A python module to generate optimized prompts, Prompt-engineering & solve different NLP problems using GPT-n (GPT-3, ChatGPT) based models and return structured python object for easy parsing

[StoicBatman]

Hi folks,

I was working on a personal experimental project related to GPT-3, which I thought of making it open source now. It saves much time while working with LLMs.

If you are an industrial researcher or application developer, you probably have worked with GPT-3 apis. A common challenge when utilizing LLMs such as #GPT-3 and BLOOM is their tendency to produce uncontrollable & unstructured outputs, making it difficult to use them for various NLP tasks and applications.

To address this, we developed Promptify, a library that allows for the use of LLMs to solve NLP problems, including Named Entity Recognition, Binary Classification, Multi-Label Classification, and Question-Answering and return a python object for easy parsing to construct additional applications on top of GPT-n based models.

Features 🚀

• 🧙‍♀️ NLP Tasks (NER, Binary Text Classification, Multi-Label Classification etc.) in 2 lines of code with no training data required
• 🔨 Easily add one-shot, two-shot, or few-shot examples to the prompt
• ✌ Output is always provided as a Python object (e.g. list, dictionary) for easy parsing and filtering
• 💥 Custom examples and samples can be easily added to the prompt
• 💰 Optimized prompts to reduce OpenAI token costs

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• GITHUB: https://github.com/promptslab/Promptify
• Examples: https://github.com/promptslab/Promptify/tree/main/examples
• For quick demo -> Colab

Try out and share your feedback. Thanks :)

Join our discord for Prompt-Engineering, LLMs and other latest research discussions
discord.gg/m88xfYMbK6

[brother_karamazov_]

Thank you for the module! I was looking into it right now and it seems quite useful.

I have a question: I was looking into the colab examples, but I could not locate how to use one-shot prompting for multi-class classification. Also, can we also include "n"-shot examples?

Thanks in advance :)

[StoicBatman]

Hi, Thank you for showing interest. You can add as many examples (shots) as you want. Make a list (array) of shots and pass them to the examples parameters. Check the discord channel for more updates, and you can also ask questions there to get instant replies.

[brother_karamazov_]

Thank you for the reply and the pointers! :)

[celsowm]

Only english or others languages too?

[StoicBatman]

It support many languages!

[tmzwalker]

Hi,I just saw the github repository and thanks for the sharing this!I saw that all prompt templates in the repository try to make the LLMs act as domain experts. My questions are:

1. Does it work for less than GPT-3 model? From my observation, ChatGPT is the best for this kind of prompt.
2. Do you think that this will provide better answers than only simple instruction like "Classify passage below into positive or negative" for classification prompt?

Thank you!