refactor: hard-cut RSS infrastructure (scope C)

Removes the entire RSS feature surface — feeds, items, embeddings, reactions,
discussion-note flow, briefing news context, settings, env-vars, and DB
tables. Keeps the URL-generic article-reader (the read_article LLM tool)
under a clean module so the LLM can still fetch arbitrary article content
from URLs the user provides.

Backend:
- New services/article_fetcher.py — single source of trafilatura URL→text
- New services/tools/article.py — read_article tool (was nested under tools/rss)
- Delete services/rss.py, rss_classifier.py, rss_filtering.py, article_context.py
- Delete services/tools/rss.py
- Delete models/rss_feed.py (RssFeed, RssItem), models/rss_item_embedding.py
- services/embeddings.py: drop upsert/semantic_search/backfill RSS helpers
- services/llm.py: remove _build_briefing_article_context, briefing-conv branch,
  ARTICLE_DISCUSS_SEED skip-RAG branch; drop get_rss_items / add_rss_feed from
  the actions list
- services/generation_task.py: drop _maybe_save_article_discussion_note + caller
- routes/chat.py: drop /api/chat/from-article/<id> endpoint
- routes/journal.py: re-import via web.py refactor (article_fetcher path)
- services/tools/__init__.py: register `article`, drop `rss`
- services/tools/_registry.py: drop the requires=='rss' check
- app.py: drop backfill_rss_item_embeddings + backfill_rss_article_content tasks
- config.py: prose-only edit (no env var change — RSS env vars were never first-class)

Frontend:
- stores/settings.ts: drop rssEnabled
- SettingsView.vue: drop the RSS-classification mention
- api/client.ts: drop openArticleInChat (the from-article endpoint is gone)

Tests:
- Delete tests/test_rss_service.py, test_news_api.py, test_article_reading.py

Migration:
- 0042_drop_rss: DROP TABLE rss_item_embeddings, rss_item_reactions, rss_items,
  rss_feeds; DELETE settings rows for rss_enabled / briefing_*_topics

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

frontend/src/api/client.ts

@@ -415,12 +415,6 @@ export async function deleteJournalMoment(id: number): Promise<void> {
   await apiDelete(`/api/journal/moments/${id}`);
 }
 
-export async function openArticleInChat(
-  itemId: number,
-): Promise<{ conversation_id: number; assistant_message_id?: number; status?: string }> {
-  return apiPost(`/api/chat/from-article/${itemId}`, {});
-}
-
 export async function geocodeAddress(address: string): Promise<{ lat: number; lon: number; display_name: string } | null> {
   try {
     const r = await apiPost<{ lat: number; lon: number; label: string }>('/api/journal/weather/geocode', { query: address });

frontend/src/stores/settings.ts

@@ -16,10 +16,6 @@ export const useSettingsStore = defineStore("settings", () => {
     () => settings.value.default_model || ""
   );
 
-  const rssEnabled = computed(
-    () => settings.value.rss_enabled === "true"
-  );
-
   // Voice status — checked once on login, refreshable from Settings
   const voiceEnabled = ref(false);
   const voiceSttReady = ref(false);
@@ -66,7 +62,6 @@ export const useSettingsStore = defineStore("settings", () => {
     loading,
     assistantName,
     defaultModel,
-    rssEnabled,
     voiceEnabled,
     voiceSttReady,
     voiceTtsReady,

frontend/src/views/SettingsView.vue

@@ -1368,7 +1368,7 @@ function formatUserDate(iso: string): string {
               <option v-for="m in installedModels" :key="m" :value="m">{{ m }}</option>
             </select>
             <p class="field-hint">
-              Model used for background tasks: title generation, tag suggestions, project summaries, and RSS classification.
+              Model used for background tasks: title generation, tag suggestions, and project summaries.
               Using a small dedicated model (e.g. qwen2.5:0.5b) keeps the chat model's KV cache warm between messages, significantly reducing response time.
               <span v-if="backgroundModel && backgroundModel === (defaultModel || defaultChatModel)" class="field-hint-warn">
                 ⚠ Setting this to the same model as Chat Model will wipe the KV cache after every background task, increasing response latency.