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#!/bin/bash
#SBATCH --job-name=gpt_user_test
#SBATCH --account=bfqt-delta-gpu
#SBATCH --partition=gpuA100x4
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=16
#SBATCH --gres=gpu:nvidia_a100:2
#SBATCH --mem=128G
#SBATCH --time=4:00:00
#SBATCH --output=gpt_user_test_%j.out
#SBATCH --error=gpt_user_test_%j.err
cd /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model
source /u/yurenh2/miniforge3/etc/profile.d/conda.sh
conda activate eval
export HF_HOME=/projects/bfqt/users/yurenh2/hf_cache/huggingface
export PYTHONPATH="${PWD}/src:${PWD}/collaborativeagents:${PYTHONPATH}"
export NCCL_P2P_DISABLE=1
# Load OpenAI API key
set -a
source .env
set +a
pip install --quiet openai python-dotenv json-repair
MODEL_8B="/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/models/llama-3.1-8b-instruct"
pkill -f "vllm.entrypoints" 2>/dev/null || true
sleep 2
# GPU 0: vLLM 8B agent, GPU 1: adapter models (embedding/extractor/reranker)
CUDA_VISIBLE_DEVICES=0 python -m vllm.entrypoints.openai.api_server \
--model $MODEL_8B --port 8003 --tensor-parallel-size 1 \
--gpu-memory-utilization 0.5 --max-model-len 8192 \
--dtype bfloat16 --disable-log-requests &
# Wait for server
for i in $(seq 1 90); do
curl -s http://localhost:8003/health > /dev/null 2>&1 && break
sleep 2
done
echo "vLLM 8B agent server ready."
cd collaborativeagents/scripts
# Large scale test: 50 profiles in parallel, 3 sessions each, all 6 methods
python run_experiments.py \
--methods vanilla,contextual,reflection,all_memory,rag,rag_vector \
--datasets math-hard \
--n-profiles 20 \
--n-sessions 5 \
--max-turns 8 \
--use-vllm \
--use-openai-user \
--openai-user-model gpt-5 \
--reward-mode llm \
--vllm-agent-url http://localhost:8003/v1 \
--parallel-profiles 20 \
--profile-path ../data/complex_profiles_v2/profiles_200.jsonl \
--output-dir ../results/gpt_user_scale_test_$(date +%Y%m%d_%H%M%S)
echo "All methods test complete!"
pkill -f "vllm.entrypoints" 2>/dev/null || true
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