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chore: remove Vercel configuration and cleanup dependencies

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This commit is contained in:
Reynov Christian
2025-11-21 18:11:34 +08:00
parent 2d1ab7be7c
commit 0724f07f3f
20 changed files with 47 additions and 80 deletions
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MT5_SETUP_GUIDE.md
+7 -7
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@@ -15,7 +15,7 @@
## ⚡ Quick Setup (3 Steps)
### Step 1: Install MT5 Platform
```
```text
1. Download MT5 from: https://www.metatrader5.com/en/download
2. Install in default location: C:\Program Files\MetaTrader 5
3. Launch MT5 and login to your account (demo recommended)
@@ -113,7 +113,7 @@ MT5_SERVER=YourBroker-ServerName
python lab/download_data.py
```
**Expected Output:**
```
```text
✅ Successfully connected to MT5
📡 Server: FBS-Demo
👤 Account: 12345678
@@ -125,7 +125,7 @@ python lab/download_data.py
```
### Test 2: Web Interface
```
```text
1. Start QuantumBotX: python run.py
2. Open: http://localhost:5000/backtest
3. Click: "Download Data MT5" button
@@ -147,7 +147,7 @@ pip install MetaTrader5-5.0.34-cp39-cp39-win_amd64.whl
```
### Error: "Failed to initialize MT5"
```
```text
✅ Check MT5 is running
✅ Verify account credentials in .env
✅ Try Demo account first
@@ -155,7 +155,7 @@ pip install MetaTrader5-5.0.34-cp39-cp39-win_amd64.whl
```
### Error: "Symbol not found"
```
```text
✅ MT5 shows: "Enable Auto Trading" in algo settings
✅ Check if symbol is visible in MT5 Market Watch
✅ Some symbols need manual activation in MT5
@@ -163,7 +163,7 @@ pip install MetaTrader5-5.0.34-cp39-cp39-win_amd64.whl
```
### Error: "Download timed out"
```
```text
✅ Reduce download period in script if needed
✅ Check internet connection stability
✅ Some brokers are faster than others
@@ -207,7 +207,7 @@ print(f"Latest close: {df['close'].iloc[-1]}")
```
**Expected Output:**
```
```text
Rows: 15800+ (4+ years of H1 data)
Date range: 2020-01-01 to current_date
Latest close: matches MT5 current price
QuantumBotX-Installer.exe
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QuantumBotX-Portable.zip
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README_STREAMLIT.md
+2 -1
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@@ -74,7 +74,8 @@ Since MetaTrader 5 requires **Windows OS and persistent terminal connections**,
2. **Create requirements.txt** (use `streamlit_requirements.txt`)
3. **Create Procfile**:
```
```bash
web: streamlit run streamlit_demo.py --server.port $PORT --server.headless true
```
api/app.py
-10
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@@ -1,10 +0,0 @@
import os
from core import create_app
# Set environment to skip MT5 initialization on Vercel
os.environ['SKIP_MT5_INIT'] = '1'
app = create_app()
if __name__ == '__main__':
app.run()
core/backtesting/engine.py
+2 -3
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@@ -2,7 +2,6 @@
import math # Import modul math
import logging # Import modul logging
import os # Import for environment variables
from core.strategies.strategy_map import STRATEGY_MAP
logger = logging.getLogger(__name__)
@@ -214,7 +213,7 @@ def run_backtest(strategy_id, params, historical_data_df, symbol_name=None):
# Final safety check - never allow lot size above 0.03 for gold
if lot_size > 0.03:
lot_size = 0.03
logger.warning(f"GOLD SAFETY: Lot capped at 0.03")
logger.warning("GOLD SAFETY: Lot capped at 0.03")
# Round to valid lot size increments
lot_size = round(lot_size, 2)
@@ -304,7 +303,7 @@ def run_backtest(strategy_id, params, historical_data_df, symbol_name=None):
logger.info(f"Backtest Complete: {len(trades)} trades, ${total_profit_clean:+.0f} profit, {win_rate_clean:.0f}% win rate")
# Debug detailed results
logger.debug(f"=== DETAILED BACKTEST RESULTS ===")
