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Overview

The Streamlit application provides a web-based dashboard for running market analysis and viewing trading signals in real-time.

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Application Structure

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Page Configuration

The application must be configured before any other Streamlit commands: 
import streamlit as st

st.set_page_config(
    page_title="XAUUSD Trading Bot",
    page_icon="📈",
    layout="wide"
)
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page_title
string
Browser tab title: “XAUUSD Trading Bot”
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page_icon
string
Browser tab icon: ”📈”
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layout
string
Page layout mode: “wide” for full-width content

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Bot Initialization

from XAUSD_AI import XAUUSDTradingBot

bot = XAUUSDTradingBot(api_key=st.secrets["GROQ_API_KEY"])
See Environment Variables for configuration details.

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UI Components

The sidebar contains the control panel for user interactions: 
with st.sidebar:
    st.header("Control Panel")
    
    # Auto-refresh toggle
    auto_refresh = st.toggle("🔄 Auto Refresh (30min)", value=False)
    
    # Run analysis button
    if st.button("📈 Run New Analysis"):
        with st.spinner("Analyzing market data..."):
            st.session_state['analysis_result'] = bot.run_analysis()
            st.session_state['last_update'] = datetime.now()

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Main Content Tabs

The dashboard uses tabs to organize different views: 
tab1, tab2 = st.tabs(["📊 Analysis", "🎯 Trading Signal"])

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Analysis Tab

Displays technical analysis and market data across timeframes: 
with tab1:
    # Technical Analysis
    st.markdown("### 📊 Technical Analysis")
    st.markdown(format_signal(result['technical_features']))
    
    # Market Data
    st.markdown("### 📈 Market Data by Timeframe")
    cols = st.columns(2)
    for idx, (tf, data) in enumerate(result['market_data'].items()):
        with cols[idx % 2]:
            display_market_data(data, tf)

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Trading Signal Tab

Displays the generated trading signal: 
with tab2:
    st.markdown("### 🎯 Trading Signal")
    st.markdown(format_signal(result['trading_signal']))

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Helper Functions

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display_market_data()

Formats and displays market data in an expandable section: 
def display_market_data(data_str, timeframe):
    """Display formatted market data in an expander"""
    with st.expander(f"📊 {timeframe} Market Data", expanded=False):
        lines = data_str.split('\n')
        for line in lines:
            if line.strip():
                st.text(line)
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data_str
string
required
Multi-line string containing market data for a specific timeframe
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timeframe
string
required
Timeframe identifier (e.g., “D1”, “H4”, “H1”). See Timeframes for supported values.

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format_signal()

Formats signal content that may be returned as string or object: 
def format_signal(signal_content):
    """Format and display trading signal content"""
    if isinstance(signal_content, str):
        return signal_content
    return signal_content.content if hasattr(signal_content, 'content') else str(signal_content)
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signal_content
string | object
required
Signal content from bot analysis results
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return
string
Formatted signal content as a string

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Auto-Refresh Feature

Implements automatic analysis refresh every 30 minutes: 
if auto_refresh:
    current_time = datetime.now()
    if 'last_refresh' not in st.session_state:
        st.session_state['last_refresh'] = current_time
    
    time_diff = (current_time - st.session_state['last_refresh']).total_seconds()
    remaining_time = 1800 - time_diff  # 1800 seconds = 30 minutes

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Session State Management

The application uses Streamlit session state to persist data:
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analysis_result
dict
Cached result from bot.run_analysis() to avoid redundant API calls
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last_update
datetime
Timestamp of the last successful analysis run
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last_refresh
datetime
Timestamp of the last auto-refresh for progress calculation

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Custom Styling

The application includes custom CSS for dark theme UI: 
st.markdown("""
    <style>
    .stApp {background-color: #0e1117}
    .metric-container {
        background-color: #1f2937;
        padding: 10px;
        border-radius: 5px;
        margin: 5px;
    }
    .stTabs [data-baseweb="tab-list"] {
        gap: 2px;
        background-color: #1f2937;
    }
    .stTabs [data-baseweb="tab"] {
        background-color: #374151;
        padding: 10px 20px;
        border-radius: 5px 5px 0 0;
    }
    </style>
""", unsafe_allow_html=True)

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Error Handling

try:
    # Main application logic
    if 'analysis_result' in st.session_state:
        result = st.session_state['analysis_result']
        # Display results...
    else:
        st.warning("⚠️ No analysis results yet. Click 'Run Analysis' to start.")
except Exception as e:
    st.error(f"Error: {str(e)}")

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Entry Point

if __name__ == "__main__":
    main()

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