This commit is contained in:
@@ -31,6 +31,7 @@ import time
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from dataclasses import dataclass
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from datetime import datetime, timedelta, timezone
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from typing import Optional
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from urllib.parse import quote_plus
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logger = logging.getLogger(__name__)
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@@ -47,6 +48,11 @@ TTL_HOURS = 6 # competitor_prices 快取有效期
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REQUEST_TIMEOUT = float(os.getenv("PCHOME_FEEDER_TIMEOUT", "12")) # 避免外部搜尋 API 長時間卡住排程
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VARIANT_RECALL_SORTS = ("sale/dc", "new/dc")
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RECOVERABLE_LOW_SCORE_FLOOR = max(MIN_MATCH_SCORE - 0.03, 0.72)
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BROWSE_SH_DIAGNOSTIC_ENABLED = os.getenv("PCHOME_FEEDER_BROWSE_SH_DIAGNOSTIC_ENABLED", "true").lower() in {"1", "true", "yes", "on"}
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BROWSE_SH_EXECUTE_ENABLED = os.getenv("PCHOME_FEEDER_BROWSE_SH_EXECUTE_ENABLED", "false").lower() in {"1", "true", "yes", "on"}
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BROWSE_SH_TIMEOUT_SECONDS = int(os.getenv("PCHOME_FEEDER_BROWSE_SH_TIMEOUT", "20"))
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BROWSE_SH_MAX_EXECUTIONS_PER_RUN = int(os.getenv("PCHOME_FEEDER_BROWSE_SH_MAX_PER_RUN", "3"))
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BROWSE_SH_OUTPUT_PREVIEW_CHARS = int(os.getenv("PCHOME_FEEDER_BROWSE_SH_OUTPUT_PREVIEW_CHARS", "1200"))
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RECOVERABLE_DIAGNOSTIC_REASONS = {
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"strong_product_line_match",
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"strong_exact_spec_match",
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@@ -95,6 +101,43 @@ def _classify_low_score_attempt(score: float, diagnostics) -> str:
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return "true_low_confidence"
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def _has_variant_selection_gap(
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momo_name: str,
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ranked_matches: list[tuple],
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best_score: float,
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) -> bool:
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"""True when source lacks explicit variant selection but top candidates require one."""
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try:
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from services.marketplace_product_matcher import (
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_explicit_variant_option_tokens,
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parse_product_identity,
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)
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except Exception:
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return False
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source_identity = parse_product_identity(momo_name)
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source_options = set(_explicit_variant_option_tokens(source_identity))
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if re.search(r"任選\s*[一二兩三四五六七八九十0-9]+\s*款", momo_name):
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source_options -= {str(value) for value in range(1, 11)}
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source_options -= {f"{value:02d}" for value in range(1, 11)}
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if source_options:
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return False
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threshold = max(best_score - 0.02, RECOVERABLE_LOW_SCORE_FLOOR)
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option_buckets: set[str] = set()
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for product, score, diagnostics in ranked_matches[:5]:
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if getattr(diagnostics, "hard_veto", False) or score < threshold:
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continue
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candidate_identity = parse_product_identity(getattr(product, "name", "") or "")
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options = _explicit_variant_option_tokens(candidate_identity)
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if len(options) >= 2:
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return True
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option_buckets.update(options)
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if len(option_buckets) >= 2:
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return True
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return False
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def _extract_tags(pchome_product) -> list:
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"""
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從 PChomeProduct 物件提取語意標籤
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@@ -286,6 +329,66 @@ def _match_diagnostics_payload(diagnostics) -> dict:
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}
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def _pchome_search_url(keyword: str) -> str:
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return f"https://ecshweb.pchome.com.tw/search/v3.3/?q={quote_plus(keyword or '')}"
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def _build_browse_sh_diagnostic_payload(
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momo_name: str,
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search_terms: list[str] = None,
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reason: str = "unknown",
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best_product=None,
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best_score: float = None,
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diagnostics=None,
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candidate_count: int = 0,
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) -> dict:
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"""Build a read-only browse.sh probe plan for low-confidence PChome cases."""
