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"""
Unified application configuration loader.
This module is the single source of truth for loading, merging, normalizing,
and validating application configuration.
"""
from __future__ import annotations
import hashlib
import json
import os
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import csv
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from copy import deepcopy
from dataclasses import asdict
from functools import lru_cache
from pathlib import Path
from typing import Any, Dict, Iterable, List, Optional, Tuple
import yaml
try:
from dotenv import load_dotenv as _load_dotenv # type: ignore
except Exception: # pragma: no cover
_load_dotenv = None
from config.schema import (
AppConfig,
AssetsConfig,
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CoarseRankConfig,
CoarseRankFusionConfig,
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ConfigMetadata,
DatabaseSettings,
ElasticsearchSettings,
EmbeddingServiceConfig,
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FineRankConfig,
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FunctionScoreConfig,
IndexConfig,
InfrastructureConfig,
QueryConfig,
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ProductEnrichConfig,
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RedisSettings,
RerankConfig,
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RerankFusionConfig,
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RerankServiceConfig,
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RerankServiceInstanceConfig,
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RuntimeConfig,
SearchConfig,
SecretsConfig,
ServicesConfig,
SPUConfig,
TenantCatalogConfig,
TranslationServiceConfig,
)
from translation.settings import build_translation_config
class ConfigurationError(Exception):
"""Raised when configuration validation fails."""
def _deep_merge(base: Dict[str, Any], override: Dict[str, Any]) -> Dict[str, Any]:
result = deepcopy(base)
for key, value in (override or {}).items():
if (
key in result
and isinstance(result[key], dict)
and isinstance(value, dict)
):
result[key] = _deep_merge(result[key], value)
else:
result[key] = deepcopy(value)
return result
def _load_yaml(path: Path) -> Dict[str, Any]:
with open(path, "r", encoding="utf-8") as handle:
data = yaml.safe_load(handle) or {}
if not isinstance(data, dict):
raise ConfigurationError(f"Configuration file root must be a mapping: {path}")
return data
def _read_rewrite_dictionary(path: Path) -> Dict[str, str]:
rewrite_dict: Dict[str, str] = {}
if not path.exists():
return rewrite_dict
with open(path, "r", encoding="utf-8") as handle:
for raw_line in handle:
line = raw_line.strip()
if not line or line.startswith("#"):
continue
parts = line.split("\t")
if len(parts) < 2:
continue
original = parts[0].strip()
replacement = parts[1].strip()
if original and replacement:
rewrite_dict[original] = replacement
return rewrite_dict
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def _read_synonym_csv_dictionary(path: Path) -> List[Dict[str, List[str]]]:
rows: List[Dict[str, List[str]]] = []
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if not path.exists():
return rows
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def _split_terms(cell: str) -> List[str]:
return [item.strip() for item in str(cell or "").split(",") if item.strip()]
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with open(path, "r", encoding="utf-8") as handle:
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reader = csv.reader(handle)
for parts in reader:
if not parts:
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continue
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if parts[0].strip().startswith("#"):
continue
normalized = [segment.strip() for segment in parts]
if len(normalized) < 3:
continue
row = {
"en_terms": _split_terms(normalized[0]),
"zh_terms": _split_terms(normalized[1]),
"attribute_terms": _split_terms(normalized[2]),
}
if any(row.values()):
rows.append(row)
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return rows
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def _read_product_title_exclusion_dictionary(path: Path) -> List[Dict[str, List[str]]]:
rules: List[Dict[str, List[str]]] = []
if not path.exists():
return rules
with open(path, "r", encoding="utf-8") as handle:
for raw_line in handle:
line = raw_line.strip()
if not line or line.startswith("#"):
continue
parts = [segment.strip() for segment in line.split("\t")]
if len(parts) != 4:
continue
def _split_cell(cell: str) -> List[str]:
return [item.strip() for item in cell.split(",") if item.strip()]
rules.append(
{
"zh_trigger_terms": _split_cell(parts[0]),
"en_trigger_terms": _split_cell(parts[1]),
"zh_title_exclusions": _split_cell(parts[2]),
"en_title_exclusions": _split_cell(parts[3]),
}
)
return rules
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_DEFAULT_STYLE_INTENT_DIMENSION_ALIASES: Dict[str, List[str]] = {
"color": ["color", "colors", "colour", "colours", "颜色", "色", "色系"],
"size": ["size", "sizes", "sizing", "尺码", "尺寸", "码数", "号码", "码"],
}
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class AppConfigLoader:
"""Load the unified application configuration."""
