Update app.py

app.py

@@ -124,241 +124,6 @@ class StockAnalyzer:
                 'symbol': symbol
             }
     
-    def get_fundamental_data(self, symbol):
-        """獲取基本面數據"""
-        try:
-            ticker = yf.Ticker(symbol)
-            info = ticker.info
-            
-            # 獲取財務數據
-            fundamental_data = {
-                'pe_ratio': info.get('trailingPE', None),  # 本益比
-                'peg_ratio': info.get('pegRatio', None),  # PEG比率
-                'pb_ratio': info.get('priceToBook', None),  # 股價淨值比
-                'dividend_yield': info.get('dividendYield', 0) * 100 if info.get('dividendYield') else 0,  # 股息殖利率
-                'roe': info.get('returnOnEquity', None),  # 股東權益報酬率
-                'debt_to_equity': info.get('debtToEquity', None),  # 負債權益比
-                'current_ratio': info.get('currentRatio', None),  # 流動比率
-                'gross_margins': info.get('grossMargins', None),  # 毛利率
-                'operating_margins': info.get('operatingMargins', None),  # 營業利益率
-                'profit_margins': info.get('profitMargins', None),  # 淨利率
-                'revenue_growth': info.get('revenueGrowth', None),  # 營收成長率
-                'earnings_growth': info.get('earningsGrowth', None),  # 盈餘成長率
-                'book_value': info.get('bookValue', None),  # 每股淨值
-                'eps': info.get('trailingEps', None),  # 每股盈餘
-                'forward_eps': info.get('forwardEps', None),  # 預估每股盈餘
-                'market_cap': info.get('marketCap', None),  # 市值
-                'enterprise_value': info.get('enterpriseValue', None),  # 企業價值
-                'price_to_sales': info.get('priceToSalesTrailing12Months', None),  # 股價營收比
-                'beta': info.get('beta', None),  # 貝塔值
-            }
-            
-            return fundamental_data
-            
-        except Exception as e:
-            print(f"基本面數據獲取失敗 {symbol}: {str(e)}")
-            return {}
-    
-    def calculate_fair_value(self, symbol, fundamental_data, current_price):
-        """計算合理價位"""
-        try:
-            fair_values = []
-            methods_used = []
-            
-            # 方法1: 本益比法 (PE Method)
-            if fundamental_data.get('eps') and fundamental_data.get('pe_ratio'):
-                industry_avg_pe = 15  # 假設產業平均本益比
-                pe_fair_value = fundamental_data['eps'] * industry_avg_pe
-                fair_values.append(pe_fair_value)
-                methods_used.append('本益比法')
-            
-            # 方法2: 淨值比法 (PB Method)  
-            if fundamental_data.get('book_value') and fundamental_data.get('pb_ratio'):
-                industry_avg_pb = 1.5  # 假設產業平均淨值比
-                pb_fair_value = fundamental_data['book_value'] * industry_avg_pb
-                fair_values.append(pb_fair_value)
-                methods_used.append('淨值比法')
-            
-            # 方法3: 股息折現模型 (DDM)
-            if fundamental_data.get('dividend_yield') and fundamental_data['dividend_yield'] > 0:
-                required_return = 0.08  # 假設要求報酬率8%
-                dividend_per_share = current_price * (fundamental_data['dividend_yield'] / 100)
-                growth_rate = fundamental_data.get('earnings_growth', 0.03)  # 假設3%成長率
-                if required_return > growth_rate:
-                    ddm_fair_value = dividend_per_share * (1 + growth_rate) / (required_return - growth_rate)
-                    fair_values.append(ddm_fair_value)
-                    methods_used.append('股息折現法')
-            
-            # 方法4: 自由現金流折現 (簡化版)
-            if fundamental_data.get('market_cap') and fundamental_data.get('profit_margins'):
-                # 簡化的DCF估算
-                estimated_fcf = fundamental_data['market_cap'] * (fundamental_data['profit_margins'] or 0.05)
-                discount_rate = 0.1  # 10%折現率
-                growth_rate = 0.03  # 3%永續成長率
-                terminal_value = estimated_fcf * (1 + growth_rate) / (discount_rate - growth_rate)
-                shares_outstanding = fundamental_data['market_cap'] / current_price if current_price else 1
-                dcf_fair_value = terminal_value / shares_outstanding
-                fair_values.append(dcf_fair_value)
-                methods_used.append('現金流折現法')
-            
-            # 計算平均合理價位
-            if fair_values:
-                average_fair_value = sum(fair_values) / len(fair_values)
-                return {
-                    'fair_value': average_fair_value,
-                    'methods_used': methods_used,
-                    'individual_values': dict(zip(methods_used, fair_values)),
-                    'upside_potential': ((average_fair_value - current_price) / current_price * 100) if current_price else 0
-                }
-            else:
-                return {
-                    'fair_value': None,
-                    'methods_used': [],
-                    'individual_values': {},
-                    'upside_potential': 0
-                }
-                
-        except Exception as e:
-            print(f"合理價位計算失敗 {symbol}: {str(e)}")
-            return {
-                'fair_value': None,
-                'methods_used': [],
-                'individual_values': {},
-                'upside_potential': 0
-            }
-    
-    def generate_investment_recommendation(self, symbol, current_price, technical_probs, fair_value_data, fundamental_data):
-        """生成投資建議"""
-        try:
-            recommendations = []
-            overall_score = 0
