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, 69 insertions, 0 deletions

diff --git a/collaborativeagents/slurm/run_grpo_training.sh b/collaborativeagents/slurm/run_grpo_training.sh
new file mode 100755
index 0000000..4f9e3f1
--- /dev/null
+++ b/collaborativeagents/slurm/run_grpo_training.sh
@@ -0,0 +1,69 @@
+#!/bin/bash
+#SBATCH --job-name=grpo_refl
+#SBATCH --account=bfqt-delta-gpu
+#SBATCH --partition=gpuA100x4
+#SBATCH --nodes=1
+#SBATCH --ntasks=1
+#SBATCH --cpus-per-task=16
+#SBATCH --gres=gpu:4
+#SBATCH --mem=200G
+#SBATCH --time=48:00:00
+#SBATCH --output=logs/grpo_reflection_%j.out
+#SBATCH --error=logs/grpo_reflection_%j.err
+
+set -e
+cd /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model
+mkdir -p collaborativeagents/slurm/logs collaborativeagents/training/outputs
+
+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:${PYTHONPATH}"
+export NCCL_P2P_DISABLE=1
+
+# Use the AWQ 70B model for judge (fits on 2 GPUs)
+JUDGE_MODEL="hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4"
+JUDGE_PORT=8000
+
+# Start vLLM server for judge model (on GPUs 2,3)
+echo "=== Starting vLLM judge server ==="
+CUDA_VISIBLE_DEVICES=2,3 python -m vllm.entrypoints.openai.api_server \
+    --model "$JUDGE_MODEL" \
+    --port $JUDGE_PORT \
+    --tensor-parallel-size 2 \
+    --max-model-len 8192 \
+    --dtype auto \
+    --trust-remote-code &
+
+VLLM_PID=$!
+echo "vLLM server PID: $VLLM_PID"
+
+# Wait for server to be ready
+echo "Waiting for vLLM server to start..."
+for i in {1..60}; do
+    if curl -s http://localhost:$JUDGE_PORT/health > /dev/null 2>&1; then
+        echo "vLLM server is ready!"
+        break
+    fi
+    sleep 10
+done
+
+# Run GRPO training (on GPUs 0,1)
+echo "=== Starting GRPO training ==="
+CUDA_VISIBLE_DEVICES=0,1 python collaborativeagents/training/train_grpo.py \
+    --model-path collaborativeagents/training/outputs/sft_reflection \
+    --data-path collaborativeagents/training/training_data/grpo_training_data.json \
+    --output-dir collaborativeagents/training/outputs/grpo_reflection \
+    --judge-url "http://localhost:$JUDGE_PORT/v1" \
+    --judge-model "$JUDGE_MODEL" \
+    --max-steps 200 \
+    --learning-rate 1e-6 \
+    --num-generations 8
+
+# Cleanup
+echo "=== Cleanup ==="
+kill $VLLM_PID 2>/dev/null || true
+
+echo "=== GRPO Training Complete ==="
+echo "Model saved to: collaborativeagents/training/outputs/grpo_reflection/final"