def __init__(
self,
*,
config_dir: Optional[Path] = None,
config_file: Optional[Path] = None,
env_file: Optional[Path] = None,
) -> None:
self.config_dir = Path(config_dir or Path(__file__).parent)
self.config_file = Path(config_file) if config_file is not None else None
self.project_root = self.config_dir.parent
self.env_file = Path(env_file) if env_file is not None else self.project_root / ".env"
def load(self, validate: bool = True) -> AppConfig:
self._load_env()
raw_config, loaded_files = self._load_raw_config()
app_config = self._build_app_config(raw_config, loaded_files)
if validate:
self._validate(app_config)
return app_config
def _load_env(self) -> None:
if _load_dotenv is not None:
_load_dotenv(self.env_file, override=False)
return
_load_env_file_fallback(self.env_file)
def _load_raw_config(self) -> Tuple[Dict[str, Any], List[str]]:
env_name = (os.getenv("APP_ENV") or os.getenv("RUNTIME_ENV") or "prod").strip().lower() or "prod"
loaded_files: List[str] = []
raw: Dict[str, Any] = {}
if self.config_file is not None:
config_path = self.config_file
if not config_path.exists():
raise ConfigurationError(f"Configuration file not found: {config_path}")
raw = _deep_merge(raw, _load_yaml(config_path))
loaded_files.append(str(config_path))
else:
base_path = self.config_dir / "base.yaml"
legacy_path = self.config_dir / "config.yaml"
primary_path = base_path if base_path.exists() else legacy_path
if not primary_path.exists():
raise ConfigurationError(f"Configuration file not found: {primary_path}")
raw = _deep_merge(raw, _load_yaml(primary_path))
loaded_files.append(str(primary_path))
env_path = self.config_dir / "environments" / f"{env_name}.yaml"
if env_path.exists():
raw = _deep_merge(raw, _load_yaml(env_path))
loaded_files.append(str(env_path))
tenant_dir = self.config_dir / "tenants"
if tenant_dir.is_dir():
tenant_files = sorted(tenant_dir.glob("*.yaml"))
if tenant_files:
tenant_config = {"default": {}, "tenants": {}}
default_path = tenant_dir / "_default.yaml"
if default_path.exists():
tenant_config["default"] = _load_yaml(default_path)
loaded_files.append(str(default_path))
for tenant_path in tenant_files:
if tenant_path.name == "_default.yaml":
continue
tenant_config["tenants"][tenant_path.stem] = _load_yaml(tenant_path)
loaded_files.append(str(tenant_path))
raw["tenant_config"] = tenant_config
return raw, loaded_files
def _build_app_config(self, raw: Dict[str, Any], loaded_files: List[str]) -> AppConfig:
assets_cfg = raw.get("assets") if isinstance(raw.get("assets"), dict) else {}
rewrite_path = (
assets_cfg.get("query_rewrite_dictionary_path")
or assets_cfg.get("rewrite_dictionary_path")
or self.config_dir / "dictionaries" / "query_rewrite.dict"
)
rewrite_path = Path(rewrite_path)
if not rewrite_path.is_absolute():
rewrite_path = (self.project_root / rewrite_path).resolve()
if not rewrite_path.exists():
legacy_rewrite_path = (self.config_dir / "query_rewrite.dict").resolve()
if legacy_rewrite_path.exists():
rewrite_path = legacy_rewrite_path
rewrite_dictionary = _read_rewrite_dictionary(rewrite_path)
search_config = self._build_search_config(raw, rewrite_dictionary)
services_config = self._build_services_config(raw.get("services") or {})
tenants_config = self._build_tenants_config(raw.get("tenant_config") or {})
runtime_config = self._build_runtime_config()
infrastructure_config = self._build_infrastructure_config(runtime_config.environment)
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product_enrich_raw = raw.get("product_enrich") if isinstance(raw.get("product_enrich"), dict) else {}
product_enrich_config = ProductEnrichConfig(
max_workers=int(product_enrich_raw.get("max_workers", 40)),
)
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metadata = ConfigMetadata(
loaded_files=tuple(loaded_files),
config_hash="",
deprecated_keys=tuple(self._detect_deprecated_keys(raw)),
)
app_config = AppConfig(
runtime=runtime_config,
infrastructure=infrastructure_config,
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product_enrich=product_enrich_config,
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search=search_config,
services=services_config,
tenants=tenants_config,
assets=AssetsConfig(query_rewrite_dictionary_path=rewrite_path),
metadata=metadata,
)
config_hash = self._compute_hash(app_config)
return AppConfig(
runtime=app_config.runtime,
infrastructure=app_config.infrastructure,
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product_enrich=app_config.product_enrich,
