upload 3 files

app.py

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+import pandas as pd
+import topicwizard
+from sklearn.decomposition import NMF
+from topicwizard.pipeline import make_topic_pipeline
+from sklearn.feature_extraction.text import CountVectorizer
+
+df = pd.read_csv('df_merged.csv')
+abstracts=df['description'].tolist()
+vectorizer = CountVectorizer(min_df=5, max_df=0.8, stop_words="english")
+model = NMF(n_components=10)
+topic_pipeline = make_topic_pipeline(vectorizer, model)
+topic_pipeline.fit(abstracts)
+topicwizard.visualize(abstracts, pipeline=topic_pipeline)
+
+app = topicwizard.get_dash_app(vectorizer, model, corpus=abstracts)
+
+# main.py
+if __name__ == "__main__":
+    app.run_server(debug=False, port=8050)

requirements.txt

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+pandas
+scikit-learn
+topic-wizard