Update app.py

app.py

@@ -1,156 +1,156 @@
-import streamlit as st
-import yfinance as yf
-import plotly.graph_objs as go
-from plotly.subplots import make_subplots
-from crew import crew_creator
-from dotenv import load_dotenv
-load_dotenv()
-
-st.set_page_config(layout="wide", page_title="Finance Agent", initial_sidebar_state="expanded")
-st.sidebar.markdown('<p class="medium-font">Configuration</p>', unsafe_allow_html=True)
-
-st.markdown("""
-<div class="analysis-card">
-    <h2 class="analysis-title">AI-Agents Finance Analyst Platform</h2>
-    <p class="analysis-content">
-        Welcome to my cutting-edge stock analysis platform, leveraging Artificial Intelligence and Large Language Models (LLMs) to deliver professional-grade investment insights. Our system offers:
-    </p>
-     <ul class="analysis-list">
-        <li class="analysis-list-item">Comprehensive Data Analysis on stocks, and investing.</li>
-        <li class="analysis-list-item">In-depth fundamental and technical analyses</li>
-        <li class="analysis-list-item">Extensive web and news research integration</li>
-        <li class="analysis-list-item">Customizable analysis parameters including time frames and specific indicators</li>
-    </ul>
-    <p class="analysis-content">
-        Users can obtain a detailed, AI-generated analysis report by simply selecting a stock symbol, specifying a time period, and choosing desired analysis indicators. This platform aims to empower investors with data-driven, AI-enhanced decision-making tools for the complex world of stock market investments.
-    </p>
-    <p class="analysis-content">
-        Please note, this analysis is for informational purposes only and should not be construed as financial or investment advice.
-</div>
-""", unsafe_allow_html=True)
-
-stock_symbol = st.sidebar.text_input("Enter Stock Symbol", value="NVDA", placeholder="META, AAPL, NVDA")
-time_period = st.sidebar.selectbox("Select Time Period", ['1mo', '3mo', '6mo', '1y', '2y', '5y', 'max'])
-indicators = st.sidebar.multiselect("Select Indicators", ['Moving Averages', 'Volume', 'RSI', 'MACD'])
-analyze_button = st.sidebar.button("📊 Analyze Stock", help="Click to start the stock analysis")
-
-# Initialize session state
-if 'analyzed' not in st.session_state:
-    st.session_state.analyzed = False
-    st.session_state.stock_info = None
-    st.session_state.stock_data = None
-    st.session_state.result_file_path = None
-
-def get_stock_data(stock_symbol, period='1y'):
-    return yf.download(stock_symbol, period=period)
-
-def plot_stock_chart(stock_data, indicators):
-    fig = make_subplots(rows=3, cols=1, shared_xaxes=True, vertical_spacing=0.05, row_heights=[0.6, 0.2, 0.2])
-
-    # Main price chart
-    fig.add_trace(go.Candlestick(x=stock_data.index,
-                                 open=stock_data['Open'],
-                                 high=stock_data['High'],
-                                 low=stock_data['Low'],
-                                 close=stock_data['Close'],
-                                 name='Price'),
-                  row=1, col=1)
-
-    # Add selected indicators
-    if 'Moving Averages' in indicators:
-        fig.add_trace(go.Scatter(x=stock_data.index, y=stock_data['Close'].rolling(window=50).mean(), name='50 MA', line=dict(color='orange')), row=1, col=1)
-        fig.add_trace(go.Scatter(x=stock_data.index, y=stock_data['Close'].rolling(window=200).mean(), name='200 MA', line=dict(color='red')), row=1, col=1)
-
-    if 'Volume' in indicators:
-        fig.add_trace(go.Bar(x=stock_data.index, y=stock_data['Volume'], name='Volume'), row=2, col=1)
-
-    if 'RSI' in indicators:
-        delta = stock_data['Close'].diff()
-        gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
-        loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
-        rs = gain / loss
-        rsi = 100 - (100 / (1 + rs))
-        fig.add_trace(go.Scatter(x=stock_data.index, y=rsi, name='RSI'), row=3, col=1)
-
-    if 'MACD' in indicators:
-        ema12 = stock_data['Close'].ewm(span=12, adjust=False).mean()
-        ema26 = stock_data['Close'].ewm(span=26, adjust=False).mean()
-        macd = ema12 - ema26
-        signal = macd.ewm(span=9, adjust=False).mean()
-        fig.add_trace(go.Scatter(x=stock_data.index, y=macd, name='MACD'), row=3, col=1)
-        fig.add_trace(go.Scatter(x=stock_data.index, y=signal, name='Signal'), row=3, col=1)
