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README.md

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+---
+license: apache-2.0
+pretty_name: CC Traces — Weka, No-Subagents (May 12 2026)
+task_categories:
+  - text-generation
+tags:
+  - llm
+  - inference
+  - benchmarking
+  - kv-cache
+  - agentic
+  - multi-turn
+  - claude
+size_categories:
+  - n<1K
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: traces.jsonl
+---
+
+# CC Traces — Weka, No-Subagents (May 12 2026)
+
+A collection of **949 multi-turn agentic traces** (≈ 136.1 k individual
+model requests) drawn from real production traffic against the Claude
+Code CLI ≥ 2.1.139. Each trace captures the full request/response
+sequence of a single agent session, including per-request KV block
+hashes, so the dataset can be replayed against an inference engine or
+used to simulate prefix-cache behavior offline.
+
+**No-subagents variant.** This dataset is a derivative of the source
+weka traces with all `WekaSubagentEntry` blocks stripped — only
+top-level main-agent turns remain. The full-subagent companion variant
+lives elsewhere. Use this corpus when you want a single
+linear agent stream per trace and don't care about the parent / child
+fan-out structure of agentic tool-calling.
+
+- **Traces:** 949
+- **Requests:** 136,118 total, mean **143.4** per trace, max **13,685**
+- **Models:** `claude-opus-4-7` (most turns), `claude-haiku-4-5-20251001`,
+  `claude-opus-4-6`, `claude-sonnet-4-6`
+- **KV block size:** 64 tokens
+- **Hash scope:** `local` — block hash IDs are only comparable *within*
+  a single trace; they are not a global content-addressable identity.
+
+## Important: tokenizer caveat
+
+The `in` field on each request and the `hash_ids` array are both
+measured in **the proxy's tokenizer** (qwen3 / o200k_base — depends on
+the originating trace_version), NOT Anthropic's BPE. Anthropic
+typically reports ~60 % of the qwen3/o200k token count for the same
+content. So the ISL numbers below are larger than what the Anthropic
+API would have billed for the same prompt — but they're self-consistent
+between `in` and `hash_ids`, which is what matters for KV-cache replay
+simulation.
+
+If you replay these traces against a real Claude (or Claude-like)
+server, the server will re-tokenize the text and see ~Claude-equivalent
+token counts, so cache-hit-rate measurements remain accurate.
+
+## What's in each trace
+
+Top-level trace fields:
+
+| field           | type             | description                                         |
+|-----------------|------------------|-----------------------------------------------------|
+| `id`            | str              | Trace identifier (the proxy session id)             |
+| `models`        | list[str]        | Models used by the trace                            |
+| `block_size`    | int              | KV block size used to derive `hash_ids` (64)        |
+| `hash_id_scope` | str              | `local` — hash IDs are per-trace, not global        |
+| `requests`      | list[object]     | Ordered list of per-request records (main-agent only) |
+
+Each entry in `requests` is:
+
+| field         | type      | description                                                              |
+|---------------|-----------|--------------------------------------------------------------------------|
+| `t`           | float     | Seconds since start of trace                                             |
+| `type`        | str       | `n` (non-streaming) or `s` (streaming)                                   |
+| `model`       | str       | Target model for this request                                            |
+| `in`          | int       | Effective prompt tokens covered by `hash_ids` (proxy tokenizer)          |
+| `out`         | int       | Output tokens (Anthropic-reported)                                       |
+| `hash_ids`    | list[int] | Per-trace local block-hash IDs for the input, one per 64-token block     |
+| `api_time`    | float     | End-to-end server time for this call (seconds)                           |
+| `think_time`  | float     | Wall-clock gap from previous request's end (seconds)                     |
+| `ttft`        | float?    | Time to first token (streaming requests only)                            |
+
+`hash_ids` make the dataset unusually useful for KV-cache work: the
+contiguous common prefix between turn *t* and turn *t − 1* exactly
+measures the portion of the input that a local prefix cache would be
+able to reuse.
+
+## Summary statistics
+
+|                              |   p50    |   p75    |   p90    |   p95    |   p99    |   mean   |
+|------------------------------|---------:|---------:|---------:|---------:|---------:|---------:|
