GenAI DLP Prompt Generator

GenAI DLP Prompt Generator is a Python tool designed to scrape DLP data and use it to generate GenAI prompt. It has three main modules:

It fetches DLP test sample data from specified URLs, saves the data in text format, and then converts these text files into PDFs.
It uses an OpenAI Assistant to generate DLP mock data
It uses OpenAI Chat Completions to generate prompts for each DLP category

The output is suitable for benchmarking DLP systems or Generative AI Language Learning Models (GenAI LLMs).

Features

Web scraping from specified URLs.
Data extraction and saving in text format.
Conversion of text data to PDF format, ideal for benchmarking DLP systems or GenAI LLMs.

Installing

To install DLP Data Scraper, clone the repository and install the required packages:

git clone https://github.com/BenderScript/DLPDataScraper.git
cd DLPDataScraper/dlp_data_scraper
pip3 install -r requirements.txt

Usage

Make sure you have a OpenAI API key and set it as an environment variable:

export OPENAI_API_KEY=<your key here>

The file with DLP categories currently under tests/dlp_categories.md. Need to be copies to a new location and the path passed to the OpenAIDLPAssistant or OpenAIChat classes.

To use the DLP Data Scraper:

The scraper access a URL with dynamic content, waits for it to load and extracts all DLP categories

from dlp_data_scraper.umbrella import Umbrella
from file_utils.FileUtils import FileUtils

pdf_data = "umbrella/pdf_data"
text_data = "umbrella/text_data"
file_utils = FileUtils()
url = (
    'https://support.umbrella.com/hc/en-us/articles/4402023980692-Data-Loss-Prevention-DLP-Test-Sample-Data-for'
    '-Built-In-Data-Identifiers')
scraper = Umbrella(url=url, text_data=text_data, pdf_data=pdf_data)
html_content = scraper.initialize_browser()
scraped_data = scraper.scrape_data()
scraper.save_data_to_files()
file_utils.convert_txt_to_pdf(text_data, pdf_data)
print("Scraping and conversion to PDF completed.")

After the run is over, the generated data under the umbrella/text_data and umbrella/pdf_data directory. There will be one file for each DLP category.

To use the OpenAI Chat DLP Prompt generator:

from prompt_gen.openai_chat import OpenAIChat


# Initialize the Assistant class
chat_gen = OpenAIChat(text_data="openai_chat_prompt/text_data",
                          pdf_data="openai_chat_prompt/pdf_data",
                          dlp_categories_file="dlp/dlp_categories.md")

chat_gen.run()

After the run is over there will 90+ LLM Prompts based on the DLP categories. The generated data will be under the openai_chat_prompt/text_data and openai_chat_prompt/pdf_data directories.

To use the OpenAI Assistant DLP generator:

from dlp_data_gen.openai_dlp_assistant import OpenAIDLPAssistant

dlp_gen_assistant = OpenAIDLPAssistant(text_data="openai_dlp/text_data", pdf_data="openai_dlp/pdf_data",
                                           dlp_categories_file="dlp/dlp_categories.md")
dlp_gen_assistant.run()

After the run is over, the generated data will be under the openai_dlp/text_data and openai_dlp/pdf_data directory. There will be a single file with mock DLP data for each category.

To use the OpenAI DLP Prompt Generator

from prompt_gen.openai_chat import OpenAIChat

chat_gen = OpenAIChat(text_data="openai_chat_prompt/text_data",
                          pdf_data="openai_chat_prompt/pdf_data",
                          dlp_categories_file="dlp/dlp_categories.md")

chat_gen.run()

Contributing

Contributions to DLP Data Scraper are welcome. Please feel free to submit pull requests or open issues to improve the project.

BenderScript / DLPrompter