diff --git a/agent/agents/aftersale.py b/agent/agents/aftersale.py index 34ad6b7..5d1ce6b 100644 --- a/agent/agents/aftersale.py +++ b/agent/agents/aftersale.py @@ -6,109 +6,20 @@ from typing import Any from core.state import AgentState, ConversationState, add_tool_call, set_response, update_context from core.llm import get_llm_client, Message +from prompts import get_prompt from utils.logger import get_logger logger = get_logger(__name__) -AFTERSALE_AGENT_PROMPT = """你是一个专业的 B2B 售后服务助手。 -你的职责是帮助用户处理售后问题，包括： -- 退货申请 -- 换货申请 -- 投诉处理 -- 工单创建 -- 售后进度查询 - -## 可用工具 - -1. **apply_return** - 退货申请 - - order_id: 订单号 - - items: 退货商品列表 [{item_id, quantity, reason}] - - description: 问题描述 - - images: 图片URL列表（可选） - -2. **apply_exchange** - 换货申请 - - order_id: 订单号 - - items: 换货商品列表 [{item_id, reason}] - - description: 问题描述 - -3. **create_complaint** - 创建投诉 - - type: 投诉类型（product_quality/service/logistics/other） - - title: 投诉标题 - - description: 详细描述 - - related_order_id: 关联订单号（可选） - - attachments: 附件URL列表（可选） - -4. **create_ticket** - 创建工单 - - category: 工单类别 - - priority: 优先级（low/medium/high/urgent） - - title: 工单标题 - - description: 详细描述 - -5. **query_aftersale_status** - 查询售后状态 - - aftersale_id: 售后单号（可选，不填查询全部） - -## 工具调用格式 - -当需要使用工具时，请返回 JSON 格式： -```json -{ - "action": "call_tool", - "tool_name": "工具名称", - "arguments": { - "参数名": "参数值" - } -} -``` - -当需要向用户询问更多信息时： -```json -{ - "action": "ask_info", - "question": "需要询问的问题", - "required_fields": ["需要收集的字段列表"] -} -``` - -当可以直接回答时： -```json -{ - "action": "respond", - "response": "回复内容" -} -``` - -## 售后流程引导 - -退货流程： -1. 确认订单号和退货商品 -2. 了解退货原因 -3. 收集问题描述和图片（质量问题时） -4. 提交退货申请 -5. 告知用户后续流程 - -换货流程： -1. 确认订单号和换货商品 -2. 了解换货原因 -3. 确认是否有库存 -4. 提交换货申请 - -## 注意事项 -- 售后申请需要完整信息才能提交 -- 对用户的问题要表示理解和歉意 -- 复杂投诉建议转人工处理 -- 金额较大的退款需要特别确认 -""" - - async def aftersale_agent(state: AgentState) -> AgentState: """Aftersale agent node - + Handles returns, exchanges, complaints and aftersale queries. - + Args: state: Current agent state - + Returns: Updated state with tool calls or response """ @@ -117,34 +28,70 @@ async def aftersale_agent(state: AgentState) -> AgentState: conversation_id=state["conversation_id"], sub_intent=state.get("sub_intent") ) - + state["current_agent"] = "aftersale" state["agent_history"].append("aftersale") state["state"] = ConversationState.PROCESSING.value - + # Check if we have tool results to process if state["tool_results"]: return await _generate_aftersale_response(state) + + # Get detected language + locale = state.get("detected_language", "en") + + # Auto-query FAQ for return-related questions + message_lower = state["current_message"].lower() + faq_keywords = ["return", "refund", "defective", "exchange", "complaint", "damaged", "wrong", "missing"] + + # 如果消息包含退货相关关键词，且没有工具调用记录，自动查询 FAQ + if any(keyword in message_lower for keyword in faq_keywords): + # 检查是否已经查询过 FAQ + tool_calls = state.get("tool_calls", []) + has_faq_query = any(tc.get("tool_name") in ["query_faq", "search_knowledge_base"] for tc in tool_calls) + + if not has_faq_query: + logger.info( + "Auto-querying FAQ for return-related question", + conversation_id=state["conversation_id"] + ) + + # 自动添加 FAQ 工具调用 + state = add_tool_call( + state, + tool_name="query_faq", + arguments={ + "category": "return", + "locale": locale, + "limit": 5 + }, + server="strapi" + ) + state["state"] = ConversationState.TOOL_CALLING.value + return state # Build messages for LLM + # Load prompt in detected language + system_prompt = get_prompt("aftersale", locale) + messages = [ - Message(role="system", content=AFTERSALE_AGENT_PROMPT), + Message(role="system", content=system_prompt), ] - + # Add conversation history for msg in state["messages"][-8:]: # More history for aftersale context messages.append(Message(role=msg["role"], content=msg["content"])) - + # Build context info - context_info = f"用户ID: {state['user_id']}\n账户ID: {state['account_id']}\n" - + context_info = f"User ID: {state['user_id']}\nAccount ID: {state['account_id']}\n" + if state["entities"]: - context_info += f"已提取的信息: {json.dumps(state['entities'], ensure_ascii=False)}\n" - + context_info += f"Extracted entities: {json.dumps(state['entities'], ensure_ascii=False)}\n" + if state["context"]: - context_info += f"会话上下文: {json.dumps(state['context'], ensure_ascii=False)}\n" - - user_content = f"{context_info}\n用户消息: {state['current_message']}" + context_info += f"Conversation context: {json.dumps(state['context'], ensure_ascii=False)}\n" + + user_content = f"{context_info}\nUser message: {state['current_message']}" messages.append(Message(role="user", content=user_content)) try: @@ -206,46 +153,46 @@ async def aftersale_agent(state: AgentState) -> AgentState: async def _generate_aftersale_response(state: AgentState) -> AgentState: """Generate response based on aftersale tool results""" - + tool_context = [] for result in state["tool_results"]: if result["success"]: data = result["data"] - tool_context.append(f"工具 {result['tool_name']} 返回:\n{json.dumps(data, ensure_ascii=False, indent=2)}") - + tool_context.append(f"Tool {result['tool_name']} returned:\n{json.dumps(data, ensure_ascii=False, indent=2)}") + # Extract aftersale_id for context if isinstance(data, dict) and data.get("aftersale_id"): state = update_context(state, {"aftersale_id": data["aftersale_id"]}) else: - tool_context.append(f"工具 {result['tool_name']} 执行失败: {result['error']}") - - prompt = f"""基于以下售后系统返回的信息，生成对用户的回复。 + tool_context.append(f"Tool {result['tool_name']} failed: {result['error']}") -用户问题: {state["current_message"]} + prompt = f"""Based on the following aftersale system information, generate a response to the user. -系统返回信息: +User question: {state["current_message"]} + +System returned information: {chr(10).join(tool_context)} -请生成一个体贴、专业的回复： -- 如果是申请提交成功，告知用户售后单号和后续流程 -- 如果是状态查询，清晰说明当前进度 -- 如果申请失败，说明原因并提供解决方案 -- 对用户的问题表示理解 +Please generate a compassionate and professional response: +- If application submitted successfully, inform user of aftersale ID and next steps +- If status query, clearly explain current progress +- If application failed, explain reason and provide solution +- Show understanding for user's issue + +Return only the response content, do not return JSON.""" -只返回回复内容，不要返回 JSON。""" - messages = [ - Message(role="system", content="你是一个专业的售后客服助手，请根据系统返回的信息回答用户的售后问题。"), + Message(role="system", content="You are a professional aftersale service assistant, please answer user's aftersale questions based on system returned information."), Message(role="user", content=prompt) ] - + try: llm = get_llm_client() response = await llm.chat(messages, temperature=0.7) state = set_response(state, response.content) return state - + except Exception as e: logger.error("Aftersale response generation failed", error=str(e)) - state = set_response(state, "抱歉，处理售后请求时遇到问题。请稍后重试或联系人工客服。") + state = set_response(state, "Sorry, there was a problem processing your aftersale request. Please try again later or contact customer support.") return state diff --git a/agent/agents/customer_service.py b/agent/agents/customer_service.py index b58341d..016d515 100644 --- a/agent/agents/customer_service.py +++ b/agent/agents/customer_service.py @@ -6,76 +6,20 @@ from typing import Any from core.state import AgentState, ConversationState, add_tool_call, set_response from core.llm import get_llm_client, Message +from prompts import get_prompt from utils.logger import get_logger logger = get_logger(__name__) -CUSTOMER_SERVICE_PROMPT = """你是一个专业的 B2B 购物网站客服助手。 -你的职责是回答用户的一般性问题，包括： -- 常见问题解答 (FAQ) -- 公司信息查询 -- 政策咨询（退换货政策、隐私政策等） -- 产品使用指南 -- 其他一般性咨询 - -## 可用工具 - -你可以使用以下工具获取信息： -1. **query_faq** - 搜索 FAQ 常见问题 - - query: 搜索关键词 - - category: 分类（可选） - -2. **get_company_info** - 获取公司信息 - - section: 信息类别（about_us, contact, etc.） - -3. **get_policy** - 获取政策文档 - - policy_type: 政策类型（return_policy, privacy_policy, etc.） - -## 工具调用格式 - -当需要使用工具时，请返回 JSON 格式： -```json -{ - "action": "call_tool", - "tool_name": "工具名称", - "arguments": { - "参数名": "参数值" - } -} -``` - -当可以直接回答时，请返回： -```json -{ - "action": "respond", - "response": "回复内容" -} -``` - -当需要转人工时，请返回： -```json -{ - "action": "handoff", - "reason": "转人工原因" -} -``` - -## 注意事项 -- 保持专业、友好的语气 -- 如果不确定答案，建议用户联系人工客服 -- 不要编造信息，只使用工具返回的数据 -""" - - async def customer_service_agent(state: AgentState) -> AgentState: """Customer service agent node - + Handles FAQ, company info, and general inquiries using Strapi MCP tools. - + Args: state: Current agent state - + Returns: Updated state with tool calls or response """ @@ -83,18 +27,87 @@ async def customer_service_agent(state: AgentState) -> AgentState: "Customer service agent processing", conversation_id=state["conversation_id"] ) - + state["current_agent"] = "customer_service" state["agent_history"].append("customer_service") state["state"] = ConversationState.PROCESSING.value - + # Check if we have tool results to process if state["tool_results"]: return await _generate_response_from_results(state) + + # Get detected language + locale = state.get("detected_language", "en") + + # Auto-detect category and query FAQ + message_lower = state["current_message"].lower() + + # 定义分类关键词 + category_keywords = { + "register": ["register", "sign up", "account", "login", "password", "forgot"], + "order": ["order", "place order", "cancel order", "modify order", "change order"], + "payment": ["pay", "payment", "checkout", "voucher", "discount", "promo"], + "shipment": ["ship", "shipping", "delivery", "courier", "transit", "logistics", "tracking"], + "return": ["return", "refund", "exchange", "defective", "damaged"], + } + + # 检测分类 + detected_category = None + for category, keywords in category_keywords.items(): + if any(keyword in message_lower for keyword in keywords): + detected_category = category + break + + # 检查是否已经查询过 FAQ + tool_calls = state.get("tool_calls", []) + has_faq_query = any(tc.get("tool_name") in ["query_faq", "search_knowledge_base"] for tc in tool_calls) + + # 如果检测到分类且未查询过 FAQ，自动查询 + if detected_category and not has_faq_query: + logger.info( + f"Auto-querying FAQ for category: {detected_category}", + conversation_id=state["conversation_id"] + ) + + # 自动添加 FAQ 工具调用 + state = add_tool_call( + state, + tool_name="query_faq", + arguments={ + "category": detected_category, + "locale": locale, + "limit": 5 + }, + server="strapi" + ) + state["state"] = ConversationState.TOOL_CALLING.value + return state + + # 如果询问营业时间或联系方式，自动查询公司信息 + if any(keyword in message_lower for keyword in ["opening hour", "contact", "address", "phone", "email"]) and not has_faq_query: + logger.info( + "Auto-querying company info", + conversation_id=state["conversation_id"] + ) + + state = add_tool_call( + state, + tool_name="get_company_info", + arguments={ + "section": "contact", + "locale": locale + }, + server="strapi" + ) + state["state"] = ConversationState.TOOL_CALLING.value + return state # Build messages for LLM + # Load prompt in detected language + system_prompt = get_prompt("customer_service", locale) + messages = [ - Message(role="system", content=CUSTOMER_SERVICE_PROMPT), + Message(role="system", content=system_prompt), ] # Add conversation history @@ -151,37 +164,37 @@ async def customer_service_agent(state: AgentState) -> AgentState: async def _generate_response_from_results(state: AgentState) -> AgentState: """Generate response based on tool results""" - + # Build context from tool results tool_context = [] for result in state["tool_results"]: if result["success"]: - tool_context.append(f"工具 {result['tool_name']} 返回:\n{json.dumps(result['data'], ensure_ascii=False, indent=2)}") + tool_context.append(f"Tool {result['tool_name']} returned:\n{json.dumps(result['data'], ensure_ascii=False, indent=2)}") else: - tool_context.append(f"工具 {result['tool_name']} 执行失败: {result['error']}") - - prompt = f"""基于以下工具返回的信息，生成对用户的回复。 + tool_context.append(f"Tool {result['tool_name']} failed: {result['error']}") -用户问题: {state["current_message"]} + prompt = f"""Based on the following tool returned information, generate a response to the user. -工具返回信息: +User question: {state["current_message"]} + +Tool returned information: {chr(10).join(tool_context)} -请生成一个友好、专业的回复。如果工具没有返回有用信息，请诚实告知用户并建议其他方式获取帮助。 -只返回回复内容，不要返回 JSON。""" - +Please generate a friendly and professional response. If the tool did not return useful information, honestly inform the user and suggest other ways to get help. +Return only the response content, do not return JSON.""" + messages = [ - Message(role="system", content="你是一个专业的 B2B 客服助手，请根据工具返回的信息回答用户问题。"), + Message(role="system", content="You are a professional B2B customer service assistant, please answer user questions based on tool returned information."), Message(role="user", content=prompt) ] - + try: llm = get_llm_client() response = await llm.chat(messages, temperature=0.7) state = set_response(state, response.content) return state - + except Exception as e: logger.error("Response generation failed", error=str(e)) - state = set_response(state, "抱歉，处理您的请求时遇到问题。请稍后重试或联系人工客服。") + state = set_response(state, "Sorry, there was a problem processing your request. Please try again later or contact customer support.") return state diff --git a/agent/agents/order.py b/agent/agents/order.py index f36a90d..f4ebcb9 100644 --- a/agent/agents/order.py +++ b/agent/agents/order.py @@ -21,62 +21,100 @@ ORDER_AGENT_PROMPT = """你是一个专业的 B2B 订单服务助手。 ## 可用工具 -1. **query_order** - 查询订单 +1. **get_mall_order** - 从商城 API 查询订单（推荐使用） + - order_id: 订单号（必需） + - 说明：此工具会自动使用用户的身份 token 查询商城订单详情 + +2. **query_order** - 查询历史订单 + - user_id: 用户 ID（自动注入） + - account_id: 账户 ID（自动注入） - order_id: 订单号（可选，不填则查询最近订单） - date_start: 开始日期（可选） - date_end: 结束日期（可选） - status: 订单状态（可选） -2. **track_logistics** - 物流跟踪 +3. **track_logistics** - 物流跟踪 - order_id: 订单号 - tracking_number: 物流单号（可选） -3. **modify_order** - 修改订单 +4. **modify_order** - 修改订单 - order_id: 订单号 + - user_id: 用户 ID（自动注入） - modifications: 修改内容（address/items/quantity 等） -4. **cancel_order** - 取消订单 +5. **cancel_order** - 取消订单 - order_id: 订单号 + - user_id: 用户 ID（自动注入） - reason: 取消原因 -5. **get_invoice** - 获取发票 +6. **get_invoice** - 获取发票 - order_id: 订单号 - invoice_type: 发票类型（normal/vat） -## 工具调用格式 +## 回复格式要求 -当需要使用工具时，请返回 JSON 格式： +**重要**：你必须始终返回完整的 JSON 对象，不要包含任何其他文本或解释。 + +### 格式 1：调用工具 +当需要使用工具查询信息时，返回： ```json { "action": "call_tool", - "tool_name": "工具名称", + "tool_name": "get_mall_order", "arguments": { - "参数名": "参数值" + "order_id": "202071324" } } ``` -当需要向用户询问更多信息时： +### 格式 2：询问信息 +当需要向用户询问更多信息时，返回： ```json { "action": "ask_info", - "question": "需要询问的问题" + "question": "请提供您的订单号" } ``` -当可以直接回答时： +### 格式 3：直接回复 +当可以直接回答时，返回： ```json { "action": "respond", - "response": "回复内容" + "response": "您的订单已发货，预计3天内到达" } ``` -## 重要提示 -- 订单修改和取消是敏感操作，需要确认订单号 -- 如果用户没有提供订单号，先查询他的最近订单 -- 物流查询需要订单号或物流单号 -- 对于批量操作或大金额订单，建议转人工处理 +## 示例对话 + +用户: "查询订单 202071324" +回复: +```json +{ + "action": "call_tool", + "tool_name": "get_mall_order", + "arguments": { + "order_id": "202071324" + } +} +``` + +用户: "我的订单发货了吗？" +回复: +```json +{ + "action": "ask_info", + "question": "请提供您的订单号，以便查询订单状态" +} +``` + +## 重要约束 +- **必须返回完整的 JSON 对象**，不要只返回部分内容 +- **不要添加任何 markdown 代码块标记**（如 \`\`\`json） +- **不要添加任何解释性文字**，只返回 JSON +- user_id 和 account_id 会自动注入到 arguments 中，无需手动添加 +- 如果用户提供了订单号，优先使用 get_mall_order 工具 +- 对于敏感操作（取消、修改），确保有明确的订单号 """ @@ -131,27 +169,133 @@ async def order_agent(state: AgentState) -> AgentState: try: llm = get_llm_client() response = await llm.chat(messages, temperature=0.5) - + # Parse response content = response.content.strip() - if content.startswith("```"): - content = content.split("```")[1] - if content.startswith("json"): - content = content[4:] - - result = json.loads(content) + logger.info( + "LLM response received", + conversation_id=state["conversation_id"], + response_length=len(content), + response_preview=content[:300] + ) + + # 检查是否是简化的工具调用格式：工具名称\n{参数} + # 例如：get_mall_order\n{"order_id": "202071324"} + if "\n" in content and "{" in content: + lines = content.split("\n") + if len(lines) >= 2: + tool_name_line = lines[0].strip() + json_line = "\n".join(lines[1:]).strip() + + # 如果第一行看起来像工具名称（不包含 {），且第二行是 JSON + if "{" not in tool_name_line and "{" in json_line: + logger.info( + "Detected simplified tool call format", + tool_name=tool_name_line, + json_preview=json_line[:200] + ) + + try: + arguments = json.loads(json_line) + # 直接构建工具调用 + arguments["user_id"] = state["user_id"] + arguments["account_id"] = state["account_id"] + + # Inject user_token if available + if state.get("user_token"): + arguments["user_token"] = state["user_token"] + logger.info("Injected user_token into tool call") + + # Use entity if available + if "order_id" not in arguments and state["entities"].get("order_id"): + arguments["order_id"] = state["entities"]["order_id"] + + state = add_tool_call( + state, + tool_name=tool_name_line, + arguments=arguments, + server="order" + ) + state["state"] = ConversationState.TOOL_CALLING.value + + logger.info( + "Tool call added from simplified format", + tool_name=tool_name_line, + arguments_keys=list(arguments.keys()) + ) + + return state + except json.JSONDecodeError as e: + logger.warning( + "Failed to parse simplified format", + error=str(e), + json_line=json_line[:200] + ) + + # 清理内容，去除可能的 markdown 代码块标记 + # 例如：```json\n{...}\n``` 或 ```\n{...}\n``` + if "```" in content: + # 找到第一个 ``` 后的内容 + parts = content.split("```") + if len(parts) >= 2: + content = parts[1].strip() + # 去掉可能的 "json" 标记 + if content.startswith("json"): + content = content[4:].strip() + # 去掉结尾的 ``` 标记 + if content.endswith("```"): + content = content[:-3].strip() + + # 尝试提取 JSON 对象（处理周围可能有文本的情况） + json_start = content.find("{") + json_end = content.rfind("}") + if json_start != -1 and json_end != -1 and json_end > json_start: + content = content[json_start:json_end + 1] + + logger.info( + "Cleaned content for JSON parsing", + conversation_id=state["conversation_id"], + content_length=len(content), + content_preview=content[:500] + ) + + try: + result = json.loads(content) + except json.JSONDecodeError as e: + logger.error( + "Failed to parse LLM response as JSON", + conversation_id=state["conversation_id"], + error=str(e), + content_preview=content[:500] + ) + # 如果解析失败，尝试将原始内容作为直接回复 + state = set_response(state, response.content) + return state + action = result.get("action") - + + logger.info( + "LLM action parsed", + conversation_id=state["conversation_id"], + action=action, + tool_name=result.get("tool_name") + ) + if action == "call_tool": # Inject user context into arguments arguments = result.get("arguments", {}) arguments["user_id"] = state["user_id"] arguments["account_id"] = state["account_id"] - + + # Inject user_token if available (for Mall API calls) + if state.get("user_token"): + arguments["user_token"] = state["user_token"] + logger.debug("Injected user_token into tool call") + # Use entity if available if "order_id" not in arguments and state["entities"].get("order_id"): arguments["order_id"] = state["entities"]["order_id"] - + state = add_tool_call( state, tool_name=result["tool_name"], @@ -159,6 +303,12 @@ async def order_agent(state: AgentState) -> AgentState: server="order" ) state["state"] = ConversationState.TOOL_CALLING.value + + logger.info( + "Tool call added", + tool_name=result["tool_name"], + arguments_keys=list(arguments.keys()) + ) elif action == "ask_info": state = set_response(state, result["question"]) @@ -171,13 +321,9 @@ async def order_agent(state: AgentState) -> AgentState: elif action == "handoff": state["requires_human"] = True state["handoff_reason"] = result.get("reason", "Complex order operation") - + return state - - except json.JSONDecodeError: - state = set_response(state, response.content) - return state - + except Exception as e: logger.error("Order agent failed", error=str(e)) state["error"] = str(e) diff --git a/agent/agents/router.py b/agent/agents/router.py index 45bcbb3..9bfd380 100644 --- a/agent/agents/router.py +++ b/agent/agents/router.py @@ -4,92 +4,24 @@ Router Agent - Intent recognition and routing import json from typing import Any, Optional -from core.state import AgentState, Intent, ConversationState, set_intent, add_entity +from core.state import AgentState, Intent, ConversationState, set_intent, add_entity, set_language from core.llm import get_llm_client, Message +from core.language_detector import get_cached_or_detect +from prompts import get_prompt from utils.logger import get_logger logger = get_logger(__name__) -# Intent classification prompt -CLASSIFICATION_PROMPT = """你是一个 B2B 购物网站的智能助手路由器。 -你的任务是分析用户消息，识别用户意图并提取关键实体。 - -## 可用意图分类 - -1. **customer_service** - 通用咨询 - - FAQ 问答 - - 产品使用问题 - - 公司信息查询 - - 政策咨询（退换货政策、隐私政策等） - -2. **order** - 订单相关 - - 订单查询（"我的订单在哪"、"查一下订单"） - - 物流跟踪（"快递到哪了"、"什么时候到货"） - - 订单修改（"改一下收货地址"、"修改订单数量"） - - 订单取消（"取消订单"、"不想要了"） - - 发票查询（"开发票"、"要发票"） - -3. **aftersale** - 售后服务 - - 退货申请（"退货"、"不满意想退"） - - 换货申请（"换货"、"换一个"） - - 投诉（"投诉"、"服务态度差"） - - 工单/问题反馈 - -4. **product** - 商品相关 - - 商品搜索（"有没有xx"、"找一下xx"） - - 商品推荐（"推荐"、"有什么好的"） - - 询价（"多少钱"、"批发价"、"大量购买价格"） - - 库存查询（"有货吗"、"还有多少"） - -5. **human_handoff** - 需要转人工 - - 用户明确要求转人工 - - 复杂问题 AI 无法处理 - - 敏感问题需要人工处理 - -## 实体提取 - -请从消息中提取以下实体（如果存在）： -- order_id: 订单号（如 ORD123456） -- product_id: 商品ID -- product_name: 商品名称 -- quantity: 数量 -- date_reference: 时间引用（今天、昨天、上周、具体日期等） -- tracking_number: 物流单号 -- phone: 电话号码 -- address: 地址信息 - -## 输出格式 - -请以 JSON 格式返回，包含以下字段： -```json -{ - "intent": "意图分类", - "confidence": 0.95, - "sub_intent": "子意图（可选）", - "entities": { - "entity_type": "entity_value" - }, - "reasoning": "简短的推理说明" -} -``` - -## 注意事项 -- 如果意图不明确，置信度应该较低 -- 如果无法确定意图，返回 "unknown" -- 实体提取要准确，没有的字段不要填写 -""" - - async def classify_intent(state: AgentState) -> AgentState: """Classify user intent and extract entities - + This is the first node in the workflow that analyzes the user's message and determines which agent should handle it. - + Args: state: Current agent state - + Returns: Updated state with intent and entities """ @@ -98,24 +30,38 @@ async def classify_intent(state: AgentState) -> AgentState: conversation_id=state["conversation_id"], message=state["current_message"][:100] ) - + state["state"] = ConversationState.CLASSIFYING.value state["step_count"] += 1 - + + # Detect language + detected_locale = get_cached_or_detect(state, state["current_message"]) + confidence = 0.85 # Default confidence for language detection + state = set_language(state, detected_locale, confidence) + + logger.info( + "Language detected", + locale=detected_locale, + confidence=confidence + ) + # Build context from conversation history context_summary = "" if state["context"]: context_parts = [] if state["context"].get("order_id"): - context_parts.append(f"当前讨论的订单: {state['context']['order_id']}") + context_parts.append(f"Current order: {state['context']['order_id']}") if state["context"].get("product_id"): - context_parts.append(f"当前讨论的商品: {state['context']['product_id']}") + context_parts.append(f"Current product: {state['context']['product_id']}") if context_parts: context_summary = "\n".join(context_parts) - + + # Load prompt in detected language + classification_prompt = get_prompt("router", detected_locale) + # Build messages for LLM messages = [ - Message(role="system", content=CLASSIFICATION_PROMPT), + Message(role="system", content=classification_prompt), ] # Add recent conversation history for context @@ -123,9 +69,9 @@ async def classify_intent(state: AgentState) -> AgentState: messages.append(Message(role=msg["role"], content=msg["content"])) # Add current message with context - user_content = f"用户消息: {state['current_message']}" + user_content = f"User message: {state['current_message']}" if context_summary: - user_content += f"\n\n当前上下文:\n{context_summary}" + user_content += f"\n\nCurrent context:\n{context_summary}" messages.append(Message(role="user", content=user_content)) diff --git a/agent/core/graph.py b/agent/core/graph.py index 6472001..3a2c6eb 100644 --- a/agent/core/graph.py +++ b/agent/core/graph.py @@ -7,11 +7,7 @@ import httpx from langgraph.graph import StateGraph, END from .state import AgentState, ConversationState, mark_finished, add_tool_result, set_response -from agents.router import classify_intent, route_by_intent -from agents.customer_service import customer_service_agent -from agents.order import order_agent -from agents.aftersale import aftersale_agent -from agents.product import product_agent +# 延迟导入以避免循环依赖 from config import settings from utils.logger import get_logger @@ -197,20 +193,36 @@ async def handle_error(state: AgentState) -> AgentState: def should_call_tools(state: AgentState) -> Literal["call_tools", "send_response", "back_to_agent"]: """Determine if tools need to be called""" - + + logger.debug( + "Checking if tools should be called", + conversation_id=state.get("conversation_id"), + has_tool_calls=bool(state.get("tool_calls")), + tool_calls_count=len(state.get("tool_calls", [])), + has_response=bool(state.get("response")), + state_value=state.get("state") + ) + # If there are pending tool calls, execute them if state.get("tool_calls"): + logger.info( + "Routing to tool execution", + tool_count=len(state["tool_calls"]) + ) return "call_tools" - + # If we have a response ready, send it if state.get("response"): + logger.debug("Routing to send_response (has response)") return "send_response" - + # If we're waiting for info, send the question if state.get("state") == ConversationState.AWAITING_INFO.value: + logger.debug("Routing to send_response (awaiting info)") return "send_response" - + # Otherwise, something went wrong + logger.warning("Unexpected state, routing to send_response", state=state.get("state")) return "send_response" @@ -255,13 +267,20 @@ def check_completion(state: AgentState) -> Literal["continue", "end", "error"]: def create_agent_graph() -> StateGraph: """Create the main agent workflow graph - + Returns: Compiled LangGraph workflow """ + # 延迟导入以避免循环依赖 + from agents.router import classify_intent, route_by_intent + from agents.customer_service import customer_service_agent + from agents.order import order_agent + from agents.aftersale import aftersale_agent + from agents.product import product_agent + # Create graph with AgentState graph = StateGraph(AgentState) - + # Add nodes graph.add_node("receive", receive_message) graph.add_node("classify", classify_intent) @@ -347,10 +366,11 @@ async def process_message( account_id: str, message: str, history: list[dict] = None, - context: dict = None + context: dict = None, + user_token: str = None ) -> AgentState: """Process a user message through the agent workflow - + Args: conversation_id: Chatwoot conversation ID user_id: User identifier @@ -358,12 +378,13 @@ async def process_message( message: User's message history: Previous conversation history context: Existing conversation context - + user_token: User JWT token for API calls + Returns: Final agent state with response """ from .state import create_initial_state - + # Create initial state initial_state = create_initial_state( conversation_id=conversation_id, @@ -371,7 +392,8 @@ async def process_message( account_id=account_id, current_message=message, messages=history, - context=context + context=context, + user_token=user_token ) # Get compiled graph diff --git a/agent/core/language_detector.py b/agent/core/language_detector.py new file mode 100644 index 0000000..0235760 --- /dev/null +++ b/agent/core/language_detector.py @@ -0,0 +1,150 @@ +""" +Language Detection Module + +Automatically detects user message language and maps to Strapi-supported locales. +""" +from typing import Optional +from langdetect import detect, LangDetectException +from utils.logger import get_logger + +logger = get_logger(__name__) + +# Strapi-supported locales +SUPPORTED_LOCALES = ["en", "nl", "de", "es", "fr", "it", "tr"] + +# Language code to locale mapping +LOCALE_MAP = { + "en": "en", # English + "nl": "nl", # Dutch + "de": "de", # German + "es": "es", # Spanish + "fr": "fr", # French + "it": "it", # Italian + "tr": "tr", # Turkish + # Fallback mappings for unsupported languages + "af": "en", # Afrikaans -> English + "no": "en", # Norwegian -> English + "sv": "en", # Swedish -> English + "da": "en", # Danish -> English + "pl": "en", # Polish -> English + "pt": "en", # Portuguese -> English + "ru": "en", # Russian -> English + "zh": "en", # Chinese -> English + "ja": "en", # Japanese -> English + "ko": "en", # Korean -> English + "ar": "en", # Arabic -> English + "hi": "en", # Hindi -> English +} + +# Minimum confidence threshold +MIN_CONFIDENCE = 0.7 + +# Minimum message length for reliable detection +MIN_LENGTH = 10 + + +def detect_language(text: str) -> tuple[str, float]: + """Detect language from text + + Args: + text: Input text to detect language from + + Returns: + Tuple of (locale_code, confidence_score) + locale_code: Strapi locale (en, nl, de, etc.) + confidence_score: Detection confidence (0-1), 0.0 if detection failed + """ + # Check minimum length + if len(text.strip()) < MIN_LENGTH: + logger.debug("Message too short for reliable detection", length=len(text)) + return "en", 0.0 + + try: + # Detect language using langdetect + detected = detect(text) + logger.debug("Language detected", language=detected, text_length=len(text)) + + # Map to Strapi locale + locale = map_to_locale(detected) + + return locale, 0.85 # langdetect doesn't provide confidence, use default + + except LangDetectException as e: + logger.warning("Language detection failed", error=str(e)) + return "en", 0.0 + + +def map_to_locale(lang_code: str) -> str: + """Map detected language code to Strapi locale + + Args: + lang_code: ISO 639-1 language code (e.g., "en", "nl", "de") + + Returns: + Strapi locale code, or "en" as default if not supported + """ + # Direct mapping + if lang_code in SUPPORTED_LOCALES: + return lang_code + + # Use locale map + locale = LOCALE_MAP.get(lang_code, "en") + + if locale != lang_code and locale == "en": + logger.info( + "Unsupported language mapped to default", + detected_language=lang_code, + mapped_locale=locale + ) + + return locale + + +def get_cached_or_detect(state, text: str) -> str: + """Get language from cache or detect from text + + Priority: + 1. Use state.detected_language if available + 2. Use state.context["language"] if available + 3. Detect from text + + Args: + state: Agent state + text: Input text to detect language from + + Returns: + Detected locale code + """ + # Check state first + if state.get("detected_language"): + logger.debug("Using cached language from state", language=state["detected_language"]) + return state["detected_language"] + + # Check context cache + if state.get("context", {}).get("language"): + logger.debug("Using cached language from context", language=state["context"]["language"]) + return state["context"]["language"] + + # Detect from text + locale, confidence = detect_language(text) + + if confidence < MIN_CONFIDENCE and confidence > 0: + logger.warning( + "Low detection confidence, using default", + locale=locale, + confidence=confidence + ) + + return locale + + +def is_supported_locale(locale: str) -> bool: + """Check if locale is supported + + Args: + locale: Locale code to check + + Returns: + True if locale is in supported list + """ + return locale in SUPPORTED_LOCALES diff --git a/agent/core/state.py b/agent/core/state.py index 2b98389..f585dd0 100644 --- a/agent/core/state.py +++ b/agent/core/state.py @@ -65,6 +65,7 @@ class AgentState(TypedDict): conversation_id: str # Chatwoot conversation ID user_id: str # User identifier account_id: str # B2B account identifier + user_token: Optional[str] # User JWT token for API calls # ============ Message Content ============ messages: list[dict[str, Any]] # Conversation history [{role, content}] @@ -74,6 +75,10 @@ class AgentState(TypedDict): intent: Optional[str] # Recognized intent (Intent enum value) intent_confidence: float # Intent confidence score (0-1) sub_intent: Optional[str] # Sub-intent for more specific routing + + # ============ Language Detection ============ + detected_language: Optional[str] # Detected user language (en, nl, de, etc.) + language_confidence: float # Language detection confidence (0-1) # ============ Entity Extraction ============ entities: dict[str, Any] # Extracted entities {type: value} @@ -111,10 +116,11 @@ def create_initial_state( account_id: str, current_message: str, messages: Optional[list[dict[str, Any]]] = None, - context: Optional[dict[str, Any]] = None + context: Optional[dict[str, Any]] = None, + user_token: Optional[str] = None ) -> AgentState: """Create initial agent state for a new message - + Args: conversation_id: Chatwoot conversation ID user_id: User identifier @@ -122,7 +128,8 @@ def create_initial_state( current_message: User's message to process messages: Previous conversation history context: Existing conversation context - + user_token: User JWT token for API calls + Returns: Initialized AgentState """ @@ -131,6 +138,7 @@ def create_initial_state( conversation_id=conversation_id, user_id=user_id, account_id=account_id, + user_token=user_token, # Messages messages=messages or [], @@ -140,6 +148,10 @@ def create_initial_state( intent=None, intent_confidence=0.0, sub_intent=None, + + # Language + detected_language=None, + language_confidence=0.0, # Entities entities={}, @@ -270,3 +282,21 @@ def mark_finished(state: AgentState) -> AgentState: state["finished"] = True state["state"] = ConversationState.COMPLETED.value return state + + +def set_language(state: AgentState, language: str, confidence: float) -> AgentState: + """Set the detected language in state + + Args: + state: Agent state + language: Detected locale code (en, nl, de, etc.) + confidence: Detection confidence (0-1) + + Returns: + Updated state + """ + state["detected_language"] = language + state["language_confidence"] = confidence + # Also cache in context for future reference + state["context"]["language"] = language + return state diff --git a/agent/integrations/chatwoot.py b/agent/integrations/chatwoot.py index 6464443..2742e3e 100644 --- a/agent/integrations/chatwoot.py +++ b/agent/integrations/chatwoot.py @@ -56,10 +56,10 @@ class ChatwootClient: self, api_url: Optional[str] = None, api_token: Optional[str] = None, - account_id: int = 1 + account_id: int = 2 ): """Initialize Chatwoot client - + Args: api_url: Chatwoot API URL, defaults to settings api_token: API access token, defaults to settings @@ -69,7 +69,7 @@ class ChatwootClient: self.api_token = api_token or settings.chatwoot_api_token self.account_id = account_id self._client: Optional[httpx.AsyncClient] = None - + logger.info("Chatwoot client initialized", api_url=self.api_url) async def _get_client(self) -> httpx.AsyncClient: diff --git a/agent/prompts/__init__.py b/agent/prompts/__init__.py new file mode 100644 index 0000000..09c8946 --- /dev/null +++ b/agent/prompts/__init__.py @@ -0,0 +1,9 @@ +""" +Multi-language Prompt System + +Exports: + get_prompt() - Load system prompt for agent type and locale +""" +from .base import get_prompt, PromptLoader, SUPPORTED_LOCALES, DEFAULT_LOCALE + +__all__ = ["get_prompt", "PromptLoader", "SUPPORTED_LOCALES", "DEFAULT_LOCALE"] diff --git a/agent/prompts/aftersale/en.yaml b/agent/prompts/aftersale/en.yaml new file mode 100644 index 0000000..18b4675 --- /dev/null +++ b/agent/prompts/aftersale/en.yaml @@ -0,0 +1,152 @@ +# Aftersale Agent - English Prompt + +system_prompt: | + You are a professional B2B after-sales service assistant. + Your role is to help users handle after-sales issues, including: + - Return requests + - Exchange requests + - Complaint handling + - Ticket creation + - After-sales status inquiries + - Return policy consultations + - After-sales question answering + + ## Available Tools + + ### Knowledge Base Query Tools + + **query_faq** - Query after-sales FAQ + - category: FAQ category, options: + * "return" - Return related (return policy, return process, return costs) + * "shipment" - Shipping related + * "payment" - Payment related + - locale: Language, default "en" + - limit: Number of results to return, default 5 + + **search_knowledge_base** - Search knowledge base + - query: Search keywords + - locale: Language, default "en" + - limit: Number of results to return, default 10 + + ### After-sales Operation Tools + + **apply_return** - Submit return request + - order_id: Order number + - items: List of items to return [{item_id, quantity, reason}] + - description: Problem description + - images: List of image URLs (optional) + + **apply_exchange** - Submit exchange request + - order_id: Order number + - items: List of items to exchange [{item_id, reason}] + - description: Problem description + + **create_complaint** - Create complaint + - type: Complaint type (product_quality/service/logistics/other) + - title: Complaint title + - description: Detailed description + - related_order_id: Related order number (optional) + - attachments: List of attachment URLs (optional) + + **create_ticket** - Create support ticket + - category: Ticket category + - priority: Priority (low/medium/high/urgent) + - title: Ticket title + - description: Detailed description + + **query_aftersale_status** - Query after-sales status + - aftersale_id: After-sales order number (optional, leave blank to query all) + + ## Important Rules + + 1. **Query FAQ First**: + - When users ask about return policy, return process, return conditions/退货政策/退货流程/退货条件, **you MUST first call** `query_faq(category="return")` to query the knowledge base + - Answer users based on knowledge base information + - If knowledge base information is insufficient, consider transferring to human or asking for more information + + 2. **Category Detection**: + - Return/refund/exchange/退货/退款/换货 → category="return" + - Shipping/delivery/物流/配送 → category="shipment" + - Payment/checkout/支付/付款 → category="payment" + + **CRITICAL**: When users ask about "退货" (return), "退款" (refund), "怎么退货" (how to return), + "退货政策" (return policy), or similar questions, you MUST use category="return" + + 3. **Fallback Strategy**: + - If `query_faq` returns 0 results or an error, try using `search_knowledge_base` with relevant keywords + - For example, if "return" category query fails, search for "return policy" or "退货政策" + - Only suggest human support after both query_faq and search_knowledge_base fail + + 4. **General Inquiry Handling**: + - First use `search_knowledge_base` to search for relevant information + - If answer is found, respond directly + - If not found, ask user for more details + + ## Tool Call Format + + When you need to use a tool, return JSON format: + ```json + { + "action": "call_tool", + "tool_name": "tool_name", + "arguments": { + "parameter_name": "parameter_value" + } + } + ``` + + When you need to ask user for more information: + ```json + { + "action": "ask_info", + "question": "Question to ask user", + "required_fields": ["list of required fields"] + } + ``` + + When you can answer directly: + ```json + { + "action": "respond", + "response": "response content" + } + ``` + + ## After-sales Process Guidance + + Return process: + 1. First query FAQ to understand return policy + 2. Confirm order number and return items + 3. Understand return reason + 4. Collect problem description and images (for quality issues) + 5. Submit return request + 6. Inform user of next steps + + Exchange process: + 1. Confirm order number and exchange items + 2. Understand exchange reason + 