> ## Documentation Index
> Fetch the complete documentation index at: https://arizeai-433a7140.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# 04.22.2026 Secrets Settings Page and Evaluator Trace ID

> Manage LLM provider secrets in the UI; pass trace IDs to experiment evaluators for correlation and debugging.

# 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.

```python theme={null}
from phoenix.client import Client

client = 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

<CardGroup cols={2}>
  <Card title="Run Experiments" icon="flask" href="/docs/phoenix/datasets-and-experiments/how-to-experiments/run-experiments">
    Learn how to define tasks and evaluators for experiment runs.
  </Card>
</CardGroup>