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"""
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索引API路由。
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提供全量和增量索引接口,供外部Java程序调用。
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"""
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支持并发的增量和全量请求:
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import asyncio
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reranker
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import re
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from fastapi import APIRouter, HTTPException
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from typing import Any, Dict, List, Optional
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重构 indexer 文档构建接口...
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from pydantic import BaseModel, Field
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import logging
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from sqlalchemy import text
# Indexer routes depend on services provided by api/indexer_app.py via this registry.
from ..service_registry import get_incremental_service, get_bulk_indexing_service, get_es_client
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logger = logging.getLogger(__name__)
router = APIRouter(prefix="/indexer", tags=["indexer"])
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class ReindexRequest(BaseModel):
"""全量重建索引请求"""
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tenant_id: str
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batch_size: int = 500
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class IndexSpusRequest(BaseModel):
"""增量索引请求(按SPU列表索引)"""
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tenant_id: str
spu_ids: List[str]
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delete_spu_ids: List[str] = Field(default_factory=list) # 显式指定要删除的SPU ID列表(可选)
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class GetDocumentsRequest(BaseModel):
"""查询文档请求(不写入ES)"""
tenant_id: str
spu_ids: List[str]
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class BuildDocItem(BaseModel):
"""
单个 SPU 的原始数据包(由上游从 MySQL 查询得到)。
- spu: 一行 SPU 记录,对应 shoplazza_product_spu 表
- skus: 该 SPU 下的所有 SKU 记录,对应 shoplazza_product_sku 表
- options: 该 SPU 的所有 Option 记录,对应 shoplazza_product_option 表
"""
spu: Dict[str, Any] = Field(..., description="单个 SPU 的原始字段(MySQL 行数据)")
skus: List[Dict[str, Any]] = Field(default_factory=list, description="该 SPU 关联的 SKU 列表")
options: List[Dict[str, Any]] = Field(default_factory=list, description="该 SPU 关联的 Option 列表")
class BuildDocsRequest(BaseModel):
"""
基于上游已查询出的 MySQL 原始数据,构建 ES 索引文档(不访问数据库、不写入 ES)。
该接口是 Java 等外部索引程序正式使用的“doc 生成接口”:
- 上游负责:全量 / 增量调度 + 从 MySQL 查询出各表数据
- 本模块负责:根据配置和算法,将原始行数据转换为与 mappings/search_products.json 一致的 ES 文档
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- 注意:已迁出的 `/indexer/enrich-content` 内容理解能力不再由本接口内置生成
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"""
tenant_id: str = Field(..., description="租户 ID,用于加载租户配置、语言策略等")
items: List[BuildDocItem] = Field(..., description="需要构建 doc 的 SPU 列表(含其 SKUs 和 Options)")
class BuildDocsFromDbRequest(BaseModel):
"""
便捷测试请求:只提供 tenant_id 和 spu_ids,由本服务从 MySQL 查询原始数据,
然后内部调用 /indexer/build-docs 的同一套逻辑构建 ES doc。
用途:
- 本地/联调时快速验证 doc 结构,无需手工构造庞大的 BuildDocsRequest JSON
- 生产正式使用建议直接走 BuildDocsRequest,由外层(Java)控制 MySQL 查询
"""
tenant_id: str = Field(..., description="租户 ID")
spu_ids: List[str] = Field(..., description="需要构建 doc 的 SPU ID 列表")
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@router.post("/reindex")
async def reindex_all(request: ReindexRequest):
"""
全量重建索引接口
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将指定租户的所有SPU数据重新索引到ES。
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注意:此接口不会删除旧索引,只会更新或创建索引。如需重建索引结构(删除后重建),请使用 `scripts/create_tenant_index.sh` 脚本。
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支持并发的增量和全量请求:
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注意:全量索引是长时间运行的操作,会在线程池中执行,不会阻塞其他请求。
全量索引和增量索引可以并行执行。
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"""
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try:
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service = get_bulk_indexing_service()
if service is None:
raise HTTPException(status_code=503, detail="Bulk indexing service is not initialized")
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支持并发的增量和全量请求:
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# 显式将同步阻塞操作放到线程池执行,确保不阻塞事件循环
# 这样全量索引和增量索引可以并行执行
loop = asyncio.get_event_loop()
result = await loop.run_in_executor(
None, # 使用默认线程池
lambda: service.bulk_index(
tenant_id=request.tenant_id,
recreate_index=False,
batch_size=request.batch_size
)
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)
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return result
