ProfessorNovaandClaude Opus 5
784b76baf7
Self-hosted knowledge management for SMEs: a split-screen Markdown editor whose sections an LLM refines while you write, and RAG question answering over the documents that result. FastAPI + Postgres/pgvector on the back, SvelteKit on the front, everything OpenAI-compatible and self-hostable. Squashed into a single commit; the development history stays local. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CA43ZJda8Rbp2hKXNy8f6b
57 lines
2.0 KiB
Python
57 lines
2.0 KiB
Python
import uuid
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from typing import Any
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from sqlalchemy import Enum, ForeignKey, Text
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from sqlalchemy.dialects.postgresql import JSONB
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from sqlalchemy.orm import Mapped, mapped_column, relationship
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from app.models.base import Base, TimestampMixin, UUIDPrimaryKeyMixin
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from app.models.enums import ConversationMode, ConversationStatus, MessageRole
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class Conversation(UUIDPrimaryKeyMixin, TimestampMixin, Base):
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"""Chat thread. The only core mode is query (RAG Q&A); EE adds insight.
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Capture is no longer a conversation — it writes a Document directly (see
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app/authoring/) — so this table holds no per-turn engine state any more.
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"""
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__tablename__ = "conversations"
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mode: Mapped[ConversationMode] = mapped_column(
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Enum(ConversationMode, native_enum=False, length=32)
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)
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status: Mapped[ConversationStatus] = mapped_column(
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Enum(ConversationStatus, native_enum=False, length=32),
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default=ConversationStatus.active,
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)
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user_id: Mapped[uuid.UUID] = mapped_column(
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ForeignKey("users.id", ondelete="CASCADE"), index=True
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)
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messages: Mapped[list["Message"]] = relationship(
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back_populates="conversation",
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cascade="all, delete-orphan",
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order_by="Message.created_at",
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)
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class Message(UUIDPrimaryKeyMixin, TimestampMixin, Base):
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__tablename__ = "messages"
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conversation_id: Mapped[uuid.UUID] = mapped_column(
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ForeignKey("conversations.id", ondelete="CASCADE"), index=True
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)
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role: Mapped[MessageRole] = mapped_column(
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Enum(MessageRole, native_enum=False, length=32)
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)
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content: Mapped[str] = mapped_column(Text)
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# Assistant turns snapshot their citations here ({"sources": [...]}) so
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# they survive reload and re-indexing — chunks are disposable, the
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# rendered citation is not.
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meta: Mapped[dict[str, Any]] = mapped_column(
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JSONB, default=dict, server_default="{}"
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)
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conversation: Mapped[Conversation] = relationship(back_populates="messages")
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