252 lines
7.7 KiB
Python
252 lines
7.7 KiB
Python
|
"""
|
|||
|
|
Aftersale Agent - Handles returns, exchanges, and complaints
|
|||
|
|
"""
|
|||
|
|
import json
|
|||
|
|
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 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
|
|||
|
|
"""
|
|||
|
|
logger.info(
|
|||
|
|
"Aftersale agent processing",
|
|||
|
|
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)
|
|||
|
|
|
|||
|
|
# Build messages for LLM
|
|||
|
|
messages = [
|
|||
|
|
Message(role="system", content=AFTERSALE_AGENT_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"
|
|||
|
|
|
|||
|
|
if state["entities"]:
|
|||
|
|
context_info += f"已提取的信息: {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']}"
|
|||
|
|
messages.append(Message(role="user", content=user_content))
|
|||
|
|
|
|||
|
|
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)
|
|||
|
|
action = result.get("action")
|
|||
|
|
|
|||
|
|
if action == "call_tool":
|
|||
|
|
arguments = result.get("arguments", {})
|
|||
|
|
arguments["user_id"] = state["user_id"]
|
|||
|
|
|
|||
|
|
# 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"],
|
|||
|
|
arguments=arguments,
|
|||
|
|
server="aftersale"
|
|||
|
|
)
|
|||
|
|
state["state"] = ConversationState.TOOL_CALLING.value
|
|||
|
|
|
|||
|
|
elif action == "ask_info":
|
|||
|
|
state = set_response(state, result["question"])
|
|||
|
|
state["state"] = ConversationState.AWAITING_INFO.value
|
|||
|
|
# Store required fields in context for next iteration
|
|||
|
|
if result.get("required_fields"):
|
|||
|
|
state = update_context(state, {"required_fields": result["required_fields"]})
|
|||
|
|
|
|||
|
|
elif action == "respond":
|
|||
|
|
state = set_response(state, result["response"])
|
|||
|
|
state["state"] = ConversationState.GENERATING.value
|
|||
|
|
|
|||
|
|
elif action == "handoff":
|
|||
|
|
state["requires_human"] = True
|
|||
|
|
state["handoff_reason"] = result.get("reason", "Complex aftersale issue")
|
|||
|
|
|
|||
|
|
return state
|
|||
|
|
|
|||
|
|
except json.JSONDecodeError:
|
|||
|
|
state = set_response(state, response.content)
|
|||
|
|
return state
|
|||
|
|
|
|||
|
|
except Exception as e:
|
|||
|
|
logger.error("Aftersale agent failed", error=str(e))
|
|||
|
|
state["error"] = str(e)
|
|||
|
|
return state
|
|||
|
|
|
|||
|
|
|
|||
|
|
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)}")
|
|||
|
|
|
|||
|
|
# 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。
|
|||
|
|
|
|||
|
|
用户问题: {state["current_message"]}
|
|||
|
|
|
|||
|
|
系统返回信息:
|
|||
|
|
{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
|
|||
|
|
|
|||
|
|
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="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。")
|
|||
|
|
return state
|