- ${imageUrl ? `
- })
- ` : `
-
-
- No Image
- `}
-
- ${price !== 'N/A' ? `¥${price}` : 'N/A'}
-
-
-
- ${escapeHtml(title)}
-
-
-
- ${category ? escapeHtml(category) : ''}
- ${vendor ? ' | ' + escapeHtml(vendor) : ''}
+
`;
});
diff --git a/providers/translation.py b/providers/translation.py
index 10bdef5..e69de29 100644
--- a/providers/translation.py
+++ b/providers/translation.py
@@ -1,170 +0,0 @@
-"""
-Translation provider - direct (in-process) or HTTP service.
-"""
-
-from __future__ import annotations
-
-import logging
-from typing import Any, Dict, List, Optional, Union
-
-from concurrent.futures import Future, ThreadPoolExecutor
-import requests
-
-from config.services_config import get_translation_config, get_translation_base_url
-
-logger = logging.getLogger(__name__)
-
-
-class HttpTranslationProvider:
- """Translation via HTTP service."""
-
- def __init__(
- self,
- base_url: str,
- model: str = "qwen",
- timeout_sec: float = 10.0,
- translation_context: Optional[str] = None,
- ):
- self.base_url = (base_url or "").rstrip("/")
- self.model = model or "qwen"
- self.timeout_sec = float(timeout_sec or 10.0)
- self.translation_context = translation_context or "e-commerce product search"
- self.executor = ThreadPoolExecutor(max_workers=4, thread_name_prefix="http-translator")
-
- def _translate_once(
- self,
- text: str,
- target_lang: str,
- source_lang: Optional[str] = None,
- ) -> Optional[str]:
- if not text or not str(text).strip():
- return text
- try:
- url = f"{self.base_url}/translate"
- payload = {
- "text": text,
- "target_lang": target_lang,
- "source_lang": source_lang or "auto",
- "model": self.model,
- }
- response = requests.post(url, json=payload, timeout=self.timeout_sec)
- if response.status_code != 200:
- logger.warning(
- "HTTP translator failed: status=%s body=%s",
- response.status_code,
- (response.text or "")[:200],
- )
- return None
- data = response.json()
- translated = data.get("translated_text")
- return translated if translated is not None else None
- except Exception as exc:
- logger.warning("HTTP translator request failed: %s", exc, exc_info=True)
- return None
-
- def translate(
- self,
- text: str,
- target_lang: str,
- source_lang: Optional[str] = None,
- context: Optional[str] = None,
- prompt: Optional[str] = None,
- ) -> Optional[str]:
- del context, prompt
- result = self._translate_once(text=text, target_lang=target_lang, source_lang=source_lang)
- return result if result is not None else text
-
- def translate_multi(
- self,
- text: str,
- target_langs: List[str],
- source_lang: Optional[str] = None,
- context: Optional[str] = None,
- async_mode: bool = True,
- prompt: Optional[str] = None,
- ) -> Dict[str, Optional[str]]:
- del context, async_mode, prompt
- out: Dict[str, Optional[str]] = {}
- for lang in target_langs:
- out[lang] = self.translate(text, lang, source_lang=source_lang)
- return out
-
- def translate_multi_async(
- self,
- text: str,
- target_langs: List[str],
- source_lang: Optional[str] = None,
- context: Optional[str] = None,
- prompt: Optional[str] = None,
- ) -> Dict[str, Union[str, Future]]:
- del context, prompt
- out: Dict[str, Union[str, Future]] = {}
- for lang in target_langs:
- out[lang] = self.executor.submit(self.translate, text, lang, source_lang)
- return out
-
- def translate_for_indexing(
- self,
- text: str,
- shop_language: str,
- source_lang: Optional[str] = None,
- context: Optional[str] = None,
- prompt: Optional[str] = None,
- index_languages: Optional[List[str]] = None,
- ) -> Dict[str, Optional[str]]:
- del context, prompt
- langs = index_languages if index_languages else ["en", "zh"]
- source = source_lang or shop_language or "auto"
- out: Dict[str, Optional[str]] = {}
- for lang in langs:
- if lang == shop_language:
- out[lang] = text
- else:
- out[lang] = self.translate(text, target_lang=lang, source_lang=source)
- return out
-
-
-def create_translation_provider(query_config: Any = None) -> Any:
- """
- Create translation provider from services config.
