Secrets Settings Page#

April 22, 2026

Available in arize-phoenix 14.11.0+

Phoenix now includes a dedicated Settings → Secrets page for managing encrypted LLM provider credentials in the UI. Previously, secrets could only be managed via the PUT /v1/secrets REST API. The new page lets admins add, replace, and delete secrets — such as OPENAI_API_KEY or ANTHROPIC_API_KEY — without writing any API calls.

• Add a new secret by entering its key name and value
• Replace an existing secret’s value in place
• Delete secrets individually
• Search and filter the secrets list by owner or key name
• Admin-only — the page and all mutations require admin access

trace_id in Experiment Evaluators#

April 22, 2026

Available in arize-phoenix-client 2.4.0+

Experiment evaluator functions can now accept a trace_id parameter. Phoenix passes the originating trace ID for each experiment run, so your evaluator can fetch the corresponding trace or use the ID for correlation.

from phoenix.client import Clientclient = Client()def my_evaluator(output, expected, trace_id=None):    # Use trace_id to fetch the originating trace if needed    score = 1.0 if output == expected else 0.0    return {"score": score, "label": "correct" if score else "incorrect"}client.experiments.run_experiment(    dataset="my-dataset",    task=lambda example: example.input["question"],    evaluators=[my_evaluator],)

• Optional parameter — add trace_id to your evaluator’s keyword arguments; runs that produce a trace pass the ID automatically
• Works with sync and async evaluators — both function-based and Evaluator protocol implementations support trace_id
• Custom Evaluator classes — add trace_id to the evaluate or async_evaluate method signature