#!/bin/bash
# Daily ML Model Training Script
# 
# Downloads fresh data and retrains the regime detection model.
# Can be run manually or scheduled via cron.
#
# Usage:
#   ./train_daily.sh           # Full workflow
#   ./train_daily.sh --skip-research  # Skip research validation

set -e  # Exit on error

SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
cd "$SCRIPT_DIR"

LOG_DIR="logs"
mkdir -p "$LOG_DIR"

TIMESTAMP=$(date +"%Y-%m-%d %H:%M:%S")
echo "[$TIMESTAMP] Starting daily training..."

# 1. Download fresh data
echo "Downloading BTC-USDT 1h data..."
uv run python main.py download -p BTC-USDT -t 1h

echo "Downloading ETH-USDT 1h data..."
uv run python main.py download -p ETH-USDT -t 1h

# 2. Research optimization (find best horizon)
echo "Running research optimization..."
uv run python research/regime_detection.py --output-horizon data/optimal_horizon.txt

# 3. Read best horizon
if [[ -f "data/optimal_horizon.txt" ]]; then
    BEST_HORIZON=$(cat data/optimal_horizon.txt)
    echo "Found optimal horizon: ${BEST_HORIZON} bars"
else
    BEST_HORIZON=102
    echo "Warning: Could not find optimal horizon file. Using default: ${BEST_HORIZON}"
fi

# 4. Train model
echo "Training ML model with horizon ${BEST_HORIZON}..."
uv run python train_model.py --horizon "$BEST_HORIZON"

# 5. Cleanup
rm -f data/optimal_horizon.txt

TIMESTAMP=$(date +"%Y-%m-%d %H:%M:%S")
echo "[$TIMESTAMP] Daily training complete."