153 lines
5.6 KiB
Python
153 lines
5.6 KiB
Python
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import streamlit as st
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import pandas as pd
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import joblib
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import os
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import sys
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# 添加项目根目录到 Path 以便导入 src
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sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
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from src.agent_app import MarketingAgent, CustomerFeatures
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# 配置页面
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st.set_page_config(
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page_title="智能银行营销助手",
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page_icon="🤖",
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layout="wide"
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)
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# 侧边栏：项目信息
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with st.sidebar:
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st.title("🏦 智能营销系统")
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st.markdown("---")
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st.info("**Day 5 演示版**")
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st.markdown("""
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**核心能力：**
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1. 📊 **LightGBM** 客户购买预测
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2. 🧠 **Agent** 策略生成
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3. 📝 **Pydantic** 结构化输出
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""")
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st.markdown("---")
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st.caption("由第 X 组开发")
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# 主界面
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st.title("🤖 客户意向预测与决策系统")
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# 1. 模拟客户输入
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st.header("1. 录入客户信息")
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col1, col2, col3 = st.columns(3)
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# 映射字典
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job_map = {
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"management": "管理人员", "technician": "技术人员", "entrepreneur": "企业家",
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"blue-collar": "蓝领", "unknown": "未知", "retired": "退休人员",
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"admin.": "行政人员", "services": "服务业", "self-employed": "自雇人士",
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"unemployed": "失业", "maid": "家政", "student": "学生"
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}
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education_map = {"tertiary": "高等教育", "secondary": "中等教育", "primary": "初等教育", "unknown": "未知"}
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marital_map = {"married": "已婚", "single": "单身", "divorced": "离异"}
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binary_map = {"yes": "是", "no": "否"}
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contact_map = {"cellular": "手机", "telephone": "座机", "unknown": "未知"}
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month_map = {
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"jan": "1月", "feb": "2月", "mar": "3月", "apr": "4月", "may": "5月", "jun": "6月",
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"jul": "7月", "aug": "8月", "sep": "9月", "oct": "10月", "nov": "11月", "dec": "12月"
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}
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poutcome_map = {"unknown": "未知", "failure": "失败", "other": "其他", "success": "成功"}
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# 辅助函数：反向查找 key
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def get_key(val, my_dict):
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for key, value in my_dict.items():
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if val == value: return key
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return val
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with col1:
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age = st.number_input("年龄", 18, 100, 30)
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job_display = st.selectbox("职业", list(job_map.values()))
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job = get_key(job_display, job_map)
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education_display = st.selectbox("教育", list(education_map.values()))
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education = get_key(education_display, education_map)
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balance = st.number_input("账户余额 (欧元)", -1000, 100000, 1500)
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with col2:
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marital_display = st.selectbox("婚姻", list(marital_map.values()))
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marital = get_key(marital_display, marital_map)
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housing_display = st.selectbox("是否有房贷", list(binary_map.values()))
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housing = get_key(housing_display, binary_map)
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loan_display = st.selectbox("是否有个人贷", list(binary_map.values()))
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loan = get_key(loan_display, binary_map)
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default_display = st.selectbox("是否有违约记录", list(binary_map.values()))
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default = get_key(default_display, binary_map)
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with col3:
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contact_display = st.selectbox("联系方式", list(contact_map.values()))
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contact = get_key(contact_display, contact_map)
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month_display = st.selectbox("最后联系月份", list(month_map.values()))
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month = get_key(month_display, month_map)
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day = st.slider("最后联系日", 1, 31, 15)
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poutcome_display = st.selectbox("上次活动结果", list(poutcome_map.values()))
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poutcome = get_key(poutcome_display, poutcome_map)
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# 隐藏的高级特征
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with st.expander("高级营销特征 (可选)"):
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campaign = st.number_input("本次活动联系次数", 1, 50, 1)
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pdays = st.number_input("距离上次联系天数 (-1代表无)", -1, 999, -1)
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previous = st.number_input("活动前联系次数", 0, 100, 0)
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# 2. 触发 Agent
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if st.button("🚀 开始分析与决策", type="primary"):
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try:
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# 构造 Pydantic 对象
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customer = CustomerFeatures(
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age=age, job=job, marital=marital, education=education,
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default=default, balance=balance, housing=housing, loan=loan,
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contact=contact, day=day, month=month,
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campaign=campaign, pdays=pdays, previous=previous, poutcome=poutcome
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)
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# 初始化 Agent
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with st.spinner("Agent 正在加载模型并思考..."):
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agent = MarketingAgent()
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decision = agent.run(customer)
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# 3. 展示结果
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st.divider()
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st.header("2. 智能分析报告")
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# 结果看板
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res_col1, res_col2 = st.columns([1, 2])
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with res_col1:
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st.metric("预测购买概率", f"{decision.risk_score:.1%}")
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if decision.risk_score > 0.6:
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st.success(f"分群：{decision.customer_segment}")
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elif decision.risk_score > 0.3:
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st.warning(f"分群：{decision.customer_segment}")
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else:
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st.error(f"分群：{decision.customer_segment}")
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with res_col2:
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st.subheader("💡 决策建议")
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st.info(decision.decision)
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st.markdown(f"**决策依据：** {decision.rationale}")
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# 行动清单
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st.subheader("📝 执行清单")
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for i, action in enumerate(decision.actions, 1):
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st.write(f"{i}. {action}")
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# JSON 视图
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with st.expander("查看原始 JSON 输出 (Traceable)"):
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st.json(decision.model_dump())
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except Exception as e:
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st.error(f"发生错误: {str(e)}")
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