-            max_score = 100
-            
-            # 技術面評分 (30%)
-            tech_score = 0
-            if technical_probs['up'] > 50:
-                tech_score = 25
-                recommendations.append("✅ 技術面: 上漲機率較高，技術指標偏多")
-            elif technical_probs['down'] > 50:
-                tech_score = 5
-                recommendations.append("❌ 技術面: 下跌機率較高，技術指標偏空")
-            else:
-                tech_score = 15
-                recommendations.append("⚠️ 技術面: 盤整機率較高，缺乏明確方向")
-            
-            # 基本面評分 (40%)
-            fundamental_score = 0
-            
-            # PE比評估
-            pe_ratio = fundamental_data.get('pe_ratio')
-            if pe_ratio:
-                if pe_ratio < 15:
-                    fundamental_score += 8
-                    recommendations.append(f"✅ 本益比: {pe_ratio:.1f} (合理偏低)")
-                elif pe_ratio > 25:
-                    fundamental_score += 2
-                    recommendations.append(f"⚠️ 本益比: {pe_ratio:.1f} (偏高)")
-                else:
-                    fundamental_score += 5
-                    recommendations.append(f"✅ 本益比: {pe_ratio:.1f} (合理)")
-            
-            # ROE評估
-            roe = fundamental_data.get('roe')
-            if roe:
-                if roe > 0.15:
-                    fundamental_score += 8
-                    recommendations.append(f"✅ ROE: {roe*100:.1f}% (優秀)")
-                elif roe > 0.10:
-                    fundamental_score += 5
-                    recommendations.append(f"✅ ROE: {roe*100:.1f}% (良好)")
-                else:
-                    fundamental_score += 2
-                    recommendations.append(f"⚠️ ROE: {roe*100:.1f}% (偏低)")
-            
-            # 負債比評估
-            debt_ratio = fundamental_data.get('debt_to_equity')
-            if debt_ratio is not None:
-                if debt_ratio < 0.5:
-                    fundamental_score += 6
-                    recommendations.append(f"✅ 負債比: {debt_ratio:.2f} (健康)")
-                elif debt_ratio < 1.0:
-                    fundamental_score += 3
-                    recommendations.append(f"⚠️ 負債比: {debt_ratio:.2f} (適中)")
-                else:
-                    fundamental_score += 1
-                    recommendations.append(f"❌ 負債比: {debt_ratio:.2f} (偏高)")
-            
-            # 成長性評估
-            revenue_growth = fundamental_data.get('revenue_growth')
-            if revenue_growth:
-                if revenue_growth > 0.1:
-                    fundamental_score += 8
-                    recommendations.append(f"✅ 營收成長: {revenue_growth*100:.1f}% (強勁)")
-                elif revenue_growth > 0:
-                    fundamental_score += 5
-                    recommendations.append(f"✅ 營收成長: {revenue_growth*100:.1f}% (正成長)")
-                else:
-                    fundamental_score += 1
-                    recommendations.append(f"❌ 營收成長: {revenue_growth*100:.1f}% (負成長)")
-            
-            # 合理價位評估 (30%)
-            valuation_score = 0
-            if fair_value_data['fair_value'] and current_price:
-                upside = fair_value_data['upside_potential']
-                if upside > 20:
-                    valuation_score = 25
-                    recommendations.append(f"✅ 估值: 現價相對合理價位有{upside:.1f}%上漲空間")
-                elif upside > 0:
-                    valuation_score = 20
-                    recommendations.append(f"✅ 估值: 現價相對合理價位有{upside:.1f}%上漲空間")
-                elif upside > -10:
-                    valuation_score = 15
-                    recommendations.append(f"⚠️ 估值: 現價接近合理價位 ({upside:+.1f}%)")
-                else:
-                    valuation_score = 5
-                    recommendations.append(f"❌ 估值: 現價高於合理價位{abs(upside):.1f}%")
-            
-            overall_score = tech_score + fundamental_score + valuation_score
-            
-            # 生成最終建議
-            if overall_score >= 70:
-                final_recommendation = "🚀 強力買入"
-                action_color = "green"
-            elif overall_score >= 55:
-                final_recommendation = "✅ 買入"
-                action_color = "lightgreen"
-            elif overall_score >= 40:
-                final_recommendation = "⚠️ 觀望"
-                action_color = "orange"
-            elif overall_score >= 25:
-                final_recommendation = "❌ 避開"
-                action_color = "lightcoral"
-            else:
-                final_recommendation = "🔻 賣出"
-                action_color = "red"
-            
-            return {
-                'overall_score': overall_score,
-                'max_score': max_score,
-                'final_recommendation': final_recommendation,
-                'action_color': action_color,
-                'detailed_analysis': recommendations,
-                'fair_value': fair_value_data['fair_value'],
-                'upside_potential': fair_value_data['upside_potential']
-            }
-            
-        except Exception as e:
-            print(f"投資建議生成失敗 {symbol}: {str(e)}")
-            return {
-                'overall_score': 50,
-                'max_score': 100,
-                'final_recommendation': "⚠️ 資料不足",
-                'action_color': "gray",
-                'detailed_analysis': ["資料不足，無法提供完整分析"],
-                'fair_value': None,
-                'upside_potential': 0
-            }
-    
     def calculate_technical_indicators(self):
         """計算技術指標"""
         if self.data is None:
@@ -578,27 +343,20 @@ class StockAnalyzer:
         
