Human Trafficking Training Assessment Tool

How to Create Dataset

Create a JSON in the same format as EK1.json or EK2.json with the same keys. Name the json file your initials and the training number to help us avoid conflicting file names.

• Put the content of the training in "content"
• Put the feature codes present in the Traning and its associated point value in "features"
• Put the total amount of points the Training earned in "total_points"

Take advantage of ChatGPT. Here's how I created EK2.json: For example, ask ChatGPT (or any other LLM):

Create an anti-human trafficking Training with this rubric below with all the features listed except for TAILORED_CONTENT and LEGAL_REGULATIONS: <insert rubric found in main.py>

Then, paste the answer chatgpt gave into content , adjust the features to what is actually present, and adjust the total points.

Try to make a variety of different trainings with various point totals. For example, make trainings with around 1000 words, 2000 words and ones with around 3000-5000 words.

Setup Instructions

1. Clone the Repository

Use the following command to clone the repository to your local machine:

git clone <repository_url>

Replace <repository_url> with the actual URL of the repository.

2. Navigate to the Project Directory

Change to the project's directory: cd <project_name>

Replace <project_name> with the name of the repository.

3. Create a Virtual Environment

Create a virtual environment named env: python -m venv env

4. Activate the Virtual Environment

On Windows: env\Scripts\activate

5. Install Dependencies

With the virtual environment activated, install the required dependencies: pip install -r requirements.txt

6. Google API Key

Replace empty string in main with your own API Key. MAKE SURE TO NOT INCLUDE YOUR KEYS WHEN YOU PUSH TO GITHUB!!!