ded6f29e
 tangwang
补充suggestion模块
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"""
Online suggestion query service.
"""
import logging
import time
from typing import Any, Dict, List, Optional
from config.tenant_config_loader import get_tenant_config_loader
from indexer.mapping_generator import get_tenant_index_name
from suggestion.builder import get_suggestion_index_name
from utils.es_client import ESClient
logger = logging.getLogger(__name__)
class SuggestionService:
def __init__(self, es_client: ESClient):
self.es_client = es_client
def _resolve_language(self, tenant_id: str, language: str) -> str:
cfg = get_tenant_config_loader().get_tenant_config(tenant_id)
index_languages = cfg.get("index_languages") or ["en", "zh"]
primary = cfg.get("primary_language") or "en"
lang = (language or "").strip().lower().replace("-", "_")
if lang in {"zh_tw", "pt_br"}:
normalized = lang
else:
normalized = lang.split("_")[0] if lang else ""
if normalized in index_languages:
return normalized
if primary in index_languages:
return primary
return index_languages[0]
def _search_products_for_suggestion(
self,
tenant_id: str,
text_value: str,
lang: str,
result_size: int,
) -> List[Dict[str, Any]]:
index_name = get_tenant_index_name(tenant_id)
title_field = f"title.{lang}"
qanchor_field = f"qanchors.{lang}"
body = {
"size": result_size,
"_source": ["spu_id", "title", "min_price", "image_url", "sales", "total_inventory"],
"query": {
"bool": {
"should": [
{"match_phrase": {qanchor_field: {"query": text_value, "boost": 3.0}}},
{"match_phrase_prefix": {title_field: {"query": text_value, "boost": 2.0}}},
{"match": {title_field: {"query": text_value, "boost": 1.0}}},
],
"minimum_should_match": 1,
}
},
"sort": [{"_score": "desc"}, {"sales": "desc"}],
}
resp = self.es_client.search(index_name=index_name, body=body, size=result_size, from_=0)
hits = resp.get("hits", {}).get("hits", []) or []
out: List[Dict[str, Any]] = []
for hit in hits:
src = hit.get("_source", {}) or {}
title_obj = src.get("title") or {}
resolved_title = None
if isinstance(title_obj, dict):
resolved_title = title_obj.get(lang) or title_obj.get("en") or title_obj.get("zh")
if not resolved_title:
for v in title_obj.values():
if v:
resolved_title = v
break
out.append(
{
"spu_id": src.get("spu_id"),
"title": resolved_title,
"price": src.get("min_price"),
"image_url": src.get("image_url"),
"score": hit.get("_score", 0.0),
}
)
return out
def search(
self,
tenant_id: str,
query: str,
language: str,
size: int = 10,
with_results: bool = True,
result_size: int = 3,
) -> Dict[str, Any]:
start = time.time()
resolved_lang = self._resolve_language(tenant_id, language)
index_name = get_suggestion_index_name(tenant_id)
sat_field = f"sat.{resolved_lang}"
dsl = {
"size": size,
"query": {
"function_score": {
"query": {
"bool": {
"filter": [
{"term": {"lang": resolved_lang}},
{"term": {"status": 1}},
],
"should": [
{
"multi_match": {
"query": query,
"type": "bool_prefix",
"fields": [sat_field, f"{sat_field}._2gram", f"{sat_field}._3gram"],
}
}
],
"minimum_should_match": 1,
}
},
"field_value_factor": {
"field": "rank_score",
"factor": 1.0,
"modifier": "log1p",
"missing": 0.0,
},
"boost_mode": "sum",
"score_mode": "sum",
}
},
"_source": [
"text",
"lang",
"rank_score",
"sources",
"top_spu_ids",
"lang_source",
"lang_confidence",
"lang_conflict",
],
}
es_resp = self.es_client.search(index_name=index_name, body=dsl, size=size, from_=0)
hits = es_resp.get("hits", {}).get("hits", []) or []
suggestions: List[Dict[str, Any]] = []
for hit in hits:
src = hit.get("_source", {}) or {}
item = {
"text": src.get("text"),
"lang": src.get("lang"),
"score": hit.get("_score", 0.0),
"rank_score": src.get("rank_score"),
"sources": src.get("sources", []),
"lang_source": src.get("lang_source"),
"lang_confidence": src.get("lang_confidence"),
"lang_conflict": src.get("lang_conflict", False),
}
if with_results:
try:
item["products"] = self._search_products_for_suggestion(
tenant_id=tenant_id,
text_value=str(src.get("text") or ""),
lang=resolved_lang,
result_size=result_size,
)
except Exception as e:
logger.warning("Failed to enrich suggestion products: %s", e)
item["products"] = []
suggestions.append(item)
took_ms = int((time.time() - start) * 1000)
return {
"query": query,
"language": language,
"resolved_language": resolved_lang,
"suggestions": suggestions,
"took_ms": took_ms,
}
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