Guardrails AI Tracing

In this example we will instrument a small program that uses the Guardrails AI framework to protect their LLM calls.

Install#

pip install openinference-instrumentation-guardrails guardrails-ai

Setup#

Connect your application to Phoenix with the register function:

from phoenix.otel import register# configure the Phoenix tracertracer_provider = register(project_name="my-llm-app", # Default is 'default'auto_instrument=True # Auto-instrument your app based on installed OI dependencies)

Run Guardrails#

From here, you can run Guardrails as normal:

from guardrails import Guardfrom guardrails.hub import TwoWordsimport openaiguard = Guard().use(    TwoWords(),)response = guard(    llm_api=openai.chat.completions.create,    prompt="What is another name for America?",    model="gpt-3.5-turbo",    max_tokens=1024,)print(response)

Observe#

Now that you have tracing setup, all invocations of underlying models used by Guardrails (completions, chat completions, embeddings) will be streamed to your running Phoenix for observability and evaluation. Additionally, Guards will be present as a new span kind in Phoenix.

Install#

Setup#

Run Guardrails#

Observe#

Resources#