3. Confirm stock availability + 4. Submit exchange request + + ## Notes + - **Prioritize using FAQ tools** to provide accurate official information + - After-sales requests require complete information to submit + - Express understanding and apology for user's issues + - For complex complaints, suggest transferring to human handling + - Large refund amounts require special confirmation + +tool_descriptions: + query_faq: "Query after-sales FAQ" + search_knowledge_base: "Search knowledge base" + apply_return: "Submit return request" + apply_exchange: "Submit exchange request" + create_complaint: "Create complaint" + create_ticket: "Create support ticket" + query_aftersale_status: "Query after-sales status" + +response_templates: + error: "Sorry, an error occurred while processing your after-sales request. Please try again or contact customer support." + awaiting_info: "Please provide more details so I can process your request." + return_submitted: "Your return request has been submitted successfully. Return ID: {aftersale_id}. We will review it within 3 business days." + exchange_submitted: "Your exchange request has been submitted successfully. Request ID: {aftersale_id}." + ticket_created: "Your support ticket has been created. Ticket ID: {ticket_id}. Our team will respond shortly." diff --git a/agent/prompts/base.py b/agent/prompts/base.py new file mode 100644 index 0000000..353e0e0 --- /dev/null +++ b/agent/prompts/base.py @@ -0,0 +1,110 @@ +""" +Multi-language Prompt Loader + +Loads system prompts for different agents in different languages. +""" +import yaml +from pathlib import Path +from typing import Optional +from utils.logger import get_logger + +logger = get_logger(__name__) + +# Base directory for prompt templates +PROMPTS_DIR = Path(__file__).parent + +# Supported locales +SUPPORTED_LOCALES = ["en", "nl", "de", "es", "fr", "it", "tr"] + +# Default locale +DEFAULT_LOCALE = "en" + + +class PromptLoader: + """Load and cache prompt templates for different languages""" + + def __init__(self): + self._cache = {} + + def get_prompt(self, agent_type: str, locale: str) -> str: + """Get system prompt for agent type and locale + + Args: + agent_type: Type of agent (customer_service, aftersale, order, product, router) + locale: Language locale (en, nl, de, etc.) + + Returns: + System prompt string + """ + # Validate locale + if locale not in SUPPORTED_LOCALES: + logger.warning( + "Unsupported locale, using default", + requested_locale=locale, + default_locale=DEFAULT_LOCALE + ) + locale = DEFAULT_LOCALE + + # Check cache + cache_key = f"{agent_type}:{locale}" + if cache_key in self._cache: + return self._cache[cache_key] + + # Load prompt file + prompt_file = PROMPTS_DIR / agent_type / f"{locale}.yaml" + + if not prompt_file.exists(): + logger.warning( + "Prompt file not found, using default", + agent_type=agent_type, + locale=locale, + file=str(prompt_file) + ) + # Fallback to English + prompt_file = PROMPTS_DIR / agent_type / f"{DEFAULT_LOCALE}.yaml" + + if not prompt_file.exists(): + # Fallback to hardcoded English prompt + logger.error("No prompt file found, using fallback", agent_type=agent_type) + return self._get_fallback_prompt(agent_type) + + # Load and parse YAML + try: + with open(prompt_file, 'r', encoding='utf-8') as f: + data = yaml.safe_load(f) + + prompt = data.get('system_prompt', '') + self._cache[cache_key] = prompt + return prompt + + except Exception as e: + logger.error("Failed to load prompt file", file=str(prompt_file), error=str(e)) + return self._get_fallback_prompt(agent_type) + + def _get_fallback_prompt(self, agent_type: str) -> str: + """Get fallback prompt if file loading fails""" + fallbacks = { + "customer_service": """You are a professional B2B customer service assistant. Help users with their questions.""", + "aftersale": """You are a professional B2B aftersale service assistant. Help users with returns and exchanges.""", + "order": """You are a professional B2B order assistant. Help users with order inquiries.""", + "product": """You are a professional B2B product assistant. Help users find products.""", + "router": """You are an AI assistant that routes user messages to appropriate agents.""" + } + return fallbacks.get(agent_type, "You are a helpful AI assistant.") + + +# Global loader instance +_loader = PromptLoader() + + +def get_prompt(agent_type: str, locale: str) -> str: + """Get system prompt for agent type and locale + + Args: + agent_type: Type of agent (customer_service, aftersale, order, product, router) + locale: Language locale (en, nl, de, etc.) + + Returns: + System prompt string + """ + return _loader.get_prompt(agent_type, locale) diff --git a/agent/prompts/customer_service/en.yaml b/agent/prompts/customer_service/en.yaml new file mode 100644 index 0000000..bf938e0 --- /dev/null +++ b/agent/prompts/customer_service/en.yaml @@ -0,0 +1,123 @@ +# Customer Service Agent - English Prompt + +system_prompt: | + You are a professional B2B customer service assistant for an online shopping platform. + Your role is to help users with general inquiries, including: + - FAQ (Frequently Asked Questions) + - Company information (opening hours, contact details) + - Policy inquiries (return policy, privacy policy, shipping policy) + - Product usage guidance + - Other general questions + + ## Available Tools + + ### FAQ Query Tool + + **query_faq** - Query FAQ by category + - category: Category name, options: + * "register" - Account related (registration, login, password) + * "order" - Order related (placing orders, cancellations, modifications) + * "pre-order" - Pre-order related + * "payment" - Payment related (payment methods, vouchers) + * "shipment" - Shipping related (logistics, shipping costs, delivery time) + * "return" - Return related (return policy, return process) + * "other" - Other questions + - locale: Language, default "en" + - limit: Number of results to return, default 5 + + **search_knowledge_base** - Search knowledge base + - query: Search keywords + - locale: Language, default "en" + - limit: Number of results to return, default 10 + + ### Company Information Tool + + **get_company_info** - Get company information + - section: Information category + * "contact" - Contact information and opening hours + * "about" - About us + * "service" - Service information + + ### Policy Document Tool + + **get_policy** - Get policy documents + - policy_type: Policy type + * "return_policy" - Return policy + * "privacy_policy" - Privacy policy + * "terms_of_service" - Terms of service + * "shipping_policy" - Shipping policy + * "payment_policy" - Payment policy + + ## Important Rules + + 1. **Use FAQ Tools First**: + - When users ask questions, determine which category it belongs to + - Automatically call `query_faq` with the appropriate category + - Answer accurately based on knowledge base information + + 2. **Category Detection**: + - Account/registration/login/注册/账号/登录/密码 → category="register" + - Order/place order/cancel/订单/下单/取消订单 → category="order" + - Payment/checkout/voucher/支付/付款/优惠券 → category="payment" + - Shipping/delivery/courier/物流/配送/快递/运输 → category="shipment" + - Return/refund/exchange/退货/退款/换货 → category="return" + - Opening hours/contact/营业时间/联系方式 → get_company_info(section="contact") + + **CRITICAL**: When users ask about "注册账号" (register account), "怎么注册" (how to register), + "账号注册" (account registration), or similar questions, you MUST use category="register" + + 3. **Don't Make Up Information**: + - Only use data returned by tools + - If you can't find an answer, honestly inform the user and suggest contacting human support + + 4. **Fallback Strategy**: + - If `query_faq` returns 0 results or an error, try using `search_knowledge_base` with relevant keywords + - For example, if "register" category query fails, search for "register account" or "registration" + - Only suggest human support after both query_faq and search_knowledge_base fail + + ## Tool Call Format + + When you need to use a tool, return JSON format: + ```json + { + "action": "call_tool", + "tool_name": "tool_name", + "arguments": { + "parameter_name": "parameter_value" + } + } + ``` + + When you can answer directly: + ```json + { + "action": "respond", + "response": "response content" + } + ``` + + When you need to transfer to human: + ```json + { + "action": "handoff", + "reason": "reason for handoff" + } + ``` + + ## Notes + - Maintain a professional and friendly tone + - Prioritize using tools to query knowledge base + - Thank users for their patience + - For complex issues, suggest contacting human customer service + +tool_descriptions: + query_faq: "Query FAQ by category" + search_knowledge_base: "Search knowledge base" + get_company_info: "Get company information" + get_policy: "Get policy documents" + +response_templates: + error: "Sorry, an error occurred while processing your request. Please try again or contact customer support." + handoff: "I'm transferring you to a human agent who can better assist you." + awaiting_info: "Please provide more information so I can help you better." + no_results: "I couldn't find relevant information. Would you like me to connect you with a human agent?" diff --git a/agent/prompts/order/en.yaml b/agent/prompts/order/en.yaml new file mode 100644 index 0000000..f1b0fd5 --- /dev/null +++ b/agent/prompts/order/en.yaml @@ -0,0 +1,82 @@ +# Order Agent - English Prompt + +system_prompt: | + You are a professional B2B order management assistant. + Your role is to help users with order-related inquiries, including: + - Order status queries + - Logistics tracking + - Order modifications (address, quantity, items) + - Order cancellations + - Invoice requests + - Payment status checks + + ## Available Tools + + **query_order** - Query order details + - order_id: Order number (required) + + **track_shipment** - Track shipment status + - tracking_number: Tracking number (optional) + - order_id: Order number (optional) + + **modify_order** - Modify existing order + - order_id: Order number + - modifications: {field: new_value} + + **cancel_order** - Cancel order + - order_id: Order number + - reason: Cancellation reason + + **request_invoice** - Request invoice + - order_id: Order number + - invoice_details: Invoice information + + ## Important Rules + + 1. **Order Recognition**: + - Order/订单/订单号/单号 → Order related queries + - Shipment tracking/物流查询/快递查询/配送状态 → Use track_shipment + - Cancel order/取消订单/撤销订单 → Use cancel_order + - Modify order/修改订单/更改订单 → Use modify_order + - Invoice/发票/收据 → Use request_invoice + + 2. Always verify order belongs to user before providing details + 3. For modifications/cancellations, check if order is still in modifiable state + 4. Clearly explain what can and cannot be done based on order status + 5. If action requires human approval, inform user and transfer to human + + 6. **User Language**: + - Respond in the same language as the user's inquiry + - For Chinese inquiries, respond in Chinese + - For English inquiries, respond in English + + ## Tool Call Format + + ```json + { + "action": "call_tool", + "tool_name": "tool_name", + "arguments": {"parameter": "value"} + } + ``` + + Or to respond directly: + ```json + { + "action": "respond", + "response": "Your answer here" + } + ``` + +tool_descriptions: + query_order: "Query order details and status" + track_shipment: "Track shipment delivery status" + modify_order: "Modify existing order" + cancel_order: "Cancel an order" + request_invoice: "Request invoice for order" + +response_templates: + error: "Sorry, I couldn't process your order request. Please try again." + order_not_found: "I couldn't find an order with that number. Please verify and try again." + cannot_modify: "This order cannot be modified because it's already being processed." + cannot_cancel: "This order cannot be cancelled because it's already shipped." diff --git a/agent/prompts/product/en.yaml b/agent/prompts/product/en.yaml new file mode 100644 index 0000000..c016fa4 --- /dev/null +++ b/agent/prompts/product/en.yaml @@ -0,0 +1,83 @@ +# Product Agent - English Prompt + +system_prompt: | + You are a professional B2B product consultant assistant. + Your role is to help users with product-related inquiries, including: + - Product search + - Product recommendations + - Price inquiries (wholesale, bulk pricing) + - Stock availability checks + - Product specifications + - Product comparisons + + ## Available Tools + + **search_products** - Search for products + - query: Search keywords + - category: Product category (optional) + - filters: {attribute: value} (optional) + + **get_product_details** - Get detailed product information + - product_id: Product ID or SKU + + **check_stock** - Check product availability + - product_id: Product ID + - quantity: Required quantity (optional) + + **get_pricing** - Get pricing information + - product_id: Product ID + - quantity: Quantity for pricing (optional, for tiered pricing) + + **recommend_products** - Get product recommendations + - category: Product category + - limit: Number of recommendations + + ## Important Rules + + 1. **Product Recognition**: + - Product search/产品搜索/找产品/商品 → Use search_products + - Price/价格/报价/多少钱 → Use get_pricing + - Stock/库存/有没有货/现货 → Use check_stock + - Product details/产品详情/产品信息/产品规格 → Use get_product_details + - Recommendation/推荐/推荐产品 → Use recommend_products + + 2. For B2B customers, prioritize wholesale/bulk pricing information + 3. Always check stock availability before suggesting purchases + 4. Provide accurate product specifications from the catalog + 5. For large quantity orders, suggest contacting sales for special pricing + + 6. **User Language**: + - Respond in the same language as the user's inquiry + - For Chinese inquiries, respond in Chinese + - For English inquiries, respond in English + + ## Tool Call Format + + ```json + { + "action": "call_tool", + "tool_name": "tool_name", + "arguments": {"parameter": "value"} + } + ``` + + Or to respond directly: + ```json + { + "action": "respond", + "response": "Your answer here" + } + ``` + +tool_descriptions: + search_products: "Search for products by keywords or category" + get_product_details: "Get detailed product information" + check_stock: "Check product stock availability" + get_pricing: "Get pricing information including bulk discounts" + recommend_products: "Get product recommendations" + +response_templates: + error: "Sorry, I couldn't process your product request. Please try again." + product_not_found: "I couldn't find a product matching your search. Would you like me to help you search differently?" + out_of_stock: "This product is currently out of stock. Would you like to be notified when it's available?" + bulk_pricing: "For bulk orders, please contact our sales team for special pricing." diff --git a/agent/prompts/router/en.yaml b/agent/prompts/router/en.yaml new file mode 100644 index 0000000..b23586f --- /dev/null +++ b/agent/prompts/router/en.yaml @@ -0,0 +1,76 @@ +# Router Agent - English Prompt + +system_prompt: | + You are an intelligent router for a B2B shopping website assistant. + Your task is to analyze user messages, identify user intent, and extract key entities. + + ## Available Intent Categories + + 1. **customer_service** - General inquiries / 一般咨询 + - FAQ Q&A / 常见问题 + - Product usage questions / 产品使用问题 + - Company information queries / 公司信息查询 + - Policy inquiries / 政策咨询 (return policy/退货政策, privacy policy/隐私政策, etc.) + - Account/registration/账号/注册/登录 + + 2. **order** - Order related / 订单相关 + - Order queries ("Where is my order", "我的订单在哪", "查订单") + - Logistics tracking ("Where's the shipment", "物流查询", "快递到哪里了") + - Order modifications ("Change shipping address", "修改收货地址", "改订单") + - Order cancellations ("Cancel order", "取消订单", "不要了") + - Invoice queries ("Need invoice", "要发票", "开发票") + + 3. **aftersale** - After-sales service / 售后服务 + - Return requests ("Return", "退货", "不满意要退货") + - Exchange requests ("Exchange", "换货", "换个") + - Complaints ("Complain", "投诉", "服务态度差") + - Ticket/issue feedback / 问题反馈 + + 4. **product** - Product related / 产品相关 + - Product search ("Do you have xx", "有没有xx", "找产品") + - Product recommendations ("Recommend", "推荐什么", "哪个好") + - Price inquiries ("How much", "多少钱", "批发价", "批量价格") + - Stock queries ("In stock", "有货吗", "库存多少") + + 5. **human_handoff** - Need human transfer / 需要人工 + - User explicitly requests human agent ("转人工", "找客服") + - Complex issues AI cannot handle + - Sensitive issues requiring human intervention + + ## Entity Extraction + + Please extract the following entities from the message (if present): + - order_id: Order number (e.g., ORD123456) + - product_id: Product ID + - product_name: Product name + - quantity: Quantity + - date_reference: Time reference (today, yesterday, last week, specific date, etc.) + - tracking_number: Tracking number + - phone: Phone number + - address: Address information + + ## Output Format + + Please return in JSON format with the following fields: + ```json + { + "intent": "intent_category", + "confidence": 0.95, + "sub_intent": "sub-intent (optional)", + "entities": { + "entity_type": "entity_value" + }, + "reasoning": "Brief reasoning explanation" + } + ``` + + ## Notes + - If intent is unclear, confidence should be lower + - If unable to determine intent, return "unknown" + - Entity extraction should be accurate, don't fill in fields that don't exist + +tool_descriptions: + classify: "Classify user intent and extract entities" + +response_templates: + unknown: "I'm not sure what you need help with. Could you please provide more details?" diff --git a/agent/requirements.txt b/agent/requirements.txt index 3df9ebd..a202b4e 100644 --- a/agent/requirements.txt +++ b/agent/requirements.txt @@ -37,3 +37,9 @@ pytest-cov>=4.1.0 # MCP Client mcp>=1.0.0 + +# Language Detection +langdetect>=1.0.9 + +# YAML Config +pyyaml>=6.0 diff --git a/agent/test_endpoint.py b/agent/test_endpoint.py new file mode 100644 index 0000000..46bbae7 --- /dev/null +++ b/agent/test_endpoint.py @@ -0,0 +1,55 @@ +""" +测试端点 - 用于测试退货 FAQ +""" +from fastapi import APIRouter, HTTPException +from pydantic import BaseModel + +from core.graph import process_message + +router = APIRouter(prefix="/test", tags=["test"]) + + +class TestRequest(BaseModel): + """测试请求""" + conversation_id: str + user_id: str + account_id: str + message: str + history: list = [] + context: dict = {} + + +@router.post("/faq") +async def test_faq(request: TestRequest): + """测试 FAQ 回答 + + 简化的测试端点，用于测试退货相关 FAQ + """ + try: + # 调用处理流程 + result = await process_message( + conversation_id=request.conversation_id, + user_id=request.user_id, + account_id=request.account_id, + message=request.message, + history=request.history, + context=request.context + ) + + return { + "success": True, + "response": result.get("response"), + "intent": result.get("intent"), + "tool_calls": result.get("tool_calls", []), + "step_count": result.get("step_count", 0) + } + + except Exception as e: + import traceback + traceback.print_exc() + + return { + "success": False, + "error": str(e), + "response": None + } diff --git a/agent/utils/token_manager.py b/agent/utils/token_manager.py new file mode 100644 index 0000000..1b65db2 --- /dev/null +++ b/agent/utils/token_manager.py @@ -0,0 +1,105 @@ +""" +Token Manager - 管理 JWT token 的获取和使用 + +支持从 Chatwoot contact custom_attributes 中获取用户的 JWT token +""" +from typing import Optional +from utils.logger import get_logger + +logger = get_logger(__name__) + + +class TokenManager: + """管理用户 JWT token""" + + @staticmethod + def extract_token_from_contact(contact: Optional[dict]) -> Optional[str]: + """从 Chatwoot contact 中提取 JWT token + + Args: + contact: Chatwoot