Asvo777/medumba-french-translator

# Medumba-French Dictionary (Streamlit) A Streamlit app to search, add, and manage Medumba ↔ French dictionary entries. Includes a lightweight multilingual embedding model for fuzzy token-level translation suggestions. ## Features - Search words or expressions in either language - Add new translations with duplicate checks - View full dictionaries for words and expressions - Embedding-based token translation demo using `paraphrase-multilingual-MiniLM-L12-v2` ## Project layout - `dictionary_manager.py` – Streamlit app - `output/` – data folder with CSVs - `translations_words.csv` - `translations_expressions.csv` - `requirements.txt` – Python dependencies ## Prerequisites - Python 3.12 (tested) - Git (to clone, optional) ## Setup (local) ```bash # 1) Clone or unzip this repo, then inside the project folder: python -m venv .venv # 2) Activate the venv (Windows PowerShell) .\.venv\Scripts\Activate.ps1 # or cmd.exe .\.venv\Scripts\activate.bat # 3) Install deps pip install --upgrade pip pip install -r requirements.txt ``` ## Run the app ```bash streamlit run dictionary_manager.py ``` Then open the printed local URL (default localhost). ## Data files The app expects the CSVs in `output/`. Edits in the UI overwrite these files. If you deploy to Streamlit Cloud, commit the `output/` CSVs so they are available at startup. ## First-run download note The SentenceTransformer model and PyTorch weights download on first run. Keep the terminal open and allow a minute. If you want a custom cache location, set `HF_HOME` to a folder with enough space before launching Streamlit. ## Deploy to Streamlit Cloud 1. Push this project to GitHub (include `output/` CSVs). 2. On share.streamlit.io, create a new app pointing to this repo. 3. Set the main file to `dictionary_manager.py` and Python version to 3.12. 4. Add `requirements.txt` as the dependency file; deployment will install them automatically. 5. Deploy. Subsequent edits to the repo will auto-trigger redeploys. ## …