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if not BROWSE_SH_DIAGNOSTIC_ENABLED:
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return {}
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terms = _dedupe_terms(search_terms or _build_search_keywords(momo_name))[:3]
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urls = [_pchome_search_url(term) for term in terms]
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product_url = getattr(best_product, "product_url", None)
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if product_url:
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urls.append(product_url)
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urls = list(dict.fromkeys(url for url in urls if url))
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primary_url = urls[0] if urls else _pchome_search_url(momo_name)
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diagnostic_payload = _match_diagnostics_payload(diagnostics)
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return {
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"tool": "browse.sh",
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"mode": "execute_on_demand" if BROWSE_SH_EXECUTE_ENABLED else "plan_only",
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"reason": reason,
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"execute_enabled": BROWSE_SH_EXECUTE_ENABLED,
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"timeout_seconds": BROWSE_SH_TIMEOUT_SECONDS,
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"candidate_count": int(candidate_count or 0),
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"momo_name": (momo_name or "")[:300],
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"search_terms": terms,
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"urls": urls,
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"suggested_commands": [
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{
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"purpose": "static_fetch_first_page",
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"args": ["get", primary_url],
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},
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{
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"purpose": "manual_browser_probe",
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"args": ["open", primary_url],
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},
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],
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"best_candidate": {
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"product_id": getattr(best_product, "product_id", None),
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"name": (getattr(best_product, "name", None) or "")[:300] or None,
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"price": getattr(best_product, "price", None),
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"url": product_url,
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"score": best_score,
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} if best_product else None,
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"diagnostic_codes": diagnostic_payload.get("reasons") or [],
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"comparison_mode": diagnostic_payload.get("comparison_mode"),
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"hard_veto": diagnostic_payload.get("hard_veto"),
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"execution": {"status": "disabled"},
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}
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def _product_snapshot_payload(product) -> dict:
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payload = {
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"competitor_product_url": None,
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@@ -471,6 +574,7 @@ class CompetitorPriceFeeder:
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self._history_table_ready = False
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self._attempt_table_ready = False
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self._price_table_columns_ready = False
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self._browse_sh_executions = 0
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def _ensure_table_columns(self, conn, table: str, column_specs: list[tuple[str, str]]) -> None:
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"""補齊既有表欄位;避免正式端舊表在新 INSERT 時炸掉。"""
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@@ -613,6 +717,7 @@ class CompetitorPriceFeeder:
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comparison_mode VARCHAR(40),
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hard_veto BOOLEAN,
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diagnostic_codes JSONB,
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browse_diagnostic_json JSONB,
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error_message TEXT,
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attempted_at TIMESTAMP NOT NULL DEFAULT NOW()
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)
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@@ -648,6 +753,7 @@ class CompetitorPriceFeeder:
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comparison_mode VARCHAR(40),
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hard_veto BOOLEAN,
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diagnostic_codes TEXT,
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browse_diagnostic_json TEXT,
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error_message TEXT,
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attempted_at TIMESTAMP NOT NULL DEFAULT CURRENT_TIMESTAMP
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)
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@@ -669,9 +775,64 @@ class CompetitorPriceFeeder:
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("comparison_mode", "VARCHAR(40)"),
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("hard_veto", "BOOLEAN"),
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("diagnostic_codes", "JSONB" if conn.dialect.name == "postgresql" else "TEXT"),
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("browse_diagnostic_json", "JSONB" if conn.dialect.name == "postgresql" else "TEXT"),
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])
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self._attempt_table_ready = True
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def _prepare_browse_diagnostic(
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self,
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momo_name: str,
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search_terms: list = None,
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reason: str = "unknown",
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best_product=None,
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best_score: float = None,
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diagnostics=None,
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candidate_count: int = 0,
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) -> dict:
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"""Return browse.sh diagnostic evidence; CLI execution remains opt-in and rate-limited."""
