| import streamlit as st
|
| import pandas as pd
|
| import plotly.graph_objects as go
|
| import plotly.express as px
|
| from datetime import datetime, timedelta
|
| from phi.agent.agent import Agent
|
| from phi.model.groq import Groq
|
| from phi.tools.yfinance import YFinanceTools
|
| from phi.tools.duckduckgo import DuckDuckGo
|
| from phi.tools.googlesearch import GoogleSearch
|
| import yfinance as yf
|
|
|
| import os
|
| from dotenv import load_dotenv
|
|
|
|
|
| load_dotenv()
|
|
|
|
|
| GROQ_API_KEY = os.getenv("GROQ_API_KEY")
|
|
|
|
|
| if not GROQ_API_KEY:
|
| st.error("GROQ_API_KEY not found. Please check your .env file.")
|
|
|
|
|
| COMMON_STOCKS = {
|
|
|
| 'NVIDIA': 'NVDA',
|
| 'APPLE': 'AAPL',
|
| 'GOOGLE': 'GOOGL',
|
| 'MICROSOFT': 'MSFT',
|
| 'TESLA': 'TSLA',
|
| 'AMAZON': 'AMZN',
|
| 'META': 'META',
|
| 'NETFLIX': 'NFLX',
|
|
|
| 'TCS': 'TCS.NS',
|
| 'RELIANCE': 'RELIANCE.NS',
|
| 'INFOSYS': 'INFY.NS',
|
| 'WIPRO': 'WIPRO.NS',
|
| 'HDFC': 'HDFCBANK.NS',
|
| 'TATAMOTORS': 'TATAMOTORS.NS',
|
| 'ICICIBANK': 'ICICIBANK.NS',
|
| 'SBIN': 'SBIN.NS',
|
| 'MARUTI': 'MARUTI.NS',
|
| 'BHARTIARTL': 'BHARTIARTL.NS',
|
| 'HCLTECH': 'HCLTECH.NS',
|
| 'ITC': 'ITC.NS',
|
| 'AXISBANK': 'AXISBANK.NS'
|
| }
|
|
|
|
|
| st.set_page_config(
|
| page_title="Advanced Stock Market Analysis",
|
| page_icon="📈",
|
| layout="wide",
|
| initial_sidebar_state="expanded"
|
| )
|
|
|
|
|
| st.markdown("""
|
| <style>
|
| .main {
|
| padding: 2rem;
|
| }
|
| .stApp {
|
| max-width: 1400px;
|
| margin: 0 auto;
|
| }
|
| .metric-card {
|
| background-color: #f8f9fa;
|
| border-radius: 10px;
|
| padding: 1rem;
|
| margin: 0.5rem 0;
|
| box-shadow: 0 2px 4px rgba(0,0,0,0.1);
|
| transition: transform 0.2s;
|
| }
|
| .metric-card:hover {
|
| transform: translateY(-2px);
|
| box-shadow: 0 4px 6px rgba(0,0,0,0.1);
|
| }
|
| .stock-header {
|
| font-size: 28px;
|
| font-weight: bold;
|
| margin-bottom: 20px;
|
| color: #f4e285;
|
| text-align: center;
|
| padding: 1rem;
|
| background: #1a1f36;
|
| border-radius: 10px;
|
| }
|
| .news-card {
|
| background-color: white;
|
| padding: 1rem;
|
| border-radius: 5px;
|
| margin: 10px 0;
|
| border-left: 4px solid #1f77b4;
|
| transition: transform 0.2s;
|
| }
|
| .news-card:hover {
|
| transform: translateX(5px);
|
| }
|
| .stButton>button {
|
| width: 100%;
|
| }
|
| .market-indicator {
|
| font-size: 16px;
|
| color: #666;
|
| text-align: center;
|
| margin-bottom: 1rem;
|
| }
|
| </style>
|
| """, unsafe_allow_html=True)
|
|
|
|
|
| if 'agents_initialized' not in st.session_state:
|
| st.session_state.agents_initialized = False
|
| st.session_state.watchlist = set()
|
| st.session_state.analysis_history = []
|
| st.session_state.last_refresh = None
|
|
|
| def initialize_agents():
|
| """Initialize all agent instances with improved error handling"""
