from sentence-transformers import SentenceTransformer
from turftopic import KeyNMF

# Encode documents using a sentence-transformer
encoder = SentenceTransformer("paraphrase-mpnet-base-v2")
embeddings = encoder.encode(documents, show_progress_bar=True)

# Initialize KeyNMF with 4 topics and a seed phrase
model = KeyNMF(
 n_components=4,
 encoder=encoder,
 seed_phrase="Expansion of the Eurozone",
 seed_exponent=3.0,
)

# Fit model 
model.fit(corpus)

# Print modelled topics
model.print_topics()