         report = f"""
 ## 📊 {self.symbol} AI 分析報告
-
 ### 📈 技術面分析：
 {chr(10).join(f"• {signal}" for signal in technical_signals)}
-
 ### 💭 市場情感：{sentiment}
-
 ### 📊 近期表現：
 - 5日漲跌幅：{price_change:+.2f}%
 - 當前價位：${recent_data['Close'].iloc[-1]:.2f}
-
 ### 🤖 AI 預測機率（短期 1-7天）：
-
 | 方向 | 機率 | 說明 |
 |------|------|------|
 | 📈 **上漲** | **{probabilities['up']:.1f}%** | 股價向上突破的可能性 |
 | 📉 **下跌** | **{probabilities['down']:.1f}%** | 股價向下修正的可能性 |
 | ➡️ **盤整** | **{probabilities['sideways']:.1f}%** | 股價維持震盪的可能性 |
-
 ### 🎯 主要預測方向：
 {direction_emoji} **{main_direction}** ({confidence_desc} - {confidence*100:.0f}%)
-
 ### 📋 投資建議：
 """
         
@@ -620,15 +378,12 @@ class StockAnalyzer:
 - 🛡️ **風險管理**：小部位測試，嚴格執行停損"""
         
         report += f"""
-
 ### 📅 中期展望（1個月）：
 基於當前技術面和市場情緒分析，建議持續關注：
 - 關鍵技術位：支撐與阻力區間
 - 市場情緒變化：新聞面和資金流向
 - 整體大盤走勢：系統性風險評估
-
 ⚠️ **風險提醒**：此分析基於歷史數據和 AI 模型預測，僅供參考。投資有風險，請謹慎評估並做好風險管理！
-
 ---
 *預測信心度：{confidence*100:.0f}% | 分析時間：{datetime.now().strftime('%Y-%m-%d %H:%M')}*
 """
@@ -738,20 +493,18 @@ def create_results_table(results):
     # 創建表格 HTML
     table_html = """
 <div style="overflow-x: auto; margin: 20px 0;">
-<table style="width: 100%; border-collapse: collapse; font-family: Arial, sans-serif; font-size: 12px;">
+<table style="width: 100%; border-collapse: collapse; font-family: Arial, sans-serif;">
 <thead>
 <tr style="background-color: #f0f0f0;">
-<th style="border: 1px solid #ddd; padding: 8px; text-align: left;">代號</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: left;">名稱</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: right;">現價</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: right;">合理價</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: right;">上漲空間</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: right;">本益比</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: right;">ROE</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: right;">綜合評分</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: center;">投資建議</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: center;">技術面</th>
-<th style="border: 1px solid #ddd; padding: 8px; text-align: left;">狀態</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: left;">股票代號</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: left;">股票名稱</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: right;">當前價格</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: right;">上漲機率(%)</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: right;">下跌機率(%)</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: right;">盤整機率(%)</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: right;">信心度(%)</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: center;">預測方向</th>
+<th style="border: 1px solid #ddd; padding: 12px; text-align: left;">狀態</th>
 </tr>
 </thead>
 <tbody>
@@ -762,50 +515,34 @@ def create_results_table(results):
         if result['error_message']:
             direction = "❌ 錯誤"
             row_color = "#fff2f2"
-            tech_direction = "❌ 錯誤"
         else:
             up_prob = float(result['up_probability'])
             down_prob = float(result['down_probability'])
             sideways_prob = float(result['sideways_probability'])
             
-            # 技術面方向
             if up_prob > down_prob and up_prob > sideways_prob:
-                tech_direction = "📈 看多"
+                direction = "📈 看多"
