Template-based NLG framework for creating text narratives out of data
Project description
pynarrator
Template-based NLG framework for creating text narratives out of data
Installation
You can install the package from pip:
pip3 install pynarrator
import os
from pynarrator import narrate_descriptive, read_data
Basic Usage
pynarrator has a range of functions for creating template-based narratives and also embedded data set that you can use by calling read_data()
. Function downloads raw data from github, if you get a SSL error when running it, please run this first:
import ssl
ssl._create_default_https_context = ssl._create_unverified_context
sales = read_data()
narrative = narrate_descriptive(sales, measure = 'Sales', dimensions = ['Region', 'Product'], coverage = 0.5)
{'Total Sales': 'Total Sales across all Regions is 38790478.42.', 'Region by Sales': 'Outlying Regions by Sales are NA (18079736.4, 47.0%), EMEA (13555412.7, 35.0%).', 'Product by Sales': 'Outlying Products by Sales are Food & Beverage (15543469.7, 40.0%), Electronics (8608962.8, 22.0%).'}
Chat GPT
In order to use ChatGPT in pynarrator, you must specify your OpenAI API token as OPENAI_API_KEY
environment variable:
os.environ['OPENAI_API_KEY'] = 'xx-xxxxxxxxxx'
from pynarrator import gpt_get_completions, enhance_narrative, translate_narrative, summarize_narrative
Improve the narrative text to make it rich with business language
enhance_narrative(narrative)
enhance_narrative(narrative, language = 'Spanish')
summarize_narrative(narrative)
Complete documentation is available at the narrator package website
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