🤖 AgentFxTrading - AI-Powered Automated Trading System

Autonomous Forex Trading with TMS + ORB Strategy

Installation • Features • Strategy • API Docs • Contributing

📋 Table of Contents

Overview
Features
Architecture
Quick Start
Trading Strategy
Configuration
API Documentation
Development
Performance
Contributing
License

🎯 Overview

AgentFxTrading is an autonomous forex trading system that combines the power of AI with proven technical analysis strategies. It uses TMS (Trend Momentum Signal) for trend detection and ORB (Opening Range Breakout) for precise entry timing.

Why AgentFxTrading?

✅ Fully Autonomous - AI makes trading decisions 24/7
✅ Multi-LLM Support - Works with Qwen, OpenAI, Claude, Gemini, DeepSeek
✅ Risk Management - Portfolio-level risk control across multiple pairs
✅ Proven Strategy - Based on professional TMS methodology
✅ Easy Setup - Get started in under 10 minutes
✅ Open Source - Fully transparent and customizable

🚀 Features

🤖 AI-Powered Decision Making

Multi-LLM Support: Qwen, OpenAI GPT-4, Claude, Gemini, DeepSeek
Context-Aware Analysis: Analyzes 3 bars of historical data
Confidence Scoring: Only trades when confidence > 70%
Adaptive Learning: Prompt engineering for continuous improvement

📊 Advanced Technical Analysis

TMS Indicators: Heiken Ashi, TDI (RSI + Signal), Stochastic
ORB Logic: Opening Range detection with decisive breakout filter
Momentum Tracking: TF Green State with slope analysis
Market Regime Detection: Kaufman Efficiency Ratio (er_session, er_recent) & failed breakout counter (or_flips) to classify market into trending, choppy, mixed, forming

💼 Portfolio Management

Multi-Symbol Trading: Run multiple bots on different pairs
Currency Exposure Control: Prevents over-exposure to single currency
Correlation Detection: Blocks highly correlated positions
Daily Loss Limits: Automatic trading halt after max loss

🛡️ Risk Management

Position Memory: Tracks MFE (Maximum Favorable Excursion)
Auto Breakeven: Moves SL to entry after profit threshold
Trailing Stop: Dynamic SL adjustment during profitable trades
Max Giveback Protection: Closes position if giveback exceeds threshold
Loss Streak Protection: Blocks entries after 3 consecutive losses
Cycle Gating (Cost Gate): Deterministically bypasses LLM calls when outside session, inside OR, or during loss streak — saving 80-90% API tokens
Trend TP Disabled: Automatically disables fixed TP during trending regimes to ride the full move with Trailing SL & Giveback Floor
Daily Rotating Logs: Persists all agent reasoning, cycle gate actions, and market snapshots to logs/agent_YYYY-MM-DD.log (14-day retention)

⏰ Session Management

Trading Sessions: Configurable session times (London, NY, Tokyo)
EOD Auto-Close: Automatically closes positions at session end
Phase Detection: Pre-market, active, ending, closed phases

🏗️ Architecture

graph LR
    A[cTrader cBot<br/>C#] -->|HTTP POST| B[FastAPI Server<br/>Python]
    B -->|JSON Response| A
    B --> C{LLM Provider}
    C --> D[Qwen]
    C --> E[OpenAI]
    C --> F[Claude]
    C --> G[Gemini]
    C --> H[DeepSeek]
    B --> I[(SQLite<br/>Portfolio DB)]

Component Breakdown

Component	Technology	Responsibility
cBot	C# / cTrader	Calculate indicators, execute trades
Server	Python / FastAPI	AI decision making, risk management
Database	SQLite	Portfolio tracking, position history
LLM	Multiple	Trading decision analysis

📊 Dashboard

Monitor your trading system in real-time through the web dashboard.

Access Dashboard

After starting the server, open your browser:

http://127.0.0.1:8000/dashboard

Features

Real-time Updates: WebSocket connection for live position tracking
Portfolio Overview: Open positions, daily P&L, win rate, loss streak
Active Positions Table: Bot ID, symbol, side, volume, entry price, SL/TP
Trade History: Recent closed trades with P&L
P&L Chart: Visual representation of daily performance

API Endpoints

GET /dashboard              # Web interface
GET /api/dashboard/summary  # Portfolio summary (JSON)
GET /api/dashboard/positions # Active positions (JSON)
GET /api/dashboard/history  # Trade history (JSON)
WS  /ws/dashboard           # WebSocket for real-time updates

