Visualize your dataset with the Bespoke Curator Viewer

IMPORTANT: We recently are retiring our local curator-viewer , now switching to a hosted Bespoke Curator Viewer.

The hosted Bespoke Curator Viewer is a rich interface to visualize data, and makes visually inspecting the data much easier.

Example:

Before your Curator run, set the CURATOR_VIEWER environment variable.

Bash:

export CURATOR_VIEWER=1

Python/colab:

import os
os.environ["CURATOR_VIEWER"]="1"

With this enabled, as curator generates data, it gets uploaded and you can see the responses streaming in the viewer. The URL for the viewer is displayed right next to the rich progress.

Then, run on any Bespoke Curator scripts, here we use examples/poem-generation/poem.py as an example, and

Example Bespoke Curator Rich CLI logs on synthetic poems

The line

Curator Viewer: ✨ Open Curator Viewer ✨ 

contains a clickable link (the following is an example viewer link, the link changes for each new Curator generation run) which opens the hosted Bespoke Curator Viewer in a new browser tab:

• https://curator.bespokelabs.ai/datasets/845c7dd33b8b4242a24ff048b5f94354

Example Bespoke Curator Viewer on synthetic poem topics link

Authenticate with a Bespoke Labs API key

By default, datasets are accessible to anyone with the link. To keep your datasets private, you can associate them with a Bespoke Labs account. Doing so also allows you to:

• Track all datasets associated with your account

• Share datasets with collaborators

• Analyze data generation costs over time

You can enable authentication as follows:

1. Sign up for a Bespoke Labs account.
2. Create an API key from the API Key page.

1. Set the BESPOKE_API_KEY and CURATOR_VIEWER environment variables:

export BESPOKE_API_KEY=<YOUR_API_KEY>
export CURATOR_VIEWER=1

With these variables set, all your datasets will be streamed to the hosted viewer and linked to your Bespoke Labs account.

1. You can visit the Datasets page to see all the datasets generated with your API keys or shared with you by others.

1. You can also visit the Cost Report page to see the data generation costs for a given period.