Guardrails AI

pip install guardrails-blindfold

export BLINDFOLD_API_KEY=your-api-key

from guardrails import Guard
from guardrails_blindfold import BlindfoldPII

guard = Guard().use(BlindfoldPII(on_fail="fix"))

result = guard.validate("Contact John Doe at john@example.com")
print(result.validated_output)
# → "Contact <Person_1> at <Email Address_1>"

guard = Guard().use(
    BlindfoldPII(
        policy="gdpr_eu",
        region="eu",
        on_fail="fix",
    )
)

result = guard.validate("Hans Mueller, hans.mueller@example.de, IBAN DE89370400440532013000")
print(result.validated_output)
# → "<Person_1>, <Email Address_1>, IBAN <IBAN_1>"

guard = Guard().use(
    BlindfoldPII(
        policy="hipaa_us",
        pii_method="redact",
        region="us",
        on_fail="fix",
    )
)

result = guard.validate("Patient Sarah Jones, SSN 123-45-6789, MRN 4567890")
print(result.validated_output)
# → PHI redacted from output

from guardrails.errors import ValidationError

guard = Guard().use(
    BlindfoldPII(policy="strict", on_fail="exception")
)

try:
    result = guard.validate("Email john@example.com")
except ValidationError as e:
    print("PII detected — output blocked")

guard = Guard().use(
    BlindfoldPII(
        entities=["Email Address", "Phone Number", "Credit Card Number"],
        on_fail="fix",
    )
)

guard = Guard().use(
    BlindfoldPII(policy="strict", on_fail="fix"),
).use(
    AnotherValidator(on_fail="exception"),
)

from guardrails import Guard
from guardrails_blindfold import BlindfoldPII
from openai import OpenAI

client = OpenAI()
guard = Guard().use(BlindfoldPII(policy="gdpr_eu", on_fail="fix"))

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Write a sample customer profile"}],
)

# Validate and protect PII in the LLM output
result = guard.validate(response.choices[0].message.content)
print(result.validated_output)  # PII tokenized