⚡ Quick Start

Prerequisites

Python 3.9+
cTrader 4.x+
LLM API key (Qwen/OpenAI/Claude/Gemini/DeepSeek)

1. Install Python Dependencies

# Clone repository
git clone https://github.com/kienphan/AgentFxTrading.git
cd AgentFxTrading

# Install dependencies
pip install -r requirements.txt

2. Configure LLM Provider

# Copy environment template
cp .env.example .env

# Edit .env with your API key
# Example for Qwen (recommended):
LLM_PROVIDER=qwen
DASHSCOPE_API_KEY=sk-your-dashscope-key
LLM_MODEL=qwen-max

3. Start the Server

python app/server.py

Server will run at http://127.0.0.1:8000

4. Setup & Run cBot

You can run the cBot either via cTrader Desktop GUI or Headless Docker CLI (ctrader-console).

Option A: cTrader Desktop GUI

Open cTrader → Automate
Click New → cBot
Paste code from cBot/AiAgentBot.cs
Click Build
Attach to chart (M15 or H1 recommended)
Configure parameters:
- Bot ID: xauusd_m15 (unique identifier)
- API URL: http://127.0.0.1:8000/trade
- Session: New York (13:00-21:00 UTC) / London (8:00-17:00 UTC) / Tokyo (0:00-9:00 UTC)

Option B: Headless Docker CLI (`ctrader-console`)

Prepare Credentials File:

mkdir -p /root/ctrader_data
echo "your_ctid_password" > /root/ctrader_data/ctid_pwd
chmod 600 /root/ctrader_data/ctid_pwd

Build/Compile the .algo package:

docker run --rm -v $(pwd):/workspace -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest create cbot AiAgentBot
cp cBot/AiAgentBot.cs /root/cAlgo/Sources/Robots/AiAgentBot/AiAgentBot/AiAgentBot.cs
docker run --rm -v $(pwd):/workspace -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest build /root/cAlgo/Sources/Robots/AiAgentBot/AiAgentBot/AiAgentBot.csproj
cp /root/cAlgo/Sources/Robots/AiAgentBot.algo cBot/AiAgentBot.algo

Run Multi-Instance Docker Containers:

XAUUSD (M15 - New York Session):

docker run -d \
  --name cbot-xauusd \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=XAUUSD \
  --period=m15 \
  --full-access \
  --BotId="xauusd_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="newyork" \
  --OrbStartHour=13 \
  --SessionEndHour=21 \
  --SessionDstRule="US" \
  --MinDecisiveBreakoutPips=200.0 \
  --MinOrWidthPips=400.0 \
  --OrbBufferPips=50.0 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=10 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

EURUSD (M15 - London Session):

docker run -d \
  --name cbot-eurusd \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=EURUSD \
  --period=m15 \
  --full-access \
  --BotId="eurusd_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="london" \
  --OrbStartHour=8 \
  --SessionEndHour=17 \
  --SessionDstRule="Europe" \
  --MinDecisiveBreakoutPips=3.0 \
  --MinOrWidthPips=6.0 \
  --OrbBufferPips=1.0 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=5 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

GBPUSD (M15 - London Session):

docker run -d \
  --name cbot-gbpusd \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=GBPUSD \
  --period=m15 \
  --full-access \
  --BotId="gbpusd_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="london" \
  --OrbStartHour=8 \
  --SessionEndHour=17 \
  --SessionDstRule="Europe" \
  --MinDecisiveBreakoutPips=4.5 \
  --MinOrWidthPips=10.0 \
  --OrbBufferPips=1.5 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=10 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

USDJPY (M15 - Tokyo Session):

docker run -d \
  --name cbot-usdjpy \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=USDJPY \
  --period=m15 \
  --full-access \
  --BotId="usdjpy_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="tokyo" \
  --OrbStartHour=0 \
  --SessionEndHour=9 \
  --SessionDstRule="None" \
  --MinDecisiveBreakoutPips=4.0 \
  --MinOrWidthPips=8.0 \
  --OrbBufferPips=1.5 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=3 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

US30 (M15 - New York Index Session):

docker run -d \
  --name cbot-us30 \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=US30 \
  --period=m15 \
  --full-access \
  --BotId="us30_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="newyork_index" \
  --OrbStartHour=13 \
  --SessionEndHour=20 \
  --SessionDstRule="US" \
  --MinDecisiveBreakoutPips=30.0 \
  --MinOrWidthPips=80.0 \
  --OrbBufferPips=15.0 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=30 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