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except HTTPException:
raise
except Exception as e:
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logger.error(f"Error in reindex for tenant_id={request.tenant_id}: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@router.post("/index")
async def index_spus(request: IndexSpusRequest):
"""
增量索引接口
根据指定的SPU ID列表,将数据索引到ES。用于增量更新指定商品。
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pu_ids参数。目前总共3个参数:
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支持两种删除方式:
1. **自动检测删除**:如果SPU在数据库中被标记为deleted=1,自动从ES中删除对应文档
2. **显式删除**:通过delete_spu_ids参数显式指定要删除的SPU(无论数据库状态如何)
删除策略说明:
- 数据库是唯一真实来源(Single Source of Truth)
- 自动检测:查询数据库时发现deleted=1,自动从ES删除
- 显式删除:调用方明确知道哪些SPU要删除,直接删除(适用于批量删除场景)
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响应格式:
- spu_ids: spu_ids对应的响应列表,每个元素包含spu_id和status(indexed/deleted/failed)
- delete_spu_ids: delete_spu_ids对应的响应列表,每个元素包含spu_id和status(deleted/not_found/failed)
- failed状态的元素会包含msg字段说明失败原因
- 最后给出总体统计:total, success_count, failed_count等
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支持并发的增量和全量请求:
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注意:增量索引在线程池中执行,可以与全量索引并行执行。
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"""
try:
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# 验证请求参数
if not request.spu_ids and not request.delete_spu_ids:
raise HTTPException(status_code=400, detail="spu_ids and delete_spu_ids cannot both be empty")
if request.spu_ids and len(request.spu_ids) > 100:
raise HTTPException(status_code=400, detail="Maximum 100 SPU IDs allowed per request for indexing")
if request.delete_spu_ids and len(request.delete_spu_ids) > 100:
raise HTTPException(status_code=400, detail="Maximum 100 SPU IDs allowed per request for deletion")
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service = get_incremental_service()
if service is None:
raise HTTPException(status_code=503, detail="Incremental indexer service is not initialized")
es_client = get_es_client()
if es_client is None:
raise HTTPException(status_code=503, detail="Elasticsearch client is not initialized")
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支持并发的增量和全量请求:
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# 显式将同步阻塞操作放到线程池执行,确保不阻塞事件循环
# 这样全量索引和增量索引可以并行执行
loop = asyncio.get_event_loop()
result = await loop.run_in_executor(
None, # 使用默认线程池
lambda: service.index_spus_to_es(
es_client=es_client,
tenant_id=request.tenant_id,
spu_ids=request.spu_ids if request.spu_ids else [],
delete_spu_ids=request.delete_spu_ids if request.delete_spu_ids else None
)
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)
return result
except HTTPException:
raise
except Exception as e:
logger.error(f"Error indexing SPUs for tenant_id={request.tenant_id}: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
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@router.post("/build-docs")
async def build_docs(request: BuildDocsRequest):
"""
构建 ES 文档(不访问数据库、不写入 ES)。
使用场景:
- 上游(例如 Java 索引程序)已经从 MySQL 查询出了 SPU / SKU / Option 等原始行数据
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已把本仓库里的 `/indexer...
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- 希望复用本项目当前保留的“索引构建”能力(多语言、翻译、向量、规格聚合等)
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- 只需要拿到与 `mappings/search_products.json` 一致的 doc 列表,由上游自行写入 ES
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- 如需 `qanchors` / `enriched_attributes` / `enriched_taxonomy_attributes`,请由外部内容理解服务生成后再自行合并
|
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重构 indexer 文档构建接口...
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"""
try:
if not request.items:
raise HTTPException(status_code=400, detail="items cannot be empty")
if len(request.items) > 200:
raise HTTPException(status_code=400, detail="Maximum 200 items allowed per request")
incremental_service = get_incremental_service()
if incremental_service is None:
raise HTTPException(status_code=503, detail="Incremental indexer service is not initialized")
# 复用增量索引服务中的 transformer 缓存与配置 / 语言 / embedding 初始化逻辑
transformer, encoder, enable_embedding = incremental_service._get_transformer_bundle(
tenant_id=request.tenant_id
)
import pandas as pd
docs: List[Dict[str, Any]] = []
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failed: List[Dict[str, Any]] = []
for item in request.items:
try:
# 将上游传入的 MySQL 行数据转换为 Pandas 结构,复用 SPUDocumentTransformer
spu_df = pd.DataFrame([item.spu])
spu_row = spu_df.iloc[0]
skus_df = pd.DataFrame(item.skus) if item.skus else pd.DataFrame()
options_df = pd.DataFrame(item.options) if item.options else pd.DataFrame()
doc = transformer.transform_spu_to_doc(
tenant_id=request.tenant_id,
spu_row=spu_row,
skus=skus_df,
options=options_df,
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重构 indexer 文档构建接口...
