Update indicators.py

indicators.py

@@ -2,7 +2,7 @@ import pandas as pd
 import pandas_ta as ta
 import plotly.graph_objects as go
 import streamlit as st
-from ai_insights import get_ai_insight  # Import AI insight function
+from ai_insights import get_ai_insight
 
 def calculate_indicators(data, ma_window, rsi_window, macd_fast, macd_slow, macd_signal):
     """
@@ -21,27 +21,27 @@ def calculate_indicators(data, ma_window, rsi_window, macd_fast, macd_slow, macd
         pandas.DataFrame: Data with calculated indicators.
     """
 
-    # 📌 **Calculate Moving Average (MA)**
+    # Calculate Moving Average (MA)
     data['MA'] = data['Close'].rolling(window=ma_window).mean()
 
-    # 📌 **Calculate Bollinger Bands**
+    # Calculate Bollinger Bands
     data['stddev'] = data['Close'].rolling(window=ma_window).std()
     data['Upper_BB'] = data['MA'] + (2 * data['stddev'])
     data['Lower_BB'] = data['MA'] - (2 * data['stddev'])
 
-    # 📌 **Calculate RSI**
+    # Calculate RSI
     delta = data['Close'].diff(1)
     gain = (delta.where(delta > 0, 0)).rolling(window=rsi_window).mean()
     loss = (-delta.where(delta < 0, 0)).rolling(window=rsi_window).mean()
     rs = gain / loss
     data['RSI'] = 100 - (100 / (1 + rs))
 
-    # 📌 **Calculate MACD**
+    # Calculate MACD
     data['MACD'] = data['Close'].ewm(span=macd_fast, adjust=False).mean() - data['Close'].ewm(span=macd_slow, adjust=False).mean()
     data['MACD_Signal'] = data['MACD'].ewm(span=macd_signal, adjust=False).mean()
     data['MACD_Hist'] = data['MACD'] - data['MACD_Signal']
 
-    # 📌 **Create Candlestick Chart with Bollinger Bands & MA**
+    # Create Candlestick Chart with Bollinger Bands & MA
     fig_candlestick = go.Figure()
     fig_candlestick.add_trace(go.Candlestick(
         x=data.index,
@@ -56,56 +56,31 @@ def calculate_indicators(data, ma_window, rsi_window, macd_fast, macd_slow, macd
     fig_candlestick.add_trace(go.Scatter(x=data.index, y=data['Lower_BB'], mode='lines', name="Lower BB", line=dict(color="purple", dash='dot')))
     fig_candlestick.update_layout(title="📈 Stock Price with Bollinger Bands & MA", xaxis_rangeslider_visible=True, template="plotly_dark", height=500, width=900)
 
-    # 📌 **Create RSI Chart**
+    # Create RSI Chart
     fig_rsi = go.Figure()
     fig_rsi.add_trace(go.Scatter(x=data.index, y=data['RSI'], mode='lines', name="RSI", line=dict(color="orange")))
     fig_rsi.add_trace(go.Scatter(x=data.index, y=[70]*len(data), mode='lines', name="Overbought (70)", line=dict(color="red", dash='dash')))
     fig_rsi.add_trace(go.Scatter(x=data.index, y=[30]*len(data), mode='lines', name="Oversold (30)", line=dict(color="green", dash='dash')))
     fig_rsi.update_layout(title="📊 Relative Strength Index (RSI)", xaxis_rangeslider_visible=False, template="plotly_dark", height=500, width=900)
 
-    # 📌 **Create MACD Chart**
+    # Create MACD Chart
     fig_macd = go.Figure()
     fig_macd.add_trace(go.Scatter(x=data.index, y=data['MACD'], mode='lines', name="MACD", line=dict(color="blue")))
     fig_macd.add_trace(go.Scatter(x=data.index, y=data['MACD_Signal'], mode='lines', name="MACD Signal", line=dict(color="red")))
     fig_macd.add_trace(go.Bar(x=data.index, y=data['MACD_Hist'], name="MACD Histogram", marker_color="purple"))
     fig_macd.update_layout(title="📉 MACD Indicator", xaxis_rangeslider_visible=False, template="plotly_dark", height=500, width=900)
 
-    # 📌 **Display Charts One Below Another**
+    # Display Charts One Below Another**
     st.subheader("📈 Stock Price with Bollinger Bands & Moving Averages")
-    st.plotly_chart(fig_candlestick, use_container_width=True)  # 📊 Stock Chart
+    st.plotly_chart(fig_candlestick, use_container_width=True)  # Stock Chart
 
     st.subheader("📊 Relative Strength Index (RSI)")
-    st.plotly_chart(fig_rsi, use_container_width=True)  # 📊 RSI Chart
+    st.plotly_chart(fig_rsi, use_container_width=True)  # RSI Chart
 
     st.subheader("📉 MACD Indicator")
-    st.plotly_chart(fig_macd, use_container_width=True)  # 📉 MACD Chart
+    st.plotly_chart(fig_macd, use_container_width=True)  # MACD Chart
 
 
     print(data.columns)
 
-    '''
-    # 📌 **Display Charts and AI Insights in a 2x2 Grid**
-    col1, col2 = st.columns((7, 1.5))  # 2/3 chart, 1/3 AI insight
-    with col1:
-        st.plotly_chart(fig_candlestick, use_container_width=True)  # 📈 Stock Price
-    with col2:
-        st.subheader("💡 AI Insight for Moving Average")
-        st.write(ma_insight)
-        st.subheader("💡 AI Insight for Bollinger Bands")
-        st.write(bb_insight)
-
-    col3, col4 = st.columns((7, 1.5))
-    with col3:
-        st.plotly_chart(fig_rsi, use_container_width=True)  # 📊 RSI
-    with col4:
-        st.subheader("💡 AI Insight for RSI")
-        st.write(rsi_insight)
-
-    col5, col6 = st.columns((7, 1.5))
-    with col5:
-        st.plotly_chart(fig_macd, use_container_width=True)  # 📉 MACD
-    with col6:
-        st.subheader("💡 AI Insight for MACD")
-        st.write(macd_insight)
-    '''
-    return data  # ✅ Return only data, all charts & AI insights are displayed in Streamlit
+    return data