-
- query_config: optional, for api_key/glossary_id/context (used by direct provider).
- """
- cfg = get_translation_config()
- provider = cfg.provider
- pc = cfg.get_provider_cfg()
-
- if provider in ("direct", "local", "inprocess"):
- from query.translator import Translator
- model = pc.get("model") or "qwen"
- qc = query_config or _empty_query_config()
- return Translator(
- model=model,
- api_key=getattr(qc, "translation_api_key", None),
- use_cache=True,
- glossary_id=getattr(qc, "translation_glossary_id", None),
- translation_context=getattr(qc, "translation_context", "e-commerce product search"),
- )
-
- if provider in ("http", "service"):
- base_url = get_translation_base_url()
- model = pc.get("model") or "qwen"
- timeout = pc.get("timeout_sec", 10.0)
- qc = query_config or _empty_query_config()
- return HttpTranslationProvider(
- base_url=base_url,
- model=model,
- timeout_sec=float(timeout),
- translation_context=getattr(qc, "translation_context", "e-commerce product search"),
- )
-
- raise ValueError(f"Unsupported translation provider: {provider}")
-
-
-def _empty_query_config() -> Any:
- """Minimal object with default translation attrs."""
- class _QC:
- translation_api_key = None
- translation_glossary_id = None
- translation_context = "e-commerce product search"
- return _QC()
diff --git a/query/llm_translate.py b/query/llm_translate.py
new file mode 100644
index 0000000..e69de29
--- /dev/null
+++ b/query/llm_translate.py
diff --git a/query/translator.py b/query/translator.py
index 1ad90e5..ee39071 100644
--- a/query/translator.py
+++ b/query/translator.py
@@ -5,6 +5,11 @@ Supports multiple translation models:
- Qwen (default): Alibaba Cloud DashScope API using qwen-mt-flash model
- DeepL: DeepL API for high-quality translations
+重要说明（Qwen 机翻限速）:
+- 当前默认使用的 `qwen-mt-flash` 为云端机翻模型，**官方限速较低，约 RPM=60（每分钟约 60 请求）**
+- 在高并发场景必须依赖 Redis 翻译缓存与批量预热，避免在用户实时请求路径上直接打满 DashScope 限流
+- 若业务侧存在大规模离线翻译或更高吞吐需求，建议评估 DeepL 或自建翻译后端
+
使用方法 (Usage):
```python
diff --git a/reranker/backends/batching_utils.py b/reranker/backends/batching_utils.py
deleted file mode 100644
index ed48f96..0000000
--- a/reranker/backends/batching_utils.py
+++ /dev/null
@@ -1,41 +0,0 @@
-"""Utilities for reranker batching and deduplication."""
-
-from __future__ import annotations
-
-from typing import Iterable, List, Sequence, Tuple
-
-
-def deduplicate_with_positions(texts: Sequence[str]) -> Tuple[List[str], List[int]]:
- """
- Deduplicate texts globally while preserving first-seen order.
-
- Returns:
- unique_texts: deduplicated texts in first-seen order
- position_to_unique: mapping from each original position to unique index
- """
- unique_texts: List[str] = []
- position_to_unique: List[int] = []
- seen: dict[str, int] = {}
-
- for text in texts:
- idx = seen.get(text)
- if idx is None:
- idx = len(unique_texts)
- seen[text] = idx
- unique_texts.append(text)
- position_to_unique.append(idx)
-
- return unique_texts, position_to_unique
-
-
-def sort_indices_by_length(lengths: Sequence[int]) -> List[int]:
- """Return stable ascending indices by lengths."""
- return sorted(range(len(lengths)), key=lambda i: lengths[i])
-
-
-def iter_batches(indices: Sequence[int], batch_size: int) -> Iterable[List[int]]:
- """Yield consecutive batches from indices."""
