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Documentation Index

Fetch the complete documentation index at: https://mintlify.com/codebytemirza/XAUUSD_TRADING_ASISTENT_AI/llms.txt

Use this file to discover all available pages before exploring further.

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MetaTrader 5 Issues

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Connection Failed

If you cannot connect to MetaTrader 5, this will prevent the bot from accessing market data.
Symptoms:
  • Bot fails to start
  • Error message: “Failed to initialize MT5”
  • No market data displayed
Solutions:
  1. Open MetaTrader 5 desktop application
  2. Log in to your account
  3. Ensure you see live price feeds
  4. Keep MT5 running while using the bot
The bot requires MT5 to be running and logged in to access market data via the API.
  1. In MT5, go to Tools → Options → Server
  2. Verify you’re connected to the server (green icon in bottom right)
  3. If disconnected, re-enter your credentials
  4. Check your internet connection
pip install --upgrade MetaTrader5
Then test the connection:
import MetaTrader5 as mt5
if mt5.initialize():
    print("MT5 initialized successfully")
    mt5.shutdown()
else:
    print("MT5 initialization failed")
The MetaTrader5 Python package works best on:
  • Windows: Full support
  • Linux: Limited support (requires Wine)
  • macOS: Limited support (requires Wine or virtual machine)
If you’re on Linux/macOS, consider using a Windows virtual machine or VPS for better compatibility.

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Symbol Not Found

Symptoms:
  • Error: “XAUUSD symbol not found”
  • No price data for gold
Solutions:
  1. Check Symbol Availability:
    • In MT5, right-click Market Watch
    • Select “Symbols”
    • Search for XAUUSD or Gold
    • Ensure it’s visible in Market Watch
  2. Verify Symbol Name:
    • Some brokers use different naming: XAUUSD, GOLD, XAUUSD.m
    • Check your broker’s symbol naming convention
    • Update the symbol name in XAUSD_AI.py if needed
Different brokers may use different symbol names. Always verify the exact symbol name in your MT5 platform.

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Data Retrieval Issues

Symptoms:
  • Incomplete historical data
  • Missing timeframe data
  • Empty dataframes
Solutions:
  1. In MT5, go to Tools → Options → Charts
  2. Set “Max bars in chart” to at least 10,000
  3. Set “Max bars in history” to at least 100,000
  4. Restart MT5
When you first add XAUUSD to Market Watch:
  • MT5 needs time to download historical data
  • Wait 5-10 minutes for complete synchronization
  • Check the status bar for download progress

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API Key Issues

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Invalid Groq API Key

An invalid or missing API key will prevent the AI component from generating trading signals.
Symptoms:
  • Error: “Invalid API key”
  • Authentication failed
  • AI analysis not working
Solutions:
  1. Check .streamlit/secrets.toml file exists
  2. Ensure format is correct:
GROQ_API_KEY = "gsk_..."
  1. No extra spaces or quotes
  2. Key should start with gsk_
  1. Visit Groq Console
  2. Navigate to API Keys section
  3. Revoke old key (if compromised)
  4. Create new API key
  5. Update .streamlit/secrets.toml
  6. Restart the Streamlit app
  • Free tier has rate limits
  • Monitor usage in Groq Console
  • Consider upgrading if hitting limits
  • Wait for quota reset (usually hourly/daily)
If you’re making frequent requests, you may hit rate limits. Space out your analysis requests or upgrade your plan.

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API Connection Timeout

Symptoms:
  • Request timeout errors
  • Slow response from AI
  • Connection refused
Solutions:
  1. Check internet connection
  2. Verify firewall isn’t blocking Groq API
  3. Try using a VPN if blocked in your region
  4. Increase timeout settings in the code

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Dependency Issues

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Package Installation Failures

Symptoms:
  • pip install errors
  • Module not found errors
  • Version conflicts
Solutions: 
# Create virtual environment
python -m venv venv

# Activate (Windows)
venv\Scripts\activate

# Activate (Linux/Mac)
source venv/bin/activate

# Install requirements
pip install -r requirements.txt
Virtual environments prevent dependency conflicts with other Python projects.
python -m pip install --upgrade pip setuptools wheel
pip install -r requirements.txt
If requirements.txt fails, install packages individually:
pip install MetaTrader5
pip install pandas numpy
pip install langchain-groq
pip install streamlit
Ensure you’re using Python 3.8 or higher:
python --version
If version is too old:
  • Download latest Python from python.org
  • Install and update PATH
  • Recreate virtual environment with new version

