A fresh same-session prior within the TTL is no longer sufficient to price
the text counterfactual warm: deriveBaselineWarmth now also requires the
static-prefix hash (system_sha8) to match. When opencode rotates the system
prompt / tool docs mid-session, the cacheable prefix changes, so a text-only
client would hit a new provider cache key too — pricing it warm against a
cold actual fabricated a huge phantom "loss" (the dashboard's 800%-worse
report). cr>0 still rescues a genuine warm read with no in-memory prior.
Wired through update(), replay(), and aggregateSessions via system_sha8.
Also surface losses honestly in the recent table (Saved/lost: negative
deltas in red instead of hidden as "—") and clarify headings as
billing-equivalent input tokens. Docs updated to match.
The savings accounting priced the text baseline as cold whenever pxpipe's own
image cache missed this turn (cr==0), fabricating a 1.25x create the text path
would never have paid and inflating reported savings ~2x. Decouple them: the
text prefix reads warm whenever a fresh same-session prior exists within the
300s TTL (wall-clock), unioned with an observed read (cr>0) for the post-restart
case. Centralised in deriveBaselineWarmth; used by all three call sites
(sessions, dashboard, fragments).
Empirical replay over ~/.pxpipe/events.jsonl (13,402 message rows): honest
headline 504.6M tokens saved vs the old cr-gated 1.05B; 1,409/12,305 fresh-prior
rows (11.4%) read warm despite a busted image cache. Dashboard now narrates the
busted-image case explicitly. Adds baseline/sessions/context-map regression
tests. Measurement only — no change to proxy behavior.
typecheck + 600 tests + build all green.
Collapse old conversation history into rendered PNG sections so the model
reads a compact image instead of re-billed text, while preserving prompt
caching and tool-call behavior. Measures real vs compressed token/cost.
Core:
- GPT history collapse (openai-history.ts): append-only, o200k token-length
sectioning. Sections seal only at a tool-closed boundary (open call-id set
empty), so a function_call and its function_call_output never split across
the collapse cut. Fixes the OpenAI 400 "No tool call found for function
call output with call_id ..." that hit long Responses-API sessions.
- Anthropic cache contract (history.ts): append-only per-chunk rendering;
cache_control markers are preserved/moved, never added; chunk boundaries
align with caller marker seams for byte-stable prefix caching.
- GPT image budget (openai.ts): detail:'original' for gpt-5.x, flagship
vision-multiplier fix, patch cap; schema-strip preserves real descriptions.
- Savings accounting (openai-savings.ts): cached_tokens + vision-token basis.
Model scope (applicability.ts):
- Default imaged scope = claude-fable-5 + gpt-5.6.
- gpt-5.5 and claude-opus-4-8 stay opt-in: same pipeline, but they degrade
reading dense imaged history (gist drift), so silently imaging them by
default is wrong. Promotion is gated on an OCR/recall threshold.
Dashboard: GPT + Anthropic rendering, per-family model toggles, persisted
metrics, thumbnail-expired session UI, reflow/newline handling.
Tests: cache-alignment (GPT + Anthropic), history sectioning + tool-boundary
invariants, savings, dashboard, sessions/restart-restore. 452 passing.
Steven