Delete tab2_quarantine.py

tab2_quarantine.py

@@ -1,443 +0,0 @@
-import streamlit as st
-import plotly.graph_objects as go
-import numpy as np
-import pandas as pd
-from openai import OpenAI
-
-def init_tab2_session_state():
-    if 'api_key' not in st.session_state:
-        st.session_state.api_key = ""
-    if 'tab2_chat_history' not in st.session_state:
-        st.session_state.tab2_chat_history = []
-    if 'tab2_ct_booster' not in st.session_state:
-        st.session_state.tab2_ct_booster = 18.0
-    if 'tab2_days_booster' not in st.session_state:
-        st.session_state.tab2_days_booster = 7
-    if 'tab2_ct_no_booster' not in st.session_state:
-        st.session_state.tab2_ct_no_booster = 18.0
-    if 'tab2_days_no_booster' not in st.session_state:
-        st.session_state.tab2_days_no_booster = 7
-
-BASE_DATA = {
-    'ct18_no_booster': {1: 0.10, 2: 0.25, 3: 0.39, 4: 0.51, 5: 0.61, 6: 0.70, 7: 0.76, 8: 0.81, 9: 0.84, 10: 0.87,
-                        11: 0.89, 12: 0.91, 13: 0.93, 14: 0.94, 15: 0.95, 16: 0.96, 17: 0.96, 18: 0.97, 19: 0.97, 20: 0.98, 21: 0.98},
-    'ct18_booster': {1: 0.44, 2: 0.65, 3: 0.77, 4: 0.84, 5: 0.89, 6: 0.92, 7: 0.94, 8: 0.95, 9: 0.97, 10: 0.97,
-                     11: 0.97, 12: 0.98, 13: 0.98, 14: 0.99, 15: 0.99, 16: 0.99, 17: 0.99, 18: 0.99, 19: 0.99, 20: 1.00, 21: 1.00},
-    'ct22_no_booster': {1: 0.49, 2: 0.57, 3: 0.65, 4: 0.72, 5: 0.78, 6: 0.83, 7: 0.86, 8: 0.89, 9: 0.91, 10: 0.92,
-                        11: 0.94, 12: 0.95, 13: 0.96, 14: 0.97, 15: 0.97, 16: 0.98, 17: 0.98, 18: 0.98, 19: 0.98, 20: 0.99, 21: 0.99},
-    'ct22_booster': {1: 0.68, 2: 0.80, 3: 0.87, 4: 0.91, 5: 0.94, 6: 0.95, 7: 0.96, 8: 0.97, 9: 0.98, 10: 0.98,
-                     11: 0.98, 12: 0.99, 13: 0.99, 14: 0.99, 15: 0.99, 16: 1.00, 17: 1.00, 18: 1.00, 19: 1.00, 20: 1.00, 21: 1.00}
-}
-
-def get_effectiveness_from_data(data_key, days):
-    data = BASE_DATA[data_key]
-    if days < 1: return 0.0
-    if days > 21: return data[21]
-    if days in data: return data[days]
-    day_lower = int(days)
-    day_upper = day_lower + 1
-    if day_upper > 21: return data[21]
-    ratio = days - day_lower
-    return data[day_lower] * (1 - ratio) + data[day_upper] * ratio
-
-def get_quarantine_effectiveness(ct_value, days, has_booster):
-    if ct_value > 25: return 0.0
-    booster_suffix = 'booster' if has_booster else 'no_booster'
-    if ct_value <= 18:
-        data_key = f'ct18_{booster_suffix}'
-        effectiveness = get_effectiveness_from_data(data_key, days)
-        if ct_value < 10:
-            boost_factor = 1.0 + (10 - ct_value) * 0.005
-            effectiveness = min(effectiveness * boost_factor, 1.0)
-        return effectiveness
-    else:
-        ct18_key = f'ct18_{booster_suffix}'
-        ct22_key = f'ct22_{booster_suffix}'
-        eff_ct18 = get_effectiveness_from_data(ct18_key, days)
-        eff_ct22 = get_effectiveness_from_data(ct22_key, days)
-        ratio = (ct_value - 18) / 7
-        return min(eff_ct18 * (1 - ratio) + eff_ct22 * ratio, 1.0)
-
-def find_days_for_target_quarantine(ct_value, target_effectiveness, has_booster):
-    for days in range(1, 22):