- if batch_size <= 0:
- raise ValueError(f"batch_size must be > 0, got {batch_size}")
- for i in range(0, len(indices), batch_size):
- yield list(indices[i : i + batch_size])
diff --git a/reranker/backends/dashscope_rerank.py b/reranker/backends/dashscope_rerank.py
index eb5ef24..fefa67c 100644
--- a/reranker/backends/dashscope_rerank.py
+++ b/reranker/backends/dashscope_rerank.py
@@ -21,11 +21,33 @@ from typing import Any, Dict, List, Tuple
from urllib import error as urllib_error
from urllib import request as urllib_request
-from reranker.backends.batching_utils import deduplicate_with_positions, iter_batches
logger = logging.getLogger("reranker.backends.dashscope_rerank")
+def deduplicate_with_positions(texts: List[str]) -> Tuple[List[str], List[int]]:
+ """
+ Deduplicate texts globally while preserving first-seen order.
+
+ Returns:
+ unique_texts: deduplicated texts in first-seen order
+ position_to_unique: mapping from each original position to unique index
+ """
+ unique_texts: List[str] = []
+ position_to_unique: List[int] = []
+ seen: Dict[str, int] = {}
+
+ for text in texts:
+ idx = seen.get(text)
+ if idx is None:
+ idx = len(unique_texts)
+ seen[text] = idx
+ unique_texts.append(text)
+ position_to_unique.append(idx)
+
+ return unique_texts, position_to_unique
+
+
class DashScopeRerankBackend:
"""
DashScope cloud reranker backend.
@@ -206,7 +228,10 @@ class DashScopeRerankBackend:
then apply global top_n/top_n_cap truncation after merge if needed.
"""
indices = list(range(len(unique_texts)))
- batches = list(iter_batches(indices, batch_size=self._batchsize))
+ batches = [
+ indices[i : i + self._batchsize]
+ for i in range(0, len(indices), self._batchsize)
+ ]
num_batches = len(batches)
max_workers = min(8, num_batches) if num_batches > 0 else 1
unique_scores: List[float] = [0.0] * len(unique_texts)
diff --git a/reranker/backends/qwen3_vllm.py b/reranker/backends/qwen3_vllm.py
index 9ca830d..4b23f8d 100644
--- a/reranker/backends/qwen3_vllm.py
+++ b/reranker/backends/qwen3_vllm.py
@@ -14,12 +14,6 @@ import threading
import time
from typing import Any, Dict, List, Tuple
-from reranker.backends.batching_utils import (
- deduplicate_with_positions,
- iter_batches,
- sort_indices_by_length,
-)
-
logger = logging.getLogger("reranker.backends.qwen3_vllm")
try:
@@ -34,6 +28,29 @@ except ImportError as e:
) from e
+def deduplicate_with_positions(texts: List[str]) -> Tuple[List[str], List[int]]:
+ """
+ Deduplicate texts globally while preserving first-seen order.
+
+ Returns:
+ unique_texts: deduplicated texts in first-seen order
+ position_to_unique: mapping from each original position to unique index
+ """
+ unique_texts: List[str] = []
+ position_to_unique: List[int] = []
+ seen: Dict[str, int] = {}
+
+ for text in texts:
+ idx = seen.get(text)
+ if idx is None:
+ idx = len(unique_texts)
+ seen[text] = idx
+ unique_texts.append(text)
+ position_to_unique.append(idx)
+
+ return unique_texts, position_to_unique
+
+
def _format_instruction(instruction: str, query: str, doc: str) -> List[Dict[str, str]]:
"""Build chat messages for one (query, doc) pair."""
