Portable format for router benchmark results (EvalPort) — worth exporting alongside the plots?

Nobody has claimed this yet.

Hi RouteLLM maintainers,

Read through `routellm/evals/evaluate.py` and the `Benchmark`/`Router` abstractions in the README. The evaluation loop is nice: for each router, `benchmark.evaluate(controller, router, num_results, ...)` yields `(threshold, accuracy, model_counts, total)` tuples, which `evaluate.py` turns into a `strong_percentage`/`accuracy` DataFrame per method, then derives `AUC` and `APGR` metrics and a matplotlib plot per benchmark (`{output}/{benchmark_name}.png`).

That's exactly the kind of result set that's useful outside the plot too — e.g. handing router-quality numbers to someone comparing RouteLLM against a different routing/eval setup, or archiving results across router versions in a diffable way, without re-parsing the printed "Model %:" lines or the cached per-benchmark pickle files.

I maintain EvalPort (https://github.com/adhabnr-ux/evalport), a small open spec — JSON Schemas under `spec/schemas/` (`resultset.json` in particular) plus Python/TS SDKs — for representing exactly this kind of scored-run output (test case id, score, grader/method metadata) in a form that isn't tied to one project's DataFrame layout.

A minimal adapter would just sit next to `generate_results()` and reshape the existing `all_results` rows:

```python
def to_resultset(df_router_result: pd.DataFrame, benchmark_name: str) -> evalport.ResultSet:
return evalport.ResultSet(
suite_id=benchmark_name,
results=[
evalport.Result(
test_case_id=f"{row.method}@{row.strong_percentage:.1f}",
score=row.accuracy,
grader=row.method, # e.g. "mf", "sw_ranking", "random"
)
for row in df_router_result.itertuples()
],
)
```

Spec: https://github.com/adhabnr-ux/evalport/blob/main/SPEC.md

Not proposing a dependency on RouteLLM's core — happy to build and maintain this as a small standalone script/adapter if it'd actually be useful to anyone comparing routers across tools. If not, feel free to close — no pressure. Thanks for RouteLLM, the `mf`/`sw_ranking`/`bert`/`causal_llm` router comparison setup is a clean piece of work.

Start with routellm/evals/evaluate.py, especially generate_results(), and review the Benchmark/Router abstractions in the README. Check EvalPort's resultset.json schema and determine whether the existing all_results rows can be exported by a standalone adapter. Done means the proposal's usefulness and output shape are agreed, with a portable result set that represents the benchmark results without changing RouteLLM core.

Written by the indexing model from the issue text.