feat: add len variable for tier conditions and LLM prompt helper

This commit is contained in:
CaIon
2026-04-25 13:24:20 +08:00
parent a7c38ec851
commit f2f3410dcf
15 changed files with 393 additions and 47 deletions
+73 -2
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@@ -1000,11 +1000,82 @@ func TestImageAudioZero(t *testing.T) {
} }
} }
// ---------------------------------------------------------------------------
// len variable tests — tier conditions based on context length
// ---------------------------------------------------------------------------
const lenTieredExpr = `len <= 200000 ? tier("standard", p * 3 + c * 15 + cr * 0.3) : tier("long_context", p * 6 + c * 22.5 + cr * 0.6)`
func TestLen_StandardTier(t *testing.T) {
params := billingexpr.TokenParams{P: 80000, C: 5000, Len: 100000, CR: 20000}
cost, trace, err := billingexpr.RunExpr(lenTieredExpr, params)
if err != nil {
t.Fatal(err)
}
want := 80000*3 + 5000*15 + 20000*0.3
if math.Abs(cost-want) > 1e-6 {
t.Errorf("cost = %f, want %f", cost, want)
}
if trace.MatchedTier != "standard" {
t.Errorf("tier = %q, want standard", trace.MatchedTier)
}
}
func TestLen_LongContextTier(t *testing.T) {
// p is low (cache subtracted), but len is high (full context)
params := billingexpr.TokenParams{P: 50000, C: 5000, Len: 300000, CR: 250000}
cost, trace, err := billingexpr.RunExpr(lenTieredExpr, params)
if err != nil {
t.Fatal(err)
}
want := 50000*6 + 5000*22.5 + 250000*0.6
if math.Abs(cost-want) > 1e-6 {
t.Errorf("cost = %f, want %f", cost, want)
}
if trace.MatchedTier != "long_context" {
t.Errorf("tier = %q, want long_context (len=300000 > 200000)", trace.MatchedTier)
}
}
func TestLen_BoundaryExact(t *testing.T) {
params := billingexpr.TokenParams{P: 100000, C: 1000, Len: 200000, CR: 100000}
_, trace, err := billingexpr.RunExpr(lenTieredExpr, params)
if err != nil {
t.Fatal(err)
}
if trace.MatchedTier != "standard" {
t.Errorf("tier = %q, want standard (len=200000 <= 200000)", trace.MatchedTier)
}
}
func TestLen_BoundaryPlusOne(t *testing.T) {
params := billingexpr.TokenParams{P: 100000, C: 1000, Len: 200001, CR: 100001}
_, trace, err := billingexpr.RunExpr(lenTieredExpr, params)
if err != nil {
t.Fatal(err)
}
if trace.MatchedTier != "long_context" {
t.Errorf("tier = %q, want long_context (len=200001 > 200000)", trace.MatchedTier)
}
}
func TestLen_ZeroDefaultsToZero(t *testing.T) {
// len defaults to 0 when not set
params := billingexpr.TokenParams{P: 1000, C: 500}
_, trace, err := billingexpr.RunExpr(lenTieredExpr, params)
if err != nil {
t.Fatal(err)
}
if trace.MatchedTier != "standard" {
t.Errorf("tier = %q, want standard (len=0 <= 200000)", trace.MatchedTier)
}
}
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
// Benchmarks: compile vs cached execution // Benchmarks: compile vs cached execution
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
const benchComplexExpr = `p <= 200000 ? tier("standard", p * 3 + c * 15 + cr * 0.3 + cc * 3.75 + cc1h * 6 + img * 3 + img_o * 30 + ai * 10 + ao * 40) : tier("long_context", p * 6 + c * 22.5 + cr * 0.6 + cc * 7.5 + cc1h * 12 + img * 6 + img_o * 60 + ai * 20 + ao * 80)` const benchComplexExpr = `len <= 200000 ? tier("standard", p * 3 + c * 15 + cr * 0.3 + cc * 3.75 + cc1h * 6 + img * 3 + img_o * 30 + ai * 10 + ao * 40) : tier("long_context", p * 6 + c * 22.5 + cr * 0.6 + cc * 7.5 + cc1h * 12 + img * 6 + img_o * 60 + ai * 20 + ao * 80)`
func BenchmarkExprCompile(b *testing.B) { func BenchmarkExprCompile(b *testing.B) {
for i := 0; i < b.N; i++ { for i := 0; i < b.N; i++ {
@@ -1015,7 +1086,7 @@ func BenchmarkExprCompile(b *testing.B) {
func BenchmarkExprRunCached(b *testing.B) { func BenchmarkExprRunCached(b *testing.B) {
billingexpr.CompileFromCache(benchComplexExpr) billingexpr.CompileFromCache(benchComplexExpr)
params := billingexpr.TokenParams{P: 150000, C: 10000, CR: 30000, CC: 5000, Img: 2000, AI: 1000, AO: 500} params := billingexpr.TokenParams{P: 150000, C: 10000, Len: 188000, CR: 30000, CC: 5000, Img: 2000, AI: 1000, AO: 500}
b.ResetTimer() b.ResetTimer()
for i := 0; i < b.N; i++ { for i := 0; i < b.N; i++ {
billingexpr.RunExpr(benchComplexExpr, params) billingexpr.RunExpr(benchComplexExpr, params)
+1
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@@ -41,6 +41,7 @@ var (
var compileEnvPrototypeV1 = map[string]interface{}{ var compileEnvPrototypeV1 = map[string]interface{}{
"p": float64(0), "p": float64(0),
"c": float64(0), "c": float64(0),
"len": float64(0),
"cr": float64(0), "cr": float64(0),
"cc": float64(0), "cc": float64(0),
"cc1h": float64(0), "cc1h": float64(0),
+16 -3
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@@ -30,7 +30,8 @@ Powered by [expr-lang/expr](https://github.com/expr-lang/expr). Expressions are
