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Update src/streamlit_app.py
Browse files- src/streamlit_app.py +149 -344
src/streamlit_app.py
CHANGED
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import streamlit as st
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import
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import pandas as pd
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from datetime import datetime
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import time
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from
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# 导入你的MsPatient类和辅助函数
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try:
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from ms_patient import MsPatient # 请根据实际路径调整
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ANNA_AGENT_AVAILABLE = True
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except ImportError:
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ANNA_AGENT_AVAILABLE = False
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# 导入辅助函数
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from integration_example import (
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load_dataset, validate_patient_data, initialize_patient_agent,
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simulate_response, export_chat_history, get_patient_summary
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)
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#
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st.set_page_config(
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page_title="
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page_icon="
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layout="wide"
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initial_sidebar_state="expanded"
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)
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# 自定义CSS样式
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st.markdown("""
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<style>
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color: #2E86AB;
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text-align: center;
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margin-bottom: 2rem;
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text-shadow: 2px 2px 4px rgba(0,0,0,0.1);
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}
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.chat-container {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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border-radius: 15px;
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padding: 20px;
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margin: 10px 0;
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box-shadow: 0 8px 16px rgba(0,0,0,0.2);
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}
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.user-message {
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background: linear-gradient(135deg, #4facfe 0%, #00f2fe 100%);
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color: white;
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padding: 15px;
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border-radius: 15px;
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margin: 10px 0;
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box-shadow: 0 4px 8px rgba(0,0,0,0.1);
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float: right;
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clear: both;
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max-width: 70%;
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margin-left: 30%;
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}
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margin: 10px 0;
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box-shadow: 0 4px 8px rgba(0,0,0,0.1);
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float: left;
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clear: both;
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max-width: 70%;
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margin-right: 30%;
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}
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background: #f0f2f6;
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padding: 15px;
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border-radius: 10px;
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margin: 10px 0;
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border-left: 4px solid #2E86AB;
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}
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.
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margin: 20px 0;
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}
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background: white;
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padding: 20px;
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border-radius: 10px;
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text-align: center;
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box-shadow: 0 4px 8px rgba(0,0,0,0.1);
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min-width: 120px;
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}
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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border: none;
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border-radius: 25px;
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padding: 0.5rem 2rem;
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font-weight: 600;
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transition: all 0.3s ease;
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}
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.stButton > button:hover {
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transform: translateY(-2px);
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box-shadow: 0 6px 12px rgba(0,0,0,0.2);
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}
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</style>
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""", unsafe_allow_html=True)
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# 初始化session state
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if 'messages' not in st.session_state:
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st.session_state.messages = []
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if 'patient_agent' not in st.session_state:
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st.session_state.patient_agent = None
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if 'current_patient_data' not in st.session_state:
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st.session_state.current_patient_data = None
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#
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# 侧边栏
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with st.sidebar:
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st.
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"
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"
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"gender": "女",
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"occupation": "软件工程师",
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"marital_status": "未婚",
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"symptom": "抑郁情绪、失眠、食欲不振"
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},
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"report": {
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"chief_complaint": "最近几个月感到情绪低落",
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"history": "工作压力大,经常加班",
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"mental_status": "情绪低落,思维迟缓"
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},
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"conversation": []
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},
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"示例患者2 - 焦虑症状": {
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"id": "example_002",
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"portrait": {
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"age": 35,
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"gender": "男",
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"occupation": "销售经理",
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"marital_status": "已婚",
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"symptom": "焦虑、心慌、担心"
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},
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"report": {
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"chief_complaint": "经常感到紧张焦虑",
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"history": "业绩压力,家庭责任重",
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"mental_status": "焦虑不安,注意力不集中"
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},
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"conversation": []
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}
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}
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selected_example = st.selectbox(
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"选择一个示例患者",
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options=list(example_patients.keys())
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)
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if st.button("🚀 启动会话", type="primary"):
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patient_data = example_patients[selected_example]
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st.session_state.current_patient_data = patient_data
