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  1. Assisted Labeling
  2. ML Assisted Labeling

OpenAI (beta)

Last updated 8 months ago

Now, we allow you to integrate OpenAI as an assisted labeling tool for your projects. With this integration, you can easily select OpenAI from the provider dropdown menu.

Sample Data

We also provide a sample for you to try on your own project. You can simply upload the document as your input data and the question set as your question to be answered.

After successfully creating the project, you need to activate the ML-assisted labeling extension and select OpenAI as the provider. Once you have chosen OpenAI, you can access several fields under the OpenAI extension. These fields include:

  1. Target text: define your text column that is going to be treated as input

  2. Target question: your selected question to be answered

  3. API token: the OpenAI secret key

  4. System prompt: introduction prompt to define the OpenAI agent role

  5. User prompt: user definition of a task to be completed in a specific labeling workflow.

In addition, you can specify your desired output through instructions and examples.

Once all fields have been filled, you can predict the label by clicking “Predict label”.

The labels will then be automatically applied to the corresponding line.

If you are experiencing the 429 error, the limitation came from the OpenAI package. Please take a look at your current usage of OpenAI API.

You can refer to for guidance.

these examples of prompt templates
804B
Datasaur sample - Open AI.csv
sample dataset
600B
Datasaur sample - Open AI (question set).json
sample question set
Sample project with OpenAI integration
Result with Open AI ML Assisted