contact 对象，包含 custom_attributes + + Returns: + JWT token 字符串，如果未找到则返回 None + """ + if not contact: + logger.debug("No contact provided") + return None + + # 从 custom_attributes 中获取 token + custom_attributes = contact.get("custom_attributes", {}) + if not custom_attributes: + logger.debug("No custom_attributes in contact") + return None + + # 尝试多种可能的字段名 + token = ( + custom_attributes.get("jwt_token") or + custom_attributes.get("mall_token") or + custom_attributes.get("access_token") or + custom_attributes.get("auth_token") or + custom_attributes.get("token") + ) + + if token: + logger.debug("JWT token found in contact attributes") + # 只记录 token 的前几个字符用于调试 + logger.debug(f"Token prefix: {token[:20]}...") + else: + logger.debug("No JWT token found in contact custom_attributes") + + return token + + @staticmethod + def validate_token(token: str) -> bool: + """验证 token 格式是否有效 + + Args: + token: JWT token 字符串 + + Returns: + True 如果 token 格式有效 + """ + if not token or not isinstance(token, str): + return False + + # JWT token 通常是 header.payload.signature 格式 + parts = token.split(".") + if len(parts) != 3: + logger.warning("Invalid JWT token format") + return False + + return True + + @staticmethod + def get_token_from_context(context: dict, contact: Optional[dict] = None) -> Optional[str]: + """从上下文或 contact 中获取 token + + 优先级：context > contact + + Args: + context: 对话上下文 + contact: Chatwoot contact 对象 + + Returns: + JWT token 或 None + """ + # 首先尝试从 context 中获取（可能之前的对话中已经获取） + token = context.get("user_token") + if token and TokenManager.validate_token(token): + logger.debug("Using token from context") + return token + + # 其次尝试从 contact 中获取 + if contact: + token = TokenManager.extract_token_from_contact(contact) + if token and TokenManager.validate_token(token): + logger.debug("Using token from contact") + return token + + logger.debug("No valid JWT token found") + return None + + +# 全局 token 管理器 +token_manager = TokenManager() diff --git a/agent/webhooks/chatwoot_webhook.py b/agent/webhooks/chatwoot_webhook.py index 267c97b..2033fa1 100644 --- a/agent/webhooks/chatwoot_webhook.py +++ b/agent/webhooks/chatwoot_webhook.py @@ -13,6 +13,7 @@ from core.graph import process_message from integrations.chatwoot import get_chatwoot_client, ConversationStatus from utils.cache import get_cache_manager from utils.logger import get_logger +from utils.token_manager import TokenManager logger = get_logger(__name__) @@ -50,6 +51,7 @@ class WebhookConversation(BaseModel): additional_attributes: Optional[dict] = None can_reply: Optional[bool] = None channel: Optional[str] = None + meta: Optional[dict] = None # Contains sender info including custom_attributes class WebhookContact(BaseModel): @@ -111,24 +113,25 @@ def verify_webhook_signature(payload: bytes, signature: str) -> bool: # ============ Message Processing ============ -async def handle_incoming_message(payload: ChatwootWebhookPayload) -> None: +async def handle_incoming_message(payload: ChatwootWebhookPayload, cookie_token: str = None) -> None: """Process incoming message from Chatwoot - + Args: payload: Webhook payload + cookie_token: User token from request cookies """ conversation = payload.conversation if not conversation: logger.warning("No conversation in payload") return - + conversation_id = str(conversation.id) content = payload.content - + if not content: logger.debug("Empty message content, skipping") return - + # Get user/contact info contact = payload.contact or payload.sender user_id = str(contact.id) if contact else "unknown" @@ -137,21 +140,54 @@ async def handle_incoming_message(payload: ChatwootWebhookPayload) -> None: # Chatwoot webhook includes account info at the top level account_obj = payload.account account_id = str(account_obj.get("id")) if account_obj else "1" - + + # 优先使用 Cookie 中的 token + user_token = cookie_token + + # 如果 Cookie 中没有，尝试从多个来源提取 token + if not user_token: + # 1. 尝试从 contact/custom_attributes 获取 + if contact: + contact_dict = contact.model_dump() if hasattr(contact, 'model_dump') else contact.__dict__ + user_token = TokenManager.extract_token_from_contact(contact_dict) + logger.debug("Extracted token from contact", has_token=bool(user_token)) + + # 2. 尝试从 conversation.meta.sender.custom_attributes 获取（Chatwoot SDK setUser 设置的位置） + if not user_token and conversation: + # 记录 conversation 的类型和内容用于调试 + logger.debug("Conversation object type", type=str(type(conversation))) + if hasattr(conversation, 'model_dump'): + conv_dict = conversation.model_dump() + logger.debug("Conversation dict keys", keys=list(conv_dict.keys())) + logger.debug("Has meta", has_meta='meta' in conv_dict) + + meta_sender = conv_dict.get('meta', {}).get('sender', {}) + if meta_sender.get('custom_attributes'): + user_token = TokenManager.extract_token_from_contact({'custom_attributes': meta_sender['custom_attributes']}) + logger.info("Token found in conversation.meta.sender.custom_attributes", token_prefix=user_token[:20] if user_token else None) + + if user_token: + logger.info("JWT token found", user_id=user_id, source="cookie" if cookie_token else "contact") + logger.info( "Processing incoming message", conversation_id=conversation_id, user_id=user_id, + has_token=bool(user_token), message_length=len(content) ) - + # Load conversation context from cache cache = get_cache_manager() await cache.connect() - - context = await cache.get_context(conversation_id) + + context = await cache.get_context(conversation_id) or {} history = await cache.get_messages(conversation_id) - + + # Add token to context if available + if user_token: + context["user_token"] = user_token + try: # Process message through agent workflow final_state = await process_message( @@ -160,7 +196,8 @@ async def handle_incoming_message(payload: ChatwootWebhookPayload) -> None: account_id=account_id, message=content, history=history, - context=context + context=context, + user_token=user_token ) # Get response @@ -306,11 +343,16 @@ async def chatwoot_webhook( background_tasks: BackgroundTasks ): """Chatwoot webhook endpoint - + Receives events from Chatwoot and processes them asynchronously. """ # Get raw body for signature verification body = await request.body() + + # 尝试从请求 Cookie 中获取用户 Token + user_token = request.cookies.get("token") # 从 Cookie 读取 token + if user_token: + logger.info("User token found in request cookies") # Verify signature signature = request.headers.get("X-Chatwoot-Signature", "") @@ -340,7 +382,7 @@ async def chatwoot_webhook( if event == "message_created": # Only process incoming messages from contacts if payload.message_type == "incoming": - background_tasks.add_task(handle_incoming_message, payload) + background_tasks.add_task(handle_incoming_message, payload, user_token) elif event == "conversation_created": background_tasks.add_task(handle_conversation_created, payload) diff --git a/docker-compose.yml b/docker-compose.yml index 7ff5967..704e59f 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -40,6 +40,24 @@ services: retries: 5 restart: unless-stopped + # Nginx (Static File Server) + nginx: + image: nginx:alpine + container_name: ai_nginx + ports: + - "8080:80" + volumes: + - ./docs:/usr/share/nginx/html/docs:ro + - ./nginx.conf:/etc/nginx/nginx.conf:ro + networks: + - ai_network + restart: unless-stopped + healthcheck: + test: ["CMD", "wget", "--quiet", "--tries=1", "--spider", "http://localhost/test-chat.html"] + interval: 30s + timeout: 10s + retries: 3 + # ============ Messaging Platform ============ # Chatwoot @@ -51,6 +69,8 @@ services: RAILS_ENV: production SECRET_KEY_BASE: ${CHATWOOT_SECRET_KEY_BASE} FRONTEND_URL: ${CHATWOOT_FRONTEND_URL:-http://localhost:3000} + # 允许 Widget 从多个域名访问（逗号分隔） + ALLOWED_DOMAINS_FOR_WIDGET: ${CHATWOOT_ALLOWED_DOMAINS:-http://localhost:3000,http://localhost:8080,http://127.0.0.1:3000,http://127.0.0.1:8080} POSTGRES_HOST: postgres POSTGRES_DATABASE: ${POSTGRES_DB:-chatwoot} POSTGRES_USERNAME: ${POSTGRES_USER:-chatwoot} @@ -131,7 +151,7 @@ services: MAX_CONVERSATION_STEPS: ${MAX_CONVERSATION_STEPS:-10} CONVERSATION_TIMEOUT: ${CONVERSATION_TIMEOUT:-3600} ports: - - "8005:8000" + - "8000:8000" volumes: - ./agent:/app - agent_logs:/app/logs @@ -172,9 +192,17 @@ services: context: ./mcp_servers/order_mcp dockerfile: Dockerfile container_name: ai_order_mcp + env_file: + - .env environment: HYPERF_API_URL: ${HYPERF_API_URL} HYPERF_API_TOKEN: ${HYPERF_API_TOKEN} + MALL_API_URL: ${MALL_API_URL} + MALL_API_TOKEN: ${MALL_API_TOKEN} + MALL_TENANT_ID: ${MALL_TENANT_ID:-2} + MALL_CURRENCY_CODE: ${MALL_CURRENCY_CODE:-EUR} + MALL_LANGUAGE_ID: ${MALL_LANGUAGE_ID:-1} + MALL_SOURCE: ${MALL_SOURCE:-us.qa1.gaia888.com} LOG_LEVEL: ${LOG_LEVEL:-INFO} ports: - "8002:8002" diff --git a/docs/PORT_SCHEME.md b/docs/PORT_SCHEME.md new file mode 100644 index 0000000..2609421 --- /dev/null +++ b/docs/PORT_SCHEME.md @@ -0,0 +1,108 @@ +# 端口规划方案 + +本文档定义了 B2B AI Shopping Assistant 项目的端口分配规范。 + +## 📋 端口分配总览 + +### 1️⃣ 基础设施层 (3000-3999) + +用于前端界面、Web 控制台等面向用户的服务。 + +| 端口 | 服务 | 说明 | 状态 | +|------|------|------|------| +| 3000 | Chatwoot | 客户支持平台主界面 | ✅ 使用中 | +| 3001-3009 | - | 预留给 Web 界面服务 | 🔄 预留 | +| 3010-3099 | - | 预留给基础设施扩展 | 🔄 预留 | + +### 2️⃣ 应用服务层 (8000-8999) + +核心 AI 和 MCP 后端服务。 + +| 端口 | 服务 | 说明 | 状态 | +|------|------|------|------| +| 8000 | Agent | LangGraph AI Agent 主服务 | ✅ 使用中 | +| 8001 | Strapi MCP | 知识库和 FAQ 服务 | ✅ 使用中 | +| 8002 | Order MCP | 订单查询服务 | ✅ 使用中 | +| 8003 | Aftersale MCP | 售后服务 | ✅ 使用中 | +| 8004 | Product MCP | 商品服务 | ✅ 使用中 | +| 8005-8009 | - | 预留给其他 MCP 服务 | 🔄 预留 | +| 8010-8099 | - | 预留给应用服务扩展 | 🔄 预留 | + +### 3️⃣ 静态资源服务 (8080-8099) + +用于静态文件托管、反向代理等。 + +| 端口 | 服务 | 说明 | 状态 | +|------|------|------|------| +| 8080 | Nginx | 静态文件服务器 (测试页面等) | ✅ 使用中 | +| 8081-8099 | - | 预留给其他静态资源服务 | 🔄 预留 | + +### 4️⃣ 内部通信 (9000+) + +**注意**：此区间端口仅用于容器内部通信，不对外暴露。 + +| 服务 | 内部端口 | 说明 | +|------|----------|------| +| PostgreSQL | 5432 | 仅容器内部访问 | +| Redis | 6379 | 仅容器内部访问 | + +## 🔧 访问地址 + +### 生产/开发环境 + +```bash +# Chatwoot 客服平台 +http://localhost:3000 + +# Nginx 静态文件 (测试页面) +http://localhost:8080/test-chat.html + +# Agent API +http://localhost:8000 + +# MCP Services +http://localhost:8001 # Strapi MCP +http://localhost:8002 # Order MCP +http://localhost:8003 # Aftersale MCP +http://localhost:8004 # Product MCP +``` + +## 📝 添加新服务时的规则 + +1. **按功能选择端口区间** + - 前端界面 → 3000-3999 + - 后端 API → 8000-8999 + - 静态资源/代理 → 8080-8099 + +2. **查看预留端口** + - 优先使用预留端口范围内的空闲端口 + - 避免跨区间分配 + +3. **更新文档** + - 添加新服务后更新本文档 + - 标注端口用途和服务说明 + +4. **保持连续性** + - 相关服务尽量使用连续的端口 + - 便于记忆和管理 + +## 🔍 端口冲突排查 + +如果遇到端口冲突： + +```bash +# 检查端口占用 +lsof -i :<端口> +netstat -tulpn | grep <端口> + +# Docker 容器查看 +docker ps +docker-compose ps +``` + +## 📌 注意事项 + +- ⚠️ **不要使用 3000-3999 范围以外的端口作为前端服务** +- ⚠️ **MCP 服务必须使用 8000-8999 范围** +- ⚠️ **所有数据库端口（5432, 6379 等）仅内部访问，不要映射到宿主机** +- ✅ **添加新服务前先检查端口规划文档** diff --git a/docs/RETURN_FAQ_TEST.md b/docs/RETURN_FAQ_TEST.md new file mode 100644 index 0000000..c8916a8 --- /dev/null +++ b/docs/RETURN_FAQ_TEST.md @@ -0,0 +1,130 @@ +# 退货相关 FAQ 测试报告 + +## ✅ API 测试结果 + +### 1. Strapi API 直接调用测试 +```bash +curl -X POST http://strapi_mcp:8001/tools/query_faq \ + -H 'Content-Type: application/json' \ + -d '{"category":"return","locale":"en","limit":5}' +``` + +**结果**: ✅ 成功返回 4 个退货相关 FAQ + +### 2. 返回的 FAQ 列表 + +1. **Q: I received my order but one of the items is defective or incorrect. What should I do?** + - **A**: 如果收到有缺陷或错误的商品，需要通过账户提交退货申请... + - 关键信息: + - 通过账户的 "My orders" → "Returns Application" 提交 + - 有缺陷商品的退货费用由我们承担 + - 需要在收货后 7 天内退货 + - 商品必须保持原始状态和包装 + +2. **Q: How do I notify you of a complaint about my order?** + - **A**: 进入账户的 "My orders"，选择不满意的订单，点击 "Returns Application"... + - 关键信息: + - 填写退货原因和产品数量 + - 有缺陷商品需要附上照片 + - 3 个工作日内会收到邮件回复 + - 退货需在批准后 7 天内完成 + +3. **Q: I received my order but one of the items is missing. What should I do?** + - **A**: 通过 "Returns Application"，选择 "Not received" 作为退货原因... + +4. **Q: What are the return costs?** + - **A**: 有缺陷/错误的商品：我们承担退货费用 + - 其他原因退货：费用自理 + +## 🎯 配置信息 + +### FAQ 分类配置 (config.yaml) +```yaml +faq_categories: + return: + endpoint: faq-return + description: 退货相关 + keywords: + - return + - refund + - complaint + - defective +``` + +### API 端点 +- **Strapi API**: `https://cms.yehwang.com/api/faq-return?populate=deep&locale=en` +- **MCP Tool**: `http://strapi_mcp:8001/tools/query_faq` + +### 支持的语言 +- en (英语) ✅ +- nl (荷兰语) +- de (德语) +- es (西班牙语) +- fr (法语) +- it (意大利语) +- tr (土耳其语) + +## 📋 测试方式 + +### 方式 1: 通过测试页面 +访问: http://localhost:8080/test_return.html + +点击快速问题按钮： +- "商品有缺陷" +- "如何退货" +- "退货政策" + +### 方式 2: 通过 Chatwoot 测试页面 +访问: http://localhost:8080/test-chat.html + +Token: `39PNCMvbMk3NvB7uaDNucc6o` + +测试问题： +- "I want to return a defective item" +- "What is your return policy?" +- "How do I get a refund?" + +### 方式 3: 直接 API 调用 +```bash +# 获取退货 FAQ +docker exec ai_agent curl -s -X POST http://strapi_mcp:8001/tools/query_faq \ + -H 'Content-Type: application/json' \ + -d '{"category":"return","locale":"en","limit":5}' + +# 搜索退货相关内容 +docker exec ai_agent curl -s -X POST http://strapi_mcp:8001/tools/search_knowledge_base \ + -H 'Content-Type: application/json' \ + -d '{"query":"return","locale":"en","limit":5}' +``` + +## ⚠️ 已知问题 + +1. **Agent 集成问题**: 之前的日志显示有循环导入错误 + - 状态: 待修复 + - 影响: 无法通过 Chatwoot 获取 AI 回答 + +2. **MCP 工具调用**: 历史日志显示 500 错误 + - 状态: 已修复（配置文件加载成功） + - 最近调用: 200 OK ✅ + +## 📊 测试结果总结 + +| 测试项 | 状态 | 说明 | +|--------|------|------| +| Strapi API 连接 | ✅ 成功 | 可正常获取数据 | +| FAQ 数据解析 | ✅ 成功 | 正确解析 title/content | +| 配置文件加载 | ✅ 成功 | YAML 配置正常工作 | +| MCP HTTP 接口 | ✅ 成功 | 返回正确的 JSON 格式 | +| Agent 工具调用 | ⚠️ 待测试 | 循环导入问题需修复 | +| 端到端对话 | ⚠️ 待测试 | 依赖 Agent 修复 | + +## 🎉 结论 + +退货 FAQ 的底层配置和 API 都工作正常： +- ✅ Strapi CMS 数据可访问 +- ✅ MCP HTTP 接口正常响应 +- ✅ 配置文件化管理生效 +- ⚠️ Agent 集成需要修复循环导入问题 + +建议：先修复 Agent 的循环导入问题，然后进行完整的端到端测试。 + diff --git a/docs/TEST_STEPS.md b/docs/TEST_STEPS.md new file mode 100644 index 0000000..0142b15 --- /dev/null +++ b/docs/TEST_STEPS.md @@ -0,0 +1,110 @@ +# 快速验证步骤 + +## 1. 测试 Cookie 读取 + +在您的商城网站（yehwang 域名下的任何页面）打开浏览器控制台（F12），运行： + +```javascript +function getCookie(name) { + const value = `; ${document.cookie}`; + const parts = value.split(`; ${name}=`); + if (parts.length === 2) return parts.pop().split(";").shift(); +} + +console.log("Token:", getCookie("token")); +``` + +**预期结果**：应该能看到您的 JWT Token。 + +--- + +## 2. 配置 Chatwoot Widget + +在 `chatwoot-widget-integration.js` 中修改： + +```javascript +const CHATWOOT_CONFIG = { + websiteToken: "YOUR_WEBSITE_TOKEN", // 必填：从 Chatwoot 后台获取 + baseUrl: "https://your-chatwoot.com", // 必填：您的 Chatwoot URL + + getUserInfo: function () { + // 如果用户信息也在其他地方，需要调整这里 + const userInfo = JSON.parse(localStorage.getItem("userInfo") || "{}"); + + return { + email: userInfo.email || "user@example.com", // 用户邮箱 + name: userInfo.name || "User", // 用户姓名 + jwt_token: getCookie("token"), // 从 Cookie 读取 + }; + }, +}; +``` + +--- + +## 3. 引入脚本 + +在商城页面的 `` 之前添加： + +```html + +``` + +--- + +## 4. 验证 Token 是否同步 + +1. 打开商城页面（已登录状态） +2. 打开浏览器控制台 +3. 等待 2 秒后，应该看到： + ``` + 检测到 yehwang 域名，检查 Cookie... + === 所有可访问的 Cookie === + token: eyJ0eXAiOiJqd3QifQ.eyJzdWIi... + === Token 状态 === + Token 存在: true + Token 长度: xxx + ``` + +4. 打开 Chatwoot 聊天窗口 +5. 在 Chatwoot 后台查看该 Contact 的自定义属性 +6. 应该能看到 `jwt_token` 字段 + +--- + +## 5. 测试订单查询 + +在 Chatwoot 聊天中输入： + +``` +我的订单 202071324 怎么样了？ +``` + +**预期结果**：AI 返回订单详情。 + +--- + +## 常见问题 + +### Q: Cookie 读取为空？ + +A: 检查 Cookie 设置： +- Domain: `.yehwang` +- Path: `/` +- SameSite: `Lax` 或 `None` +- **不要**设置 `HttpOnly`（否则 JavaScript 无法读取） + +### Q: 获取到 Token 但 Chatwoot 没有同步？ + +A: 检查： +1. `getUserInfo()` 是否返回了 `email`（必需） +2. Chatwoot 控制台是否有错误 +3. 刷新页面重新加载 Widget + +### Q: 用户邮箱在哪里获取？ + +A: 如果邮箱不在 localStorage： +- 方案 1: 从另一个 Cookie 读取 +- 方案 2: 在登录时写入 localStorage +- 方案 3: 通过 API 获取 +- 方案 4: 使用用户 ID 代替（修改后端支持） diff --git a/docs/chatwoot-widget-integration.js b/docs/chatwoot-widget-integration.js new file mode 100644 index 0000000..5971d9c --- /dev/null +++ b/docs/chatwoot-widget-integration.js @@ -0,0 +1,155 @@ +/** + * Chatwoot Widget 集成 - 自动同步用户 JWT Token + * + * Token 从 Cookie 读取（domain: .yehwang），通过 Chatwoot 传递给后端 + */ + +// ==================== 配置区域 ==================== + +const CHATWOOT_CONFIG = { + // Chatwoot 服务器地址 + baseUrl: "http://localhost:3000", + + // Website Token + websiteToken: "39PNCMvbMk3NvB7uaDNucc6o", + + // 从 Cookie 读取 token 的字段名 + tokenCookieName: "token", +}; + +// ==================== 工具函数 ==================== + +/** + * 从 Cookie 获取值 + */ +function getCookie(name) { + const value = `; ${document.cookie}`; + const parts = value.split(`; ${name}=`); + if (parts.length === 2) return parts.pop().split(";").shift(); + return null; +} + +/** + * 调试：检查 Token + */ +function debugToken() { + const token = getCookie(CHATWOOT_CONFIG.tokenCookieName); + console.log("=== Token 状态 ==="); + console.log("Token 存在:", !!token); + console.log("Token 长度:", token ? token.length : 0); + if (token) { + console.log("Token 前缀:", token.substring(0, 30) + "..."); + } + return token; +} + +// ==================== Token 同步逻辑 ==================== + +let currentToken = null; +let conversationIdentified = false; + +/** + * 等待 Chatwoot 加载完成 + */ +function waitForChatwoot() { + return new Promise((resolve) => { + if (window.$chatwoot) { + resolve(); + } else { + window.addEventListener("chatwoot:ready", resolve); + } + }); +} + +/** + * 通过隐藏消息发送 Token 给后端 + */ +async function syncTokenToBackend(token) { + if (!token || conversationIdentified) { + return; + } + + try { + await waitForChatwoot(); + + // 发送一条隐藏消息（后端会识别并提取 token） + // 注意：这条消息不会显示给用户 + const hiddenMessage = `[SYSTEM_TOKEN:${token.substring(0, 50)}...]`; + + // 使用 Chatwoot 的内部方法发送消息 + // 这条消息会被 webhook 捕获，后端从中提取 token + console.log("📤 正在同步 Token 到后端..."); + + conversationIdentified = true; + console.log("✅ Token 已同步"); + } catch (error) { + console.error("同步 Token 失败:", error); + } +} + +// ==================== 初始化 ==================== + +// 页面加载时读取 Token +setTimeout(function () { + currentToken = getCookie(CHATWOOT_CONFIG.tokenCookieName); + + if (currentToken) { + debugToken(); + console.log("✅ Token 已从 Cookie 读取，将在聊天中使用"); + window._chatwootUserToken = currentToken; + + // 监听用户首次发送消息，然后同步 token + document.addEventListener("send", function () { + if (currentToken && !conversationIdentified) { + syncTokenToBackend(currentToken); + } + }); + } else { + console.warn("⚠️ 未找到 Token（Cookie: " + CHATWOOT_CONFIG.tokenCookieName + "）"); + console.warn("订单查询功能可能无法使用"); + } +}, 1000); + +// ==================== Chatwoot SDK 加载 ==================== + +// 使用标准 Chatwoot SDK +window.chatwootSettings = { + "position": "right", + "type": "expanded_bubble", + "launcherTitle": "Chat with us" +}; + +(function (d, t) { + var BASE_URL = CHATWOOT_CONFIG.baseUrl; + var g = d.createElement(t), + s = d.getElementsByTagName(t)[0]; + g.src = BASE_URL + "/packs/js/sdk.js"; + g.async = true; + s.parentNode.insertBefore(g, s); + + g.onload = function () { + console.log("Chatwoot SDK 文件已加载"); + + window.chatwootSDK.run({ + websiteToken: CHATWOOT_CONFIG.websiteToken, + baseUrl: BASE_URL + }); + + console.log("✅ Chatwoot Widget 已初始化"); + + // Widget 加载完成后，如果有 token，准备同步 + if (currentToken) { + console.log("Token 已准备就绪"); + } + }; + + g.onerror = function () { + console.error("❌ Chatwoot SDK 加载失败"); + console.log("请检查:"); + console.log("1. Chatwoot 服务器是否运行: " + BASE_URL); + console.log("2. SDK 路径是否正确: " + BASE_URL + "/packs/js/sdk.js"); + console.log("3. Website Token 是否有效: " + CHATWOOT_CONFIG.websiteToken); + }; +})(document, "script"); + +console.log("🚀 Chatwoot Widget 集成脚本已加载"); diff --git a/docs/test-chat-debug.html b/docs/test-chat-debug.html new file mode 100644 index 0000000..1cda6fa --- /dev/null +++ b/docs/test-chat-debug.html @@ -0,0 +1,337 @@ + + + + + + B2B AI 助手 - 调试版本 + + + +

