getting-started.md

Getting Started

This guide will help you set up and run the Learning Path Index (LPI) project on your local machine.

Prerequisites

Before you begin, ensure you have the following installed:

• Python (tested with version 3.x): Download and install Python from the official website.
• Git: Download and install Git from the official website.
• Docker (optional): While not strictly necessary, Docker simplifies running certain components. Install Docker following the instructions for your operating system.

Installation

The LPI project consists of several independent applications (applets) that work together:

• Web scraper
• LLM Variant 01 (Ollama)
• LLM Variant 02 (OpenAI)

Note: This guide focuses on setting up the general repository. Each applet may have additional instructions.

Step 1: Clone the Repository

Clone the repository to your local machine using the following command:

git clone https://github.com/neomatrix369/learning-path-index.git learning-path-index

cd learning-path-index

Step 2: Install Dependencies

Python dependencies for each applet are located in the ./requirements/ directory, with each applet having a separate file. Here's how to install them using a virtual environment:

Create a virtual environment:

python -m venv venv

Activate the virtual environment

MacOS/Linux

. venv/bin/activate

Windows

venv\Scripts\activate

Install base dependencies

pip install -r requirements/base.txt

Install dependencies for specific applets

Each applet may have additional dependencies. Look for a requirements.txt file within the directory for the specific applet (e.g., requirements/scraper.txt) and install them using:

pip install -r requirements/<applet_name>.txt

Replace <applet_name> with the actual name of the applet (e.g., scraper).

Step 3: Setup pre-commit hooks

Pre-commit hooks automate tasks like code formatting and linting. Install them using:

pre-commit install

Step 4: Setup the Applets

Each applet has its own setup and usage instructions. Refer to the documentation specific to each applet for detailed guidance on:

• Web scraper: Installation instructions and usage guide.

• LLM Variant 01 (Ollama): Instructions on setting up and using Ollama.

• LLM Variant 02 (OpenAI): Instructions on creating an OpenAI account and API keys.

Tip: Look for additional documentation files within the directory for each applet.

Troubleshooting

Here are some common issues or errors that you might face:

• Dependency Conflicts: Ensure that your dependencies are up to date and consistent with the versions specified in the requirements directory.
• OpenAI Rate limit error: The free tier of OpenAI has limitations on API calls. Consider upgrading to a paid account if you frequently encounter this error.

For further assistance, refer to the project's documentation (if available) or reach out to the project maintainers on the GitHub repository.