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# 初始化患者智能体
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if ANNA_AGENT_AVAILABLE:
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agent, message = initialize_patient_agent(patient_data)
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if agent:
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st.session_state.patient_agent = agent
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st.success(f"✅ 患者智能体已启动!{message}")
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else:
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st.error(f"❌ 启动失败: {message}")
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st.session_state.patient_agent = None
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else:
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st.warning("
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st.rerun()
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else:
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# 处理上传的文件
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try:
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data = load_dataset(uploaded_file)
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if data and isinstance(data, list):
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patients_df = pd.DataFrame(data)
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st.markdown("### 👥 患者列表")
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# 显示患者信息表格
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display_df = patients_df[['id']].copy()
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if 'portrait' in patients_df.columns:
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display_df['年龄'] = patients_df['portrait'].apply(lambda x: x.get('age', 'N/A') if isinstance(x, dict) else 'N/A')
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display_df['性别'] = patients_df['portrait'].apply(lambda x: x.get('gender', 'N/A') if isinstance(x, dict) else 'N/A')
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display_df['症状'] = patients_df['portrait'].apply(lambda x: x.get('symptom', 'N/A') if isinstance(x, dict) else 'N/A')
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selected_id = st.selectbox("选择患者ID", options=patients_df['id'].tolist())
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if st.button("🚀 启动会话", type="primary"):
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selected_patient = patients_df[patients_df['id'] == selected_id].iloc[0].to_dict()
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st.session_state.current_patient_data = selected_patient
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# 初始化患者智能体
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if ANNA_AGENT_AVAILABLE:
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agent, message = initialize_patient_agent(selected_patient)
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if agent:
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st.session_state.patient_agent = agent
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st.success(f"✅ 患者智能体已启动!{message}")
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else:
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st.error(f"❌ 启动失败: {message}")
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st.session_state.patient_agent = None
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else:
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st.warning("⚠️ 使用模拟模式")
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st.session_state.patient_agent = None
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st.rerun()
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except Exception as e:
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st.error(f"❌ 文件加载失败: {str(e)})")
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# 分隔线
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st.markdown("---")
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#
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if
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st.
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""
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if st.button("🔄 重置会话"):
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st.session_state.messages = []
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st.rerun()
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with col2:
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if st.button("💾 导出记录"):
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if st.session_state.messages:
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chat_history = {
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"patient_id": st.session_state.current_patient_data.get('id', 'unknown') if st.session_state.current_patient_data else 'unknown',
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"timestamp": datetime.now().isoformat(),
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"messages": st.session_state.messages
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}
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st.download_button(
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label="📥 下载聊天记录",
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data=json.dumps(chat_history, ensure_ascii=False, indent=2),
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file_name=f"chat_history_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json",
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mime="application/json"
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)
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#
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if st.session_state.
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""", unsafe_allow_html=True)
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else:
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# 显示聊天历史
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chat_container = st.container()
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with chat_container:
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for message in st.session_state.messages:
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if message["role"] == "user":
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st.markdown(f"""
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<div class="user-message">
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<strong>咨询师:</strong> {message["content"]}
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</div>
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""", unsafe_allow_html=True)
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else:
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st.markdown(f"""
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<div class="assistant-message">
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<strong>来访者:</strong> {message["content"]}
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</div>
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""", unsafe_allow_html=True)
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# 输入框
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with st.form(key="chat_form", clear_on_submit=True):
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col1, col2 = st.columns([4, 1])
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with col1:
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user_input = st.text_area(
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"输入您的话语:",
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placeholder="请输入您想对来访者说的话...",
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height=100,
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key="user_input"
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)
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with col2:
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st.markdown("<br>", unsafe_allow_html=True) # 增加一些间距
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submit_button = st.form_submit_button("💬 发送", type="primary")
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if submit_button and user_input:
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# 添加用户消息到聊天历史
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st.session_state.messages.append({"role": "user", "content": user_input})
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try:
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# 模拟调用(你需要替换为实际的调用)
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# if st.session_state.patient_agent:
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# response = st.session_state.patient_agent.chat(user_input)
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# else:
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# response = "抱歉,智能体尚未初始化。"
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# 临时模拟回复
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time.sleep(1) # 模拟思考时间
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response = f"谢谢您的关心。您说'{user_input}',这让我想到..."
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# 添加助手回复到聊天历史
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st.session_state.messages.append({"role": "assistant", "content": response})
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except Exception as e:
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st.error(f"❌ 生成回复时出错: {str(e)}")
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st.session_state.messages.append({
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"role": "assistant",
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"content": "抱歉,我现在无法回复。请稍后再试。"
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})
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st.rerun()
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st.
