parththakkar106andClaude Fable 5
db9f904222
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01KFsGHju9szibJJa2YJcdbg
48 lines
2.8 KiB
Markdown
48 lines
2.8 KiB
Markdown
# Phase 6 — Auto Summarization + Memory Bank (optional)
|
||
|
||
**Goal:** replicate modern AI Dungeon's Memory System (per
|
||
help.aidungeon.com/faq/the-memory-system): AI-generated memories, a running Story Summary, and
|
||
embedding-based retrieval. This phase makes extra AI calls (summarization + embeddings), so it is
|
||
opt-in per adventure and gated on the endpoint supporting it.
|
||
|
||
## Auto Summarization
|
||
|
||
- [x] **Memories**: every 6 actions (starting at action 12), summarize that block of
|
||
player actions + AI responses into a short "memory" via a background AI call
|
||
(same provider, cheap/configurable model override).
|
||
- [x] **Story Summary**: every 15 actions, update the Story Summary plot component — a running
|
||
overview of the plot — folding in recent memories; compress it when it grows too long.
|
||
- [x] Story Summary stays **manually editable**; user edits inform future updates
|
||
(they are the base text for the next summarization pass) but are never overwritten silently.
|
||
- [x] Summarization failures are non-fatal: log, retry next interval.
|
||
(Failed calls appear on the debug page; cursors only advance on success, so the
|
||
next turn retries. Implementation: `backend/app/memorybank.py`.)
|
||
|
||
## Memory Bank
|
||
|
||
- [x] Store each memory with an **embedding vector** (OpenAI-compatible `/v1/embeddings`;
|
||
embedding model configurable in Settings; feature disabled if unavailable).
|
||
- [x] Each turn, embed the recent story text and rank memories by cosine similarity;
|
||
inject the top-K "Used Memories" into context as their own component
|
||
(between Story Summary and story cards in the layout). Pinned memories are always
|
||
included; top-K is a setting (default 5).
|
||
- [x] Configurable bank capacity (AI Dungeon tiers: 25–400; ours: a setting, default 200);
|
||
when full, evict least-recently-used/least-retrieved memories ("Forgotten Memories").
|
||
- [x] SQLite storage for vectors (JSON blob + in-memory cosine ranking — pure Python,
|
||
no numpy needed at this scale).
|
||
|
||
## UI
|
||
|
||
- [x] Memory Bank panel: list memories (used / idle / forgotten), edit or delete, pin favorites,
|
||
see which memories were retrieved for a given turn (🔍 on an AI action → Insights snapshot).
|
||
- [x] Insights integration: retrieved memories shown as a context section with similarity scores.
|
||
- [x] Adventure settings: toggle auto-summarization / memory bank (per adventure, in the Memory
|
||
panel); summary + embedding models are chosen globally in Settings (deliberate
|
||
simplification — one endpoint config for the whole app).
|
||
|
||
## Exit criteria
|
||
|
||
Play a 40+ action adventure: memories appear every 6 actions, the Story Summary updates every 15,
|
||
an early-game fact that scrolled out of the raw history gets retrieved via the Memory Bank when it
|
||
becomes relevant again, and Insights shows exactly which memories were injected and why.
|