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WordHunt

WordHunt is a Contexto-style semantic word guessing game built with Streamlit.

Setup

pip install -r requirements.txt
python build_index.py
streamlit run app.py

Notes

  • Initial embedding/index generation is time-consuming because it creates embeddings for 50,000 words.
  • Vocabulary generation uses the most frequent English words (daily-life friendly) and stores 50,000 lowercase alphabetic terms.
  • After data/embeddings.npy and data/faiss.index are built, gameplay is fast and runs offline.
  • The app computes embeddings only for user guesses during runtime.
  • The data/ artifacts are tracked so Streamlit deployments can run app.py without rebuilding the index.

About

WordHunt: A semantic word-guessing game powered by sentence embeddings and FAISS vector search. Guess daily words by exploring embedding space—get ranked feedback (1-50k) via L2-normalized inner-product similarity on 50,000 common English words.

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