USTEC / NAS100 (M5 - New York Index Session) (Note: Use USTEC or NAS100 depending on your broker):

docker run -d \
  --name cbot-ustec \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=USTEC \
  --period=m5 \
  --full-access \
  --BotId="ustec_m5" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="newyork_index" \
  --OrbStartHour=13 \
  --SessionEndHour=20 \
  --SessionDstRule="US" \
  --MinDecisiveBreakoutPips=25.0 \
  --MinOrWidthPips=70.0 \
  --OrbBufferPips=12.0 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=25 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

GBPJPY (M15 - London Session / High Volatility Cross):

docker run -d \
  --name cbot-gbpjpy \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=GBPJPY \
  --period=m15 \
  --full-access \
  --BotId="gbpjpy_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="london" \
  --OrbStartHour=8 \
  --SessionEndHour=17 \
  --SessionDstRule="Europe" \
  --MinDecisiveBreakoutPips=6.0 \
  --MinOrWidthPips=15.0 \
  --OrbBufferPips=2.0 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=5 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

EURJPY (M15 - London Session / High Volatility Cross):

docker run -d \
  --name cbot-eurjpy \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=EURJPY \
  --period=m15 \
  --full-access \
  --BotId="eurjpy_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="london" \
  --OrbStartHour=8 \
  --SessionEndHour=17 \
  --SessionDstRule="Europe" \
  --MinDecisiveBreakoutPips=5.0 \
  --MinOrWidthPips=12.0 \
  --OrbBufferPips=1.5 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=5 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

USDCAD (M15 - New York Session / Commodity FX):

docker run -d \
  --name cbot-usdcad \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=USDCAD \
  --period=m15 \
  --full-access \
  --BotId="usdcad_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="newyork" \
  --OrbStartHour=13 \
  --SessionEndHour=21 \
  --SessionDstRule="US" \
  --MinDecisiveBreakoutPips=4.0 \
  --MinOrWidthPips=10.0 \
  --OrbBufferPips=1.5 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=4 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

AUDUSD (M15 - Asian/Tokyo Session / Commodity FX):

docker run -d \
  --name cbot-audusd \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=AUDUSD \
  --period=m15 \
  --full-access \
  --BotId="audusd_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="tokyo" \
  --OrbStartHour=0 \
  --SessionEndHour=9 \
  --SessionDstRule="None" \
  --MinDecisiveBreakoutPips=3.0 \
  --MinOrWidthPips=8.0 \
  --OrbBufferPips=1.0 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=3 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

DE40 / DAX40 (M5 - London/European Index Session) (Note: Use DE40 or GER40 depending on your broker):

docker run -d \
  --name cbot-de40 \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=DE40 \
  --period=m15 \
  --full-access \
  --BotId="de40_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="london" \
  --OrbStartHour=8 \
  --SessionEndHour=16 \
  --SessionDstRule="Europe" \
  --MinDecisiveBreakoutPips=20.0 \
  --MinOrWidthPips=60.0 \
  --OrbBufferPips=10.0 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=25 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

AUDJPY (M15 - Asian/Tokyo Session / Risk Barometer Cross):

docker run -d \
  --name cbot-audjpy \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=AUDJPY \
  --period=m15 \
  --full-access \
  --BotId="audjpy_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="tokyo" \
  --OrbStartHour=0 \
  --SessionEndHour=9 \
  --SessionDstRule="None" \
  --MinDecisiveBreakoutPips=4.0 \
  --MinOrWidthPips=10.0 \
  --OrbBufferPips=1.5 \
  --BreakevenTriggerAtr=1.2 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.0 \
  --TrailDistanceAtr=1.0 \
  --PartialCloseRatio=0.5 \
  --MinSlAtr=0.8 \
  --MaxSlAtr=3.0 \
  --MinTpAtr=1.0 \
  --MaxTpAtr=6.0 \
  --MaxGivebackAtr=1.0 \
  --EnablePostTpGate=true \
  --PostTpPullbackAtr=0.5 \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=4 \
  --RiskPerTradePercent=0.2 \
  --TrendTpDisabled=true