-
-    fig.update_layout(
-        title='Stock Analysis',
-        yaxis_title='Price',
-        xaxis_rangeslider_visible=False,
-        height=800,
-        showlegend=True
-    )
-
-    fig.update_xaxes(
-        rangeselector=dict(
-            buttons=list([
-                dict(count=1, label="1m", step="month", stepmode="backward"),
-                dict(count=6, label="6m", step="month", stepmode="backward"),
-                dict(count=1, label="YTD", step="year", stepmode="todate"),
-                dict(count=1, label="1y", step="year", stepmode="backward"),
-                dict(step="all")
-            ])
-        ),
-        rangeslider=dict(visible=False),
-        type="date"
-    )
-
-    return fig
-
-if analyze_button:
-    st.session_state.analyzed = False  # Reset analyzed state
-    st.snow()
-
-    # Fetch stock info and data
-    with st.spinner(f"Fetching data for {stock_symbol}..."):
-        stock = yf.Ticker(stock_symbol)
-        st.session_state.stock_info = stock.info
-        st.session_state.stock_data = get_stock_data(stock_symbol, period=time_period)
-
-    # Create and run the crew
-    with st.spinner("Running analysis, please wait..."):
-        
-        st.session_state.result_file_path = crew_creator(stock_symbol)
-    
-    st.session_state.analyzed = True
-
-# Display stock info if available
-if st.session_state.stock_info:
-    st.markdown('<p class="medium-font">Stock Information</p>', unsafe_allow_html=True)
-    info = st.session_state.stock_info
-    col1, col2, col3 = st.columns(3)
-    with col1:
-        st.markdown(f"**Company Name:** {info.get('longName', 'N/A')}")
-        st.markdown(f"**Sector:** {info.get('sector', 'N/A')}")
-    with col2:
-        st.markdown(f"**Industry:** {info.get('industry', 'N/A')}")
-        st.markdown(f"**Country:** {info.get('country', 'N/A')}")
-    with col3:
-        st.markdown(f"**Current Price:** ${info.get('currentPrice', 'N/A')}")
-        st.markdown(f"**Market Cap:** ${info.get('marketCap', 'N/A')}")
-
-# Display CrewAI result if available
-if st.session_state.result_file_path:
-    st.markdown('<p class="medium-font">Analysis Result</p>', unsafe_allow_html=True)
-        
-    # with open(st.session_state.result_file_path, 'r') as file:
-    #     result = file.read()
-    st.markdown("---")
-
-    st.markdown(st.session_state.result_file_path)
-
-# Display chart
-if st.session_state.analyzed and st.session_state.stock_data is not None:
-    st.markdown('<p class="medium-font">Interactive Stock Chart</p>', unsafe_allow_html=True)
-    st.plotly_chart(plot_stock_chart(st.session_state.stock_data, indicators), use_container_width=True)
-
-
-st.markdown("---")
+import streamlit as st
+import yfinance as yf
+import plotly.graph_objs as go
+from plotly.subplots import make_subplots
+from crew import crew_creator
+from dotenv import load_dotenv
+load_dotenv()
+
+st.set_page_config(layout="wide", page_title="Finance Agent", initial_sidebar_state="expanded")
+st.sidebar.markdown('<p class="medium-font">Configuration</p>', unsafe_allow_html=True)
+
+st.markdown("""
+<div class="analysis-card">
+    <h2 class="analysis-title">AI-Agents Finance Analyst Platform</h2>
+    <p class="analysis-content">
+        Welcome to my cutting-edge stock analysis platform, leveraging Artificial Intelligence and Large Language Models (LLMs) to deliver professional-grade investment insights. Our system offers:
+    </p>
+     <ul class="analysis-list">
+        <li class="analysis-list-item">Comprehensive Data Analysis on stocks, and investing.</li>
+        <li class="analysis-list-item">In-depth fundamental and technical analyses</li>
+        <li class="analysis-list-item">Extensive web and news research integration</li>
+        <li class="analysis-list-item">Customizable analysis parameters including time frames and specific indicators</li>
+    </ul>
+    <p class="analysis-content">
+        Users can obtain a detailed, AI-generated analysis report by simply selecting a stock symbol, specifying a time period, and choosing desired analysis indicators. This platform aims to empower investors with data-driven, AI-enhanced decision-making tools for the complex world of stock market investments.
+    </p>
+    <p class="analysis-content">
+        Please note, this analysis is for informational purposes only and should not be construed as financial or investment advice.