-        if get_quarantine_effectiveness(ct_value, days, has_booster) >= target_effectiveness:
-            return days
-    return 21
-
-def get_ct_category(ct_value):
-    if ct_value <= 18: return "高病毒量 (Ct ≤ 18)"
-    elif ct_value <= 25: return "中病毒量 (18 < Ct ≤ 25)"
-    else: return "低病毒量 (Ct > 25，假設無傳染性)"
-
-def extract_quarantine_params(text):
-    import re
-    text_lower = text.lower()
-    
-    # 提取 Ct 值
-    ct_patterns = [r'ct\s*[=值]?\s*(\d+\.?\d*)', r'(\d+\.?\d*)\s*ct']
-    ct_value = None
-    for pattern in ct_patterns:
-        match = re.search(pattern, text_lower)
-        if match:
-            try:
-                ct_value = float(match.group(1))
-                if 10 <= ct_value <= 25:
-                    break
-            except:
-                continue
-    
-    # 提取天數
-    day_patterns = [r'(\d+)\s*天', r'隔離\s*(\d+)', r'檢疫\s*(\d+)']
-    days = None
-    for pattern in day_patterns:
-        match = re.search(pattern, text)
-        if match:
-            try:
-                days = int(match.group(1))
-                if 1 <= days <= 21:
-                    break
-            except:
-                continue
-    
-    # 檢查目標效益
-    target_eff = None
-    eff_patterns = [r'要.*?(\d+).*?%', r'達到.*?(\d+).*?%', r'(\d+).*?%.*?效益']
-    for pattern in eff_patterns:
-        match = re.search(pattern, text)
-        if match:
-            try:
-                target_eff = float(match.group(1)) / 100
-                if 0 <= target_eff <= 1:
-                    break
-            except:
-                continue
-    if '90%' in text: target_eff = 0.9
-    if '100%' in text or '百分之百' in text: target_eff = 1.0
-    
-    # 🔥 關鍵改進：檢測是否明確只問一種疫苗狀態
-    has_booster = None
-    
-    # 明確只問有加強劑的模式
-    only_with_booster_patterns = [
-        r'(只|僅|單獨|專門).{0,5}(有|已接種|��了).{0,5}(加強劑|疫苗)',
-        r'^(有|已接種|打了).{0,5}(加強劑|疫苗).*[?？]$'  # 以"有加強劑"開頭，問號結尾
-    ]
-    
-    # 明確只問無加強劑的模式
-    only_without_booster_patterns = [
-        r'(只|僅|單獨|專門).{0,5}(無|沒有|未接種|沒打).{0,5}(加強劑|疫苗)',
-        r'^(無|沒有|未接種|沒打).{0,5}(加強劑|疫苗).*[?？]$'
-    ]
-    
-    for pattern in only_with_booster_patterns:
-        if re.search(pattern, text):
-            has_booster = True
-            break
-    
-    if has_booster is None:
-        for pattern in only_without_booster_patterns:
-            if re.search(pattern, text):
-                has_booster = False
-                break
-    
-    # ✅ 預設：如果沒有明確指定，返回 None，觸發雙情境分析
-    return ct_value, days, target_eff, has_booster
-
-def call_gpt4_quarantine(prompt, api_key):
-    try:
-        client = OpenAI(api_key=api_key)
-        response = client.chat.completions.create(
-            model="gpt-4",
-            messages=[
-                {"role": "system", "content": "你是COVID-19 Omicron防疫專家，擅長同時分析有/無加強劑兩種情境。"},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7,
-            max_tokens=1500
-        )
-        return response.choices[0].message.content
-    except Exception as e:
-        return f"❌ API 呼叫失敗: {str(e)}"
-
-def create_3d_plot(ct_mesh, day_mesh, effectiveness_mesh, selected_ct, quarantine_days, 
-                   user_eff, has_booster, title, colorscale, marker_color):