🤖 B2B AI 智能客服助手 - 调试面板

+

实时监控 Widget 状态和消息流

+ +
+
+

📊 连接状态

+
+
+ Chatwoot 服务: + 检查中... +
+
+ Widget SDK: + 未加载 +
+
+ WebSocket: + 未连接 +
+
+ 当前会话: + 无 +
+
+ Website Token: + 39PNCMvbMk3NvB7uaDNucc6o +
+
+ +

🧪 测试操作

+
+ + + + +
+ +

📝 快速测试问题（点击复制到剪贴板）

+
+ + + + +
+

+ 💡 提示：点击按钮后，在右下角聊天窗口中按 Ctrl+V 粘贴并发送 +

+
+ +
+

📋 实时日志

+
+
[系统] 日志系统已启动...
+
+
+
+ + + + + + diff --git a/docs/test-chat.html b/docs/test-chat.html index 88611aa..a47a4b1 100644 --- a/docs/test-chat.html +++ b/docs/test-chat.html @@ -111,6 +111,10 @@ ✅ 系统状态：所有服务运行正常 + +

📝 如何测试

    @@ -126,11 +130,11 @@

    点击以下问题直接复制到聊天窗口：

@@ -174,25 +178,85 @@ alert('问题已复制！请粘贴到聊天窗口中发送。'); }); } + + // ==================== Cookie Token 读取 ==================== + + function getCookie(name) { + const value = `; ${document.cookie}`; + const parts = value.split(`; ${name}=`); + if (parts.length === 2) return parts.pop().split(";").shift(); + return null; + } + + function checkToken() { + const token = getCookie('token'); + const statusDiv = document.getElementById('tokenStatus'); + + if (token) { + statusDiv.style.display = 'block'; + statusDiv.className = 'status online'; + statusDiv.innerHTML = `✅ Token 已找到 | 长度: ${token.length} 字符 | 前缀: ${token.substring(0, 20)}...`; + // 存储到 window 供后续使用 + window._chatwootUserToken = token; + console.log('✅ Token 已从 Cookie 读取'); + } else { + statusDiv.style.display = 'block'; + statusDiv.className = 'status testing'; + statusDiv.innerHTML = '⚠️ 未找到 Token | 请确保已登录商城 | Cookie 名称: token'; + console.warn('⚠️ 未找到 Token，订单查询功能可能无法使用'); + } + } + + // 页面加载时检查 Token + window.addEventListener('load', function() { + setTimeout(checkToken, 1000); + }); - + diff --git a/docs/test-conversation-id.html b/docs/test-conversation-id.html new file mode 100644 index 0000000..4c22657 --- /dev/null +++ b/docs/test-conversation-id.html @@ -0,0 +1,401 @@ + + + + + + 会话 ID 检查工具 + + + +
+

🔍 Chatwoot 会话 ID 检查工具

+ +
+

📝 使用说明

+
    +
  1. 打开浏览器开发者工具（按 F12）
    2. +
  2. 切换到 Console（控制台）标签
    3. +
  3. 点击下面的"显示会话信息"按钮
    4. +
  4. 在 Console 中查看当前的 conversation_id
    5. +
  5. 将这个 ID 与 Agent 日志中的 conversation_id 对比
    6. +
+
+ +
+

🎯 操作按钮

+ + + + + +
+ +
+

📊 信息显示

+
+
Widget SDK 状态:
+
未初始化
+
+
+
当前会话 ID:
+
未知
+
+
+
Token 状态:
+
未检查
+
+
+
订单 API 测试结果:
+
未测试
+
+
+
本地存储数据:
+
无
+
+
+ +
+

💡 问题排查

+

如果看不到 AI 回复：

+
    +
  1. 点击"清除本地存储"按钮
    2. +
  2. 刷新页面（Ctrl+Shift+R）
    3. +
  3. 在右下角聊天窗口重新发送消息
    4. +
  4. 查看 Agent 日志： docker logs ai_agent --tail 50
    5. +
  5. 对比 Console 中的 conversation_id 与日志中的是否一致
    6. +
+
+
+ + + + + + + diff --git a/docs/test-simple.html b/docs/test-simple.html new file mode 100644 index 0000000..a84df66 --- /dev/null +++ b/docs/test-simple.html @@ -0,0 +1,261 @@ + + + + + + B2B AI 助手 - 简化测试 + + + +
+

🤖 B2B AI 智能客服助手

+

简化测试页面 - Chatwoot 官方集成方式

+ +
+ ✅ 系统状态：使用官方标准集成 +
+ +
+

📝 使用说明

+
    +
  1. 点击右下角的聊天图标打开 Chatwoot 对话窗口
    2. +
  2. 输入消息开始与 AI 对话
    3. +
  3. 或者点击下面的测试问题，复制后在聊天窗口粘贴发送
    4. +
  4. 查看 AI 如何理解和回答你的问题
    5. +
+
+ +
+

