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"""
Search API routes.
"""
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from fastapi import APIRouter, HTTPException, Query, Request
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from typing import Optional
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import uuid
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from ..models import (
SearchRequest,
ImageSearchRequest,
SearchResponse,
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SearchSuggestResponse,
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DocumentResponse,
ErrorResponse
)
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from context.request_context import create_request_context, set_current_request_context, clear_current_request_context
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router = APIRouter(prefix="/search", tags=["search"])
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def extract_request_info(request: Request) -> tuple[str, str]:
"""Extract request ID and user ID from HTTP request"""
# Try to get request ID from headers
reqid = request.headers.get('X-Request-ID') or str(uuid.uuid4())[:8]
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# Try to get user ID from headers; if not found, use "-1" for correlation
uid = request.headers.get('X-User-ID') or request.headers.get('User-ID') or "-1"
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return reqid, uid
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@router.post("/", response_model=SearchResponse)
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async def search(request: SearchRequest, http_request: Request):
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"""
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Execute text search query (外部友好格式).
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Supports:
- Multi-language query processing
- Boolean operators (AND, OR, RANK, ANDNOT)
- Semantic search with embeddings
- Custom ranking functions
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- Exact match filters and range filters
- Faceted search
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Requires tenant_id in header (X-Tenant-ID) or query parameter (tenant_id).
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"""
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reqid, uid = extract_request_info(http_request)
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# Extract tenant_id (required)
tenant_id = http_request.headers.get('X-Tenant-ID')
if not tenant_id:
# Try to get from query string
from urllib.parse import parse_qs
query_string = http_request.url.query
if query_string:
params = parse_qs(query_string)
tenant_id = params.get('tenant_id', [None])[0]
if not tenant_id:
raise HTTPException(
status_code=400,
detail="tenant_id is required. Provide it via header 'X-Tenant-ID' or query parameter 'tenant_id'"
)
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# Create request context
context = create_request_context(reqid=reqid, uid=uid)
# Set context in thread-local storage
set_current_request_context(context)
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# Log request start (English logs, with key search parameters)
client_ip = http_request.client.host if http_request.client else "unknown"
user_agent = http_request.headers.get("User-Agent", "unknown")[:200]
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context.logger.info(
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"Received search request | "
f"Tenant: {tenant_id} | "
f"Query: {request.query} | "
f"IP: {client_ip} | "
f"User agent: {user_agent} | "
f"size: {request.size} | from: {request.from_} | "
f"sort_by: {request.sort_by} | sort_order: {request.sort_order} | "
f"min_score: {request.min_score} | "
f"language: {request.language} | "
f"debug: {request.debug} | "
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f"ai_search: {request.ai_search} | "
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f"sku_filter_dimension: {request.sku_filter_dimension} | "
f"filters: {request.filters} | "
f"range_filters: {request.range_filters} | "
f"facets: {request.facets}",
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extra={'reqid': context.reqid, 'uid': context.uid}
)
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# Get searcher from app state
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from api.app import get_searcher
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searcher = get_searcher()
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# Execute search with context (using backend defaults from config)
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result = searcher.search(
query=request.query,
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tenant_id=tenant_id,
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size=request.size,
from_=request.from_,
filters=request.filters,
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range_filters=request.range_filters,
facets=request.facets,
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min_score=request.min_score,
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context=context,
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sort_by=request.sort_by,
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sort_order=request.sort_order,
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debug=request.debug,
language=request.language,
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sku_filter_dimension=request.sku_filter_dimension,
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ai_search=request.ai_search,
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# Include performance summary in response
performance_summary = context.get_summary() if context else None
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# Convert to response model
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response = SearchResponse(
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results=result.results,
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total=result.total,
max_score=result.max_score,
took_ms=result.took_ms,
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facets=result.facets,
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query_info=result.query_info,
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suggestions=result.suggestions,
related_searches=result.related_searches,
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performance_info=performance_summary,
debug_info=result.debug_info
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# Log complete response JSON
context.logger.info(
"Search response | "
f"Total results: {response.total} | "
f"Max score: {response.max_score:.4f} | "
f"Time: {response.took_ms}ms | "
f"Response: {response.model_dump_json()}",
extra={'reqid': context.reqid, 'uid': context.uid}
)
return response
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except Exception as e:
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# Log error in context
if context:
context.set_error(e)
context.logger.error(
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f"Search request failed | error: {str(e)}",
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extra={'reqid': context.reqid, 'uid': context.uid}
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raise HTTPException(status_code=500, detail=str(e))
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# Clear thread-local context
clear_current_request_context()
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@router.post("/image", response_model=SearchResponse)
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async def search_by_image(request: ImageSearchRequest, http_request: Request):
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"""
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Search by image similarity (外部友好格式).
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Uses image embeddings to find visually similar products.
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Supports exact match filters and range filters.