logger.debug("=== DETAILED BACKTEST RESULTS ===")
logger.debug(f"Initial Capital: {initial_capital}")
logger.debug(f"Final Capital: {capital}")
logger.debug(f"Total Profit: {total_profit}")
core/routes/ai_mentor.py
+1 -1
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@@ -5,7 +5,7 @@ Routes untuk menampilkan laporan AI mentor dan interaksi pengguna
"""
from flask import Blueprint, render_template, request, jsonify, flash, redirect, url_for
from datetime import datetime, date, timedelta
from datetime import datetime, date
from core.ai.trading_mentor_ai import IndonesianTradingMentorAI, TradingSession
from core.db.models import (
get_trading_session_data, save_ai_mentor_report,
last_broker.json
+1 -1
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@@ -1,5 +1,5 @@
{
"broker": "FBS-Demo",
"company": "FBS Markets Inc.",
"last_check": "2025-10-16T03:19:13.829792"
"last_check": "2025-10-22T14:43:57.762205"
}
requirements.txt
-1
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@@ -4,7 +4,6 @@ charset-normalizer==3.4.2
click==8.2.1
colorama==0.4.6
Flask==3.1.1
gunicorn==22.0.0
idna==3.10
itsdangerous==2.2.0
Jinja2==3.1.6
setup_quantumbotx.py
+1 -1
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@@ -82,7 +82,7 @@ def create_desktop_shortcut():
try:
# Get user's desktop path
desktop = Path.home() / "Desktop"
shortcut_path = desktop / "QuantumBotX.lnk"
desktop / "QuantumBotX.lnk"
# Create a simple batch file that will be the shortcut target
shortcut_bat = '''@echo off
streamlit_demo.py
-2
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@@ -1,8 +1,6 @@
import streamlit as st
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
import time
import random
# Page configuration
testing/BACKTESTING_FIX_SUMMARY.md
+3 -3
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@@ -16,7 +16,7 @@ After comprehensive testing, I identified the **PRIMARY ISSUE**:
The enhanced backtesting engine was calculating spread costs that were **100% of the risk amount per trade**:
```
```text
Original Calculation:
- Risk per trade: $100 (1% of $10,000)
- Spread cost: $100 (100% of risk!)
@@ -54,7 +54,7 @@ spread_cost = spread_pips * 1.0 * lot_size # $0.50 for 0.5 lot
## 📊 BEFORE vs AFTER COMPARISON
### **BEFORE (Broken)**
```
```text
EURUSD Bollinger Squeeze Test:
- Gross Profit: -$10,000.03
- Spread Costs: -$7,414.00
@@ -64,7 +64,7 @@ EURUSD Bollinger Squeeze Test:
```
### **AFTER (Fixed)**
```
```text
EURUSD Test Results:
- Spread costs: ~0.5% of risk per trade
- Reasonable drawdowns (<50%)
testing/create_crypto_bot.py
+11 -11
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@@ -47,7 +47,7 @@ try:
def check_crypto_symbols():
"""Check if crypto symbols are available and get current prices"""
print(f"\\n💰 CRYPTO MARKET CHECK")
print("\\n💰 CRYPTO MARKET CHECK")
print("=" * 30)
if not mt5.initialize():
@@ -96,7 +96,7 @@ try:
def create_trading_plan():
"""Create a trading plan for SatoshiJakarta"""
print(f"\\n📋 SATOSHIJAKARTA TRADING PLAN")
print("\\n📋 SATOSHIJAKARTA TRADING PLAN")
print("=" * 40)
plan = {
@@ -137,11 +137,11 @@ try:
print(f" Size: {plan['secondary_pair']['position_size']}")
print(f" Why: {plan['secondary_pair']['reasoning']}")
print(f"\\n🛡️ Risk Management:")
print("\\n🛡️ Risk Management:")
for key, value in plan['risk_management'].items():
print(f" {key.replace('_', ' ').title()}: {value}")
print(f"\\n⏰ Trading Schedule:")
print("\\n⏰ Trading Schedule:")
for day, activity in plan['schedule'].items():
print(f" {day.title()}: {activity}")
@@ -149,7 +149,7 @@ try:
def show_next_steps():
"""Show immediate next steps"""
print(f"\\n🎯 IMMEDIATE NEXT STEPS")
print("\\n🎯 IMMEDIATE NEXT STEPS")
print("=" * 30)
steps = [
@@ -185,12 +185,12 @@ try:
print(f" 🎯 Action: {step_info['action']}")
print(f" ⏱️ Time: {step_info['time']}")
print(f"\\n🔥 TOTAL SETUP TIME: 12 minutes!")
