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interactive-story/backend/app/context/builder.py
T
parththakkar106andClaude Opus 5 7c538c8235 Stop retried and deleted actions from corrupting story context and memories
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
2026-08-03 15:23:59 +05:30

280 lines
12 KiB
Python

"""Context assembly per AI Dungeon's memory system
(help.aidungeon.com/faq/the-memory-system):
[AI Instructions] always included
[Plot Essentials] always included (classic "Memory")
[Story Summary] always included (manual in Phase 3, auto in Phase 6)
[Used Memories] top-K memory-bank retrievals (Phase 6, when enabled)
[Triggered Story Cards] "World Lore: <entry>", conditional; first dropped when over budget
[Story history] newest actions that fit the remaining token budget
[Author's Note] injected AUTHORS_NOTE_DEPTH actions before the end of history
[Latest player action] (+ script frontMemory right after it, Phase 4)
"""
import functools
from dataclasses import dataclass
import tiktoken
from .. import models, worldstate
AUTHORS_NOTE_DEPTH = 3 # actions from the end of history
CARD_BUDGET_SHARE = 0.4 # max share of non-reserved budget that story cards may take
SEPARATOR = "\n\n"
@functools.lru_cache(maxsize=1)
def _encoding() -> tiktoken.Encoding:
return tiktoken.get_encoding("cl100k_base")
def count_tokens(text: str) -> int:
return len(_encoding().encode(text))
def truncate_to_last_tokens(text: str, budget: int) -> str:
tokens = _encoding().encode(text)
if len(tokens) <= budget:
return text
return _encoding().decode(tokens[-budget:])
@dataclass
class Section:
label: str
text: str
@property
def tokens(self) -> int:
return count_tokens(self.text)
def _script_memory(adventure: models.Adventure) -> dict:
"""Script-provided memory overrides (populated by Phase 4 scripting)."""
state = adventure.script_state if isinstance(adventure.script_state, dict) else {}
memory = state.get("memory")
return memory if isinstance(memory, dict) else {}
def _history_text(action: models.Action) -> str:
"""An AI turn as the model should see it in replayed history: its narration
with the state block it emitted re-appended (reconstructed from the stored
delta). The block is stripped before storage/UI, so without this every past
AI turn would look like one that emitted nothing — biasing the model, by
imitation, to stop emitting too. Player turns and blockless turns are
returned unchanged."""
text = action.text
snap = action.context_snapshot if isinstance(action.context_snapshot, dict) else None
if snap:
ws = snap.get("world_state")
if isinstance(ws, dict):
block = worldstate.render_delta_block(ws.get("delta") or {})
if block:
text = f"{text}\n{block}"
return text
def story_actions(
adventure: models.Adventure, exclude_action_id: int | None = None
) -> list[models.Action]:
"""The adventure's non-empty actions, as the model should see them.
`exclude_action_id` drops one action from the story — used by retry, where
the row being regenerated is still attached to the adventure (it holds the
variant history) but must not appear in the context assembled to replace it.
"""
return [
a for a in adventure.actions
if a.text.strip() and (exclude_action_id is None or a.id != exclude_action_id)
]
def _visible_npcs(actions: list[models.Action], stat_schema: dict) -> dict[str, str]:
"""Defined NPCs whose trigger words appear in the recent story — the ones
"in scene", so only their stats get injected. Maps npc id -> display name."""
recent = SEPARATOR.join(a.text for a in actions[-6:]).lower()
visible: dict[str, str] = {}
for npc_key, ndef in (stat_schema.get("npcs") or {}).items():
if not isinstance(ndef, dict):
continue
if any(trigger in recent for trigger in worldstate.npc_triggers(ndef, npc_key)):
visible[npc_key] = worldstate.npc_name(ndef, npc_key)
return visible
def _match_cards(cards: list[models.StoryCard], window_text: str) -> list[dict]:
"""AI Dungeon trigger rules: case-insensitive, space-sensitive, partial-word
('boat' triggers on 'boats'). Returns one record per card with the keyword that fired."""
haystack = window_text.lower()
matched = []
for card in cards:
for key in (k.strip().lower() for k in card.keys.split(",")):
if key and key in haystack:
matched.append(
{"id": card.id, "name": card.name, "keyword": key, "entry": card.entry}
)
break
return matched
def build_context(
adventure: models.Adventure,
settings: models.Settings,
memory_bank: dict | None = None,
exclude_action_id: int | None = None,
) -> tuple[str, str, dict]:
"""Returns (system_text, story_text, context_report). `memory_bank` is the
result of memorybank.retrieve_memories (None when the bank is off);
`exclude_action_id` omits one action from the story (see story_actions)."""