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Import Errors

Symptoms:
  • ModuleNotFoundError
  • ImportError
  • Missing dependencies
Solutions: 
# Verify package installation
pip list | grep -E "MetaTrader5|pandas|numpy|langchain|streamlit"

# Reinstall specific package
pip uninstall <package-name>
pip install <package-name>

# Clear pip cache if needed
pip cache purge
pip install -r requirements.txt

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Streamlit Dashboard Issues

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Dashboard Won’t Start

Symptoms:
  • streamlit run app.py fails
  • Port already in use
  • Application crashes on startup
Solutions: 
# Default Streamlit port is 8501
# Windows
netstat -ano | findstr :8501

# Linux/Mac
lsof -i :8501
Use a different port:
streamlit run app.py --server.port 8502

# Clear cache directory
rm -rf ~/.streamlit/cache

# Or use Streamlit command
streamlit cache clear
Ensure you’re in the correct directory:
# Navigate to project directory
cd /path/to/xauusd-trading-bot

# Verify app.py exists
ls -la app.py

# Run Streamlit
streamlit run app.py

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Dashboard Shows Errors

Symptoms:
  • Red error messages in dashboard
  • Features not working
  • No data displayed
Solutions:
  1. Check Browser Console:
    • Press F12 in browser
    • Look for JavaScript errors
    • Try different browser
  2. Refresh the Page:
    • Click “Rerun” in Streamlit
    • Hard refresh: Ctrl+Shift+R (Windows/Linux) or Cmd+Shift+R (Mac)
  3. Check Logs:
    • Look at terminal where Streamlit is running
    • Check for error messages
    • Debug based on error output
Streamlit dashboard errors are often displayed both in the browser and terminal. Check both locations for complete error information.

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Performance Issues

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Slow Analysis

Symptoms:
  • Analysis takes too long
  • Dashboard freezes
  • Timeout errors
Solutions:
  • Focus on fewer timeframes initially
  • Comment out some timeframes in XAUSD_AI.py
  • Start with H4, H1, M30 for faster analysis
  • Reduce the number of bars fetched
  • Use smaller lookback periods
  • Balance between data sufficiency and speed
  • Close unnecessary applications
  • Ensure adequate RAM (4GB+ recommended)
  • Check CPU usage
  • Consider upgrading hardware for intensive analysis

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High Memory Usage

Solutions:
  • Clear Python cache regularly
  • Restart the Streamlit app periodically
  • Limit auto-refresh frequency
  • Use smaller data batches

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Data Accuracy Issues

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Inconsistent Signals

Trading signals may vary based on market conditions, timeframe, and data availability.
This is Normal If:
  • Markets are volatile or choppy
  • Different timeframes show conflicting signals
  • Major news events are occurring
Investigate If:
  • Signals change drastically within seconds
  • Data appears corrupted or unusual
  • Indicators show impossible values
Solutions:
  1. Verify MT5 data feed is stable
  2. Check for broker server issues
  3. Compare with MT5’s built-in indicators
  4. Ensure sufficient historical data

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Spread Warnings

Symptoms:
  • High spread alerts
  • “Spread too wide” messages
This is Normal:
  • During market open/close
  • Major news releases
  • Low liquidity periods
  • Some broker’s typical spreads
High spreads can significantly impact profitability. The bot alerts you to avoid trading during unfavorable spread conditions.

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Getting Additional Help

Add debug logging to help diagnose issues:
import logging
logging.basicConfig(level=logging.DEBUG)
When reporting issues, include:
  • Python version: python --version
  • Package versions: pip list
  • Operating system
  • MT5 version
  • Error messages (complete text)
  • Steps to reproduce
  • Check GitHub Issues for similar problems
  • Search existing solutions
  • Create detailed issue reports
  • Provide code samples and error logs
If you’ve tried all troubleshooting steps and still face issues, consider checking the updated version of the project or reaching out through GitHub Issues with detailed information about your problem.

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