Opening a finished adventure fetched every action in one response: 589.5 kB on
production's longest, and nothing about that curve bends on its own, because a
story only ever gets longer. The page load now brings the newest 60 actions
and the reader pages up from there. On the harness's 600-action fixture that
is 606.0 kB down to 62.6 kB, and -- the part that matters -- it no longer
depends on how long the story is.
Paged by anchor, not by offset. `before_id` is the oldest action the caller
holds; the server returns what precedes it. An offset counted back from the
newest would shift every older position the moment a turn lands, which is
exactly when someone is likely to be scrolling, and the reader would get one
action twice and never see another. It also keeps working when the story stops
being a flat list: comparing indices to order a branch survives the story tree,
treating them as positions does not.
`has_more` comes from fetching one row past the window rather than from
counting. A deleted anchor -- undo, mid-scroll -- reports the end rather than
guessing and serving a page the reader already has.
GET /{id}/actions and POST /{id}/undo now return {actions, total, has_more}
instead of a bare list. Undo is the action most likely to be repeated several
times running, so having it re-fetch the whole story would have undone the
paging on the worst case.
The adventure payload gets its window through set_committed_value rather than
by assignment: the actions relationship cascades delete-orphan, so assigning a
60-item list to it would delete everything outside the window on the next
flush.
In Play.jsx the prepend is followed by a useLayoutEffect that restores the
scroll position, before paint, so the story does not jump. Loading starts 400px
from the top rather than at it, guarded by a ref because scroll fires far
faster than React re-renders. There is a button as well as the scroll trigger:
on a short viewport the transcript may not be tall enough to scroll at all, and
a reader who cannot scroll must still be able to reach the beginning.
Verified against a running backend and a 220-action adventure: the page load
returns 60 of 220 ending on the newest, and walking back from an anchor returns
exactly the actions before it.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_017Dvvqn9ZDR4ixeFPHNbww7
Three fallout bugs from keeping the retried action row alive (906ba42),
plus two long-standing cursor bugs the same investigation turned up.
Retry context leak: the row being regenerated is still attached to the
adventure, so it was replayed as established story and the model wrote a
continuation of the attempt it was meant to replace — the story visibly
blended both takes. It leaked into four places, not one: history replay,
story-card trigger matching, in-scene NPC detection, and the memory-bank
similarity query. Adds a shared context.story_actions(exclude_action_id),
threaded through build_context and retrieve_memories.
Memory holdback: a memory could summarize the just-generated turn; retry
rewrites Action.text but memory_cursor has already advanced, so the memory
was never regenerated and went on describing narration no longer in the
story. settled_story_actions() holds the newest action back one turn —
only the last action is retryable, so that makes it unreachable. The
settled list is always a prefix, so cursors stay valid and nothing is
skipped. The run_post_turn clamp deliberately still uses the full count:
clamping to settled rewinds legacy adventures a step and double-covers an
action.
Cursor bookkeeping: memory_cursor is a position into story_actions() while
Memory.source_* are Action.index values, and the two diverge as soon as
anything is deleted. Deleting a middle action slid a never-summarized
action into the covered range, skipping it forever; and pruning a memory
left the actions it covered stranded behind the cursor. Adds
note_action_removed() (called before the delete in delete_action and
undo_turn) and a rewind in prune_dangling_memories. delete_action also
now prunes at all, which it never did.
Not addressed: editing an already-summarized action still leaves its
memory stale, and the cumulative story summary can't have one fact
un-mixed from it.
117 backend tests pass, including new test_memory_settling.py (12) and
two retry-context regression tests.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UeQVy5bEjLhfgWNc27Efet
Retry used to delete the last AI action and generate a replacement, so the
discarded narration was simply gone. The row survives now: each attempt is
appended to actions.variants with variant_index naming the live one, and a
ChatGPT-style pager under the message browses them.
Action.text still mirrors the active variant, so the context builder, memory
bank, summarizer and export needed no changes. A variant carries only what
differs between attempts -- the text, the reasoning, and the state it
produced -- never the assembled prompt, which is identical across attempts of
one turn and is the bulk of context_snapshot.
Only the last message can be switched, restoring the script/world state that
attempt produced; earlier turns were written as a continuation of whatever is
active there, so theirs are read-only previews.
Three things that would otherwise bite:
- generate_turn now wraps _generate_turn and watches for a save sentinel. If
the generator ends without it (provider error, empty reply, script stop,
client hangup) it re-applies the previous variant -- otherwise a failed
retry leaves rolled-back stats under un-rolled-back text.
- Retry reuses the turn's own index rather than next_index, or the clock the
world-state cooldowns run on advances on a re-run of the same turn.
- Editing a message rewrites the active variant too, or paging away and back
silently reverts the edit.
Migrations 34/35 verified as an upgrade against a populated database, not
just a fresh schema. test_state_revert's retry test asserted the old delete
behaviour and was rewritten.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01UeQVy5bEjLhfgWNc27Efet
