Initial commit

app.py

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+import gradio as gr
+import yfinance as yf
+import pandas as pd
+import plotly.graph_objects as go
+from prophet import Prophet
+
+def analyze_stock(ticker):
+    stock = yf.Ticker(ticker)
+    hist = stock.history(period="1y")
+    if hist.empty:
+        return "股票代码无效，请检查后重试（示例：AAPL, TSLA, 600036.SS）", None, None
+    
+    fig = go.Figure(data=[go.Candlestick(x=hist.index,
+                open=hist['Open'],
+                high=hist['High'],
+                low=hist['Low'],
+                close=hist['Close'])])
+    fig.update_layout(title=f"{ticker} 股票K线图", xaxis_title="日期", yaxis_title="价格")
+    
+    df = hist[['Close']].reset_index()
+    df.columns = ['ds', 'y']
+    model = Prophet(daily_seasonality=True)
+    model.fit(df)
+    future = model.make_future_dataframe(periods=7)
+    forecast = model.predict(future)
+    
+    fig2 = go.Figure()
+    fig2.add_trace(go.Scatter(x=df['ds'], y=df['y'], mode='lines', name='历史价格'))
+    fig2.add_trace(go.Scatter(x=forecast['ds'], y=forecast['yhat'], mode='lines', name='预测价格'))
+    fig2.update_layout(title=f"{ticker} 7天价格预测", xaxis_title="日期", yaxis_title="价格")
+    
+    hist['MA20'] = hist['Close'].rolling(20).mean()
+    current_price = hist['Close'].iloc[-1]
+    ma20 = hist['MA20'].iloc[-1]
+    signal = "📈 看涨" if current_price > ma20 else "📉 看跌"
+    
+    result_text = f"当前价格: ${current_price:.2f}\n20日均线: ${ma20:.2f}\n信号: {signal}"
+    return result_text, fig, fig2
+
+with gr.Blocks(title="股票AI分析") as demo:
+    gr.Markdown("# 📈 股票AI分析系统")
+    gr.Markdown("输入股票代码（美股直接输入，A股加.SS后缀，如`600036.SS`）")
+    
+    ticker_input = gr.Textbox(label="股票代码", value="AAPL")
+    analyze_btn = gr.Button("分析", variant="primary")
+    
+    signal_output = gr.Textbox(label="分析结果")
+    kchart = gr.Plot(label="K线图")
+    pred_chart = gr.Plot(label="价格预测")
+    
+    gr.Markdown("### 示例代码:\n- 美股: `AAPL`, `TSLA`, `GOOGL`\n- A股: `600036.SS`, `000001.SZ`\n- 港股: `00700.HK`")
+    
+    analyze_btn.click(
+        fn=analyze_stock,
+        inputs=ticker_input,
+        outputs=[signal_output, kchart, pred_chart]
+    )
+
+demo.launch()

requirements.txt

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+gradio==4.19.1
+yfinance==0.2.28
+pandas==2.1.4
+numpy==1.26.3
+plotly==5.19.0
+prophet==1.1.5