Files
assistant/mcp_servers/product_mcp/server.py
wangliang 0f13102a02 fix: 改进错误处理和清理测试代码
## 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>
2026-01-27 13:15:58 +08:00

459 lines
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"""
Product MCP Server - Product search, recommendations, and quotes
"""
import sys
import os
from typing import Optional, List, Dict, Any
# Add shared module to path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from fastmcp import FastMCP
from pydantic_settings import BaseSettings
from pydantic import ConfigDict
class Settings(BaseSettings):
"""Server configuration"""
hyperf_api_url: str
hyperf_api_token: str
mall_api_url: str
mall_tenant_id: str = "2"
mall_currency_code: str = "EUR"
mall_language_id: str = "1"
mall_source: str = "us.qa1.gaia888.com"
log_level: str = "INFO"
model_config = ConfigDict(env_file=".env")
settings = Settings()
# Create MCP server
mcp = FastMCP(
"Product Service"
)
# Tool registry for HTTP access
_tools: Dict[str, Any] = {}
def register_tool(name: str):
"""Decorator to register tool in _tools dict"""
def decorator(func):
_tools[name] = func
return func
return decorator
# Hyperf client for this server
from shared.hyperf_client import HyperfClient
hyperf = HyperfClient(settings.hyperf_api_url, settings.hyperf_api_token)
@register_tool("get_product_detail")
@mcp.tool()
async def get_product_detail(
product_id: str
) -> dict:
"""Get product details
Args:
product_id: Product ID
Returns:
Detailed product information including specifications, pricing, and stock
"""
try:
result = await hyperf.get(f"/products/{product_id}")
return {
"success": True,
"product": result
}
except Exception as e:
return {
"success": False,
"error": str(e),
"product": None
}
@register_tool("recommend_products")
@mcp.tool()
async def recommend_products(
user_id: str,
account_id: str,
context: Optional[dict] = None,
strategy: str = "hybrid",
limit: int = 10
) -> dict:
"""Get personalized product recommendations
Args:
user_id: User identifier
account_id: B2B account identifier
context: Optional context for recommendations:
- current_query: Current search query
- recent_views: List of recently viewed product IDs
- cart_items: Items in cart
strategy: Recommendation strategy (collaborative, content_based, hybrid)
limit: Maximum recommendations to return (default: 10)
Returns:
List of recommended products with reasons
"""
payload = {
"user_id": user_id,
"account_id": account_id,
"strategy": strategy,
"limit": limit
}
if context:
payload["context"] = context
try:
result = await hyperf.post("/products/recommend", json=payload)
return {
"success": True,
"recommendations": result.get("recommendations", [])
}
except Exception as e:
return {
"success": False,
"error": str(e),
"recommendations": []
}
@register_tool("get_quote")
@mcp.tool()
async def get_quote(
product_id: str,
quantity: int,
account_id: str,
delivery_province: Optional[str] = None,
delivery_city: Optional[str] = None
) -> dict:
"""Get B2B price quote
Args:
product_id: Product ID
quantity: Desired quantity
account_id: B2B account ID (for customer-specific pricing)
delivery_province: Delivery province (for shipping calculation)
delivery_city: Delivery city (for shipping calculation)
Returns:
Detailed quote with unit price, discounts, tax, and shipping
"""
payload = {
"product_id": product_id,
"quantity": quantity,
"account_id": account_id
}
if delivery_province or delivery_city:
payload["delivery_address"] = {}
if delivery_province:
payload["delivery_address"]["province"] = delivery_province
if delivery_city:
payload["delivery_address"]["city"] = delivery_city
try:
result = await hyperf.post("/products/quote", json=payload)
return {
"success": True,
"quote_id": result.get("quote_id"),
"product_id": product_id,
"quantity": quantity,
"unit_price": result.get("unit_price"),
"subtotal": result.get("subtotal"),
"discount": result.get("discount", 0),
"discount_reason": result.get("discount_reason"),
"tax": result.get("tax"),
"shipping_fee": result.get("shipping_fee"),
"total_price": result.get("total_price"),
"validity": result.get("validity"),
"payment_terms": result.get("payment_terms"),
"estimated_delivery": result.get("estimated_delivery")
}
except Exception as e:
return {
"success": False,
"error": str(e)
}
@register_tool("check_inventory")
@mcp.tool()
async def check_inventory(
product_ids: List[str],
warehouse: Optional[str] = None
) -> dict:
"""Check product inventory/stock
Args:
product_ids: List of product IDs to check
warehouse: Specific warehouse to check (optional)
Returns:
Inventory status for each product
"""
payload = {"product_ids": product_ids}
if warehouse:
payload["warehouse"] = warehouse
try:
result = await hyperf.post("/products/inventory/check", json=payload)
return {
"success": True,
"inventory": result.get("inventory", [])
}
except Exception as e:
return {
"success": False,
"error": str(e),
"inventory": []
}
@register_tool("get_categories")
@mcp.tool()
async def get_categories() -> dict:
"""Get product category tree
Returns:
Hierarchical category structure
"""
try:
result = await hyperf.get("/products/categories")
return {
"success": True,
"categories": result.get("categories", [])
}
except Exception as e:
return {
"success": False,
"error": str(e),
"categories": []
}
@register_tool("search_products")
@mcp.tool()
async def search_products(
keyword: str,
page_size: int = 5,
page: int = 1
) -> dict:
"""Search products from Mall API
从 Mall API 搜索商品 SPU根据关键词
Args:
keyword: 搜索关键词(商品名称、编号等)
page_size: 每页数量 (default: 5, max 100)
page: 页码 (default: 1)
Returns:
商品列表,包含 SPU 信息、商品图片、价格等
Product list including SPU ID, name, image, price, etc.