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"""
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reqid, uid = extract_request_info(http_request)
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# Extract tenant_id (required)
tenant_id = http_request.headers.get('X-Tenant-ID')
if not tenant_id:
from urllib.parse import parse_qs
query_string = http_request.url.query
if query_string:
params = parse_qs(query_string)
tenant_id = params.get('tenant_id', [None])[0]
if not tenant_id:
raise HTTPException(
status_code=400,
detail="tenant_id is required. Provide it via header 'X-Tenant-ID' or query parameter 'tenant_id'"
)
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# Create request context
context = create_request_context(reqid=reqid, uid=uid)
# Set context in thread-local storage
set_current_request_context(context)
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# Log request start for image search (English)
client_ip = http_request.client.host if http_request.client else "unknown"
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context.logger.info(
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"Received image search request | "
f"Tenant: {tenant_id} | "
f"Image URL: {request.image_url} | "
f"IP: {client_ip}",
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extra={'reqid': context.reqid, 'uid': context.uid}
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from api.app import get_searcher
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searcher = get_searcher()
# Execute image search
result = searcher.search_by_image(
image_url=request.image_url,
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tenant_id=tenant_id,
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size=request.size,
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filters=request.filters,
range_filters=request.range_filters
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# Include performance summary in response
performance_summary = context.get_summary() if context else None
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response = SearchResponse(
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results=result.results,
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total=result.total,
max_score=result.max_score,
took_ms=result.took_ms,
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facets=result.facets,
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query_info=result.query_info,
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suggestions=result.suggestions,
related_searches=result.related_searches,
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performance_info=performance_summary
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# Log complete response JSON
context.logger.info(
"Image search response | "
f"Total results: {response.total} | "
f"Max score: {response.max_score:.4f} | "
f"Time: {response.took_ms}ms | "
f"Response: {response.model_dump_json()}",
extra={'reqid': context.reqid, 'uid': context.uid}
)
return response
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except ValueError as e:
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if context:
context.set_error(e)
context.logger.error(
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f"Image search request parameter error | error: {str(e)}",
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extra={'reqid': context.reqid, 'uid': context.uid}
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raise HTTPException(status_code=400, detail=str(e))
except Exception as e:
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if context:
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f"Image search request failed | error: {str(e)}",
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extra={'reqid': context.reqid, 'uid': context.uid}
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# Clear thread-local context
clear_current_request_context()
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@router.get("/suggestions", response_model=SearchSuggestResponse)
async def search_suggestions(
q: str = Query(..., min_length=1, description="搜索查询"),
size: int = Query(5, ge=1, le=20, description="建议数量"),
types: str = Query("query", description="建议类型(逗号分隔): query, product, category, brand")
):
"""
获取搜索建议(自动补全)。
功能说明:
- 查询建议(query):基于历史搜索和热门搜索
- 商品建议(product):匹配的商品
- 类目建议(category):匹配的类目
- 品牌建议(brand):匹配的品牌
注意:此功能暂未实现,仅返回框架响应。
"""
import time
start_time = time.time()
# TODO: 实现搜索建议逻辑
# 1. 从搜索历史中获取建议
# 2. 从商品标题中匹配前缀
# 3. 从类目、品牌中匹配
# 临时返回空结果
suggestions = []
# 示例结构(暂不实现):
# suggestions = [
# {
# "text": "芭比娃娃",
# "type": "query",
# "highlight": "<em>芭</em>比娃娃",
# "popularity": 850
# }
# ]
took_ms = int((time.time() - start_time) * 1000)
return SearchSuggestResponse(
query=q,
suggestions=suggestions,
took_ms=took_ms
)
@router.get("/instant", response_model=SearchResponse)
async def instant_search(
q: str = Query(..., min_length=2, description="搜索查询"),
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size: int = Query(5, ge=1, le=20, description="结果数量"),
tenant_id: str = Query(..., description="租户ID")
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"""
即时搜索(Instant Search)。
功能说明:
- 边输入边搜索,无需点击搜索按钮
- 返回简化的搜索结果
注意:此功能暂未实现,调用标准搜索接口。
TODO: 优化即时搜索性能
- 添加防抖/节流
- 实现结果缓存
- 简化返回字段
"""
from api.app import get_searcher
searcher = get_searcher()
result = searcher.search(
query=q,
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tenant_id=tenant_id,
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size=size,
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from_=0,
sku_filter_dimension=None # Instant search doesn't support SKU filtering
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return SearchResponse(
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results=result.results,
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total=result.total,
max_score=result.max_score,
took_ms=result.took_ms,
facets=result.facets,
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tangwang
重构:SPU级别索引、统一索引架构...
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query_info=result.query_info,
suggestions=result.suggestions,
related_searches=result.related_searches
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6aa246be
tangwang
问题:Pydantic 应该能自动...
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)
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be52af70
tangwang
first commit
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@router.get("/{doc_id}", response_model=DocumentResponse)
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tangwang
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async def get_document(doc_id: str, http_request: Request):
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tangwang
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"""
Get a single document by ID.
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tangwang
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Requires tenant_id in header (X-Tenant-ID) or query parameter (tenant_id).
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tangwang
first commit
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"""
try:
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e4a39cc8
tangwang
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# Extract tenant_id (required)
tenant_id = http_request.headers.get('X-Tenant-ID')
if not tenant_id:
# Try to get from query string
from urllib.parse import parse_qs
query_string = http_request.url.query
if query_string:
params = parse_qs(query_string)
tenant_id = params.get('tenant_id', [None])[0]
if not tenant_id:
raise HTTPException(
status_code=400,
detail="tenant_id is required. Provide it via header 'X-Tenant-ID' or query parameter 'tenant_id'"
)
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bb3c5ef8
tangwang
灌入数据流程跑通
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from api.app import get_searcher
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tangwang
first commit
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searcher = get_searcher()
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e4a39cc8
tangwang
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doc = searcher.get_document(tenant_id=tenant_id, doc_id=doc_id)
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tangwang
first commit
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if doc is None:
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raise HTTPException(status_code=404, detail=f"Document {doc_id} not found for tenant {tenant_id}")
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be52af70
tangwang
first commit
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return DocumentResponse(id=doc_id, source=doc)
except HTTPException:
raise
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
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