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search=app_config.search,
services=app_config.services,
tenants=app_config.tenants,
assets=app_config.assets,
metadata=ConfigMetadata(
loaded_files=app_config.metadata.loaded_files,
config_hash=config_hash,
deprecated_keys=app_config.metadata.deprecated_keys,
),
)
def _build_search_config(self, raw: Dict[str, Any], rewrite_dictionary: Dict[str, str]) -> SearchConfig:
field_boosts = raw.get("field_boosts") or {}
if not isinstance(field_boosts, dict):
raise ConfigurationError("field_boosts must be a mapping")
indexes: List[IndexConfig] = []
for item in raw.get("indexes") or []:
if not isinstance(item, dict):
raise ConfigurationError("indexes items must be mappings")
indexes.append(
IndexConfig(
name=str(item["name"]),
label=str(item.get("label") or item["name"]),
fields=list(item.get("fields") or []),
boost=float(item.get("boost", 1.0)),
example=item.get("example"),
)
)
query_cfg = raw.get("query_config") if isinstance(raw.get("query_config"), dict) else {}
search_fields = query_cfg.get("search_fields") if isinstance(query_cfg.get("search_fields"), dict) else {}
text_strategy = (
query_cfg.get("text_query_strategy")
if isinstance(query_cfg.get("text_query_strategy"), dict)
else {}
)
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style_intent_cfg = (
query_cfg.get("style_intent")
if isinstance(query_cfg.get("style_intent"), dict)
else {}
)
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product_title_exclusion_cfg = (
query_cfg.get("product_title_exclusion")
if isinstance(query_cfg.get("product_title_exclusion"), dict)
else {}
)
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def _resolve_project_path(value: Any, default_path: Path) -> Path:
if value in (None, ""):
return default_path
candidate = Path(str(value))
if candidate.is_absolute():
return candidate
return self.project_root / candidate
style_color_path = _resolve_project_path(
style_intent_cfg.get("color_dictionary_path"),
self.config_dir / "dictionaries" / "style_intent_color.csv",
)
style_size_path = _resolve_project_path(
style_intent_cfg.get("size_dictionary_path"),
self.config_dir / "dictionaries" / "style_intent_size.csv",
)
configured_dimension_aliases = (
style_intent_cfg.get("dimension_aliases")
if isinstance(style_intent_cfg.get("dimension_aliases"), dict)
else {}
)
style_dimension_aliases: Dict[str, List[str]] = {}
for intent_type, default_aliases in _DEFAULT_STYLE_INTENT_DIMENSION_ALIASES.items():
aliases = configured_dimension_aliases.get(intent_type)
if isinstance(aliases, list) and aliases:
style_dimension_aliases[intent_type] = [str(alias) for alias in aliases if str(alias).strip()]
else:
style_dimension_aliases[intent_type] = list(default_aliases)
style_intent_terms = {
"color": _read_synonym_csv_dictionary(style_color_path),
"size": _read_synonym_csv_dictionary(style_size_path),
}
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product_title_exclusion_path = _resolve_project_path(
product_title_exclusion_cfg.get("dictionary_path"),
self.config_dir / "dictionaries" / "product_title_exclusion.tsv",
)
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query_config = QueryConfig(
supported_languages=list(query_cfg.get("supported_languages") or ["zh", "en"]),
default_language=str(query_cfg.get("default_language") or "en"),
enable_text_embedding=bool(query_cfg.get("enable_text_embedding", True)),
enable_query_rewrite=bool(query_cfg.get("enable_query_rewrite", True)),
rewrite_dictionary=rewrite_dictionary,
text_embedding_field=query_cfg.get("text_embedding_field"),
image_embedding_field=query_cfg.get("image_embedding_field"),
source_fields=query_cfg.get("source_fields"),
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knn_text_boost=float(
query_cfg.get("knn_text_boost", query_cfg.get("knn_boost", 0.25))
),
knn_image_boost=float(
query_cfg.get("knn_image_boost", query_cfg.get("knn_boost", 0.25))
),
knn_text_k=int(query_cfg.get("knn_text_k", 120)),
knn_text_num_candidates=int(query_cfg.get("knn_text_num_candidates", 400)),
knn_text_k_long=int(query_cfg.get("knn_text_k_long", 160)),
knn_text_num_candidates_long=int(
query_cfg.get("knn_text_num_candidates_long", 500)
),
knn_image_k=int(query_cfg.get("knn_image_k", 120)),
knn_image_num_candidates=int(query_cfg.get("knn_image_num_candidates", 400)),
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multilingual_fields=list(
search_fields.get(
"multilingual_fields",
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[],
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)