| 变量 | 含义 | | 变量 | 含义 |
|------|------| |------|------|
| `p` | 输入 token 数。**自动排除**表达式中单独计价的子类别(见下方说明) | | `p` | 输入 token 数**计价用**。**自动排除**表达式中单独计价的子类别(见下方说明) |
| `len` | 输入上下文总长度(**条件判断用**)。不受自动排除影响,始终反映完整输入长度。非 Claude:等于原始 `prompt_tokens`;Claude:等于文本输入 + 缓存读取 + 缓存创建 |
| `cr` | 缓存命中(读取)token 数 | | `cr` | 缓存命中(读取)token 数 |
| `cc` | 缓存创建 token 数(Claude 5分钟 TTL / 通用) | | `cc` | 缓存创建 token 数(Claude 5分钟 TTL / 通用) |
| `cc1h` | 缓存创建 token 数 — 1小时 TTLClaude 专用) | | `cc1h` | 缓存创建 token 数 — 1小时 TTLClaude 专用) |
@@ -51,6 +52,8 @@ Powered by [expr-lang/expr](https://github.com/expr-lang/expr). Expressions are
**规则:如果表达式使用了某个子类别变量,对应的 token 就从 `p` 或 `c` 中扣除;如果没使用,那些 token 就留在 `p` 或 `c` 里按基础价格计费。** **规则:如果表达式使用了某个子类别变量,对应的 token 就从 `p` 或 `c` 中扣除;如果没使用,那些 token 就留在 `p` 或 `c` 里按基础价格计费。**
> **重要:`len` 不受自动排除影响。** `len` 始终代表完整的输入上下文长度,不管表达式是否单独对缓存/图片/音频定价。因此**阶梯条件应使用 `len` 而非 `p`**,以避免缓存命中导致 `p` 降低而误判档位。
举例说明(假设上游返回的原始数据:prompt_tokens=1000,其中包含 200 cache read、100 image): 举例说明(假设上游返回的原始数据:prompt_tokens=1000,其中包含 200 cache read、100 image):
| 表达式 | `p` 的值 | 说明 | | 表达式 | `p` 的值 | 说明 |
@@ -93,8 +96,8 @@ Powered by [expr-lang/expr](https://github.com/expr-lang/expr). Expressions are
# Simple flat pricing # Simple flat pricing
tier("base", p * 2.5 + c * 15 + cr * 0.25) tier("base", p * 2.5 + c * 15 + cr * 0.25)
# Multi-tier (Claude Sonnet style) # Multi-tier (Claude Sonnet style) — use len for tier conditions
p <= 200000 len <= 200000
? tier("standard", p * 3 + c * 15 + cr * 0.3 + cc * 3.75 + cc1h * 6) ? tier("standard", p * 3 + c * 15 + cr * 0.3 + cc * 3.75 + cc1h * 6)
: tier("long_context", p * 6 + c * 22.5 + cr * 0.6 + cc * 7.5 + cc1h * 12) : tier("long_context", p * 6 + c * 22.5 + cr * 0.6 + cc * 7.5 + cc1h * 12)
@@ -199,6 +202,16 @@ Example: `p * 2.5 + c * 15 + cr * 0.25`
- Expression uses `cr` → cache read tokens subtracted from `p` - Expression uses `cr` → cache read tokens subtracted from `p`
- Expression doesn't use `img` → image tokens stay in `p`, priced at $2.50 - Expression doesn't use `img` → image tokens stay in `p`, priced at $2.50
### `len` — Context Length Variable
`len` represents the total input context length, designed for **tier condition evaluation** (e.g. `len <= 200000 ? ...`). Unlike `p`, `len` is never reduced by sub-category exclusion.
**Computation rules:**
- **Non-Claude (GPT/OpenAI format)**: `len = prompt_tokens` (the raw total from the upstream response)
- **Claude format**: `len = input_tokens + cache_read_tokens + cache_creation_tokens` (since Claude's `input_tokens` is text-only, cache must be added back to reflect full context length)
This ensures that heavy cache usage doesn't cause the tier condition to incorrectly evaluate to a lower tier. For example, if a request has 300K total context but 250K is cached, `p` with cache subtracted would be only 50K (standard tier), while `len` correctly reports 300K (long-context tier).
### Quota Conversion ### Quota Conversion
Expression coefficients are $/1M tokens. Conversion to internal quota: Expression coefficients are $/1M tokens. Conversion to internal quota:
+3 -1
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@@ -13,7 +13,8 @@ import (
// RunExpr compiles (with cache) and executes an expression string. // RunExpr compiles (with cache) and executes an expression string.
// The environment exposes: // The environment exposes:
// - p, c — prompt / completion tokens // - p, c — prompt / completion tokens (auto-excluding separately-priced sub-categories)
// - len — total input context length for tier conditions (never reduced by sub-category exclusion)
// - cr, cc, cc1h — cache read / creation / creation-1h tokens // - cr, cc, cc1h — cache read / creation / creation-1h tokens
// - tier(name, value) — trace callback that records which tier matched // - tier(name, value) — trace callback that records which tier matched
// - max, min, abs, ceil, floor — standard math helpers // - max, min, abs, ceil, floor — standard math helpers
@@ -54,6 +55,7 @@ func runProgram(prog *vm.Program, params TokenParams, request RequestInput) (flo
env := map[string]interface{}{ env := map[string]interface{}{
"p": params.P, "p": params.P,
"c": params.C, "c": params.C,
"len": params.Len,
"cr": params.CR, "cr": params.CR,
"cc": params.CC, "cc": params.CC,
"cc1h": params.CC1h, "cc1h": params.CC1h,
+3 -2
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@@ -14,8 +14,9 @@ type RequestInput struct {
// Fields beyond P and C are optional — when absent they default to 0, // Fields beyond P and C are optional — when absent they default to 0,
// which means cache-unaware expressions keep working unchanged. // which means cache-unaware expressions keep working unchanged.
