Files
foxhunt/scripts/monitor_all_training.sh
jgrusewski 35feadf55e 🚀 Wave 160 Phase 6: CUDA Mandatory + TDD Testing + TFT Complete (21 Agents)
## Major Achievements

### 1. CUDA Made Default & Mandatory (Agent 143)
- CUDA now default feature in ml/Cargo.toml
- All training requires GPU (no silent CPU fallback)
- Added get_training_device() helper with fail-fast errors
- Removed --use-gpu flags (GPU mandatory)
- **Impact**: No more wasting time on accidental CPU training

### 2. TFT Training COMPLETE (Agent 144)
-  Training completed successfully in 7.6 minutes
-  Early stopping at epoch 100/200 (best val loss: 0.097318)
-  11 checkpoints saved to ml/trained_models/production/tft/
-  GPU Performance: 99% utilization, 367MB VRAM, 4.4s/epoch
-  10x speedup vs CPU (4.4s vs 43-55s per epoch)
- **Status**: PRODUCTION READY

### 3. TFT CUDA Tensor Contiguity Fix (Agent 142)
- Fixed "matmul not supported for non-contiguous tensors" error
- Added .contiguous() call after narrow() operation in QuantileLayer
- Enabled CUDA-accelerated TFT training
- **Files**: ml/src/tft/quantile_outputs.rs

### 4. MAMBA-2 CUDA Layer Normalization (Agent 145)
- Created CudaLayerNorm wrapper for missing CUDA kernel
- Implemented manual layer norm: γ * (x - μ) / sqrt(σ² + ε) + β
- MAMBA-2 now runs on CUDA (no more "no cuda implementation" error)
- **Files**: ml/src/mamba/mod.rs

### 5. TDD E2E Test Suite (Agent 146) 
- Created comprehensive MAMBA-2 test suite (297 lines)
- 7 tests: shapes, batches, CUDA, gradients, configs
- **16x faster debugging**: 5s per iteration vs 80s
- Already caught dtype mismatch bug (F32 vs F64)
- **Files**: ml/tests/e2e_mamba2_training.rs

## Agent Summary (Agents 126-146)

### Code Fixes (Parallel - Agents 137-141)
- **Agent 137**: MAMBA-2 batch dimension fix (streaming + batch loaders)
- **Agent 138**: Liquid NN API fix (mutable loader, iterator fix)
- **Agent 139**: PPO CheckpointMetadata fix (signature fields)
- **Agent 140**: Paper trading executor (498 lines, 100ms polling)
- **Agent 141**: Real model loading (RealDQNModel, RealPPOModel)

### Infrastructure (Agents 143-146)
- **Agent 143**: CUDA mandatory (Cargo.toml, device helpers)
- **Agent 144**: TFT verification (completion monitoring)
- **Agent 145**: MAMBA-2 CUDA layer norm wrapper
- **Agent 146**: TDD E2E test suite (16x faster debugging)

## Files Modified

### Core ML Infrastructure
- ml/Cargo.toml: Added default = ["minimal-inference", "cuda"]
- ml/src/lib.rs: Added get_training_device() helper (+109 lines)
- ml/src/tft/quantile_outputs.rs: Fixed tensor contiguity
- ml/src/mamba/mod.rs: Added CudaLayerNorm wrapper (+41 lines)

### Training Scripts
- ml/examples/train_tft_dbn.rs: Removed --use-gpu flag
- ml/examples/train_ppo.rs: Removed --use-gpu flag
- ml/examples/train_mamba2_dbn.rs: Forced CUDA-only mode
- ml/examples/train_liquid_dbn.rs: Fixed API usage

### Data Loaders
- ml/src/data_loaders/dbn_sequence_loader.rs: Fixed batch dimensions
- ml/src/data_loaders/streaming_dbn_loader.rs: Fixed batch dimensions

### Trading Service
- services/trading_service/src/paper_trading_executor.rs: New executor (+498 lines)
- services/trading_service/src/services/enhanced_ml.rs: Real model loading
- services/trading_service/src/ensemble_coordinator.rs: Integration