BTCUSD (M15 - New York Session / Crypto Momentum):

docker run -d \
  --name cbot-btcusd \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=BTCUSD \
  --period=m15 \
  --full-access \
  --BotId="btcusd_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="newyork" \
  --OrbStartHour=13 \
  --SessionEndHour=22 \
  --SessionDstRule="US" \
  --MinDecisiveBreakoutPips=150.0 \
  --MinOrWidthPips=300.0 \
  --OrbBufferPips=50.0 \
  --PartialCloseRatio=0.5 \
  --EnablePostTpGate=true \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=1.5 \
  --RiskPerTradePercent=0.2 \
  --UseAtr=true \
  --AtrPeriod=14 \
  --AtrSlMultiplier=2.0 \
  --AtrTpMultiplier=3.5 \
  --BreakevenTriggerAtr=1.5 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.5 \
  --TrailDistanceAtr=1.5 \
  --MinSlAtr=1.0 \
  --MaxSlAtr=4.0 \
  --MinTpAtr=1.5 \
  --MaxTpAtr=8.0 \
  --MaxGivebackAtr=1.5 \
  --PostTpPullbackAtr=0.5 \
  --TrendTpDisabled=true

ETHUSD (M15 - New York Session / Crypto Momentum):

docker run -d \
  --name cbot-ethusd \
  --restart unless-stopped \
  --network host \
  -v $(pwd):/workspace \
  -v /root:/root \
  ghcr.io/spotware/ctrader-console:latest \
  run /workspace/cBot/AiAgentBot.algo \
  --ctid=your_email@example.com \
  --pwd-file=/root/ctrader_data/ctid_pwd \
  --account=YOUR_ACCOUNT_ID \
  --symbol=ETHUSD \
  --period=m15 \
  --full-access \
  --BotId="ethusd_m15" \
  --ApiUrl="http://127.0.0.1:8000/trade" \
  --AccountLabel="demo" \
  --TmsTimeFrame="Hour" \
  --EmaPeriod=5 \
  --SessionName="newyork" \
  --OrbStartHour=13 \
  --SessionEndHour=22 \
  --SessionDstRule="US" \
  --MinDecisiveBreakoutPips=80.0 \
  --MinOrWidthPips=150.0 \
  --OrbBufferPips=25.0 \
  --PartialCloseRatio=0.5 \
  --EnablePostTpGate=true \
  --BounceTradeEnabled=true \
  --BounceDistanceThreshold=1.5 \
  --RiskPerTradePercent=0.2 \
  --UseAtr=true \
  --AtrPeriod=14 \
  --AtrSlMultiplier=2.0 \
  --AtrTpMultiplier=3.5 \
  --BreakevenTriggerAtr=1.5 \
  --BreakevenOffsetAtr=0.1 \
  --TrailTriggerAtr=2.5 \
  --TrailDistanceAtr=1.5 \
  --MinSlAtr=1.0 \
  --MaxSlAtr=4.0 \
  --MinTpAtr=1.5 \
  --MaxTpAtr=8.0 \
  --MaxGivebackAtr=1.5 \
  --PostTpPullbackAtr=0.5 \
  --TrendTpDisabled=true

5. Start Trading! 🎉

The bot will automatically:

Calculate indicators on each bar close
Send market snapshot to AI server
Receive trading decision
Execute trades with risk management

📈 Trading Strategy

TMS (Trend Momentum Signal)

TMS identifies the directional bias using three confirmations:

Indicator	Bullish Signal	Bearish Signal
TDI	Green > Red	Green < Red
Heiken Ashi	Green candle	Red candle
Stochastic	K > D	K < D

Key Concept: Bias is locked until next cross, preventing whipsaws.

ORB (Opening Range Breakout)

ORB provides precise entry timing:

Opening Range: High/Low of first 15 minutes of session
Breakout: Price closes beyond OR boundary
Decisive Filter: Breakout must be decisive (≥ MinDecisiveBreakoutPips, default 10.0 pips on XAUUSD)

Market Regime (Kaufman Efficiency Ratio)

The system computes real-time efficiency metrics to adapt its trading and exit behavior:

er_session & er_recent: Kaufman Efficiency Ratio ($ER = \frac{|\text{Net Move}|}{\sum |\text{Bar Moves}|}$). $1.0$ represents a clean directional move, while $\approx 0.0$ indicates chop.
or_flips: Counts failed breakouts outside the Opening Range that close back inside (indicates chop day).
Regimes:
- trending ($ER \ge 0.35$): Disables fixed TP (TrendTpDisabled = true), lets Trailing SL and Giveback Floor capture the full trend run.
- choppy (or_flips \ge 5): High risk of stop-hunting traps → Cycle Gate forces HOLD.
- mixed: Standard trading discipline; entries only on confirmed setups.
- forming: Early session range formation ($< 6$ bars).

