Productize VedAstro user range scan entry
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732642856
@@ -80,9 +80,9 @@ OFFICIAL_SEARCH_EVENTS_ENDPOINT_PATH = "/Calculate/SearchEvents"
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OFFICIAL_SEARCH_EVENTS_METHOD = "POST"
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OFFICIAL_SEARCH_EVENTS_PROFILE_VERSION = "official_builder_search_events_v1"
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OFFICIAL_RANGE_SCAN_EVENT_TAGS = {
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"marriage": ["Marriage", "General"],
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"wealth": ["LendingMoney", "BorrowingMoney", "General"],
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"career": ["General", "Building", "Travel"],
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"marriage": ["Marriage", "Personal", "General"],
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"wealth": ["LendingMoney", "BorrowingMoney", "BuyingSelling", "General"],
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"career": ["Personal", "General", "Building", "Travel"],
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}
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VEDASTRO_CALCULATION_COVERAGE = {
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"official_python_library_calculations": "596+",
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@@ -204,6 +204,52 @@ RANGE_SCAN_SIGNAL_METADATA = {
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},
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},
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}
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RANGE_SCAN_OFFICIAL_TAG_MATCHES = {
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"marriage": {"Marriage"},
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"wealth": {"LendingMoney", "BorrowingMoney", "BuyingSelling"},
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"career": {"Building", "Travel"},
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}
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RANGE_SCAN_ALIAS_TERMS = {
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"marriage": {
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"marriage",
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"spouse",
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"wedding",
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"relationship",
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"partner",
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"partnership",
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},
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"wealth": {
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"wealth",
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"money",
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"finance",
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"financial",
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"income",
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"gain",
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"gains",
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"lending",
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"borrowing",
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"business",
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"cash",
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},
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"career": {
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"career",
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"profession",
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"work",
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"job",
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"business",
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"travel",
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"building",
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"public",
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"status",
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},
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}
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MATCH_METADATA_BY_TYPE = {
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"exact_id": {"signal_lift": 3, "confidence": "high"},
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"official_tag": {"signal_lift": 2, "confidence": "medium_high"},
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"alias": {"signal_lift": 1, "confidence": "low"},
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"rejected": {"signal_lift": 0, "confidence": "rejected"},
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}
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ALIAS_NEGATIVE_GUARD_TERMS = {"noise", "without", "generic", "irrelevant", "insignificance", "not"}
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DEFAULT_TIMEOUT_SECONDS = 120
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TIMEOUT_ENV = "VEDASTRO_TIMEOUT_SECONDS"
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BACKOFF_ENV = "VEDASTRO_RETRY_BACKOFF_SECONDS"
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@@ -653,9 +699,20 @@ def _normalize_range_scan_success(
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allowlist = RANGE_SCAN_EVENT_ALLOWLIST.get(domain, {})
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allowed_ids = allowlist.get("event_ids", set())
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allowed_tags = allowlist.get("tags", set())
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official_tags = RANGE_SCAN_OFFICIAL_TAG_MATCHES.get(domain, set())
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alias_terms = RANGE_SCAN_ALIAS_TERMS.get(domain, set())
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original_event_count = len(events)
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evidence_ledger = []
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mapping_details = []
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matched_tags: set[str] = set()
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recommended_allowlist_candidates: set[str] = set()
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match_counts = {
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"exact_id": 0,
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"official_tag": 0,
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"alias": 0,
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"rejected": 0,
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}
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for index, event in enumerate(events, start=1):
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if not isinstance(event, dict):
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continue
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@@ -665,15 +722,75 @@ def _normalize_range_scan_success(
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if not isinstance(tags, list):
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tags = []
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tag_set = {str(tag) for tag in tags}
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if event_id not in allowed_ids and tag_set.isdisjoint(allowed_tags):
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continue
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matched_by = "rejected"
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matched_terms: list[str] = []
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drop_reason = "no_supported_match"
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signal_metadata = RANGE_SCAN_SIGNAL_METADATA.get(domain, {}).get(event_id, {})
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if event_id in allowed_ids:
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matched_by = "exact_id"
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matched_terms = [event_id]
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drop_reason = ""
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else:
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official_tag_hits = sorted(tag_set.intersection(official_tags))
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if official_tag_hits:
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matched_by = "official_tag"
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matched_terms = official_tag_hits
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drop_reason = ""
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else:
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haystack_parts = [
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str(event_id),
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str(event.get("Description") or ""),
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str(event.get("description") or ""),
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str(event.get("Name") or ""),
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" ".join(str(tag) for tag in tags),
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]
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haystack = " ".join(part.lower() for part in haystack_parts if part)
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alias_hits = sorted(term for term in alias_terms if term in haystack)
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guard_hits = sorted(term for term in ALIAS_NEGATIVE_GUARD_TERMS if term in haystack)
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if alias_hits and not guard_hits:
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matched_by = "alias"
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matched_terms = alias_hits
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drop_reason = ""
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match_counts[matched_by] += 1
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if matched_by == "rejected":
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mapping_details.append(
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{
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"event_id": event_id,
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"matched_by": matched_by,
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"matched_terms": matched_terms,
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"drop_reason": drop_reason,
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"tags": tags,
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}
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)
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continue
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if matched_by == "official_tag":
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matched_tags.update(matched_terms)
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if event_id not in allowed_ids and not tag_set.intersection(allowed_tags):
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recommended_allowlist_candidates.add(event_id)
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elif matched_by == "alias":
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if event_id not in allowed_ids:
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recommended_allowlist_candidates.add(event_id)
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match_meta = MATCH_METADATA_BY_TYPE[matched_by]
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mapping_details.append(
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{
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"event_id": event_id,
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"matched_by": matched_by,
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"matched_terms": matched_terms,
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"drop_reason": drop_reason,
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"tags": tags,
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}
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)
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evidence_ledger.append(
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{
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"source": "vedastro_service_adapter_candidate",
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"operation": "range_scan",
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"domain": domain,
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"event_id": event_id,
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"matched_by": matched_by,
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"matched_terms": matched_terms,
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"signal_lift": match_meta["signal_lift"],
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"confidence": match_meta["confidence"],
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"drop_reason": None,
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"signal_key": signal_metadata.get("signal_key"),
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"signal_label": signal_metadata.get("signal_label") or event.get("name") or event_id,
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"signal_family": signal_metadata.get("signal_family"),
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@@ -709,6 +826,15 @@ def _normalize_range_scan_success(
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"allowlist_event_count": len(evidence_ledger),
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"filtered_event_count": len(evidence_ledger),
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"raw_event_count": original_event_count,
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"mapping_replay": {
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"raw_event_count": original_event_count,
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"filtered_event_count": len(evidence_ledger),
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"zero_event_domains": [domain] if original_event_count > 0 and not evidence_ledger else [],
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"match_counts": match_counts,
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"matched_tags": sorted(matched_tags),
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"recommended_allowlist_candidates": sorted(recommended_allowlist_candidates),
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"events": mapping_details,
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},
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**(payload.get("source_metadata") or {}),
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}
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result = {
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