type TokenParams struct { type TokenParams struct {
P float64 // prompt tokens (text) P float64 // prompt tokens (text) — auto-excludes sub-categories priced separately
C float64 // completion tokens (text) C float64 // completion tokens (text) — auto-excludes sub-categories priced separately
Len float64 // total input context length for tier conditions (non-Claude: raw prompt_tokens; Claude: text + cache read + cache creation)
CR float64 // cache read (hit) tokens CR float64 // cache read (hit) tokens
CC float64 // cache creation tokens (5-min TTL for Claude, generic for others) CC float64 // cache creation tokens (5-min TTL for Claude, generic for others)
CC1h float64 // cache creation tokens — 1-hour TTL (Claude only) CC1h float64 // cache creation tokens — 1-hour TTL (Claude only)
+3 -2
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@@ -255,8 +255,9 @@ func modelPriceHelperTiered(c *gin.Context, info *relaycommon.RelayInfo, promptT
} }
rawCost, trace, err := billingexpr.RunExprWithRequest(exprStr, billingexpr.TokenParams{ rawCost, trace, err := billingexpr.RunExprWithRequest(exprStr, billingexpr.TokenParams{
P: float64(promptTokens), P: float64(promptTokens),
C: float64(estimatedCompletionTokens), C: float64(estimatedCompletionTokens),
Len: float64(promptTokens),
}, requestInput) }, requestInput)
if err != nil { if err != nil {
return types.PriceData{}, fmt.Errorf("model %s tiered expr run failed: %w", info.OriginModelName, err) return types.PriceData{}, fmt.Errorf("model %s tiered expr run failed: %w", info.OriginModelName, err)
+3 -2
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@@ -160,8 +160,9 @@ func PostWssConsumeQuota(ctx *gin.Context, relayInfo *relaycommon.RelayInfo, mod
var tieredResult *billingexpr.TieredResult var tieredResult *billingexpr.TieredResult
tieredOk, tieredQuota, tieredRes := TryTieredSettle(relayInfo, billingexpr.TokenParams{ tieredOk, tieredQuota, tieredRes := TryTieredSettle(relayInfo, billingexpr.TokenParams{
P: float64(usage.InputTokens), P: float64(usage.InputTokens),
C: float64(usage.OutputTokens), C: float64(usage.OutputTokens),
Len: float64(usage.InputTokens),
}) })
if tieredOk { if tieredOk {
tieredResult = tieredRes tieredResult = tieredRes
+9
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@@ -35,6 +35,14 @@ func BuildTieredTokenParams(usage *dto.Usage, isClaudeUsageSemantic bool, usedVa
imgO := float64(usage.CompletionTokenDetails.ImageTokens) imgO := float64(usage.CompletionTokenDetails.ImageTokens)
ao := float64(usage.CompletionTokenDetails.AudioTokens) ao := float64(usage.CompletionTokenDetails.AudioTokens)
// len = total input context length for tier condition evaluation.
// Non-Claude: prompt_tokens already includes everything.
// Claude: input_tokens is text-only, so add cache read + cache creation.
inputLen := p
if isClaudeUsageSemantic {
inputLen = p + cr + cc5m + cc1h
}
if !isClaudeUsageSemantic { if !isClaudeUsageSemantic {
if usedVars["cr"] { if usedVars["cr"] {
p -= cr p -= cr
@@ -69,6 +77,7 @@ func BuildTieredTokenParams(usage *dto.Usage, isClaudeUsageSemantic bool, usedVa
return billingexpr.TokenParams{ return billingexpr.TokenParams{
P: p, P: p,
C: c, C: c,
Len: inputLen,
CR: cr, CR: cr,
CC: cc5m, CC: cc5m,
CC1h: cc1h, CC1h: cc1h,
+91
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@@ -604,6 +604,97 @@ func TestBuildTieredTokenParams_ParityWithRatio_Image(t *testing.T) {
} }
} }
// ---------------------------------------------------------------------------
// BuildTieredTokenParams: Len computation tests
// ---------------------------------------------------------------------------
func TestBuildTieredTokenParams_Len_GPT(t *testing.T) {
usage := &dto.Usage{
PromptTokens: 10000,
CompletionTokens: 2000,
PromptTokensDetails: dto.InputTokenDetails{
CachedTokens: 3000,
TextTokens: 7000,
},
}
expr := `tier("base", p * 2.5 + c * 15 + cr * 0.25)`
usedVars := billingexpr.UsedVars(expr)
params := BuildTieredTokenParams(usage, false, usedVars)
// Non-Claude: Len = raw PromptTokens
if params.Len != 10000 {
t.Fatalf("Len = %f, want 10000 (raw PromptTokens)", params.Len)
}
// P should be reduced by cache
if params.P != 7000 {
t.Fatalf("P = %f, want 7000 (PromptTokens - CachedTokens)", params.P)
}
}
func TestBuildTieredTokenParams_Len_Claude(t *testing.T) {
usage := &dto.Usage{
PromptTokens: 5000,
CompletionTokens: 2000,
UsageSemantic: "anthropic",
PromptTokensDetails: dto.InputTokenDetails{
CachedTokens: 3000,
TextTokens: 5000,
},
ClaudeCacheCreation5mTokens: 1000,
ClaudeCacheCreation1hTokens: 500,
}
expr := `tier("base", p * 3 + c * 15 + cr * 0.3 + cc * 3.75 + cc1h * 6)`
usedVars := billingexpr.UsedVars(expr)
params := BuildTieredTokenParams(usage, true, usedVars)
// Claude: Len = PromptTokens + CachedTokens + CacheCreation5m + CacheCreation1h
wantLen := float64(5000 + 3000 + 1000 + 500)
if params.Len != wantLen {