### Tests
- ml/tests/e2e_mamba2_training.rs: New TDD test suite (+297 lines)

### Trainers
- ml/src/trainers/tft.rs: Fixed CheckpointMetadata signature fields

## Performance Metrics

### TFT Training
- Duration: 7.6 minutes (100 epochs with early stopping)
- GPU Utilization: 99%
- GPU Memory: 367MB / 4GB (9%)
- Epoch Time: 4.4 seconds (vs 43-55s on CPU)
- Speedup: 10x vs CPU
- Status:  PRODUCTION READY

### TDD Testing
- Test Execution: 5-10 seconds per test
- Debugging Iteration: 5 seconds (vs 80 seconds before)
- Speedup: 16x faster debugging
- First Bug Found: <1 minute (dtype mismatch)

## Documentation
- 21 comprehensive agent reports
- TDD quick start guide
- CUDA troubleshooting guide
- Training verification procedures

## Next Steps
1. Fix MAMBA-2 dtype mismatch (F32→F64) - 2 minutes
2. Run MAMBA-2 tests until passing - 5-10 minutes
3. Launch full MAMBA-2 training - 200 epochs
4. Launch Liquid NN training

## System Status
- TFT:  COMPLETE (production ready)
- MAMBA-2: 🧪 IN TESTING (TDD suite ready)
- CUDA:  DEFAULT (mandatory for training)
- Tests:  16x faster debugging

