A unified, tokenized corpus of 15,000 multi-turn agentic-coding sessions (618K turns, 41 turns/session avg) drawn from three publicly-released upstream datasets. Built for benchmarking LLM serving systems on realistic multi-turn coding-agent workloads.
Most LLM serving benchmarks use single-shot prompts. Real coding agents work in long multi-turn loops where each turn appends to a growing prompt. This corpus captures that shape… See the full description on the dataset page:
https://huggingface.co/datasets/thoughtworks/agentic-coding-trajectories.