-    fig = go.Figure()
-    fig.add_trace(go.Surface(
-        x=ct_mesh, y=day_mesh, z=effectiveness_mesh, colorscale=colorscale, showscale=True,
-        colorbar=dict(title="防疫效益", tickvals=[0, 0.25, 0.5, 0.75, 1.0], ticktext=['0%', '25%', '50%', '75%', '100%']),
-        opacity=0.9, name=title,
-        contours=dict(x=dict(show=True, color='white', width=1), y=dict(show=True, color='white', width=1), z=dict(show=True, color='white', width=1))
-    ))
-    fig.add_trace(go.Scatter3d(
-        x=[selected_ct], y=[quarantine_days], z=[user_eff], mode='markers+text',
-        marker=dict(size=12, color=marker_color, symbol='circle', line=dict(color='white', width=3)),
-        text=[f'{user_eff*100:.0f}%'], textposition='top center',
-        textfont=dict(size=14, color='white', family='Arial Black'), name='當前情境', showlegend=True
-    ))
-    fig.update_layout(
-        title={'text': title, 'x': 0.5, 'xanchor': 'center', 'font': {'size': 16}},
-        scene=dict(
-            xaxis=dict(title='X-病毒量(Ct值)', range=[10, 25], tickvals=[10, 15, 18, 20, 25],
-                      showgrid=True, gridwidth=2, gridcolor='rgb(200, 200, 200)', showbackground=True, backgroundcolor='rgba(240, 240, 240, 0.9)'),
-            yaxis=dict(title='Y-隔離檢疫天數', range=[1, 21], tickvals=[1, 5, 7, 10, 14, 21],
-                      showgrid=True, gridwidth=2, gridcolor='rgb(200, 200, 200)', showbackground=True, backgroundcolor='rgba(240, 240, 240, 0.9)'),
-            zaxis=dict(title='Z-防疫效益', range=[0, 1], tickvals=[0, 0.25, 0.5, 0.75, 1.0], ticktext=['0%', '25%', '50%', '75%', '100%'],
-                      showgrid=True, gridwidth=2, gridcolor='rgb(200, 200, 200)', showbackground=True, backgroundcolor='rgba(240, 240, 240, 0.9)'),
-            camera=dict(eye=dict(x=1.5, y=-1.5, z=1.3), center=dict(x=0, y=0, z=0)),
-            aspectmode='manual', aspectratio=dict(x=1, y=1.2, z=0.8)
-        ),
-        height=600, showlegend=True,
-        legend=dict(x=0.02, y=0.98, bgcolor='rgba(255, 255, 255, 0.9)', bordercolor='black', borderwidth=1),
-        margin=dict(l=0, r=0, t=40, b=0)
-    )
-    return fig
-
-def render():
-    init_tab2_session_state()
-    
-    with st.sidebar:
-        st.header("🏥 防疫決策工具 (隔離檢疫)")
-        st.markdown("**Omicron 變異株 - 雙情境對比**")
-        st.markdown("---")
-        
-        st.subheader("💉 有加強劑情境")
-        ct_booster = st.slider("🦠 接觸者Ct值", 10.0, 25.0, st.session_state.tab2_ct_booster, 0.5, key="tab2_ct_booster_slider")
-        st.session_state.tab2_ct_booster = ct_booster
-        st.caption("10 (高病毒量) ← → 25 (中病毒量)")
-        
-        days_booster = st.slider("📅 隔離檢疫天數", 1, 21, st.session_state.tab2_days_booster, key="tab2_days_booster_slider")
-        st.session_state.tab2_days_booster = days_booster
-        st.caption("1天 ← → 21天")
-        
-        eff_booster = get_quarantine_effectiveness(ct_booster, days_booster, True)
-        st.metric("📊 防疫效益", f"{eff_booster * 100:.0f}%", "有加強劑")
-        
-        st.markdown("---")
-        st.subheader("💊 無加強劑情境")
-        
-        ct_no_booster = st.slider("🦠 接觸者Ct值  ", 10.0, 25.0, st.session_state.tab2_ct_no_booster, 0.5, key="tab2_ct_no_booster_slider")