|
| if not st.session_state.agents_initialized:
|
| try:
|
| st.session_state.web_agent = Agent(
|
| name="Web Search Agent",
|
| role="Search the web for the information",
|
| model=Groq(api_key=GROQ_API_KEY,
|
| id="llama-3.3-70b-versatile"),
|
| tools=[
|
| GoogleSearch(fixed_language='english', fixed_max_results=5)
|
|
|
| ],
|
| instructions=['Always include sources and verification'],
|
| show_tool_calls=True,
|
| markdown=True
|
| )
|
|
|
| st.session_state.finance_agent = Agent(
|
| name="Financial AI Agent",
|
| role="Providing financial insights",
|
| model=Groq(api_key=GROQ_API_KEY,
|
| id="llama-3.3-70b-versatile"),
|
| tools=[
|
| YFinanceTools(
|
| stock_price=True,
|
| company_news=True,
|
| analyst_recommendations=True,
|
| historical_prices=True
|
| )
|
| ],
|
| instructions=["Provide detailed analysis with data visualization"],
|
| show_tool_calls=True,
|
| markdown=True
|
| )
|
|
|
| st.session_state.multi_ai_agent = Agent(
|
| name='A Stock Market Agent',
|
| role='A comprehensive assistant specializing in stock market analysis',
|
| model=Groq(api_key=GROQ_API_KEY,
|
| id="llama-3.3-70b-versatile"),
|
| team=[st.session_state.web_agent, st.session_state.finance_agent],
|
| instructions=["Provide comprehensive analysis with multiple data sources"],
|
| show_tool_calls=True,
|
| markdown=True
|
| )
|
|
|
| st.session_state.agents_initialized = True
|
| return True
|
| except Exception as e:
|
| st.error(f"Error initializing agents: {str(e)}")
|
| return False
|
|
|
| def get_symbol_from_name(stock_name):
|
| """Enhanced function to fetch stock symbol from full stock name"""
|
| try:
|
|
|
| stock_name = stock_name.strip().upper()
|
|
|
|
|
| if stock_name in COMMON_STOCKS:
|
| return COMMON_STOCKS[stock_name]
|
|
|
|
|
| ticker = yf.Ticker(stock_name)
|
| try:
|
| info = ticker.info
|
| if info and 'symbol' in info:
|
| return stock_name
|
| except:
|
| pass
|
|
|
|
|
| try:
|
| indian_symbol = f"{stock_name}.NS"
|
| ticker = yf.Ticker(indian_symbol)
|
| info = ticker.info
|
| if info and 'symbol' in info:
|
| return indian_symbol
|
| except:
|
|
|
| try:
|
| bse_symbol = f"{stock_name}.BO"
|
| ticker = yf.Ticker(bse_symbol)
|
| info = ticker.info
|
| if info and 'symbol' in info:
|
| return bse_symbol
|
| except:
|
| pass
|
|
|
| st.error(f"Could not find valid symbol for {stock_name}")
|
| return None
|
| except Exception as e:
|
| st.error(f"Error processing {stock_name}: {str(e)}")
|
| return None
|
|
|
| def get_stock_data(symbol, period="1y"):
|
| """Enhanced function to fetch stock data with proper cache handling"""
|
| try:
|
|
|
| stock = yf.Ticker(symbol)
|
|
|
|
|
| try:
|
| info = stock.info
|
| if not info:
|
| raise ValueError("No data retrieved for symbol")
|
| except Exception as info_error:
|
|
|
