feat: 修复 Codex 缓存 token 计费并优化代码结构

- 修复 Codex API 缓存 token 重复计费问题 (input_tokens 包含 cached_tokens)
- 提取共享代码到 src/providers/shared/usage-utils.ts,消除重复
- 前端定价页面增加缓存倍率配置列
- 修复 var 为 const,favicon 改为云图标

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
dreamhunter2333andClaude Opus 4.5 committed 2026-01-30 21:06:44 +08:00
1 parent 6a648f3fa7
commit bdb4825cdc
8 files changed
+150 -188

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+1 -1
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@@ -2,7 +2,7 @@
<html lang="zh-CN">
<head>
<meta charset="UTF-8" />
<link rel="icon" type="image/svg+xml" href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>🤖</text></svg>" />
<link rel="icon" type="image/svg+xml" href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>☁️</text></svg>" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>Awsl One API - 管理控制台</title>
</head>
+20 -7
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@@ -27,7 +27,7 @@ export function Pricing() {
const [editMode, setEditMode] = useState<EditMode>('table')
const [jsonValue, setJsonValue] = useState('')
const [pricingRows, setPricingRows] = useState<
Array<{ model: string; input: number; output: number }>
Array<{ model: string; input: number; output: number; cache: number }>
>([])
const [searchQuery, setSearchQuery] = useState('')
@@ -48,6 +48,7 @@ export function Pricing() {
model,
input: pricing.input,
output: pricing.output,
cache: pricing.cache || 0,
}))
setPricingRows(rows)
setJsonValue(JSON.stringify(data, null, 2))
@@ -82,6 +83,7 @@ export function Pricing() {
config[row.model] = {
input: row.input || 0,
output: row.output || 0,
cache: row.cache || 0,
}
}
})
@@ -105,6 +107,7 @@ export function Pricing() {
config[row.model] = {
input: row.input || 0,
output: row.output || 0,
cache: row.cache || 0,
}
}
})
@@ -117,6 +120,7 @@ export function Pricing() {
model,
input: (pricing as { input: number }).input || 0,
output: (pricing as { output: number }).output || 0,
cache: (pricing as { cache?: number }).cache || 0,
}))
setPricingRows(rows)
setEditMode('table')
@@ -127,14 +131,14 @@ export function Pricing() {
}
const addRow = () => {
setPricingRows([...pricingRows, { model: '', input: 0, output: 0 }])
setPricingRows([...pricingRows, { model: '', input: 0, output: 0, cache: 0 }])
}
const removeRow = (index: number) => {
setPricingRows(pricingRows.filter((_, i) => i !== index))
}
const updateRow = (index: number, field: 'model' | 'input' | 'output', value: string | number) => {
const updateRow = (index: number, field: 'model' | 'input' | 'output' | 'cache', value: string | number) => {
const newRows = [...pricingRows]
;(newRows[index] as any)[field] = value
setPricingRows(newRows)
@@ -211,17 +215,18 @@ export function Pricing() {
{/* Table */}
<div className="rounded-xl border bg-card overflow-hidden">
{/* Header */}
<div className="grid gap-2 px-4 py-2.5 border-b bg-muted/30" style={{ gridTemplateColumns: '2fr 1fr 1fr 40px' }}>
<div className="grid gap-2 px-4 py-2.5 border-b bg-muted/30" style={{ gridTemplateColumns: '2fr 1fr 1fr 1fr 40px' }}>
<span className="text-xs font-medium text-muted-foreground">模型名称</span>
<span className="text-xs font-medium text-muted-foreground">输入倍率</span>
<span className="text-xs font-medium text-muted-foreground">输出倍率</span>
<span className="text-xs font-medium text-muted-foreground">缓存倍率</span>
<span />
</div>
{/* Rows */}
<div className="divide-y">
{filteredRows.map((row) => (
<div key={row._i} className="grid gap-2 px-4 py-2 items-center hover:bg-muted/20 transition-colors" style={{ gridTemplateColumns: '2fr 1fr 1fr 40px' }}>
<div key={row._i} className="grid gap-2 px-4 py-2 items-center hover:bg-muted/20 transition-colors" style={{ gridTemplateColumns: '2fr 1fr 1fr 1fr 40px' }}>
<Input
value={row.model}
