
LIT Prompts sɣur Colarusso
Create, save, and run interconnecting template-based prompts for Large Language Models (LLMs) using direct input along with content from your active browser window.
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A project of Suffolk University Law School's Legal Innovation & Technology (LIT) Lab, this extension was designed to help students explore the use of Large Language Models (LLMs) and prompt engineering. Users can create and save prompt templates for use by the extension with any OpenAI-compatible API.
Templates can use data from ones active browser window (e.g., selected text or the whole text of a webpage) as well as text input provided by the user. They can also feed into each other, allowing one to create complex interactions. For example: (1) summarize and ask questions of a webpage (e.g., What are the main conclusions of this article? What did so and so say about this or that?); or (2) translate selected text from one language into another. Then draft a reply in the original language.
Templates can use data from ones active browser window (e.g., selected text or the whole text of a webpage) as well as text input provided by the user. They can also feed into each other, allowing one to create complex interactions. For example: (1) summarize and ask questions of a webpage (e.g., What are the main conclusions of this article? What did so and so say about this or that?); or (2) translate selected text from one language into another. Then draft a reply in the original language.
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- Lqem
- 0.2.1
- Teɣzi
- 3,07 MB
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- hace 6 días (18 de ago. de 2025)
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Tizmilin n tuffɣa n 0.2.1
- Because the internal month variable {{month}} returned a zero-index month (0-11), the {{month1}} variable was added to return the current month indexed at 1 (1-12). Note: the {{month2d}} variable now returns a padded version of the {{month1}} variable (e.g.,
01
) instead of the {{month}} variable. - The default OpenAI models were changed to avoid models that no longer work (e.g.
gpt-3.5-turbo
was replaced bygpt-4o-mini
).
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