Preserve news query intent and extract nonduplicated semantic page content

services/search/content.py

@@ -233,7 +233,7 @@ def fetch_webpage_content(url: str, timeout: int = 5, retry_attempt: int = 0,
     effective_cap = min(max_bytes or WEB_FETCH_SOFT_MAX_BYTES, WEB_FETCH_HARD_MAX_BYTES)
     # The cap is part of the cache identity: a truncated soft-cap fetch must
     # not be served to a later full-budget request for the same URL.
-    cache_key = generate_cache_key(f"{url}#cap={effective_cap}")
+    cache_key = generate_cache_key(f"{url}#cap={effective_cap}#extract=semantic-v2")
     cache_file = CONTENT_CACHE_DIR / f"{cache_key}.cache"
 
     # Check cache
@@ -398,15 +398,26 @@ def fetch_webpage_content(url: str, timeout: int = 5, retry_attempt: int = 0,
     js_rendered = _detect_js_frameworks(soup)
     js_message = "Page appears to be rendered by a JavaScript framework; content may be incomplete." if js_rendered else ""
 
-    # Main textual content (heuristic): prefer semantic / "content"-classed
+    # Prefer semantic containers even without CSS classes. Work on a copy so
-    # containers to skip nav/footer/boilerplate; tuned for article pages.
+    # lists/tables and metadata extraction below still see the original DOM.
+    text_soup = copy.copy(soup)
+    for noise in text_soup.select('script, style, noscript, template, nav, footer, aside, [role="navigation"], [role="banner"], [role="contentinfo"]'):
+        noise.extract()
     main_content = ""
-    content_areas = soup.find_all(
+    semantic_main = text_soup.find('main') or text_soup.find(attrs={'role': 'main'})
-        ["main", "article", "section", "div"],
+    content_areas = [semantic_main] if semantic_main else text_soup.find_all('article')
-        class_=re.compile("content|main|body|article|post|entry|text", re.I),
+    if not content_areas:
-    )
+        content_areas = text_soup.find_all(
+            ["section", "div"],
+            class_=re.compile("content|main|body|article|post|entry|text", re.I),
+        )
+    # Ancestor and child matches contain the same text. Emit each subtree once,
+    # while retaining separate sibling articles/cards.
+    candidate_ids = {id(area) for area in content_areas}
+    content_areas = [area for area in content_areas
+                     if not any(id(parent) in candidate_ids for parent in area.parents)]
     if content_areas:
-        for area in content_areas[:3]:
+        for area in content_areas:
             main_content += area.get_text(separator=" ", strip=True) + " "
     main_content = re.sub(r"\s+", " ", main_content).strip()
 
@@ -414,8 +425,8 @@ def fetch_webpage_content(url: str, timeout: int = 5, retry_attempt: int = 0,
     # obvious boilerplate stripped so UI/deep-research search results do not
     # look empty for app/landing pages.
     THIN_CONTENT_CHARS = 600
-    if len(main_content) < THIN_CONTENT_CHARS:
+    if len(main_content) < THIN_CONTENT_CHARS and not semantic_main:
-        body = soup.find("body")
+        body = text_soup.find("body")
         if body:
             body_copy = copy.copy(body)
             for noise in body_copy.find_all(

src/clean_agent_preview.py

@@ -3458,6 +3458,11 @@ def preserve_requested_web_recency(name, args, *, user_text='', prior_search_int
         if not query:
             return args
     normalized = dict(args)
+    # Keep the user's explicit news intent when a model rewrites it to a
+    # subject plus "today". Freshness alone does not select the news vertical.
+    if (re.search(r'\b(?:news|neews|headlines)\b', user, re.I)
+            and not re.search(r'\b(?:news|headlines)\b', query, re.I)):
+        query += ' news'
     current_year = datetime.now(timezone.utc).year
     current_intent = bool(re.search(
         r"\b(?:latest|recent|current|today(?:'s)?|news|updates?|"

tests/test_search_content_extraction_parity.py

@@ -36,6 +36,23 @@ class _FakeErrorResponse:
         )
 
 
+@pytest.mark.parametrize('wrapper', ['main', 'article', 'div class="content"'])
+def test_extraction_does_not_repeat_nested_content_or_include_navigation(wrapper, tmp_path, monkeypatch):
+    closing = wrapper.split()[0]
+    html = (f'<html><body><nav>{"Navigation item " * 100}</nav><{wrapper}>'
+            '<header>Article title and publication date</header>'
+            '<div class="article-body"><div class="entry-content">'
+            '<p>Unique substantive evidence.</p></div></div>'
+            f'</{closing}><footer>Unrelated links</footer></body></html>')
+    monkeypatch.setattr(service_content, 'CONTENT_CACHE_DIR', tmp_path)
+    monkeypatch.setattr(service_content, '_get_public_url', lambda *a, **k: _FakeResponse(html))
+    result = service_content.fetch_webpage_content('https://example.com/nested')
+    assert result['content'].count('Unique substantive evidence.') == 1
+    assert 'Navigation item' not in result['content']
+    assert 'Unrelated links' not in result['content']
+    assert 'Article title' in result['content']
+
+
 @pytest.mark.parametrize("module", [service_content])
 def test_content_fetcher_extracts_og_image_and_body_fallback(module, tmp_path, monkeypatch):
     html = """

tests/test_search_observation_budget.py

@@ -1,4 +1,13 @@
 from src.clean_agent_preview import preview_tool_result_text
+from src.clean_agent_preview import preserve_requested_web_recency
+
+
+def test_news_intent_survives_query_rewording_without_changing_other_fresh_queries():
+    result = preserve_requested_web_recency('web_search', {'query': 'artificial intelligence today'}, user_text='ai news today')
+    assert result['query'] == 'artificial intelligence today news'
+    assert result['time_filter'] == 'day'
+    result = preserve_requested_web_recency('web_search', {'query': 'current browser privacy features'}, user_text='compare current browser privacy features')
+    assert result['query'] == 'current browser privacy features'
 
 
 def test_all_fetched_sources_survive_observation_budget():