onChange={(e) => updateRow(row._i, 'model', e.target.value)}
@@ -244,6 +249,14 @@ export function Pricing() {
min="0"
className="font-mono text-sm h-8"
/>
<Input
type="number"
value={row.cache}
onChange={(e) => updateRow(row._i, 'cache', parseFloat(e.target.value) || 0)}
step="0.001"
min="0"
className="font-mono text-sm h-8"
/>
<Button
type="button"
variant="ghost"
@@ -284,10 +297,10 @@ export function Pricing() {
onChange={(e) => setJsonValue(e.target.value)}
rows={20}
className="font-mono text-sm"
placeholder='{"gpt-4": {"input": 30, "output": 60}, ...}'
placeholder='{"gpt-4": {"input": 30, "output": 60, "cache": 3}, ...}'
/>
<p className="text-xs text-muted-foreground">
格式:模型名称 → {"{"} input: 输入倍率, output: 输出倍率 {"}"}
格式:模型名称 → {"{"} input: 输入倍率, output: 输出倍率, cache: 缓存倍率 {"}"}
</p>
</div>
</div>
+1
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@@ -28,6 +28,7 @@ export interface TokenConfig {
export interface PricingModel {
input: number
output: number
cache?: number
}
export type PricingConfig = Record<string, PricingModel>
+11 -6
View File
@@ -31,23 +31,28 @@ export const TokenUtils = {
async processUsage(c: Context<HonoCustomType>, apiKey: string, model: string, targetChannelKey: string, targetChannelConfig: ChannelConfig, usage: Usage): Promise<void> {
console.log("Usage data:", usage);
// Get pricing and calculate cost
const pricing = await this.getPricing(c, model, targetChannelConfig);
const hasTokens = usage.prompt_tokens != null && usage.completion_tokens != null;
if (pricing && hasTokens) {
const inputCost = usage.prompt_tokens! * pricing.input;
const outputCost = usage.completion_tokens! * pricing.output;
const totalCost = inputCost + outputCost;
// Update token usage and log data
let cacheCost = 0;
if (usage.cached_tokens && usage.cached_tokens > 0 && pricing.cache) {
cacheCost = usage.cached_tokens * pricing.cache;
}
const totalCost = inputCost + outputCost + cacheCost;
await this.updateUsage(c, apiKey, totalCost);
// 长度不够直接显示 *
var maskedApiKey = apiKey.length < 3 ? '*'.repeat(apiKey.length) : (
const maskedApiKey = apiKey.length < 3 ? '*'.repeat(apiKey.length) : (
apiKey.slice(0, apiKey.length / 3)
+ '*'.repeat(apiKey.length / 3)
+ apiKey.slice((2 * apiKey.length) / 3)
);
console.log(`Model: ${model}, Channel: ${targetChannelKey}, apiKey: ${maskedApiKey}, Cost: ${totalCost}`);
console.log(`Model: ${model}, Channel: ${targetChannelKey}, apiKey: ${maskedApiKey}, Cost: ${totalCost} (input: ${inputCost}, cache: ${cacheCost}, output: ${outputCost})`);
} else {
console.warn(`No pricing found for model: ${model} in channel: ${targetChannelKey}`);
}
+6 -87
View File
@@ -1,28 +1,10 @@
import { Context } from "hono"
type OpenAIResponsesUsage = {
input_tokens?: number;
output_tokens?: number;
total_tokens?: number;
prompt_tokens?: number;
completion_tokens?: number;
}
type OpenAIResponsesResponse = {
usage?: OpenAIResponsesUsage;
input_tokens?: number;
output_tokens?: number;
total_tokens?: number;
prompt_tokens?: number;
completion_tokens?: number;
}
type OpenAIResponsesStreamEvent = {
type?: string;
response?: OpenAIResponsesResponse;
delta?: string;
text?: string;
}
import {
OpenAIResponsesResponse,
OpenAIResponsesStreamEvent,
extractUsageFromResponse,
estimateUsageFromBodies,
} from "./shared/usage-utils"
const buildProxyRequest = (
request: Request,
@@ -52,69 +34,6 @@ const buildProxyRequest = (
})
}
const normalizeUsage = (raw?: OpenAIResponsesUsage): Usage | null => {
if (!raw) return null
const promptTokens = raw.prompt_tokens ?? raw.input_tokens
const completionTokens = raw.completion_tokens ?? raw.output_tokens
const totalTokens = raw.total_tokens ?? (
(promptTokens ?? 0) + (completionTokens ?? 0)
)
if (promptTokens == null && completionTokens == null && totalTokens == null) {
return null
}
return {
