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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.py` that will download an image from Wikipedia named `random_image.png` 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`.
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.