feat: 修复 H5 底部导航覆盖 + 更新项目进度文档
## H5 底部导航修复 (Bug #10) - 精简 App.vue，移除重复 tabbar，仅保留全局样式 - uni-page 设置 height: calc(100% - 50px) + overflow-y: auto - 内容区域精确停在底部导航上方，独立滚动不再叠加 - 恢复 custom-tab-bar 组件 ## 项目进度文档 - PROGRESS.md 更新至 10 个 Bug 修复 - 新增 H5 底部导航修复记录 - 新增历史变更条目
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TradeMate Dev
@@ -1,11 +1,13 @@
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from typing import Dict, Any, Optional, List
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select, and_
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from sqlalchemy import select, and_, or_
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from app.models.quotation import Quotation, QuotationItem
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from app.models.customer import Customer
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from app.models.user import Product
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from app.ai.router import get_ai_router
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from datetime import datetime
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import logging
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import json
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logger = logging.getLogger(__name__)
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@@ -90,6 +92,135 @@ class QuotationService:
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await self.db.flush()
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return await self._to_dict(q)
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async def generate_from_inquiry(
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self, user_id: str, inquiry_text: str, customer_id: Optional[str] = None,
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) -> Dict[str, Any]:
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ai = get_ai_router()
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schema = {
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"type": "object",
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"properties": {
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"product_requests": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"product_name": {"type": "string"},
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"quantity": {"type": "integer"},
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"unit": {"type": "string"},
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"specifications": {"type": "string"},
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"target_price": {"type": "string"},
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},
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},
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},
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"payment_terms": {"type": "string"},
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"delivery_terms": {"type": "string"},
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"urgency": {"type": "string"},
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},
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}
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extract_result = await ai.extract(inquiry_text, schema)
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extracted = extract_result.get("data", {})
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product_requests = extracted.get("product_requests", [])
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if not product_requests:
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schema_simple = {
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"type": "object",
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"properties": {
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"product_name": {"type": "string"},
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"quantity": {"type": "integer"},
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"specifications": {"type": "string"},
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},
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}
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extract_result = await ai.extract(inquiry_text, schema_simple)
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extracted = extract_result.get("data", {})
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if extracted.get("product_name"):
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product_requests = [{
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"product_name": extracted["product_name"],
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"quantity": extracted.get("quantity", 1),
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"unit": "pcs",
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"specifications": extracted.get("specifications", ""),
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}]
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product_result = await self.db.execute(
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select(Product).where(
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and_(
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Product.user_id == user_id,
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Product.is_active == True,
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)
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)
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)
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user_products = product_result.scalars().all()
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matched_products = []
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for req in product_requests:
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req_name = req.get("product_name", "").lower()
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best_match = None
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best_score = 0
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for p in user_products:
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score = 0
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p_name = (p.name or "").lower()
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p_name_en = (p.name_en or "").lower()
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if req_name in p_name or p_name in req_name:
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score += 3
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if req_name in p_name_en or p_name_en in req_name:
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score += 2
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keywords = p.keywords or []
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for kw in keywords:
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if isinstance(kw, str) and kw.lower() in req_name:
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score += 1
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if score > best_score:
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best_score = score
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best_match = p
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if best_match and best_score > 0:
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unit_price = float(best_match.price) if best_match.price else 0
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quantity = req.get("quantity", 1)
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matched_products.append({
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"product_id": str(best_match.id),
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"product_name": best_match.name,
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"description": best_match.description_en or best_match.description,
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"quantity": quantity,
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"unit_price": unit_price,
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"total_price": unit_price * quantity,
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"unit": req.get("unit", "pcs"),
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"match_score": best_score,
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})
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else:
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matched_products.append({
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"product_id": None,
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"product_name": req.get("product_name", "Unknown"),
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"description": req.get("specifications", ""),
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"quantity": req.get("quantity", 1),
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"unit_price": 0,
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"total_price": 0,
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"unit": req.get("unit", "pcs"),
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"match_score": 0,
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})
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subtotal = sum(p["total_price"] for p in matched_products)
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total = subtotal
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suggested_quotation = {
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"title": f"Quotation - {', '.join(p['product_name'] for p in matched_products[:3])}",
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"items": matched_products,
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"subtotal": subtotal,
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"total": total,
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"payment_terms": extracted.get("payment_terms", "T/T"),
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"delivery_terms": extracted.get("delivery_terms", "FOB"),
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"lead_time": "15-20 days" if extracted.get("urgency") != "urgent" else "7-10 days",
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"notes": f"Generated from customer inquiry: {inquiry_text[:100]}..." if len(inquiry_text) > 100 else f"Generated from customer inquiry: {inquiry_text}",
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"extracted_data": extracted,
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"matched_count": len([p for p in matched_products if p["product_id"]]),
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"unmatched_count": len([p for p in matched_products if not p["product_id"]]),
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}
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return suggested_quotation
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async def generate_quotation_text(self, q: Quotation) -> str:
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items_result = await self.db.execute(
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select(QuotationItem).where(QuotationItem.quotation_id == q.id)
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