prompt_tokens: promptTokens,
completion_tokens: completionTokens,
total_tokens: totalTokens,
}
}
const extractUsageFromResponse = (res?: OpenAIResponsesResponse): Usage | null => {
if (!res) return null
return normalizeUsage(res.usage || res)
}
const estimateTokensFromText = (text: string): number => {
if (!text) return 0
const bytes = new TextEncoder().encode(text).length
return Math.ceil(bytes / 4)
}
const estimateUsageFromBodies = (
requestBody: any,
responseBody?: any,
streamedOutputText?: string
): Usage | null => {
const promptText = requestBody ? JSON.stringify(requestBody) : ""
const completionText = streamedOutputText
? streamedOutputText
: (responseBody ? JSON.stringify(responseBody) : "")
const promptTokens = estimateTokensFromText(promptText)
const completionTokens = estimateTokensFromText(completionText)
if (!promptTokens && !completionTokens) return null
return {
prompt_tokens: promptTokens,
completion_tokens: completionTokens,
total_tokens: promptTokens + completionTokens,
}
}
const checkoutUsageData = async (
saveUsage: (usage: Usage) => Promise<void>,
response: Response | OpenAIResponsesResponse
): Promise<void> => {
try {
const res = response instanceof Response
? await response.clone().json<OpenAIResponsesResponse>()
: response
const usage = extractUsageFromResponse(res)
if (!usage) return
await saveUsage(usage)
} catch (error) {
console.error("Error logging usage data:", error)
}
}
const processStreamData = async (
lines: string[],
usageSaved: { value: boolean },
+6 -87
View File
@@ -1,28 +1,10 @@
import { Context } from "hono"
type OpenAIResponsesUsage = {
input_tokens?: number;
output_tokens?: number;
total_tokens?: number;
prompt_tokens?: number;
completion_tokens?: number;
}
type OpenAIResponsesResponse = {
usage?: OpenAIResponsesUsage;
input_tokens?: number;
output_tokens?: number;
total_tokens?: number;
prompt_tokens?: number;
completion_tokens?: number;
}
type OpenAIResponsesStreamEvent = {
type?: string;
response?: OpenAIResponsesResponse;
delta?: string;
text?: string;
}
import {
OpenAIResponsesResponse,
OpenAIResponsesStreamEvent,
extractUsageFromResponse,
estimateUsageFromBodies,
} from "./shared/usage-utils"
const buildProxyRequest = (
request: Request,
@@ -44,69 +26,6 @@ const buildProxyRequest = (
})
}
const normalizeUsage = (raw?: OpenAIResponsesUsage): Usage | null => {
if (!raw) return null
const promptTokens = raw.prompt_tokens ?? raw.input_tokens
const completionTokens = raw.completion_tokens ?? raw.output_tokens
const totalTokens = raw.total_tokens ?? (
(promptTokens ?? 0) + (completionTokens ?? 0)
)
if (promptTokens == null && completionTokens == null && totalTokens == null) {
return null
}
return {
prompt_tokens: promptTokens,
completion_tokens: completionTokens,
total_tokens: totalTokens,
}
}
const extractUsageFromResponse = (res?: OpenAIResponsesResponse): Usage | null => {
if (!res) return null
return normalizeUsage(res.usage || res)
}
const estimateTokensFromText = (text: string): number => {
if (!text) return 0
const bytes = new TextEncoder().encode(text).length
return Math.ceil(bytes / 4)
}
const estimateUsageFromBodies = (
requestBody: any,
responseBody?: any,
streamedOutputText?: string
): Usage | null => {
const promptText = requestBody ? JSON.stringify(requestBody) : ""
const completionText = streamedOutputText
? streamedOutputText
: (responseBody ? JSON.stringify(responseBody) : "")
const promptTokens = estimateTokensFromText(promptText)
const completionTokens = estimateTokensFromText(completionText)
if (!promptTokens && !completionTokens) return null
return {
prompt_tokens: promptTokens,
completion_tokens: completionTokens,
total_tokens: promptTokens + completionTokens,
}
}
const checkoutUsageData = async (
saveUsage: (usage: Usage) => Promise<void>,
response: Response | OpenAIResponsesResponse
