LLM Chat Labeling Editor
Overview of the text labeling editor in Ango Hub
Last updated
Overview of the text labeling editor in Ango Hub
Last updated
While you may integrate your OpenRouter account with this feature and chat with LLMs present in it, chatting with custom LLMs (outside of OpenRouter) is a feature reserved to paid iMerit customers. Please contact us for more.
Ango Hub provides a labeling editor with which users can have live conversations with LLMs, and with which existing LLM conversations can be annotated.
The LLM Chat Labeling Editor is opened when a user opens a LLM Chat-type asset. For more information on how to create and/or import such assets, please .
This article will exclusively go over Ango Hub’s LLM Chat labeling interface. Features common to all labeling editors (audio, image, PDF, and text) are instead .
Pre-existing conversations are conversations which already happened outside of the Ango Hub platform and you import them to be annotated.
Live conversations start empty, and the annotator has a live conversation with your LLM directly from Ango Hub.
Once the LLM Chat-type assets have been created, if they are empty (of the "live" type), when the user enters the asset, they will be greeted with an empty message UI:
To prompt the LLM, enter your text in the text area labeled Enter prompt here... and hit Enter or the Send button. The LLM will receive your prompt and answer.
You may use Markdown and, between dollar signs, LaTeX in your prompts. To preview the final, formatted version of your prompt, click on the "Markdown" icon to the left of the prompt text area:
If the model's outputs also contain Markdown or LaTeX, they will automatically be formatted. To view a message's output in plain text (unformatted), click on the Switch to Raw Text button below the message:
Click on Save or Submit when you are done.
As outlined in , there are two possible types of LLM Chat assets: "pre-existing" and "live" conversations.
Regardless of whether the chat is a pre-existing one or a live one, from the Tools section on the left-hand side of the screen, select a -type tool. Then, click on the chat message you would like to classify. The classifications that have been nested under the Message-type tool will appear, and you will be able to answer them.