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col1, col2, col3 = st.columns(3)
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with col1:
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if st.session_state.messages:
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st.metric("💬 对话轮数", len(st.session_state.messages) // 2)
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import streamlit as st
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from openai import OpenAI
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import time
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from datasets import load_dataset # 导入Hugging Face datasets库
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# =======================================================================
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# 1. 导入您的类和数据
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# =======================================================================
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# 请将 'your_agent_file' 替换为包含 MsPatient 类的实际文件名
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from ms_patient import MsPatient
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# 使用Streamlit的缓存功能来加载和缓存数据集
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@st.cache_data
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def load_hf_dataset():
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"""
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从Hugging Face Hub加载并缓存数据集。
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这将返回一个字典列表,每个字典代表一个病人数据。
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"""
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try:
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# 加载'train'分割部分的数据
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dataset = load_dataset("sci-m-wang/Anna-CPsyCounD", split='train')
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# 转换为pandas DataFrame再转为字典列表,方便处理
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return dataset.to_pandas().to_dict('records')
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except Exception as e:
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st.error(f"从Hugging Face加载数据集失败: {e}")
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return []
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# 加载数据
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ALL_PATIENTS = load_hf_dataset()
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# =======================================================================
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# 2. Streamlit 应用界面
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# =======================================================================
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# --- 页面配置 ---
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st.set_page_config(
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page_title="与Anna对话",
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page_icon="�",
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layout="wide"
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)
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# --- 自定义CSS样式 ---
|
45 |
st.markdown("""
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<style>
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47 |
+
/* 主聊天容器 */
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+
.st-emotion-cache-1y4p8pa {
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+
padding-top: 2rem;
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}
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+
/* 聊天消息 */
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+
.st-chat-message {
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+
border-radius: 0.8rem;
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+
padding: 0.9rem 1.2rem;
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+
box-shadow: 0 2px 5px rgba(0,0,0,0.05);
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+
background-color: #ffffff;
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}
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+
.st-chat-message[data-testid="chat-message-container-user"] {
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+
background-color: #dcf8c6;
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}
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+
/* 侧边栏 */
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+
.st-sidebar {
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+
background-color: #f8f9fa;
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+
border-right: 1px solid #e9ecef;
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}
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+
.st-sidebar h2 {
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+
color: #343a40;
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}
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+
.st-expanderHeader {
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+
font-size: 1.1rem;
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font-weight: 600;
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}
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</style>
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""", unsafe_allow_html=True)
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76 |
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+
# --- 初始化 Session State ---
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+
if "patient_agent" not in st.session_state:
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+
st.session_state.patient_agent = None
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80 |
+
if "messages" not in st.session_state:
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81 |
+
st.session_state.messages = []
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82 |
+
if "selected_patient_id" not in st.session_state:
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83 |
+
st.session_state.selected_patient_id = None
|
84 |
+
if "openai_client" not in st.session_state:
|
85 |
+
st.session_state.openai_client = None
|
86 |
+
if "model_name" not in st.session_state:
|
87 |
+
st.session_state.model_name = "gpt-4o-mini" # 默认模型
|
88 |
|
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+
# --- 侧边栏 ---
|
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with st.sidebar:
|
91 |
+
st.title("👩 AnnaAgent 设置")
|
92 |
+
st.markdown("---")
|
93 |
+
|
94 |
+
# API Key 输入
|
95 |
+
with st.expander("🔑 API 设置", expanded=True):
|
96 |
+
api_key = st.text_input("输入您的 OpenAI API Key", type="password", help="您的API Key将仅用于本次会话,不会被储存。")
|
97 |
+
base_url = st.text_input("API Base URL (可选)", value="https://api.openai.com/v1")
|
98 |
+
model_name = st.text_input("模型名称", value=st.session_state.model_name)
|
99 |
+
|
100 |
+
if st.button("连接模型"):
|
101 |
+
if api_key:
|
102 |
+
try:
|
103 |
+
st.session_state.openai_client = OpenAI(api_key=api_key, base_url=base_url)
|
104 |
+
st.session_state.model_name = model_name
|
105 |
+
st.success("连接成功!")
