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diff --git a/collaborativeagents/scripts/contextual_test_small.sbatch b/collaborativeagents/scripts/contextual_test_small.sbatch
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+++ b/collaborativeagents/scripts/contextual_test_small.sbatch
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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