bertopicRoute BERTopic topic modeling, embedding, vectorizer, labeling, visualization, and serialization workflows.
Independent GitHub snapshot · Automated classification · Original documentation governs
BERTopic turns documents, precomputed embeddings, or multimodal inputs into topic models you can fit, inspect, label, visualize, and save.
python -m pip install bertopic
Use only the optional packages that the chosen workflow needs. For example, multimodal image workflows use bertopic[vision], while label and backend workflows may require openai, litellm, langchain, llama-cpp-python, spacy, fastembed, model2vec, gensim, flair, safetensors, or datamapplot.
If you are working from a local checkout to inspect the package, editable install is also fine:
python -m pip install -e .
Run the bundled environment check first:
python scripts/check_env.py
Add --smoke for a tiny no-download fit/load-style smoke that uses synthetic documents and precomputed embeddings.
sub-skills/topic-modeling/ — build BERTopic models, fit and transform data, run partial_fit, mutate topics, and combine or reduce fitted models.sub-skills/embeddings-backends/ — choose embedding backends, build custom embedders, inventory optional backend imports, and handle precomputed or multimodal embeddings.sub-skills/vectorizers-ctfidf/ — tune ClassTfidfTransformer, CountVectorizer, and OnlineCountVectorizer for better topic words.sub-skills/representations-labeling/ — rerank keywords, generate labels, chain representation models, and manage multi-aspect topic outputs.sub-skills/analysis-visualization/ — inspect fitted models with topic tables, hierarchies, distributions, and plots.sub-skills/serialization/ — save, reload, and share fitted models locally or through the Hugging Face Hub.When a task spans more than one route, start with the earliest route in the pipeline and move forward: embeddings → model building → topic-word tuning → labels → analysis → serialization.
references/workflows.md for the fastest route through common BERTopic tasks.references/troubleshooting.md when imports, optional dependencies, plotting, or save/load fail.references/repo-provenance.md before deciding whether this skill matches the current checkout.