feat(briefing): cache + map-reduce article context for rich discuss chats

The Discuss button on news cards was producing one-shot replies because
the model got the whole trafilatura blob dropped into history with a
canned "summarize and discuss this article" prompt — no length guard, no
prep, no invitation to converse. Large articles got silently truncated by
Ollama; small articles got a tepid reply.

This reworks discuss_article around a three-layer cache:

  context_prepared  →  content_full  →  fresh trafilatura fetch

First click on a small article fetches once, writes through to both
caches, and passes the body straight into the synthetic read_article
tool-result. First click on a large article additionally runs a parallel
map step (services/article_context.py) that chunks the body on paragraph
boundaries, summarizes each ~8k chunk to ~300 words of dense factual
prose via the background model, and concatenates the summaries under
section headers — all pinned to num_ctx=16384 so the map step doesn't
itself fall victim to silent truncation. Repeat clicks on either path
skip straight to the chat turn.

The canned summary prompt is replaced with a conversational seed that
invites the user into an actual discussion rather than a one-shot
synopsis, matching the goal of "have a conversation about an article,
not just read it."

discuss_topic is intentionally left untouched — it's the multi-article
aggregation path and needs a separate rework. Follow-up task will decide
whether to retire it or rework it on the cached-context approach.

Closes task #106.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

src/fabledassistant/models/rss_feed.py

@@ -46,6 +46,17 @@ class RssItem(Base):
     published_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
     # Truncated to 2000 chars to keep DB size reasonable
     content: Mapped[str] = mapped_column(Text, default="")
+    # Full trafilatura-extracted article body, populated lazily on first
+    # discuss-click / enrichment pass. Nullable — most items never get this
+    # cached. Expires naturally with the item (90-day retention).
+    content_full: Mapped[str | None] = mapped_column(Text, nullable=True)
+    # Map-reduced conversation-ready context derived from content_full. See
+    # services/article_context.py — populated on first discuss click so
+    # repeat clicks skip both the fetch and the LLM map step.
+    context_prepared: Mapped[str | None] = mapped_column(Text, nullable=True)
+    content_fetched_at: Mapped[datetime | None] = mapped_column(
+        DateTime(timezone=True), nullable=True
+    )
     fetched_at: Mapped[datetime] = mapped_column(
         DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
     )