris dataset for demonstrative purposes
iris = load_iris(as_frame=True)
df = iris.data.assign(target=iris.target_names[iris.target])

weave.show(df)

An interactive weave dashboard will appear, similar to the animation shown below:

The following animations show how you can interactively plot charts and publish your dashboard to share with your colleagues:

Plot a chartโ€‹

  1. Hover your mouse next to a panel and click Add a new panel.
  2. Copy the Weave Expression for the dataset you want to plot. This Weave Expression is the path/location of the dataset object in the Weave compute graph.
  3. Click on Table to change this Weave Panel type.
  4. From the dropdown, select Plot.

Share a dashboardโ€‹

Select the Publish button in the top right of your view to share your Weave Board:

How to get startedโ€‹

If this is your first time using Weave, we suggest that you explore the following topics:

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