+                row_color = "#f0fff0"  # 淡綠色
             elif down_prob > up_prob and down_prob > sideways_prob:
-                tech_direction = "📉 看空"
-            else:
-                tech_direction = "➡️ 盤整"
-            
-            # 根據投資建議決定背景顏色
-            recommendation = result.get('recommendation', '')
-            if '強力買入' in recommendation or '買入' in recommendation:
-                row_color = "#e8f5e8"  # 淡綠色
-            elif '觀望' in recommendation:
-                row_color = "#fff8dc"  # 淡黃色
-            elif '避開' in recommendation or '賣出' in recommendation:
-                row_color = "#ffe4e1"  # 淡紅色
+                direction = "📉 看空"
+                row_color = "#fff0f0"  # 淡紅色
             else:
+                direction = "➡️ 盤整"
                 row_color = "#f8f8f8"  # 淡灰色
         
-        status = "✅ 成功" if not result['error_message'] else f"❌ {result['error_message'][:20]}..."
-        
-        # 投資建議樣式
-        rec_color = result.get('recommendation_color', 'gray')
-        investment_rec = f"<span style='color: {rec_color}; font-weight: bold;'>{result.get('recommendation', 'N/A')}</span>"
+        status = "✅ 成功" if not result['error_message'] else f"❌ {result['error_message'][:30]}..."
         
         table_html += f"""
 <tr style="background-color: {row_color};">
-<td style="border: 1px solid #ddd; padding: 6px; font-weight: bold; font-size: 11px;">{result['symbol']}</td>
-<td style="border: 1px solid #ddd; padding: 6px; font-size: 11px;">{result['name'][:10]}{'...' if len(result['name']) > 10 else ''}</td>
-<td style="border: 1px solid #ddd; padding: 6px; text-align: right;">{result['current_price']}</td>
-<td style="border: 1px solid #ddd; padding: 6px; text-align: right;">{result.get('fair_value', 'N/A')}</td>
-<td style="border: 1px solid #ddd; padding: 6px; text-align: right;">{result.get('upside_potential', 'N/A')}</td>
-<td style="border: 1px solid #ddd; padding: 6px; text-align: right;">{result.get('pe_ratio', 'N/A')}</td>
-<td style="border: 1px solid #ddd; padding: 6px; text-align: right;">{result.get('roe', 'N/A')}</td>
-<td style="border: 1px solid #ddd; padding: 6px; text-align: right; font-weight: bold;">{result.get('investment_score', 'N/A')}</td>
-<td style="border: 1px solid #ddd; padding: 6px; text-align: center;">{investment_rec}</td>
-<td style="border: 1px solid #ddd; padding: 6px; text-align: center;">{tech_direction}</td>
-<td style="border: 1px solid #ddd; padding: 6px; font-size: 10px;">{status}</td>
+<td style="border: 1px solid #ddd; padding: 8px; font-weight: bold;">{result['symbol']}</td>
+<td style="border: 1px solid #ddd; padding: 8px;">{result['name']}</td>
+<td style="border: 1px solid #ddd; padding: 8px; text-align: right;">{result['current_price']}</td>
+<td style="border: 1px solid #ddd; padding: 8px; text-align: right;">{result['up_probability']}</td>
+<td style="border: 1px solid #ddd; padding: 8px; text-align: right;">{result['down_probability']}</td>
+<td style="border: 1px solid #ddd; padding: 8px; text-align: right;">{result['sideways_probability']}</td>
+<td style="border: 1px solid #ddd; padding: 8px; text-align: right;">{result['confidence']}</td>
+<td style="border: 1px solid #ddd; padding: 8px; text-align: center;">{direction}</td>
+<td style="border: 1px solid #ddd; padding: 8px;">{status}</td>
 </tr>
 """
     
