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>
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wangliang
@@ -249,11 +249,8 @@ async def get_categories() -> dict:
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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 = 60,
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page: int = 1,
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user_token: str = None,
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user_id: str = None,
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account_id: str = None
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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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@@ -261,46 +258,33 @@ async def search_products(
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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: 60, max 100)
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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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user_token: 用户 JWT token（必需，用于 Mall API 认证）
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user_id: 用户 ID（自动注入）
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account_id: 账户 ID（自动注入）
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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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if not user_token:
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return {
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"success": False,
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"error": "用户未登录，请先登录账户以搜索商品",
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"products": [],
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"total": 0,
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"require_login": True
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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(
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f"search_products called with keyword={keyword}, "
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f"user_token_prefix={user_token[:20] if user_token else None}..."
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)
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print(f"[DEBUG] search_products called: keyword={keyword}, user_token={user_token[:20] if user_token else None}...")
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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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# 使用用户 token 创建 Mall 客户端
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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=user_token,
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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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@@ -310,9 +294,10 @@ async def search_products(
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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"result={result}"
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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: {result}")
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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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@@ -328,12 +313,21 @@ async def search_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("productName"),
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"product_image": product.get("productImage"),
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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("stock"),
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"sales_count": product.get("salesCount", 0)
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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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@@ -382,18 +376,32 @@ if __name__ == "__main__":
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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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# Call the tool with arguments
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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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tool_result = await tool_obj.run(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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@@ -414,11 +422,17 @@ if __name__ == "__main__":
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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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