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)
if doc is None:
failed.append(
{
"spu_id": str(item.spu.get("id")),
"error": "transform_spu_to_doc returned None",
}
)
continue
# 在“构建 doc”接口中,是否补齐 embedding 由内部配置决定(与增量索引一致)
# 此处不强制生成 / 不强制关闭,只复用 transformer_bundle 的 encoder / enable_embedding 设置。
if enable_embedding and encoder:
title_obj = doc.get("title") or {}
title_text = None
if isinstance(title_obj, dict):
title_text = title_obj.get("en") or title_obj.get("zh")
if not title_text:
for v in title_obj.values():
if v and str(v).strip():
title_text = str(v)
break
if title_text and str(title_text).strip():
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tidy
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import numpy as np
embeddings = encoder.encode(title_text)
if embeddings is None or len(embeddings) == 0:
raise RuntimeError(
f"title_embedding empty for spu_id={doc.get('spu_id')}"
)
emb0 = np.asarray(embeddings[0], dtype=np.float32)
if emb0.ndim != 1 or emb0.size == 0 or not np.isfinite(emb0).all():
raise RuntimeError(
f"title_embedding invalid for spu_id={doc.get('spu_id')}"
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cnclip
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)
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tidy
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doc["title_embedding"] = emb0.tolist()
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重构 indexer 文档构建接口...
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docs.append(doc)
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except Exception as e:
failed.append(
{
"spu_id": str(item.spu.get("id")),
"error": str(e),
}
)
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重构 indexer 文档构建接口...
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return {
"tenant_id": request.tenant_id,
"docs": docs,
"total": len(request.items),
"success_count": len(docs),
"failed_count": len(failed),
"failed": failed,
}
except HTTPException:
raise
except Exception as e:
logger.error(f"Error building docs for tenant_id={request.tenant_id}: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@router.post("/build-docs-from-db")
async def build_docs_from_db(request: BuildDocsFromDbRequest):
"""
基于数据库数据构建 ES 文档(测试 / 调试用)。
- 入参:tenant_id + spu_ids
- 步骤:
1. 使用增量索引服务的查询能力,从 MySQL 批量加载 SPU / SKU / Option
2. 组装为 BuildDocsRequest 的 items
3. 内部调用与 /indexer/build-docs 相同的构建逻辑,返回 ES-ready docs
注意:
- 该接口主要用于本项目自测和调试;正式生产建议由上游(Java)自行查库后调用 /indexer/build-docs
"""
try:
if not request.spu_ids:
raise HTTPException(status_code=400, detail="spu_ids cannot be empty")
if len(request.spu_ids) > 200:
raise HTTPException(status_code=400, detail="Maximum 200 SPU IDs allowed per request")
incremental_service = get_incremental_service()
if incremental_service is None:
raise HTTPException(status_code=503, detail="Incremental indexer service is not initialized")
# 直接复用增量服务里的批量查询方法,从 MySQL 拉取原始行数据
# 只加载未删除的记录(include_deleted=False)
spu_df = incremental_service._load_spus_for_spu_ids(
tenant_id=request.tenant_id,
spu_ids=request.spu_ids,
include_deleted=False
)
if spu_df.empty:
return {
"tenant_id": request.tenant_id,
"docs": [],
"total": 0,
"success_count": 0,
"failed_count": len(request.spu_ids),
"failed": [
{"spu_id": spu_id, "error": "SPU not found or deleted"}
for spu_id in request.spu_ids
],
}
# 仅对存在的 spu_id 构建 item,避免无效 ID
# _load_skus_for_spu_ids / _load_options_for_spu_ids 会自动过滤不存在的 spu_id
existing_ids = [str(int(i)) for i in spu_df["id"].tolist()]
skus_df = incremental_service._load_skus_for_spu_ids(
tenant_id=request.tenant_id, spu_ids=existing_ids
)
options_df = incremental_service._load_options_for_spu_ids(
tenant_id=request.tenant_id, spu_ids=existing_ids
)
import pandas as pd
# group by spu_id 方便取子集
sku_groups = skus_df.groupby("spu_id") if not skus_df.empty else None
option_groups = options_df.groupby("spu_id") if not options_df.empty else None
items: List[BuildDocItem] = []
failed: List[Dict[str, Any]] = []
for _, spu_row in spu_df.iterrows():
spu_id = int(spu_row["id"])
try:
spu_dict = spu_row.to_dict()
skus = (
sku_groups.get_group(spu_id).to_dict("records")
if sku_groups is not None and spu_id in sku_groups.groups
else []
)
options = (
option_groups.get_group(spu_id).to_dict("records")
if option_groups is not None and spu_id in option_groups.groups
else []