),
shared_fields=list(
search_fields.get(
"shared_fields",
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[],
) or []
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),
core_multilingual_fields=list(
search_fields.get(
"core_multilingual_fields",
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[],
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)
),
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base_minimum_should_match=str(text_strategy.get("base_minimum_should_match", "70%")),
translation_minimum_should_match=str(text_strategy.get("translation_minimum_should_match", "70%")),
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translation_boost=float(text_strategy.get("translation_boost", 0.4)),
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tie_breaker_base_query=float(text_strategy.get("tie_breaker_base_query", 0.9)),
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best_fields={
str(field): float(boost)
for field, boost in dict(text_strategy.get("best_fields") or {}).items()
},
best_fields_boost=float(text_strategy.get("best_fields_boost", 2.0)),
phrase_fields={
str(field): float(boost)
for field, boost in dict(text_strategy.get("phrase_fields") or {}).items()
},
phrase_match_boost=float(text_strategy.get("phrase_match_boost", 3.0)),
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zh_to_en_model=str(query_cfg.get("zh_to_en_model") or "opus-mt-zh-en"),
en_to_zh_model=str(query_cfg.get("en_to_zh_model") or "opus-mt-en-zh"),
default_translation_model=str(
query_cfg.get("default_translation_model") or "nllb-200-distilled-600m"
),
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zh_to_en_model_source_not_in_index=(
str(v)
if (v := query_cfg.get("zh_to_en_model__source_not_in_index"))
not in (None, "")
else None
),
en_to_zh_model_source_not_in_index=(
str(v)
if (v := query_cfg.get("en_to_zh_model__source_not_in_index"))
not in (None, "")
else None
),
default_translation_model_source_not_in_index=(
str(v)
if (v := query_cfg.get("default_translation_model__source_not_in_index"))
not in (None, "")
else None
),
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translation_embedding_wait_budget_ms_source_in_index=int(
query_cfg.get("translation_embedding_wait_budget_ms_source_in_index", 80)
),
translation_embedding_wait_budget_ms_source_not_in_index=int(
query_cfg.get("translation_embedding_wait_budget_ms_source_not_in_index", 200)
),
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style_intent_enabled=bool(style_intent_cfg.get("enabled", True)),
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融合公式优化。加入意图匹配因子
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style_intent_selected_sku_boost=float(
style_intent_cfg.get("selected_sku_boost", 1.2)
),
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style_intent_terms=style_intent_terms,
style_intent_dimension_aliases=style_dimension_aliases,
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product_title_exclusion_enabled=bool(product_title_exclusion_cfg.get("enabled", True)),
product_title_exclusion_rules=_read_product_title_exclusion_dictionary(
product_title_exclusion_path
),
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)
function_score_cfg = raw.get("function_score") if isinstance(raw.get("function_score"), dict) else {}
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coarse_rank_cfg = raw.get("coarse_rank") if isinstance(raw.get("coarse_rank"), dict) else {}
coarse_fusion_raw = (
coarse_rank_cfg.get("fusion") if isinstance(coarse_rank_cfg.get("fusion"), dict) else {}
)
fine_rank_cfg = raw.get("fine_rank") if isinstance(raw.get("fine_rank"), dict) else {}
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rerank_cfg = raw.get("rerank") if isinstance(raw.get("rerank"), dict) else {}
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fusion_raw = rerank_cfg.get("fusion") if isinstance(rerank_cfg.get("fusion"), dict) else {}
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spu_cfg = raw.get("spu_config") if isinstance(raw.get("spu_config"), dict) else {}
return SearchConfig(
field_boosts={str(key): float(value) for key, value in field_boosts.items()},
indexes=indexes,
query_config=query_config,
function_score=FunctionScoreConfig(
score_mode=str(function_score_cfg.get("score_mode") or "sum"),
boost_mode=str(function_score_cfg.get("boost_mode") or "multiply"),
functions=list(function_score_cfg.get("functions") or []),
),
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ES 拉取 coarse_rank...