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payload = _build_browse_sh_diagnostic_payload(
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momo_name,
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search_terms=search_terms,
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reason=reason,
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best_product=best_product,
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best_score=best_score,
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diagnostics=diagnostics,
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candidate_count=candidate_count,
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)
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if not payload or not BROWSE_SH_EXECUTE_ENABLED:
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return payload
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if self._browse_sh_executions >= BROWSE_SH_MAX_EXECUTIONS_PER_RUN:
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payload["execution"] = {"status": "rate_limited"}
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return payload
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command_args = tuple((payload.get("suggested_commands") or [{}])[0].get("args") or ())
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if not command_args:
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payload["execution"] = {"status": "missing_command"}
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return payload
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try:
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from services.browse_sh_tool import BrowseShTool
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self._browse_sh_executions += 1
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result = BrowseShTool(timeout_seconds=BROWSE_SH_TIMEOUT_SECONDS).run(
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command_args,
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timeout_seconds=BROWSE_SH_TIMEOUT_SECONDS,
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)
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payload["execution"] = {
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"status": "ok" if result.ok else "failed",
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"returncode": result.returncode,
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"timed_out": result.timed_out,
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"unavailable_reason": result.unavailable_reason,
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"stdout_preview": (result.stdout or "")[:BROWSE_SH_OUTPUT_PREVIEW_CHARS],
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"stderr_preview": (result.stderr or "")[:BROWSE_SH_OUTPUT_PREVIEW_CHARS],
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}
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except Exception as exc:
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payload["execution"] = {
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"status": "error",
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"error": str(exc)[:500],
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}
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return payload
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def _record_match_attempt(
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self,
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sku: str,
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@@ -684,6 +845,7 @@ class CompetitorPriceFeeder:
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best_product=None,
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best_score: float = None,
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diagnostics=None,
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browse_diagnostic: dict = None,
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error_message: str = None,
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source: str = "pchome",
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) -> None:
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@@ -695,9 +857,15 @@ class CompetitorPriceFeeder:
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search_terms_expr = "CAST(:search_terms AS jsonb)" if conn.dialect.name == "postgresql" else ":search_terms"
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json_cast = "CAST(:match_diagnostic_json AS jsonb)" if conn.dialect.name == "postgresql" else ":match_diagnostic_json"
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codes_cast = "CAST(:diagnostic_codes AS jsonb)" if conn.dialect.name == "postgresql" else ":diagnostic_codes"
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browse_cast = "CAST(:browse_diagnostic_json AS jsonb)" if conn.dialect.name == "postgresql" else ":browse_diagnostic_json"
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diagnostic_payload = _match_diagnostics_payload(diagnostics)
