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
Installation
With pip
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
Quick tour
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'}]
GPT-3 Example with NER, MultiLabel, Question Generation Task
🎮
Features - 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)
Supporting wide-range of Prompt-Based NLP tasks :
Task Name | Colab Notebook | Status |
---|---|---|
Named Entity Recognition | NER Examples with GPT-3 | |
Multi-Label Text Classification | Classification Examples with GPT-3 | |
Multi-Class Text Classification | Classification Examples with GPT-3 | |
Binary Text Classification | Classification Examples with GPT-3 | |
Question-Answering | QA Task Examples with GPT-3 | |
Question-Answer Generation | QA Task Examples with GPT-3 | |
Relation-Extraction | Relation-Extraction Examples with GPT-3 | |
Summarization | Summarization Task Examples with GPT-3 | |
Explanation | Explanation Task Examples with GPT-3 | |
SQL Writer | SQL Writer Example with GPT-3 | |
Tabular Data | ||
Image Data | ||
More Prompts |
Docs
Community
💁 Contributing
We welcome any contributions to our open source project, including new features, improvements to infrastructure, and more comprehensive documentation. Please see the contributing guidelines