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coarse_rank=CoarseRankConfig(
enabled=bool(coarse_rank_cfg.get("enabled", True)),
input_window=int(coarse_rank_cfg.get("input_window", 700)),
output_window=int(coarse_rank_cfg.get("output_window", 240)),
fusion=CoarseRankFusionConfig(
text_bias=float(coarse_fusion_raw.get("text_bias", 0.1)),
text_exponent=float(coarse_fusion_raw.get("text_exponent", 0.35)),
knn_text_weight=float(coarse_fusion_raw.get("knn_text_weight", 1.0)),
knn_image_weight=float(coarse_fusion_raw.get("knn_image_weight", 1.0)),
knn_tie_breaker=float(coarse_fusion_raw.get("knn_tie_breaker", 0.0)),
knn_bias=float(coarse_fusion_raw.get("knn_bias", 0.6)),
knn_exponent=float(coarse_fusion_raw.get("knn_exponent", 0.2)),
),
),
fine_rank=FineRankConfig(
enabled=bool(fine_rank_cfg.get("enabled", True)),
input_window=int(fine_rank_cfg.get("input_window", 240)),
output_window=int(fine_rank_cfg.get("output_window", 80)),
timeout_sec=float(fine_rank_cfg.get("timeout_sec", 10.0)),
rerank_query_template=str(fine_rank_cfg.get("rerank_query_template") or "{query}"),
rerank_doc_template=str(fine_rank_cfg.get("rerank_doc_template") or "{title}"),
service_profile=(
str(v)
if (v := fine_rank_cfg.get("service_profile")) not in (None, "")
else "fine"
),
),
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rerank=RerankConfig(
enabled=bool(rerank_cfg.get("enabled", True)),
rerank_window=int(rerank_cfg.get("rerank_window", 384)),
timeout_sec=float(rerank_cfg.get("timeout_sec", 15.0)),
weight_es=float(rerank_cfg.get("weight_es", 0.4)),
weight_ai=float(rerank_cfg.get("weight_ai", 0.6)),
rerank_query_template=str(rerank_cfg.get("rerank_query_template") or "{query}"),
rerank_doc_template=str(rerank_cfg.get("rerank_doc_template") or "{title}"),
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service_profile=(
str(v)
if (v := rerank_cfg.get("service_profile")) not in (None, "")
else None
),
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fusion=RerankFusionConfig(
rerank_bias=float(fusion_raw.get("rerank_bias", 0.00001)),
rerank_exponent=float(fusion_raw.get("rerank_exponent", 1.0)),
text_bias=float(fusion_raw.get("text_bias", 0.1)),
text_exponent=float(fusion_raw.get("text_exponent", 0.35)),
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tangwang
修改_extract_combin...
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knn_text_weight=float(fusion_raw.get("knn_text_weight", 1.0)),
knn_image_weight=float(fusion_raw.get("knn_image_weight", 1.0)),
knn_tie_breaker=float(fusion_raw.get("knn_tie_breaker", 0.0)),
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knn_bias=float(fusion_raw.get("knn_bias", 0.6)),
knn_exponent=float(fusion_raw.get("knn_exponent", 0.2)),
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fine_bias=float(fusion_raw.get("fine_bias", 0.00001)),
fine_exponent=float(fusion_raw.get("fine_exponent", 1.0)),
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),
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config optimize
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),
spu_config=SPUConfig(
enabled=bool(spu_cfg.get("enabled", False)),
spu_field=spu_cfg.get("spu_field"),
inner_hits_size=int(spu_cfg.get("inner_hits_size", 3)),
searchable_option_dimensions=list(
spu_cfg.get("searchable_option_dimensions") or ["option1", "option2", "option3"]
),
),
es_index_name=str(raw.get("es_index_name") or "search_products"),
es_settings=dict(raw.get("es_settings") or {}),
)
def _build_services_config(self, raw: Dict[str, Any]) -> ServicesConfig:
if not isinstance(raw, dict):
raise ConfigurationError("services must be a mapping")
translation_raw = raw.get("translation") if isinstance(raw.get("translation"), dict) else {}
normalized_translation = build_translation_config(translation_raw)
translation_config = TranslationServiceConfig(
endpoint=str(normalized_translation["service_url"]).rstrip("/"),
timeout_sec=float(normalized_translation["timeout_sec"]),
default_model=str(normalized_translation["default_model"]),
default_scene=str(normalized_translation["default_scene"]),
cache=dict(normalized_translation["cache"]),
capabilities={str(key): dict(value) for key, value in normalized_translation["capabilities"].items()},
)
embedding_raw = raw.get("embedding") if isinstance(raw.get("embedding"), dict) else {}
embedding_provider = str(embedding_raw.get("provider") or "http").strip().lower()
embedding_providers = dict(embedding_raw.get("providers") or {})
if embedding_provider not in embedding_providers:
raise ConfigurationError(f"services.embedding.providers.{embedding_provider} must be configured")