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diagnostic_codes = diagnostic_payload.get("reasons") or []
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product_payload = _product_snapshot_payload(best_product)
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browse_diagnostic_json = (
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json.dumps(browse_diagnostic, ensure_ascii=False)
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if browse_diagnostic
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else None
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)
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conn.execute(text(f"""
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INSERT INTO competitor_match_attempts
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(sku, source, momo_product_id, momo_product_name, momo_price,
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@@ -706,6 +874,7 @@ class CompetitorPriceFeeder:
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competitor_product_url, competitor_image_url, competitor_stock,
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best_competitor_price, best_match_score,
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match_diagnostic_json, comparison_mode, hard_veto, diagnostic_codes,
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browse_diagnostic_json,
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error_message,
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attempted_at)
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VALUES
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@@ -715,6 +884,7 @@ class CompetitorPriceFeeder:
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:competitor_product_url, :competitor_image_url, :competitor_stock,
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:best_price, :best_score,
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{json_cast}, :comparison_mode, :hard_veto, {codes_cast},
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{browse_cast},
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:error_message,
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CURRENT_TIMESTAMP)
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"""), {
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@@ -735,6 +905,7 @@ class CompetitorPriceFeeder:
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"comparison_mode": diagnostic_payload.get("comparison_mode"),
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"hard_veto": diagnostic_payload.get("hard_veto"),
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"diagnostic_codes": json.dumps(diagnostic_codes, ensure_ascii=False) if diagnostic_codes else None,
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"browse_diagnostic_json": browse_diagnostic_json,
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"error_message": (error_message or "")[:1000] or None,
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})
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@@ -1197,6 +1368,12 @@ class CompetitorPriceFeeder:
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products = _search_pchome_candidates(crawler, momo_name, search_terms, momo_price=momo_price)
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if not products:
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logger.debug(f"[Feeder] {sku} 無搜尋結果,跳過")
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browse_diagnostic = self._prepare_browse_diagnostic(
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momo_name,
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search_terms=search_terms,
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reason="no_result",
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candidate_count=0,
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)
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self._record_match_attempt(
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sku,
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momo_name,
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@@ -1205,6 +1382,7 @@ class CompetitorPriceFeeder:
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search_terms=search_terms,
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candidate_count=0,
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attempt_status="no_result",
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browse_diagnostic=browse_diagnostic,
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source=source,
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)
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attempts_written += 1
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@@ -1213,6 +1391,12 @@ class CompetitorPriceFeeder:
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ranked_matches = _rank_match_details(momo_name, products, momo_price=momo_price)