@@ -817,81 +554,6 @@ def create_results_table(results):
     
     return table_html
 
-def create_detailed_analysis_report(results):
-    """創建詳細分析報告"""
-    if not results:
-        return ""
-    
-    # 過濾成功的結果
-    success_results = [r for r in results if r['error_message'] == '']
-    
-    if not success_results:
-        return "<p>沒有成功分析的股票可顯示詳細報告。</p>"
-    
-    report_html = """
-<div style="font-family: Arial, sans-serif; margin: 20px 0;">
-"""
-    
-    for result in success_results[:5]:  # 只顯示前5個成功的結果
-        symbol = result['symbol']
-        name = result['name']
-        recommendation = result.get('recommendation', 'N/A')
-        rec_color = result.get('recommendation_color', 'gray')
-        score = result.get('investment_score', 'N/A')
-        detailed_analysis = result.get('detailed_analysis', [])
-        
-        report_html += f"""
-<div style="border: 2px solid #ddd; border-radius: 10px; padding: 15px; margin: 15px 0; background-color: #fafafa;">
-    <h3 style="color: #333; margin: 0 0 10px 0;">
-        📈 {symbol} - {name}
-        <span style="float: right; color: {rec_color}; font-weight: bold;">{recommendation}</span>
-    </h3>
-    
-    <div style="background: linear-gradient(90deg, #f0f0f0 0%, #e0e0e0 {score}%, #f0f0f0 100%); 
-                border-radius: 5px; padding: 5px; margin: 10px 0;">
-        <strong>綜合評分: {score}/100</strong>
-    </div>
-    
-    <div style="display: grid; grid-template-columns: 1fr 1fr; gap: 15px; margin: 15px 0;">
-        <div>
-            <h4 style="color: #2e7d32; margin: 5px 0;">📊 基本資訊</h4>
-            <ul style="margin: 5px 0; padding-left: 20px;">
-                <li>現價: {result['current_price']}</li>
-                <li>合理價: {result.get('fair_value', 'N/A')}</li>
-                <li>上漲空間: {result.get('upside_potential', 'N/A')}</li>
-            </ul>
-        </div>
-        <div>
-            <h4 style="color: #1976d2; margin: 5px 0;">📈 財務指標</h4>
-            <ul style="margin: 5px 0; padding-left: 20px;">
-                <li>本益比: {result.get('pe_ratio', 'N/A')}</li>
-                <li>ROE: {result.get('roe', 'N/A')}</li>
-                <li>技術面: {result['up_probability']}%↑ {result['down_probability']}%↓</li>
-            </ul>
-        </div>
-    </div>
-    
-    <div>
-        <h4 style="color: #f57c00; margin: 10px 0 5px 0;">🔍 詳細分析</h4>
-        <ul style="margin: 0; padding-left: 20px; line-height: 1.6;">
-"""
-        
-        for analysis_point in detailed_analysis:
-            report_html += f"<li>{analysis_point}</li>"
-        
-        report_html += """
-        </ul>
-    </div>
-</div>
-"""
-    
-    if len(success_results) > 5:
-        report_html += f"<p style='text-align: center; color: #666;'>... 還有 {len(success_results) - 5} 支股票的詳細分析結果</p>"
-    
-    report_html += "</div>"
-    
-    return report_html
-
 def create_batch_analysis_charts(results):
     """創建批次分析結果圖表"""
     if not results:
@@ -1025,7 +687,7 @@ def batch_analyze_stocks(stock_input_text):
     """批次分析股票清單"""
     # 檢查輸入是否為空
     if not stock_input_text or not stock_input_text.strip():
-        return "❌ 請輸入股票代號！", "", None, None, None, None, "", ""
+        return "❌ 請輸入股票代號！", "", None, None, None, None, ""
     
