WocaFuckOff

Project Overview

• Purpose: Automated helper for Wocabee language practice using a browser CDP connection.
• Main script: startup.py ! The script doesn't have a gui, if you want I made a docker image for this project !
• Main Solver script solver.py
• Primary language focus: Slovak (designed for Slovak → English), but the approach is language-agnostic in principle.

Quick Notes

• AI-assisted: This project was created with AI help and may contain bugs or imperfect heuristics. Don't be scared of making an issue and reposting any bugs or imperfections!
• Playwright-powered: Uses Playwright with an installed Chromium build inside the container.
• Notification support: Optional integration with ntfy for runtime and startup error notifications.

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Requirements

• WocaBee: Please make sure that you have a valid WocaBee account and the package already completed before you farm it, the script is supposed to do the tedious grind currently
• Python: 3.9+ recommended
• Libraries: See requirements.txt (if present). At minimum the script uses playwright, requests, toml.
• Playwright: Please use the playwright install-deps and playwright install command to fully install all additional dependencies

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Usage

• There are 2 ways to use the script, you can either use the script or the docker

Docker

• Follow the instructions on the WocaFuckOff-docker repository page

Local

• Before you start the script you need to download the dependencies using these commands

# Installing requirements and dependencies
python -m pip install -r requirements.txt
python -m playwright install-deps
python -m playwright install

• You need to use a chromium based browser, doing the before mentioned playwright install-deps should download one that works ! NOTE: Please don't use your own chromium based browser, It has not beed tested properly !
• The startup script will automatically open the chromium browser with the correct arguments
• Running the bot:
• While using the startup.py script, you need to insert username and password into the config.toml file

# You rely on config.toml for all variables
python startup.py

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Configuration

• Create and edit a config.toml file (You can use the config.example.toml file as a base). All variables are:

Variable	Default	Description	Optionable
urlbase	https://wocabee.app/app	Target Wocabee URL	✅ ! Dont change unless you know what you are doing !
debug_port	https://localhost:9222	CDP endpoint	✅ ! Dont change unless you know what you are doing !
wordlist_file	wordlist.json	JSON file storing word mappings	✅ ! Dont change unless you know what you are doing !
picture_file	picturelist.json	JSON file storing image mappings	✅ ! Dont change unless you know what you are doing !
placeholder_words	translate,check	Words to ignore	✅ ! Dont change unless you know what you are doing !
username	(empty)	Login username	❎
password	(empty)	Login password	❎
double_points	false	Enable double points mode	✅
addon_points	5000	Target addon points	✅
milestone_reminder	1000	Reminder interval	✅
headless	false	Enable headless browser mode	✅
class_index	0	Class selection index	✅
package_index	0	Package selection index	✅
ntfy_server	(empty)	ntfy server URL	✅
ntfy_topic	(empty)	ntfy topic	✅
ntfy_token	(empty)	ntfy auth token	✅

Example config snippet (see the example config.toml for the full file):

urlbase = "https://wocabee.app/app"
debug_port = "http://localhost:9222"
wordlist_file = "wordlist.json"
picture_file = "picturelist.json"
placeholder_words = ["", "translate", "check"]
class_index = 0
package_index = 0
addon_points = 1000
milestone_reminder = 100
headless = true
double_points = false
username = "coolUsername"
password = "coolPassword"
ntfy_server = "https://example.ntfy.server"
ntfy_topic = "wocabee-bot"
ntfy_token = "secret_token_here"

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How it works (short)

• The startup.py script opens a chromium browser with specific arguments and automatically navigates to a specific class and package you want to farm
• The solver.py script automatically starts and attaches to the browser via CDP, finds the website, and automates UI actions with Playwright.
• Mappings for words and pictures are stored in JSON files (wordlist.json, picturelist.json). Unknown items may prompt for manual input once and get saved. ! NOTE: If you get specific new words, please map them and send them into an issue under the tags additional word mapping or additional picture mapping

Limitations & Caveats

• The project was generated/assisted by AI — expect brittle behavior and imperfect code, if any issue arises please report it in the issues.
• It assumes specific DOM IDs and classes on the target site; UI changes will break handlers.
• Designed and tested against Slovak-English examples; other languages may require adjusting the translation fallback settings and the source language in the translator calls.
• Use responsibly: automated interaction with websites may violate terms of service. I am not responsible for any bans that might come with breaking ToS of the WocaBee app.

Troubleshooting

• If handlers fail to click elements, the site DOM may have changed; open solver.py and inspect the locator logic.
• Network/translation failures fallback to manual prompts — check wordlist.json and picturelist.json for saved entries.

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License & Attribution

• This project uses the MIT license