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metadata
title: Semantrix
emoji: 🔠
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: 5.1.0
app_file: app.py
pinned: false
license: other

Semantrix Game

This repository contains the implementation of the Semantrix game, a word guessing game using word embeddings. The game supports multiple languages (Spanish and English) and can be configured to use either a Word2Vec model or a SentenceTransformer model for word embeddings.

Modules

app.py

This module defines a Gradio-based web application for the Semantrix game. The application allows users to play the game in either Spanish or English, using different embedding models for word similarity.

Functions

  • convert_to_markdown_centered(text): Converts text to a centered markdown format for displaying game history and last attempt.

    • Parameters:
      • text (str): The text to be converted.
    • Returns: str: The centered markdown formatted text.

  • reset(difficulty, lang, model): Resets the game state based on the selected difficulty, language, and model.

    • Parameters:
      • difficulty: The selected difficulty level.
      • lang: The selected language.
      • model: The selected embedding model.
    • Returns: list: A list of initial output components for the UI.

  • change(state, inp): Changes the game state by incrementing the state variable.

    • Parameters:
      • state: The current game state.
      • inp: The user input.
    • Returns: list: A list containing the updated state and input component.

  • update(state, radio, inp, hint): Updates the game state and UI components based on the current state and user inputs.

    • Parameters:
      • state: The current game state.
      • radio: The radio input component.
      • inp: The user input.
      • hint: The hint state.
    • Returns: list: A list of updated output components for the UI.

game.py

This module defines the Semantrix class, which implements a word guessing game using word embeddings. The game can be configured to use either a Word2Vec model or a SentenceTransformer model for word embeddings. The game supports multiple languages and difficulty levels.

Classes

  • Semantrix: A class that implements the Semantrix word guessing game.
    • Methods:
      • __init__(self, lang=0, model_type="SentenceTransformer"): Initializes the Semantrix game with the specified language and model type.
      • prepare_game(self, difficulty): Prepares the game with the selected difficulty level.
      • gen_rank(self, repeated): Generates the ranking file based on the scores.
      • play_game(self, word): Plays the game with the selected word and returns feedback.
      • curiosity(self): Generates a curiosity hint about the secret word once the game is over.

hints.py

This module provides functions to generate dynamic hints and curiosities about a secret word using language models (LLMs).

Functions

  • hint(secret, n, model, last_hint, lang, Config): Generates a dynamic hint based on the secret word and the number of hints given.

    • Parameters:
      • secret (str): The secret word.
      • n (int): The number of hints already given.
      • model: The sentence transformer model used for encoding.
      • last_hint (int): The index of the last hint given.
      • lang (int): The language code (0 for Spanish, 1 for English).
      • Config: Configuration object containing hint templates.
    • Returns: tuple: A tuple containing the generated hint (str), the updated number of hints (int), and the index of the last hint given (int).

  • curiosity(secret, Config): Generates a curiosity about the secret word.

    • Parameters:
      • secret (str): The secret word.
      • Config: Configuration object containing the curiosity template.
    • Returns: str: The generated curiosity.

  • ireplace(old, new, text): Replaces all occurrences of a substring in a string, case-insensitively.

    • Parameters:
      • old (str): The substring to be replaced.
      • new (str): The substring to replace with.
      • text (str): The original string.
    • Returns: str: The modified string with all occurrences of the old substring replaced by the new substring.

How to Run

  1. Clone the repository.
  2. Install the required dependencies.
  3. Run the app.py script to launch the Gradio web application.

Dependencies

  • Gradio
  • OpenAI
  • SentenceTransformers
  • Gensim
  • NumPy

License

This project is licensed under the MIT License.