llama-stack/docs/source/building_applications/evaluation.md
Xi Yan 8b655e3cd2
fix!: update eval-tasks -> benchmarks (#1032)
# What does this PR do?

- Update `/eval-tasks` to `/benchmarks`
- ⚠️ Remove differentiation between `app` v.s. `benchmark` eval task
config. Now we only have `BenchmarkConfig`. The overloaded `benchmark`
is confusing and do not add any value. Backward compatibility is being
kept as the "type" is not being used anywhere.

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan
- This change is backward compatible 
- Run notebook test with

```
pytest -v -s --nbval-lax ./docs/getting_started.ipynb
pytest -v -s --nbval-lax ./docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb
```

<img width="846" alt="image"
src="https://github.com/user-attachments/assets/d2fc06a7-593a-444f-bc1f-10ab9b0c843d"
/>



[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)

---------

Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
Signed-off-by: Ben Browning <bbrownin@redhat.com>
Signed-off-by: Sébastien Han <seb@redhat.com>
Signed-off-by: reidliu <reid201711@gmail.com>
Co-authored-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
Co-authored-by: Ben Browning <ben324@gmail.com>
Co-authored-by: Sébastien Han <seb@redhat.com>
Co-authored-by: Reid <61492567+reidliu41@users.noreply.github.com>
Co-authored-by: reidliu <reid201711@gmail.com>
Co-authored-by: Yuan Tang <terrytangyuan@gmail.com>
2025-02-13 16:40:58 -08:00

784 B

Testing & Evaluation

Llama Stack provides built-in tools for evaluating your applications:

  1. Benchmarking: Test against standard datasets
  2. Application Evaluation: Score your application's outputs
  3. Custom Metrics: Define your own evaluation criteria

Here's how to set up basic evaluation:

# Create an evaluation task
response = client.benchmarks.register(
    benchmark_id="my_eval",
    dataset_id="my_dataset",
    scoring_functions=["accuracy", "relevance"],
)

# Run evaluation
job = client.eval.run_eval(
    benchmark_id="my_eval",
    task_config={
        "type": "app",
        "eval_candidate": {"type": "agent", "config": agent_config},
    },
)

# Get results
result = client.eval.job_result(benchmark_id="my_eval", job_id=job.job_id)