t.Fatalf("Len = %f, want %f (text + cache read + cache creation)", params.Len, wantLen)
}
// Claude: P is not reduced (isClaudeUsageSemantic = true)
if params.P != 5000 {
t.Fatalf("P = %f, want 5000 (no subtraction for Claude)", params.P)
}
}
func TestBuildTieredTokenParams_Len_TierCondition(t *testing.T) {
// Test that len-based tier conditions work correctly when p is reduced by cache
usage := &dto.Usage{
PromptTokens: 300000,
CompletionTokens: 5000,
PromptTokensDetails: dto.InputTokenDetails{
CachedTokens: 250000,
TextTokens: 50000,
},
}
expr := `len <= 200000 ? tier("standard", p * 3 + c * 15 + cr * 0.3) : tier("long_context", p * 6 + c * 22.5 + cr * 0.6)`
usedVars := billingexpr.UsedVars(expr)
params := BuildTieredTokenParams(usage, false, usedVars)
// Len = 300000 (raw prompt), P = 50000 (300000 - 250000 cache)
if params.Len != 300000 {
t.Fatalf("Len = %f, want 300000", params.Len)
}
if params.P != 50000 {
t.Fatalf("P = %f, want 50000", params.P)
}
// Run expression: len=300000 > 200000, so long_context tier
cost, trace, err := billingexpr.RunExpr(expr, params)
if err != nil {
t.Fatal(err)
}
if trace.MatchedTier != "long_context" {
t.Fatalf("tier = %s, want long_context (len=300000 but p=50000)", trace.MatchedTier)
}
// long_context: 50000*6 + 5000*22.5 + 250000*0.6
wantCost := 50000.0*6 + 5000*22.5 + 250000*0.6
if math.Abs(cost-wantCost) > 1e-6 {
t.Fatalf("cost = %f, want %f", cost, wantCost)
}
}
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
// Stress test: 1000 concurrent goroutines, complex tiered expr vs ratio, // Stress test: 1000 concurrent goroutines, complex tiered expr vs ratio,
// random token counts, verify correctness and measure performance // random token counts, verify correctness and measure performance
+4 -4
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@@ -54,10 +54,10 @@ func SmokeTestExpr(exprStr string) error {
func smokeTestExpr(exprStr string) error { func smokeTestExpr(exprStr string) error {
vectors := []billingexpr.TokenParams{ vectors := []billingexpr.TokenParams{
{P: 0, C: 0}, {P: 0, C: 0, Len: 0},
{P: 1000, C: 1000}, {P: 1000, C: 1000, Len: 1000},
{P: 100000, C: 100000}, {P: 100000, C: 100000, Len: 100000},
{P: 1000000, C: 1000000}, {P: 1000000, C: 1000000, Len: 1000000},
} }
requests := []billingexpr.RequestInput{ requests := []billingexpr.RequestInput{
{}, {},
@@ -21,7 +21,7 @@ import React from 'react';
import { Avatar, Tag, Table, Typography } from '@douyinfe/semi-ui'; import { Avatar, Tag, Table, Typography } from '@douyinfe/semi-ui';
import { IconPriceTag } from '@douyinfe/semi-icons'; import { IconPriceTag } from '@douyinfe/semi-icons';
import { parseTiersFromExpr, getCurrencyConfig } from '../../../../../helpers'; import { parseTiersFromExpr, getCurrencyConfig } from '../../../../../helpers';
import { BILLING_VARS } from '../../../../../constants'; import { BILLING_PRICING_VARS } from '../../../../../constants';
import { import {
splitBillingExprAndRequestRules, splitBillingExprAndRequestRules,
tryParseRequestRuleExpr, tryParseRequestRuleExpr,
@@ -113,7 +113,7 @@ export default function DynamicPricingBreakdown({ billingExpr, t }) {
); );
} }
const priceFields = BILLING_VARS.map((v) => [v.field, v.shortLabel]); const priceFields = BILLING_PRICING_VARS.map((v) => [v.field, v.shortLabel]);
const tierColumns = [ const tierColumns = [
{ {
+12 -5
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@@ -13,6 +13,7 @@
export const BILLING_VARS = [ export const BILLING_VARS = [
{ key: 'p', field: 'inputPrice', tierField: 'input_unit_cost', label: '输入价格', shortLabel: '输入', side: 'input', isBase: true }, { key: 'p', field: 'inputPrice', tierField: 'input_unit_cost', label: '输入价格', shortLabel: '输入', side: 'input', isBase: true },
{ key: 'c', field: 'outputPrice', tierField: 'output_unit_cost', label: '补全价格', shortLabel: '补全', side: 'output', isBase: true }, { key: 'c', field: 'outputPrice', tierField: 'output_unit_cost', label: '补全价格', shortLabel: '补全', side: 'output', isBase: true },
{ key: 'len', field: null, tierField: null, label: '输入长度', shortLabel: '长度', side: 'condition', isConditionOnly: true },
{ key: 'cr', field: 'cacheReadPrice', tierField: 'cache_read_unit_cost', label: '缓存读取价格', shortLabel: '缓存读', side: 'input', group: 'cache' }, { key: 'cr', field: 'cacheReadPrice', tierField: 'cache_read_unit_cost', label: '缓存读取价格', shortLabel: '缓存读', side: 'input', group: 'cache' },
{ key: 'cc', field: 'cacheCreatePrice', tierField: 'cache_create_unit_cost', label: '缓存创建价格', shortLabel: '缓存创建', side: 'input', group: 'cache' }, { key: 'cc', field: 'cacheCreatePrice', tierField: 'cache_create_unit_cost', label: '缓存创建价格', shortLabel: '缓存创建', side: 'input', group: 'cache' },
{ key: 'cc1h', field: 'cacheCreate1hPrice', tierField: 'cache_create_1h_unit_cost', label: '1h缓存创建价格', shortLabel: '1h缓存创建', side: 'input', group: 'cache' }, { key: 'cc1h', field: 'cacheCreate1hPrice', tierField: 'cache_create_1h_unit_cost', label: '1h缓存创建价格', shortLabel: '1h缓存创建', side: 'input', group: 'cache' },
