feat(dashboard): v0.7.4 — 热力图双击弹窗展示当日模型用量（Token/请求/费用/命中率）+ by_model 结构化升级

src-tauri/src/dashboard.rs

@@ -132,8 +132,8 @@ pub struct DailyRow {
     pub cost_usd: f64,
     pub total_tokens: u64,
     pub cache_hit_rate: f64,
-    /// Per-model token breakdown for stacked-bar rendering
-    pub by_model: HashMap<String, u64>,
+    /// Per-model structured breakdown (tokens / requests / cost / cacheHitRate).
+    pub by_model: HashMap<String, TotalsRow>,
     /// Per-provider token breakdown for stacked-bar rendering
     pub by_provider: HashMap<String, u64>,
     /// Per-provider, per-model nested token breakdown (provider → model → tokens),
@@ -980,7 +980,7 @@ fn aggregate(records: &[UsageRecord], range: &str, now_ms: u64) -> RangeStats {
     }
 
     let mut totals = TotalsRow::default();
-    let mut by_day: HashMap<String, (TotalsRow, HashMap<String, u64>, HashMap<String, HashMap<String, u64>>)> = HashMap::new();
+    let mut by_day: HashMap<String, (TotalsRow, HashMap<String, TotalsRow>, HashMap<String, HashMap<String, u64>>)> = HashMap::new();
     let mut by_model: HashMap<String, (ModelRow, TotalsRow)> = HashMap::new();
 
     for r in &filtered {
@@ -988,8 +988,7 @@ fn aggregate(records: &[UsageRecord], range: &str, now_ms: u64) -> RangeStats {
         let dk = day_key(r.time);
         let (day_totals, day_models, day_prov_models) = by_day.entry(dk.clone()).or_default();
         day_totals.add(r);
-        *day_models.entry(r.model.clone()).or_insert(0) +=
-            r.input_other + r.output + r.input_cache_read + r.input_cache_creation;
+        day_models.entry(r.model.clone()).or_default().add(r);
         let provider_key = r.provider.clone().unwrap_or_else(|| "unknown".to_string());
         *day_prov_models
             .entry(provider_key)
@@ -1024,12 +1023,22 @@ fn aggregate(records: &[UsageRecord], range: &str, now_ms: u64) -> RangeStats {
         .map(|(date, (t, by_model, by_provider_model))| {
             let ti = t.input_other + t.input_cache_read + t.input_cache_creation;
             let ch = if ti > 0 { t.input_cache_read as f64 / ti as f64 } else { 0.0 };
+            // Per-model cache_hit_rate (not cumulative; computed from the
+            // model's own input token split).
+            let by_model_finalized: HashMap<String, TotalsRow> = by_model
+                .into_iter()
+                .map(|(k, mut mt)| {
+                    let mi = mt.input_other + mt.input_cache_read + mt.input_cache_creation;
+                    mt.cache_hit_rate = if mi > 0 { mt.input_cache_read as f64 / mi as f64 } else { 0.0 };
+                    (k, mt)
+                })
+                .collect();
             DailyRow {
                 date, requests: t.requests,
                 input_other: t.input_other, output: t.output,
                 input_cache_read: t.input_cache_read, input_cache_creation: t.input_cache_creation,
                 cost_usd: t.cost_usd, total_tokens: t.total_tokens, cache_hit_rate: ch,
-                by_model,
+                by_model: by_model_finalized,
                 by_provider: by_provider_model
                     .iter()
                     .map(|(p, m)| (p.clone(), m.values().sum::<u64>()))