Offical Guardrails AI SDK
Project description
guardrails-client
A thin REST client for the guardrails-api.
Quickstart
pip install guardrails-ai-sdk
from guardrails_ai.sdk import GuardrailsAI, Guard, ValidationOutcome
# Init the GuardrailsAI client
client = GuardrailsAI(api_key="xxx")
# Fetch a Guard from the server
guard: Guard = await client.guards.retrieve(name="my-guard")
print(guard)
# Run a Guard to validate content
validation_outcome: ValidationOutcome = await client.guards.validate(name="my-guard", llm_output="Hello, world.")
if not validation_outcome.validation_passed:
print(validation_outcome.validation_summaries)
# Create Guarded Chat Completions
chat_completion = await client.guards.chat.completions.create(guard_name="my-guard", model="gpt-5-nano", messages=[{ "role": "user", "content": "Hello, world." }])
print(chat_completion.choices[0].message.content)
print(chat_completion.guardrails)
# Stream Guarded Chat Completions
completion_stream = await client.guards.chat.completions.create(
guard_name="my-first-guard",
model="gpt-5-nano",
messages=[
{"role": "user", "content": "Give yourself a realistic name and introduce yourself."}
],
stream=True
)
full_text = ""
validation_summaries = []
async for chunk in completion_stream:
full_text += chunk.choices[0].delta.content
validation_summaries.extend(chunk.guardrails.get("validation_summaries", []))
print("\n ==> Validation Summaries: ", validation_summaries)
print("\n ==> Final Content: ", full_text)
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