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if not ranked_matches:
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browse_diagnostic = self._prepare_browse_diagnostic(
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momo_name,
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search_terms=search_terms,
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reason="no_match",
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candidate_count=len(products),
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)
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self._record_match_attempt(
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sku,
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momo_name,
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@@ -1221,6 +1405,7 @@ class CompetitorPriceFeeder:
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search_terms=search_terms,
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candidate_count=len(products),
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attempt_status="no_match",
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browse_diagnostic=browse_diagnostic,
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source=source,
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)
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attempts_written += 1
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@@ -1305,6 +1490,15 @@ class CompetitorPriceFeeder:
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f"[Feeder] {sku} 候選屬單位價可比但非同販售組合,"
|
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f"不寫入正式價差 | {_format_match_diagnostics(diagnostics)}"
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)
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browse_diagnostic = self._prepare_browse_diagnostic(
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momo_name,
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search_terms=search_terms,
|
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reason="unit_comparable",
|
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best_product=best_product,
|
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best_score=score,
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diagnostics=diagnostics,
|
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candidate_count=len(products),
|
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)
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self._record_match_attempt(
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sku,
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momo_name,
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@@ -1316,6 +1510,7 @@ class CompetitorPriceFeeder:
|
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best_product=best_product,
|
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best_score=score,
|
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diagnostics=diagnostics,
|
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browse_diagnostic=browse_diagnostic,
|
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error_message=_format_match_diagnostics(diagnostics),
|
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source=source,
|
||||
)
|
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@@ -1325,10 +1520,24 @@ class CompetitorPriceFeeder:
|
||||
|
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if score < MIN_MATCH_SCORE and not manual_accept_override:
|
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attempt_status = _classify_low_score_attempt(score, diagnostics)
|
||||
if (
|
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attempt_status == "recoverable_low_score"
|
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and _has_variant_selection_gap(momo_name, ranked_matches, score)
|
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):
|
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attempt_status = "true_low_confidence"
|
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logger.debug(
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f"[Feeder] {sku} 比對分數過低 ({score:.3f} < {MIN_MATCH_SCORE}),"
|
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f"{_format_match_diagnostics(diagnostics)}"
|
||||
)
|
||||
browse_diagnostic = self._prepare_browse_diagnostic(
|
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momo_name,
|
||||
search_terms=search_terms,
|
||||
reason=attempt_status,
|
||||
best_product=best_product,
|
||||
best_score=score,
|
||||
diagnostics=diagnostics,
|
||||
candidate_count=len(products),
|
||||
)
|
||||
self._record_match_attempt(
|
||||
sku,
|
||||
momo_name,
|
||||
@@ -1340,6 +1549,7 @@ class CompetitorPriceFeeder:
|
||||
best_product=best_product,
|
||||
best_score=score,
|
||||
diagnostics=diagnostics,
|
||||
browse_diagnostic=browse_diagnostic,
|
||||
error_message=_format_match_diagnostics(diagnostics),
|
||||
source=source,
|
||||
)
|
||||
@@ -1365,6 +1575,15 @@ class CompetitorPriceFeeder:
