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9c60174 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | #!/bin/bash
# Example SLURM array script for the Plan-Act-Read agentic retrieval pipeline
# over hierarchical memory.
#
#SBATCH -J agentic_hier
#SBATCH -A ${SLURM_ACCOUNT:-your-account}
#SBATCH -p ${PARTITIONS:-cpu}
#SBATCH --nodes=1
#SBATCH --time=04:00:00
#SBATCH --array=0-7
#SBATCH --output=logs/agentic_hier_%A_%a.log
#SBATCH --export=ALL,NV_API_KEY
set -euo pipefail
PROJECT_DIR="${PROJECT_DIR:-$(pwd)}"
cd "$PROJECT_DIR"
MODEL_NAME="${MODEL_NAME:-gpt-5.5}"
TOP_K="${TOP_K:-20}"
SHARD_ROOT="${SHARD_ROOT:-output/shards/v5_${MODEL_NAME//./_}_nchunks10}"
shard_id=$(printf "%02d" "$SLURM_ARRAY_TASK_ID")
export ret_cache="$SHARD_ROOT/ret_cache/shard_${shard_id}.jsonl"
export plan_cache="response_cache/qa/${MODEL_NAME//./_}_plan_cache_shard_${shard_id}"
export reading_cache="response_cache/qa/${MODEL_NAME//./_}_reading_cache_shard_${shard_id}"
python main.py \
--in_file "$SHARD_ROOT/dataset/shard_${shard_id}.json" \
--out_file "$SHARD_ROOT/agentic_hier/part_${shard_id}.jsonl" \
--model_name "$MODEL_NAME" \
--top_k "$TOP_K" \
--n_chunks 10 \
--nvidia \
--all_sessions_file dataset/all_sessions.json \
--hier_v2 \
--hier_union \
--mode agent
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