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>
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@@ -507,81 +507,3 @@ async def delete_model_route():
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return jsonify({"error": str(e)}), 500
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@chat_bp.route("/from-article/<int:item_id>", methods=["POST"])
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@login_required
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async def create_conversation_from_article(item_id: int):
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"""Create a chat conversation seeded for article discussion and auto-run.
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Mirrors the briefing ``discuss_article`` route: creates a fresh
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conversation, stages the shared synthetic read_article exchange + seed
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prompt, then kicks off generation so the client lands on an in-flight
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stream. The Flutter and web chat screens reconnect to the running buffer
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on mount.
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"""
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from sqlalchemy import select as _select
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from fabledassistant.models import async_session as _async_session
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from fabledassistant.models.rss_feed import RssItem, RssFeed
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from fabledassistant.services.article_context import (
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EmptyArticleError,
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seed_article_discussion,
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)
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uid = get_current_user_id()
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async with _async_session() as session:
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result = await session.execute(
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_select(RssItem)
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.join(RssFeed, RssItem.feed_id == RssFeed.id)
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.where(RssItem.id == item_id, RssFeed.user_id == uid)
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)
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item = result.scalars().first()
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if item is None:
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return jsonify({"error": "Article not found"}), 404
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conv_title = (item.title or "Article discussion")[:80]
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conv = await create_conversation(uid, title=conv_title, conversation_type="chat")
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model = await get_setting(uid, "default_model", "") or Config.OLLAMA_MODEL
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try:
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discuss_prompt = await seed_article_discussion(conv.id, item, model)
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except EmptyArticleError as e:
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# Roll back the empty conversation so the user doesn't end up with a
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# phantom entry in their chat list.
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try:
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await delete_conversation(uid, conv.id)
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except Exception:
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logger.warning("Failed to clean up empty article conversation %s", conv.id)
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return jsonify({"error": str(e)}), 422
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# Reload conversation so we see the two messages the helper just added.
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conv = await get_conversation(uid, conv.id)
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assert conv is not None
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history: list[dict] = []
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for msg in conv.messages:
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if msg.role == "system":
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continue
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msg_dict: dict = {"role": msg.role, "content": msg.content or ""}
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if msg.tool_calls:
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msg_dict["tool_calls"] = [
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{"function": {"name": tc["function"], "arguments": tc["arguments"]}}
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for tc in msg.tool_calls
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]
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history.append(msg_dict)
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for tc in msg.tool_calls:
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history.append({"role": "tool", "content": json.dumps(tc.get("result", {}))})
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else:
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history.append(msg_dict)
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assistant_msg = await add_message(conv.id, "assistant", "", status="generating")
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buf = create_buffer(conv.id, assistant_msg.id)
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asyncio.create_task(run_generation(
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buf, history, model, uid, conv.id, conv.title or "", discuss_prompt,
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))
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return jsonify({
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"conversation_id": conv.id,
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"assistant_message_id": assistant_msg.id,
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"status": "generating",
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}), 202
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