import numpy as np
import topicwizard
from sklearn.datasets import fetch_20newsgroups
from sklearn.feature_extraction.text import CountVectorizer
from turftopic import KeyNMF

print("Fetching data")
newsgroups = fetch_20newsgroups(
    subset="all",
    remove=("headers", "footers", "quotes"),
)
texts = newsgroups.data
labels = list(np.array(newsgroups.target_names)[newsgroups.target])

model = KeyNMF(
    20,
    vectorizer=CountVectorizer(
        stop_words="english",
        max_features=8000,
        ngram_range=(1, 2),
    ),
)
topic_data = model.prepare_topic_data(texts)

topicwizard.easy_deploy(topic_data, dest_dir=".")