SETTLEMENT TELEMETRY

Inference Log

MID: guudWFkvjXXyiE7s

Log MIDguudWFkvjXXyiE7s
Typechat_completion
Aliasdeepseek-v4-flash-g3 / gucs9pn4RAHUO73l
Hostinforaxi-server:3300:v1.1.4013-14-gbfebabe6d
Mode / Protoreq-v1-chatcmplopenai-chatcmpl
Vendor/LLMvolcengine-bizplan-dtx/deepseek-v4-flash-ga-260731
Statussuccess
User Pricing
214 × 1.35 = 0.000289
0 × 0.045 = 0.000000
282 × 4.05 = 0.001142
CNY 0.001431
Vendor Cost
214 × 1.2 = 0.000257
0 × 0.04 = 0.000000
282 × 3.6 = 0.001015
CNY 0.001272
Latency5.50941402s
Summary
{
  "system_prefix": null,
  "history_count": 1,
  "user_summary": {
    "text": "请围绕下面的关键词写一段连贯的分析(约 200 tokens 的输入):结合实际案例、背后的设计取舍、分布式系统、以及未来发展趋势、碳中和、under high concurrency、cache strategy、性能优化、关键原理与影响、结合实际案例、服务治理、under high concur",
    "has_image": false,
    "has_tool_result": false
  },
  "assistant_summary": {
    "text": "在分布式系统的高并发场景下,缓存策略与数据一致性构成核心权衡:如电商秒杀采用本地缓存加Redis集群,以最终一致性换取吞吐,同时通过负载均衡与内存管理(如堆外缓存)降低GC压力。关键原理在于将热点读流量从数据库分流,但缓存穿透、击穿需借助布隆过滤与熔断治理。实际案例中,服务治理框架(如Sentine",
    "tool_calls": [],
    "stop_reason": "stop"
  }
}
Stop Reasonstop
Token Usage
{
  "completion_tokens": 282,
  "completion_tokens_details": {
    "reasoning_tokens": 90
  },
  "prompt_tokens": 214,
  "prompt_tokens_details": {
    "cached_tokens": 0
  },
  "total_tokens": 496
}
Fixes
Created At9/9/2026, 2:32:05 PM