print(f"Then you'll have 24/7 crypto profit machine! 🚀")
print("\\n🔥 TOTAL SETUP TIME: 12 minutes!")
print("Then you'll have 24/7 crypto profit machine! 🚀")
def show_crypto_advantages():
"""Show why crypto trading is perfect for Indonesian traders"""
print(f"\\n🇮🇩 WHY CRYPTO IS PERFECT FOR INDONESIA")
print("\\n🇮🇩 WHY CRYPTO IS PERFECT FOR INDONESIA")
print("=" * 45)
advantages = [
@@ -230,7 +230,7 @@ try:
# Show next steps
show_next_steps()
print(f"\\n" + "=" * 60)
print("\\n" + "=" * 60)
print("🎉 SATOSHIJAKARTA IS READY!")
print("=" * 60)
print("✅ Bot configured for Bitcoin & Ethereum")
@@ -239,10 +239,10 @@ try:
print("✅ Weekend mode active for 24/7 profits")
print("✅ Perfect for your timezone and goals")
print(f"\\n🚀 FROM JAKARTA TO THE MOON!")
print("\\n🚀 FROM JAKARTA TO THE MOON!")
print("Your crypto trading journey starts NOW! 🌙🇮🇩")
print(f"\\n💎 REMEMBER:")
print("\\n💎 REMEMBER:")
print("Satoshi Nakamoto gave us Bitcoin...")
print("SatoshiJakarta will give you PROFITS! ₿💰")
testing/crypto_integration_demo.py
+1 -2
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@@ -8,7 +8,6 @@ import sys
import os
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
# Add the project root to the path
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
@@ -153,7 +152,7 @@ def test_crypto_strategy_performance():
total_profit += strategy_stats['profit']
total_trades += strategy_stats['trades']
print(f"\\n🏆 Overall Results:")
print("\\n🏆 Overall Results:")
print(f" Total Profit: ${total_profit:,.2f}")
print(f" Total Trades: {total_trades}")
print(f" Average Profit per Trade: ${total_profit/max(total_trades,1):,.2f}")
testing/debug_backtest_execution.py
+12 -13
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@@ -65,7 +65,6 @@ def debug_enhanced_backtest():
df_with_signals = strategy.analyze_df(df.copy())
# Add ATR
import pandas_ta as ta
df_with_signals.ta.atr(length=14, append=True)
df_with_signals.dropna(inplace=True)
df_with_signals.reset_index(inplace=True)
@@ -78,7 +77,7 @@ def debug_enhanced_backtest():
# Show signal bars
signal_bars = df_with_signals[df_with_signals['signal'] != 'HOLD']
print(f"Signal bars:")
print("Signal bars:")
for i, row in signal_bars.iterrows():
print(f" Index {i}: {row['signal']} | Close: {row['close']:.5f} | ATR: {row.get('ATRr_14', 'Missing')}")
@@ -87,7 +86,7 @@ def debug_enhanced_backtest():
return
# Manual backtest loop simulation
print(f"\\n🔄 SIMULATING BACKTEST LOOP...")
print("\\n🔄 SIMULATING BACKTEST LOOP...")
# Initialize
engine = EnhancedBacktestEngine()
@@ -102,7 +101,7 @@ def debug_enhanced_backtest():
sl_atr_multiplier = float(params.get('sl_atr_multiplier', params.get('sl_pips', 2.0)))
tp_atr_multiplier = float(params.get('tp_atr_multiplier', params.get('tp_pips', 4.0)))
print(f"Engine parameters:")
print("Engine parameters:")
print(f" Risk: {risk_percent}%")
print(f" SL: {sl_atr_multiplier}x ATR")
print(f" TP: {tp_atr_multiplier}x ATR")
@@ -129,7 +128,7 @@ def debug_enhanced_backtest():
print(f" ATR: {atr_value}")
if atr_value <= 0:
print(f" ❌ Invalid ATR - skipping")
print(" ❌ Invalid ATR - skipping")
continue
# Calculate distances
@@ -147,7 +146,7 @@ def debug_enhanced_backtest():
print(f" Calculated lot size: {lot_size}")
if lot_size <= 0:
print(f" ❌ Invalid lot size - skipping")
print(" ❌ Invalid lot size - skipping")
continue
# Calculate entry price
@@ -174,10 +173,10 @@ def debug_enhanced_backtest():
estimated_risk = sl_distance * lot_size * config['contract_size']
max_risk_dollar = capital * config.get('emergency_brake_percent', 0.05)
if estimated_risk > max_risk_dollar:
print(f" 🚨 Emergency brake triggered - skipping")
print(" 🚨 Emergency brake triggered - skipping")
continue
print(f" ✅ Trade would be executed!")
print(" ✅ Trade would be executed!")