-        st.session_state.tab2_ct_no_booster = ct_no_booster
-        
-        days_no_booster = st.slider("📅 隔離檢疫天數  ", 1, 21, st.session_state.tab2_days_no_booster, key="tab2_days_no_booster_slider")
-        st.session_state.tab2_days_no_booster = days_no_booster
-        
-        eff_no_booster = get_quarantine_effectiveness(ct_no_booster, days_no_booster, False)
-        st.metric("📊 防疫效益", f"{eff_no_booster * 100:.0f}%", "無加強劑")
-        
-        st.markdown("---")
-        improvement = (eff_booster - eff_no_booster) * 100
-        if improvement > 0:
-            st.metric("💉 疫苗加成", f"+{improvement:.0f}%", "效益提升")
-        elif improvement < 0:
-            st.metric("⚠️ 效益差異", f"{improvement:.0f}%", "無加強劑較高")
-        
-        st.markdown("---")
-        if st.button("🤖 生成 AI 雙情境分析", type="primary", use_container_width=True, key="tab2_ai_report"):
-            if not st.session_state.api_key:
-                st.error("❌ 請先輸入 OpenAI API Key")
-            else:
-                with st.spinner("AI 正在分析兩種情境..."):
-                    prompt = f"""你是COVID-19 Omicron防疫專家。請對比分析以下兩種情境：
-
-**情境1: 有加強劑**
-- Ct 值: {ct_booster}
-- 隔離天數: {days_booster} 天
-- 防疫效益: {eff_booster*100:.1f}%
-
-**情境2: 無加強劑**
-- Ct 值: {ct_no_booster}
-- 隔離天數: {days_no_booster} 天
-- 防疫效益: {eff_no_booster*100:.1f}%
-
-**疫苗加成效益:** {improvement:.1f} 個百分點
-
-請提供：
-1. 兩種情境的效益評估與對比
-2. 疫苗接種對隔離政策的影響分析
-3. 針對兩種情境的具體隔離建議
-4. 實務操作建議
-
-請用繁體中文回答，簡潔專業。"""
-                    
-                    response = call_gpt4_quarantine(prompt, st.session_state.api_key)
-                    st.session_state.tab2_chat_history.append({
-                        "type": "dual_summary",
-                        "ct_booster": ct_booster, "days_booster": days_booster, "eff_booster": eff_booster,
-                        "ct_no_booster": ct_no_booster, "days_no_booster": days_no_booster, "eff_no_booster": eff_no_booster,
-                        "response": response
-                    })
-        
-        with st.expander("🎯 使用說明"):
-            st.markdown("""
-            **左側滑桿：** 手動探索參數，觀察3D圖變化
-            **右側AI：** 獨立查詢，不會影響左側滑桿
-            **AI特性：** 自動同時分析有/無加強劑兩種情況
-            """)
-
-    col1, col2 = st.columns([2, 1])
-
-    with col1:
-        ct_range = np.arange(10, 25.5, 0.5)
-        day_range = np.arange(1, 22, 1)
-        ct_mesh, day_mesh = np.meshgrid(ct_range, day_range)
-        effectiveness_with_booster = np.zeros_like(ct_mesh)
-        effectiveness_without_booster = np.zeros_like(ct_mesh)
-        
-        for i in range(len(day_range)):
-            for j in range(len(ct_range)):
-                effectiveness_with_booster[i, j] = get_quarantine_effectiveness(ct_mesh[i, j], day_mesh[i, j], True)
-                effectiveness_without_booster[i, j] = get_quarantine_effectiveness(ct_mesh[i, j], day_mesh[i, j], False)
-
-        user_eff_booster = get_quarantine_effectiveness(ct_booster, days_booster, True)
-        user_eff_no_booster = get_quarantine_effectiveness(ct_no_booster, days_no_booster, False)
-
-        st.markdown("### 💉 有加強劑情境")
-        fig1 = create_3d_plot(ct_mesh, day_mesh, effectiveness_with_booster, ct_booster, days_booster, 