script_mem = _script_memory(adventure)
actions = story_actions(adventure, exclude_action_id)
# ----- Always-included components -----
system_sections: list[Section] = [Section("narrator", settings.narrator_prompt.strip())]
# RPG world state (Phase 12): current stats/milestones + how to report changes.
stat_schema = adventure.scenario.stat_schema if adventure.scenario else None
has_ws = worldstate.has_schema(stat_schema)
if has_ws:
guide = worldstate.render_reference(stat_schema)
if guide:
system_sections.append(Section("world_state_guide", guide))
block = worldstate.render_state_section(
adventure.world_state, stat_schema, _visible_npcs(actions, stat_schema)
)
if block:
system_sections.append(Section("world_state", block))
system_sections.append(Section("world_state_rule", worldstate.EMIT_RULE))
if isinstance(script_mem.get("context"), str) and script_mem["context"].strip():
system_sections.append(Section("script_context", script_mem["context"].strip()))
if adventure.ai_instructions.strip():
system_sections.append(Section("ai_instructions", adventure.ai_instructions.strip()))
if adventure.memory.strip():
system_sections.append(
Section("plot_essentials", f"Plot essentials:\n{adventure.memory.strip()}")
)
if adventure.story_summary.strip():
system_sections.append(
Section("story_summary", f"Story summary:\n{adventure.story_summary.strip()}")
)
if memory_bank and memory_bank.get("used"):
lines = "\n".join(f"- {m['text']}" for m in memory_bank["used"])
system_sections.append(Section("used_memories", f"Memories:\n{lines}"))
authors_note_text = adventure.authors_note.strip()
if isinstance(script_mem.get("authorsNote"), str) and script_mem["authorsNote"].strip():
authors_note_text = script_mem["authorsNote"].strip()
authors_note = f"[Author's note: {authors_note_text}]" if authors_note_text else ""
front_memory = ""
if isinstance(script_mem.get("frontMemory"), str):
front_memory = script_mem["frontMemory"].strip()
reserved = (
sum(s.tokens for s in system_sections)
+ count_tokens(authors_note)
+ count_tokens(front_memory)
+ (count_tokens(worldstate.EMIT_REMINDER) if has_ws else 0)
)
available = max(256, settings.context_token_budget - reserved)
# ----- Story cards: triggered by recent story text (the window history could fill) -----
trigger_window = truncate_to_last_tokens(SEPARATOR.join(a.text for a in actions), available)
triggered = _match_cards(adventure.story_cards, trigger_window)
card_budget = int(available * CARD_BUDGET_SHARE)
card_records = []
lore_lines: list[str] = []
used = 0
for match in triggered:
line = f"World Lore: {match['entry'].strip()}"
tokens = count_tokens(line)
included = used + tokens <= card_budget
if included:
lore_lines.append(line)
used += tokens
card_records.append(
{"id": match["id"], "name": match["name"], "keyword": match["keyword"],
"included": included}
)
if lore_lines:
system_sections.append(Section("world_lore", "\n".join(lore_lines)))
# ----- Story history: newest first until the remaining budget is spent -----
history_budget = available - used
included_actions: list[models.Action] = []
spent = 0
oldest_truncated = False
for action in reversed(actions):
# Budget on the text as it will actually appear — with the re-attached
# state block (B) when this adventure tracks world state.
rendered = _history_text(action) if has_ws else action.text
tokens = count_tokens(rendered) + count_tokens(SEPARATOR)
if spent + tokens > history_budget:
if not included_actions:
# Even the newest action alone is over budget: hard-truncate it.
included_actions.append(
models.Action(
adventure_id=action.adventure_id, index=action.index,
type=action.type,
text=truncate_to_last_tokens(action.text, history_budget),
)
)
oldest_truncated = True
break
included_actions.append(action)
spent += tokens
included_actions.reverse()
# ----- Assemble story text with author's note near the end -----
# Re-attach each AI turn's state block (stripped before storage) so recent
# history shows the model its own emit pattern to imitate.
texts = [_history_text(a) if has_ws else a.text for a in included_actions]
note_sections: list[Section] = []
if authors_note:
pos = max(0, len(texts) - AUTHORS_NOTE_DEPTH)
before, after = texts[:pos], texts[pos:]
if before:
note_sections.append(Section("history", SEPARATOR.join(before)))
note_sections.append(Section("authors_note", authors_note))
note_sections.append(Section("recent_history", SEPARATOR.join(after)))
else:
note_sections.append(Section("history", SEPARATOR.join(texts)))
if front_memory:
note_sections.append(Section("front_memory", front_memory))
if has_ws:
# Terminal reminder: the emit rule sits up in the system block, far from
# where the model generates; repeat it last, in the strongest recency slot.
note_sections.append(Section("world_state_reminder", worldstate.EMIT_REMINDER))
story_sections = [s for s in note_sections if s.text]
system_text = SEPARATOR.join(s.text for s in system_sections if s.text)
story_text = SEPARATOR.join(s.text for s in story_sections)
all_sections = [s for s in system_sections if s.text] + story_sections
report = {
"sections": [
{"label": s.label, "text": s.text, "tokens": s.tokens} for s in all_sections
],
"prompt": {"system": system_text, "story": story_text},
"tokens": {
"total": count_tokens(system_text) + count_tokens(story_text),
"budget": settings.context_token_budget,
},
"cards": card_records,
"memories": memory_bank,
"history": {
"included": len(included_actions),
"total": len(actions),
"oldest_truncated": oldest_truncated,
},
"settings": {
"model": settings.model,
"api_mode": settings.api_mode,
"temperature": settings.temperature,
"max_output_tokens": settings.max_output_tokens,
},
}
return system_text, story_text, report