Quantitative Edge-Case Rules

BIAS-FRESH Exception: When a TDI cross just occurred ($\le 1$ bar ago), early momentum is treated as the start of a fresh trend leg, not an extended move → Favors entering immediately.
Anti-Chase Rule: When price broke out $\ge 4$ bars ago under an old bias without a pullback, DO NOT chase at extremes → Holds and waits for a pullback.
Position Memory & Giveback Floor: Tracks Peak Profit ($MFE$) on every tick. If floating profit drops below the maximum giveback threshold, the position is closed immediately to lock in gains.

Entry Rules

IF TMS_BULLISH AND ORB_BREAKOUT_UP AND DECISIVE:
    → BUY
    
IF TMS_BEARISH AND ORB_BREAKOUT_DOWN AND DECISIVE:
    → SELL
    
ELSE:
    → HOLD

Exit Rules

Condition	Action
TDI Green flat/hook/checkmark	CLOSE_ALL
Bias reverses	Auto close
Session ends (EOD)	Auto close (EOD Force-Flatten safety net)
Profit ≥ 1.2x ATR	Move SL to breakeven (+0.1x ATR offset)
Profit ≥ 2.0x ATR	Trail SL by 1.0x ATR
Giveback ≥ 1.0x ATR	Auto close (Max giveback protection)

⚙️ Configuration

cBot Parameters

TMS Settings (Multi-Timeframe)

Parameter	Default	Description
TMS Timeframe (Macro)	Hour (H1)	Macro trend bias timeframe (H1, H4, M15, etc.)
RSI Period	6	RSI calculation period
Red Period	6	Signal line period

Stochastic Settings

Parameter	Default	Description
%K Period	6	Fast stochastic
%D Period	6	Slow stochastic
Slowing	4	Smoothing factor

Entry Filters

Parameter	Default	Description
Max Bars After Cross	5	Entry window
Min Angle Delta	0.0	Angle filter (0=off)
Min Decisive Breakout	10.0 pips	Breakout strength (default tuned for XAUUSD)

Exit Management

Parameter	Default	Description
Flat Threshold	0.01	TDI flatness
Breakeven Trigger	30.0 pips	Profit to move SL
Breakeven Offset	2.0 pips	Profit locked at breakeven
Trail Trigger	50.0 pips	Profit to start trailing
Trail Distance	25.0 pips	SL distance from price

Session

Parameter	Default	Description
Session Start Hour	13 (UTC)	New York open (Winter UTC)
Session End Hour	21 (UTC)	New York close (EOD force-flatten)
Opening Range	15 min	OR calculation window
Min OR Width	20.0 pips	Minimum OR width
ORB Buffer	3.0 pips	Buffer to avoid fakeouts
DST Rule	US	Auto daylight saving adjustment

Risk Management (Dynamic Sizing & ATR)

Parameter	Default	Description
Use ATR for SL/TP	true	Calculate dynamic SL/TP based on ATR
ATR Period	14	Period for ATR calculation
ATR SL Multiplier	1.5	Multiplier for ATR Stop Loss distance
ATR TP Multiplier	2.0	Multiplier for ATR Take Profit distance
Risk per Trade (%)	0.2	Percentage of balance risked per trade

Guardrails

Parameter	Default	Description
Min SL	20.0 pips	Minimum stop loss
Max SL	80.0 pips	Maximum stop loss
Min TP	30.0 pips	Minimum take profit
Max TP	250.0 pips	Maximum take profit
Max Giveback	30.0 pips	Giveback threshold to force close
Max Loss Streak	3	Block after N losses
Bias Flip Exit	true	Auto close on bias change
Trend TP Disabled	true	Disable fixed TP in trending regime

📊 Recommended Presets by Symbol

Cryptocurrency

Parameter	BTCUSD	ETHUSD
Trading Session	New York	New York
DST Rule	`US`	`US`
Min Decisive Breakout	`150.0 pips`	`80.0 pips`
Min OR Width	`300.0 pips`	`150.0 pips`
ORB Buffer	`50.0 pips`	`25.0 pips`
Breakeven Trigger	`1.5x ATR`	`1.5x ATR`
Breakeven Offset	`0.1x ATR`	`0.1x ATR`
Trail Trigger	`2.5x ATR`	`2.5x ATR`
Trail Distance	`1.5x ATR`	`1.5x ATR`
Min SL / Max SL	`1.0x / 4.0x ATR`	`1.0x / 4.0x ATR`
Min TP / Max TP	`1.5x / 8.0x ATR`	`1.5x / 8.0x ATR`
Max Giveback	`1.5x ATR`	`1.5x ATR`
Recommended Timeframe	`M15`	`M15`
EMA Period	`5`	`5`
Post-TP Gate / Pullback	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)
TDI Bounce Trade	`1.5`	`1.5`
Partial Close at BE	`0.5 (50%)`	`0.5 (50%)`
Risk per Trade	`0.2%`	`0.2%`
Use ATR for SL/TP	`true`	`true`
ATR Period	`14`	`14`
ATR SL Multiplier	`2.0x ATR`	`2.0x ATR`
ATR TP Multiplier	`3.5x ATR`	`3.5x ATR`

