use codex_otel::MetricsClient;use codex_otel::MetricsConfig;use codex_otel::Result;use opentelemetry::KeyValue;use opentelemetry_sdk::metrics::InMemoryMetricExporter;use opentelemetry_sdk::metrics::data::AggregatedMetrics;use opentelemetry_sdk::metrics::data::Metric;use opentelemetry_sdk::metrics::data::MetricData;use opentelemetry_sdk::metrics::data::ResourceMetrics;use std::collections::BTreeMap;pub(crate) fn build_metrics_with_defaults(    default_tags: &[(&str, &str)],) -> Result<(MetricsClient, InMemoryMetricExporter)> {    let exporter = InMemoryMetricExporter::default();    let mut config = MetricsConfig::in_memory(        "test",        "codex-cli",        env!("CARGO_PKG_VERSION"),        exporter.clone(),    );    for (key, value) in default_tags {        config = config.with_tag(*key, *value)?;    }    let metrics = MetricsClient::new(config)?;    Ok((metrics, exporter))}pub(crate) fn latest_metrics(exporter: &InMemoryMetricExporter) -> ResourceMetrics {    exporter        .get_finished_metrics()        .expect("finished metrics should be available")        .into_iter()        .last()        .expect("metrics export should exist")}pub(crate) fn find_metric<'a>(    resource_metrics: &'a ResourceMetrics,    name: &str,) -> Option<&'a Metric> {    for scope_metrics in resource_metrics.scope_metrics() {        for metric in scope_metrics.metrics() {            if metric.name() == name {                return Some(metric);            }        }    }    None}pub(crate) fn attributes_to_map<'a>(    attributes: impl Iterator<Item = &'a KeyValue>,) -> BTreeMap<String, String> {    attributes        .map(|kv| (kv.key.as_str().to_string(), kv.value.as_str().to_string()))        .collect()}pub(crate) fn histogram_data(    resource_metrics: &ResourceMetrics,    name: &str,) -> (Vec<f64>, Vec<u64>, f64, u64) {    let metric = find_metric(resource_metrics, name).expect("metric should exist");    match metric.data() {        AggregatedMetrics::F64(data) => match data {            MetricData::Histogram(histogram) => {                let points: Vec<_> = histogram.data_points().collect();                assert_eq!(points.len(), 1);                let point = points[0];                let bounds = point.bounds().collect();                let bucket_counts = point.bucket_counts().collect();                (bounds, bucket_counts, point.sum(), point.count())            }            _ => panic!("unexpected histogram aggregation"),        },        _ => panic!("unexpected metric data type"),    }}