In-Application

pip install guardrails-ai

guardrails configure

pip install guardrails-ai-detect-pii

pip install guardrails-ai-regex-match

# Import Guard and Validator
from guardrails_ai.regex_match import RegexMatch
from guardrails import Guard

# Initialize the Guard with
guard = Guard().use(
    RegexMatch(regex="^[A-Z][a-z]*$")
)

print(guard.parse("Caesar").validation_passed)  # Guardrail Passes
print(
    guard.parse("Caesar Salad")
    .validation_passed
)  # Guardrail Fails

pip install guardrails-ai-regex-match guardrails-ai-valid-length

from guardrails_ai.regex_match import RegexMatch
from guardrails_ai.valid_length import ValidLength
from guardrails import Guard

guard = Guard().use(
    RegexMatch(regex="^[A-Z][a-z]*$"),
    ValidLength(min=1, max=12)
)

print(guard.parse("Caesar").validation_passed)  # Guardrail Passes
print(
    guard.parse("Caesar Salad")
    .validation_passed
)  # Guardrail Fails due to regex match
print(
    guard.parse("Caesarisagreatleader")
    .validation_passed
)  # Guardrail Fails due to length

from pydantic import BaseModel, Field

class Pet(BaseModel):
    pet_type: str = Field(description="Species of pet")
    name: str = Field(description="a unique pet name")

from guardrails import Guard

prompt = """
What kind of pet should I get and what should I name it?
${gr.complete_json_suffix_v2}
"""
guard = Guard.for_pydantic(output_class=Pet)

res = guard(
    model="gpt-3.5-turbo",
    messages=[{
        "role": "user",
        "content": prompt
    }]
)

print(f"{res.validated_output}")

{
    "pet_type": "dog",
    "name": "Buddy"
}

npm i @guardrails-ai/core