embedding_backend = str(embedding_raw.get("backend") or "").strip().lower()
embedding_backends = {
str(key).strip().lower(): dict(value)
for key, value in dict(embedding_raw.get("backends") or {}).items()
}
if embedding_backend not in embedding_backends:
raise ConfigurationError(f"services.embedding.backends.{embedding_backend} must be configured")
image_backend = str(embedding_raw.get("image_backend") or "clip_as_service").strip().lower()
image_backends = {
str(key).strip().lower(): dict(value)
for key, value in dict(embedding_raw.get("image_backends") or {}).items()
}
if not image_backends:
image_backends = {
"clip_as_service": {
"server": "grpc://127.0.0.1:51000",
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tangwang
多模态模型配置
|
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"model_name": "CN-CLIP/ViT-H-14",
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config optimize
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"batch_size": 8,
"normalize_embeddings": True,
},
"local_cnclip": {
|
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多模态模型配置
|
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|
"model_name": "ViT-H-14",
|
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tangwang
config optimize
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"device": None,
"batch_size": 8,
"normalize_embeddings": True,
},
}
if image_backend not in image_backends:
raise ConfigurationError(f"services.embedding.image_backends.{image_backend} must be configured")
embedding_config = EmbeddingServiceConfig(
provider=embedding_provider,
providers=embedding_providers,
backend=embedding_backend,
backends=embedding_backends,
image_backend=image_backend,
image_backends=image_backends,
)
rerank_raw = raw.get("rerank") if isinstance(raw.get("rerank"), dict) else {}
rerank_provider = str(rerank_raw.get("provider") or "http").strip().lower()
rerank_providers = dict(rerank_raw.get("providers") or {})
if rerank_provider not in rerank_providers:
raise ConfigurationError(f"services.rerank.providers.{rerank_provider} must be configured")
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tangwang
config optimize
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rerank_backends = {
str(key).strip().lower(): dict(value)
for key, value in dict(rerank_raw.get("backends") or {}).items()
}
|
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tangwang
漏斗参数调优&呈现优化
|
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|
default_instance = str(rerank_raw.get("default_instance") or "default").strip() or "default"
raw_instances = rerank_raw.get("instances") if isinstance(rerank_raw.get("instances"), dict) else {}
if not raw_instances:
legacy_backend = str(rerank_raw.get("backend") or "").strip().lower()
if legacy_backend not in rerank_backends:
raise ConfigurationError(f"services.rerank.backends.{legacy_backend} must be configured")
provider_cfg = dict(rerank_providers.get(rerank_provider) or {})
raw_instances = {
default_instance: {
"host": "0.0.0.0",
"port": 6007,
"backend": legacy_backend,
"base_url": provider_cfg.get("base_url"),
"service_url": provider_cfg.get("service_url"),
}
}
rerank_instances = {}
for instance_name, instance_raw in raw_instances.items():
if not isinstance(instance_raw, dict):
raise ConfigurationError(f"services.rerank.instances.{instance_name} must be a mapping")
normalized_instance_name = str(instance_name).strip()
backend_name = str(instance_raw.get("backend") or "").strip().lower()
if backend_name not in rerank_backends:
raise ConfigurationError(
f"services.rerank.instances.{normalized_instance_name}.backend must reference configured services.rerank.backends"
)
port = int(instance_raw.get("port", 6007))
rerank_instances[normalized_instance_name] = RerankServiceInstanceConfig(
host=str(instance_raw.get("host") or "0.0.0.0"),
port=port,
backend=backend_name,
runtime_dir=(
str(v)
if (v := instance_raw.get("runtime_dir")) not in (None, "")
else None
),
base_url=(
str(v).rstrip("/")
if (v := instance_raw.get("base_url")) not in (None, "")
else None
),
service_url=(
str(v).rstrip("/")
if (v := instance_raw.get("service_url")) not in (None, "")
else None
),
)
if default_instance not in rerank_instances:
raise ConfigurationError(
f"services.rerank.default_instance={default_instance!r} must exist in services.rerank.instances"
)
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config optimize
|
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|
rerank_request = dict(rerank_raw.get("request") or {})
