feat(rag): lite-model document summaries — non-markdown docs summarized at import, summary chunk retrieves and resolves to the full source doc

app/models.py

@@ -50,6 +50,12 @@ class Document(Base):
     content: Mapped[str] = mapped_column(Text)  # full markdown — the RAG context
     content_hash: Mapped[str] = mapped_column(String(64), index=True)  # sha256 for change detection
     indexed_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), server_default=func.now())
+    #: Lite-model summary, phase 30. Natural-language summary of the
+    #: document (non-markdown A9 docs only, generated at import time by the
+    #: aipi ``lite`` model). NULL for markdown docs, pre-phase-30 rows, and
+    #: the fail-soft path where summary generation failed but the document
+    #: was still indexed.
+    summary: Mapped[str | None] = mapped_column(Text, default=None)
 
     chunks: Mapped[list[Chunk]] = relationship(
         back_populates="document", cascade="all, delete-orphan"
@@ -66,6 +72,10 @@ class Chunk(Base):
     position: Mapped[int] = mapped_column(Integer)
     content: Mapped[str] = mapped_column(Text)
     embedding: Mapped[list[float] | None] = mapped_column(Vector(EMBEDDING_DIM))
+    #: Summary chunk, position −1, phase 30. Marks the single extra embedded
+    #: chunk mirroring ``Document.summary``; default False keeps every
+    #: pre-phase-30 row (and ordinary content chunks) valid.
+    is_summary: Mapped[bool] = mapped_column(Boolean, default=False)
 
     document: Mapped[Document] = relationship(back_populates="chunks")