#!/usr/bin/env bash
# GLM 실행 래퍼 — glm-call.py 기반 (v2)
# 사용법: run-glm.sh <task_id> <task_file_path> [role] [model]
set -euo pipefail

TASK_ID="${1:?Usage: run-glm.sh <task_id> <task_file_path> [role] [model]}"
TASK_FILE="${2:?Usage: run-glm.sh <task_id> <task_file_path> [role] [model]}"
ROLE="${3:-backend}"
MODEL="${4:-glm-5}"
WORKSPACE_ROOT="/home/jay/workspace"
LOG_DIR="${WORKSPACE_ROOT}/teams/dev8/logs"
OUTPUT_DIR="${WORKSPACE_ROOT}/teams/dev8/outputs"

mkdir -p "$LOG_DIR" "$OUTPUT_DIR"
LOG_FILE="${LOG_DIR}/${TASK_ID}.log"
OUTPUT_FILE="${OUTPUT_DIR}/${TASK_ID}.md"

echo "[$(date '+%Y-%m-%d %H:%M:%S')] [${TASK_ID}] glm-call.py 호출 시작 (role=${ROLE}, model=${MODEL})" >> "$LOG_FILE"

python3 "${WORKSPACE_ROOT}/tools/glm-call.py" \
  --role "${ROLE}" \
  --task-file "${TASK_FILE}" \
  --model "${MODEL}" \
  --output "${OUTPUT_FILE}" \
  2>&1 | tee -a "$LOG_FILE"

EXIT_CODE=${PIPESTATUS[0]}
echo "[$(date '+%Y-%m-%d %H:%M:%S')] [${TASK_ID}] glm-call.py 호출 완료 (exit: ${EXIT_CODE})" >> "$LOG_FILE"
exit $EXIT_CODE