Metals & Indices

Parameter	XAUUSD	US30	USTEC	DE40
Trading Session	New York	New York (Index)	New York (Index)	London
DST Rule	`US`	`US`	`US`	`Europe`
Min Decisive Breakout	`100.0 pips`	`100.0 pips`	`80.0 pips`	`70.0 pips`
Min OR Width	`250.0 pips`	`300.0 pips`	`250.0 pips`	`200.0 pips`
ORB Buffer	`30.0 pips`	`50.0 pips`	`40.0 pips`	`35.0 pips`
Breakeven Trigger	`1.2x ATR`	`2.0x ATR`	`2.0x ATR`	`2.0x ATR`
Breakeven Offset	`0.1x ATR`	`0.1x ATR`	`0.1x ATR`	`0.1x ATR`
Trail Trigger	`2.0x ATR`	`3.0x ATR`	`3.0x ATR`	`3.0x ATR`
Trail Distance	`1.0x ATR`	`1.5x ATR`	`1.5x ATR`	`1.5x ATR`
Min SL / Max SL	`0.8x / 3.0x ATR`	`1.5x / 4.5x ATR`	`1.5x / 4.5x ATR`	`1.5x / 4.5x ATR`
Min TP / Max TP	`1.0x / 6.0x ATR`	`2.0x / 8.0x ATR`	`2.0x / 8.0x ATR`	`2.0x / 8.0x ATR`
Max Giveback	`1.0x ATR`	`1.5x ATR`	`1.5x ATR`	`1.5x ATR`
Recommended Timeframe	`M15`	`M15`	`M5`	`M15`
EMA Period	`5`	`5`	`5`	`5`
Post-TP Gate / Pullback	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)
TDI Bounce Trade	`1.5`	`1.5`	`1.5`	`1.5`
Partial Close at BE	`0.5 (50%)`	`0.5 (50%)`	`0.5 (50%)`	`0.5 (50%)`
Risk per Trade	`0.2%`	`0.2%`	`0.2%`	`0.2%`
Use ATR for SL/TP	`true`	`true`	`true`	`true`
ATR Period	`14`	`14`	`14`	`14`
ATR SL Multiplier	`1.5x ATR`	`2.5x ATR`	`2.5x ATR`	`2.5x ATR`
ATR TP Multiplier	`2.0x ATR`	`3.5x ATR`	`3.5x ATR`	`3.5x ATR`

Forex Majors

Parameter	EURUSD	GBPUSD	USDJPY	USDCAD
Trading Session	London	London	Tokyo	New York
DST Rule	`Europe`	`Europe`	`None`	`US`
Min Decisive Breakout	`2.5 pips`	`3.5 pips`	`3.0 pips`	`3.5 pips`
Min OR Width	`5.0 pips`	`7.0 pips`	`5.0 pips`	`7.0 pips`
ORB Buffer	`1.0 pips`	`1.2 pips`	`1.0 pips`	`1.2 pips`
Breakeven Trigger	`1.2x ATR`	`1.2x ATR`	`1.2x ATR`	`1.2x ATR`
Breakeven Offset	`0.1x ATR`	`0.1x ATR`	`0.1x ATR`	`0.1x ATR`
Trail Trigger	`2.0x ATR`	`2.0x ATR`	`2.0x ATR`	`2.0x ATR`
Trail Distance	`1.0x ATR`	`1.0x ATR`	`1.0x ATR`	`1.0x ATR`
Min SL / Max SL	`0.8x / 3.0x ATR`	`0.8x / 3.0x ATR`	`0.8x / 3.0x ATR`	`0.8x / 3.0x ATR`
Min TP / Max TP	`1.0x / 6.0x ATR`	`1.0x / 6.0x ATR`	`1.0x / 6.0x ATR`	`1.0x / 6.0x ATR`
Max Giveback	`1.0x ATR`	`1.0x ATR`	`1.0x ATR`	`1.0x ATR`
Recommended Timeframe	`M15`	`M15`	`M15`	`M15`
EMA Period	`5`	`5`	`5`	`5`
Post-TP Gate / Pullback	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)
TDI Bounce Trade	`1.5`	`1.5`	`1.5`	`1.5`
Partial Close at BE	`0.5 (50%)`	`0.5 (50%)`	`0.5 (50%)`	`0.5 (50%)`
Risk per Trade	`0.2%`	`0.2%`	`0.2%`	`0.2%`
Use ATR for SL/TP	`true`	`true`	`true`	`true`
ATR Period	`14`	`14`	`14`	`14`
ATR SL Multiplier	`1.5x ATR`	`1.5x ATR`	`1.5x ATR`	`1.5x ATR`
ATR TP Multiplier	`2.0x ATR`	`2.0x ATR`	`2.0x ATR`	`2.0x ATR`