-                             user_eff_booster, True, "隔離檢疫效益 - 有加強劑 (Omicron)",
-                             [[0.0, 'rgb(239, 68, 68)'], [0.33, 'rgb(245, 158, 11)'], [0.67, 'rgb(16, 185, 129)'], [1.0, 'rgb(59, 130, 246)']], 'blue')
-        st.plotly_chart(fig1, use_container_width=True)
-
-        st.markdown("### ⚠️ 無加強劑情境")
-        fig2 = create_3d_plot(ct_mesh, day_mesh, effectiveness_without_booster, ct_no_booster, days_no_booster,
-                             user_eff_no_booster, False, "隔離檢疫效益 - 無加強劑 (Omicron)",
-                             [[0.0, 'rgb(239, 68, 68)'], [0.33, 'rgb(245, 158, 11)'], [0.67, 'rgb(16, 185, 129)'], [1.0, 'rgb(59, 130, 246)']], 'red')
-        st.plotly_chart(fig2, use_container_width=True)
-
-        st.markdown("### 📊 雙情境對比")
-        col_info1, col_info2 = st.columns(2)
-        with col_info1:
-            st.info(f"""**💉 有加強劑情境**\n- Ct值: {ct_booster} ({get_ct_category(ct_booster)})\n- 隔離: {days_booster} 天\n- 效益: {user_eff_booster*100:.0f}%""")
-        with col_info2:
-            st.warning(f"""**⚠️ 無加強劑情境**\n- Ct值: {ct_no_booster} ({get_ct_category(ct_no_booster)})\n- 隔離: {days_no_booster} 天\n- 效益: {user_eff_no_booster*100:.0f}%""")
-
-    with col2:
-        st.subheader("🤖 AI 智能查詢")
-        st.info("💡 AI會自動分析有/無加強劑兩種情況，不會影響左側滑桿")
-        
-        user_input = st.text_input("輸入問題", placeholder="例如: Ct 18 隔離7天效益如何?", label_visibility="collapsed", key="tab2_user_input")
-        
-        if st.button("📤 發送", use_container_width=True, key="tab2_send"):
-            if not st.session_state.api_key:
-                st.error("❌ 請先輸入 OpenAI API Key")
-            elif user_input.strip():
-                with st.spinner("AI 分析中..."):
-                    extracted_ct, extracted_days, target_eff, extracted_booster = extract_quarantine_params(user_input)
-                    
-                    # 使用提取的Ct值，若無則使用滑桿的值作為參考
-                    ct_to_use = extracted_ct if extracted_ct else ct_booster
-                    
-                    # 🔥 根據查詢類型構建不同的 prompt
-                    if target_eff is not None:
-                        # 反向查詢：要達到X%效益需要多少天
-                        days_with = find_days_for_target_quarantine(ct_to_use, target_eff, True)
-                        days_without = find_days_for_target_quarantine(ct_to_use, target_eff, False)
-                        eff_with = get_quarantine_effectiveness(ct_to_use, days_with, True)
-                        eff_without = get_quarantine_effectiveness(ct_to_use, days_without, False)
-                        
-                        prompt = f"""用戶問題：{user_input}
-
-根據精確計算結果：
-
-**情境1 - 有接種加強劑：**
-- Ct 值: {ct_to_use}
-- 目標效益: {target_eff*100:.0f}%
-- 需要隔離: {days_with} 天
-- 實際達到: {eff_with*100:.1f}%
-
-**情境2 - 沒有接種加強劑：**
-- Ct 值: {ct_to_use}
-- 目標效益: {target_eff*100:.0f}%
-- 需要隔離: {days_without} 天
-- 實際達到: {eff_without*100:.1f}%
-
-**關鍵差異：** 接種加強劑可以減少 {days_without - days_with} 天隔離
-
-請用繁體中文簡潔回答：
-1️⃣ 有加強劑需要隔離{days_with}天
-2️⃣ 沒有加強劑需要隔離{days_without}天
-3️⃣ 疫苗可以縮短{days_without - days_with}天
-
-直接回答數據，不要解釋背景知識。"""
-                    
-                    elif extracted_days is not None:
