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

src-tauri/src/proxy/response_processor.rs

@@ -112,6 +112,19 @@ pub async fn handle_non_streaming(
 
             spawn_log_usage(state, ctx, usage, &model, status.as_u16(), false);
         } else {
+            let model = json_value
+                .get("model")
+                .and_then(|m| m.as_str())
+                .unwrap_or(&ctx.request_model)
+                .to_string();
+            spawn_log_usage(
+                state,
+                ctx,
+                TokenUsage::default(),
+                &model,
+                status.as_u16(),
+                false,
+            );
             log::debug!(
                 "[{}] 未能解析 usage 信息，跳过记录",
                 parser_config.app_type_str
@@ -123,6 +136,14 @@ pub async fn handle_non_streaming(
             ctx.tag,
             body_bytes.len()
         );
+        spawn_log_usage(
+            state,
+            ctx,
+            TokenUsage::default(),
+            &ctx.request_model,
+            status.as_u16(),
+            false,
+        );
     }
 
     log::info!("[{}] ====== 请求结束 ======", ctx.tag);
@@ -243,6 +264,7 @@ fn create_usage_collector(
     let start_time = ctx.start_time;
     let stream_parser = parser_config.stream_parser;
     let model_extractor = parser_config.model_extractor;
+    let session_id = ctx.session_id.clone();
 
     SseUsageCollector::new(start_time, move |events, first_token_ms| {
         if let Some(usage) = stream_parser(&events) {
@@ -251,6 +273,7 @@ fn create_usage_collector(
 
             let state = state.clone();
             let provider_id = provider_id.clone();
+            let session_id = session_id.clone();
 
             tokio::spawn(async move {
                 log_usage_internal(
@@ -263,10 +286,32 @@ fn create_usage_collector(
                     first_token_ms,
                     true, // is_streaming
                     status_code,
+                    Some(session_id),
                 )
                 .await;
             });
         } else {
+            let model = model_extractor(&events, &request_model);
+            let latency_ms = start_time.elapsed().as_millis() as u64;
+            let state = state.clone();
+            let provider_id = provider_id.clone();
+            let session_id = session_id.clone();
+
+            tokio::spawn(async move {
+                log_usage_internal(
+                    &state,
+                    &provider_id,
+                    app_type_str,
+                    &model,
+                    TokenUsage::default(),
+                    latency_ms,
+                    first_token_ms,
+                    true, // is_streaming
+                    status_code,
+                    Some(session_id),
+                )
+                .await;
+            });
             log::debug!("[{tag}] 流式响应缺少 usage 统计，跳过消费记录");
         }
     })
@@ -286,6 +331,7 @@ fn spawn_log_usage(
     let app_type_str = ctx.app_type_str.to_string();
     let model = model.to_string();
     let latency_ms = ctx.latency_ms();
+    let session_id = ctx.session_id.clone();
 
     tokio::spawn(async move {
         log_usage_internal(
@@ -298,6 +344,7 @@ fn spawn_log_usage(
             None,
             is_streaming,
             status_code,
+            Some(session_id),
         )
         .await;
     });
@@ -315,6 +362,7 @@ async fn log_usage_internal(
     first_token_ms: Option<u64>,
     is_streaming: bool,
     status_code: u16,
+    session_id: Option<String>,
 ) {
     use super::usage::logger::UsageLogger;
 
@@ -338,6 +386,15 @@ async fn log_usage_internal(
 
     let request_id = uuid::Uuid::new_v4().to_string();
 
+    log::debug!(
+        "[{app_type}] 记录请求日志: id={request_id}, provider={provider_id}, model={model}, streaming={is_streaming}, status={status_code}, latency_ms={latency_ms}, first_token_ms={first_token_ms:?}, session={}, input={}, output={}, cache_read={}, cache_creation={}",
+        session_id.as_deref().unwrap_or("none"),
+        usage.input_tokens,
+        usage.output_tokens,
+        usage.cache_read_tokens,
+        usage.cache_creation_tokens
+    );
+
     if let Err(e) = logger.log_with_calculation(
         request_id,
         provider_id.to_string(),
@@ -348,7 +405,7 @@ async fn log_usage_internal(
         latency_ms,
         first_token_ms,
         status_code,
-        None,
+        session_id,
         None, // provider_type
         is_streaming,
     ) {