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chore: sync Arize skills from arize-skills@597d609bfe5f07fd7d24acfdb408a082911b18fc and phoenix@746247cbb07b0dc7803b87c69dd8c77811c33f59 (#1583)

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This commit is contained in:
Jim Bennett
2026-05-03 18:05:44 -07:00
committed by GitHub
parent 82b58047e0
commit c7b2aecb94
40 changed files with 1316 additions and 423 deletions
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28
skills/phoenix-evals/references/experiments-overview.md
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@@ -14,9 +14,10 @@ EXPERIMENT → Run task on all examples, score results
## Basic Usage
```python
from phoenix.client.experiments import run_experiment
from phoenix.client import Client
experiment = run_experiment(
client = Client()
experiment = client.experiments.run_experiment(
dataset=my_dataset,
task=my_task,
evaluators=[accuracy, faithfulness],
@@ -40,7 +41,28 @@ print(experiment.aggregate_scores)
Test setup before full execution:
```python
experiment = run_experiment(dataset, task, evaluators, dry_run=3) # Just 3 examples
experiment = client.experiments.run_experiment(
dataset=dataset,
task=task,
evaluators=evaluators,
dry_run=3,
) # Just 3 examples
```
## Async Usage
Use `AsyncClient` when your task or evaluators make network calls and you want higher throughput:
```python
from phoenix.client import AsyncClient
client = AsyncClient()
experiment = await client.experiments.run_experiment(
dataset=my_dataset,
task=my_async_task,
evaluators=[accuracy, faithfulness],
experiment_name="improved-retrieval-v2",
)
```
## Best Practices