Forex Crosses

Parameter	GBPJPY	EURJPY	AUDJPY
Trading Session	London	London	Tokyo
DST Rule	`Europe`	`Europe`	`None`
Min Decisive Breakout	`5.0 pips`	`4.0 pips`	`3.0 pips`
Min OR Width	`10.0 pips`	`8.0 pips`	`5.0 pips`
ORB Buffer	`1.5 pips`	`1.2 pips`	`1.0 pips`
Breakeven Trigger	`1.2x ATR`	`1.2x ATR`	`1.2x ATR`
Breakeven Offset	`0.1x ATR`	`0.1x ATR`	`0.1x ATR`
Trail Trigger	`2.0x ATR`	`2.0x ATR`	`2.0x ATR`
Trail Distance	`1.0x ATR`	`1.0x ATR`	`1.0x ATR`
Min SL / Max SL	`0.8x / 3.0x ATR`	`0.8x / 3.0x ATR`	`0.8x / 3.0x ATR`
Min TP / Max TP	`1.0x / 6.0x ATR`	`1.0x / 6.0x ATR`	`1.0x / 6.0x ATR`
Max Giveback	`1.0x ATR`	`1.0x ATR`	`1.0x ATR`
Recommended Timeframe	`M15`	`M15`	`M15`
EMA Period	`5`	`5`	`5`
Post-TP Gate / Pullback	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)	`true` (`0.5x ATR`)
TDI Bounce Trade	`1.5`	`1.5`	`1.5`
Partial Close at BE	`0.5 (50%)`	`0.5 (50%)`	`0.5 (50%)`
Risk per Trade	`0.2%`	`0.2%`	`0.2%`
Use ATR for SL/TP	`true`	`true`	`true`
ATR Period	`14`	`14`	`14`
ATR SL Multiplier	`1.5x ATR`	`1.5x ATR`	`1.5x ATR`
ATR TP Multiplier	`2.0x ATR`	`2.0x ATR`	`2.0x ATR`

Portfolio Manager Settings

Edit app/portfolio.py:

class PortfolioConfig:
    MAX_POSITIONS = 4              # Max open positions
    MAX_CURRENCY_EXPOSURE = 2      # Max positions per currency
    MAX_CORRELATED_POSITIONS = 2   # Max correlated positions
    MAX_DAILY_LOSS = -200.0        # Daily loss limit (USD)
    MAX_MARGIN_USAGE_PCT = 50.0    # Max margin usage

📡 API Documentation

POST /trade

Main endpoint for trading decisions.

Request (from cBot):

{
  "bot_id": "eurusd_bot",
  "symbol": "EURUSD",
  "timeframe": "M15",
  "ask": 1.0850,
  "bid": 1.0848,
  "bars": [
    {"ha_color": "Green", "tdi_green": 55.2, "tdi_red": 52.1, "stoch_k": 75.0, "stoch_d": 70.0},
    {"ha_color": "Green", "tdi_green": 54.8, "tdi_red": 51.9, "stoch_k": 72.0, "stoch_d": 68.0},
    {"ha_color": "Red", "tdi_green": 53.5, "tdi_red": 52.5, "stoch_k": 65.0, "stoch_d": 62.0}
  ],
  "tms": {
    "bias": "BULLISH",
    "bars_since_cross": 2,
    "long_entry": true,
    "short_entry": false,
    "green_tf_value": 55.2,
    "green_tf_slope": 0.4
  },
  "orb": {
    "or_high": 1.0845,
    "or_low": 1.0830,
    "breakout_direction": "up",
    "breakout_distance_pips": 5.0,
    "is_decisive": true,
    "bars_since_breakout": 1
  },
  "position": null,
  "session": {
    "phase": "active",
    "minutes_to_end": 180
  }
}

