Prompt flow

Create flows using Microsoft PromptFlow and send their traces to Phoenix

This integration will allow you to trace Microsoft PromptFlow flows and send their traces intoarize-phoenix.

Launch Phoenix

Phoenix Developer Edition

Sign up for Phoenix:

Sign up for an Arize Phoenix account at https://app.phoenix.arize.com/login

Install packages:

pip install arize-phoenix-otel

Connect your application to your cloud instance:

import os
from phoenix.otel import register

# Add Phoenix API Key for tracing
PHOENIX_API_KEY = "ADD YOUR API KEY"
os.environ["PHOENIX_CLIENT_HEADERS"] = f"api_key={PHOENIX_API_KEY}"
os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "https://app.phoenix.arize.com"

# configure the Phoenix tracer
tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
) 

Your Phoenix API key can be found on the Keys section of your dashboard.

Command Line

Launch your local Phoenix instance:

pip install arize-phoenix
phoenix serve

For details on customizing a local terminal deployment, see Terminal Setup.

Install packages:

pip install arize-phoenix-otel

Connect your application to your instance using:

from phoenix.otel import register

tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  endpoint="http://localhost:6006/v1/traces",
)

See Quickstart: Deployment for more details

Docker

Pull latest Phoenix image from Docker Hub:

docker pull arizephoenix/phoenix:latest

Run your containerized instance:

docker run -p 6006:6006 arizephoenix/phoenix:latest

This will expose the Phoenix on localhost:6006

Install packages:

pip install arize-phoenix-otel

Connect your application to your instance using:

from phoenix.otel import register

tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  endpoint="http://localhost:6006/v1/traces",
)

For more info on using Phoenix with Docker, see Docker

Notebook

Install packages:

pip install arize-phoenix

Launch Phoenix:

import phoenix as px
px.launch_app()

Connect your notebook to Phoenix:

from phoenix.otel import register

tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
)

By default, notebook instances do not have persistent storage, so your traces will disappear after the notebook is closed. See Persistence or use one of the other deployment options to retain traces.

Install

pip install promptflow

Setup

Set up the OpenTelemetry endpoint to point to Phoenix and use Prompt flow's setup_exporter_from_environ to start tracing any further flows and LLM calls.

import os
from opentelemetry.sdk.environment_variables import OTEL_EXPORTER_OTLP_ENDPOINT
from promptflow.tracing._start_trace import setup_exporter_from_environ

endpoint = f"http://127.0.0.1:6006/v1/traces" # replace with your Phoenix endpoint if self-hosting
os.environ[OTEL_EXPORTER_OTLP_ENDPOINT] = endpoint
setup_exporter_from_environ()

Run PromptFlow

Proceed with creating Prompt flow flows as usual. See this example notebook for inspiration.

Observe

You should see the spans render in Phoenix as shown in the below screenshots.

Resources

• Example Notebook