| if not symbol.endswith('.NS') and not symbol.endswith('.BO'):
|
| try:
|
| indian_symbol = f"{symbol}.NS"
|
| stock = yf.Ticker(indian_symbol)
|
| info = stock.info
|
| symbol = indian_symbol
|
| except:
|
|
|
| try:
|
| bse_symbol = f"{symbol}.BO"
|
| stock = yf.Ticker(bse_symbol)
|
| info = stock.info
|
| symbol = bse_symbol
|
| except:
|
| raise info_error
|
| else:
|
| raise info_error
|
|
|
|
|
| hist = stock.history(period=period, interval="1d", auto_adjust=True)
|
|
|
| if hist.empty:
|
| raise ValueError("No historical data available")
|
|
|
| return info, hist
|
| except Exception as e:
|
| st.error(f"Error fetching data for {symbol}: {str(e)}")
|
| return None, None
|
|
|
| def create_price_chart(hist_data, symbol):
|
| """Create an interactive price chart using plotly"""
|
| fig = go.Figure()
|
|
|
|
|
| fig.add_trace(go.Candlestick(
|
| x=hist_data.index,
|
| open=hist_data['Open'],
|
| high=hist_data['High'],
|
| low=hist_data['Low'],
|
| close=hist_data['Close'],
|
| name='Price'
|
| ))
|
|
|
|
|
| ma20 = hist_data['Close'].rolling(window=20).mean()
|
| ma50 = hist_data['Close'].rolling(window=50).mean()
|
|
|
| fig.add_trace(go.Scatter(x=hist_data.index, y=ma20, name='20 Day MA', line=dict(color='orange')))
|
| fig.add_trace(go.Scatter(x=hist_data.index, y=ma50, name='50 Day MA', line=dict(color='blue')))
|
|
|
| fig.update_layout(
|
| title=f'{symbol} Stock Price',
|
| yaxis_title='Price',
|
| template='plotly_white',
|
| xaxis_rangeslider_visible=False,
|
| height=600
|
| )
|
|
|
| return fig
|
|
|
| def create_volume_chart(hist_data):
|
| """Create enhanced volume chart using plotly"""
|
|
|
| volume_ma = hist_data['Volume'].rolling(window=20).mean()
|
|
|
| fig = go.Figure()
|
|
|
|
|
| fig.add_trace(go.Bar(
|
| x=hist_data.index,
|
| y=hist_data['Volume'],
|
| name='Volume',
|
| marker_color='rgba(31, 119, 180, 0.3)'
|
| ))
|
|
|
|
|
| fig.add_trace(go.Scatter(
|
| x=hist_data.index,
|
| y=volume_ma,
|
| name='20 Day Volume MA',
|
| line=dict(color='red')
|
| ))
|
|
|
| fig.update_layout(
|
| title='Trading Volume Analysis',
|
| yaxis_title='Volume',
|
| template='plotly_white',
|
| height=400
|
| )
|
|
|
| return fig
|
|
|
| def format_large_number(number):
|
| """Format large numbers into readable format"""
|
| if number >= 1e12:
|
| return f"${number/1e12:.2f}T"
|
| elif number >= 1e9:
|
| return f"${number/1e9:.2f}B"
|
| elif number >= 1e6:
|
| return f"${number/1e6:.2f}M"
|
| else:
|
| return f"${number:,.2f}"
|
|
|
| def display_metrics(info):
|
| """Display enhanced key metrics in a grid"""
|
| col1, col2, col3, col4 = st.columns(4)
|
|
|
| with col1:
|
| st.markdown('<div class="metric-card">', unsafe_allow_html=True)
|
| market_cap = info.get('marketCap', 'N/A')
|
| if market_cap != 'N/A':
|
| market_cap = format_large_number(market_cap)
|