# For debugging, let's see if we can find the next exit
for j in range(i+1, len(df_with_signals)):
@@ -199,7 +198,7 @@ def debug_enhanced_backtest():
break
if j > i + 10: # Only check next 10 bars
print(f" ⏰ No exit in next 10 bars")
print(" ⏰ No exit in next 10 bars")
break
trades.append({'signal': signal, 'entry': entry_price})
@@ -207,14 +206,14 @@ def debug_enhanced_backtest():
if len(trades) >= 3: # Limit debug output
break
print(f"\\n📋 DEBUG SUMMARY:")
print("\\n📋 DEBUG SUMMARY:")
print(f"Processed {len(trades)} potential trades")
if len(trades) > 0:
print(f"✅ Trade logic is working - trades should execute")
print(f"❓ The issue might be in the actual enhanced_engine implementation")
print("✅ Trade logic is working - trades should execute")
print("❓ The issue might be in the actual enhanced_engine implementation")
else:
print(f"❌ No trades processed - issue in trade logic")
print("❌ No trades processed - issue in trade logic")
except Exception as e:
print(f"Error in debug: {e}")
testing/test_ai_mentor_integration.py
+2 -2
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@@ -9,7 +9,7 @@ import sys
import os
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from datetime import date, datetime, timedelta
from datetime import date, timedelta
from core.ai.trading_mentor_ai import IndonesianTradingMentorAI, TradingSession
from core.db.models import (
create_trading_session, log_trade_for_ai_analysis,
@@ -127,7 +127,7 @@ def test_historical_reports():
emotions_cycle = ['tenang', 'serakah', 'frustasi', 'takut', 'tenang', 'serakah', 'tenang']
for test_date, emotion in zip(historical_dates, emotions_cycle):
session_id = create_trading_session(
create_trading_session(
session_date=test_date,
emotions=emotion,
market_conditions='normal',
testing/test_analysis_api.py
+2 -2
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@@ -31,7 +31,7 @@ try:
# Check if bot 3 is in active_bots
if bot_id in active_bots:
bot_instance = active_bots[bot_id]
print(f"Bot instance found:")
print("Bot instance found:")
print(f" - Alive: {bot_instance.is_alive()}")
print(f" - Status: {bot_instance.status}")
if hasattr(bot_instance, 'last_analysis'):
@@ -42,7 +42,7 @@ try:
# Get bot from database
bot_data = queries.get_bot_by_id(bot_id)
if bot_data:
print(f"\\nBot in database:")
print("\\nBot in database:")
print(f" - Name: {bot_data['name']}")
print(f" - Market: {bot_data['market']}")
print(f" - Status: {bot_data['status']}")
testing/test_atr_education.py
+2 -2
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@@ -69,7 +69,7 @@ def test_atr_education_system():
print(f" Risk-to-Reward: {example['risk_to_reward_ratio']}")
if example['protection_active']:
print(f" 🛡️ PROTECTION: System reduced risk for safety!")
print(" 🛡️ PROTECTION: System reduced risk for safety!")
# Test 3: Parameter validation
print("\n3. ⚙️ Parameter Validation:")
@@ -161,7 +161,7 @@ def demonstrate_atr_protection():
print(f" 💰 PROTECTION SAVED: ${savings:.0f}")
print(f" 🎯 System automatically reduced risk by {(savings/example['amount_to_risk_target']*100):.0f}%")
print(f"\\n 📝 Explanation:")
print("\\n 📝 Explanation:")
for exp in example['explanation']:
print(f" {exp}")
testing/test_crypto_fixes.py
-3
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@@ -8,10 +8,7 @@ import sys
import os
sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
import pandas as pd
import numpy as np
import logging
from pathlib import Path
# Set up logging to see what's happening
logging.basicConfig(level=logging.INFO, format='%(levelname)s:%(name)s:%(message)s')
vercel.json
-15
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@@ -1,15 +0,0 @@
{
"routes": [
{
"src": "/(.*)",
"dest": "/api/app.py"
}
],
"env": {
"SKIP_MT5_INIT": "1"
}
],
"env": {
"SKIP_MT5_INIT": "1"
}
}