Arize Phoenix (arize-phoenix)

# === OPTION A: Local dev (run Phoenix server + instrument your app) ===

# 1. Launch Phoenix server locally
import phoenix as px
px.launch_app()  # Opens UI at http://localhost:6006

# 2. Instrument with OTel
from phoenix.otel import register
from openinference.instrumentation.openai import OpenAIInstrumentor

tracer_provider = register(
    project_name='my-app',
    # auto_instrument=True  # Only works if openinference-instrumentation-* pkgs are installed
)
OpenAIInstrumentor().instrument(tracer_provider=tracer_provider)

import openai
client = openai.OpenAI()
response = client.chat.completions.create(
    model='gpt-4o',
    messages=[{'role': 'user', 'content': 'Hello!'}]
)
# Trace visible in Phoenix UI at http://localhost:6006

# === OPTION B: Production (app code → deployed Phoenix server) ===
import os
os.environ['PHOENIX_COLLECTOR_ENDPOINT'] = 'https://app.phoenix.arize.com/s/my-space'
os.environ['PHOENIX_API_KEY'] = 'your-phoenix-api-key'

from phoenix.otel import register
tracer_provider = register(project_name='prod-app', batch=True)
OpenAIInstrumentor().instrument(tracer_provider=tracer_provider)

# === Phoenix Client (REST API) ===
from phoenix.client import Client
ph = Client()  # reads PHOENIX_BASE_URL and PHOENIX_API_KEY from env

# Query traces
spans = ph.spans.query(project_name='my-app')

# === Evaluations ===
from phoenix.evals import llm_classify, OpenAIModel
model = OpenAIModel(model='gpt-4o')
results = llm_classify(
    dataframe=spans_df,
    model=model,
    template='hallucination',  # built-in template
    rails=['factual', 'hallucinated']
)