rewards-farmer/README.md

# User0332/rewards-farmer

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

```sh
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.

```sh
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. Currently, this image is named `keypress_times.png` and is located in the root directory of the project (yes, I used a random image from my keyboard analysis to do this). You may 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 3.14+ and Poetry installed.

Windows (PowerShell)
```sh
poetry install
iex (poetry env activate)
```

*nix (Bash)
```sh
poetry install
eval $(poetry env activate)
```

You must also have a [webdriver for Microsoft Edge](https://learn.microsoft.com/en-us/microsoft-edge/webdriver/?tabs=c-sharp) 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.

# Logging

The script logs to the console. Two optional environment variables change that:

| Variable | Default | Effect |
| --- | --- | --- |
| `REWARDS_FARMER_LOG_LEVEL` | `INFO` | Set to `DEBUG` to also attach the full stack trace to every `[FAIL]` line. |
| `REWARDS_FARMER_LOG_FILE` | unset | Path to also write the log to, useful for unattended runs. |

Windows (PowerShell)
```sh
$env:REWARDS_FARMER_LOG_LEVEL="DEBUG"; $env:REWARDS_FARMER_LOG_FILE="run.log"; python src/main.py
```

*nix (Bash)
```sh
REWARDS_FARMER_LOG_LEVEL=DEBUG REWARDS_FARMER_LOG_FILE=run.log python src/main.py
```

If you are opening an issue about a crash, running with `REWARDS_FARMER_LOG_LEVEL=DEBUG` and attaching the log is the most useful thing you can include.

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