Setting Up the Project

00:00 For this project, you’ll need the following libraries installed: SentenceTransformers, ChromaDB, more-itertools, Polars, and the Google genai software development kit.

00:11 If you’re working in the same directory as the first half of this course, you already have SentenceTransformers and ChromaDB installed.

00:18 If not, you can review the past lessons for installation steps.

00:22 You’ll use Polars for some data prep. Polars is a fast, efficient DataFrame library. Install it with the command python -m pip install polars.

00:33 more-itertools expands on Python’s built-in itertools library and will be used for loading data into ChromaDB. Install it with python -m pip install more-itertools.

00:45 You’ll also need to be set up with Google Gemini, since we’ll be using the Gemini API for LLM calls. To access the Gemini API, you’ll need to create a Google account, generate a free API key, and the directions can be found at this link: https://ai.google.dev/gemini-api/docs/api-key, and then install the Google genai software development kit for Python with the command python -m pip install google-genai.

01:17 After you’ve completed these steps, minimally, your project should look like this. In your main project folder, you have your virtual environment, where you installed your dependencies.

01:27 And you may still have a chroma_data/ folder, and if you do, that’s fine, don’t worry about it. One more thing you need to add is a config.json. That’s where you’ll store your new Gemini API key as a JSON.

01:39 It should look like this. Make sure that both gemini-secret-key and your API key are strings. And that’s all you need for dependencies and setup for now.

01:50 Next lesson, we’re back to coding.