)
items.append(
BuildDocItem(
spu=spu_dict,
skus=skus,
options=options,
)
)
except Exception as e:
failed.append(
{
"spu_id": str(spu_id),
"error": str(e),
}
)
if not items:
return {
"tenant_id": request.tenant_id,
"docs": [],
"total": 0,
"success_count": 0,
"failed_count": len(request.spu_ids),
"failed": failed
or [
{"spu_id": spu_id, "error": "SPU not found or data load failed"}
for spu_id in request.spu_ids
],
}
# 调用与 /indexer/build-docs 相同的构建逻辑
build_request = BuildDocsRequest(tenant_id=request.tenant_id, items=items)
result = await build_docs(build_request)
# 合并两层 failed 信息
merged_failed = list(result.get("failed", [])) if isinstance(result, dict) else []
merged_failed.extend(failed)
if isinstance(result, dict):
result["failed"] = merged_failed
# 更新 failed_count
result["failed_count"] = len(merged_failed)
return result
return result
except HTTPException:
raise
except Exception as e:
logger.error(f"Error building docs from DB for tenant_id={request.tenant_id}: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
|
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@router.post("/documents")
async def get_documents(request: GetDocumentsRequest):
"""
查询文档接口
根据SPU ID列表获取ES文档数据(不写入ES)。用于查看、调试或验证SPU数据。
"""
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feat: 增量索引服务、租户配置...
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try:
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if not request.spu_ids:
raise HTTPException(status_code=400, detail="spu_ids cannot be empty")
if len(request.spu_ids) > 100:
raise HTTPException(status_code=400, detail="Maximum 100 SPU IDs allowed per request")
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service = get_incremental_service()
if service is None:
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raise HTTPException(status_code=503, detail="Incremental indexer service is not initialized")
success_list, failed_list = [], []
for spu_id in request.spu_ids:
try:
doc = service.get_spu_document(tenant_id=request.tenant_id, spu_id=spu_id)
(success_list if doc else failed_list).append({
"spu_id": spu_id,
"document": doc
} if doc else {
"spu_id": spu_id,
"error": "SPU not found or deleted"
})
except Exception as e:
failed_list.append({"spu_id": spu_id, "error": str(e)})
return {
"success": success_list,
"failed": failed_list,
"total": len(request.spu_ids),
"success_count": len(success_list),
"failed_count": len(failed_list)
}
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except HTTPException:
raise
except Exception as e:
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feat: 新增增量索引接口并重构...
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logger.error(f"Error getting documents for tenant_id={request.tenant_id}: {e}", exc_info=True)
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raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")
@router.get("/health")
async def indexer_health_check():
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"""检查索引服务健康状态"""
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try:
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service = get_incremental_service()
if service is None:
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return {"status": "unavailable", "database": "unknown", "preloaded_data": {"category_mappings": 0}}
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feat: 增量索引服务、租户配置...
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try:
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with service.db_engine.connect() as conn:
conn.execute(text("SELECT 1"))
db_status = "connected"
except Exception as e:
db_status = f"disconnected: {str(e)}"
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return {
"status": "available",
"database": db_status,
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api/routes/indexe...
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"preloaded_data": {"category_mappings": len(service.category_id_to_name)}
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feat: 增量索引服务、租户配置...
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}
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except Exception as e:
logger.error(f"Error checking indexer health: {e}", exc_info=True)
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return {"status": "error", "message": str(e)}
|