-                        # 正向查詢：隔離X天的效益
-                        days_to_use = extracted_days
-                        eff_with = get_quarantine_effectiveness(ct_to_use, days_to_use, True)
-                        eff_without = get_quarantine_effectiveness(ct_to_use, days_to_use, False)
-                        
-                        prompt = f"""用戶問題：{user_input}
-
-根據精確計算結果：
-
-**情境1 - 有接種加強劑：**
-- Ct 值: {ct_to_use}
-- 隔離天數: {days_to_use} 天
-- 防疫效益: {eff_with*100:.1f}%
-
-**情境2 - 沒有接種加強劑：**
-- Ct 值: {ct_to_use}
-- 隔離天數: {days_to_use} 天
-- 防疫效益: {eff_without*100:.1f}%
-
-**關鍵差異：** 疫苗提升 {(eff_with - eff_without)*100:.1f} 個百分點效益
-
-請用繁體中文簡潔回答：
-1️⃣ 有加強劑：隔離{days_to_use}天可達{eff_with*100:.1f}%效益
-2️⃣ 沒有加強劑：隔離{days_to_use}天可達{eff_without*100:.1f}%效益
-3️⃣ 疫苗優勢：提升{(eff_with - eff_without)*100:.1f}個百分點
-
-直接回答數據，不要解釋背景知識。"""
-                    
-                    else:
-                        # 一般查詢
-                        prompt = f"""用戶問題：{user_input}
-
-作為專業防疫顧問，請針對 Ct={ct_to_use} 的情況，同時分析有/無加強劑兩種情境。
-
-請用繁體中文回答，必須包含：
-1️⃣ 有接種加強劑的情況（天數、效益）
-2️⃣ 沒有接種加強劑的情況（天數、效益）
-3️⃣ 兩者比較（疫苗優勢）
-
-簡潔回答，不要解釋背景知識。"""
-                    
-                    response = call_gpt4_quarantine(prompt, st.session_state.api_key)
-                    
-                    # ✅ 只保存對話記錄，完全不影響左側滑桿
-                    st.session_state.tab2_chat_history.append({
-                        "type": "user_query",
-                        "question": user_input,
-                        "response": response
-                    })
-        
-        st.markdown("---")
-        st.markdown("##### 📜 對話記錄")
-        if st.session_state.tab2_chat_history:
-            for chat in reversed(st.session_state.tab2_chat_history):
-                with st.container():
-                    if chat["type"] == "dual_summary":
-                        st.markdown(f"""**🤖 AI雙情境分析**
-- 💉有加強劑: Ct={chat['ct_booster']}, {chat['days_booster']}天, {chat['eff_booster']*100:.0f}%
-- ⚠️無加強劑: Ct={chat['ct_no_booster']}, {chat['days_no_booster']}天, {chat['eff_no_booster']*100:.0f}%""")
-                        st.markdown(chat["response"])
-                    else:
-                        st.markdown(f"**👤 問題:** {chat['question']}")
-                        st.markdown(f"**🤖 回答:** {chat['response']}")
-                    st.markdown("---")
-            if st.button("🗑️ 清除記錄", use_container_width=True, key="tab2_clear"):
-                st.session_state.tab2_chat_history = []
-                st.rerun()
-        else:
-            st.info("💡 輸入問題開始查詢\n\nAI會自動分析兩種情況")
-
-    st.markdown("---")
-    with st.expander("📊 數據對比表"):
-        test_days = [3, 5, 7, 10, 14]
-        st.markdown(f"**以 Ct={ct_booster} 為例**")
-        df = pd.DataFrame({
-            '天數': test_days,
-            '有加強劑': [f"{get_quarantine_effectiveness(ct_booster,d,True)*100:.0f}%" for d in test_days],
-            '無加強劑': [f"{get_quarantine_effectiveness(ct_booster,d,False)*100:.0f}%" for d in test_days],
-            '差異': [f"+{(get_quarantine_effectiveness(ct_booster,d,True)-get_quarantine_effectiveness(ct_booster,d,False))*100:.0f}%" for d in test_days]
-        })
-        st.dataframe(df, use_container_width=True)