@@ -24,18 +25,20 @@ export const BILLING_VARS = [
export const BILLING_VAR_KEYS = BILLING_VARS.map((v) => v.key); export const BILLING_VAR_KEYS = BILLING_VARS.map((v) => v.key);
export const BILLING_EXTRA_VARS = BILLING_VARS.filter((v) => !v.isBase); export const BILLING_PRICING_VARS = BILLING_VARS.filter((v) => !v.isConditionOnly);
export const BILLING_EXTRA_VARS = BILLING_VARS.filter((v) => !v.isBase && !v.isConditionOnly);
export const BILLING_VAR_KEY_TO_FIELD = Object.fromEntries( export const BILLING_VAR_KEY_TO_FIELD = Object.fromEntries(
BILLING_VARS.map((v) => [v.key, v.field]), BILLING_PRICING_VARS.map((v) => [v.key, v.field]),
); );
export const BILLING_VAR_FIELD_TO_LABEL = Object.fromEntries( export const BILLING_VAR_FIELD_TO_LABEL = Object.fromEntries(
BILLING_VARS.map((v) => [v.field, v.label]), BILLING_PRICING_VARS.map((v) => [v.field, v.label]),
); );
export const BILLING_VAR_FIELD_TO_SHORT_LABEL = Object.fromEntries( export const BILLING_VAR_FIELD_TO_SHORT_LABEL = Object.fromEntries(
BILLING_VARS.map((v) => [v.field, v.shortLabel]), BILLING_PRICING_VARS.map((v) => [v.field, v.shortLabel]),
); );
export const BILLING_CACHE_VAR_MAP = BILLING_EXTRA_VARS.map((v) => ({ export const BILLING_CACHE_VAR_MAP = BILLING_EXTRA_VARS.map((v) => ({
@@ -44,6 +47,10 @@ export const BILLING_CACHE_VAR_MAP = BILLING_EXTRA_VARS.map((v) => ({
})); }));
export const BILLING_VAR_REGEX = new RegExp( export const BILLING_VAR_REGEX = new RegExp(
`\\b(${BILLING_VAR_KEYS.join('|')})\\s*\\*\\s*([\\d.eE+-]+)`, `\\b(${BILLING_PRICING_VARS.map((v) => v.key).join('|')})\\s*\\*\\s*([\\d.eE+-]+)`,
'g', 'g',
); );
export const BILLING_CONDITION_VARS = BILLING_VARS.filter(
(v) => v.isBase || v.isConditionOnly,
).map((v) => v.key);
+5 -5
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@@ -22,7 +22,7 @@ import { Modal, Tag, Typography, Avatar } from '@douyinfe/semi-ui';
import { copy, showSuccess } from './utils'; import { copy, showSuccess } from './utils';
import { MOBILE_BREAKPOINT } from '../hooks/common/useIsMobile'; import { MOBILE_BREAKPOINT } from '../hooks/common/useIsMobile';
import { import {
BILLING_VARS, BILLING_PRICING_VARS,
BILLING_VAR_KEY_TO_FIELD, BILLING_VAR_KEY_TO_FIELD,
BILLING_VAR_REGEX, BILLING_VAR_REGEX,
} from '../constants'; } from '../constants';
@@ -2246,7 +2246,7 @@ export function parseTiersFromExpr(exprStr) {
if (!exprStr) return []; if (!exprStr) return [];
try { try {
const { body } = stripExprVersion(exprStr); const { body } = stripExprVersion(exprStr);
const condGroup = `((?:(?:p|c)\\s*(?:<|<=|>|>=)\\s*[\\d.eE+]+)(?:\\s*&&\\s*(?:p|c)\\s*(?:<|<=|>|>=)\\s*[\\d.eE+]+)*)`; const condGroup = `((?:(?:p|c|len)\\s*(?:<|<=|>|>=)\\s*[\\d.eE+]+)(?:\\s*&&\\s*(?:p|c|len)\\s*(?:<|<=|>|>=)\\s*[\\d.eE+]+)*)`;
const tierRe = new RegExp(`(?:${condGroup}\\s*\\?\\s*)?tier\\("([^"]*)",\\s*([^)]+)\\)`, 'g'); const tierRe = new RegExp(`(?:${condGroup}\\s*\\?\\s*)?tier\\("([^"]*)",\\s*([^)]+)\\)`, 'g');
const tiers = []; const tiers = [];
let m; let m;
@@ -2255,7 +2255,7 @@ export function parseTiersFromExpr(exprStr) {
const conditions = []; const conditions = [];
if (condStr) { if (condStr) {
for (const cp of condStr.split(/\s*&&\s*/)) { for (const cp of condStr.split(/\s*&&\s*/)) {
const cm = cp.trim().match(/^(p|c)\s*(<|<=|>|>=)\s*([\d.eE+]+)$/); const cm = cp.trim().match(/^(p|c|len)\s*(<|<=|>|>=)\s*([\d.eE+]+)$/);
if (cm) conditions.push({ var: cm[1], op: cm[2], value: Number(cm[3]) }); if (cm) conditions.push({ var: cm[1], op: cm[2], value: Number(cm[3]) });
} }
} }
@@ -2293,7 +2293,7 @@ export function renderTieredModelPrice(opts) {
const { symbol, rate } = getCurrencyConfig(); const { symbol, rate } = getCurrencyConfig();
const gr = groupRatio || 1; const gr = groupRatio || 1;
const priceLines = BILLING_VARS.map((v) => [v.field, v.label]); const priceLines = BILLING_PRICING_VARS.map((v) => [v.field, v.label]);
const lines = [ const lines = [
buildBillingText('命中档位:{{tier}}', { tier: matchedTier || tier.label }), buildBillingText('命中档位:{{tier}}', { tier: matchedTier || tier.label }),
@@ -2334,7 +2334,7 @@ export function renderTieredModelPriceSimple(opts) {
]; ];
if (tier && isPriceDisplayMode(displayMode)) { if (tier && isPriceDisplayMode(displayMode)) {
const priceSegments = BILLING_VARS.map((v) => [v.field, v.shortLabel]); const priceSegments = BILLING_PRICING_VARS.map((v) => [v.field, v.shortLabel]);
for (const [field, label] of priceSegments) { for (const [field, label] of priceSegments) {
if (tier[field] > 0) { if (tier[field] > 0) {
segments.push({ segments.push({
+2 -2
View File
@@ -18,7 +18,7 @@ For commercial licensing, please contact support@quantumnous.com
*/ */
import { Toast, Pagination } from '@douyinfe/semi-ui'; import { Toast, Pagination } from '@douyinfe/semi-ui';
