feat(briefing): add rss_classifier service for LLM-based topic tagging

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

tests/test_rss_service.py

@@ -40,3 +40,91 @@ def test_extract_item_prefers_content_over_summary():
     entry.published_parsed = None
     item = extract_item(entry)
     assert item["content"] == "Full content here"
+
+
+@pytest.mark.asyncio
+async def test_classify_items_batch_returns_topic_map():
+    """classify_items_batch should return a dict mapping item_id to topic list."""
+    from unittest.mock import AsyncMock
+    from fabledassistant.services.rss_classifier import classify_items_batch
+
+    fake_response = '{"1": ["technology", "ai"], "2": ["politics"]}'
+
+    with patch(
+        "fabledassistant.services.rss_classifier._llm_classify",
+        new_callable=AsyncMock,
+        return_value=fake_response,
+    ):
+        items = [
+            {"id": 1, "title": "OpenAI releases GPT-5", "content": "..."},
+            {"id": 2, "title": "EU passes new law", "content": "..."},
+        ]
+        result = await classify_items_batch(items, user_include_topics=[])
+        assert result[1] == ["technology", "ai"]
+        assert result[2] == ["politics"]
+
+
+@pytest.mark.asyncio
+async def test_classify_items_batch_handles_llm_failure():
+    """classify_items_batch should return empty dict on LLM error."""
+    from unittest.mock import AsyncMock
+    from fabledassistant.services.rss_classifier import classify_items_batch
+
+    with patch(
+        "fabledassistant.services.rss_classifier._llm_classify",
+        new_callable=AsyncMock,
+        side_effect=Exception("LLM unavailable"),
+    ):
+        items = [{"id": 5, "title": "Some news", "content": ""}]
+        result = await classify_items_batch(items, user_include_topics=[])
+        assert result == {}
+
+
+def test_score_rss_items_excludes_blacklisted_topics():
+    """Items with excluded topics should be removed."""
+    from fabledassistant.services.briefing_preferences import score_and_filter_items
+
+    items = [
+        {"id": 1, "title": "Tech news", "topics": ["technology"], "published_at": "2026-03-25T08:00:00"},
+        {"id": 2, "title": "Sports score", "topics": ["sports"], "published_at": "2026-03-25T08:00:00"},
+    ]
+    result = score_and_filter_items(
+        items,
+        include_topics=["technology"],
+        exclude_topics=["sports"],
+        topic_scores={},
+        max_items=10,
+    )
+    ids = [r["id"] for r in result]
+    assert 1 in ids
+    assert 2 not in ids
+
+
+def test_score_rss_items_boosts_included_topics():
+    """Items matching include_topics should rank higher than neutral items."""
+    from fabledassistant.services.briefing_preferences import score_and_filter_items
+
+    items = [
+        {"id": 1, "title": "Random news", "topics": ["other"], "published_at": "2026-03-25T07:00:00"},
+        {"id": 2, "title": "Tech news", "topics": ["technology"], "published_at": "2026-03-25T06:00:00"},
+    ]
+    result = score_and_filter_items(
+        items,
+        include_topics=["technology"],
+        exclude_topics=[],
+        topic_scores={},
+        max_items=10,
+    )
+    assert result[0]["id"] == 2
+
+
+def test_score_rss_items_no_preferences_returns_all():
+    """With no preferences, all items should be returned sorted by recency."""
+    from fabledassistant.services.briefing_preferences import score_and_filter_items
+
+    items = [
+        {"id": 1, "title": "A", "topics": [], "published_at": "2026-03-24T10:00:00"},
+        {"id": 2, "title": "B", "topics": [], "published_at": "2026-03-25T10:00:00"},
+    ]
+    result = score_and_filter_items(items, [], [], {}, max_items=10)
+    assert result[0]["id"] == 2  # Newer first