|
106 |
+
if st.session_state.patient_agent:
|
107 |
+
st.session_state.patient_agent.client = st.session_state.openai_client
|
108 |
+
except Exception as e:
|
109 |
+
st.error(f"连接失败: {e}")
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|
110 |
else:
|
111 |
+
st.warning("请输入API Key。")
|
112 |
+
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|
113 |
st.markdown("---")
|
114 |
+
|
115 |
+
# 病人选择
|
116 |
+
if not ALL_PATIENTS:
|
117 |
+
st.error("无法加载病人数据,请检查网络连接或数据集名称。")
|
118 |
+
else:
|
119 |
+
patient_options = {p["id"]: f"{p['portrait']['gender']},{p['portrait']['age']}岁 - {p['portrait']['symptom']}" for p in ALL_PATIENTS}
|
120 |
+
selected_id = st.selectbox(
|
121 |
+
"选择一位病人进行对话",
|
122 |
+
options=list(patient_options.keys()),
|
123 |
+
format_func=lambda x: patient_options[x]
|
124 |
+
)
|
125 |
+
|
126 |
+
# 当选择的病人变化时,重置状态
|
127 |
+
if st.session_state.selected_patient_id != selected_id:
|
128 |
+
st.session_state.selected_patient_id = selected_id
|
129 |
+
selected_patient_data = next((p for p in ALL_PATIENTS if p["id"] == selected_id), None)
|
130 |
+
|
131 |
+
with st.spinner("正在生成病人角色..."):
|
132 |
+
st.session_state.patient_agent = MsPatient(
|
133 |
+
portrait=selected_patient_data["portrait"],
|
134 |
+
report=selected_patient_data["report"],
|
135 |
+
previous_conversations=selected_patient_data["conversation"],
|
136 |
+
language="Chinese",
|
137 |
+
client=st.session_state.openai_client
|
|
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|
138 |
)
|
139 |
+
st.session_state.messages = [{"role": "assistant", "content": "你好,医生..."}]
|
140 |
+
st.rerun()
|
141 |
|
142 |
+
# 显示病人信息
|
143 |
+
if st.session_state.patient_agent:
|
144 |
+
st.markdown("---")
|
145 |
+
st.subheader("病人信息")
|
146 |
+
agent = st.session_state.patient_agent
|
147 |
+
st.info(f"""
|
148 |
+
**基本情况**: {agent.portrait['gender']}, {agent.portrait['age']}岁, {agent.portrait['occupation']}, {agent.portrait['marital_status']}
|
|
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|
|
149 |
|
150 |
+
**近期状态**: {agent.status}
|
151 |
+
""")
|
|
|
|
|
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|
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|
|
|
152 |
|
153 |
+
with st.expander("查看完整系统提示 (System Prompt)"):
|
154 |
+
st.code(agent.get_system_prompt(), language='markdown')
|
|
|
155 |
|
|
|
|
|
|
|
156 |
|
157 |
+
# --- 主聊天界面 ---
|
158 |
+
st.title("💬 与 Anna 对话")
|
159 |
+
st.caption("这是一个模拟心理咨询的AI Agent。由 `MsPatient` 类驱动。")
|
160 |
|
161 |
+
# 显示聊天记录
|
162 |
+
for message in st.session_state.messages:
|
163 |
+
avatar = "👩" if message["role"] == "assistant" else "🧑⚕️"
|
164 |
+
with st.chat_message(message["role"], avatar=avatar):
|
165 |
+
st.markdown(message["content"])
|
166 |
|
167 |
+
# 获取用户输入
|
168 |
+
if prompt := st.chat_input("请输入您想说的话..."):
|
169 |
+
st.session_state.messages.append({"role": "user", "content": prompt})
|
170 |
+
with st.chat_message("user", avatar="🧑⚕️"):
|
171 |
+
st.markdown(prompt)
|
172 |
+
|
173 |
+
if st.session_state.patient_agent:
|
174 |
+
with st.chat_message("assistant", avatar="👩"):
|
175 |
+
with st.spinner("Anna正在思考..."):
|
176 |
+
response = st.session_state.patient_agent.chat(prompt)
|
177 |
+
st.markdown(response)
|
178 |
+
|
179 |
+
st.session_state.messages.append({"role": "assistant", "content": response})
|
180 |
+
else:
|
181 |
+
st.warning("请先在左侧选择一位病人并配置API Key。")
|