Add collaborativeagents module and update gitignore

- Add collaborativeagents subproject with adapters, agents, and evaluation modules
- Update .gitignore to exclude large binary files (.whl, .tar), wandb logs, and results

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

1 files changed, 124 insertions, 0 deletions

diff --git a/collaborativeagents/scripts/test_rag_empty_v2.sbatch b/collaborativeagents/scripts/test_rag_empty_v2.sbatch
new file mode 100644
index 0000000..834dccb
--- /dev/null
+++ b/collaborativeagents/scripts/test_rag_empty_v2.sbatch
@@ -0,0 +1,124 @@
+#!/bin/bash
+#SBATCH --job-name=rag_empty
+#SBATCH --account=bfqt-delta-gpu
+#SBATCH --partition=gpuH200x8
+#SBATCH --nodes=1
+#SBATCH --ntasks=1
+#SBATCH --cpus-per-task=32
+#SBATCH --gres=gpu:8
+#SBATCH --mem=400G
+#SBATCH --time=04:00:00
+#SBATCH --output=/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/rag_empty-%j.out
+#SBATCH --error=/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/rag_empty-%j.err
+
+# Test RAG with EMPTY memory store - start fresh and accumulate
+# Using 8 GPUs with TP=4 for 70B to avoid CUDA errors
+
+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"
+export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
+export NCCL_P2P_DISABLE=1
+
+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 Empty Memory Store Test v2 ==="
+echo "Using 8 GPUs: TP=4 for 70B user sim, TP=2 for 8B agent"
+date
+nvidia-smi --query-gpu=index,name,memory.total --format=csv
+
+# Clear empty store
+echo "Clearing empty memory 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
+echo "Starting vLLM servers..."
+
+# User simulator on GPUs 0-3 (70B, TP=4)
+CUDA_VISIBLE_DEVICES=0,1,2,3 python -m vllm.entrypoints.openai.api_server \
+    --model $USER_MODEL \
+    --port 8004 --tensor-parallel-size 4 --gpu-memory-utilization 0.90 \
+    --max-model-len 16384 --dtype bfloat16 --download-dir $HF_HOME \
+    --disable-log-requests &
+USER_PID=$!
+
+# Agent on GPUs 4-5 (8B, TP=2)
+CUDA_VISIBLE_DEVICES=4,5 python -m vllm.entrypoints.openai.api_server \
+    --model $AGENT_MODEL \
+    --port 8003 --tensor-parallel-size 2 --gpu-memory-utilization 0.40 \
+    --max-model-len 16384 --dtype bfloat16 \
+    --disable-log-requests &
+AGENT_PID=$!
+
+# Wait for servers
+echo "Waiting for vLLM servers..."
+for i in {1..300}; do
+    if curl -s http://localhost:8004/health > /dev/null 2>&1; then
+        echo "User simulator (8004) ready after $((i*5)) seconds"
+        break
+    fi
+    sleep 5
+done
+for i in {1..120}; do
+    if curl -s http://localhost:8003/health > /dev/null 2>&1; then
+        echo "Agent (8003) ready after $((i*5)) seconds"
+        break
+    fi
+    sleep 5
+done
+
+if ! curl -s http://localhost:8004/health > /dev/null 2>&1; then
+    echo "ERROR: User server not healthy"
+    kill $USER_PID $AGENT_PID 2>/dev/null
+    exit 1
+fi
+if ! curl -s http://localhost:8003/health > /dev/null 2>&1; then
+    echo "ERROR: Agent server not healthy"
+    kill $USER_PID $AGENT_PID 2>/dev/null
+    exit 1
+fi
+echo "Both vLLM servers ready"
+sleep 5
+
+OUTPUT_DIR="../results/rag_empty_test_$(date +%Y%m%d_%H%M%S)"
+
+for METHOD in vanilla rag rag_vector; do
+    echo ""
+    echo "============================================"
+    echo "Testing method: $METHOD"
+    echo "============================================"
+
+    # Clear memory store before each method
+    > /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/data/corpora/empty_store/memory_cards.jsonl
+    rm -f /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/data/corpora/empty_store/memory_embeddings.npy
+
+    date
+    START=$(date +%s)
+
+    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 $PROFILE_PATH
+
+    END=$(date +%s)
+    ELAPSED=$((END-START))
+
+    if [[ "$METHOD" == "rag" || "$METHOD" == "rag_vector" ]]; then
+        CARD_COUNT=$(wc -l < /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/data/corpora/empty_store/memory_cards.jsonl 2>/dev/null || echo 0)
+        echo "Memory cards accumulated: $CARD_COUNT"
+    fi
+
+    echo "Method $METHOD: completed in ${ELAPSED}s"
+done
+
+echo ""
+echo "=== Test Complete ==="
+echo "Results: $OUTPUT_DIR"
+date
+
+pkill -f "vllm.entrypoints" 2>/dev/null || true