return [
@@ -71,19 +88,17 @@ class Qwen3VLLMRerankerBackend:
sort_by_doc_length = os.getenv("RERANK_VLLM_SORT_BY_DOC_LENGTH")
if sort_by_doc_length is None:
sort_by_doc_length = self._config.get("sort_by_doc_length", True)
- length_sort_mode = os.getenv("RERANK_VLLM_LENGTH_SORT_MODE") or self._config.get("length_sort_mode", "char")
self._infer_batch_size = int(infer_batch_size)
self._sort_by_doc_length = str(sort_by_doc_length).strip().lower() in {"1", "true", "yes", "y", "on"}
- self._length_sort_mode = str(length_sort_mode).strip().lower()
if not torch.cuda.is_available():
raise RuntimeError("qwen3_vllm backend requires CUDA GPU, but torch.cuda.is_available() is False")
if dtype not in {"float16", "half", "auto"}:
raise ValueError(f"Unsupported dtype for qwen3_vllm: {dtype!r}. Use float16/half/auto.")
if self._infer_batch_size <= 0:
- raise ValueError(f"infer_batch_size must be > 0, got {self._infer_batch_size}")
- if self._length_sort_mode not in {"char", "token"}:
- raise ValueError(f"length_sort_mode must be 'char' or 'token', got {self._length_sort_mode!r}")
+ raise ValueError(
+ f"infer_batch_size must be > 0, got {self._infer_batch_size}"
+ )
logger.info(
"[Qwen3_VLLM] Loading model %s (max_model_len=%s, tp=%s, gpu_mem=%.2f, dtype=%s, prefix_caching=%s)",
@@ -196,21 +211,7 @@ class Qwen3VLLMRerankerBackend:
"""
if not docs:
return []
- if self._length_sort_mode == "char":
- return [len(text) for text in docs]
- try:
- enc = self._tokenizer(
- docs,
- add_special_tokens=False,
- truncation=True,
- max_length=self._max_prompt_len,
- return_length=True,
- )
- lengths = enc.get("length")
- if isinstance(lengths, list) and len(lengths) == len(docs):
- return [int(x) for x in lengths]
- except Exception as exc:
- logger.debug("Length estimation fallback to char length: %s", exc)
+ # Use simple character length to approximate document length.
return [len(text) for text in docs]
def score_with_meta(
@@ -247,7 +248,6 @@ class Qwen3VLLMRerankerBackend:
"infer_batch_size": self._infer_batch_size,
"inference_batches": 0,
"sort_by_doc_length": self._sort_by_doc_length,
- "length_sort_mode": self._length_sort_mode,
}
# Deduplicate globally by text, keep mapping to original indices.
@@ -257,11 +257,12 @@ class Qwen3VLLMRerankerBackend:
lengths = self._estimate_doc_lengths(unique_texts)
order = list(range(len(unique_texts)))
if self._sort_by_doc_length and len(unique_texts) > 1:
- order = sort_indices_by_length(lengths)
+ order = sorted(order, key=lambda i: lengths[i])
unique_scores: List[float] = [0.0] * len(unique_texts)
inference_batches = 0
- for batch_indices in iter_batches(order, self._infer_batch_size):
+ for start in range(0, len(order), self._infer_batch_size):
+ batch_indices = order[start : start + self._infer_batch_size]
inference_batches += 1
pairs = [(query, unique_texts[i]) for i in batch_indices]
prompts = self._process_inputs(pairs)
diff --git a/scripts/service_ctl.sh b/scripts/service_ctl.sh
index bdf7f06..5887483 100755
--- a/scripts/service_ctl.sh
+++ b/scripts/service_ctl.sh
@@ -684,6 +684,7 @@ status_one() {
local pid_info="-"
local health="down"
local health_body=""
+ local curl_timeout_opts=(--connect-timeout 8 --max-time 8)
if [ "${service}" = "tei" ]; then
local cid
@@ -696,7 +697,7 @@ status_one() {
local path
path="$(health_path_for_service "${service}")"
if [ -n "${port}" ] && [ -n "${path}" ]; then
- if health_body="$(curl -fsS "http://127.0.0.1:${port}${path}" 2>/dev/null)"; then
+ if health_body="$(curl -fsS "${curl_timeout_opts[@]}" "http://127.0.0.1:${port}${path}" 2>/dev/null)"; then
