#!/bin/bash
#SBATCH --job-name=gen_profiles
#SBATCH --account=bfqt-delta-gpu
#SBATCH --partition=cpu
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=4
#SBATCH --mem=16G
#SBATCH --time=00:30:00
#SBATCH --output=logs/gen_profiles_%j.out
#SBATCH --error=logs/gen_profiles_%j.err

# Generate 100 user profiles from schema (no LLM required)
# This is fast and doesn't need GPU

set -e

cd /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model

# Create logs directory
mkdir -p collaborativeagents/slurm/logs
mkdir -p collaborativeagents/data/complex_profiles_v2

echo "Starting profile generation at $(date)"
echo "Job ID: $SLURM_JOB_ID"

# Use the eval environment (has required packages)
source /u/yurenh2/miniforge3/etc/profile.d/conda.sh
conda activate eval

# Generate profiles from schema (no LLM needed)
python collaborativeagents/scripts/generate_profiles_v2.py \
    --num_profiles 100 \
    --from_schema collaborativeagents/data/preference_schema_v2_sample.json \
    --output collaborativeagents/data/complex_profiles_v2/profiles_100.jsonl \
    --seed 42

echo "Profile generation completed at $(date)"
echo "Output: collaborativeagents/data/complex_profiles_v2/profiles_100.jsonl"