Promptify

Prompt Engineering, Solve NLP Problems with LLM's & Easily generate different NLP Task prompts for popular generative models like GPT, PaLM, and more with Promptify

This repository is tested on Python 3.7+, openai 0.25+.

You should install Promptify using Pip command

pip3 install promptify

or

pip3 install git+https://github.com/promptslab/Promptify.git

To immediately use a LLM model for your NLP task, we provide the Pipeline API.

from promptify import Prompter,OpenAI, Pipeline sentence = """The patient is a 93-year-old female with a medical   history of chronic right hip pain, osteoporosis,  hypertension, depression, and chronic atrial  fibrillation admitted for evaluation and management  of severe nausea and vomiting and urinary tract  infection""" model = OpenAI(api_key) # or `HubModel()` for Huggingface-based inference or 'Azure' etc prompter = Prompter('ner.jinja') # select a template or provide custom template pipe = Pipeline(prompter , model) result = pipe.fit(sentence, domain="medical", labels=None) ### Output [ {"E": "93-year-old", "T": "Age"}, {"E": "chronic right hip pain", "T": "Medical Condition"}, {"E": "osteoporosis", "T": "Medical Condition"}, {"E": "hypertension", "T": "Medical Condition"}, {"E": "depression", "T": "Medical Condition"}, {"E": "chronic atrial fibrillation", "T": "Medical Condition"}, {"E": "severe nausea and vomiting", "T": "Symptom"}, {"E": "urinary tract infection", "T": "Medical Condition"}, {"Branch": "Internal Medicine", "Group": "Geriatrics"}, ] 

• Perform NLP tasks (such as NER and classification) in just 2 lines of code, with no training data required
• Easily add one shot, two shot, or few shot examples to the prompt
• Handling out-of-bounds prediction from LLMS (GPT, t5, etc.)
• Output always provided as a Python object (e.g. list, dictionary) for easy parsing and filtering. This is a major advantage over LLMs generated output, whose unstructured and raw output makes it difficult to use in business or other applications.
• Custom examples and samples can be easily added to the prompt
• 🤗 Run inference on any model stored on the Huggingface Hub (see notebook guide).
• Optimized prompts to reduce OpenAI token costs (coming soon)

Promptify Docs

 @misc{Promptify2022, title = {Promptify: Structured Output from LLMs}, author = {Pal, Ankit}, year = {2022}, howpublished = {\url{https://github.com/promptslab/Promptify}}, note = {Prompt-Engineering components for NLP tasks in Python} } 

We welcome any contributions to our open source project, including new features, improvements to infrastructure, and more comprehensive documentation. Please see the contributing guidelines