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Table Labeler

Perform labeling, data extraction and text transformation, for Excel or CSV spreadsheet columns.

The Table Labeler plugin allows you to easily apply GPT3 to tabular data by row. It can perform labeling, data extraction, and text transformation for Excel or CSV spreadsheet columns. With this plugin, you can streamline your data processing tasks and obtain valuable insights from your data. Whether you need to classify data, extract specific information, or transform text, the Table Labeler plugin has got you covered. Plus, with its user-friendly interface, you'll find it easy and intuitive to use. Say goodbye to manual data processing and let this plugin handle the heavy lifting for you!

Learn how to use Table Labeler effectively! Here are a few example prompts, tips, and the documentation of available commands.

Example prompts

  1. Prompt 1: "Apply GPT3 to tabular data by row."

  2. Prompt 2: "Can you help me apply a GPT transformation to the next rows of my table?"

  3. Prompt 3: "I want to apply a GPT prompt to each row of my table individually."

  4. Prompt 4: "How can I use GPT to transform multiple rows of my table?"

  5. Prompt 5: "I need assistance with applying GPT to the remaining rows in my table."

Features and commands

apply_llm_to_next_rowsThis command applies a GPT transformation to the next rows of a table. It starts at a specified row index and applies the instruction to each row individually.
link_sheetThis command links a Google Sheet to a conversation. It allows you to connect your table data to GPT3 for further transformations.
list_filesThis command displays the files that are currently uploaded. It is used to manage and view the files available for GPT3 transformations.
preview_apply_llm_to_rowsThis command allows you to preview the results of applying a GPT prompt to a column(s) of a table for a new or existing column. It shows how the instruction will be applied to each row individually.
save_fileThis command saves a dataframe for downloading or further use using Python. It asks the user for the desired columns and saves the modified column at the beginning of the dataframe by default.
show_dataframeThis command shows the current dataframe in the browser. It allows you to view the table data and any modifications made using GPT3 transformations.
upload_sheetThis command provides instructions for uploading a sheet. It guides you on how to upload your table data to Julius.ai for processing and GPT3 transformations.
use_file_for_labelingThis command loads a file into memory for labeling. It allows you to use an uploaded file for applying GPT3 transformations to the table data. Make sure to check if the file is uploaded and the naming matches before using it.


User authenticationOAuth2
API documentation

For AI

DescriptionApply GPT3 to tabular data by row.


First added11 October 2023

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