rerank_request.setdefault("max_docs", 1000)
rerank_request.setdefault("normalize", True)
rerank_config = RerankServiceConfig(
provider=rerank_provider,
providers=rerank_providers,
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漏斗参数调优&呈现优化
|
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default_instance=default_instance,
instances=rerank_instances,
|
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tangwang
config optimize
|
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|
backends=rerank_backends,
request=rerank_request,
)
return ServicesConfig(
translation=translation_config,
embedding=embedding_config,
rerank=rerank_config,
)
def _build_tenants_config(self, raw: Dict[str, Any]) -> TenantCatalogConfig:
if not isinstance(raw, dict):
raise ConfigurationError("tenant_config must be a mapping")
default_cfg = raw.get("default") if isinstance(raw.get("default"), dict) else {}
tenants_cfg = raw.get("tenants") if isinstance(raw.get("tenants"), dict) else {}
return TenantCatalogConfig(
default=dict(default_cfg),
tenants={str(key): dict(value) for key, value in tenants_cfg.items()},
)
def _build_runtime_config(self) -> RuntimeConfig:
environment = (os.getenv("APP_ENV") or os.getenv("RUNTIME_ENV") or "prod").strip().lower() or "prod"
namespace = os.getenv("ES_INDEX_NAMESPACE")
if namespace is None:
namespace = "" if environment == "prod" else f"{environment}_"
return RuntimeConfig(
environment=environment,
index_namespace=namespace,
api_host=os.getenv("API_HOST", "0.0.0.0"),
api_port=int(os.getenv("API_PORT", 6002)),
indexer_host=os.getenv("INDEXER_HOST", "0.0.0.0"),
indexer_port=int(os.getenv("INDEXER_PORT", 6004)),
|
fe80e80e
tangwang
fix host config
|
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|
embedding_host=os.getenv("EMBEDDING_HOST", "0.0.0.0"),
|
86d8358b
tangwang
config optimize
|
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embedding_port=int(os.getenv("EMBEDDING_PORT", 6005)),
embedding_text_port=int(os.getenv("EMBEDDING_TEXT_PORT", 6005)),
embedding_image_port=int(os.getenv("EMBEDDING_IMAGE_PORT", 6008)),
translator_host=os.getenv("TRANSLATION_HOST", "127.0.0.1"),
translator_port=int(os.getenv("TRANSLATION_PORT", 6006)),
reranker_host=os.getenv("RERANKER_HOST", "127.0.0.1"),
reranker_port=int(os.getenv("RERANKER_PORT", 6007)),
)
def _build_infrastructure_config(self, environment: str) -> InfrastructureConfig:
del environment
return InfrastructureConfig(
elasticsearch=ElasticsearchSettings(
host=os.getenv("ES_HOST", "http://localhost:9200"),
username=os.getenv("ES_USERNAME"),
password=os.getenv("ES_PASSWORD"),
),
redis=RedisSettings(
host=os.getenv("REDIS_HOST", "localhost"),
port=int(os.getenv("REDIS_PORT", 6479)),
snapshot_db=int(os.getenv("REDIS_SNAPSHOT_DB", 0)),
password=os.getenv("REDIS_PASSWORD"),
socket_timeout=int(os.getenv("REDIS_SOCKET_TIMEOUT", 1)),
socket_connect_timeout=int(os.getenv("REDIS_SOCKET_CONNECT_TIMEOUT", 1)),
retry_on_timeout=os.getenv("REDIS_RETRY_ON_TIMEOUT", "false").strip().lower() == "true",
cache_expire_days=int(os.getenv("REDIS_CACHE_EXPIRE_DAYS", 360 * 2)),
embedding_cache_prefix=os.getenv("REDIS_EMBEDDING_CACHE_PREFIX", "embedding"),
anchor_cache_prefix=os.getenv("REDIS_ANCHOR_CACHE_PREFIX", "product_anchors"),
anchor_cache_expire_days=int(os.getenv("REDIS_ANCHOR_CACHE_EXPIRE_DAYS", 30)),
),
database=DatabaseSettings(
host=os.getenv("DB_HOST"),
port=int(os.getenv("DB_PORT", 3306)) if os.getenv("DB_PORT") else 3306,
database=os.getenv("DB_DATABASE"),
username=os.getenv("DB_USERNAME"),
password=os.getenv("DB_PASSWORD"),
),
secrets=SecretsConfig(
dashscope_api_key=os.getenv("DASHSCOPE_API_KEY"),
deepl_auth_key=os.getenv("DEEPL_AUTH_KEY"),
),
)
def _validate(self, app_config: AppConfig) -> None:
errors: List[str] = []
if not app_config.search.es_index_name:
errors.append("search.es_index_name is required")
if not app_config.search.field_boosts:
errors.append("search.field_boosts cannot be empty")
else:
for field_name, boost in app_config.search.field_boosts.items():
if boost < 0:
errors.append(f"field_boosts.{field_name} must be non-negative")
query_config = app_config.search.query_config
if not query_config.supported_languages:
errors.append("query_config.supported_languages must not be empty")
if query_config.default_language not in query_config.supported_languages:
errors.append("query_config.default_language must be included in supported_languages")
for name, values in (
("multilingual_fields", query_config.multilingual_fields),
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tangwang
config optimize
|
