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diff --git a/collaborativeagents/slurm/generate_profiles.sh b/collaborativeagents/slurm/generate_profiles.sh
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+#!/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"