Dataset Viewer
Auto-converted to Parquet Duplicate
id
stringlengths
36
36
models
listlengths
1
4
block_size
int64
64
64
hash_id_scope
stringclasses
1 value
requests
listlengths
3
3.05k
002001296e8a8c38ad9d7cc436d691afc602
[ "claude-haiku-4-5-20251001", "claude-opus-4-8" ]
64
local
[{"t":0.0,"model":"claude-opus-4-8","in":640,"out":20,"hash_ids":[0,1,2,3,4,5,6,7,8,9],"api_time":1.(...TRUNCATED)
006c98de37d819e95b0840e25426bb7ca99d
[ "claude-opus-4-8" ]
64
local
[{"t":0.0,"model":"claude-opus-4-8","in":448,"out":14,"hash_ids":[0,1,2,3,4,5,6],"api_time":1.45,"ty(...TRUNCATED)
00ca01c4aaeccee751ae6285beb54dea262f
[ "claude-fable-5", "claude-haiku-4-5-20251001" ]
64
local
[{"t":0.0,"model":"claude-fable-5","in":640,"out":24,"hash_ids":[0,1,2,3,4,5,6,7,8,9],"api_time":5.3(...TRUNCATED)
0196085d85d2075a50b74cd8795ffbdcea9a
[ "claude-opus-4-7", "claude-opus-4-8" ]
64
local
[{"t":0.0,"model":"claude-opus-4-8","in":88384,"out":1978,"hash_ids":[0,1,2,3,4,5,6,7,8,9,10,11,12,1(...TRUNCATED)
02bc0afb13f7a2d9efa86c28511261d85c0e
[ "claude-haiku-4-5-20251001", "claude-opus-4-8" ]
64
local
[{"t":0.0,"model":"claude-opus-4-8","in":37760,"out":548,"hash_ids":[0,1,2,3,4,5,6,7,8,9,10,11,12,13(...TRUNCATED)
03e110ac6921c2fe9ac7772a9654314a2beb
[ "claude-fable-5", "claude-opus-4-6" ]
64
local
[{"t":0.0,"model":"claude-fable-5","in":704,"out":23,"hash_ids":[0,1,2,3,4,5,6,7,8,9,10],"api_time":(...TRUNCATED)
0470d446a4514dfe0c6ad0be92853bd13287
[ "claude-fable-5", "claude-haiku-4-5-20251001", "claude-opus-4-6", "claude-opus-4-8" ]
64
local
[{"t":0.0,"model":"claude-fable-5","in":448,"out":24,"hash_ids":[0,1,2,3,4,5,6],"api_time":4.1370000(...TRUNCATED)
04dba6fe621301a1d01fd63b8d02c9645c48
[ "claude-opus-4-8" ]
64
local
[{"t":0.0,"model":"claude-opus-4-8","in":384,"out":29,"hash_ids":[0,1,2,3,4,5],"api_time":2.151,"typ(...TRUNCATED)
05c249572509162371b7b82339674db64b5d
[ "claude-opus-4-8" ]
64
local
[{"t":0.0,"model":"claude-opus-4-8","in":448,"out":17,"hash_ids":[0,1,2,3,4,5,6],"api_time":2.698,"t(...TRUNCATED)
05f72f78a037cfa5cd4e4541960a574701d9
[ "claude-opus-4-8" ]
64
local
[{"t":0.0,"model":"claude-opus-4-8","in":448,"out":17,"hash_ids":[0,1,2,3,4,5,6],"api_time":1.366,"t(...TRUNCATED)
End of preview. Expand in Data Studio

semianalysisai/cc-traces-weka-062126

WekaTrace corpus derived from SemiAnalysis Claude Code proxy traces. Built 2026-06-21 17:48:24 UTC via utils/agentic/build_weka_hf_dataset.py.

Filters

  • Trace version: exactly v7
  • min Anthropic requests per session: 20
  • Claude Code CLI ≥ 2.1.139 (every row)
  • peak concurrent sub-agent groups ≤ 10
  • Non-image rows only (image content excluded at source)
  • Classifier calls excluded (max_tokens<=64 AND no tools → SUGGESTION MODE, title-gen, Security Monitor)
  • Exact-duplicate proxy rows deduped by (timestamp, model, in, out, dur_ms, agent_id)
  • Dynamic-workflow-bug sessions excluded: Claude Code CLI < 2.1.174 emitted dynamic-workflow subagents without a subagent-label header, so they appear as many interleaved unlabeled trajectories in one session. Dropped when peak concurrent unlabeled multi-turn trajectories ≥ 3 (changelog 2.1.174).
  • Per-request ISL cap: input ≤ 990,016 tokens (weka in = hash-block count × 64). Drops KV-cache-block overcount artifacts that read above ~1M while preserving the surviving timeline.

ISL cap — KV-cache-block overcount note

Requests whose input length (in) exceeded 990,016 tokens (the closest multiple of 64 to 990k) were dropped from this build, while preserving the surviving timeline's relative timestamps.

Why. The weka in field is derived from the proxy's hash_token_count, which is recorded as (number of 64-token KV-cache prefix blocks) × 64 — it is always an exact multiple of 64, not a true tokenizer count. For very large agentic contexts with heavy prompt caching this block count drifts above the real prompt size: cross-checking against the billed token columns (input + cache_read + cache_write) shows it tracks ~1.00× on average but overcounts by as much as ~260k tokens in the heavy-cache-write tail. That tail pushed a small number of requests past 1M in even though no request's real prompt actually exceeds 1M. These inflated rows are the artifacts removed here.

Applied at request granularity (main-agent turns and sub-agent inner requests evaluated independently); a sub-agent group is dropped only if every inner request was over the cap.

Stats

traces:             393
main_turns:          56,798
subagent_groups:           1,697
subagent_inner_requests:          42,029
total_model_requests:          98,827
total_input_tokens:  21,635,381,376
total_output_tokens:     106,474,498

Distribution plots

Main-agent stream

Main-stream distributions — log x

Main-stream distributions — linear x

Sub-agent fan-out

Sub-agent distributions — log x

Sub-agent distributions — linear x

Source script

python utils/agentic/sample_proxy_traces.py --out '<workdir>/proxy' --sampling top --min-trace-version 7 --max-trace-version 7 --min-requests 20 --require-cli-min 2.1.139 --max-parallel-subagents 10 --exclude-dynamic-workflow-bug

Loader plugin

Load in aiperf via:

--public-dataset semianalysis_cc_traces_weka_with_subagents
Downloads last month
262