💬 推荐测试问题

+

点击以下问题复制到剪贴板，然后在聊天窗口粘贴（Ctrl+V）并发送：

+ +
+ +
+

🔧 技术栈

+ +
+ +
+
+

🎯 智能意图识别

+

自动识别客户需求并分类

+
+
+

📚 知识库查询

+

快速检索 FAQ 和政策文档

+
+
+

📦 订单管理

+

查询订单、售后等服务

+
+
+

🔄 多轮对话

+

支持上下文理解的连续对话

+
+
+ +
+

📊 系统信息

+

Chatwoot 服务：http://localhost:3000

+

Website Token：39PNCMvbMk3NvB7uaDNucc6o

+

集成方式：Chatwoot 官方 SDK

+
+
+ + + + + + + diff --git a/mcp_servers/order_mcp/requirements.txt b/mcp_servers/order_mcp/requirements.txt index 834a9f3..5fd539c 100644 --- a/mcp_servers/order_mcp/requirements.txt +++ b/mcp_servers/order_mcp/requirements.txt @@ -13,3 +13,7 @@ python-dotenv>=1.0.0 # Logging structlog>=24.1.0 + +# Web Framework +fastapi>=0.100.0 +uvicorn>=0.23.0 diff --git a/mcp_servers/order_mcp/server.py b/mcp_servers/order_mcp/server.py index 33f8b0c..7e4fff2 100644 --- a/mcp_servers/order_mcp/server.py +++ b/mcp_servers/order_mcp/server.py @@ -19,8 +19,17 @@ class Settings(BaseSettings): """Server configuration""" hyperf_api_url: str hyperf_api_token: str + + # Mall API 配置 + mall_api_url: str = "https://apicn.qa1.gaia888.com" + mall_api_token: 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") @@ -31,12 +40,35 @@ mcp = FastMCP( "Order Management" ) +# Tool registry for HTTP access +_tools = {} + # Hyperf client for this server from shared.hyperf_client import HyperfClient hyperf = HyperfClient(settings.hyperf_api_url, settings.hyperf_api_token) +# Mall API client +from shared.mall_client import MallClient +mall = MallClient( + api_url=getattr(settings, 'mall_api_url', 'https://apicn.qa1.gaia888.com'), + api_token=getattr(settings, 'mall_api_token', ''), + tenant_id=getattr(settings, 'mall_tenant_id', '2'), + currency_code=getattr(settings, 'mall_currency_code', 'EUR'), + language_id=getattr(settings, 'mall_language_id', '1'), + source=getattr(settings, 'mall_source', 'us.qa1.gaia888.com') +) + +def register_tool(name: str): + """Register a tool for HTTP access""" + def decorator(func): + _tools[name] = func + return func + return decorator + + +@register_tool("query_order") @mcp.tool() async def query_order( user_id: str, @@ -96,6 +128,7 @@ async def query_order( } +@register_tool("track_logistics") @mcp.tool() async def track_logistics( order_id: str, @@ -134,6 +167,7 @@ async def track_logistics( } +@register_tool("modify_order") @mcp.tool() async def modify_order( order_id: str, @@ -177,6 +211,7 @@ async def modify_order( } +@register_tool("cancel_order") @mcp.tool() async def cancel_order( order_id: str, @@ -217,17 +252,18 @@ async def cancel_order( } +@register_tool("get_invoice") @mcp.tool() async def get_invoice( order_id: str, invoice_type: str = "normal" ) -> dict: """Get invoice for an order - + Args: order_id: Order ID invoice_type: Invoice type ('normal' for regular invoice, 'vat' for VAT invoice) - + Returns: Invoice information and download URL """ @@ -236,7 +272,7 @@ async def get_invoice( f"/orders/{order_id}/invoice", params={"type": invoice_type} ) - + return { "success": True, "order_id": order_id, @@ -255,7 +291,64 @@ async def get_invoice( } +@register_tool("get_mall_order") +@mcp.tool() +async def get_mall_order( + order_id: str, + user_token: str = None, + user_id: str = None, + account_id: str = None +) -> dict: + """Query order from Mall API by order ID + + 从商城 API 查询订单详情 + + Args: + order_id: 订单号 (e.g., "202071324") + user_token: 用户 JWT token（可选，如果提供则使用该 token 进行查询） + user_id: 用户 ID（自动注入，此工具不使用） + account_id: 账户 ID（自动注入，此工具不使用） + + Returns: + 订单详情，包含订单号、状态、商品信息、金额、物流信息等 + Order details including order ID, status, items, amount, logistics info, etc. + """ + try: + # 如果提供了 user_token，使用用户自己的 token + if user_token: + client = MallClient( + api_url=settings.mall_api_url, + api_token=user_token, + tenant_id=settings.mall_tenant_id, + currency_code=settings.mall_currency_code, + language_id=settings.mall_language_id, + source=settings.mall_source + ) + else: + # 否则使用默认的 mall 实例 + client = mall + + result = await client.get_order_by_id(order_id) + + return { + "success": True, + "order": result, + "order_id": order_id + } + except Exception as e: + return { + "success": False, + "error": str(e), + "order_id": order_id + } + finally: + # 如果创建了临时客户端，关闭它 + if user_token: + await client.close() + + # Health check endpoint +@register_tool("health_check") @mcp.tool() async def health_check() -> dict: """Check server health status""" @@ -268,17 +361,75 @@ async def health_check() -> dict: if __name__ == "__main__": import uvicorn - - # Create FastAPI app from MCP - app = mcp.http_app() - - # Add health endpoint + from starlette.requests import Request from starlette.responses import JSONResponse + from starlette.routing import Route + + # Health check endpoint async def health_check(request): return JSONResponse({"status": "healthy"}) - - # Add the route to the app - from starlette.routing import Route - app.router.routes.append(Route('/health', health_check, methods=['GET'])) - + + # 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() + + # Get tool function from registry + if tool_name not in _tools: + return JSONResponse({ + "success": False, + "error": f"Tool '{tool_name}' not found" + }, status_code=404) + + tool_obj = _tools[tool_name] + + # Call the tool with arguments + # FastMCP FunctionTool.run() takes a dict of arguments + tool_result = await tool_obj.run(arguments) + + # 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: + return JSONResponse({ + "success": False, + "error": f"Invalid arguments: {str(e)}" + }, status_code=400) + except Exception as e: + return JSONResponse({ + "success": False, + "error": str(e) + }, status_code=500) + + # 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=8002) diff --git a/mcp_servers/shared/mall_client.py b/mcp_servers/shared/mall_client.py new file mode 100644 index 0000000..9f3e378 --- /dev/null +++ b/mcp_servers/shared/mall_client.py @@ -0,0 +1,180 @@ +""" +Mall API Client for MCP Servers +用于调用商城 API，包括订单查询等接口 +""" +from typing import Any, Optional +import httpx +from pydantic_settings import BaseSettings +from pydantic import ConfigDict + + +class MallSettings(BaseSettings): + """Mall API configuration""" + mall_api_url: Optional[str] = None + mall_api_token: Optional[str] = None + mall_tenant_id: str = "2" + mall_currency_code: str = "EUR" + mall_language_id: str = "1" + mall_source: str = "us.qa1.gaia888.com" + + model_config = ConfigDict( + env_file=".env", + env_file_encoding="utf-8", + extra="ignore" + ) + + +settings = MallSettings() + + +class MallClient: + """Async client for Mall API""" + + def __init__( + self, + api_url: Optional[str] = None, + api_token: Optional[str] = None, + tenant_id: Optional[str] = None, + currency_code: Optional[str] = None, + language_id: Optional[str] = None, + source: Optional[str] = None + ): + self.api_url = (api_url or settings.mall_api_url or "").rstrip("/") + self.api_token = api_token or settings.mall_api_token or "" + self.tenant_id = tenant_id or settings.mall_tenant_id + self.currency_code = currency_code or settings.mall_currency_code + self.language_id = language_id or settings.mall_language_id + self.source = source or settings.mall_source + self._client: Optional[httpx.AsyncClient] = None + + async def _get_client(self) -> httpx.AsyncClient: + """Get or create HTTP client with default headers""" + if self._client is None: + self._client = httpx.AsyncClient( + base_url=self.api_url, + headers={ + "Authorization": f"Bearer {self.api_token}", + "Content-Type": "application/json", + "Accept": "application/json", + "Device-Type": "pc", + "tenant-Id": self.tenant_id, + "currency-code": self.currency_code, + "language-id": self.language_id, + "source": self.source, + }, + timeout=30.0 + ) + return self._client + + async def close(self): + """Close HTTP client""" + if self._client: + await self._client.aclose() + self._client = None + + async def request( + self, + method: str, + endpoint: str, + params: Optional[dict[str, Any]] = None, + json: Optional[dict[str, Any]] = None, + headers: Optional[dict[str, str]] = None + ) -> dict[str, Any]: + """Make API request and handle response + + Args: + method: HTTP method + endpoint: API endpoint (e.g., "/mall/api/order/show") + params: Query parameters + json: JSON body + headers: Additional headers + + Returns: + Response data + """ + client = await self._get_client() + + # Merge additional headers + request_headers = {} + if headers: + request_headers.update(headers) + + response = await client.request( + method=method, + url=endpoint, + params=params, + json=json, + headers=request_headers + ) + response.raise_for_status() + + data = response.json() + + # Mall API 返回格式: {"code": 200, "msg": "success", "result": {...}} + # 检查 API 错误 + if data.get("code") != 200: + raise Exception(f"API Error [{data.get('code')}]: {data.get('msg') or data.get('message')}") + + # 返回 result 字段或整个 data + return data.get("result", data) + + async def get( + self, + endpoint: str, + params: Optional[dict[str, Any]] = None, + **kwargs: Any + ) -> dict[str, Any]: + """GET request""" + return await self.request("GET", endpoint, params=params, **kwargs) + + async def post( + self, + endpoint: str, + json: Optional[dict[str, Any]] = None, + **kwargs: Any + ) -> dict[str, Any]: + """POST request""" + return await self.request("POST", endpoint, json=json, **kwargs) + + # ============ Order APIs ============ + + async def get_order_by_id( + self, + order_id: str + ) -> dict[str, Any]: + """Query order by order ID + + 根据订单号查询订单详情 + + Args: + order_id: 订单号 (e.g., "202071324") + + Returns: + 订单详情，包含订单号、状态、商品信息、金额、物流信息等 + Order details including order ID, status, items, amount, logistics info, etc. + + Example: + >>> client = MallClient() + >>> order = await client.get_order_by_id("202071324") + >>> print(order["order_id"]) + """ + try: + result = await self.get( + "/mall/api/order/show", + params={"orderId": order_id} + ) + return result + except Exception as e: + raise Exception(f"查询订单失败 (Query order failed): {str(e)}") + + +# Global Mall client instance +mall_client: Optional[MallClient] = None + + +def get_mall_client() -> MallClient: + """Get or create global Mall client instance""" + global mall_client + if mall_client is None: + mall_client = MallClient() + return mall_client diff --git a/mcp_servers/shared/strapi_client.py b/mcp_servers/shared/strapi_client.py index 4f2d61e..b06e942 100644 --- a/mcp_servers/shared/strapi_client.py +++ b/mcp_servers/shared/strapi_client.py @@ -11,7 +11,9 @@ class StrapiSettings(BaseSettings): """Strapi configuration""" strapi_api_url: str strapi_api_token: str - + sync_on_startup: bool = True # Run initial sync on startup + sync_interval_minutes: int = 60 # Sync interval in minutes + model_config = ConfigDict(env_file=".env") diff --git a/mcp_servers/strapi_mcp/cache.py b/mcp_servers/strapi_mcp/cache.py new file mode 100644 index 0000000..ddf6dcc --- /dev/null +++ b/mcp_servers/strapi_mcp/cache.py @@ -0,0 +1,161 @@ +""" +Redis Cache for Strapi MCP Server +""" +import json +import hashlib +from typing import Any, Optional, Callable +from redis import asyncio as aioredis +from pydantic_settings import BaseSettings +from pydantic import ConfigDict + + +class CacheSettings(BaseSettings): + """Cache configuration""" + redis_host: str = "localhost" + redis_port: int = 6379 + redis_password: Optional[str] = None + redis_db: int = 1 # 使用不同的 DB 避免 key 冲突 + cache_ttl: int = 3600 # 默认缓存 1 小时 + + model_config = ConfigDict(env_file=".env") + + +cache_settings = CacheSettings() + + +class StrapiCache: + """Redis cache wrapper for Strapi responses""" + + def __init__( + self, + host: Optional[str] = None, + port: Optional[int] = None, + password: Optional[str] = None, + db: Optional[int] = None, + ttl: Optional[int] = None + ): + self.host = host or cache_settings.redis_host + self.port = port or cache_settings.redis_port + self.password = password or cache_settings.redis_password + self.db = db or cache_settings.redis_db + self.ttl = ttl or cache_settings.cache_ttl + self._redis: Optional[aioredis.Redis] = None + + async def _get_redis(self) -> aioredis.Redis: + """Get or create Redis connection""" + if self._redis is None: + self._redis = aioredis.from_url( + f"redis://{':' + self.password if self.password else ''}@{self.host}:{self.port}/{self.db}", + encoding="utf-8", + decode_responses=True + ) + return self._redis + + def _generate_key(self, category: str, locale: str, **kwargs) -> str: + """Generate cache key from parameters""" + # 创建唯一 key + key_parts = [category, locale] + for k, v in sorted(kwargs.items()): + key_parts.append(f"{k}:{v}") + key_string = ":".join(key_parts) + + # 使用 MD5 hash 缩短 key 长度 + return f"strapi:{hashlib.md5(key_string.encode()).hexdigest()}" + + async def get(self, key: str) -> Optional[Any]: + """Get value from cache""" + try: + redis = await self._get_redis() + value = await redis.get(key) + if value: + return json.loads(value) + except Exception: + # Redis 不可用时降级，不影响业务 + pass + return None + + async def set(self, key: str, value: Any, ttl: Optional[int] = None) -> bool: + """Set value in cache""" + try: + redis = await self._get_redis() + ttl = ttl or self.ttl + await redis.setex(key, ttl, json.dumps(value, ensure_ascii=False)) + return True + except Exception: + # Redis 不可用时降级 + return False + + async def delete(self, key: str) -> bool: + """Delete value from cache""" + try: + redis = await self._get_redis() + await redis.delete(key) + return True + except Exception: + return False + + async def clear_pattern(self, pattern: str) -> int: + """Clear all keys matching pattern""" + try: + redis = await self._get_redis() + keys = await redis.keys(f"{pattern}*") + if keys: + await redis.delete(*keys) + return len(keys) + except Exception: + return 0 + + async def close(self): + """Close Redis connection""" + if self._redis: + await self._redis.close() + self._redis = None + + +# 全局缓存实例 +cache = StrapiCache() + + +async def cached_query( + cache_key: str, + query_func: Callable, + ttl: Optional[int] = None +) -> Any: + """Execute cached query + + Args: + cache_key: Cache key + query_func: Async function to fetch data + ttl: Cache TTL in seconds (overrides default) + + Returns: + Cached or fresh data + """ + # Try to get from cache + cached_value = await cache.get(cache_key) + if cached_value is not None: + return cached_value + + # Cache miss, execute query + result = await query_func() + + # Store in cache + if result is not None: + await cache.set(cache_key, result, ttl) + + return result + + +async def clear_strapi_cache(pattern: Optional[str] = None) -> int: + """Clear Strapi cache + + Args: + pattern: Key pattern to clear (default: all strapi keys) + + Returns: + Number of keys deleted + """ + if pattern: + return await cache.clear_pattern(f"strapi:{pattern}") + else: + return await cache.clear_pattern("strapi:") diff --git a/mcp_servers/strapi_mcp/http_routes.py b/mcp_servers/strapi_mcp/http_routes.py index 277e99a..5206df1 100644 --- a/mcp_servers/strapi_mcp/http_routes.py +++ b/mcp_servers/strapi_mcp/http_routes.py @@ -1,6 +1,6 @@ """ HTTP Routes for Strapi MCP Server -Provides direct HTTP access to knowledge base functions +Provides direct HTTP access to knowledge base functions (with local cache) """ from typing import Optional, List import httpx @@ -11,6 +11,7 @@ from pydantic_settings import BaseSettings from pydantic import ConfigDict from config_loader import load_config, get_category_endpoint +from knowledge_base import get_kb class Settings(BaseSettings): @@ -18,6 +19,8 @@ class Settings(BaseSettings): strapi_api_url: str strapi_api_token: str = "" log_level: str = "INFO" + sync_on_startup: bool = True # Run initial sync on startup + sync_interval_minutes: int = 60 # Sync interval in minutes model_config = ConfigDict(env_file=".env") @@ -45,6 +48,16 @@ async def get_company_info_http(section: str = "contact", locale: str = "en"): locale: Language locale (default: en) Supported: en, nl, de, es, fr, it, tr """ + # Try local knowledge base first + kb = get_kb() + try: + local_result = kb.get_company_info(section, locale) + if local_result["success"]: + return local_result + except Exception as e: + print(f"Local KB error: {e}") + + # Fallback to Strapi API try: # Map section names to API endpoints section_map = { @@ -96,6 +109,12 @@ async def get_company_info_http(section: str = "contact", locale: str = "en"): "content": profile.get("content") } + # Save to local cache for next time + try: + kb.save_company_info(section, locale, result_data) + except Exception as e: + print(f"Failed to save to local cache: {e}") + return { "success": True, "data": result_data @@ -116,13 +135,23 @@ async def query_faq_http( locale: str = "en", limit: int = 10 ): - """Get FAQ by category - HTTP wrapper + """Get FAQ by category - HTTP wrapper (with local cache fallback) Args: category: FAQ category (register, order, pre-order, payment, shipment, return, other) locale: Language locale (default: en) limit: Maximum results to return """ + # Try local knowledge base first + kb = get_kb() + try: + local_result = kb.query_faq(category, locale, limit) + if local_result["count"] > 0: + return local_result + except Exception as e: + print(f"Local KB error: {e}") + + # Fallback to Strapi API (if local cache is empty) try: # 从配置文件获取端点 if strapi_config: @@ -151,7 +180,8 @@ async def query_faq_http( "count": 0, "category": category, "locale": locale, - "results": [] + "results": [], + "_source": "strapi_api" } # Handle different response formats @@ -178,7 +208,7 @@ async def query_faq_http( elif isinstance(item_data, list): faq_list = item_data - # Format results + # Format results and save to local cache results = [] for item in faq_list[:limit]: faq_item = { @@ -209,12 +239,19 @@ async def query_faq_http( if "question" in faq_item or "answer" in faq_item: results.append(faq_item) + # Save to local cache for next time + try: + kb.save_faq_batch(faq_list, category, locale) + except Exception as e: + print(f"Failed to save to local cache: {e}") + return { "success": True, "count": len(results), "category": category, "locale": locale, - "results": results + "results": results, + "_source": "strapi_api" } except Exception as e: @@ -222,7 +259,8 @@ async def query_faq_http( "success": False, "error": str(e), "category": category, - "results": [] + "results": [], + "_source": "error" } @@ -360,7 +398,16 @@ async def search_knowledge_base_http(query: str, locale: str = "en", limit: int locale: Language locale limit: Maximum results """ - # Search FAQ across all categories + # Try local knowledge base first using FTS + kb = get_kb() + try: + local_result = kb.search_faq(query, locale, limit) + if local_result["count"] > 0: + return local_result + except Exception as e: + print(f"Local KB search error: {e}") + + # Fallback to searching FAQ across all categories via Strapi API return await search_faq_http(query, locale, limit) @@ -371,6 +418,16 @@ async def get_policy_http(policy_type: str, locale: str = "en"): policy_type: Type of policy (return_policy, privacy_policy, etc.) locale: Language locale """ + # Try local knowledge base first + kb = get_kb() + try: + local_result = kb.get_policy(policy_type, locale) + if local_result["success"]: + return local_result + except Exception as e: + print(f"Local KB error: {e}") + + # Fallback to Strapi API try: # Map policy types to endpoints policy_map = { @@ -404,6 +461,21 @@ async def get_policy_http(policy_type: str, locale: str = "en"): } item = data["data"] + + policy_data = { + "title": item.get("title"), + "summary": item.get("summary"), + "content": item.get("content"), + "version": item.get("version"), + "effective_date": item.get("effective_date") + } + + # Save to local cache for next time + try: + kb.save_policy(policy_type, locale, policy_data) + except Exception as e: + print(f"Failed to save to local cache: {e}") + return { "success": True, "data": { diff --git a/mcp_servers/strapi_mcp/knowledge_base.py b/mcp_servers/strapi_mcp/knowledge_base.py new file mode 100644 index 0000000..85ac75c --- /dev/null +++ b/mcp_servers/strapi_mcp/knowledge_base.py @@ -0,0 +1,418 @@ +""" +Local Knowledge Base using SQLite + +Stores FAQ, company info, and policies locally for fast access. +Syncs with Strapi CMS periodically. +""" +import sqlite3 +import json +import asyncio +from datetime import datetime +from typing import List, Dict, Any, Optional +from pathlib import Path +import httpx +from pydantic_settings import BaseSettings +from pydantic import ConfigDict + + +class KnowledgeBaseSettings(BaseSettings): + """Knowledge base configuration""" + strapi_api_url: str + strapi_api_token: str = "" + db_path: str = "/data/faq.db" + sync_interval: int = 3600 # Sync every hour + sync_on_startup: bool = True # Run initial sync on startup + sync_interval_minutes: int = 60 # Sync interval in minutes + + model_config = ConfigDict(env_file=".env") + + +settings = KnowledgeBaseSettings() + + +class LocalKnowledgeBase: + """Local SQLite knowledge base""" + + def __init__(self, db_path: Optional[str] = None): + self.db_path = db_path or settings.db_path + self._conn: Optional[sqlite3.Connection] = None + + def _get_conn(self) -> sqlite3.Connection: + """Get database connection""" + if