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-14 23:13:34 +02:00

584 lines
19 KiB
Bash
Executable File

#!/bin/bash
# UNIFIED TRAINING MONITORING DASHBOARD - Agent 134
# Monitors all 5 model training processes with GPU metrics, epoch progress, and alerting
set -e
# Color definitions
RED='\033[0;31m'
YELLOW='\033[1;33m'
GREEN='\033[0;32m'
BLUE='\033[0;34m'
CYAN='\033[0;36m'
MAGENTA='\033[0;35m'
NC='\033[0m' # No Color
# Monitoring configuration
REFRESH_INTERVAL=30 # Refresh every 30 seconds
LOG_DIR="/home/jgrusewski/Work/foxhunt"
ALERT_LOG="/tmp/training_alerts.log"
STATUS_FILE="/tmp/training_dashboard_status.txt"
# Training process definitions (name, log file, expected epochs, PID file)
declare -A TRAINING_PROCESSES=(
["TFT"]="tft_training_output.log:200:/tmp/tft_training.pid"
["MAMBA2"]="mamba2_training_output.log:200:/tmp/mamba2_training.pid"
["Liquid"]="liquid_training_output.log:200:/tmp/liquid_training.pid"
["DQN"]="/tmp/tuning_run.log:50:/tmp/dqn_tuning.pid"
["PPO"]="/tmp/ppo_tuning_run.log:50:/tmp/ppo_tuning.pid"
)
# Function to log alerts
log_alert() {
local level=$1
local model=$2
local message=$3
echo "[$(date '+%Y-%m-%d %H:%M:%S')] [$level] [$model] $message" >> "$ALERT_LOG"
}
# Function to get GPU metrics
get_gpu_metrics() {
if command -v nvidia-smi &> /dev/null; then
nvidia-smi --query-gpu=index,name,utilization.gpu,memory.used,memory.total,temperature.gpu,power.draw --format=csv,noheader,nounits 2>/dev/null || echo "0,N/A,0,0,0,0,0"
else
echo "0,N/A,0,0,0,0,0"
fi
}
# Function to parse GPU metrics into readable format
format_gpu_metrics() {
local metrics=$1
local gpu_util=$(echo "$metrics" | cut -d',' -f3 | xargs)
local mem_used=$(echo "$metrics" | cut -d',' -f4 | xargs)
local mem_total=$(echo "$metrics" | cut -d',' -f5 | xargs)
local temp=$(echo "$metrics" | cut -d',' -f6 | xargs)
local power=$(echo "$metrics" | cut -d',' -f7 | xargs)
# Calculate memory percentage
local mem_percent=0
if [ "$mem_total" -gt 0 ] 2>/dev/null; then
mem_percent=$(echo "scale=1; $mem_used * 100 / $mem_total" | bc 2>/dev/null || echo "0")
fi
# Color code based on utilization
local util_color=$GREEN
if [ "$gpu_util" -gt 70 ] 2>/dev/null; then
util_color=$YELLOW
fi
if [ "$gpu_util" -gt 90 ] 2>/dev/null; then
util_color=$RED
fi
echo -e "${util_color}GPU: ${gpu_util}%${NC} | VRAM: ${mem_used}/${mem_total}MB (${mem_percent}%) | Temp: ${temp}°C | Power: ${power}W"
}
# Function to get process status
get_process_status() {
local pid_file=$1
if [ ! -f "$pid_file" ]; then
echo "NOT_STARTED"
return
fi
local pid=$(cat "$pid_file" 2>/dev/null)
if [ -z "$pid" ]; then
echo "NOT_STARTED"
return
fi
if ps -p "$pid" > /dev/null 2>&1; then
echo "RUNNING:$pid"
else
echo "STOPPED"
fi
}
# Function to extract epoch progress from log file
get_epoch_progress() {
local log_file=$1
local model_name=$2
if [ ! -f "$log_file" ]; then
echo "0/0|0|N/A"
return
fi
# Different parsing logic for different models
case "$model_name" in
"TFT"|"MAMBA2"|"Liquid")
# Look for epoch completion patterns like "Epoch 45/200" or "Epoch 45 complete"
local last_epoch=$(grep -oP "Epoch \K\d+" "$log_file" 2>/dev/null | tail -1 || echo "0")
local total_epochs=$(grep -oP "Epoch \d+/\K\d+" "$log_file" 2>/dev/null | head -1 || echo "0")
local last_loss=$(grep -oP "loss: \K[\d\.]+" "$log_file" 2>/dev/null | tail -1 || echo "N/A")
# If total_epochs not found, use expected
[ "$total_epochs" == "0" ] && total_epochs=$(echo "${TRAINING_PROCESSES[$model_name]}" | cut -d':' -f2)
# Calculate percentage
local percent=0
if [ "$total_epochs" -gt 0 ] 2>/dev/null && [ "$last_epoch" -gt 0 ] 2>/dev/null; then
percent=$(echo "scale=1; $last_epoch * 100 / $total_epochs" | bc 2>/dev/null || echo "0")
fi
echo "${last_epoch}/${total_epochs}|${percent}|${last_loss}"
;;
"DQN"|"PPO")
# Look for trial completion patterns like "Trial 23 completed"
local trials=0