import { toastConstants, BILLING_VARS, BILLING_VAR_REGEX } from '../constants'; import { toastConstants, BILLING_PRICING_VARS, BILLING_VAR_REGEX } from '../constants';
import React from 'react'; import React from 'react';
import { toast } from 'react-toastify'; import { toast } from 'react-toastify';
import { import {
@@ -927,7 +927,7 @@ export const formatDynamicPriceSummary = (billingExpr, t, groupRatio = 1) => {
} }
const hasCoeffs = 'p' in varCoeffs || 'c' in varCoeffs; const hasCoeffs = 'p' in varCoeffs || 'c' in varCoeffs;
const varLabels = BILLING_VARS.map((v) => [v.key, v.label]); const varLabels = BILLING_PRICING_VARS.map((v) => [v.key, v.label]);
const hasTimeCondition = /\b(?:hour|minute|weekday|month|day)\(/.test(exprBody); const hasTimeCondition = /\b(?:hour|minute|weekday|month|day)\(/.test(exprBody);
const hasRequestCondition = /\b(?:param|header)\(/.test(exprBody); const hasRequestCondition = /\b(?:param|header)\(/.test(exprBody);
@@ -31,9 +31,10 @@ import {
TextArea, TextArea,
Typography, Typography,
} from '@douyinfe/semi-ui'; } from '@douyinfe/semi-ui';
import { IconDelete, IconPlus } from '@douyinfe/semi-icons'; import { IconCopy, IconDelete, IconPlus } from '@douyinfe/semi-icons';
import { renderQuota } from '../../../../helpers/render'; import { renderQuota } from '../../../../helpers/render';
import { BILLING_EXTRA_VARS, BILLING_CACHE_VAR_MAP } from '../../../../constants'; import { copy, showSuccess } from '../../../../helpers';
import { BILLING_EXTRA_VARS, BILLING_CACHE_VAR_MAP, BILLING_CONDITION_VARS } from '../../../../constants';
import { import {
createEmptyCondition, createEmptyCondition,
createEmptyTimeCondition, createEmptyTimeCondition,
@@ -70,6 +71,7 @@ function priceToUnitCost(price) {
const OPS = ['<', '<=', '>', '>=']; const OPS = ['<', '<=', '>', '>='];
const VAR_OPTIONS = [ const VAR_OPTIONS = [
{ value: 'len', label: 'len (长度)' },
{ value: 'p', label: 'p (输入)' }, { value: 'p', label: 'p (输入)' },
{ value: 'c', label: 'c (输出)' }, { value: 'c', label: 'c (输出)' },
]; ];
@@ -224,7 +226,7 @@ function tryParseVisualConfig(exprStr) {
} }
// Multi-tier: cond1 ? tier(body) : cond2 ? tier(body) : tier(body) // Multi-tier: cond1 ? tier(body) : cond2 ? tier(body) : tier(body)
const condGroup = `((?:(?:p|c)\\s*(?:<|<=|>|>=)\\s*[\\d.eE+]+)(?:\\s*&&\\s*(?:p|c)\\s*(?:<|<=|>|>=)\\s*[\\d.eE+]+)*)`; const condGroup = `((?:(?:p|c|len)\\s*(?:<|<=|>|>=)\\s*[\\d.eE+]+)(?:\\s*&&\\s*(?:p|c|len)\\s*(?:<|<=|>|>=)\\s*[\\d.eE+]+)*)`;
const tierRe = new RegExp( const tierRe = new RegExp(
`(?:${condGroup}\\s*\\?\\s*)?tier\\("([^"]*)",\\s*${bodyPat}\\)`, `(?:${condGroup}\\s*\\?\\s*)?tier\\("([^"]*)",\\s*${bodyPat}\\)`,
'g', 'g',
@@ -237,7 +239,7 @@ function tryParseVisualConfig(exprStr) {
if (condStr) { if (condStr) {
const condParts = condStr.split(/\s*&&\s*/); const condParts = condStr.split(/\s*&&\s*/);
for (const cp of condParts) { for (const cp of condParts) {
const cm = cp.trim().match(/^(p|c)\s*(<|<=|>|>=)\s*([\d.eE+]+)$/); const cm = cp.trim().match(/^(p|c|len)\s*(<|<=|>|>=)\s*([\d.eE+]+)$/);
if (cm) { if (cm) {
conditions.push({ var: cm[1], op: cm[2], value: Number(cm[3]) }); conditions.push({ var: cm[1], op: cm[2], value: Number(cm[3]) });
} }
@@ -283,7 +285,7 @@ function ConditionRow({ cond, onChange, onRemove, t }) {
}}> }}>
<Select <Select
size='small' size='small'
value={cond.var || 'p'} value={cond.var || 'len'}
onChange={(val) => onChange({ ...cond, var: val })} onChange={(val) => onChange({ ...cond, var: val })}
> >
{VAR_OPTIONS.map((v) => ( {VAR_OPTIONS.map((v) => (
@@ -500,7 +502,7 @@ function ExtendedPriceBlock({ tier, index, onUpdate, t }) {
function VisualTierCard({ tier, index, isLast, isOnly, onUpdate, onRemove, t }) { function VisualTierCard({ tier, index, isLast, isOnly, onUpdate, onRemove, t }) {
const conditions = tier.conditions || []; const conditions = tier.conditions || [];
const varLabel = { p: t('输入'), c: t('输出') }; const varLabel = { len: t('长度'), p: t('输入'), c: t('输出') };
const condSummary = useMemo(() => { const condSummary = useMemo(() => {
if (conditions.length === 0) return t('无条件(兜底档)'); if (conditions.length === 0) return t('无条件(兜底档)');
return conditions return conditions
@@ -525,7 +527,7 @@ function VisualTierCard({ tier, index, isLast, isOnly, onUpdate, onRemove, t })
const addCondition = () => { const addCondition = () => {
if (conditions.length >= 2) return; if (conditions.length >= 2) return;
const usedVars = conditions.map((c) => c.var); const usedVars = conditions.map((c) => c.var);
const nextVar = usedVars.includes('p') ? 'c' : 'p'; const nextVar = usedVars.includes('len') ? 'c' : 'len';
onUpdate(index, 'conditions', [ onUpdate(index, 'conditions', [
...conditions, ...conditions,
{ var: nextVar, op: '<', value: 200000 }, { var: nextVar, op: '<', value: 200000 },
