Sample LLM traces — Sharing-is-Caring badge
These JSONL files are unedited captures of every LLM call from real
playthroughs of The Apprentice. One JSON object per line, schema
documented in ../README.md.
Files
| File | Records | Calls | Notes |
|---|---|---|---|
three-playthroughs-fantasy-en.jsonl |
117 | All oracle-wizard-lora (the fine-tune) |
Three back-to-back playthroughs in one Python process. Default Tobin / the Hollow hero+village, English, fantasy theme. ~422k prompt tokens / ~43k output tokens total. 90 JSON-mode calls (resolutions + fork picks) + 27 text-mode calls (interludes + epilogue + theme expansion). |
Quick exploration
Inspect with jq:
# Distinct models served
jq -r '.model_returned' three-playthroughs-fantasy-en.jsonl | sort -u
# Just the responses
jq -r '.response' three-playthroughs-fantasy-en.jsonl | head -3
# Calls by mode
jq -r '.mode' three-playthroughs-fantasy-en.jsonl | sort | uniq -c
# Latency distribution (ms)
jq -r '.latency_ms' three-playthroughs-fantasy-en.jsonl | sort -n | awk '
{a[NR]=$1; sum+=$1} END {
print "min:",a[1],"p50:",a[int(NR/2)],"p95:",a[int(NR*0.95)],"max:",a[NR],"mean:",sum/NR
}'
How these were generated
LLM-call tracing is default-on in this app. Set
ORACLES_TRACE_DISABLE=1 to opt out. Each session writes to
traces/oracles-trace-<12-char-hex>.jsonl. The
curate_trace script copies one of
those session files into this directory under a friendlier label.