User-requested comparison of inter-turn external gap distribution between
the production agentic trace (Qwen3-Coder) and a production chatbot trace
(qwen3-max chat). Both computed as
T_external = next_turn.start_ms - prev_turn.end_ms
on the same kind of pipeline (raw input + raw output join on request_id,
session structure from the formatted trace's parent_chat_id chains).
The chatbot trace lives as two files on dash0:
input : bailian-trace/qwen-trace-260321-260327/qwen3-max-input-032309-032311.jsonl
output : bailian-trace/qwen-trace-260321-260327/qwen3-max-output-032109-032711.jsonl
The raw input has no session_id (uuid is per-record, user_id has only 4
distinct tenant values for 346 k requests). We recover session structure
from the formatted file (qwen_chat_blksz_64_032309-032311.jsonl, which
groups requests by parent_chat_id), matching each formatted record to a
raw record by (timestamp, output_length) — prompt_token_num is anonymized
to 0 in this trace, so we use generate_token_num as the join key.
End time is derived from time_to_finish_token (ms duration) not the "time"
string field (which is the log-write time, not request completion).
Numbers (chatbot, 42 228 inter-turn gaps over 32 262 multi-turn sessions):
p25 4.85 s p50 7.18 s p75 8.22 s p90 15.0 s p99 43 s
4% gaps < 1 s 29% < 5 s 78% < 10 s 98% < 30 s
Compare to agentic (same metric, scripts/compute_inter_turn_gap_remote.py):
p25 0.69 s p50 1.6 s p75 8.6 s p90 44 s p99 738 s
39% gaps < 1 s 67% < 5 s 77% < 10 s 87% < 30 s
Distributions differ in shape, not just location:
- Chatbot is tight, unimodal around 5–10 s (human interaction).
- Agentic is bimodal: a sub-second autonomous tool-call mode (39 % < 1 s)
plus a long-pause tail (13 % > 30 s, p99 = 738 s) for sessions where
the operator steps away.
- The sub-second tool-call mass is where dispatch coupling lives —
those turns have W_turn ≫ T_external for any current scheduler.
The earlier "chatbot has T_human ≈ 30 s" hand-wave was wrong empirically.
The right framing for §2.3 is "agentic has a sub-second tool-call mode
that chatbot doesn't", not "chatbot has think-time and agentic doesn't".
Adds:
- scripts/compute_inter_turn_gap_chatbot.py: dash0-side aggregator
(raw input/output join + formatted alignment by ts + output_length)
- analysis/characterization/data/chatbot_inter_turn_gap.json: CDF cache
- scripts/plot_inter_turn_gap.py: overlays both curves on log-x
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Gahow Wang
876d09db83