fix: relevance scoring per topic + URL keyword filter for child pages
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processor.py: simplify _score_quality prompt to single axis — "how relevant is this text to topic X?" — instead of averaging relevance + density + credibility, which let off-topic but well-written content pass through exhaustive.py: pre-compute topic keywords (stopword-filtered) at scraper init; filter child URLs (discovered during crawl, depth>0) to only add ones whose URL path or title contains a topic keyword; seed URLs (depth=0, from DDG/Wikipedia/Reddit) are always included since those searches are already topic-scoped Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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co-authored by
Claude Sonnet 4.6
parent
0c7176dd0b
commit
f7d62345b8
+37
-11
@@ -90,6 +90,14 @@ class ExhaustiveScraper:
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Keeps expanding until saturation or limits hit.
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"""
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# Common stopwords to ignore when extracting topic keywords
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_STOPWORDS = {
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'the','a','an','and','or','of','in','on','at','to','for','is','are','was',
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'were','be','been','have','has','had','do','does','did','about','with','from',
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'el','la','los','las','de','del','en','un','una','y','o','que','se','por',
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'con','para','sobre','como','pero','más',
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}
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def __init__(self, db: ResearchDB, session_id: int, topic: str,
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progress_callback=None):
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self.db = db
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@@ -100,6 +108,18 @@ class ExhaustiveScraper:
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self.total_sources = 0
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self._stop = False
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self._http: Optional[aiohttp.ClientSession] = None
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# Pre-compute topic keywords for child-URL relevance filtering
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self._keywords = [
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w for w in re.findall(r'\b\w{3,}\b', topic.lower())
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if w not in self._STOPWORDS
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]
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def _url_is_relevant(self, url: str, title: str = "") -> bool:
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"""True if URL path or title contains at least one topic keyword."""
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if not self._keywords:
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return True
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text = (urlparse(url).path + " " + (title or "")).lower()
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return any(kw in text for kw in self._keywords)
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async def stop(self):
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self._stop = True
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@@ -300,13 +320,16 @@ class ExhaustiveScraper:
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content, title = await self._extract_youtube(url)
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elif source_type == "wikipedia":
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content, title, new_urls = await self._extract_wikipedia(url)
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added = 0
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for new_url in (new_urls or []):
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await self.db.add_source(
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self.session_id, new_url, "wikipedia",
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depth=source["depth"] + 1
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)
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if self._url_is_relevant(new_url):
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await self.db.add_source(
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self.session_id, new_url, "wikipedia",
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depth=source["depth"] + 1
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)
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added += 1
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await self._mark_scraped(source_id, content, title, url)
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return len(new_urls or [])
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return added
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elif source_type == "reddit":
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content, title = await self._extract_reddit(url)
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# Small delay between Reddit requests to avoid rate limiting
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@@ -315,14 +338,17 @@ class ExhaustiveScraper:
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content, title = await self._extract_pdf(url)
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else:
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content, title, new_urls = await self._extract_web(url, source["depth"])
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added = 0
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for new_url in (new_urls or []):
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await self.db.add_source(
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self.session_id, new_url,
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detect_source_type(new_url),
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depth=source["depth"] + 1
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)
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if self._url_is_relevant(new_url):
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await self.db.add_source(
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self.session_id, new_url,
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detect_source_type(new_url),
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depth=source["depth"] + 1
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)
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added += 1
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await self._mark_scraped(source_id, content, title, url)
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return len(new_urls or [])
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return added
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await self._mark_scraped(source_id, content, title, url)
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return 0
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