"""
try:
from shared.mall_client import MallClient
import logging
logger = logging.getLogger(__name__)
logger.info(f"search_products called with keyword={keyword}")
print(f"[DEBUG] search_products called: keyword={keyword}")
# 创建 Mall 客户端(无需 token
mall = MallClient(
api_url=settings.mall_api_url,
api_token=None, # 不需要 token
tenant_id=settings.mall_tenant_id,
currency_code=settings.mall_currency_code,
language_id=settings.mall_language_id,
source=settings.mall_source
)
print(f"[DEBUG] Calling Mall API: keyword={keyword}, page_size={page_size}, page={page}")
result = await mall.search_spu_products(
keyword=keyword,
page_size=page_size,
page=page
)
logger.info(
f"Mall API returned: result_type={type(result).__name__}, "
f"result_keys={list(result.keys()) if isinstance(result, dict) else 'not a dict'}, "
f"total={result.get('total', 'N/A') if isinstance(result, dict) else 'N/A'}, "
f"data_length={len(result.get('data', {}).get('data', [])) if isinstance(result, dict) and isinstance(result.get('data'), dict) else 'N/A'}"
)
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'}")
# 解析返回结果
# Mall API 返回结构: {"total": X, "data": {"data": [...], ...}}
if "data" in result and isinstance(result["data"], dict):
products = result["data"].get("data", [])
else:
products = result.get("list", [])
total = result.get("total", 0)
# 格式化商品数据
formatted_products = []
for product in products:
formatted_products.append({
"spu_id": product.get("spuId"),
"spu_sn": product.get("spuSn"),
"product_name": product.get("spuName"), # 修正字段名
"product_image": product.get("masterImage"), # 修正字段名
"price": product.get("price"),
"special_price": product.get("specialPrice"),
"stock": product.get("stockDescribe"), # 修正字段名
"sales_count": product.get("salesCount", 0),
# 额外有用字段
"href": product.get("href"),
"spu_type": product.get("spuType"),
"spu_type_name": product.get("spuTypeName"),
"min_price": product.get("minPrice"),
"max_price": product.get("maxPrice"),
"price_with_currency": product.get("priceWithCurrency"),
"mark_price": product.get("markPrice"),
"skus_count": len(product.get("skus", []))
})
return {
"success": True,
"products": formatted_products,
"total": total,
"keyword": keyword
}
except Exception as e:
return {
"success": False,
"error": str(e),
"products": [],
"total": 0
}
finally:
# 关闭客户端
if 'client' in dir() and 'mall' in dir():
await mall.close()
# Health check endpoint
@register_tool("health_check")
@mcp.tool()
async def health_check() -> dict:
"""Check server health status"""
return {
"status": "healthy",
"service": "product_mcp",
"version": "1.0.0"
}
if __name__ == "__main__":
import uvicorn
from starlette.responses import JSONResponse
from starlette.routing import Route
from starlette.requests import Request
# Custom tool execution endpoint
async def execute_tool(request: Request):
"""Execute an MCP tool via HTTP"""
tool_name = request.path_params["tool_name"]
try:
# Get arguments from request body
arguments = await request.json()
print(f"[DEBUG HTTP] Tool: {tool_name}, Args: {arguments}")
# Get tool function from registry
if tool_name not in _tools:
print(f"[ERROR] Tool '{tool_name}' not found in registry")
return JSONResponse({
"success": False,
"error": f"Tool '{tool_name}' not found"
}, status_code=404)
tool_obj = _tools[tool_name]
print(f"[DEBUG HTTP] Tool object: {tool_obj}, type: {type(tool_obj)}")
# Filter arguments to only include parameters expected by the tool
# Get parameter names from tool's parameters schema
tool_params = tool_obj.parameters.get('properties', {})
filtered_args = {k: v for k, v in arguments.items() if k in tool_params}
if len(filtered_args) < len(arguments):
print(f"[DEBUG HTTP] Filtered arguments: {arguments} -> {filtered_args}")
# Call the tool with filtered arguments
# FastMCP FunctionTool.run() takes a dict of arguments
print(f"[DEBUG HTTP] Calling tool.run()...")
tool_result = await tool_obj.run(filtered_args)
print(f"[DEBUG HTTP] Tool result: {tool_result}")
# Extract content from ToolResult
# ToolResult.content is a list of TextContent objects with a 'text' attribute
if tool_result.content and len(tool_result.content) > 0:
content = tool_result.content[0].text
# Try to parse as JSON if possible
try:
import json
result = json.loads(content)
except:
result = content
else:
result = None
return JSONResponse({
"success": True,
"result": result
})
except TypeError as e:
print(f"[ERROR] TypeError: {e}")
import traceback
traceback.print_exc()
return JSONResponse({
"success": False,
"error": f"Invalid arguments: {str(e)}"
}, status_code=400)
except Exception as e:
print(f"[ERROR] Exception: {e}")
import traceback
traceback.print_exc()
return JSONResponse({
"success": False,
"error": str(e)
}, status_code=500)
# Health check endpoint
async def health_check(request):
return JSONResponse({"status": "healthy"})
# Create routes list
routes = [
Route('/health', health_check, methods=['GET']),
Route('/tools/{tool_name}', execute_tool, methods=['POST'])
]
# Create app from MCP with custom routes
app = mcp.http_app()
# Add our custom routes to the existing app
for route in routes:
app.router.routes.append(route)
uvicorn.run(app, host="0.0.0.0", port=8004)