feat: centralize cost breakdown calculations in pipeline
Extract token-type and per-model cost calculations from cmd/costs.go into a dedicated pipeline.AggregateCostBreakdown() function. This eliminates duplicate cost calculation logic between CLI and TUI. New types: - TokenTypeCosts: aggregate costs by input/output/cache types - ModelCostBreakdown: per-model cost components Benefits: - Single source of truth for cost calculations - Uses LookupPricingAt() for historical accuracy - Both CLI and TUI now share the same cost logic - Easier to maintain and extend Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
62
cmd/costs.go
62
cmd/costs.go
@@ -3,9 +3,8 @@ package cmd
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import (
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"fmt"
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"cburn/internal/cli"
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"cburn/internal/config"
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"cburn/internal/pipeline"
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"github.com/theirongolddev/cburn/internal/cli"
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"github.com/theirongolddev/cburn/internal/pipeline"
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"github.com/spf13/cobra"
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)
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@@ -32,7 +31,7 @@ func runCosts(_ *cobra.Command, _ []string) error {
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filtered, since, until := applyFilters(result.Sessions)
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stats := pipeline.Aggregate(filtered, since, until)
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models := pipeline.AggregateModels(filtered, since, until)
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tokenCosts, modelCosts := pipeline.AggregateCostBreakdown(filtered, since, until)
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if stats.TotalSessions == 0 {
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fmt.Println("\n No sessions in the selected time range.")
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@@ -54,30 +53,14 @@ func runCosts(_ *cobra.Command, _ []string) error {
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cost float64
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}
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// Calculate costs per token type from raw token counts using canonical pricing
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var inputCost, outputCost, cache5mCost, cache1hCost, cacheReadCost float64
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for _, s := range pipeline.FilterByTime(filtered, since, until) {
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for modelName, mu := range s.Models {
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p, ok := config.LookupPricing(modelName)
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if !ok {
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continue
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}
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inputCost += float64(mu.InputTokens) * p.InputPerMTok / 1_000_000
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outputCost += float64(mu.OutputTokens) * p.OutputPerMTok / 1_000_000
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cache5mCost += float64(mu.CacheCreation5mTokens) * p.CacheWrite5mPerMTok / 1_000_000
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cache1hCost += float64(mu.CacheCreation1hTokens) * p.CacheWrite1hPerMTok / 1_000_000
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cacheReadCost += float64(mu.CacheReadTokens) * p.CacheReadPerMTok / 1_000_000
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}
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}
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totalCost := inputCost + outputCost + cache5mCost + cache1hCost + cacheReadCost
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totalCost := tokenCosts.TotalCost
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costs := []tokenCost{
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{"Output", outputCost},
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{"Cache Write (1h)", cache1hCost},
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{"Input", inputCost},
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{"Cache Write (5m)", cache5mCost},
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{"Cache Read", cacheReadCost},
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{"Output", tokenCosts.OutputCost},
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{"Cache Write (1h)", tokenCosts.Cache1hCost},
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{"Input", tokenCosts.InputCost},
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{"Cache Write (5m)", tokenCosts.Cache5mCost},
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{"Cache Read", tokenCosts.CacheReadCost},
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}
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// Sort by cost descending (already in expected order, but ensure)
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@@ -116,29 +99,22 @@ func runCosts(_ *cobra.Command, _ []string) error {
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}
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// Cost by model
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modelRows := make([][]string, 0, len(models)+2)
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for _, ms := range models {
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p, _ := config.LookupPricing(ms.Model)
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mInput := float64(ms.InputTokens) * p.InputPerMTok / 1_000_000
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mOutput := float64(ms.OutputTokens) * p.OutputPerMTok / 1_000_000
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mCache := float64(ms.CacheCreation5m)*p.CacheWrite5mPerMTok/1_000_000 +
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float64(ms.CacheCreation1h)*p.CacheWrite1hPerMTok/1_000_000 +
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float64(ms.CacheReadTokens)*p.CacheReadPerMTok/1_000_000
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modelRows := make([][]string, 0, len(modelCosts)+2)
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for _, mc := range modelCosts {
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modelRows = append(modelRows, []string{
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shortModel(ms.Model),
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cli.FormatCost(mInput),
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cli.FormatCost(mOutput),
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cli.FormatCost(mCache),
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cli.FormatCost(ms.EstimatedCost),
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shortModel(mc.Model),
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cli.FormatCost(mc.InputCost),
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cli.FormatCost(mc.OutputCost),
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cli.FormatCost(mc.CacheCost),
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cli.FormatCost(mc.TotalCost),
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})
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}
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modelRows = append(modelRows, []string{"---"})
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modelRows = append(modelRows, []string{
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"TOTAL",
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cli.FormatCost(inputCost),
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cli.FormatCost(outputCost),
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cli.FormatCost(cache5mCost + cache1hCost + cacheReadCost),
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cli.FormatCost(tokenCosts.InputCost),
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cli.FormatCost(tokenCosts.OutputCost),
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cli.FormatCost(tokenCosts.CacheCost),
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cli.FormatCost(totalCost),
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})
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