add visual search custom image instructions

README.md

@@ -19,6 +19,8 @@ cp /path/to/my_amazing_wordlist.txt nouns.txt
 
 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.
 

src/rewards_tasks.py

@@ -15,6 +15,8 @@ import mouse_trajectory
 import mimic_typing
 import element_selectors
 
+VISUAL_SEARCH_IMAGE_PATH = os.path.abspath("keypress_times.png")
+
 class RewardsTaskUtils:
 	def __init__(self, driver: webdriver.Edge):
 		self.driver = driver
@@ -119,7 +121,7 @@ class RewardsTaskUtils:
 
 		file_input = self.wait_for_element(self.elements.get_visual_search_file_input)
 
-		file_input.send_keys(os.path.abspath("keypress_times.png"))
+		file_input.send_keys(VISUAL_SEARCH_IMAGE_PATH)
 
 		time.sleep(random.uniform(3, 5))