## 主要修复 ### 1. JSON 解析错误处理 - 修复所有 Agent 的 LLM 响应解析失败时返回原始内容的问题 - 当 JSON 解析失败时,返回友好的兜底消息而不是原始文本 - 影响文件: customer_service.py, order.py, product.py, aftersale.py ### 2. FAQ 快速路径修复 - 修复 customer_service.py 中变量定义顺序问题 - has_faq_query 在使用前未定义导致 NameError - 添加详细的错误日志记录 ### 3. Chatwoot 集成改进 - 添加响应内容调试日志 - 改进错误处理和日志记录 ### 4. 订单查询优化 - 将订单列表默认返回数量从 10 条改为 5 条 - 统一 MCP 工具层和 Mall Client 层的默认值 ### 5. 代码清理 - 删除所有测试代码和示例文件 - 刋试文件包括: test_*.py, test_*.html, test_*.sh - 删除测试目录: tests/, agent/tests/, agent/examples/ Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
459 lines
14 KiB
Python
459 lines
14 KiB
Python
"""
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Product MCP Server - Product search, recommendations, and quotes
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"""
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import sys
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import os
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from typing import Optional, List, Dict, Any
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# Add shared module to path
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from fastmcp import FastMCP
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from pydantic_settings import BaseSettings
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from pydantic import ConfigDict
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class Settings(BaseSettings):
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"""Server configuration"""
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hyperf_api_url: str
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hyperf_api_token: str
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mall_api_url: str
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mall_tenant_id: str = "2"
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mall_currency_code: str = "EUR"
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mall_language_id: str = "1"
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mall_source: str = "us.qa1.gaia888.com"
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log_level: str = "INFO"
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model_config = ConfigDict(env_file=".env")
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settings = Settings()
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# Create MCP server
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mcp = FastMCP(
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"Product Service"
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)
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# Tool registry for HTTP access
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_tools: Dict[str, Any] = {}
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def register_tool(name: str):
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"""Decorator to register tool in _tools dict"""
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def decorator(func):
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_tools[name] = func
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return func
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return decorator
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# Hyperf client for this server
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from shared.hyperf_client import HyperfClient
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hyperf = HyperfClient(settings.hyperf_api_url, settings.hyperf_api_token)
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@register_tool("get_product_detail")
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@mcp.tool()
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async def get_product_detail(
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product_id: str
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) -> dict:
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"""Get product details
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Args:
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product_id: Product ID
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Returns:
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Detailed product information including specifications, pricing, and stock
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"""
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try:
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result = await hyperf.get(f"/products/{product_id}")
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return {
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"success": True,
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"product": result
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}
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except Exception as e:
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return {
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"success": False,
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"error": str(e),
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"product": None
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}
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@register_tool("recommend_products")
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@mcp.tool()
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async def recommend_products(
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user_id: str,
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account_id: str,
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context: Optional[dict] = None,
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strategy: str = "hybrid",
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limit: int = 10
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) -> dict:
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"""Get personalized product recommendations
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Args:
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user_id: User identifier
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account_id: B2B account identifier
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context: Optional context for recommendations:
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- current_query: Current search query
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- recent_views: List of recently viewed product IDs
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- cart_items: Items in cart
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strategy: Recommendation strategy (collaborative, content_based, hybrid)
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limit: Maximum recommendations to return (default: 10)
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Returns:
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List of recommended products with reasons
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"""
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payload = {
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"user_id": user_id,
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"account_id": account_id,
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"strategy": strategy,
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"limit": limit
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}
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if context:
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payload["context"] = context
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try:
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result = await hyperf.post("/products/recommend", json=payload)
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return {
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"success": True,
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"recommendations": result.get("recommendations", [])
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}
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except Exception as e:
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return {
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"success": False,
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"error": str(e),
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"recommendations": []
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}
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@register_tool("get_quote")
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@mcp.tool()
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async def get_quote(
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product_id: str,
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quantity: int,
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account_id: str,
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delivery_province: Optional[str] = None,
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delivery_city: Optional[str] = None
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) -> dict:
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"""Get B2B price quote
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Args:
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product_id: Product ID
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quantity: Desired quantity
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account_id: B2B account ID (for customer-specific pricing)
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delivery_province: Delivery province (for shipping calculation)
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delivery_city: Delivery city (for shipping calculation)
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Returns:
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Detailed quote with unit price, discounts, tax, and shipping
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"""
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payload = {
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"product_id": product_id,
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"quantity": quantity,
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"account_id": account_id
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}
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if delivery_province or delivery_city:
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payload["delivery_address"] = {}
