Files
CC-Switch/src/components/usage/UsageTrendChart.tsx
T
Dex Miller 5376ea042b Feat/usage improvements (#508)
* i18n: update cache terminology across all languages

- Change 'Cache Read' to 'Cache Hit' in all languages
- Change 'Cache Write' to 'Cache Creation' in all languages
- Update zh: 缓存读取 → 缓存命中, 缓存写入 → 缓存创建
- Update en: Cache Read → Cache Hit, Cache Write → Cache Creation
- Update ja: キャッシュ読取 → キャッシュヒット, キャッシュ書込 → キャッシュ作成

Affected keys: cacheReadTokens, cacheCreationTokens, cacheReadCost,
cacheWriteCost, cacheRead, cacheWrite

* feat(usage): add cache metrics to trend chart

- Add cache creation tokens visualization (orange line)
- Add cache hit tokens visualization (purple line)
- Add gradient definitions for new cache metrics
- Include cache data in hourly aggregation
- Display cache metrics alongside input/output tokens

This provides better visibility into cache usage patterns over time.

* fix(usage): fix timezone handling in datetime picker

- Add timestampToLocalDatetime() to convert Unix timestamp to local datetime
- Add localDatetimeToTimestamp() with validation for incomplete input
- Fix issue where typing hours/minutes would jump to previous day
- Validate datetime format completeness before conversion
- Use local timezone instead of UTC for datetime-local input

This resolves the issue where users couldn't fine-tune time selection
and the input would jump unexpectedly when editing hours or minutes.

* feat(usage): add auto-refresh for usage statistics

- Add 30-second auto-refresh interval for all usage queries
- Disable background refresh to save resources
- Apply to: summary, trends, provider stats, model stats, request logs
- Queries automatically update when tab is active
- Pause refresh when user switches to another tab

This keeps usage data fresh without manual refresh.

* fix(proxy): improve usage logging and cache token parsing

- Log requests even when usage parsing fails (with default values)
- Add detailed debug logging for usage metrics
- Support cache_read_input_tokens field in Codex responses
- Fallback to input_tokens_details.cached_tokens if needed
- Add test case for cached_tokens in input_tokens_details
- Ensure all requests are tracked in database for analytics

This fixes missing request logs when API responses lack usage data
and improves cache token detection across different response formats.

* style(rust): use inline format args in format! macros

- Replace format!("...", var) with format!("...{var}")
- Update universal provider ID formatting
- Update error message formatting
- Update config.toml generation in Codex provider

Fixes clippy::uninlined_format_args warnings.

* feat(proxy): enhance provider router logging

- Add debug logs for failover queue provider count
- Log circuit breaker state for each provider check
- Add logs for missing current provider scenarios
- Log when no current provider is configured
- Use inline format args for better readability

This improves debugging of provider selection and failover behavior.

* feat(database): update model pricing data

- Update Claude models to full version format (e.g. claude-opus-4-5-20251101)
- Add GPT-5.2 series model pricing (10 models)
- Add GPT-5.1 series model pricing (10 models)
- Add GPT-5 series model pricing (12 models)
- Add Gemini 3 series model pricing (2 models)
- Update Gemini 2.5 series model ID format (use dot separator)
- Unify display names by removing thinking level suffixes

* fix(usage): correct Gemini output token calculation

Fix Gemini API output token parsing to use totalTokenCount - promptTokenCount
instead of candidatesTokenCount alone. This ensures thoughtsTokenCount is
included in output statistics.

- Update from_gemini_response to calculate output from total - input
- Update from_gemini_stream_chunks with same logic for consistency
- Fix from_codex_stream_events to use adjusted token calculation
- Add test case for responses with thoughtsTokenCount
- Update existing tests to match new calculation logic

* fix(usage): correct cache token billing and add Codex format auto-detection

- Avoid double-billing cache tokens by subtracting from input before calculation
- Add smart Codex parser that auto-detects OpenAI vs Codex API format
- Extract model name from Codex responses for accurate tracking

* fix(proxy): improve takeover detection with live config check

- Add live config takeover detection for hot-switch decision
- Rebuild takeover when backup is missing or placeholder remains
- Make detect_takeover_in_live_config_for_app public
- Fix is_takeover_active to use actual takeover status

* refactor(usage): simplify model pricing lookup by removing suffix fallback

Replace complex suffix-stripping fallback with direct prefix/suffix cleanup.
Model IDs are now cleaned by removing vendor prefix (before /) and colon
suffix (after :), then matched exactly against pricing table.