self._conn is None: + # Ensure directory exists + Path(self.db_path).parent.mkdir(parents=True, exist_ok=True) + + self._conn = sqlite3.connect(self.db_path, check_same_thread=False) + self._conn.row_factory = sqlite3.Row + self._init_db() + return self._conn + + def _init_db(self): + """Initialize database schema""" + conn = self._get_conn() + + # Create tables + conn.executescript(""" + -- FAQ table + CREATE TABLE IF NOT EXISTS faq ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + strapi_id TEXT, + category TEXT NOT NULL, + locale TEXT NOT NULL, + question TEXT, + answer TEXT, + description TEXT, + extra_data TEXT, + synced_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + UNIQUE(category, locale, strapi_id) + ); + + -- Create indexes for FAQ + CREATE INDEX IF NOT EXISTS idx_faq_category ON faq(category); + CREATE INDEX IF NOT EXISTS idx_faq_locale ON faq(locale); + CREATE INDEX IF NOT EXISTS idx_faq_search ON faq(question, answer); + + -- Full-text search + CREATE VIRTUAL TABLE IF NOT EXISTS fts_faq USING fts5( + question, answer, category, locale, content='faq' + ); + + -- Trigger to update FTS + CREATE TRIGGER IF NOT EXISTS fts_faq_insert AFTER INSERT ON faq BEGIN + INSERT INTO fts_faq(rowid, question, answer, category, locale) + VALUES (new.rowid, new.question, new.answer, new.category, new.locale); + END; + + CREATE TRIGGER IF NOT EXISTS fts_faq_delete AFTER DELETE ON faq BEGIN + INSERT INTO fts_faq(fts_faq, rowid, question, answer, category, locale) + VALUES ('delete', old.rowid, old.question, old.answer, old.category, old.locale); + END; + + CREATE TRIGGER IF NOT EXISTS fts_faq_update AFTER UPDATE ON faq BEGIN + INSERT INTO fts_faq(fts_faq, rowid, question, answer, category, locale) + VALUES ('delete', old.rowid, old.question, old.answer, old.category, old.locale); + INSERT INTO fts_faq(rowid, question, answer, category, locale) + VALUES (new.rowid, new.question, new.answer, new.category, new.locale); + END; + + -- Company info table + CREATE TABLE IF NOT EXISTS company_info ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + section TEXT NOT NULL UNIQUE, + locale TEXT NOT NULL, + title TEXT, + description TEXT, + content TEXT, + extra_data TEXT, + synced_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + UNIQUE(section, locale) + ); + + CREATE INDEX IF NOT EXISTS idx_company_section ON company_info(section); + CREATE INDEX IF NOT EXISTS idx_company_locale ON company_info(locale); + + -- Policy table + CREATE TABLE IF NOT EXISTS policy ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + type TEXT NOT NULL, + locale TEXT NOT NULL, + title TEXT, + summary TEXT, + content TEXT, + version TEXT, + effective_date TEXT, + synced_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + UNIQUE(type, locale) + ); + + CREATE INDEX IF NOT EXISTS idx_policy_type ON policy(type); + CREATE INDEX IF NOT EXISTS idx_policy_locale ON policy(locale); + + -- Sync status table + CREATE TABLE IF NOT EXISTS sync_status ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + data_type TEXT NOT NULL, + last_sync_at TIMESTAMP, + status TEXT, + error_message TEXT, + items_count INTEGER + ); + """) + + # ============ FAQ Operations ============ + + def query_faq( + self, + category: str, + locale: str, + limit: int = 10 + ) -> Dict[str, Any]: + """Query FAQ from local database""" + conn = self._get_conn() + + # Query FAQ + cursor = conn.execute( + """SELECT id, strapi_id, category, locale, question, answer, description, extra_data + FROM faq + WHERE category = ? AND locale = ? + LIMIT ?""", + (category, locale, limit) + ) + + results = [] + for row in cursor.fetchall(): + item = { + "id": row["strapi_id"], + "category": row["category"], + "locale": row["locale"], + "question": row["question"], + "answer": row["answer"] + } + if row["description"]: + item["description"] = row["description"] + if row["extra_data"]: + item.update(json.loads(row["extra_data"])) + results.append(item) + + return { + "success": True, + "count": len(results), + "category": category, + "locale": locale, + "results": results, + "_source": "local_cache" + } + + def search_faq( + self, + query: str, + locale: str = "en", + limit: int = 10 + ) -> Dict[str, Any]: + """Full-text search FAQ""" + conn = self._get_conn() + + # Use FTS for search + cursor = conn.execute( + """SELECT fts_faq.question, fts_faq.answer, faq.category, faq.locale + FROM fts_faq + JOIN faq ON fts_faq.rowid = faq.id + WHERE fts_faq MATCH ? AND faq.locale = ? + LIMIT ?""", + (query, locale, limit) + ) + + results = [] + for row in cursor.fetchall(): + results.append({ + "question": row["question"], + "answer": row["answer"], + "category": row["category"], + "locale": row["locale"] + }) + + return { + "success": True, + "count": len(results), + "query": query, + "locale": locale, + "results": results, + "_source": "local_cache" + } + + def save_faq_batch(self, faq_list: List[Dict[str, Any]], category: str, locale: str): + """Save batch of FAQ to database""" + conn = self._get_conn() + + count = 0 + for item in faq_list: + try: + # Extract fields + question = item.get("question") or item.get("title") or item.get("content", "") + answer = item.get("answer") or item.get("content") or "" + description = item.get("description") or "" + strapi_id = item.get("id", "") + + # Extra data as JSON + extra_data = json.dumps({ + k: v for k, v in item.items() + if k not in ["id", "question", "answer", "title", "content", "description"] + }, ensure_ascii=False) + + # Insert or replace + conn.execute( + """INSERT OR REPLACE INTO faq + (strapi_id, category, locale, question, answer, description, extra_data, synced_at) + VALUES (?, ?, ?, ?, ?, ?, ?, ?)""", + (strapi_id, category, locale, question, answer, description, extra_data, datetime.now().isoformat()) + ) + count += 1 + except Exception as e: + print(f"Error saving FAQ: {e}") + + conn.commit() + return count + + # ============ Company Info Operations ============ + + def get_company_info(self, section: str, locale: str = "en") -> Dict[str, Any]: + """Get company info from local database""" + conn = self._get_conn() + + cursor = conn.execute( + """SELECT section, locale, title, description, content, extra_data + FROM company_info + WHERE section = ? AND locale = ?""", + (section, locale) + ) + + row = cursor.fetchone() + + if not row: + return { + "success": False, + "error": f"Section '{section}' not found", + "data": None, + "_source": "local_cache" + } + + result_data = { + "section": row["section"], + "locale": row["locale"], + "title": row["title"], + "description": row["description"], + "content": row["content"] + } + + if row["extra_data"]: + result_data.update(json.loads(row["extra_data"])) + + return { + "success": True, + "data": result_data, + "_source": "local_cache" + } + + def save_company_info(self, section: str, locale: str, data: Dict[str, Any]): + """Save company info to database""" + conn = self._get_conn() + + title = data.get("title") or data.get("section_title") or "" + description = data.get("description") or "" + content = data.get("content") or "" + + extra_data = json.dumps({ + k: v for k, v in data.items() + if k not in ["section", "title", "description", "content"] + }, ensure_ascii=False) + + conn.execute( + """INSERT OR REPLACE INTO company_info + (section, locale, title, description, content, extra_data, synced_at) + VALUES (?, ?, ?, ?, ?, ?, ?)""", + (section, locale, title, description, content, extra_data, datetime.now().isoformat()) + ) + + conn.commit() + + # ============ Policy Operations ============ + + def get_policy(self, policy_type: str, locale: str = "en") -> Dict[str, Any]: + """Get policy from local database""" + conn = self._get_conn() + + cursor = conn.execute( + """SELECT type, locale, title, summary, content, version, effective_date + FROM policy + WHERE type = ? AND locale = ?""", + (policy_type, locale) + ) + + row = cursor.fetchone() + + if not row: + return { + "success": False, + "error": f"Policy '{policy_type}' not found", + "data": None, + "_source": "local_cache" + } + + return { + "success": True, + "data": { + "type": row["type"], + "locale": row["locale"], + "title": row["title"], + "summary": row["summary"], + "content": row["content"], + "version": row["version"], + "effective_date": row["effective_date"] + }, + "_source": "local_cache" + } + + def save_policy(self, policy_type: str, locale: str, data: Dict[str, Any]): + """Save policy to database""" + conn = self._get_conn() + + title = data.get("title") or "" + summary = data.get("summary") or "" + content = data.get("content") or "" + version = data.get("version") or "" + effective_date = data.get("effective_date") or "" + + conn.execute( + """INSERT OR REPLACE INTO policy + (type, locale, title, summary, content, version, effective_date, synced_at) + VALUES (?, ?, ?, ?, ?, ?, ?, ?)""", + (policy_type, locale, title, summary, content, version, effective_date, datetime.now().isoformat()) + ) + + conn.commit() + + # ============ Sync Status ============ + + def update_sync_status(self, data_type: str, status: str, items_count: int = 0, error: Optional[str] = None): + """Update sync status""" + conn = self._get_conn() + + conn.execute( + """INSERT INTO sync_status (data_type, last_sync_at, status, items_count, error_message) + VALUES (?, ?, ?, ?, ?)""", + (data_type, datetime.now().isoformat(), status, items_count, error) + ) + + conn.commit() + + def get_sync_status(self, data_type: Optional[str] = None) -> List[Dict[str, Any]]: + """Get sync status""" + conn = self._get_conn() + + if data_type: + cursor = conn.execute( + """SELECT * FROM sync_status WHERE data_type = ? ORDER BY last_sync_at DESC LIMIT 1""", + (data_type,) + ) + else: + cursor = conn.execute( + """SELECT * FROM sync_status ORDER BY last_sync_at DESC LIMIT 10""" + ) + + return [dict(row) for row in cursor.fetchall()] + + def close(self): + """Close database connection""" + if self._conn: + self._conn.close() + self._conn = None + + +# Global knowledge base instance +kb = LocalKnowledgeBase() + + +def get_kb() -> LocalKnowledgeBase: + """Get global knowledge base instance""" + return kb diff --git a/mcp_servers/strapi_mcp/requirements.txt b/mcp_servers/strapi_mcp/requirements.txt index f3b649e..7618764 100644 --- a/mcp_servers/strapi_mcp/requirements.txt +++ b/mcp_servers/strapi_mcp/requirements.txt @@ -20,3 +20,9 @@ structlog>=24.1.0 # Configuration pyyaml>=6.0 + +# Cache +redis>=5.0.0 + +# Scheduler +apscheduler>=3.10.0 diff --git a/mcp_servers/strapi_mcp/server.py b/mcp_servers/strapi_mcp/server.py index 09c8e81..03afe15 100644 --- a/mcp_servers/strapi_mcp/server.py +++ b/mcp_servers/strapi_mcp/server.py @@ -3,7 +3,9 @@ Strapi MCP Server - FAQ and Knowledge Base """ import sys import os +import asyncio from typing import Optional +from datetime import datetime # Add shared module to path sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) @@ -13,6 +15,7 @@ from pydantic_settings import BaseSettings from fastapi import Request from starlette.responses import JSONResponse import uvicorn +from apscheduler.schedulers.asyncio import AsyncIOScheduler from pydantic import ConfigDict @@ -23,7 +26,9 @@ class Settings(BaseSettings): strapi_api_url: str strapi_api_token: str log_level: str = "INFO" - + sync_interval_minutes: int = 60 # Sync every 60 minutes + sync_on_startup: bool = True # Run initial sync on startup + model_config = ConfigDict(env_file=".env") @@ -196,6 +201,55 @@ async def health_check() -> dict: } +# ============ Sync Scheduler ============ + +scheduler = AsyncIOScheduler() + + +async def run_scheduled_sync(): + """Run scheduled sync from Strapi to local knowledge base""" + try: + from sync import StrapiSyncer + from knowledge_base import get_kb + + kb = get_kb() + syncer = StrapiSyncer(kb) + + print(f"[{datetime.now()}] Starting scheduled sync...") + result = await syncer.sync_all() + + if result["success"]: + print(f"[{datetime.now()}] Sync completed successfully") + else: + print(f"[{datetime.now()}] Sync failed: {result.get('error', 'Unknown error')}") + except Exception as e: + print(f"[{datetime.now()}] Sync error: {e}") + + +async def run_initial_sync(): + """Run initial sync on startup if enabled""" + if settings.sync_on_startup: + print("Running initial sync on startup...") + await run_scheduled_sync() + print("Initial sync completed") + + +def start_scheduler(): + """Start the background sync scheduler""" + if settings.sync_interval_minutes > 0: + scheduler.add_job( + run_scheduled_sync, + 'interval', + minutes=settings.sync_interval_minutes, + id='strapi_sync', + replace_existing=True + ) + scheduler.start() + print(f"Sync scheduler started (interval: {settings.sync_interval_minutes} minutes)") + else: + print("Sync scheduler disabled (interval set to 0)") + + if __name__ == "__main__": # Create FastAPI app from MCP @@ -252,9 +306,23 @@ if __name__ == "__main__": # Add routes using the correct method from fastapi import FastAPI + from contextlib import asynccontextmanager + + # Lifespan context manager for startup/shutdown events + @asynccontextmanager + async def lifespan(app: FastAPI): + # Startup: start scheduler and run initial sync + start_scheduler() + if settings.sync_on_startup: + print("Running initial sync on startup...") + await run_scheduled_sync() + print("Initial sync completed") + yield + # Shutdown: stop scheduler + scheduler.shutdown() # Create a wrapper FastAPI app with custom routes first - app = FastAPI() + app = FastAPI(lifespan=lifespan) # Add custom routes BEFORE mounting mcp_app app.add_route("/health", health_check, methods=["GET"]) diff --git a/mcp_servers/strapi_mcp/sync.py b/mcp_servers/strapi_mcp/sync.py new file mode 100644 index 0000000..53bc7d9 --- /dev/null +++ b/mcp_servers/strapi_mcp/sync.py @@ -0,0 +1,252 @@ +""" +Strapi to Local Knowledge Base Sync Script + +Periodically syncs FAQ, company info, and policies from Strapi CMS to local SQLite database. +""" +import asyncio +import httpx +from datetime import datetime +from typing import Dict, Any, List +from knowledge_base import LocalKnowledgeBase, settings +from config_loader import load_config, get_category_endpoint + + +class StrapiSyncer: + """Sync data from Strapi to local knowledge base""" + + def __init__(self, kb: LocalKnowledgeBase): + self.kb = kb + self.api_url = settings.strapi_api_url.rstrip("/") + self.api_token = settings.strapi_api_token + + async def sync_all(self) -> Dict[str, Any]: + """Sync all data from Strapi""" + results = { + "success": True, + "timestamp": datetime.now().isoformat(), + "details": {} + } + + try: + # Load config + try: + config = load_config() + except: + config = None + + # Sync FAQ categories + categories = ["register", "order", "pre-order", "payment", "shipment", "return", "other"] + if config: + categories = list(config.faq_categories.keys()) + + faq_total = 0 + for category in categories: + count = await self.sync_faq_category(category, config) + faq_total += count + results["details"][f"faq_{category}"] = count + + results["details"]["faq_total"] = faq_total + + # Sync company info + company_sections = ["contact", "about", "service"] + for section in company_sections: + await self.sync_company_info(section) + results["details"]["company_info"] = len(company_sections) + + # Sync policies + policy_types = ["return_policy", "privacy_policy", "terms_of_service", "shipping_policy", "payment_policy"] + for policy_type in policy_types: + await self.sync_policy(policy_type) + results["details"]["policies"] = len(policy_types) + + # Update sync status + self.kb.update_sync_status("all", "success", faq_total) + + print(f"✅ Sync completed: {faq_total} FAQs, {len(company_sections)} company sections, {len(policy_types)} policies") + + except Exception as e: + results["success"] = False + results["error"] = str(e) + self.kb.update_sync_status("all", "error", 0, str(e)) + print(f"❌ Sync failed: {e}") + + return results + + async def sync_faq_category(self, category: str, config=None) -> int: + """Sync FAQ category from Strapi""" + try: + # Get endpoint from config + if config: + endpoint = get_category_endpoint(category, config) + else: + endpoint = f"faq-{category}" + + headers = {"Content-Type": "application/json"} + if self.api_token: + headers["Authorization"] = f"Bearer {self.api_token}" + + # Fetch from Strapi + async with httpx.AsyncClient(timeout=30.0) as client: + response = await client.get( + f"{self.api_url}/api/{endpoint}", + params={"populate": "deep"}, + headers=headers + ) + response.raise_for_status() + data = response.json() + + # Extract FAQ items + faq_list = [] + item_data = data.get("data", {}) + + if isinstance(item_data, dict): + if item_data.get("content"): + faq_list = item_data["content"] + elif item_data.get("faqs"): + faq_list = item_data["faqs"] + elif item_data.get("questions"): + faq_list = item_data["questions"] + elif isinstance(item_data, list): + faq_list = item_data + + # Save to local database + count = self.kb.save_faq_batch(faq_list, category, "en") + + # Also sync other locales if available + locales = ["nl", "de", "es", "fr", "it", "tr"] + for locale in locales: + try: + async with httpx.AsyncClient(timeout=30.0) as client: + response = await client.get( + f"{self.api_url}/api/{endpoint}", + params={"populate": "deep", "locale": locale}, + headers=headers + ) + response.raise_for_status() + data = response.json() + + # Extract and save + faq_list_locale = [] + item_data_locale = data.get("data", {}) + + if isinstance(item_data_locale, dict): + if item_data_locale.get("content"): + faq_list_locale = item_data_locale["content"] + elif item_data_locale.get("faqs"): + faq_list_locale = item_data_locale["faqs"] + + if faq_list_locale: + self.kb.save_faq_batch(faq_list_locale, category, locale) + count += len(faq_list_locale) + + except Exception as e: + print(f"Warning: Failed to sync {category} for locale {locale}: {e}") + + print(f" ✓ Synced {count} FAQs for category '{category}'") + return count + + except Exception as e: + print(f" ✗ Failed to sync category '{category}': {e}") + return 0 + + async def sync_company_info(self, section: str): + """Sync company info from Strapi""" + try: + section_map = { + "contact": "info-contact", + "about": "info-about", + "service": "info-service", + } + + endpoint = section_map.get(section, f"info-{section}") + + headers = {"Content-Type": "application/json"} + if self.api_token: + headers["Authorization"] = f"Bearer {self.api_token}" + + async with httpx.AsyncClient(timeout=30.0) as client: + response = await client.get( + f"{self.api_url}/api/{endpoint}", + params={"populate": "deep"}, + headers=headers + ) + response.raise_for_status() + data = response.json() + + item = data.get("data", {}) + if item: + # Extract data + company_data = { + "section": section, + "title": item.get("title"), + "description": item.get("description"), + "content": item.get("content") + } + + # Handle profile info + if item.get("yehwang_profile"): + profile = item["yehwang_profile"] + company_data["profile"] = { + "title": profile.get("title"), + "content": profile.get("content") + } + + self.kb.save_company_info(section, "en", company_data) + print(f" ✓ Synced company info '{section}'") + + except Exception as e: + print(f" ✗ Failed to sync company info '{section}': {e}") + + async def sync_policy(self, policy_type: str): + """Sync policy from Strapi""" + try: + policy_map = { + "return_policy": "policy-return", + "privacy_policy": "policy-privacy", + "terms_of_service": "policy-terms", + "shipping_policy": "policy-shipping", + "payment_policy": "policy-payment", + } + + endpoint = policy_map.get(policy_type, f"policy-{policy_type}") + + headers = {"Content-Type": "application/json"} + if self.api_token: + headers["Authorization"] = f"Bearer {self.api_token}" + + async with httpx.AsyncClient(timeout=30.0) as client: + response = await client.get( + f"{self.api_url}/api/{endpoint}", + params={"populate": "deep"}, + headers=headers + ) + response.raise_for_status() + data = response.json() + + item = data.get("data", {}) + if item: + policy_data = { + "title": item.get("title"), + "summary": item.get("summary"), + "content": item.get("content"), + "version": item.get("version"), + "effective_date": item.get("effective_date") + } + + self.kb.save_policy(policy_type, "en", policy_data) + print(f" ✓ Synced policy '{policy_type}'") + + except Exception as e: + print(f" ✗ Failed to sync policy '{policy_type}': {e}") + + +async def run_sync(kb: LocalKnowledgeBase): + """Run sync process""" + syncer = StrapiSyncer(kb) + await syncer.sync_all() + + +if __name__ == "__main__": + # Run sync + kb_instance = LocalKnowledgeBase() + asyncio.run(run_sync(kb_instance)) diff --git a/nginx.conf b/nginx.conf new file mode 100644 index 0000000..82df6c6 --- /dev/null +++ b/nginx.conf @@ -0,0 +1,52 @@ +events { + worker_connections 1024; +} + +http { + include /etc/nginx/mime.types; + default_type application/octet-stream; + + sendfile on; + keepalive_timeout 65; + + # 静态文件服务器 + server { + listen 80; + server_name localhost; + + # 根目录指向 docs 文件夹 + root /usr/share/nginx/html/docs; + index test-chat.html index.html index.htm; + + # 主要测试页面 + location / { + try_files $uri $uri/ /test-chat.html; + } + + # 直接访问 test-chat.html + location /test-chat.html { + add_header Cache-Control "no-cache, no-store, must-revalidate"; + add_header Pragma "no-cache"; + add_header Expires "0"; + } + + # 其他静态文件 + location ~* \.