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>
17 lines
312 B
Python
17 lines
312 B
Python
from pydantic import BaseModel
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class GameSetupChatRequest(BaseModel):
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messages: list[dict] = []
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class GameSetupProposal(BaseModel):
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name: str
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description: str
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class GameSetupChatResponse(BaseModel):
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messages: list[dict]
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assistant_text: str | None
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proposal: GameSetupProposal | None
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