health="ok"
else
health="fail"
@@ -723,7 +724,7 @@ status_one() {
local path
path="$(health_path_for_service "${service}")"
if [ -n "${port}" ] && [ -n "${path}" ]; then
- if health_body="$(curl -fsS "http://127.0.0.1:${port}${path}" 2>/dev/null)"; then
+ if health_body="$(curl -fsS "${curl_timeout_opts[@]}" "http://127.0.0.1:${port}${path}" 2>/dev/null)"; then
health="ok"
else
health="fail"
diff --git a/search/searcher.py b/search/searcher.py
index 6c4057e..e1641fb 100644
--- a/search/searcher.py
+++ b/search/searcher.py
@@ -598,7 +598,6 @@ class Searcher:
es_hits = []
if 'hits' in es_response and 'hits' in es_response['hits']:
es_hits = es_response['hits']['hits']
-
# Extract total and max_score
total = es_response.get('hits', {}).get('total', {})
if isinstance(total, dict):
@@ -616,6 +615,37 @@ class Searcher:
sku_filter_dimension=sku_filter_dimension
)
+ # Build per-result debug info (per SPU) when debug mode is enabled
+ per_result_debug = []
+ if debug and es_hits and formatted_results:
+ for hit, spu in zip(es_hits, formatted_results):
+ source = hit.get("_source", {}) or {}
+ raw_score = hit.get("_score")
+ try:
+ es_score = float(raw_score) if raw_score is not None else 0.0
+ except (TypeError, ValueError):
+ es_score = 0.0
+ try:
+ normalized = float(es_score) / float(max_score) if max_score else None
+ except (TypeError, ValueError, ZeroDivisionError):
+ normalized = None
+
+ title_multilingual = source.get("title") if isinstance(source.get("title"), dict) else None
+ brief_multilingual = source.get("brief") if isinstance(source.get("brief"), dict) else None
+ vendor_multilingual = source.get("vendor") if isinstance(source.get("vendor"), dict) else None
+
+ per_result_debug.append(
+ {
+ "spu_id": spu.spu_id,
+ "es_id": hit.get("_id"),
+ "es_score": es_score,
+ "es_score_normalized": normalized,
+ "title_multilingual": title_multilingual,
+ "brief_multilingual": brief_multilingual,
+ "vendor_multilingual": vendor_multilingual,
+ }
+ )
+
# Format facets
standardized_facets = None
if facets:
@@ -676,6 +706,8 @@ class Searcher:
},
"search_params": context.metadata.get('search_params', {})
}
+ if per_result_debug:
+ debug_info["per_result"] = per_result_debug
# Build result
result = SearchResult(
diff --git a/tests/test_reranker_batching_utils.py b/tests/test_reranker_batching_utils.py
deleted file mode 100644
index 709d327..0000000
--- a/tests/test_reranker_batching_utils.py
+++ /dev/null
@@ -1,32 +0,0 @@
-import pytest
-
-from reranker.backends.batching_utils import (
- deduplicate_with_positions,
- iter_batches,
- sort_indices_by_length,
-)
-
-
-def test_deduplicate_with_positions_global_not_adjacent():
- texts = ["a", "b", "a", "c", "b", "a"]
- unique, mapping = deduplicate_with_positions(texts)
- assert unique == ["a", "b", "c"]
- assert mapping == [0, 1, 0, 2, 1, 0]
-
-
-def test_sort_indices_by_length_stable():
- lengths = [5, 2, 2, 9, 4]
- order = sort_indices_by_length(lengths)
- # Stable sort: index 1 remains ahead of index 2 when lengths are equal.
- assert order == [1, 2, 4, 0, 3]
-
-
-def test_iter_batches():
- indices = list(range(10))
- batches = list(iter_batches(indices, 4))
- assert batches == [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9]]
-
-
-def test_iter_batches_invalid_batch_size():
- with pytest.raises(ValueError, match="batch_size must be > 0"):
- list(iter_batches([0, 1], 0))
--
libgit2 0.21.2
+
+ ${debugHtml}
+ ${imageUrl ? `
+
+ ` : `
+
+
+ No Image
+ `}
+
+ ${price !== 'N/A' ? `¥${price}` : 'N/A'}
+
+
+
+ ${escapeHtml(title)}
+
+
+