Update app.py

app.py

@@ -8,6 +8,7 @@ from GoogleNews import GoogleNews
 from transformers import pipeline
 from datetime import datetime, timedelta
 import matplotlib
+import yfinance as yf
 matplotlib.use('Agg')
 
 # Set up logging
@@ -26,6 +27,24 @@ sentiment_analyzer = pipeline(
 )
 logging.info("Model initialized successfully")
 
+# 상장 종목 심볼 매핑을 위한 일반적인 종목명 사전 (필요에 따라 확장)
+COMMON_TICKERS = {
+    "apple": "AAPL",
+    "microsoft": "MSFT",
+    "amazon": "AMZN",
+    "google": "GOOGL",
+    "alphabet": "GOOGL",
+    "facebook": "META",
+    "meta": "META",
+    "tesla": "TSLA",
+    "nvidia": "NVDA",
+    "bitcoin": "BTC-USD",
+    "ethereum": "ETH-USD",
+    "samsung": "005930.KS",  # 한국 삼성전자
+    "hyundai": "005380.KS",  # 현대자동차
+    "sk hynix": "000660.KS",  # SK하이닉스
+}
+
 def fetch_articles(query, max_articles=30):
     try:
         logging.info(f"Fetching up to {max_articles} articles for query: '{query}'")
@@ -144,6 +163,84 @@ def calculate_sentiment_score(sentiment_label, time_weight):
     
     return base_score, weighted_addition
 
+def get_stock_ticker(asset_name):
+    """
+    자산명으로부터 주식 티커 심볼을 추출
+    """
+    # 소문자로 변환하여 매핑 확인
+    asset_lower = asset_name.lower()
+    
+    # 직접 티커로 입력한 경우 (대문자 3-5자 형태)
+    if asset_name.isupper() and 3 <= len(asset_name) <= 5:
+        return asset_name
+    
+    # 일반적인 종목명 매핑 확인
+    if asset_lower in COMMON_TICKERS:
+        return COMMON_TICKERS[asset_lower]
+    
+    # 그 외의 경우 yfinance로 검색 시도
+    try:
+        ticker_search = yf.Ticker(asset_name)
+        # 기본 정보 가져와서 유효한 티커인지 확인
+        info = ticker_search.info
+        if 'symbol' in info:
+            return info['symbol']
+    except:
+        pass
+    
+    return None
+
+def create_stock_chart(ticker, period="1mo"):
+    """
+    주식 티커에 대한 차트 생성
+    """
+    try:
+        logging.info(f"Fetching stock data for {ticker}")
+        stock_data = yf.download(ticker, period=period)
+        
+        if stock_data.empty:
+            logging.warning(f"No stock data found for ticker: {ticker}")
+            return None
+            
+        fig, ax = plt.subplots(figsize=(10, 6))
+        
+        # 종가 그래프
+        ax.plot(stock_data.index, stock_data['Close'], label='Close Price', color='blue')
+        
+        # 이동평균선 추가 (20일)
+        if len(stock_data) > 20:
+            stock_data['MA20'] = stock_data['Close'].rolling(window=20).mean()
+            ax.plot(stock_data.index, stock_data['MA20'], label='20-day MA', color='orange')
+        
+        # 거래량 서브플롯 추가
+        ax2 = ax.twinx()
+        ax2.bar(stock_data.index, stock_data['Volume'], alpha=0.3, color='gray', label='Volume')
+        ax2.set_ylabel('Volume')
+        
+        # 차트 스타일링
+        ax.set_title(f"{ticker} Stock Price")
+        ax.set_xlabel('Date')
+        ax.set_ylabel('Price')
+        ax.grid(True, alpha=0.3)
+        
+        # 범례 추가
+        lines, labels = ax.get_legend_handles_labels()
+        lines2, labels2 = ax2.get_legend_handles_labels()
+        ax.legend(lines + lines2, labels + labels2, loc='upper left')
+        
+        plt.tight_layout()
+        
+        # 이미지 저장
+        chart_path = f"stock_chart_{ticker.replace('-', '_')}.png"
+        plt.savefig(chart_path)
+        plt.close()
+        
+        logging.info(f"Stock chart created: {chart_path}")
+        return chart_path
+    except Exception as e:
+        logging.error(f"Error creating stock chart for {ticker}: {e}")
+        return None
+
 def analyze_asset_sentiment(asset_name):
     logging.info(f"Starting sentiment analysis for asset: {asset_name}")
     logging.info("Fetching up to 30 articles")
@@ -168,7 +265,14 @@ def analyze_asset_sentiment(asset_name):
     # 종합 점수 계산 및 그래프 생성
     sentiment_summary = create_sentiment_summary(analyzed_articles, asset_name)
     
-    return convert_to_dataframe(analyzed_articles), sentiment_summary
+    # 주식 티커 확인 및 차트 생성
+    stock_chart = None
+    ticker = get_stock_ticker(asset_name)
+    if ticker:
+        logging.info(f"Found ticker {ticker} for asset {asset_name}")
+        stock_chart = create_stock_chart(ticker)
+    
+    return convert_to_dataframe(analyzed_articles), sentiment_summary, stock_chart, ticker
 
 def create_sentiment_summary(analyzed_articles, asset_name):
     """
@@ -293,6 +397,15 @@ with gr.Blocks() as iface:
         inputs=input_asset,
     )
     
+    # 주식 차트 영역 추가
+    with gr.Row():
+        with gr.Column():
+            with gr.Blocks():
+                gr.Markdown("## Stock Chart")
+                with gr.Row():
+                    stock_chart = gr.Image(type="filepath", label="Stock Price Chart")
+                    ticker_info = gr.Textbox(label="Ticker Symbol")
+    
     with gr.Row():
         with gr.Column():
             with gr.Blocks():
@@ -312,7 +425,7 @@ with gr.Blocks() as iface:
     analyze_button.click(
         analyze_asset_sentiment,
         inputs=[input_asset],
-        outputs=[articles_output, sentiment_summary],
+        outputs=[articles_output, sentiment_summary, stock_chart, ticker_info],
     )
 
 logging.info("Launching Gradio interface")