A curated dataset collection of 787 multi-turn agentic LLM sessions (24,881 total LLM iterations) designed for benchmarking stateful LLM serving systems. Every session exhibits at least 5 turns with prefix growth and builds to at least 10K tokens of context — making it ideal for evaluating tiered KV Cache solutions like LMCache.
Modern LLM agents (coding assistants, research agents, tool-calling systems) make dozens of… See the full description on the dataset page:
https://huggingface.co/datasets/sammshen/lmcache-agentic-traces.
