OpenInference guardrails Instrumentation
Python auto-instrumentation library for LLM applications implemented with Guardrails
Guards are fully OpenTelemetry-compatible and can be sent to an OpenTelemetry collector for monitoring, such as Arize Phoenix or Arize AX.
Installation
pip install openinference-instrumentation-guardrails
Quickstart
This quickstart shows you how to instrument your guardrailed LLM application
Install required packages.
pip install openinference-instrumentation-guardrails guardrails-ai arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp
Start Phoenix in the background as a collector. By default, it listens on http://localhost:6006. You can visit the app via a browser at the same address. (Phoenix does not send data over the internet. It only operates locally on your machine.)
python -m phoenix.server.main serve
Install the TwoWords validator that's used in the Guard.
guardrails hub install hub://guardrails/two_words
Set up GuardrailsInstrumentor to trace your guardrails application and sends the traces to Phoenix at the endpoint defined below.
from openinference.instrumentation.guardrails import GuardrailsInstrumentor
from opentelemetry import trace as trace_api
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.sdk.trace.export import SimpleSpanProcessor
import os
os.environ["OPENAI_API_KEY"] = "YOUR_KEY_HERE"
endpoint = "http://127.0.0.1:6006/v1/traces"
tracer_provider = trace_sdk.TracerProvider()
tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))
trace_api.set_tracer_provider(tracer_provider)
GuardrailsInstrumentor().instrument()
Set up a simple example of LLM call using a Guard
from guardrails import Guard
from guardrails.hub import TwoWords
import openai
guard = 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)
More Info
1 maintainer
Metadata
1 maintainer
Release files for openinference-instrumentation-guardrails 0.1.25
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| openinference_instrumentation_guardrails-0.1.25.tar.gz | 9.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| openinference_instrumentation_guardrails-0.1.25-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 20.9 kB
Release files / openinference_instrumentation_guardrails-0.1.25.tar.gz
| Download URL | openinference_instrumentation_guardrails-0.1.25.tar.gz |
|---|---|
| Size | 9.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3d5d09f0a533c1a50dd59a3720209da974dc518f236f54914a644500fca1b9d2
|
|
BLAKE2b-256 checksum How to use checksums |
3552ed65a96ae1b5595b66a550a841474dbf31ab36c749ef96ca54e80b191406
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 1, 2026.
Transparency logRelease files / openinference_instrumentation_guardrails-0.1.25-py3-none-any.whl
| Download URL | openinference_instrumentation_guardrails-0.1.25-py3-none-any.whl |
|---|---|
| Size | 11.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
61bbc5789dca0d4f2a0ec73cfa55211e59aa1decaf9e129a2b108227b8ef51b1
|
|
BLAKE2b-256 checksum How to use checksums |
d5276815ed296fbb4fcbba0134b2d8e554cef24ac67f3d3a5aeaa70229a2b26a
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 1, 2026.
Transparency log