Response (from AI):

{
  "action": "BUY",
  "volume_lots": 0.01,
  "sl_pips": 0,
  "tp_pips": 0,
  "reason": "TMS BULLISH bias confirmed, ORB decisive breakout UP (+5.0p), momentum rising"
}

Note: sl_pips / tp_pips returned by the LLM are ignored by the cBot when UseAtr = true (default). The cBot computes SL/TP dynamically from ATR (SL = AtrSlMultiplier × ATR, TP = AtrTpMultiplier × ATR, clamped by ATR-based Min/Max guardrails), then applies risk-based position sizing. The LLM decides direction (action), timing, and a relative volume_lots suggestion only.

POST /portfolio/report

Report position changes for portfolio tracking.

{
  "bot_id": "eurusd_bot",
  "action": "open",
  "symbol": "EURUSD",
  "side": "BUY",
  "volume": 0.01,
  "entry_price": 1.0850,
  "sl_pips": 10.0,
  "tp_pips": 20.0
}

GET /portfolio/status

Get current portfolio status.

curl http://127.0.0.1:8000/portfolio/status

🛠️ Development

Project Structure

AgentFxTrading/
├── app/
│   ├── llm_client.py      # LLM abstraction layer
│   ├── server.py          # FastAPI server
│   └── portfolio.py       # Portfolio risk management
├── cBot/
│   └── AiAgentBot.cs      # cTrader cBot
├── .env.example           # Environment template
├── requirements.txt       # Python dependencies
├── README.md              # Documentation (6 languages)
└── portfolio.db           # SQLite database (auto-created)

Adding New LLM Provider

Create new class in app/llm_client.py:

class NewProviderClient(LLMClient):
    def __init__(self, api_key: str, model: str):
        # Initialize client
        pass
    
    async def chat(self, messages: List[Dict[str, str]], **kwargs) -> str:
        # Implement chat logic
        pass

Update create_llm_client():

elif provider == "newprovider":
    return NewProviderClient(
        api_key=os.getenv("NEWPROVIDER_API_KEY"),
        model=os.getenv("LLM_MODEL")
    )

Improving the Prompt

Edit SYSTEM_PROMPT in app/server.py to adjust trading logic.

📊 Performance

Backtest Results

⚠️ Disclaimer: Past performance does not guarantee future results. Always test with demo account first.

Metric	Value
Win Rate	~55-65%
Risk/Reward	1:2 average
Max Drawdown	~15%
Sharpe Ratio	~1.2

Live Trading Tips

Start with Demo: Always test strategy first
Small Position Size: Start with 0.01 lots
Monitor Daily: Check portfolio status regularly
Adjust Parameters: Tune based on market conditions
Risk Management: Never risk more than 2% per trade

🤝 Contributing

Contributions are welcome! Here's how you can help:

Ways to Contribute

Star the repo ⭐ - Shows support
Report bugs 🐛 - Open an issue
Suggest features 💡 - Open a feature request
Submit PRs 🔧 - Code contributions
Improve docs 📚 - Documentation improvements
Share results 📈 - Share your backtest/live results

Development Guidelines

Follow existing code style
Write tests for new features
Update documentation
Keep PRs focused and small

Community

💬 Discussions
🐛 Issues
📧 Email: senior1206@gmail.com

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

TMS Strategy: Based on professional TMS methodology
cTrader: For providing excellent API
Open Source Community: For amazing libraries and tools

📈 Star History

If you find this project useful, please consider giving it a ⭐!

⬆ Back to Top

Name		Name	Last commit message	Last commit date
app		app
cBot		cBot
static		static
templates		templates
.env.example		.env.example
.gitignore		.gitignore
README.ja.md		README.ja.md
README.md		README.md
README.pt.md		README.pt.md
README.ru.md		README.ru.md
README.vi.md		README.vi.md
README.zh.md		README.zh.md
apply_optimized_presets.py		apply_optimized_presets.py
generate_readme_tables.py		generate_readme_tables.py
patch.py		patch.py
patch_js.sh		patch_js.sh
patch_ui.sh		patch_ui.sh
requirements.txt		requirements.txt
tables.md		tables.md
update_db.py		update_db.py
update_readmes.py		update_readmes.py

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