bvandeusen
a773c11aa0
- Embed RSS items at fetch time (nomic-embed-text); backfill at startup
- Semantic news search injected into chat system prompt ("Recent News You've Seen")
when items match query above 0.55 cosine threshold (independent of note RAG)
- "Discuss in chat" button on news cards — creates a seeded conversation with
the article title + full content, navigates directly to the new chat
- Briefing compilation now passes 500-char article excerpts (not just headlines)
to the LLM and uses 8192 num_ctx to accommodate the larger prompt
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
26 lines
832 B
Python
26 lines
832 B
Python
from datetime import datetime, timezone
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from sqlalchemy import DateTime, ForeignKey, Integer
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from sqlalchemy.dialects.postgresql import JSONB
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from sqlalchemy.orm import Mapped, mapped_column
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from fabledassistant.models import Base
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class RssItemEmbedding(Base):
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"""Stores the embedding vector for an RSS item, used for semantic news search."""
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__tablename__ = "rss_item_embeddings"
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rss_item_id: Mapped[int] = mapped_column(
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Integer,
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ForeignKey("rss_items.id", ondelete="CASCADE"),
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primary_key=True,
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)
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user_id: Mapped[int] = mapped_column(Integer, nullable=False, index=True)
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embedding: Mapped[list] = mapped_column(JSONB, nullable=False)
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updated_at: Mapped[datetime] = mapped_column(
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DateTime(timezone=True),
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default=lambda: datetime.now(timezone.utc),
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)
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