Skip to main content

Guardrails for evaluating AI-generated content

Project description

AIGuardrail: AI Content Guardrails

AIGuardrail is a comprehensive Python library designed to evaluate and safeguard AI-generated content. It provides robust checks for safety, factual consistency, readability, privacy, token efficiency, and protection against malicious content.


🚀 Features

  • Output Moderation: Detect toxic, offensive, or inappropriate language.
  • Factual Consistency & Hallucination Detection: Prevent AI-generated inaccuracies or hallucinated information.
  • PII Redaction: Identify and flag personally identifiable information (PII).
  • Prompt Injection Protection: Detect potential prompt injection attacks.
  • Token Management: Optimize content length based on token limits.
  • Response Quality Checks: Evaluate readability, verbosity, and bias in AI outputs.

📦 Installation

Install aiguardrail via pip:

pip install aiguardrail

🛠️ Usage

Evaluate text quickly against all available guardrails:

from aiguardrail.guardrails import evaluate_guardrails

text = "According to the source, this event took place in March."

results_df, final_score = evaluate_guardrails(text)

print(results_df)
print(f"Overall Guardrail Score: {final_score}")

Evaluate specific guardrails only:

specific_guardrails = ["GR-S-001", "GR-Q-005", "GR-C-002"]

results_df, final_score = evaluate_guardrails(text, selected_guardrail_ids=specific_guardrails)

print(results_df)
print(f"Overall Guardrail Score: {final_score}")

📚 Available Guardrails

Retrieve metadata about all guardrails easily:

from aiguardrail.guardrails import list_available_guardrails

guardrails = list_available_guardrails()
for gr in guardrails:
    print(f"{gr['id']} - {gr['name']} [{gr['area']}]")

Example output:

GR-S-001 - Output Moderation [Security]
GR-Q-001 - Hallucination Detection [Quality]
GR-S-005 - PII Redaction [Security]
...

📜 License

Guardrails-Eval is licensed under the MIT License. See LICENSE for details.

‍💻 Author

SHUBHAM GANESH MHASKE

Email: mhaskeshubham1200@gmail.com

⭐ Enjoy using aiguardrail !

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aiguardrail-0.1.0.tar.gz (6.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aiguardrail-0.1.0-py3-none-any.whl (7.0 kB view details)

Uploaded Python 3

File details

Details for the file aiguardrail-0.1.0.tar.gz.

File metadata

  • Download URL: aiguardrail-0.1.0.tar.gz
  • Upload date:
  • Size: 6.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.4

File hashes

Hashes for aiguardrail-0.1.0.tar.gz
Algorithm Hash digest
SHA256 30f534d8a6b3ec3dca267cefe9fe5a853664ff864fa16ad5b3f063e9239d89ec
MD5 0ad8c12420636b140e8b2a952e698665
BLAKE2b-256 10470e91c75c8db828a1ce10be21aadc1bdd219f3eeafe616e3eb9b8b3bb73ba

See more details on using hashes here.

File details

Details for the file aiguardrail-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: aiguardrail-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 7.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.4

File hashes

Hashes for aiguardrail-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 61849784e89fa3aa128bf89ce2770cb1c76bb98f59ffb3d35ab2724120b59a7a
MD5 1b6d87bf6394d6b2b2fa2bd518724bf9
BLAKE2b-256 546c9b96bbf1e024b14a8072c53efe9da5936c782199a72560de9c53a3df7b2b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page