apps/api/main_hf_simple.py

"""
Hugging Face Spaces 超简版 - 直接内联数据加载
"""
from fastapi import FastAPI, Request
from fastapi.middleware.cors import CORSMiddleware
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
from pathlib import Path
import pandas as pd

app = FastAPI(
    title="海关数据查询系统",
    description="巴西海关贸易数据查询服务",
    version="1.0.0"
)

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"],
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

BASE_DIR = Path(__file__).resolve().parent.parent.parent
STATIC_DIR = BASE_DIR / "apps" / "api" / "static"

# 挂载静态文件
app.mount("/static", StaticFiles(directory=str(STATIC_DIR)), name="static")

@app.get("/")
async def serve_ui():
    """返回前端页面"""
    return FileResponse(str(STATIC_DIR / "index.html"))

@app.get("/api/v1/health")
async def health_check():
    """健康检查"""
    return {"status": "ok", "service": "Customs Data API"}

@app.post("/api/v1/trade/search")
async def search_trade_records(request: Request):
    """
    查询贸易记录 - 直接从CSV读取
    """
    try:
        body = await request.json()
    except:
        body = {}
    
    # 提取参数
    source_country = body.get('source_country')
    trade_direction = body.get('trade_direction')
    hs_code = body.get('hs_code')
    product_name = body.get('product_name')
    importer_name = body.get('importer_name')
    exporter_name = body.get('exporter_name')
    page = int(body.get('page', 1))
    limit = int(body.get('limit', 20))
    
    # 加载CSV
    csv_path = BASE_DIR / "data" / "standard_trade_records_sample.csv"
    df = pd.read_csv(csv_path)
    
    # 过滤
    filtered_df = df.copy()
    if source_country:
        filtered_df = filtered_df[filtered_df['source_country'] == source_country]
    if trade_direction:
        filtered_df = filtered_df[filtered_df['trade_direction'] == trade_direction]
    if hs_code:
        filtered_df = filtered_df[filtered_df['hs_code'].astype(str).str.startswith(str(hs_code))]
    if product_name:
        filtered_df = filtered_df[filtered_df['product_name'].str.contains(product_name, na=False, case=False)]
    if importer_name:
        filtered_df = filtered_df[filtered_df['importer_name'].str.contains(importer_name, na=False, case=False)]
    if exporter_name:
        filtered_df = filtered_df[filtered_df['exporter_name'].str.contains(exporter_name, na=False, case=False)]
    
    total = len(filtered_df)
    
    # 分页
    offset = (page - 1) * limit
    page_df = filtered_df.iloc[offset:offset + limit]
    
    # 构建响应
    items = []
    for _, row in page_df.iterrows():
        trade_date_str = str(row['trade_date']).split()[0] if pd.notna(row['trade_date']) else '2023-01-01'
        items.append({
            'record_id': str(row['record_id']),
            'source_record_id': str(row['source_record_id']),
            'source_country': str(row['source_country']),
            'trade_direction': str(row['trade_direction']),
            'trade_date': trade_date_str,
            'importer_name': str(row['importer_name']) if pd.notna(row['importer_name']) else "",
            'exporter_name': str(row['exporter_name']) if pd.notna(row['exporter_name']) else "",
            'hs_code': str(row['hs_code']) if pd.notna(row['hs_code']) else None,
            'product_name': str(row['product_name']) if pd.notna(row['product_name']) else None,
            'amount': float(row['amount']) if pd.notna(row['amount']) else None,
            'currency': str(row['currency']) if pd.notna(row['currency']) else None,
            'weight': float(row['weight']) if pd.notna(row['weight']) else None,
            'weight_unit': str(row['weight_unit']) if pd.notna(row['weight_unit']) else None,
            'origin_country': str(row['origin_country']) if pd.notna(row['origin_country']) else None,
            'destination_country': str(row['destination_country']) if pd.notna(row['destination_country']) else None,
            'departure_port': str(row['departure_port']) if pd.notna(row['departure_port']) else None,
            'arrival_port': str(row['arrival_port']) if pd.notna(row['arrival_port']) else None,
            'transport_mode': str(row['transport_mode']) if pd.notna(row['transport_mode']) else None
        })
    
    return {'total': total, 'items': items}

if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=7860)