{"id":21203703,"url":"https://github.com/bl33h/wordleai","last_synced_at":"2025-03-14T22:44:23.452Z","repository":{"id":234840812,"uuid":"789600524","full_name":"bl33h/wordleAi","owner":"bl33h","description":"A project to simulate the Wordle game with models like Constraints and Minimax to solve it.","archived":false,"fork":false,"pushed_at":"2024-05-21T01:23:37.000Z","size":393,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-21T15:15:21.394Z","etag":null,"topics":["ai","artificial-intelligence","constraints","minimax","minimax-algorithm","wordle","wordle-ai","wordle-game"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bl33h.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-04-21T02:35:39.000Z","updated_at":"2024-05-21T01:10:33.000Z","dependencies_parsed_at":"2024-04-21T03:43:16.887Z","dependency_job_id":"7f3acd15-f60e-4a63-92c6-3c9cc7062f68","html_url":"https://github.com/bl33h/wordleAi","commit_stats":null,"previous_names":["bl33h/wordleai"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bl33h%2FwordleAi","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bl33h%2FwordleAi/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bl33h%2FwordleAi/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bl33h%2FwordleAi/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bl33h","download_url":"https://codeload.github.com/bl33h/wordleAi/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243658177,"owners_count":20326464,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","artificial-intelligence","constraints","minimax","minimax-algorithm","wordle","wordle-ai","wordle-game"],"created_at":"2024-11-20T20:26:16.274Z","updated_at":"2025-03-14T22:44:23.133Z","avatar_url":"https://github.com/bl33h.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# wordleAi\nThis project is designed to simulate the Wordle game, where players guess a five-letter word within six tries. The project includes two solving models: Constraints and Minimax, to analyze their performance in solving the game.\n\n\u003cp align=\"center\"\u003e\n  \u003cbr\u003e\n  \u003cimg src=\"https://i.giphy.com/62HRHz7zZZYThhTwEI.webp\" alt=\"wb\" width=\"400\"\u003e\n  \u003cbr\u003e\n\u003c/p\u003e\n\u003cp align=\"center\" \u003e\n  \u003ca href=\"#features\"\u003eFeatures\u003c/a\u003e •\n  \u003ca href=\"#Files\"\u003eFiles\u003c/a\u003e •\n  \u003ca href=\"#how-to-use\"\u003eHow To Use\u003c/a\u003e •\n  \u003ca href=\"#packages\"\u003ePackages\u003c/a\u003e  • \n  \u003ca href=\"#packages\"\u003eReferences\u003c/a\u003e  \n\u003c/p\u003e\n\n## Features\n- **Wordle Game Simulation**: Play the Wordle game with a maximum of 6 guesses.\n- **Constraints Model**: Uses constraint satisfaction techniques to solve the game.\n- **Minimax Model**: Implements the Minimax algorithm for optimal solution finding.\n- **Performance Analysis**: Visualize and compare the success rate, total time, and accuracy of different models.\n- **Graphical Representations**: Generate graphs to compare model performances.\n\n## Files\n- main.py: The main entry point of the project. It initializes the Wordle game and allows the user to play or run simulations with different solving models.\n- wordle.py: Contains the core logic for the Wordle game, including initializing the game, processing guesses, and determining win/loss conditions.\n- answers.txt: Contains the list of possible answers for the Wordle game.\n- guesses.txt: Contains the list of possible guesses for the Wordle game.\n- agent.py: Defines the agent that interacts with the Wordle game, making guesses and receiving feedback.\n- state.py: Manages the state of the Wordle game, including the current guesses, remaining attempts, and whether the game has been won or lost.\n- file_functions.py: Contains functions for reading and writing to files, primarily used for loading word lists and saving game results.\n- feedback.py: Handles the feedback mechanism, providing hints based on the player's guesses and the actual word.\n- minimax.py: Implements the Minimax algorithm, a decision-making algorithm used for finding the optimal solution in the Wordle game.\n- constraints.py: Implements the Constraints model, which uses constraint satisfaction techniques to solve the Wordle game by narrowing down possible words based on given feedback.\n- performance.py: Contains functions to measure the performance of the solving models. It compares success rates, total solving time, and accuracy.\n- graphs.py: Generates various graphs to visualize the performance of different solving models. This includes histograms for total time distribution and bar charts for success rates and accuracy.\n\n## Packages\nThe project requires the following Python packages:\n- pandas: For data manipulation and analysis.\n- matplotlib: For creating static, animated, and interactive visualizations.\n- seaborn: For making statistical graphics.\n- numpy: For supporting large, multi-dimensional arrays and matrices.\n- scipy: For scientific and technical computing.\n  \nYou can install these packages using the following command:\n```\n$ pip install pandas matplotlib seaborn numpy scipy\n```\n\n## How To Use\nTo clone and run this application, you'll need [Git](https://git-scm.com) and [Python](https://www.python.org/downloads/) installed on your computer. From your command line:\n\n```\n# Clone this repository\n$ git clone https://github.com/bl33h/wordleAi\n\n# Open the project\n$ cd src\n\n# Run the app\n$ python main.py\n```\n\n## References\nThe information located in src/data was retrieved from the [roget repository](https://github.com/jonhoo/roget/tree/main)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbl33h%2Fwordleai","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbl33h%2Fwordleai","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbl33h%2Fwordleai/lists"}