| st.metric("Market Cap", market_cap)
|
| st.markdown('</div>', unsafe_allow_html=True)
|
|
|
| with col2:
|
| st.markdown('<div class="metric-card">', unsafe_allow_html=True)
|
| pe_ratio = info.get('trailingPE', 'N/A')
|
| if pe_ratio != 'N/A':
|
| pe_ratio = f"{pe_ratio:.2f}"
|
| st.metric("P/E Ratio", pe_ratio)
|
| st.markdown('</div>', unsafe_allow_html=True)
|
|
|
| with col3:
|
| st.markdown('<div class="metric-card">', unsafe_allow_html=True)
|
| high = info.get('fiftyTwoWeekHigh', 'N/A')
|
| if high != 'N/A':
|
| high = f"${high:.2f}"
|
| st.metric("52 Week High", high)
|
| st.markdown('</div>', unsafe_allow_html=True)
|
|
|
| with col4:
|
| st.markdown('<div class="metric-card">', unsafe_allow_html=True)
|
| low = info.get('fiftyTwoWeekLow', 'N/A')
|
| if low != 'N/A':
|
| low = f"${low:.2f}"
|
| st.metric("52 Week Low", low)
|
| st.markdown('</div>', unsafe_allow_html=True)
|
|
|
| def main():
|
|
|
| with st.sidebar:
|
| st.header("📊 Analysis Options")
|
| analysis_type = st.selectbox(
|
| "Choose Analysis Type",
|
| ["Comprehensive Analysis", "Technical Analysis", "Fundamental Analysis",
|
| "News Analysis", "Sentiment Analysis"]
|
| )
|
|
|
|
|
| market = st.selectbox(
|
| "Select Market",
|
| ["US Market", "Indian Market (NSE)", "Indian Market (BSE)"]
|
| )
|
|
|
| st.markdown("---")
|
|
|
|
|
|
|
|
|
| st.markdown('<h1 class="stock-header">🤖 Advanced Stock Market Analysis By NeuSpaarX</h1>',
|
| unsafe_allow_html=True)
|
|
|
|
|
| col1, col2 = st.columns([2, 1])
|
| with col1:
|
| stock_input = st.text_input(
|
| "Enter Stock Name or Symbol",
|
| help="Enter company name (e.g., NVIDIA) or symbol (e.g., NVDA)"
|
| )
|
| with col2:
|
| date_range = st.selectbox(
|
| "Select Time Range",
|
| ["1 Month", "3 Months", "6 Months", "1 Year", "5 Years"], key="time_range"
|
| )
|
|
|
| period_map = {
|
| "1 Month": "1mo",
|
| "3 Months": "3mo",
|
| "6 Months": "6mo",
|
| "1 Year": "1y",
|
| "5 Years": "5y"
|
| }
|
| period = period_map[date_range]
|
|
|
| if st.button("Analyze", type="primary"):
|
| if not stock_input:
|
| st.error("Please enter a stock name or symbol.")
|
| return
|
|
|
|
|
| stock_symbol = get_symbol_from_name(stock_input)
|
| if stock_symbol:
|
| try:
|
|
|
| if initialize_agents():
|
|
|
| with st.spinner(f"Analyzing {stock_symbol}..."):
|
|
|
| info, hist = get_stock_data(stock_symbol, period=period)
|
|
|
| if info and hist is not None:
|
|
|
| market_status = "🟢 Market Open" if info.get('regularMarketOpen') else "🔴 Market Closed"
|
| st.markdown(f"<div class='market-indicator'>{market_status}</div>", unsafe_allow_html=True)
|
|
|
|
|
| overview_tab, charts_tab = st.tabs(["Overview", "Charts"])
|
|
|
| with overview_tab:
|
|
|
| st.markdown("### Company Overview")
|
| st.write(info.get('longBusinessSummary', 'No description available.'))