* feat(database): add Chinese AI model pricing data

Add pricing for domestic AI models (CNY/1M tokens):
- Doubao-Seed-Code (ByteDance)
- DeepSeek V3/V3.1/V3.2
- Kimi K2/K2-Thinking/K2-Turbo (Moonshot)
- MiniMax M2/M2.1/M2.1-Lightning
- GLM-4.6/4.7 (Zhipu)
- Mimo V2 Flash (Xiaomi)

Also fix test case to use correct model ID and remove invalid currency column.

* refactor(proxy): improve header forwarding with blacklist approach

Change from whitelist to blacklist mode for request header forwarding.
Only skip headers that will be overridden (auth, host, content-length).
This preserves client's original headers and improves compatibility.

* fix(proxy): bypass timeout and retry configs when failover is disabled

When auto_failover_enabled is false, timeout and retry configurations
should not affect normal request flow. This change ensures:

- create_forwarder: passes 0 for all timeout/retry params when failover
  is disabled, effectively bypassing these checks
- streaming_timeout_config: returns 0 for both first_byte_timeout and
  idle_timeout when failover is disabled

This prevents unnecessary timeout errors and retry attempts when users
have explicitly disabled the failover feature.

* fix(proxy): handle zero value input in failover config fields

* refactor(proxy): remove retry logic and add enabled check for failover

* refactor(proxy): distinguish circuit-open from no-provider errors

* Align usage stats to sliding windows

* feat(proxy): add body and header filtering for upstream requests

* feat(proxy): enable transparent passthrough for headers

- Passthrough anthropic-beta header as-is from client
- Passthrough anthropic-version header from client
- Passthrough client IP headers (x-forwarded-for, x-real-ip) by default
- Filter private params (underscore-prefixed fields) from request body
- No database changes required

* feat(proxy): extract session ID from client requests for logging

- Add SessionIdExtractor to parse session ID from Claude/Codex requests
- Support extraction from metadata.user_id, headers, previous_response_id
- Pass session_id through RequestContext to usage logger
- Enable request correlation by session in proxy_request_logs
2025-12-31 22:57:00 +08:00