): Promise<void> => {
try {
const res = response instanceof Response
? await response.clone().json<OpenAIResponsesResponse>()
: response
const usage = extractUsageFromResponse(res)
if (!usage) return
await saveUsage(usage)
} catch (error) {
console.error("Error logging usage data:", error)
}
}
const processStreamData = async (
lines: string[],
usageSaved: { value: boolean },
+103
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@@ -0,0 +1,103 @@
export type InputTokensDetails = {
cached_tokens?: number;
}
export type OpenAIResponsesUsage = {
input_tokens?: number;
output_tokens?: number;
total_tokens?: number;
prompt_tokens?: number;
completion_tokens?: number;
input_tokens_details?: InputTokensDetails;
prompt_tokens_details?: InputTokensDetails;
}
export type OpenAIResponsesResponse = {
usage?: OpenAIResponsesUsage;
input_tokens?: number;
output_tokens?: number;
total_tokens?: number;
prompt_tokens?: number;
completion_tokens?: number;
input_tokens_details?: InputTokensDetails;
prompt_tokens_details?: InputTokensDetails;
}
export type OpenAIResponsesStreamEvent = {
type?: string;
response?: OpenAIResponsesResponse;
delta?: string;
text?: string;
}
export const normalizeUsage = (raw?: OpenAIResponsesUsage): Usage | null => {
if (!raw) return null
const cachedTokens =
raw.input_tokens_details?.cached_tokens ??
raw.prompt_tokens_details?.cached_tokens ??
0
const rawInputTokens = raw.prompt_tokens ?? raw.input_tokens ?? 0
const actualInputTokens = cachedTokens > 0
? Math.max(0, rawInputTokens - cachedTokens)
: rawInputTokens
const completionTokens = raw.completion_tokens ?? raw.output_tokens
const totalTokens = raw.total_tokens ?? (
(actualInputTokens ?? 0) + (cachedTokens ?? 0) + (completionTokens ?? 0)
)
if (actualInputTokens == null && completionTokens == null && totalTokens == null) {
return null
}
return {
prompt_tokens: actualInputTokens,
completion_tokens: completionTokens,
total_tokens: totalTokens,
cached_tokens: cachedTokens > 0 ? cachedTokens : undefined,
}
}
export const extractUsageFromResponse = (res?: OpenAIResponsesResponse): Usage | null => {
if (!res) return null
const usageData: OpenAIResponsesUsage = {
input_tokens: res.usage?.input_tokens ?? res.input_tokens,
output_tokens: res.usage?.output_tokens ?? res.output_tokens,
total_tokens: res.usage?.total_tokens ?? res.total_tokens,
prompt_tokens: res.usage?.prompt_tokens ?? res.prompt_tokens,
completion_tokens: res.usage?.completion_tokens ?? res.completion_tokens,
input_tokens_details: res.usage?.input_tokens_details ?? res.input_tokens_details,
prompt_tokens_details: res.usage?.prompt_tokens_details ?? res.prompt_tokens_details,
}
return normalizeUsage(usageData)
}
export const estimateTokensFromText = (text: string): number => {
if (!text) return 0
const bytes = new TextEncoder().encode(text).length
return Math.ceil(bytes / 4)
}
export const estimateUsageFromBodies = (
requestBody: any,
responseBody?: any,
streamedOutputText?: string
): Usage | null => {
const promptText = requestBody ? JSON.stringify(requestBody) : ""
const completionText = streamedOutputText
? streamedOutputText
: (responseBody ? JSON.stringify(responseBody) : "")
const promptTokens = estimateTokensFromText(promptText)
const completionTokens = estimateTokensFromText(completionText)
if (!promptTokens && !completionTokens) return null
return {
prompt_tokens: promptTokens,
completion_tokens: completionTokens,
total_tokens: promptTokens + completionTokens,
}
}
Vendored
+2
View File
@@ -63,6 +63,7 @@ type Usage = {
prompt_tokens?: number,
completion_tokens?: number,
total_tokens?: number,
cached_tokens?: number,
}
type AwslKeyPayload = {
@@ -79,6 +80,7 @@ type CommonResponse = {
type ModelPricing = {
input: number;
output: number;
cache?: number;
}
type ApiTokenData = {