mardausdennis dd92cface3 read the search row before waiting on the panel's close button
read_search_points waited for the close button before reading anything, so a panel that rendered its content but not its button failed the whole search task while the number was already on screen. Traced to that wait with a stacktrace. Closing is best effort now.
2026-08-28 23:46:41 +02:00
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2026-08-22 09:26:17 -04:00
2026-08-24 13:57:38 -04:00
2026-08-27 08:59:56 -04:00
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User0332/rewards-farmer

Automation for MS Rewards based on https://youtu.be/4qdPcMNaioA.

Running Instructions

IMPORTANT: Use at your own risk. Microsoft may take action against your account for using automated scripts to gain rewards points. The YouTube video contains more details about the techniques implemented to avoid detection of this script.

Clone the repository.

git clone https://github.com/User0332/rewards-farmer

A sample nouns.txt file is included in the project root and can be modified by the user to contain seed words for the LLM to complete 20 searches. The wordlist should be separated by newline.

cd rewards-farmer
# Edit the included nouns.txt file to add or replace words as needed

You should also have an Ollama account created (for the LLM), the ollama tool installed, and you should have signed in to the Ollama CLI via the command line using ollama signin. This project will use a minimal amount of Ollama cloud usage using gemma4:cloud. If you wish to use a different model, please change the model parameter in the get_ollama_response function in src/llm_utils.py.

You must also provide an image for the script to upload to complete the visual search task. A helper script is included at src/random_image_for_visual_search.py that will download an image from Wikipedia named visual_search.jpg into the project root for you. You may also provide an image of your own, just ensure that the absolute path of the image is placed in the VISUAL_SEARCH_IMAGE_PATH constant at the top of rewards_tasks.py.

Activate the virtual environment & install dependencies (you may have to use python -m poetry instead of poetry). You must have Python 3.12+ and Poetry installed.

If iex (poetry env activate) fails with "Cannot bind argument to parameter 'Command' because it is null", poetry install did not create an environment. Run python --version first: an older Python leaves poetry with nothing to activate, and the message explaining that goes to stderr rather than into iex.

Windows (PowerShell)

poetry install
iex (poetry env activate)

*nix (Bash)

poetry install
eval $(poetry env activate)

You must also have a webdriver for Microsoft Edge installed. If you already have the Edge Browser installed, you probably have this component as well.

The profile directory in src/constants.py is set to Default. If this signs you in to a global profile that you do not want to use for automation, then you can create a new profile from within the webdriver instance manually and then change the PROFILE_NAME constant to Profile 1 (or the equivalent number).

Run main.py (python src/main.py, it must be run from the root directory so the relative paths work out), wait for the page to launch, and then CTRL-C to quit the application immediately. Sign in to the created profile with your Microsoft account on both Bing and rewards.bing.com.

EU Users: you may have to accept a consent banner once on rewards.bing.com and on the Bing search page, bing.com. Once you consent, your choice will be saved for future runs using the same profile, so you will not need to interact with the banner during automated runs.

Close all webdriver browser instances. Run main.py again; the automation should start working.

Please open up a GitHub issue if you run into any difficulties.

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