Add topic-modeling pipelines (v1-v3) and evaluator#3
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… ranked by BERTopic, refresh enhanced evaluator and README
…ansformers 2.6, scikit-learn 1.4, other updates)
- Add README.md and requirements.txt for all folders - Add anonymizer.py for privacy compliance - Rename gemma_summarization_task/ to monolithic_summarizers_DEPRE/ - Remove obsolete cleaning/nomoi/ files - Update pipeline orchestrator path resolution
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Introduction of
topic_modeling/module – three pipelines plus an evaluator – without touching any other part of the repo.Pipelines
src/consultation_topic_modeling_v1.py– baseline BERTopic workflow.src/consultation_topic_modeling_v2.py– improved version (automatic stop-words, SBERT/GTE embeddings, UMAP + HDBSCAN, JSON titling).src/consultation_topic_modeling_v3.py– hybrid key-phrase approach inspired by QualIT (Gemma key-phrase extraction, hallucination filter, titles).Evaluator
src/evaluate_topics.py– asks an LLM (Gemini API or local Gemma) to grade how well each auto-generated topic title fits its representative comments.--dump_promptsto write prompts to disk without burning API tokens.**Documentation
House-keeping
.gitignoreto keep secrets & artefacts out of the repo (*.env,/topic_modeling/.env,__pycache__/)..envwith the Gemini API key is not committed.Tested
Ran all three pipelines locally on consultation 320 and generated outputs under
outputs/v1|v2|v3/320/.Evaluator tested with both
--gemini(free-tier Flash) and--localGemma.Security / secrets
No credentials or personal data included.
API key remains in
topic_modeling/.env, which is ignored by Git.Impact on existing code
Only
.gitignoremodified; all other existing directories remain unchanged.