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if delivery_province:
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payload["delivery_address"]["province"] = delivery_province
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if delivery_city:
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payload["delivery_address"]["city"] = delivery_city
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try:
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result = await hyperf.post("/products/quote", json=payload)
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return {
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"success": True,
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"quote_id": result.get("quote_id"),
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"product_id": product_id,
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"quantity": quantity,
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"unit_price": result.get("unit_price"),
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"subtotal": result.get("subtotal"),
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"discount": result.get("discount", 0),
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"discount_reason": result.get("discount_reason"),
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"tax": result.get("tax"),
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"shipping_fee": result.get("shipping_fee"),
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"total_price": result.get("total_price"),
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"validity": result.get("validity"),
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"payment_terms": result.get("payment_terms"),
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"estimated_delivery": result.get("estimated_delivery")
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}
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except Exception as e:
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return {
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"success": False,
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"error": str(e)
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}
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@register_tool("check_inventory")
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@mcp.tool()
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async def check_inventory(
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product_ids: List[str],
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warehouse: Optional[str] = None
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) -> dict:
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"""Check product inventory/stock
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Args:
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product_ids: List of product IDs to check
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warehouse: Specific warehouse to check (optional)
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Returns:
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Inventory status for each product
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"""
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payload = {"product_ids": product_ids}
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if warehouse:
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payload["warehouse"] = warehouse
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try:
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result = await hyperf.post("/products/inventory/check", json=payload)
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return {
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"success": True,
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"inventory": result.get("inventory", [])
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}
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except Exception as e:
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return {
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"success": False,
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"error": str(e),
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"inventory": []
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}
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@register_tool("get_categories")
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@mcp.tool()
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async def get_categories() -> dict:
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"""Get product category tree
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Returns:
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Hierarchical category structure
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"""
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try:
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result = await hyperf.get("/products/categories")
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return {
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"success": True,
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"categories": result.get("categories", [])
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}
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except Exception as e:
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return {
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"success": False,
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"error": str(e),
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"categories": []
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}
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@register_tool("search_products")
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@mcp.tool()
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async def search_products(
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keyword: str,
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page_size: int = 5,
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page: int = 1
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) -> dict:
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"""Search products from Mall API
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从 Mall API 搜索商品 SPU(根据关键词)
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Args:
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keyword: 搜索关键词(商品名称、编号等)
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page_size: 每页数量 (default: 5, max 100)
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page: 页码 (default: 1)
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Returns:
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商品列表,包含 SPU 信息、商品图片、价格等
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Product list including SPU ID, name, image, price, etc.
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"""
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try:
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from shared.mall_client import MallClient
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import logging
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logger = logging.getLogger(__name__)
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logger.info(f"search_products called with keyword={keyword}")
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print(f"[DEBUG] search_products called: keyword={keyword}")
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# 创建 Mall 客户端(无需 token)
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mall = MallClient(
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api_url=settings.mall_api_url,
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api_token=None, # 不需要 token
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tenant_id=settings.mall_tenant_id,
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currency_code=settings.mall_currency_code,
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language_id=settings.mall_language_id,
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source=settings.mall_source
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)
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print(f"[DEBUG] Calling Mall API: keyword={keyword}, page_size={page_size}, page={page}")
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result = await mall.search_spu_products(
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keyword=keyword,
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page_size=page_size,
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page=page
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)
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logger.info(
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f"Mall API returned: result_type={type(result).__name__}, "
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f"result_keys={list(result.keys()) if isinstance(result, dict) else 'not a dict'}, "
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f"total={result.get('total', 'N/A') if isinstance(result, dict) else 'N/A'}, "
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f"data_length={len(result.get('data', {}).get('data', [])) if isinstance(result, dict) and isinstance(result.get('data'), dict) else 'N/A'}"
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)
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print(f"[DEBUG] Mall API returned: total={result.get('total', 'N/A')}, data_keys={list(result.get('data', {}).keys()) if isinstance(result.get('data'), dict) else 'N/A'}")
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# 解析返回结果
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# Mall API 返回结构: {"total": X, "data": {"data": [...], ...}}
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if "data" in result and isinstance(result["data"], dict):
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products = result["data"].get("data", [])
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else:
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products = result.get("list", [])
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total = result.get("total", 0)
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# 格式化商品数据
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formatted_products = []