|
|
|
|
|
| st.markdown("### Key Metrics")
|
| display_metrics(info)
|
|
|
|
|
| col1, col2 = st.columns(2)
|
| with col1:
|
| st.markdown("### Company Details")
|
| st.write(f"Sector: {info.get('sector', 'N/A')}")
|
| st.write(f"Industry: {info.get('industry', 'N/A')}")
|
| st.write(f"Country: {info.get('country', 'N/A')}")
|
| st.write(f"Employees: {info.get('fullTimeEmployees', 'N/A'):,}")
|
|
|
| with col2:
|
| st.markdown("### Trading Information")
|
| st.write(f"Exchange: {info.get('exchange', 'N/A')}")
|
| st.write(f"Currency: {info.get('currency', 'N/A')}")
|
| st.write(f"Volume: {info.get('volume', 'N/A'):,}")
|
|
|
| with charts_tab:
|
|
|
| st.markdown("### Price Analysis")
|
| price_chart = create_price_chart(hist, stock_symbol)
|
| st.plotly_chart(price_chart, use_container_width=True)
|
|
|
|
|
| volume_chart = create_volume_chart(hist)
|
| st.plotly_chart(volume_chart, use_container_width=True)
|
|
|
|
|
| st.markdown("### Technical Indicators")
|
| col1, col2, col3 = st.columns(3)
|
|
|
| with col1:
|
| rsi = hist['Close'].diff()
|
| rsi_pos = rsi.copy()
|
| rsi_neg = rsi.copy()
|
| rsi_pos[rsi_pos < 0] = 0
|
| rsi_neg[rsi_neg > 0] = 0
|
| rsi_14_pos = rsi_pos.rolling(window=14).mean()
|
| rsi_14_neg = abs(rsi_neg.rolling(window=14).mean())
|
| rsi_14 = 100 - (100 / (1 + rsi_14_pos / rsi_14_neg))
|
| st.metric("RSI (14)", f"{rsi_14.iloc[-1]:.2f}")
|
|
|
| with col2:
|
| ma20 = hist['Close'].rolling(window=20).mean()
|
| ma50 = hist['Close'].rolling(window=50).mean()
|
| cross_signal = "Bullish" if ma20.iloc[-1] > ma50.iloc[-1] else "Bearish"
|
| st.metric("MA Cross Signal", cross_signal)
|
|
|
| with col3:
|
| volatility = hist['Close'].pct_change().std() * (252 ** 0.5) * 100
|
| st.metric("Annualized Volatility", f"{volatility:.2f}%")
|
|
|
|
|
|
|
| if st.button("🔄 Refresh Data"):
|
| st.session_state.last_refresh = datetime.now()
|
| st.experimental_rerun()
|
|
|
| except Exception as e:
|
| st.error(f"An error occurred: {str(e)}")
|
|
|
|
|
| if st.session_state.analysis_history:
|
| st.markdown("---")
|
| st.markdown("### Recent Analysis History")
|
| history_df = pd.DataFrame(st.session_state.analysis_history)
|
| history_df['timestamp'] = history_df['timestamp'].dt.strftime('%Y-%m-%d %H:%M:%S')
|
| st.dataframe(history_df, use_container_width=True)
|
|
|
|
|
| st.markdown("---")
|
| st.markdown("### About")
|
| st.markdown("""
|
| This advanced stock market analysis tool combines:
|
| - Real-time market data analysis
|
| - AI-powered insights and predictions
|
| - Technical and fundamental analysis
|
| - News and sentiment analysis
|
| - Interactive charts and visualizations
|
|
|
| Features:
|
| - Support for both US and Indian markets (NSE/BSE)
|
| - Company name and symbol resolution
|
| - Watchlist management
|
| - Multiple timeframe analysis
|
| - Technical indicators
|
|
|
| Use the sidebar to configure your analysis preferences and manage your watchlist.
|
| """)
|
|
|
|
|
| if st.session_state.last_refresh:
|
| st.markdown(f"<div class='market-indicator'>Last refreshed: {st.session_state.last_refresh.strftime('%Y-%m-%d %H:%M:%S')}</div>",
|
| unsafe_allow_html=True)
|
|
|
| if __name__ == "__main__":
|
| main()
|
|
|