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|
("core_multilingual_fields", query_config.core_multilingual_fields),
):
if not values:
errors.append(f"query_config.{name} must not be empty")
if not set(query_config.core_multilingual_fields).issubset(set(query_config.multilingual_fields)):
errors.append("query_config.core_multilingual_fields must be a subset of multilingual_fields")
if app_config.search.spu_config.enabled and not app_config.search.spu_config.spu_field:
errors.append("spu_config.spu_field is required when spu_config.enabled is true")
if not app_config.tenants.default or not app_config.tenants.default.get("index_languages"):
errors.append("tenant_config.default.index_languages must be configured")
if app_config.metadata.deprecated_keys:
errors.append(
"Deprecated tenant config keys are not supported: "
+ ", ".join(app_config.metadata.deprecated_keys)
)
embedding_provider_cfg = app_config.services.embedding.get_provider_config()
if not embedding_provider_cfg.get("text_base_url"):
errors.append("services.embedding.providers.<provider>.text_base_url is required")
if not embedding_provider_cfg.get("image_base_url"):
errors.append("services.embedding.providers.<provider>.image_base_url is required")
rerank_provider_cfg = app_config.services.rerank.get_provider_config()
|
daa2690b
tangwang
漏斗参数调优&呈现优化
|
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|
provider_instances = rerank_provider_cfg.get("instances")
if not isinstance(provider_instances, dict):
provider_instances = {}
for instance_name in app_config.services.rerank.instances:
instance_cfg = app_config.services.rerank.get_instance(instance_name)
provider_instance_cfg = provider_instances.get(instance_name) if isinstance(provider_instances, dict) else None
has_instance_url = False
if isinstance(provider_instance_cfg, dict):
has_instance_url = bool(provider_instance_cfg.get("service_url") or provider_instance_cfg.get("base_url"))
if not has_instance_url and not instance_cfg.service_url and not instance_cfg.base_url:
errors.append(
f"services.rerank instance {instance_name!r} must define service_url/base_url either under providers.<provider>.instances or services.rerank.instances"
)
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config optimize
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|
if errors:
raise ConfigurationError("Configuration validation failed:\n" + "\n".join(f" - {err}" for err in errors))
def _compute_hash(self, app_config: AppConfig) -> str:
payload = asdict(app_config)
payload["metadata"]["config_hash"] = ""
payload["infrastructure"]["elasticsearch"]["password"] = "***" if payload["infrastructure"]["elasticsearch"].get("password") else None
payload["infrastructure"]["database"]["password"] = "***" if payload["infrastructure"]["database"].get("password") else None
payload["infrastructure"]["redis"]["password"] = "***" if payload["infrastructure"]["redis"].get("password") else None
payload["infrastructure"]["secrets"]["dashscope_api_key"] = "***" if payload["infrastructure"]["secrets"].get("dashscope_api_key") else None
payload["infrastructure"]["secrets"]["deepl_auth_key"] = "***" if payload["infrastructure"]["secrets"].get("deepl_auth_key") else None
blob = json.dumps(payload, ensure_ascii=False, sort_keys=True, default=str)
return hashlib.sha256(blob.encode("utf-8")).hexdigest()[:16]
def _detect_deprecated_keys(self, raw: Dict[str, Any]) -> Iterable[str]:
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product_enrich支持并发
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# Translation-era legacy flags have been removed; keep the hook for future
# deprecations, but currently no deprecated keys are detected.
return ()
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tangwang
config optimize
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@lru_cache(maxsize=1)
def get_app_config() -> AppConfig:
"""Return the process-global application configuration."""
return AppConfigLoader().load()
def reload_app_config() -> AppConfig:
"""Clear the cached configuration and reload it."""
get_app_config.cache_clear()
return get_app_config()
def _load_env_file_fallback(path: Path) -> None:
if not path.exists():
return
with open(path, "r", encoding="utf-8") as handle:
for raw_line in handle:
line = raw_line.strip()
if not line or line.startswith("#") or "=" not in line:
continue
key, value = line.split("=", 1)
key = key.strip()
value = value.strip().strip('"').strip("'")
if key and key not in os.environ:
os.environ[key] = value
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