+| ISL (tokens)                 |  123,952 |  245,124 |  391,085 |  490,478 |  720,485 |  178,018 |
+| OSL (tokens)                 |      261 |      664 |    1,614 |    2,805 |    7,013 |      711 |
+| `think_time` (s)             |     1.29 |     2.92 |    54.97 |   181.78 | 1,887.83 |   351.34 |
+| Turn depth (requests/trace)  |       56 |      118 |      252 |      437 |    1,497 |      143 |
+| Token growth per turn        |      395 |      952 |    2,504 |    5,399 |   87,849 |      758 |
+| Cache hit rate per request   |   0.8404 |   0.9243 |   0.9678 |   0.9970 |   0.9995 |   0.7509 |
+
+### Why is "token growth per turn" sometimes negative?
+
+Agentic prompts usually grow monotonically — each turn appends the
+user's new message + assistant's reply to the running context, so the
+next turn's `in` is at least as big as the previous. **But ~1% of
+adjacent-turn deltas in this corpus are sharply negative** (Δin
+< −100K tokens, often −500K to −800K). These are real production
+events, not data errors: they're **context compaction**.
+
+Claude Code (and similar agentic clients) summarize long conversations
+when the context grows close to the model's limit, replacing dozens of
+prior messages with a short summary. After that summary is committed,
+the next turn's prompt drops from ~800K back to ~10–80K tokens — a
+sharp negative delta. Some sessions in this corpus compact 10+ times
+in a row, which produces clusters of large negative growth events
+that are visible in the histogram's left tail.
+
+If you're modeling raw prompt growth, treat negative deltas as
+"context reset" events and either skip them or count them separately.
+If you're modeling realistic agentic load, leave them in — they're
+part of how long sessions stay under the context budget.
+
+Mean per-request prefix-cache hit rate across the full corpus is
+**~75 %**, with a strong mode near 1.0 (steady-state cache reuse) and a
+secondary mass near 0 (cold-start / reset turns).
+
+## Plots
+
+Combined 3×2 distributions with p50 / p75 / p90 / p99 percentile
+markers on each panel. Two variants: log-x for the heavy-tailed
+metrics, linear-x for the bounded ones.
+
+### Log-x
+
+Best for the long-tailed distributions (think_time, ISL, OSL, turn
+depth). Token growth stays linear (it has negative values from
+context-compaction events).
+
+![Distributions — log x](plots/distributions_log.png)
+
+### Linear-x
+
+Linear axes everywhere. Heavy tails clipped at p99 with a count of
+clipped values in each panel's subtitle so they're not silently
+dropped.
+
+![Distributions — linear x](plots/distributions_linear.png)
+
+## How this dataset was built
+
+1. **Sampled** from the SemiAnalysis Claude Code proxy database.
+   Filtered to: Anthropic models only (`model LIKE 'claude-%'`), HTTP
+   200 + no proxy error, `privacy_mode = 'anon'` (request bodies are
+   redacted; metric columns are intact), and the post-2026-04-16
+   timeframe (after the `subagent_label` migration so subagent
+   classification is reliable).
+2. **Converted** flat per-row dumps into v1 weka format using the
+   conversation-view subagent grouping algorithm from the SemiAnalysis
+   claude-code-proxy. Hash IDs were remapped to per-trace local ints
+   (`hash_id_scope: "local"`).
+3. **Subagent entries removed.** This is the no-subagents variant of
+   the corpus, so every `WekaSubagentEntry` block was filtered out of
+   each trace's `requests` list. Traces that became empty after
+   filtering (entirely Agent-SDK or utility-only sessions) were
+   dropped.
+4. **Proxy-hash-bug outliers removed.** Sessions containing any
+   single row with `in > 1,000,000` proxy-tokens were dropped (25
+   sessions). These are confirmed proxy hashing artifacts (v1/v2/v4
+   over-count `hash_token_count` for sessions with document content
+   blocks or pre-v3 tool-call histories — not legitimate token sizes
+   that the model actually saw).
+
+## Intended uses
+
+- **Inference benchmarking:** replay traces against a serving engine
+  (vLLM, SGLang, TRT-LLM, etc.) to measure throughput / latency under a
+  realistic agentic workload.
+- **KV-cache research:** the `hash_ids` field exposes block-level
+  prefix structure directly without needing to re-tokenize any text.
+- **Capacity planning:** the ISL / OSL / think-time / turn-depth
+  distributions are a reasonable first-order model of traffic from
+  long-context agentic clients.
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("semianalysisai/cc-traces-weka-no-subagents-051226", split="train")
+print(ds[0]["id"], len(ds[0]["requests"]))
+```
+
+## License & attribution
+
+Released under the **Apache 2.0** license.

traces.jsonl

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