     try:
         # 從文字輸入框解析股票清單
@@ -1035,7 +697,7 @@ def batch_analyze_stocks(stock_input_text):
         stock_symbols = [symbol.strip().upper() for symbol in stock_symbols if symbol.strip()]
         
         if not stock_symbols:
-            return "❌ 未能解析出有效的股票代號！", "", None, None, None, None, "", ""
+            return "❌ 未能解析出有效的股票代號！", "", None, None, None, None, ""
         
         # 準備結果列表
         results = []
@@ -1066,16 +728,8 @@ def batch_analyze_stocks(stock_input_text):
                         'down_probability': 'ERROR',
                         'sideways_probability': 'ERROR',
                         'confidence': 'ERROR',
-                        'fair_value': 'N/A',
-                        'upside_potential': 'N/A',
-                        'investment_score': 'N/A',
-                        'recommendation': '❌ 錯誤',
-                        'recommendation_color': 'red',
-                        'pe_ratio': 'N/A',
-                        'roe': 'N/A',
                         'analysis_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
-                        'error_message': message,
-                        'detailed_analysis': []
+                        'error_message': message
                     })
                     progress_messages.append(f"❌ {symbol}: {message}")
                     continue
@@ -1091,16 +745,8 @@ def batch_analyze_stocks(stock_input_text):
                         'down_probability': 'ERROR',
                         'sideways_probability': 'ERROR',
                         'confidence': 'ERROR',
-                        'fair_value': 'N/A',
-                        'upside_potential': 'N/A',
-                        'investment_score': 'N/A',
-                        'recommendation': '❌ 數據不足',
-                        'recommendation_color': 'red',
-                        'pe_ratio': 'N/A',
-                        'roe': 'N/A',
                         'analysis_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
-                        'error_message': '數據不足，無法分析',
-                        'detailed_analysis': []
+                        'error_message': '數據不足，無法分析'
                     })
                     progress_messages.append(f"❌ {symbol}: 數據不足")
                     continue
@@ -1126,38 +772,18 @@ def batch_analyze_stocks(stock_input_text):
                 
                 # 獲取股票資訊
                 stock_info = analyzer.get_stock_info(symbol)
-                current_price = latest['Close']
-                
-                # 獲取基本面數據
-                fundamental_data = analyzer.get_fundamental_data(symbol)
-                
-                # 計算合理價位
-                fair_value_data = analyzer.calculate_fair_value(symbol, fundamental_data, current_price)
-                
-                # 生成投資建議
-                investment_rec = analyzer.generate_investment_recommendation(
-                    symbol, current_price, probabilities, fair_value_data, fundamental_data
-                )
                 
                 # 記錄成功結果
                 results.append({
                     'symbol': symbol,
                     'name': stock_info['name'],
-                    'current_price': f"{current_price:.2f}" if current_price else 'N/A',
+                    'current_price': f"{latest['Close']:.2f}" if latest['Close'] else 'N/A',
                     'up_probability': f"{probabilities['up']:.1f}",
                     'down_probability': f"{probabilities['down']:.1f}",
                     'sideways_probability': f"{probabilities['sideways']:.1f}",
                     'confidence': f"{probabilities['confidence']*100:.1f}",
-                    'fair_value': f"{fair_value_data['fair_value']:.2f}" if fair_value_data['fair_value'] else 'N/A',
-                    'upside_potential': f"{fair_value_data['upside_potential']:+.1f}%" if fair_value_data['upside_potential'] else 'N/A',
-                    'investment_score': f"{investment_rec['overall_score']:.0f}",
-                    'recommendation': investment_rec['final_recommendation'],
-                    'recommendation_color': investment_rec['action_color'],
-                    'pe_ratio': f"{fundamental_data.get('pe_ratio', 0):.1f}" if fundamental_data.get('pe_ratio') else 'N/A',
-                    'roe': f"{fundamental_data.get('roe', 0)*100:.1f}%" if fundamental_data.get('roe') else 'N/A',
                     'analysis_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
-                    'error_message': '',
-                    'detailed_analysis': investment_rec['detailed_analysis']
+                    'error_message': ''
                 })
                 
