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| pretty_name: AgentLoad synthetic agent traces (PrefixAnvil) | |
| license: other | |
| task_categories: [other] | |
| tags: [llm-inference, prefix-caching, kv-cache, agents, synthetic] | |
| size_categories: [n<1K] | |
| # AgentLoad synthetic agent traces | |
| Synthetic OpenAI-compatible chat-completion request logs of tool-using agent sessions, with **ground-truth | |
| labels of injected prefix-cache fragmentation** (F1–F8). Generated by `prefixanvil gen` (PrefixAnvil AgentLoad); | |
| fully reproducible from a small JSON config and a seed. No real user data. The traces are generated by | |
| PrefixAnvil — https://github.com/NagaYu/prefixanvil | |
| ## License | |
| This dataset is made publicly visible solely so it can be read and evaluated. It is All Rights Reserved — no | |
| license is granted beyond viewing and downloading for evaluation. Licensing or transfer inquiries: | |
| https://nagayu-portfolio.nagayu.workers.dev/en | |
| ## Files | |
| | file | content | | |
| |---|---| | |
| | `bench_main.jsonl` | 377 requests, 40 sessions, all eight fragmentation types injected at 6% each | | |
| | `bench_main.labels.jsonl` | one line per injected event: `request_index`, `request_id`, `fault` (F1–F8), `scope` (within/cross session), `reference_request_id`, `location` | | |
| | `bench_xsession.jsonl` | 155 requests, 30 sessions, no faults; each session's client lists the same tools in its own order | | |
| | `configs/*.json` | the exact generator configs (seeds included) | | |
| Each request line: `request_id`, `session_id`, `timestamp`, `model`, `messages`, `tools`. | |
| ## How it was generated | |
| ```bash | |
| prefixanvil gen --config fixtures/bench/bench_main.json --out bench_main.jsonl | |
| prefixanvil gen --config fixtures/bench/bench_xsession.json --out bench_xsession.jsonl | |
| ``` | |
| Byte-identical output for the same config (pure-Python RNG; checked in CI). File sha256 of the four `.jsonl` | |
| files in this folder: | |
| | file | sha256 | | |
| |---|---| | |
| | `bench_main.jsonl` | `cee5445df3364b3fc0a2af4a1f906356d537076857a5c4059ce96a6b800ef000` | | |
| | `bench_main.labels.jsonl` | `5b114c0cf4547eadb77454313d82249e1fdccd869118d72864a31c16415b623a` | | |
| | `bench_xsession.jsonl` | `271a8a6f3c2a61e9ae4b0878285e65ac96e17bf0b08202b415bff2c3a2f819df` | | |
| | `bench_xsession.labels.jsonl` | `ec1431b9afd077cdc20026ca7886c5169f821ff4f0ec3224bba81a73d9af0b39` | | |
| ## Fragmentation types | |
| F1 volatile values (timestamps, UUIDs, run ids) · F2 non-deterministic JSON serialization · F3 tool-set churn · | |
| F4 per-user interpolation · F5 conditional system sections · F6 whitespace/format drift · F7 retrieved context | |
| inserted before stable instructions · F8 rewritten history. | |
| At most one event per request/reference pair, so the cause of each first divergence is unambiguous. | |
| ## Benchmark headline | |
| Measured on Kaggle 2 × Tesla T4 (free tier) with Qwen2.5-7B-Instruct-AWQ and vLLM 0.33.0, replaying these | |
| traces at concurrency 1 (run `t4-20261111-0408`). Hit rate and prefill are determined by the cache algorithm, | |
| not the GPU; TTFT/GPU-seconds (in `BENCH.md`) are **T4 reference values only**. | |
| | trace | policy | token-weighted hit rate | recomputed prefill tokens | | |
| |---|---|---:|---:| | |
| | bench_main | raw | 74.71% | 241,640 | | |
| | bench_main | L1 canonicalization | 81.79% | 172,268 (−28.7%) | | |
| | bench_main | L2 relocation (reference) | 83.61% | 155,068 (−35.8%) | | |
| | bench_xsession | raw | 86.63% | 50,120 | | |
| | bench_xsession | L1 session-stable (deployed policy) | 86.69% | 49,273 | | |
| | bench_xsession | L1 stateless name-sort (ceiling) | 95.31% | 17,369 | | |
| L1/L2 are prompt transforms; identical generated text is not guaranteed (Phase 3 sampled L1-vs-raw match 10/18, | |
| L2-vs-raw 4/6, against an 18/18 raw-vs-raw control). Full numbers, fidelity and the NVIDIA Dynamo trial are in | |
| `BENCH.md`. | |
| ## Limitations | |
| Synthetic text (word-salad sentences), synthetic tools, open-loop (assistant turns are generated, not model | |
| outputs). Useful for measuring prefix-cache behaviour, not for training or evaluating language quality. | |