Thorsten
419f5e3a89
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>
8 lines
305 B
Python
8 lines
305 B
Python
from app.models.character import Character
|
|
from app.models.game import Game, GameParticipant
|
|
from app.models.message import Message
|
|
from app.models.rulebook_chunk import RulebookChunk
|
|
from app.models.user import User
|
|
|
|
__all__ = ["User", "Game", "GameParticipant", "Character", "Message", "RulebookChunk"]
|