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#!/bin/bash
#SBATCH --job-name=rag_test
#SBATCH --account=bfqt-delta-gpu
#SBATCH --partition=gpuH200x8-interactive
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=32
#SBATCH --gres=gpu:4
#SBATCH --mem=200G
#SBATCH --time=00:40:00
#SBATCH --output=/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/rag_test-%j.out
#SBATCH --error=/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/rag_test-%j.err
# Test with explicit device assignment:
# - vLLM user sim: GPUs 0,1
# - vLLM agent: GPUs 2,3 (0.45 memory)
# - Embedding: cuda:2
# - Reranker: cuda:3
# - Extractor: cuda:2
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 "=== RAG Test v5 ==="
echo "Explicit device assignment: embed->cuda:2, reranker->cuda:3, extractor->cuda:2"
echo "5 profiles, 15 sessions"
date
nvidia-smi --query-gpu=index,name,memory.total --format=csv
# Clear empty store
> /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/data/corpora/empty_store/memory_cards.jsonl
rm -f /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/data/corpora/empty_store/memory_embeddings.npy
# 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 (restored to 0.45 since HF models now explicitly assigned)
CUDA_VISIBLE_DEVICES=2,3 python -m vllm.entrypoints.openai.api_server \
--model $AGENT_MODEL \
--port 8003 --tensor-parallel-size 2 --gpu-memory-utilization 0.45 \
--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 $((i*5))s"
break
fi
sleep 5
done
sleep 5
OUTPUT_DIR="../results/rag_test_v5_$(date +%Y%m%d_%H%M%S)"
for METHOD in vanilla rag rag_vector; do
echo ""
echo "============================================"
echo "Testing: $METHOD"
echo "============================================"
# Clear memory store before each method
> /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/data/corpora/empty_store/memory_cards.jsonl
rm -f /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/data/corpora/empty_store/memory_embeddings.npy
date
python scripts/run_experiments.py --methods $METHOD \
--datasets math-hard --n-profiles 5 --n-sessions 15 --max-turns 15 \
--use-vllm --no-batch-processing --parallel-profiles 5 \
--output-dir $OUTPUT_DIR --profile-path $PROFILE_PATH
echo "Method $METHOD completed"
done
echo ""
echo "=== Done ==="
date
pkill -f "vllm.entrypoints" 2>/dev/null || true
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