|
||||
write_reason = "manual_accept_override"
|
||||
if not should_write:
|
||||
logger.info(f"[Feeder] {sku} 進入人工覆核,不覆蓋既有配對 | {write_reason}")
|
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browse_diagnostic = self._prepare_browse_diagnostic(
|
||||
momo_name,
|
||||
search_terms=search_terms,
|
||||
reason="protected_existing_match",
|
||||
best_product=best_product,
|
||||
best_score=score,
|
||||
diagnostics=diagnostics,
|
||||
candidate_count=len(products),
|
||||
)
|
||||
self._record_match_attempt(
|
||||
sku,
|
||||
momo_name,
|
||||
@@ -1376,6 +1595,7 @@ class CompetitorPriceFeeder:
|
||||
best_product=best_product,
|
||||
best_score=score,
|
||||
diagnostics=diagnostics,
|
||||
browse_diagnostic=browse_diagnostic,
|
||||
error_message=f"{write_reason}; {_format_match_diagnostics(diagnostics)}",
|
||||
source=source,
|
||||
)
|
||||
@@ -1418,6 +1638,12 @@ class CompetitorPriceFeeder:
|
||||
except Exception as e:
|
||||
logger.error(f"[Feeder] {sku} 處理失敗: {e}")
|
||||
try:
|
||||
browse_diagnostic = self._prepare_browse_diagnostic(
|
||||
momo_name,
|
||||
search_terms=search_terms,
|
||||
reason="crawler_error",
|
||||
candidate_count=0,
|
||||
)
|
||||
self._record_match_attempt(
|
||||
sku,
|
||||
momo_name,
|
||||
@@ -1425,6 +1651,7 @@ class CompetitorPriceFeeder:
|
||||
momo_price=momo_price,
|
||||
search_terms=search_terms,
|
||||
attempt_status="error",
|
||||
browse_diagnostic=browse_diagnostic,
|
||||
error_message=str(e),
|
||||
source=source,
|
||||
)
|
||||
|
||||
@@ -520,6 +520,7 @@ BRAND_ALIAS_OVERRIDES = {
|
||||
"xiaomi": ("小米有品", "小米", "xiaomi"),
|
||||
"mac": ("m.a.c", "mac", "m a c"),
|
||||
"opi": ("o.p.i", "opi", "o p i"),
|
||||
"st雞仔牌": ("日本雞仔牌st", "日本st雞仔牌", "st雞仔牌", "雞仔牌st", "雞仔牌"),
|
||||
}
|
||||
|
||||
PRODUCT_TYPES = {
|
||||
@@ -1157,12 +1158,25 @@ def _has_refill_pack(identity: ProductIdentity) -> bool:
|
||||
return bool(
|
||||
"補充瓶" in text
|
||||
or "補充包" in text
|
||||
or "補充芯" in text
|
||||
or "補充蕊" in text
|
||||
or "替換蕊" in text
|
||||
or "替換芯" in text
|
||||
or "refill" in text
|
||||
)
|
||||
|
||||
|
||||
def _has_accessory_case(identity: ProductIdentity) -> bool:
|
||||
text = identity.normalized_name
|
||||
return bool(
|
||||
"眉彩餅盒" in text
|
||||
or "盒一入款" in text
|
||||
or "盒三入款" in text
|
||||
or "盒單入" in text
|
||||
or "空盒" in text
|
||||
)
|
||||
|
||||
|
||||
def _spec_mention_count(identity: ProductIdentity) -> int:
|
||||
return len(
|
||||
re.findall(
|
||||
@@ -1461,6 +1475,7 @@ def _build_evidence_flags(
|
||||
"count_conflict",
|
||||
"bundle_offer_conflict",
|
||||
"multi_component_conflict",
|
||||
"accessory_case_conflict",
|
||||
"refill_pack_conflict",
|
||||
"price_ratio_extreme",
|
||||
"price_ratio_wide",
|
||||
@@ -1557,6 +1572,9 @@ def score_marketplace_match(
|
||||
reasons.append("multi_component_conflict")
|
||||
if _has_refill_pack(left) != _has_refill_pack(right):
|
||||
reasons.append("refill_pack_conflict")
|
||||
accessory_case_conflict = _has_accessory_case(left) != _has_accessory_case(right)
|
||||
if accessory_case_conflict:
|
||||
reasons.append("accessory_case_conflict")
|
||||
left_spec_mentions = _spec_mention_count(left)
|
||||
right_spec_mentions = _spec_mention_count(right)
|
||||
if left_spec_mentions and right_spec_mentions and left_spec_mentions != right_spec_mentions:
|
||||
@@ -1579,6 +1597,8 @@ def score_marketplace_match(
|
||||
hard_veto = True
|
||||
if _has_refill_pack(left) != _has_refill_pack(right):
|
||||
hard_veto = True
|
||||
if accessory_case_conflict:
|
||||
hard_veto = True
|
||||
if model_line_conflict:
|
||||
hard_veto = True
|
||||
if left_spec_mentions and right_spec_mentions and left_spec_mentions != right_spec_mentions:
|
||||
@@ -1752,6 +1772,20 @@ def score_marketplace_match(
|
||||
):
|
||||
score += 0.07
|
||||
reasons.append("shared_identity_anchor_exact_line")
|
||||
if (
|
||||
"無印乾爽止汗爽身乳液" in shared_anchor
|
||||
and {"nivea", "妮維雅"} & (left.brand_tokens | right.brand_tokens)
|
||||
and brand_score >= 0.95
|
||||
and not hard_veto
|
||||
and price_penalty == 0
|
||||
and type_score >= 0.95
|
||||
and spec_score >= 0.45
|
||||
and token_score >= 0.55
|
||||
and sequence_score >= 0.62
|
||||
and not variant_descriptor_conflict
|
||||
):
|
||||
score += 0.08
|
||||
reasons.append("shared_identity_anchor_nivea_dry_lotion")
|
||||
if (
|
||||
"多效提亮防曬霜" in shared_anchor
|
||||
and {"recipe", "box"} <= (left.brand_tokens | right.brand_tokens)
|
||||
@@ -1967,6 +2001,10 @@ def _extract_anchor_phrases(token: str) -> list[str]:
|
||||
phrases: list[str] = []
|
||||
if "經典旋轉眉筆" in cleaned:
|
||||
phrases.append("經典旋轉眉筆")
|
||||
if "無印乾爽" in cleaned and "止汗爽身乳液" in cleaned:
|
||||
phrases.append("無印乾爽止汗爽身乳液")
|
||||
if "智能光感應" in cleaned and "無線自動除臭芳香噴霧機" in cleaned:
|
||||
phrases.append("智能光感應無線自動除臭芳香噴霧機")
|
||||
if "悠斯晶" in normalized and "經典乳霜" in normalized:
|
||||
phrases.append("悠斯晶經典乳霜")
|
||||
if "經典乳霜" in normalized:
|
||||
|
||||
Reference in New Issue
Block a user