@@ -694,7 +696,7 @@ function VisualEditor({ visualConfig, onChange, t }) {
) { ) {
newTiers[newTiers.length - 1] = { newTiers[newTiers.length - 1] = {
...newTiers[newTiers.length - 1], ...newTiers[newTiers.length - 1],
conditions: [{ var: 'p', op: '<', value: 200000 }], conditions: [{ var: 'len', op: '<', value: 200000 }],
}; };
} }
newTiers.push({ newTiers.push({
@@ -723,7 +725,7 @@ function VisualEditor({ visualConfig, onChange, t }) {
<div> <div>
<Banner <Banner
type='info' type='info'
description={t('每个档位可设置 0~2 个条件(对 p 和 c),最后一档为兜底档无需条件。')} description={t('每个档位可设置 0~2 个条件(对 len、p 和 c),最后一档为兜底档无需条件。len 为输入上下文总长度(含缓存),推荐用于阶梯条件。')}
style={{ marginBottom: 12 }} style={{ marginBottom: 12 }}
/> />
@@ -762,16 +764,16 @@ const PRESET_GROUPS = [
presets: [ presets: [
{ key: 'flat', label: 'Flat', expr: 'tier("base", p * 2 + c * 4)' }, { key: 'flat', label: 'Flat', expr: 'tier("base", p * 2 + c * 4)' },
{ key: 'claude-opus', label: 'Claude Opus 4.6', expr: 'tier("base", p * 5 + c * 25 + cr * 0.5 + cc * 6.25 + cc1h * 10)' }, { key: 'claude-opus', label: 'Claude Opus 4.6', expr: 'tier("base", p * 5 + c * 25 + cr * 0.5 + cc * 6.25 + cc1h * 10)' },
{ key: 'gpt-5.4', label: 'GPT-5.4', expr: 'p <= 272000 ? tier("standard", p * 2.5 + c * 15 + cr * 0.25) : tier("long_context", p * 5 + c * 22.5 + cr * 0.5)' }, { key: 'gpt-5.4', label: 'GPT-5.4', expr: 'len <= 272000 ? tier("standard", p * 2.5 + c * 15 + cr * 0.25) : tier("long_context", p * 5 + c * 22.5 + cr * 0.5)' },
], ],
}, },
{ {
group: '阶梯计费', group: '阶梯计费',
presets: [ presets: [
{ key: 'claude-sonnet', label: 'Claude Sonnet 4.5', expr: 'p <= 200000 ? tier("standard", p * 3 + c * 15 + cr * 0.3 + cc * 3.75 + cc1h * 6) : tier("long_context", p * 6 + c * 22.5 + cr * 0.6 + cc * 7.5 + cc1h * 12)' }, { key: 'claude-sonnet', label: 'Claude Sonnet 4.5', expr: 'len <= 200000 ? tier("standard", p * 3 + c * 15 + cr * 0.3 + cc * 3.75 + cc1h * 6) : tier("long_context", p * 6 + c * 22.5 + cr * 0.6 + cc * 7.5 + cc1h * 12)' },
{ key: 'qwen3-max', label: 'Qwen3 Max', expr: 'p <= 32000 ? tier("short", p * 1.2 + c * 6 + cr * 0.24 + cc * 1.5) : p <= 128000 ? tier("mid", p * 2.4 + c * 12 + cr * 0.48 + cc * 3) : tier("long", p * 3 + c * 15 + cr * 0.6 + cc * 3.75)' }, { key: 'qwen3-max', label: 'Qwen3 Max', expr: 'len <= 32000 ? tier("short", p * 1.2 + c * 6 + cr * 0.24 + cc * 1.5) : len <= 128000 ? tier("mid", p * 2.4 + c * 12 + cr * 0.48 + cc * 3) : tier("long", p * 3 + c * 15 + cr * 0.6 + cc * 3.75)' },
{ key: 'glm-4.5-air', label: 'GLM-4.5 Air', expr: 'p < 32000 && c < 200 ? tier("short_output", p * 0.8 + c * 2 + cr * 0.16) : p < 32000 && c >= 200 ? tier("long_output", p * 0.8 + c * 6 + cr * 0.16) : tier("mid_context", p * 1.2 + c * 8 + cr * 0.24)' }, { key: 'glm-4.5-air', label: 'GLM-4.5 Air', expr: 'len < 32000 && c < 200 ? tier("short_output", p * 0.8 + c * 2 + cr * 0.16) : len < 32000 && c >= 200 ? tier("long_output", p * 0.8 + c * 6 + cr * 0.16) : tier("mid_context", p * 1.2 + c * 8 + cr * 0.24)' },
{ key: 'doubao-seed-1.8', label: 'Doubao Seed 1.8', expr: 'p <= 32000 && c <= 200 ? tier("discount", p * 0.8 + c * 2 + cr * 0.16 + cc * 0.17) : p <= 32000 ? tier("short", p * 0.8 + c * 8 + cr * 0.16 + cc * 0.17) : p <= 128000 ? tier("mid", p * 1.2 + c * 16 + cr * 0.16 + cc * 0.17) : tier("long", p * 2.4 + c * 24 + cr * 0.16 + cc * 0.17)' }, { key: 'doubao-seed-1.8', label: 'Doubao Seed 1.8', expr: 'len <= 32000 && c <= 200 ? tier("discount", p * 0.8 + c * 2 + cr * 0.16 + cc * 0.17) : len <= 32000 ? tier("short", p * 0.8 + c * 8 + cr * 0.16 + cc * 0.17) : len <= 128000 ? tier("mid", p * 1.2 + c * 16 + cr * 0.16 + cc * 0.17) : tier("long", p * 2.4 + c * 24 + cr * 0.16 + cc * 0.17)' },
], ],
}, },
{ {
@@ -793,7 +795,7 @@ const PRESET_GROUPS = [
}, },
{ {
key: 'gpt-5.4-tiers', label: 'GPT-5.4 Priority/Flex', key: 'gpt-5.4-tiers', label: 'GPT-5.4 Priority/Flex',
expr: 'p <= 272000 ? tier("standard", p * 2.5 + c * 15 + cr * 0.25) : tier("long_context", p * 5 + c * 22.5 + cr * 0.5)', expr: 'len <= 272000 ? tier("standard", p * 2.5 + c * 15 + cr * 0.25) : tier("long_context", p * 5 + c * 22.5 + cr * 0.5)',
requestRules: [ requestRules: [
{ conditions: [{ source: SOURCE_PARAM, path: 'service_tier', mode: MATCH_EQ, value: 'priority' }], multiplier: '2' }, { conditions: [{ source: SOURCE_PARAM, path: 'service_tier', mode: MATCH_EQ, value: 'priority' }], multiplier: '2' },
{ conditions: [{ source: SOURCE_PARAM, path: 'service_tier', mode: MATCH_EQ, value: 'flex' }], multiplier: '0.5' }, { conditions: [{ source: SOURCE_PARAM, path: 'service_tier', mode: MATCH_EQ, value: 'flex' }], multiplier: '0.5' },
@@ -880,7 +882,8 @@ function RawExprEditor({ exprString, onChange, t }) {
<div> <div>
<div> <div>
{t('变量')}: <code>p</code> ({t('输入 Token')}), <code>c</code> ( {t('变量')}: <code>p</code> ({t('输入 Token')}), <code>c</code> (