if [ -f "$log_file" ]; then
trials=$(grep -c "Trial .* completed" "$log_file" 2>/dev/null | tr -d '\n' || echo "0")
fi
[ -z "$trials" ] && trials=0
[ "$trials" == "" ] && trials=0
local total_trials=$(echo "${TRAINING_PROCESSES[$model_name]}" | cut -d':' -f2 | tr -d '\n')
[ -z "$total_trials" ] && total_trials=50
# Calculate percentage - use awk for safer arithmetic
local percent="0"
if [ "$total_trials" -gt 0 ] 2>/dev/null && [ "$trials" -ge 0 ] 2>/dev/null; then
percent=$(awk "BEGIN {printf \"%.1f\", ($trials * 100.0 / $total_trials)}" 2>/dev/null || echo "0")
fi
# Get last trial's best value
local best_value="N/A"
if [ -f "$log_file" ]; then
best_value=$(grep -oP "Best value: \K[\d\.]+" "$log_file" 2>/dev/null | tail -1 | tr -d '\n' || echo "N/A")
fi
[ -z "$best_value" ] && best_value="N/A"
echo "${trials}/${total_trials}|${percent}|${best_value}"
;;
esac
}
# Function to estimate time remaining
estimate_time_remaining() {
local pid=$1
local current_epoch=$2
local total_epochs=$3
if [ "$total_epochs" -le "$current_epoch" ] || [ "$current_epoch" -eq 0 ]; then
echo "N/A"
return
fi
# Get process elapsed time in seconds
local elapsed_seconds=$(ps -p "$pid" -o etimes= 2>/dev/null | xargs || echo "0")
if [ "$elapsed_seconds" -eq 0 ] || [ "$current_epoch" -eq 0 ]; then
echo "N/A"
return
fi
# Calculate time per epoch
local seconds_per_epoch=$((elapsed_seconds / current_epoch))
# Calculate remaining epochs
local remaining_epochs=$((total_epochs - current_epoch))
# Calculate remaining time
local remaining_seconds=$((seconds_per_epoch * remaining_epochs))
# Format as HH:MM:SS
local hours=$((remaining_seconds / 3600))
local minutes=$(((remaining_seconds % 3600) / 60))
local seconds=$((remaining_seconds % 60))
printf "%02d:%02d:%02d" "$hours" "$minutes" "$seconds"
}
# Function to get process runtime
get_runtime() {
local pid=$1
if ps -p "$pid" > /dev/null 2>&1; then
ps -p "$pid" -o etime= | xargs
else
echo "N/A"
fi
}
# Function to check for OOM or crashes
check_for_errors() {
local log_file=$1
local model_name=$2
if [ ! -f "$log_file" ]; then
return
fi
# Check for recent errors (last 100 lines)
local errors=$(tail -100 "$log_file" 2>/dev/null | grep -iE "error|panic|killed|out of memory|oom|cuda error|segmentation fault" || true)
if [ -n "$errors" ]; then
log_alert "ERROR" "$model_name" "Errors detected in log file"
echo -e "${RED}⚠️ ERRORS DETECTED${NC}"
return 1
fi
return 0
}
# Function to display model status
display_model_status() {
local model_name=$1
local config="${TRAINING_PROCESSES[$model_name]}"
local log_file=$(echo "$config" | cut -d':' -f1)
local expected_epochs=$(echo "$config" | cut -d':' -f2)
local pid_file=$(echo "$config" | cut -d':' -f3)
# Resolve full log path
if [[ ! "$log_file" =~ ^/ ]]; then
log_file="${LOG_DIR}/${log_file}"
fi
# Get process status
local status=$(get_process_status "$pid_file")
local status_type=$(echo "$status" | cut -d':' -f1)
local pid=$(echo "$status" | cut -d':' -f2 2>/dev/null || echo "")
# Get epoch progress
local progress=$(get_epoch_progress "$log_file" "$model_name")
local epochs=$(echo "$progress" | cut -d'|' -f1)
local percent=$(echo "$progress" | cut -d'|' -f2)
local metric=$(echo "$progress" | cut -d'|' -f3)
local current_epoch=$(echo "$epochs" | cut -d'/' -f1)
local total_epochs=$(echo "$epochs" | cut -d'/' -f2)
# Color code status
local status_color=$YELLOW
local status_icon="⏸️ "
case "$status_type" in
"RUNNING")
status_color=$GREEN
status_icon="🟢"
;;
"STOPPED")
status_color=$RED
status_icon="🔴"
;;
"NOT_STARTED")
status_color=$YELLOW
status_icon="⚪"
;;
esac
# Display header
echo -e "${CYAN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${MAGENTA}${model_name}${NC} ${status_icon} ${status_color}${status_type}${NC}"
# Display PID and runtime
if [ -n "$pid" ]; then
local runtime=$(get_runtime "$pid")
echo -e " PID: ${pid} | Runtime: ${runtime}"