+</div>
+""", unsafe_allow_html=True)
+
+stock_symbol = st.sidebar.text_input("Enter Stock Symbol", value="META", placeholder="META, AAPL, NVDA")
+time_period = st.sidebar.selectbox("Select Time Period", ['1mo', '3mo', '6mo', '1y', '2y', '5y', 'max'])
+indicators = st.sidebar.multiselect("Select Indicators", ['Moving Averages', 'Volume', 'RSI', 'MACD'])
+analyze_button = st.sidebar.button("📊 Analyze Stock", help="Click to start the stock analysis")
+
+# Initialize session state
+if 'analyzed' not in st.session_state:
+    st.session_state.analyzed = False
+    st.session_state.stock_info = None
+    st.session_state.stock_data = None
+    st.session_state.result_file_path = None
+
+def get_stock_data(stock_symbol, period='1y'):
+    return yf.download(stock_symbol, period=period)
+
+def plot_stock_chart(stock_data, indicators):
+    fig = make_subplots(rows=3, cols=1, shared_xaxes=True, vertical_spacing=0.05, row_heights=[0.6, 0.2, 0.2])
+
+    # Main price chart
+    fig.add_trace(go.Candlestick(x=stock_data.index,
+                                 open=stock_data['Open'],
+                                 high=stock_data['High'],
+                                 low=stock_data['Low'],
+                                 close=stock_data['Close'],
+                                 name='Price'),
+                  row=1, col=1)
+
+    # Add selected indicators
+    if 'Moving Averages' in indicators:
+        fig.add_trace(go.Scatter(x=stock_data.index, y=stock_data['Close'].rolling(window=50).mean(), name='50 MA', line=dict(color='orange')), row=1, col=1)
+        fig.add_trace(go.Scatter(x=stock_data.index, y=stock_data['Close'].rolling(window=200).mean(), name='200 MA', line=dict(color='red')), row=1, col=1)
+
+    if 'Volume' in indicators:
+        fig.add_trace(go.Bar(x=stock_data.index, y=stock_data['Volume'], name='Volume'), row=2, col=1)
+
+    if 'RSI' in indicators:
+        delta = stock_data['Close'].diff()
+        gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
+        loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
+        rs = gain / loss
+        rsi = 100 - (100 / (1 + rs))
+        fig.add_trace(go.Scatter(x=stock_data.index, y=rsi, name='RSI'), row=3, col=1)
+
+    if 'MACD' in indicators:
+        ema12 = stock_data['Close'].ewm(span=12, adjust=False).mean()
+        ema26 = stock_data['Close'].ewm(span=26, adjust=False).mean()
+        macd = ema12 - ema26
+        signal = macd.ewm(span=9, adjust=False).mean()
+        fig.add_trace(go.Scatter(x=stock_data.index, y=macd, name='MACD'), row=3, col=1)
+        fig.add_trace(go.Scatter(x=stock_data.index, y=signal, name='Signal'), row=3, col=1)
+
+    fig.update_layout(
+        title='Stock Analysis',
+        yaxis_title='Price',
+        xaxis_rangeslider_visible=False,
+        height=800,
+        showlegend=True
+    )
+
+    fig.update_xaxes(
+        rangeselector=dict(
+            buttons=list([
+                dict(count=1, label="1m", step="month", stepmode="backward"),
+                dict(count=6, label="6m", step="month", stepmode="backward"),
+                dict(count=1, label="YTD", step="year", stepmode="todate"),
+                dict(count=1, label="1y", step="year", stepmode="backward"),
+                dict(step="all")
+            ])
+        ),
+        rangeslider=dict(visible=False),
+        type="date"
+    )
+
+    return fig
+
+if analyze_button:
+    st.session_state.analyzed = False  # Reset analyzed state
+    st.snow()
+
+    # Fetch stock info and data
+    with st.spinner(f"Fetching data for {stock_symbol}..."):
+        stock = yf.Ticker(stock_symbol)
+        st.session_state.stock_info = stock.info
+        st.session_state.stock_data = get_stock_data(stock_symbol, period=time_period)
+
+    # Create and run the crew
+    with st.spinner("Running analysis, please wait..."):
+        
+        st.session_state.result_file_path = crew_creator(stock_symbol)
+    
+    st.session_state.analyzed = True
+
+# Display stock info if available
+if st.session_state.stock_info:
+    st.markdown('<p class="medium-font">Stock Information</p>', unsafe_allow_html=True)
+    info = st.session_state.stock_info
+    col1, col2, col3 = st.columns(3)
+    with col1:
+        st.markdown(f"**Company Name:** {info.get('longName', 'N/A')}")
+        st.markdown(f"**Sector:** {info.get('sector', 'N/A')}")
+    with col2:
+        st.markdown(f"**Industry:** {info.get('industry', 'N/A')}")
+        st.markdown(f"**Country:** {info.get('country', 'N/A')}")
+    with col3:
+        st.markdown(f"**Current Price:** ${info.get('currentPrice', 'N/A')}")
+        st.markdown(f"**Market Cap:** ${info.get('marketCap', 'N/A')}")
+
+# Display CrewAI result if available
+if st.session_state.result_file_path:
+    st.markdown('<p class="medium-font">Analysis Result</p>', unsafe_allow_html=True)
+        
+    # with open(st.session_state.result_file_path, 'r') as file:
+    #     result = file.read()
+    st.markdown("---")
+
+    st.markdown(st.session_state.result_file_path)
+
+# Display chart
+if st.session_state.analyzed and st.session_state.stock_data is not None:
+    st.markdown('<p class="medium-font">Interactive Stock Chart</p>', unsafe_allow_html=True)
+    st.plotly_chart(plot_stock_chart(st.session_state.stock_data, indicators), use_container_width=True)
+
+
+st.markdown("---")
 st.markdown('<p class="small-font">Crafted by base234 </p>', unsafe_allow_html=True)