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#!/bin/bash
#SBATCH --job-name=ctx_test
#SBATCH --account=bfqt-delta-gpu
#SBATCH --partition=gpuH200x8-interactive
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=16
#SBATCH --gres=gpu:4
#SBATCH --mem=100G
#SBATCH --time=00:20:00
#SBATCH --output=/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/ctx_test-%j.out
#SBATCH --error=/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/ctx_test-%j.err
# Small-scale contextual test: 1 profile, 15 sessions
# Testing fix: token estimation ratio changed from 4:1 to 2.5:1
cd /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/collaborativeagents
source /u/yurenh2/miniforge3/etc/profile.d/conda.sh
conda activate eval
export HF_HOME=/projects/bfqt/users/yurenh2/hf_cache/huggingface
export PYTHONPATH="/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/src:$PYTHONPATH"
PROFILE_PATH="/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/collaborativeagents/data/complex_profiles_v2/profiles_200.jsonl"
AGENT_MODEL="/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/models/llama-3.1-8b-instruct"
USER_MODEL="meta-llama/Llama-3.1-70B-Instruct"
echo "=== Contextual Test (Token Fix) ==="
echo "Fix: token estimation 4:1 -> 2.5:1"
echo "1 profile, 15 sessions"
date
nvidia-smi --query-gpu=index,name,memory.total --format=csv
# Start vLLM servers
# User simulator: GPUs 0,1
CUDA_VISIBLE_DEVICES=0,1 python -m vllm.entrypoints.openai.api_server \
--model $USER_MODEL \
--port 8004 --tensor-parallel-size 2 --gpu-memory-utilization 0.90 \
--max-model-len 16384 --dtype bfloat16 --download-dir $HF_HOME &
# Agent: GPUs 2,3
CUDA_VISIBLE_DEVICES=2,3 python -m vllm.entrypoints.openai.api_server \
--model $AGENT_MODEL \
--port 8003 --tensor-parallel-size 2 --gpu-memory-utilization 0.90 \
--max-model-len 16384 --dtype bfloat16 &
echo "Waiting for vLLM servers..."
for i in {1..200}; do
if curl -s http://localhost:8004/health > /dev/null 2>&1; then
echo "User simulator ready after $((i*5))s"
break
fi
sleep 5
done
for i in {1..60}; do
if curl -s http://localhost:8003/health > /dev/null 2>&1; then
echo "Agent ready after $((i*5))s"
break
fi
sleep 5
done
sleep 5
OUTPUT_DIR="../results/contextual_test_$(date +%Y%m%d_%H%M%S)"
echo ""
echo "============================================"
echo "Testing: contextual (with token fix)"
echo "============================================"
date
python scripts/run_experiments.py --methods contextual \
--datasets math-hard --n-profiles 1 --n-sessions 15 --max-turns 15 \
--use-vllm --no-batch-processing --parallel-profiles 1 \
--output-dir $OUTPUT_DIR --profile-path $PROFILE_PATH
echo ""
echo "=== Done ==="
date
pkill -f "vllm.entrypoints" 2>/dev/null || true
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