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for product in products:
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formatted_products.append({
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"spu_id": product.get("spuId"),
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"spu_sn": product.get("spuSn"),
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"product_name": product.get("spuName"), # 修正字段名
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"product_image": product.get("masterImage"), # 修正字段名
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"price": product.get("price"),
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"special_price": product.get("specialPrice"),
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"stock": product.get("stockDescribe"), # 修正字段名
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"sales_count": product.get("salesCount", 0),
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# 额外有用字段
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"href": product.get("href"),
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"spu_type": product.get("spuType"),
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"spu_type_name": product.get("spuTypeName"),
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"min_price": product.get("minPrice"),
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"max_price": product.get("maxPrice"),
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"price_with_currency": product.get("priceWithCurrency"),
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"mark_price": product.get("markPrice"),
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"skus_count": len(product.get("skus", []))
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})
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return {
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"success": True,
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"products": formatted_products,
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"total": total,
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"keyword": keyword
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}
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except Exception as e:
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return {
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"success": False,
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"error": str(e),
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"products": [],
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"total": 0
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}
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finally:
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# 关闭客户端
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if 'client' in dir() and 'mall' in dir():
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await mall.close()
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# Health check endpoint
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@register_tool("health_check")
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@mcp.tool()
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async def health_check() -> dict:
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"""Check server health status"""
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return {
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"status": "healthy",
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"service": "product_mcp",
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"version": "1.0.0"
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}
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if __name__ == "__main__":
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import uvicorn
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from starlette.responses import JSONResponse
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from starlette.routing import Route
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from starlette.requests import Request
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# Custom tool execution endpoint
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async def execute_tool(request: Request):
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"""Execute an MCP tool via HTTP"""
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tool_name = request.path_params["tool_name"]
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try:
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# Get arguments from request body
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arguments = await request.json()
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print(f"[DEBUG HTTP] Tool: {tool_name}, Args: {arguments}")
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# Get tool function from registry
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if tool_name not in _tools:
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print(f"[ERROR] Tool '{tool_name}' not found in registry")
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return JSONResponse({
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"success": False,
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"error": f"Tool '{tool_name}' not found"
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}, status_code=404)
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tool_obj = _tools[tool_name]
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print(f"[DEBUG HTTP] Tool object: {tool_obj}, type: {type(tool_obj)}")
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# Filter arguments to only include parameters expected by the tool
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# Get parameter names from tool's parameters schema
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tool_params = tool_obj.parameters.get('properties', {})
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filtered_args = {k: v for k, v in arguments.items() if k in tool_params}
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if len(filtered_args) < len(arguments):
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print(f"[DEBUG HTTP] Filtered arguments: {arguments} -> {filtered_args}")
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# Call the tool with filtered arguments
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# FastMCP FunctionTool.run() takes a dict of arguments
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print(f"[DEBUG HTTP] Calling tool.run()...")
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tool_result = await tool_obj.run(filtered_args)
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print(f"[DEBUG HTTP] Tool result: {tool_result}")
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# Extract content from ToolResult
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# ToolResult.content is a list of TextContent objects with a 'text' attribute
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if tool_result.content and len(tool_result.content) > 0:
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content = tool_result.content[0].text
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# Try to parse as JSON if possible
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try:
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import json
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result = json.loads(content)
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except:
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result = content
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else:
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result = None
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return JSONResponse({
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"success": True,
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"result": result
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})
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except TypeError as e:
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print(f"[ERROR] TypeError: {e}")
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import traceback
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traceback.print_exc()
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return JSONResponse({
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"success": False,
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"error": f"Invalid arguments: {str(e)}"
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}, status_code=400)
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except Exception as e:
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print(f"[ERROR] Exception: {e}")
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import traceback
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traceback.print_exc()
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return JSONResponse({
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"success": False,
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"error": str(e)
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}, status_code=500)
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# Health check endpoint
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async def health_check(request):
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return JSONResponse({"status": "healthy"})
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# Create routes list
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routes = [
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Route('/health', health_check, methods=['GET']),
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Route('/tools/{tool_name}', execute_tool, methods=['POST'])
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]
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# Create app from MCP with custom routes
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app = mcp.http_app()
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# Add our custom routes to the existing app
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for route in routes:
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app.router.routes.append(route)
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uvicorn.run(app, host="0.0.0.0", port=8004)
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