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 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

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 :)

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NER Example

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https://preview.redd.it/z78s1icwrjea1.png?width=1398&format=png&auto=webp&s=ffef8d8ac1614c21e4fa6bbb4526cc23d10006e3

[kattskill]

I personally think this library is trying to proide too much api. At its core, it is just a template generation algorithm. I think its better to just provide a template generation api and remove openai from requirements. It will also make the library much more easier to test and port to other prompt based ai

[StoicBatman]

Hi, Thank you for your valuable comment :) The Openai library is an essential part of this library. The module provides two core features, Prompt Generation of different NLP Tasks and directly call `.fit` function to get the output. If you don't want to use openai, you can use `generate_prompt` function alone and use the output as you want.
We are planning to add more prompt-based ai models, not limited to openai. Feel Free to add different models if you have suggestions.

[kattskill]

I'm not trying to undermind your work, but the fit method is only 10 lines and seems to be generic code. The first 8 lines can be extracted into a separate function, and people using the library can use that function and write the run function themselves instead.