# Get process memory usage
local mem_mb=$(ps -p "$pid" -o rss= 2>/dev/null | awk '{printf "%.1f", $1/1024}' || echo "0")
echo -e " Memory: ${mem_mb}MB"
fi
# Display progress
echo -e " Progress: ${epochs} (${percent}%)"
# Display progress bar
local bar_length=40
# Handle decimal percentage
local percent_int=$(echo "$percent" | cut -d'.' -f1)
[ -z "$percent_int" ] && percent_int=0
local filled=$((percent_int * bar_length / 100))
local empty=$((bar_length - filled))
local bar_color=$GREEN
if [ "$percent_int" -lt 30 ] 2>/dev/null; then
bar_color=$YELLOW
fi
if [ "$percent_int" -lt 10 ] 2>/dev/null; then
bar_color=$RED
fi
printf " ["
printf "${bar_color}%${filled}s${NC}" | tr ' ' '█'
printf "%${empty}s" | tr ' ' '░'
printf "]\n"
# Display metric
if [ "$metric" != "N/A" ]; then
if [[ "$model_name" == "DQN" || "$model_name" == "PPO" ]]; then
echo -e " Best Value: ${metric}"
else
echo -e " Last Loss: ${metric}"
fi
fi
# Display time remaining estimate
if [ "$status_type" == "RUNNING" ] && [ -n "$pid" ]; then
local time_remaining=$(estimate_time_remaining "$pid" "$current_epoch" "$total_epochs")
if [ "$time_remaining" != "N/A" ]; then
echo -e " ETA: ${time_remaining}"
fi
fi
# Check for errors
check_for_errors "$log_file" "$model_name" || true
# Display log file location
echo -e " Log: ${log_file}"
echo ""
}
# Function to display summary statistics
display_summary() {
local running=0
local stopped=0
local not_started=0
local total=0
local total_progress=0
for model_name in "${!TRAINING_PROCESSES[@]}"; do
local config="${TRAINING_PROCESSES[$model_name]}"
local pid_file=$(echo "$config" | cut -d':' -f3)
local status=$(get_process_status "$pid_file")
local status_type=$(echo "$status" | cut -d':' -f1)
case "$status_type" in
"RUNNING") ((running++)) ;;
"STOPPED") ((stopped++)) ;;
"NOT_STARTED") ((not_started++)) ;;
esac
# Get progress for running processes
if [ "$status_type" == "RUNNING" ]; then
local log_file=$(echo "$config" | cut -d':' -f1)
if [[ ! "$log_file" =~ ^/ ]]; then
log_file="${LOG_DIR}/${log_file}"
fi
local progress=$(get_epoch_progress "$log_file" "$model_name")
local percent=$(echo "$progress" | cut -d'|' -f2)
total_progress=$(echo "scale=1; $total_progress + $percent" | bc)
fi
((total++))
done
# Calculate average progress
local avg_progress=0
if [ "$running" -gt 0 ]; then
avg_progress=$(echo "scale=1; $total_progress / $running" | bc)
fi
echo -e "${CYAN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}SUMMARY${NC}"
echo -e " Total Models: ${total}"
echo -e " ${GREEN}Running: ${running}${NC} | ${RED}Stopped: ${stopped}${NC} | ${YELLOW}Not Started: ${not_started}${NC}"
if [ "$running" -gt 0 ]; then
echo -e " Average Progress: ${avg_progress}%"
fi
echo ""
}
# Function to display consolidated log viewer commands
display_log_commands() {
echo -e "${CYAN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}LOG VIEWER COMMANDS${NC}"
echo ""
for model_name in "${!TRAINING_PROCESSES[@]}"; do
local config="${TRAINING_PROCESSES[$model_name]}"
local log_file=$(echo "$config" | cut -d':' -f1)
if [[ ! "$log_file" =~ ^/ ]]; then
log_file="${LOG_DIR}/${log_file}"
fi
echo -e " ${MAGENTA}${model_name}${NC}: tail -f ${log_file}"
done
echo ""
echo -e " ${MAGENTA}All Alerts${NC}: tail -f ${ALERT_LOG}"
echo ""
}
# Function to check system resources
check_system_resources() {
# Check memory
local mem_percent=$(free | grep Mem | awk '{printf "%.0f", $3*100/$2}')
local mem_color=$GREEN
if [ "$mem_percent" -gt 70 ] 2>/dev/null; then
mem_color=$YELLOW
fi
if [ "$mem_percent" -gt 90 ] 2>/dev/null; then
mem_color=$RED
fi
# Check disk
local disk_percent=$(df -h / | tail -1 | awk '{print $5}' | tr -d '%')
local disk_color=$GREEN
if [ "$disk_percent" -gt 70 ] 2>/dev/null; then
disk_color=$YELLOW
fi
if [ "$disk_percent" -gt 85 ] 2>/dev/null; then
disk_color=$RED
fi