{t('输出 Token')}), <code>cr</code> ({t('缓存读取')}),{' '} {t('输出 Token')}), <code>len</code> ({t('输入长度')}),{' '}
<code>cr</code> ({t('缓存读取')}),{' '}
<code>cc</code> ({t('缓存创建')}),{' '} <code>cc</code> ({t('缓存创建')}),{' '}
<code>cc1h</code> ({t('缓存创建-1小时')}) <code>cc1h</code> ({t('缓存创建-1小时')})
</div> </div>
@@ -968,7 +971,11 @@ function evalExprLocally(exprStr, p, c, extraTokenValues) {
matchedTier = name; matchedTier = name;
return value; return value;
}; };
const env = { p, c, tier: tierFn, max: Math.max, min: Math.min, abs: Math.abs, ceil: Math.ceil, floor: Math.floor }; const cacheReadTokens = extraTokenValues.cacheReadTokens || 0;
const cacheCreateTokens = extraTokenValues.cacheCreateTokens || 0;
const cacheCreate1hTokens = extraTokenValues.cacheCreate1hTokens || 0;
const len = p + cacheReadTokens + cacheCreateTokens + cacheCreate1hTokens;
const env = { p, c, len, tier: tierFn, max: Math.max, min: Math.min, abs: Math.abs, ceil: Math.ceil, floor: Math.floor };
for (const field of EXTRA_ESTIMATOR_FIELDS) { for (const field of EXTRA_ESTIMATOR_FIELDS) {
env[field.var] = extraTokenValues[field.stateKey] || 0; env[field.var] = extraTokenValues[field.stateKey] || 0;
} }
@@ -1220,6 +1227,146 @@ function RuleGroupCard({ group, index, onChange, onRemove, t }) {
); );
} }
// ---------------------------------------------------------------------------
// LLM prompt helper copyable prompt for LLM-assisted expression design
// ---------------------------------------------------------------------------
const LLM_PROMPT_TEMPLATE = `你是一个 AI API 计费表达式设计助手。用户需要你帮忙设计一个计费表达式(billing expression),用于 AI API 网关的模型计费。
## 表达式语言
表达式基于 expr-lang/expr支持标准算术运算和三元运算符
### Token 变量
输入侧
- p 输入 token 计价用系统会自动排除表达式中单独计价的子类别如用了 cr缓存 token 就从 p 中扣除
- len 输入上下文总长度条件判断用不受自动排除影响始终反映完整输入长度用于阶梯条件判断
- cr 缓存命中读取token
- cc 缓存创建 token 5分钟 TTL
- cc1h 缓存创建 token 1小时 TTLClaude 专用
- img 图片输入 token
- ai 音频输入 token
输出侧
- c 输出 token 同样会自动排除单独计价的子类别
- img_o 图片输出 token
- ao 音频输出 token
### p/c 自动排除机制
p c 是兜底变量代表所有没有被表达式单独定价的 token如果表达式使用了某个子类别变量 cr对应 token 就从 p 中扣除避免重复计费没用到的子类别 token 则留在 p/c 中按基础价格计费
重要len 不受自动排除影响阶梯条件应使用 len 而非 p以避免缓存命中导致 p 降低而误判档位
### 内置函数
- tier(name, value) 标记计费档位名称必须包裹费用表达式
- max(a, b)min(a, b) 取大/小值
- ceil(x)floor(x)abs(x) 向上取整向下取整绝对值
- header(name) 读取请求头
- param(path) 读取请求体 JSON 路径gjson 语法
- has(source, substr) 子字符串检查
- hour(tz)minute(tz)weekday(tz)month(tz)day(tz) 时间函数tz 为时区如 "Asia/Shanghai"
### 价格系数
表达式中的数字系数是 $/1M tokens 的价格例如 p * 2.5 表示输入 $2.50/1M tokens
## 表达式示例
简单定价
tier("base", p * 2.5 + c * 15)
带缓存的定价
tier("base", p * 2.5 + c * 15 + cr * 0.25)
多档阶梯 len 做条件
len <= 200000
? tier("standard", p * 3 + c * 15 + cr * 0.3 + cc * 3.75 + cc1h * 6)
: tier("long_context", p * 6 + c * 22.5 + cr * 0.6 + cc * 7.5 + cc1h * 12)
图片模型
tier("base", p * 2 + c * 8 + img * 2.5)
多模态含音频
tier("base", p * 0.43 + c * 3.06 + img * 0.78 + ai * 3.81 + ao * 15.11)
三档阶梯示例
len <= 128000
? tier("standard", p * 1.1 + c * 4.4)
: (len <= 1000000
? tier("medium", p * 2.2 + c * 8.8)
: tier("long", p * 4.4 + c * 17.6))
## 规则
1. 每个叶子分支必须用 tier("名称", 费用表达式) 包裹
2. tier 名称用英文 "base""standard""long_context"
3. 阶梯条件用 len不要用 p支持 <<=>>=
4. 多档用嵌套三元运算符条件1 ? tier(...) : (条件2 ? tier(...) : tier(...))
5. 价格系数直接写供应商官方 $/1M tokens 价格
6. 不需要缓存/图片/音频单独定价时可以不写对应变量它们的 token 会自动包含在 p/c
请根据用户提供的模型信息和定价需求生成计费表达式`;
function LlmPromptHelper({ t, model }) {
const [open, setOpen] = useState(false);
const modelName = model?.name || '';
const prompt = useMemo(() => {
if (modelName) {
return LLM_PROMPT_TEMPLATE + `\n\n当前模型:${modelName}`;
}
return LLM_PROMPT_TEMPLATE;
}, [modelName]);
const handleCopy = useCallback(async () => {
const ok = await copy(prompt);
if (ok) showSuccess(t('已复制到剪贴板'));
}, [prompt, t]);
return (
<div style={{ marginBottom: 12 }}>
<Button
theme='borderless'
size='small'
icon={<IconCopy />}
onClick={() => setOpen(!open)}
style={{ color: 'var(--semi-color-tertiary)' }}
>
{t('LLM 辅助设计提示词')}
</Button>
<Collapsible isOpen={open}>
<Card
bodyStyle={{ padding: 12 }}
style={{ marginTop: 8, background: 'var(--semi-color-fill-0)' }}
>
<div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center', marginBottom: 8 }}>
<Text size='small' type='secondary'>
{t('复制以下提示词发送给 LLM(如 ChatGPT / Claude),让它帮你设计计费表达式')}
</Text>
<Button
icon={<IconCopy />}
size='small'
theme='light'
onClick={handleCopy}
>
{t('复制提示词')}
</Button>
</div>
<TextArea
value={prompt}
readonly
autosize={{ minRows: 6, maxRows: 20 }}
style={{ fontFamily: 'monospace', fontSize: 12 }}
/>
</Card>
</Collapsible>
</div>
);
}
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
// Main component // Main component
// --------------------------------------------------------------------------- // ---------------------------------------------------------------------------
@@ -1543,6 +1690,8 @@ export default function TieredPricingEditor({ model, onExprChange, requestRuleEx
</div> </div>
</Card> </Card>
<LlmPromptHelper t={t} model={model} />
</div> </div>
); );
} }