name: topic-modeler description: Extract topics from text collections using LDA (Latent Dirichlet Allocation) with keyword extraction and topic visualization.

Topic Modeler

Extract topics from text collections using LDA.

Features

• LDA Topic Modeling: Latent Dirichlet Allocation
• Topic Keywords: Extract representative keywords per topic
• Document Classification: Assign documents to topics
• Visualization: Topic word clouds and distributions
• Coherence Scores: Evaluate topic quality

CLI Usage

python topic_modeler.py --input documents.csv --column text --topics 5 --output topics.json

Dependencies

• gensim>=4.3.0
• nltk>=3.8.0
• pandas>=2.0.0
• matplotlib>=3.7.0
• wordcloud>=1.9.0