225 lines
7.3 KiB
TypeScript

import { useTranslation } from "react-i18next";
import {
AreaChart,
Area,
XAxis,
YAxis,
CartesianGrid,
Tooltip,
ResponsiveContainer,
Legend,
} from "recharts";
import { useUsageTrends } from "@/lib/query/usage";
import { Loader2 } from "lucide-react";
interface UsageTrendChartProps {
days: number;
}
export function UsageTrendChart({ days }: UsageTrendChartProps) {
const { t, i18n } = useTranslation();
const { data: trends, isLoading } = useUsageTrends(days);
if (isLoading) {
return (
<div className="flex h-[350px] items-center justify-center rounded-xl bg-card/40 border border-border/50">
<Loader2 className="h-8 w-8 animate-spin text-muted-foreground/30" />
</div>
);
}
const isToday = days === 1;
const dateLocale =
i18n.language === "zh"
? "zh-CN"
: i18n.language === "ja"
? "ja-JP"
: "en-US";
const chartData =
trends?.map((stat) => {
const pointDate = new Date(stat.date);
return {
rawDate: stat.date,
label: isToday
? pointDate.toLocaleString(dateLocale, {
month: "2-digit",
day: "2-digit",
hour: "2-digit",
minute: "2-digit",
})
: pointDate.toLocaleDateString(dateLocale, {
month: "2-digit",
day: "2-digit",
}),
hour: pointDate.getHours(),
inputTokens: stat.totalInputTokens,
outputTokens: stat.totalOutputTokens,
cacheCreationTokens: stat.totalCacheCreationTokens,
cacheReadTokens: stat.totalCacheReadTokens,
cost: parseFloat(stat.totalCost),
};
}) || [];
const displayData = chartData;
const CustomTooltip = ({ active, payload, label }: any) => {
if (active && payload && payload.length) {
return (
<div className="rounded-lg border bg-background/95 p-3 shadow-lg backdrop-blur-md">
<p className="mb-2 font-medium">{label}</p>
{payload.map((entry: any, index: number) => (
<div
key={index}
className="flex items-center gap-2 text-sm"
style={{ color: entry.color }}
>
<div
className="h-2 w-2 rounded-full"
style={{ backgroundColor: entry.color }}
/>
<span className="font-medium">{entry.name}:</span>
<span>
{entry.name.includes(t("usage.cost", "成本"))
? `$${typeof entry.value === "number" ? entry.value.toFixed(6) : entry.value}`
: entry.value.toLocaleString()}
</span>
</div>
))}
</div>
);
}
return null;
};
return (
<div className="rounded-xl border border-border/50 bg-card/40 p-6 backdrop-blur-sm">
<div className="mb-6 flex items-center justify-between">
<h3 className="text-lg font-semibold">
{t("usage.trends", "使用趋势")}
</h3>
<p className="text-sm text-muted-foreground">
{isToday
? t("usage.rangeToday", "今天 (按小时)")
: days === 7
? t("usage.rangeLast7Days", "过去 7 天")
: t("usage.rangeLast30Days", "过去 30 天")}
</p>
</div>
<div className="h-[350px] w-full">
<ResponsiveContainer width="100%" height="100%">
<AreaChart
data={displayData}
margin={{ top: 10, right: 10, left: 0, bottom: 0 }}
>
<defs>
<linearGradient id="colorInput" x1="0" y1="0" x2="0" y2="1">
<stop offset="5%" stopColor="#3b82f6" stopOpacity={0.2} />
<stop offset="95%" stopColor="#3b82f6" stopOpacity={0} />
</linearGradient>
<linearGradient id="colorOutput" x1="0" y1="0" x2="0" y2="1">
<stop offset="5%" stopColor="#22c55e" stopOpacity={0.2} />
<stop offset="95%" stopColor="#22c55e" stopOpacity={0} />
</linearGradient>
<linearGradient
id="colorCacheCreation"
x1="0"
y1="0"
x2="0"
y2="1"
>
<stop offset="5%" stopColor="#f97316" stopOpacity={0.2} />
<stop offset="95%" stopColor="#f97316" stopOpacity={0} />
</linearGradient>
<linearGradient id="colorCacheRead" x1="0" y1="0" x2="0" y2="1">
<stop offset="5%" stopColor="#a855f7" stopOpacity={0.2} />
<stop offset="95%" stopColor="#a855f7" stopOpacity={0} />
</linearGradient>
</defs>
<CartesianGrid
strokeDasharray="3 3"
vertical={false}
stroke="hsl(var(--border))"
opacity={0.4}
/>
<XAxis
dataKey="label"
axisLine={false}
tickLine={false}
tick={{ fill: "hsl(var(--muted-foreground))", fontSize: 12 }}
dy={10}
/>
<YAxis
yAxisId="tokens"
axisLine={false}
tickLine={false}
tick={{ fill: "hsl(var(--muted-foreground))", fontSize: 12 }}
tickFormatter={(value) => `${(value / 1000).toFixed(0)}k`}
/>
<YAxis
yAxisId="cost"
orientation="right"
axisLine={false}
tickLine={false}
tick={{ fill: "hsl(var(--muted-foreground))", fontSize: 12 }}
tickFormatter={(value) => `$${value}`}
/>
<Tooltip content={<CustomTooltip />} />
<Legend />
<Area
yAxisId="tokens"
type="monotone"
dataKey="inputTokens"
name={t("usage.inputTokens", "输入 Tokens")}
stroke="#3b82f6"
fillOpacity={1}
fill="url(#colorInput)"
strokeWidth={2}
/>
<Area
yAxisId="tokens"
type="monotone"
dataKey="outputTokens"
name={t("usage.outputTokens", "输出 Tokens")}
stroke="#22c55e"
fillOpacity={1}
fill="url(#colorOutput)"
strokeWidth={2}
/>
<Area
yAxisId="tokens"
type="monotone"
dataKey="cacheCreationTokens"
name={t("usage.cacheCreationTokens", "缓存创建")}
stroke="#f97316"
fillOpacity={1}
fill="url(#colorCacheCreation)"
strokeWidth={2}
/>
<Area
yAxisId="tokens"
type="monotone"
dataKey="cacheReadTokens"
name={t("usage.cacheReadTokens", "缓存命中")}
stroke="#a855f7"
fillOpacity={1}
fill="url(#colorCacheRead)"
strokeWidth={2}
/>
<Area
yAxisId="cost"
type="monotone"
dataKey="cost"
name={t("usage.cost", "成本")}
stroke="#f43f5e"
fill="none"
strokeWidth={2}
strokeDasharray="4 4"
/>
</AreaChart>
</ResponsiveContainer>
</div>
</div>
);
}