update_world_state relied entirely on the DM remembering to call it —
no code checked whether it actually happened. Add refresh_if_due(),
called at the top of every DM turn: it counts messages since the
summary was last touched (by the tool or a prior auto-refresh), and
once AUTO_REFRESH_MESSAGE_THRESHOLD (10) is crossed, forces a
dedicated summarization call — a separate, tool-free completion whose
only job is to fold the new messages into the existing summary — and
persists the result directly, without waiting on the main DM turn's
discretion.
The trigger condition (message count) is deterministic; only the
summary text itself still needs an LLM, which is unavoidable for a
task that requires understanding, not just counting.
context.py gained count_messages_since() and build_transcript_text()
(an uncapped, since-filtered plain-text transcript for the
summarizer, as opposed to build_context()'s char-budget-capped chat
list for the main DM call) — factored out of the same underlying
message-labeling logic to avoid duplicating the name-resolution joins.
Verified with a fake LLM client: confirmed the trigger fires exactly
at the threshold and not before, resets after firing, and that the
second refresh's prompt carries the prior summary forward while only
including messages since that refresh (not the whole history again).
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Context was pure full-text replay of every message, capped at 40k
chars with oldest-dropped-first — no summarization/world-state layer,
as called out as still-missing in an earlier conversation.
Add a new update_world_state DM tool that persists a compact,
DM-authored recap (key NPCs, current location, open plot threads,
party/inventory state) to a new world_state table, one row per game.
It's injected into the system prompt every turn, ahead of the raw
message window. The DM is instructed to call it regularly — at every
scene change or major event, not just at the end — sending the full
current picture each time (matches the replace-not-merge pattern
already used for combat_stats/abilities/equipment).
Since the summary now backs up everything older, shrink the raw
message window from 40k to 16k chars — it's recent continuity now,
not the sole memory of the session. Full history remains available
via "Volltext laden" regardless, since that reads the messages table
directly rather than through this context builder.
Simplified from the original plan sketch (state JSONB) to a single
free-text summary field — natural-language recaps are something an
LLM authors well; a structured world model would need a schema the
DM would have to conform to for no real benefit here.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Only the player character's HP was tracked before, so a monster's
death was never detected — only the DM's own (unenforced) narration
of it. Add a new update_monster_hp tool the DM calls whenever an
NPC/monster is introduced or takes damage, stored as DM-only
bookkeeping on Game (never exposed via GameRead, since HP/AC of NPCs
is meant to stay secret from players). The tool reports back
"defeated": true once HP drops to 0 so the DM can react to it — but
unlike a character dying, this does NOT auto-end the session; whether
a monster's death should end the game is a separate decision left to
the DM's own end_game call, or to a future rule.
Building an isolated test for this caught a real bug along the way:
the update mutated the matched monster's dict in place before
reassigning the list, which made SQLAlchemy's old-vs-new JSONB
comparison see identical content and silently skip writing the
change. Fixed by building fresh dicts instead of mutating shared ones.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Games now have a status/ended_reason pair. The DM can call the new
end_game tool when the story reaches a real conclusion (victory,
defeat, or a resolved one-shot), and the backend independently ends
the game whenever a character's HP drops to 0 or below, regardless of
whether the DM narrates it. The frontend shows a banner and a
"Beendet" badge once a game ends.
HP moves from the freeform combat_stats bag into dedicated
current_hp/max_hp columns on Character, since reliably detecting 0 HP
requires a real integer rather than parsing strings like "3/10" out of
an LLM-authored key/value dict. Also fixed combat_stats to fully
replace on each upsert instead of merging, matching its documented
contract — the merge was leaving stale keys (old HP/TP text) behind
after the model stopped sending them.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
- Character sheets gain structured combat_stats, abilities (name +
plain-language explanation), and equipment fields, populated by the
upsert_character_sheet tool; the detail page renders them as their
own sections instead of one prose block, with a player-card-style
attribute grid (full ability names + modifiers).
- Fix double-escaped unicode occasionally left in tool-call JSON
arguments (a model quirk) and stop the app's own json.dumps calls
from re-introducing it (ensure_ascii=False).
- Render chat messages as markdown (react-markdown + Tailwind
typography) instead of raw text, and widen the games/characters/
chat layout to use more of the screen on desktop.
- Sharpen the DM system prompt: state the ability + DC for each
offered action option before the player commits, and narrate rolls
as DC → result → pass/fail before the story consequence; also stop
re-asking Session-0 questions already answered in the game's
name/description.
- Make the DM's LLM provider configurable (xai default, lmstudio for
a local OpenAI-compatible server via host.docker.internal) instead
of hardcoded to x.ai.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
RAG: switch Postgres to pgvector, chunk and embed the three D&D
rulebooks locally via sentence-transformers, and retrieve relevant
excerpts per DM turn (query = latest player message) to ground the
system prompt. Retrieval runs off the event loop and is capped by a
relevance threshold and a max character budget so it can't blow up
context size or cost.
Game setup wizard: creating a game now opens a short chat where the
DM asks about genre, length, and the player's experience level, then
proposes a name and description via a tool call. The player can edit
both before creating the game. Stateless endpoint — the frontend
carries the conversation, no DB needed since the game doesn't exist
yet.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
FastAPI + Postgres backend with fastapi-users auth, games/characters
CRUD, and a WebSocket chat endpoint where an x.ai Grok DM narrates
play, rolls dice, and maintains character sheets via tool calls.
React + Tailwind frontend covers registration/login, game list and
creation, participation-code join flow, character viewer, and a
real-time chat session view. Docker Compose skeleton (Postgres +
backend) included; Caddy/frontend container wiring is deferred to
the deploy milestone.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Thorsten