aiguardrail

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 !