                 progress_messages.append(f"✅ {symbol}: 分析完成")
@@ -1172,16 +798,8 @@ def batch_analyze_stocks(stock_input_text):
                     'down_probability': 'ERROR',
                     'sideways_probability': 'ERROR',
                     'confidence': 'ERROR',
-                    'fair_value': 'N/A',
-                    'upside_potential': 'N/A',
-                    'investment_score': 'N/A',
-                    'recommendation': '❌ 系統錯誤',
-                    'recommendation_color': 'red',
-                    'pe_ratio': 'N/A',
-                    'roe': 'N/A',
                     'analysis_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
-                    'error_message': f'未預期錯誤: {str(e)}',
-                    'detailed_analysis': []
+                    'error_message': f'未預期錯誤: {str(e)}'
                 })
                 progress_messages.append(f"❌ {symbol}: 未預期錯誤")
         
@@ -1191,18 +809,15 @@ def batch_analyze_stocks(stock_input_text):
         
         summary_message = f"""
 📈 批次分析完成！
-
 📊 **分析統計：**
 - 總計股票數：{len(stock_symbols)}
 - 成功分析：{success_count}
 - 分析失敗：{error_count}
-
 � **圖表已生成：**
 - 📊 機率比較柱狀圖
 - 🎯 信心度散佈圖
 - 📈 綜合評分雷達圖
 - 🥧 市場情緒餅圖
-
 🎯 **請查看下方圖表進行投資決策分析！**
 """
         
@@ -1211,12 +826,11 @@ def batch_analyze_stocks(stock_input_text):
         # 創建圖表和結果表格
         chart_bar, chart_scatter, chart_radar, chart_pie = create_batch_analysis_charts(results)
         results_table = create_results_table(results)
-        detailed_report = create_detailed_analysis_report(results)
         
-        return summary_message, progress_log, chart_bar, chart_scatter, chart_radar, chart_pie, results_table, detailed_report
+        return summary_message, progress_log, chart_bar, chart_scatter, chart_radar, chart_pie, results_table
         
     except Exception as e:
-        return f"❌ 批次分析過程中發生錯誤：{str(e)}", "", None, None, None, None, "", ""
+        return f"❌ 批次分析過程中發生錯誤：{str(e)}", "", None, None, None, None, ""
 
 # 創建 Gradio 界面
 with gr.Blocks(title="AI 股票分析師", theme=gr.themes.Soft()) as app:
@@ -1306,16 +920,12 @@ with gr.Blocks(title="AI 股票分析師", theme=gr.themes.Soft()) as app:
                     stock_input_batch = gr.Textbox(
                         label="📝 股票代號清單",
                         placeholder="""請輸入多個股票代號，支援多種分隔方式：
-
 • 換行分隔：
 2330.TW
 2317.TW
 1303.TW
-
 • 逗號分隔：2330.TW, 2317.TW, 1303.TW
-
 • 空格分隔：2330.TW 2317.TW 1303.TW
-
 • 混合分隔：2330.TW, 2317.TW
 1303.TW; AAPL TSLA""",
                         lines=8,
@@ -1373,12 +983,8 @@ with gr.Blocks(title="AI 股票分析師", theme=gr.themes.Soft()) as app:
                     chart_sentiment = gr.Plot(label="🥧 整體市場情緒分佈")
             
             # 詳細結果表格
-            gr.Markdown("## 📋 綜合分析結果")
-            results_table = gr.HTML(label="基本面 + 技術面綜合分析表格")
-            
-            # 詳細分析報告
-            gr.Markdown("## 📊 個股詳細分析")
-            detailed_analysis = gr.HTML(label="詳細投資分析報告")
+            gr.Markdown("## 📋 詳細分析結果")
+            results_table = gr.HTML(label="分析結果表格")
             
             # 快速範例按鈕事件綁定
             example_tw_btn.click(
@@ -1412,8 +1018,7 @@ with gr.Blocks(title="AI 股票分析師", theme=gr.themes.Soft()) as app:
                     chart_confidence, 
                     chart_radar, 
                     chart_sentiment,
-                    results_table,
-                    detailed_analysis
+                    results_table
                 ]
             )