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'] )