Log MIDguudZ3VdX83hxaKe
Tx MIDguudZ3ZIQQQRjctN
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
215 × 1.35 = 0.000290
0 × 0.045 = 0.000000
298 × 4.05 = 0.001207
CNY 0.001497
Vendor Cost
215 × 1.2 = 0.000258
0 × 0.04 = 0.000000
298 × 3.6 = 0.001073
CNY 0.001331
Latency5.31964904s
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):需要考虑的权衡、内存管理、the system throughput、数据一致性、人工智能、以及未来发展趋势、结合实际案例、在生产环境中、服务治理、性能优化、背后的设计取舍、load balancing、latency dist",
"has_image": false,
"has_tool_result": false
},
"assistant_summary": {
"text": "在生产环境中,系统吞吐量与延迟分布受负载均衡、并发控制和算法复杂度的共同制约。设计取舍需权衡内存管理与数据一致性:例如流式响应场景,采用缓冲队列可降低首字延迟,但增加内存压力;若强一致要求同步复制,则吞吐下降。以分布式数据库为例,Raft共识在节点故障时保障一致性,却牺牲可用性,而最终一致性模型(如",
"tool_calls": [],
"stop_reason": "length"
}
}Stop Reasonlength
Token Usage
{
"completion_tokens": 298,
"completion_tokens_details": {
"reasoning_tokens": 41
},
"prompt_tokens": 215,
"prompt_tokens_details": {
"cached_tokens": 0
},
"total_tokens": 513
}Fixes
Created At9/9/2026, 2:32:13 PM