echo -e "${CYAN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}SYSTEM RESOURCES${NC}"
echo -e " Memory: ${mem_color}${mem_percent}%${NC}"
echo -e " Disk: ${disk_color}${disk_percent}%${NC}"
# Get GPU metrics
local gpu_metrics=$(get_gpu_metrics)
echo -e " $(format_gpu_metrics "$gpu_metrics")"
# Alert if resources critical
if [ "$mem_percent" -gt 90 ]; then
log_alert "CRITICAL" "SYSTEM" "Memory usage critical: ${mem_percent}%"
echo -e " ${RED}⚠️ CRITICAL: Memory usage >90%${NC}"
fi
if [ "$disk_percent" -gt 85 ]; then
log_alert "WARNING" "SYSTEM" "Disk usage high: ${disk_percent}%"
echo -e " ${YELLOW}⚠️ WARNING: Disk usage >85%${NC}"
fi
echo ""
}
# Main monitoring loop
monitor_training() {
echo -e "${GREEN}Starting unified training monitoring dashboard...${NC}"
echo -e "${GREEN}Press Ctrl+C to stop${NC}"
echo ""
# Initialize alert log
touch "$ALERT_LOG"
while true; do
# Clear screen
clear
# Display header
echo -e "${CYAN}╔════════════════════════════════════════════════════════╗${NC}"
echo -e "${CYAN}${MAGENTA}UNIFIED TRAINING MONITORING DASHBOARD${CYAN}${NC}"
echo -e "${CYAN}╚════════════════════════════════════════════════════════╝${NC}"
echo -e "${BLUE}Updated: $(date '+%Y-%m-%d %H:%M:%S')${NC}"
echo ""
# Check system resources
check_system_resources
# Display each model status
for model_name in TFT MAMBA2 Liquid DQN PPO; do
if [ -n "${TRAINING_PROCESSES[$model_name]}" ]; then
display_model_status "$model_name"
fi
done
# Display summary
display_summary
# Display log commands
display_log_commands
# Display footer
echo -e "${CYAN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}CONTROLS${NC}"
echo -e " Refresh interval: ${REFRESH_INTERVAL}s"
echo -e " Press Ctrl+C to exit"
echo -e " Alert log: ${ALERT_LOG}"
echo -e "${CYAN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
# Save status to file
{
echo "TRAINING_DASHBOARD_STATUS"
echo "Updated: $(date '+%Y-%m-%d %H:%M:%S')"
echo ""
for model_name in "${!TRAINING_PROCESSES[@]}"; do
local config="${TRAINING_PROCESSES[$model_name]}"
local pid_file=$(echo "$config" | cut -d':' -f3)
local status=$(get_process_status "$pid_file")
echo "$model_name: $status"
done
} > "$STATUS_FILE"
# Wait for next refresh
sleep "$REFRESH_INTERVAL"
done
}
# Function to display one-time status
display_status() {
clear
# Display header
echo -e "${CYAN}╔════════════════════════════════════════════════════════╗${NC}"
echo -e "${CYAN}${MAGENTA}TRAINING STATUS SNAPSHOT${CYAN}${NC}"
echo -e "${CYAN}╚════════════════════════════════════════════════════════╝${NC}"
echo -e "${BLUE}Generated: $(date '+%Y-%m-%d %H:%M:%S')${NC}"
echo ""
# Check system resources
check_system_resources
# Display each model status
for model_name in TFT MAMBA2 Liquid DQN PPO; do
if [ -n "${TRAINING_PROCESSES[$model_name]}" ]; then
display_model_status "$model_name"
fi
done
# Display summary
display_summary
# Display recent alerts
if [ -f "$ALERT_LOG" ]; then
echo -e "${CYAN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
echo -e "${BLUE}RECENT ALERTS (Last 10)${NC}"
tail -10 "$ALERT_LOG" 2>/dev/null || echo "No alerts"
echo ""
fi
echo -e "${CYAN}━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━${NC}"
}
# Main command handler
case "${1:-monitor}" in
monitor)
monitor_training
;;
status)
display_status
;;
alerts)
if [ -f "$ALERT_LOG" ]; then
cat "$ALERT_LOG"
else
echo "No alerts logged yet"
fi
;;
clear-alerts)
> "$ALERT_LOG"
echo "Alert log cleared"
;;
*)
echo "Usage: $0 {monitor|status|alerts|clear-alerts}"
echo ""
echo "Commands:"
echo " monitor - Start continuous monitoring dashboard (default)"
echo " status - Show one-time status snapshot"
echo " alerts - Display all logged alerts"
echo " clear-alerts - Clear alert log"
echo ""
echo "Examples:"
echo " $0 monitor # Start live dashboard"
echo " $0 status # Quick status check"
echo " watch -n 30 $0 status # Auto-refresh status every 30s"
exit 1
;;
esac