#!/bin/bash #SBATCH --job-name=test_batch_fix #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=0:30:00 #SBATCH --output=test_batch_fix_%j.out #SBATCH --error=test_batch_fix_%j.err # Quick test: Verify batched agent calls fix # 10 profiles × 2 sessions = 20 sessions with 10 parallel # Should see ~500+ sessions/hr with batching (vs ~60 without) 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 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 # Start vLLM server 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 & for i in $(seq 1 90); do curl -s http://localhost:8003/health > /dev/null 2>&1 && break sleep 2 done echo "vLLM ready." cd collaborativeagents/scripts # Test with vanilla (simplest method) echo "=== Testing batched agent calls ===" python run_experiments.py \ --methods vanilla \ --datasets math-hard \ --n-profiles 10 \ --n-sessions 2 \ --max-turns 8 \ --use-vllm \ --use-openai-user \ --openai-user-model gpt-5-mini \ --reward-mode llm \ --vllm-agent-url http://localhost:8003/v1 \ --parallel-profiles 10 \ --profile-path ../data/complex_profiles_v2/profiles_200.jsonl \ --output-dir ../results/test_batch_fix_$(date +%Y%m%d_%H%M%S) echo "Test complete!" pkill -f "vllm.entrypoints" 2>/dev/null || true