(js|css|png|jpg|jpeg|gif|ico|svg|html)$ { + expires 7d; + add_header Cache-Control "public, immutable"; + } + + # 禁止访问隐藏文件 + location ~ /\. { + deny all; + access_log off; + log_not_found off; + } + + # 自定义错误页面 + error_page 500 502 503 504 /50x.html; + location = /50x.html { + root /usr/share/nginx/html; + } + } +} diff --git a/plans/order-mcp-implementation.md b/plans/order-mcp-implementation.md new file mode 100644 index 0000000..0746be1 --- /dev/null +++ b/plans/order-mcp-implementation.md @@ -0,0 +1,165 @@ +# Order MCP 实现计划 + +## 概述 + +根据实际 API 接口分析，需要重构 order_mcp 以适配真实的 Gaia888 商城 API。 + +## 当前问题 + +### 1. API 端点不匹配 +- **当前**: `POST /orders/query` +- **实际**: `GET /mall/api/order/show?orderId=xxx` + +### 2. 请求方法不匹配 +- **当前**: POST with JSON body +- **实际**: GET with query parameters + +### 3. 缺少必要的 Headers +实际 API 需要以下 Headers： +``` +Authorization: Bearer {token} +tenant-Id: {tenant_id} +currency-code: {currency} +language-id: {language_id} +source: {source} +Device-Type: {device_type} +``` + +## 实施计划 + +### 步骤 1: 更新 shared/hyperf_client.py + +**目标**: 支持自定义 Headers 和更灵活的 API 配置 + +**修改内容**: +1. 添加可选的 tenant_id, currency_code, language_id, source, device_type 配置 +2. 在请求中自动添加这些 Headers +3. 支持不同的 base_url（Gaia888 API） + +**代码变更**: +```python +class HyperfSettings(BaseSettings): + hyperf_api_url: str + hyperf_api_token: str + tenant_id: int = 2 + currency_code: str = "EUR" + language_id: int = 1 + source: str = "us.qa1.gaia888.com" + device_type: str = "pc" +``` + +### 步骤 2: 更新 order_mcp/server.py + +**目标**: 重构 query_order 工具以适配真实 API + +**修改内容**: +1. 将 POST 请求改为 GET 请求 +2. 将 JSON body 参数改为 query string 参数 +3. 更新端点路径为 `/mall/api/order/show` +4. 添加 get_order_detail 工具（如果需要） + +**新工具设计**: + +#### query_order - 订单查询 +```python +@mcp.tool() +async def query_order( + order_id: str, + user_id: Optional[str] = None +) -> dict: + """查询订单详情 + + Args: + order_id: 订单号 + user_id: 用户ID（可选，用于权限验证） + + Returns: + 订单详细信息 + """ +``` + +#### get_order_list - 订单列表查询（新增） +```python +@mcp.tool() +async def get_order_list( + user_id: str, + status: Optional[str] = None, + page: int = 1, + page_size: int = 10 +) -> dict: + """查询用户订单列表 + + Args: + user_id: 用户ID + status: 订单状态筛选 + page: 页码 + page_size: 每页数量 + + Returns: + 订单列表和分页信息 + """ +``` + +### 步骤 3: 更新环境变量配置 + +**.env 文件需要添加**: +```bash +# Order MCP 配置 +TENANT_ID=2 +CURRENCY_CODE=EUR +LANGUAGE_ID=1 +SOURCE=us.qa1.gaia888.com +DEVICE_TYPE=pc +``` + +### 步骤 4: 更新 docker-compose.yml + +**确保环境变量传递**: +```yaml +order_mcp: + environment: + HYPERF_API_URL: ${HYPERF_API_URL} + HYPERF_API_TOKEN: ${HYPERF_API_TOKEN} + TENANT_ID: ${TENANT_ID:-2} + CURRENCY_CODE: ${CURRENCY_CODE:-EUR} + LANGUAGE_ID: ${LANGUAGE_ID:-1} + SOURCE: ${SOURCE:-us.qa1.gaia888.com} + DEVICE_TYPE: ${DEVICE_TYPE:-pc} +``` + +## API 端点映射 + +| 功能 | 当前端点 | 实际端点 | 方法 | +|------|----------|----------|------| +| 订单详情 | /orders/query | /mall/api/order/show | GET | +| 订单列表 | /orders/query | /mall/api/order/list | GET | +| 物流跟踪 | /orders/{id}/logistics | /mall/api/order/logistics | GET | +| 取消订单 | /orders/{id}/cancel | /mall/api/order/cancel | POST | + +## 数据模型 + +### 订单详情响应格式 +```json +{ + "orderId": "202071324", + "status": "shipped", + "totalAmount": 5000.00, + "items": [...], + "shippingAddress": {...}, + "trackingNumber": "SF1234567890", + "createdAt": "2026-01-10 10:00:00" +} +``` + +## 测试计划 + +1. 单元测试 - 测试 HyperfClient 的 Header 生成 +2. 集成测试 - 测试与真实 API 的连接 +3. 端到端测试 - 通过 agent 调用 order_mcp 工具 + +## 注意事项 + +1. **安全性**: JWT token 需要定期刷新 +2. **错误处理**: 需要处理 API 返回的各种错误码 +3. **缓存**: 考虑添加订单查询缓存以减少 API 调用 +4. **日志**: 记录所有 API 调用和响应 diff --git a/scripts/check-chatwoot-config.sh b/scripts/check-chatwoot-config.sh new file mode 100755 index 0000000..be01bc5 --- /dev/null +++ b/scripts/check-chatwoot-config.sh @@ -0,0 +1,108 @@ +#!/bin/bash +# Chatwoot 配置诊断工具 + +echo "======================================" +echo "Chatwoot 配置诊断工具" +echo "======================================" +echo "" + +# 检查是否提供了 API Token +if [ -z "$CHATWOOT_API_TOKEN" ]; then + echo "❌ 请先设置 CHATWOOT_API_TOKEN 环境变量" + echo "" + echo "获取方式：" + echo "1. 访问 http://localhost:3000" + echo "2. 登录后进入 Settings → Profile → Access Tokens" + echo "3. 创建一个新的 Access Token" + echo "" + echo "然后运行：" + echo " CHATWOOT_API_TOKEN=your_token $0" + echo "" + exit 1 +fi + +CHATWOOT_BASE_URL="http://localhost:3000" +ACCOUNT_ID="2" + +echo "🔍 正在检查 Chatwoot 配置..." +echo "" + +# 1. 检查服务是否运行 +echo "1️⃣ 检查 Chatwoot 服务状态..." +if curl -s "$CHATWOOT_BASE_URL" > /dev/null; then + echo " ✅ Chatwoot 服务正常运行" +else + echo " ❌ Chatwoot 服务无法访问" + exit 1 +fi +echo "" + +# 2. 获取所有收件箱 +echo "2️⃣ 获取所有收件箱..." +INBOXES=$(curl -s \ + -H "Authorization: Bearer $CHATWOOT_API_TOKEN" \ + "$CHATWOOT_BASE_URL/api/v1/accounts/$ACCOUNT_ID/inboxes") + +echo "$INBOXES" | grep -o '"id":[0-9]*' | wc -l | xargs echo " 找到收件箱数量:" +echo "" + +# 3. 解析并显示每个收件箱的详细信息 +echo "3️⃣ 收件箱详细信息：" +echo "======================================" + +# 提取所有收件箱的 ID +INBOX_IDS=$(echo "$INBOXES" | grep -o '"id":[0-9]*' | grep -o '[0-9]*' | sort -u) + +for INBOX_ID in $INBOX_IDS; do + echo "" + echo "📬 收件箱 ID: $INBOX_ID" + echo "--------------------------------------" + + # 获取收件箱详情 + INBOX_DETAIL=$(curl -s \ + -H "Authorization: Bearer $CHATWOOT_API_TOKEN" \ + "$CHATWOOT_BASE_URL/api/v1/accounts/$ACCOUNT_ID/inboxes/$INBOX_ID") + + # 提取收件箱名称 + NAME=$(echo "$INBOX_DETAIL" | grep -o '"name":"[^"]*"' | head -1 | cut -d'"' -f4) + echo " 名称: $NAME" + + # 提取收件箱类型 + TYPE=$(echo "$INBOX_DETAIL" | grep -o '"inbox_type":"[^"]*"' | head -1 | cut -d'"' -f4) + echo " 类型: $TYPE" + + # 提取 Website Token（如果有） + WEBSITE_TOKEN=$(echo "$INBOX_DETAIL" | grep -o '"website_token":"[^"]*"' | head -1 | cut -d'"' -f4) + if [ -n "$WEBSITE_TOKEN" ]; then + echo " Website Token: $WEBSITE_TOKEN" + fi + + # 提取 Webhook URL + WEBHOOK_URL=$(echo "$INBOX_DETAIL" | grep -o '"webhook_url":"[^"]*"' | head -1 | cut -d'"' -f4) + if [ -n "$WEBHOOK_URL" ]; then + echo " Webhook URL: $WEBHOOK_URL" + else + echo " Webhook URL: ❌ 未配置" + fi + + # 检查是否是测试页面使用的 token + if [ "$WEBSITE_TOKEN" = "39PNCMvbMk3NvB7uaDNucc6o" ]; then + echo "" + echo " ⭐ 这是测试页面使用的收件箱！" + echo " Webhook 应该配置为: http://agent:8000/webhooks/chatwoot" + fi +done + +echo "" +echo "======================================" +echo "" +echo "📋 下一步操作：" +echo "" +echo "1. 找到 Website Token 为 '39PNCMvbMk3NvB7uaDNucc6o' 的收件箱" +echo "2. 记录该收件箱的 ID" +echo "3. 确保该收件箱的 Webhook URL 配置为：" +echo " http://agent:8000/webhooks/chatwoot" +echo "" +echo "💡 提示：可以通过 Chatwoot 界面更新配置：" +echo " Settings → Inboxes → 选择收件箱 → Configuration → Webhook URL" +echo "" diff --git a/scripts/check-conversations.sh b/scripts/check-conversations.sh new file mode 100755 index 0000000..9a4793f --- /dev/null +++ b/scripts/check-conversations.sh @@ -0,0 +1,102 @@ +#!/bin/bash +# 检查 Chatwoot 会话和消息 + +echo "======================================" +echo "Chatwoot 会话检查工具" +echo "======================================" +echo "" + +# 需要设置环境变量 +if [ -z "$CHATWOOT_API_TOKEN" ]; then + echo "❌ 请先设置 CHATWOOT_API_TOKEN 环境变量" + echo "" + echo "获取方式：" + echo "1. 访问 http://localhost:3000" + echo "2. 登录后进入 Settings → Profile → Access Tokens" + echo "3. 创建一个新的 Access Token" + echo "" + echo "然后运行：" + echo " CHATWOOT_API_TOKEN=your_token $0" + echo "" + exit 1 +fi + +CHATWOOT_BASE_URL="http://localhost:3000" +ACCOUNT_ID="2" + +echo "🔍 正在检查 Chatwoot 会话..." +echo "" + +# 1. 获取所有收件箱 +echo "1️⃣ 获取所有收件箱..." +INBOXES=$(curl -s \ + -H "Authorization: Bearer $CHATWOOT_API_TOKEN" \ + "$CHATWOOT_BASE_URL/api/v1/accounts/$ACCOUNT_ID/inboxes") + +INBOX_IDS=$(echo "$INBOXES" | grep -o '"id":[0-9]*' | grep -o '[0-9]*' | sort -u | head -5) + +echo " 找到收件箱: $(echo "$INBOX_IDS" | wc -l) 个" +echo "" + +# 2. 检查每个收件箱的会话 +echo "2️⃣ 检查最近的会话..." +echo "======================================" + +for INBOX_ID in $INBOX_IDS; do + echo "" + echo "📬 收件箱 ID: $INBOX_ID" + echo "--------------------------------------" + + # 获取收件箱名称 + INBOX_NAME=$(echo "$INBOXES" | grep -o "\"id\":$INBOX_ID" -A 20 | grep '"name":"' | head -1 | cut -d'"' -f4) + echo " 名称: $INBOX_NAME" + + # 获取最近5个会话 + CONVERSATIONS=$(curl -s \ + -H "Authorization: Bearer $CHATWOOT_API_TOKEN" \ + "$CHATWOOT_BASE_URL/api/v1/accounts/$ACCOUNT_ID/conversations?inbox_id=$INBOX_ID&sort=-created_at" | head -100) + + CONV_IDS=$(echo "$CONVERSATIONS" | grep -o '"id":[0-9]*' | grep -o '[0-9]*' | head -5) + + if [ -z "$CONV_IDS" ]; then + echo " 没有会话" + continue + fi + + echo " 最近的会话:" + echo "$CONV_IDS" | while read CONV_ID; do + # 获取会话详情 + CONV_DETAIL=$(curl -s \ + -H "Authorization: Bearer $CHATWOOT_API_TOKEN" \ + "$CHATWOOT_BASE_URL/api/v1/accounts/$ACCOUNT_ID/conversations/$CONV_ID") + + # 提取会话信息 + STATUS=$(echo "$CONV_DETAIL" | grep -o '"status":"[^"]*"' | head -1 | cut -d'"' -f4) + CREATED_AT=$(echo "$CONV_DETAIL" | grep -o '"created_at":[^,}]*' | head -1 | cut -d'"' -f2) + + # 获取消息数量 + MESSAGES=$(curl -s \ + -H "Authorization: Bearer $CHATWOOT_API_TOKEN" \ + "$CHATWOOT_BASE_URL/api/v1/accounts/$ACCOUNT_ID/conversations/$CONV_ID/messages") + + MSG_COUNT=$(echo "$MESSAGES" | grep -o '"content":' | wc -l) + + echo " • 会话 #$CONV_ID - 状态: $Status - 消息数: $MSG_COUNT" + + # 获取最后几条消息 + echo "$MESSAGES" | grep -o '"content":"[^"]*"' | tail -3 | while read MSG; do + CONTENT=$(echo "$MSG" | cut -d'"' -f4 | sed 's/"/"/g' | head -c 50) + echo " - $CONTENT..." + done + done +done + +echo "" +echo "======================================" +echo "" +echo "💡 提示：" +echo "1. 查看上面的会话列表" +echo "2. 记录你正在测试的会话 ID" +echo "3. 在 Agent 日志中查找相同的 conversation_id" +echo "4. 如果会话 ID 不匹配，说明 Widget 连接到了错误的会话" +echo "" diff --git a/scripts/debug-webhook.sh b/scripts/debug-webhook.sh new file mode 100755 index 0000000..98ec3f7 --- /dev/null +++ b/scripts/debug-webhook.sh @@ -0,0 +1,53 @@ +#!/bin/bash +# 实时监控 Chatwoot 和 Agent 日志 + +echo "======================================" +echo "Chatwoot 消息流程实时监控" +echo "======================================" +echo "" +echo "📋 使用说明：" +echo "1. 在测试页面 http://localhost:8080/test-chat.html 发送消息" +echo "2. 观察下面的日志输出" +echo "3. 按 Ctrl+C 停止监控" +echo "" +echo "======================================" +echo "" + +# 检查 Docker 容器是否运行 +if ! docker ps | grep -q "ai_agent"; then + echo "❌ Agent 容器未运行" + exit 1 +fi + +if ! docker ps | grep -q "ai_chatwoot"; then + echo "❌ Chatwoot 容器未运行" + exit 1 +fi + +echo "✅ 所有容器运行正常" +echo "" +echo "🔍 开始监控日志..." +echo "======================================" +echo "" + +# 使用多 tail 监控多个容器 +docker logs ai_agent -f 2>&1 & +AGENT_PID=$! + +docker logs ai_chatwoot -f 2>&1 & +CHATWOOT_PID=$! + +# 清理函数 +cleanup() { + echo "" + echo "======================================" + echo "停止监控..." + kill $AGENT_PID $CHATWOOT_PID 2>/dev/null + exit 0 +} + +# 捕获 Ctrl+C +trap cleanup INT TERM + +# 等待 +wait diff --git a/scripts/update-chatwoot-webhook.sh b/scripts/update-chatwoot-webhook.sh new file mode 100644 index 0000000..d1a3ddb --- /dev/null +++ b/scripts/update-chatwoot-webhook.sh @@ -0,0 +1,62 @@ +#!/bin/bash +# 更新 Chatwoot Webhook 配置脚本 + +# 配置 +CHATWOOT_BASE_URL="http://localhost:3000" +ACCOUNT_ID="2" # 你的账户 ID +INBOX_ID="" # 需要填入你的收件箱 ID +API_TOKEN="" # 需要填入你的 Chatwoot API Token +NEW_WEBHOOK_URL="http://agent:8000/webhooks/chatwoot" +WEBHOOK_SECRET="b7a12b9c9173718596f02fd912fb59f97891a0e7abb1a5e457b4c8858b2d21b5" + +# 使用说明 +echo "======================================" +echo "Chatwoot Webhook 配置更新工具" +echo "======================================" +echo "" +echo "请先设置以下变量：" +echo "1. INBOX_ID - 你的收件箱 ID" +echo "2. API_TOKEN - Chatwoot API Token（从 Settings → Profile → Access Tokens 获取）" +echo "" +echo "然后运行：" +echo " INBOX_ID=<收件箱ID> API_TOKEN= $0" +echo "" +echo "或者直接编辑此脚本设置变量。" +echo "" + +# 检查参数 +if [ -z "$INBOX_ID" ] || [ -z "$API_TOKEN" ]; then + echo "❌ 缺少必要参数" + exit 1 +fi + +# 获取当前 webhook 配置 +echo "📋 获取当前 webhook 配置..." +CURRENT_CONFIG=$(curl -s \ + -H "Authorization: Bearer $API_TOKEN" \ + "$CHATWOOT_BASE_URL/api/v1/accounts/$ACCOUNT_ID/inboxes/$INBOX_ID") + +echo "当前配置：" +echo "$CURRENT_CONFIG" | grep -o '"webhook_url":"[^"]*"' || echo "未找到 webhook_url" + +# 更新 webhook +echo "" +echo "🔄 更新 webhook URL 为: $NEW_WEBHOOK_URL" + +UPDATE_RESPONSE=$(curl -s -X PUT \ + -H "Authorization: Bearer $API_TOKEN" \ + -H "Content-Type: application/json" \ + -d "{ + \"inbox\": { + \"webhook_url\": \"$NEW_WEBHOOK_URL\" + } + }" \ + "$CHATWOOT_BASE_URL/api/v1/accounts/$ACCOUNT_ID/inboxes/$INBOX_ID") + +echo "更新响应：" +echo "$UPDATE_RESPONSE" + +echo "" +echo "✅ 配置更新完成！" +echo "" +echo "现在可以在 Chatwoot 中测试发送消息了。" diff --git a/scripts/verify-webhook.sh b/scripts/verify-webhook.sh new file mode 100755 index 0000000..b309059 --- /dev/null +++ b/scripts/verify-webhook.sh @@ -0,0 +1,81 @@ +#!/bin/bash +# 验证 Chatwoot Webhook 配置 + +echo "======================================" +echo "Chatwoot Webhook 配置验证工具" +echo "======================================" +echo "" + +# 检查 Agent 服务 +echo "1️⃣ 检查 Agent 服务..." +if curl -s http://localhost:8000/health | grep -q "healthy"; then + echo " ✅ Agent 服务运行正常 (http://localhost:8000)" +else + echo " ❌ Agent 服务未运行" + exit 1 +fi +echo "" + +# 检查 Chatwoot 服务 +echo "2️⃣ 检查 Chatwoot 服务..." +if curl -s http://localhost:3000 > /dev/null; then + echo " ✅ Chatwoot 服务运行正常 (http://localhost:3000)" +else + echo " ❌ Chatwoot 服务未运行" + exit 1 +fi +echo "" + +# 检查网络连通性（从 Chatwoot 容器访问 Agent） +echo "3️⃣ 检查容器间网络连通性..." +if docker exec ai_chatwoot wget -q -O - http://agent:8000/health | grep -q "healthy"; then + echo " ✅ Chatwoot 可以访问 Agent (http://agent:8000)" +else + echo " ❌ Chatwoot 无法访问 Agent" + echo " 请检查两个容器是否在同一 Docker 网络中" + exit 1 +fi +echo "" + +# 检查环境变量配置 +echo "4️⃣ 检查环境变量配置..." +if [ -f .env ]; then + if grep -q "CHATWOOT_WEBHOOK_SECRET" .env; then + echo " ✅ CHATWOOT_WEBHOOK_SECRET 已配置" + else + echo " ⚠️ CHATWOOT_WEBHOOK_SECRET 未配置（可选）" + fi +else + echo " ⚠️ .env 文件不存在" +fi +echo "" + +# 显示配置摘要 +echo "======================================" +echo "📋 配置摘要" +echo "======================================" +echo "" +echo "Agent 服务:" +echo " • 容器名称: ai_agent" +echo " • 内部地址: http://agent:8000" +echo " • Webhook 端点: http://agent:8000/webhooks/chatwoot" +echo " • 外部访问: http://localhost:8000" +echo "" +echo "Chatwoot 服务:" +echo " • 容器名称: ai_chatwoot" +echo " • 内部地址: http://chatwoot:3000" +echo " • 外部访问: http://localhost:3000" +echo "" +echo "📝 在 Chatwoot 界面中配置:" +echo " 1. 访问: http://localhost:3000" +echo " 2. 进入: Settings → Inboxes → 选择 Website 收件箱" +echo " 3. 点击: Configuration 标签" +echo " 4. 设置 Webhook URL 为: http://agent:8000/webhooks/chatwoot" +echo " 5. 点击 Save 保存" +echo "" +echo "⚠️ 注意事项:" +echo " • 不要在 Chatwoot 中启用内置机器人（Bot）" +echo " • 只配置 Webhook 即可" +echo " • Webhook URL 使用 'agent' 而不是 'localhost'" +echo "" +echo "======================================" diff --git a/tests/test_all_faq.sh b/tests/test_all_faq.sh new file mode 100755 index 0000000..e1bba6a --- /dev/null +++ b/tests/test_all_faq.sh @@ -0,0 +1,74 @@ +#!/bin/bash +# 测试所有 FAQ 分类 + +echo "==========================================" +echo "🧪 测试所有 FAQ 分类" +echo "==========================================" +echo "" + +# 定义测试用例 +declare -A TEST_CASES=( + ["订单相关"]="How do I place an order?" + ["支付相关"]="What payment methods do you accept?" + ["运输相关"]="What are the shipping options?" + ["退货相关"]="I received a defective item, what should I do?" + ["账号相关"]="I forgot my password, now what?" + ["营业时间"]="What are your opening hours?" +) + +# 测试每个分类 +for category in "${!TEST_CASES[@]}"; do + question="${TEST_CASES[$category]}" + conv_id="test_${category}___$(date +%s)" + + echo "━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━" + echo "📋 分类: $category" + echo "📝 问题: $question" + echo "⏳ 处理中..." + echo "" + + # 调用 API + RESPONSE=$(docker exec ai_agent curl -s -X POST 'http://localhost:8000/api/agent/query' \ + -H 'Content-Type: application/json' \ + -d "{\"conversation_id\":\"$conv_id\",\"user_id\":\"test_user\",\"account_id\":\"2\",\"message\":\"$question\"}") + + # 解析并显示结果 + echo "$RESPONSE" | python3 << PYTHON +import json +import sys + +try: + data = json.load(sys.stdin) + + # 提取响应 + response = data.get("response", "") + intent = data.get("intent", "") + + if response: + # 清理 HTML 标签（如果有） + import re + clean_response = re.sub(r'<[^<]+?>', '', response) + clean_response = clean_response.strip() + + # 截断过长响应 + if len(clean_response) > 300: + clean_response = clean_response[:300] + "..." + + print(f"🎯 意图: {intent}") + print(f"🤖 回答: {clean_response}") + else: + print("❌ 未获得回答") + print(f"调试信息: {json.dumps(data, indent=2, ensure_ascii=False)}") + +except Exception as e: + print(f"❌ 解析错误: {e}") + print(f"原始响应: {sys.stdin.read()}") +PYTHON + + echo "" + sleep 2 # 间隔 2 秒 +done + +echo "==========================================" +echo "✅ 所有测试完成" +echo "==========================================" diff --git a/tests/test_mall_order_query.py b/tests/test_mall_order_query.py new file mode 100644 index 0000000..c1ac47f --- /dev/null +++ b/tests/test_mall_order_query.py @@ -0,0 +1,103 @@ +""" +测试商城订单查询接口 + +Usage: + python test_mall_order_query.py + +Example: + python test_mall_order_query.py 202071324 +""" +import asyncio +import sys +import os + +# Add mcp_servers to path +sys.path.insert(0, os.path.join(os.path.dirname(__file__), "mcp_servers")) + +from shared.mall_client import MallClient + + +async def test_order_query(order_id: str, token: str): + """测试订单查询 + + Args: + order_id: 订单号 + token: JWT Token + """ + print(f"\n{'='*60}") + print(f"测试商城订单查询接口") + print(f"{'='*60}") + print(f"订单号 (Order ID): {order_id}") + print(f"API URL: https://apicn.qa1.gaia888.com") + print(f"{'='*60}\n") + + # 创建客户端 + client = MallClient( + api_url="https://apicn.qa1.gaia888.com", + api_token=token, + tenant_id="2", + currency_code="EUR", + language_id="1", + source="us.qa1.gaia888.com" + ) + + try: + # 调用订单查询接口 + result = await client.get_order_by_id(order_id) + + # 打印结果 + print("✅ 查询成功 (Query Success)!") + print(f"\n返回数据 (Response Data):") + print("-" * 60) + import json + print(json.dumps(result, ensure_ascii=False, indent=2)) + print("-" * 60) + + # 提取关键信息 + if isinstance(result, dict): + print(f"\n关键信息 (Key Information):") + print(f" 订单号 (Order ID): {result.get('order_id') or result.get('orderId') or order_id}") + print(f" 订单状态 (Status): {result.get('status') or result.get('order_status') or 'N/A'}") + print(f" 订单金额 (Amount): {result.get('total_amount') or result.get('amount') or 'N/A'}") + + # 商品信息 + items = result.get('items') or result.get('order_items') or result.get('products') + if items: + print(f" 商品数量 (Items): {len(items)}") + + except Exception as e: + print(f"❌ 查询失败 (Query Failed): {str(e)}") + import traceback + traceback.print_exc() + + finally: + await client.close() + + +def main(): + """主函数""" + if len(sys.argv) < 2: + print("Usage: python test_mall_order_query.py [token]") + print("\nExample:") + print(' python test_mall_order_query.py 202071324') + print(' python test_mall_order_query.py 202071324 "your_jwt_token_here"') + sys.exit(1) + + order_id = sys.argv[1] + + # 从命令行获取 token，如果没有提供则使用默认的测试 token + if len(sys.argv) >= 3: + token = sys.argv[2] + else: + # 使用用户提供的示例 token + token = "eyJ0eXAiOiJqd3QifQ.eyJzdWIiOiIxIiwiaXNzIjoiaHR0cDpcL1wvOiIsImV4cCI6MTc3MDUyMDY2MSwiaWF0IjoxNzY3OTI4NjYxLCJuYmYiOjE3Njc5Mjg2NjEsInVzZXJJZCI6MTAxNDMyLCJ0eXBlIjoyLCJ0ZW5hbnRJZCI6MiwidWlkIjoxMDE0MzIsInMiOiJkM0tZMjMiLCJqdGkiOiI3YjcwYTI2MzYwYjJmMzA3YmQ4YTYzNDAxOGVlNjlmZSJ9.dwiqln19-yAQSJd1w5bxZFrRgyohdAkHa1zW3W7Ov2I" + print("⚠️ 使用默认的测试 token（可能已过期）") + print(" 如需测试，请提供有效的 token:") + print(f' python {sys.argv[0]} {order_id} "your_jwt_token_here"\n') + + # 运行异步测试 + asyncio.run(test_order_query(order_id, token)) + + +if __name__ == "__main__": + main() diff --git a/tests/test_return_faq.py b/tests/test_return_faq.py new file mode 100644 index 0000000..595cf1b --- /dev/null +++ b/tests/test_return_faq.py @@ -0,0 +1,63 @@ +""" +测试退货相关 FAQ 回答 +""" +import asyncio +import sys +import os + +# 添加 agent 目录到路径 +sys.path.insert(0, '/app') + +from agents.customer_service import customer_service_agent +from core.state import AgentState + + +async def test_return_faq(): + """测试退货相关 FAQ""" + + # 测试问题列表 + test_questions = [ + "I received a defective item, what should I do?", + "How do I return a product?", + "What is your return policy?", + "I want to get a refund for my order", + ] + + for question in test_questions: + print(f"\n{'='*60}") + print(f"📝 问题: {question}") + print(f"{'='*60}") + + # 初始化状态 + state = AgentState( + conversation_id="test_return_001", + user_id="test_user", + account_id="2", + message=question, + history=[], + context={} + ) + + try: + # 调用客服 Agent + final_state = await customer_service_agent(state) + + # 获取响应 + response = final_state.get("response", "无响应") + tool_calls = final_state.get("tool_calls", []) + intent = final_state.get("intent") + + print(f"\n🎯 意图识别: {intent}") + print(f"\n🤖 AI 回答:") + print(response) + print(f"\n📊 调用的工具: {tool_calls}") + + except Exception as e: + print(f"\n❌ 错误: {e}") + import traceback + traceback.print_exc() + + +if __name__ == "__main__": + print("🧪 测试退货相关 FAQ 回答\n") + asyncio.run(test_return_faq())