datafog 3.2.0b12

Scan, redact, and manage PII in your documents before they get uploaded to a Retrieval Augmented Generation (RAG) system.

Open-source DevSecOps for Generative AI Systems.

Overview

What is DataFog?

DataFog is an open-source DevSecOps platform that lets you scan and redact Personally Identifiable Information (PII) out of your Generative AI applications.

Core Problem

How it works

Installation

DataFog can be installed via pip:

pip install datafog

Examples - Updated for v3.1

Base case: PII annotation of text-files

from datafog import OCRPIIAnnotator, TextPIIAnnotator
import json
import requests

response = requests.get('https://gist.githubusercontent.com/sidmohan0/1aa3ec38b4e6594d3c34b113f2e0962d/raw/42e57146197be0f85a5901cd1dcdd9ad15b31bab/sotu_2023.txt')
response.raise_for_status()  # Ensure the request was successful
text = response.text
# print(text)
text_annotator = TextPIIAnnotator()
annotated_text = text_annotator.run(text, output_path=f"sotu_2023_output.json")
print("Annotated Text:", annotated_text)

OCR Reference Set (Images)

image_set = {
    "medical_invoice": "https://s3.amazonaws.com/thumbnails.venngage.com/template/dc377004-1c2d-49f2-8ddf-d63f11c8d9c2.png",
    "sales_receipt": "https://templates.invoicehome.com/sales-receipt-template-us-classic-white-750px.png",
    "press_release": "https://newsroom.cisco.com/c/dam/r/newsroom/en/us/assets/a/y2023/m09/cisco_splunk_1200x675_v3.png",
    "insurance_claim_scanned_form": "https://www.pdffiller.com/preview/101/35/101035394.png",
    "scanned_internal_record": "https://www.pdffiller.com/preview/435/972/435972694.png",
    "executive_email": "https://pbs.twimg.com/media/GM3-wpeWkAAP-cX.jpg"
}

OCR text extraction from images + PII annotation

with this, you can then run the following steps:

from datafog import OCRPIIAnnotator, TextPIIAnnotator
import json

image_url = image_set["executive_email"]

annotator = OCRPIIAnnotator()
annotated_text = annotator.run(image_url, output_path=f"executive_email_output.json")
print("Annotated Text:", annotated_text)

and the output should look like this:

Annotated Text: {'DATE_TIME': ['Wednesday', 'June 12, 2019'], 'LOC': [], 'NRP': [], 'ORG': [], 'PER': ['Kevin Scott Sent', 'Satya Nadella', 'Bill Gates Subject', 'Thoughts']}

With PySpark

Note: as of 3.1.0, you'll need to start the Spark session by instancing the DataFog class as shown below

from datafog import DataFog
from datafog.pii_annotation import ImageProcessor
datafog = DataFog()

# let's process the images that we shared above
processed_images = [(name, ImageProcessor().download_image(url=image_url)) for name, image_url in image_set.items()]

from datafog.pii_annotation import SparkService
parsed_images = [(name, ImageProcessor().parse_image(img)) for name, img in processed_images]

df = SparkService().spark.createDataFrame(parsed_images, ["image_name", "parsed_data"])

# Display DataFrame
df.show(truncate=False)

Contributing

DataFog is a community-driven open-source platform and we've been fortunate to have a small and growing contributor base. We'd love to hear ideas, feedback, suggestions for improvement - anything on your mind about what you think can be done to make DataFog better! Join our Discord and join our growing community.

Dev Notes

• Justfile commands:
  • just format to apply formatting.
  • just lint to check formatting and style.

Testing

To run the datafog unit tests, check out this repository and do

tox

License

This software is published under the MIT license.