data_name=nq_hotpotqa_train

export CUDA_VISIBLE_DEVICES=3,4,5,6
export DATA_DIR=data/${data_name} # first download the data from https://huggingface.co/datasets/PeterJinGo/nq_hotpotqa_train

WAND_PROJECT="SearchAgent"

export BASE_MODEL='Qwen/Qwen2.5-7B'
export EXPERIMENT_NAME="search-agent-grpo-qwen2.5-7b-rag-e5-40G-ug"
export VLLM_ATTENTION_BACKEND=XFORMERS

PYTHONUNBUFFERED=1 python3 -m verl.trainer.main_ppo \
    data.train_files=$DATA_DIR/train_e5_ug.parquet \
    data.val_files=$DATA_DIR/test_e5_ug.parquet \
    data.train_data_num=null \
    data.val_data_num=null \
    data.train_batch_size=64 \
    data.val_batch_size=32 \
    data.max_prompt_length=6000 \
    data.max_response_length=500 \
    data.max_start_length=2000 \
    data.max_obs_length=800 \
    data.shuffle_train_dataloader=True \
    algorithm.adv_estimator=grpo \
    actor_rollout_ref.model.path=$BASE_MODEL \
    actor_rollout_ref.actor.optim.lr=1e-6 \
    actor_rollout_ref.actor.optim.lr_warmup_steps_ratio=0.285 \
    actor_rollout_ref.actor.use_kl_loss=true \
    actor_rollout_ref.model.enable_gradient_checkpointing=true \
    actor_rollout_ref.model.use_remove_padding=True \
    actor_rollout_ref.actor.ppo_mini_batch_size=16 \
    actor_rollout_ref.actor.ppo_micro_batch_size=8 \
    actor_rollout_ref.actor.fsdp_config.param_offload=false \
    actor_rollout_ref.actor.fsdp_config.grad_offload=false \
    actor_rollout_ref.actor.fsdp_config.optimizer_offload=false \
    actor_rollout_ref.rollout.log_prob_micro_batch_size=16 \
    actor_rollout_ref.rollout.tensor_model_parallel_size=1 \
    actor_rollout_ref.rollout.name=vllm \
    actor_rollout_ref.rollout.gpu_memory_utilization=0.3 \
    actor_rollout_ref.ref.log_prob_micro_batch_size=16 \
    actor_rollout_ref.ref.fsdp_config.param_offload=True \
    actor_rollout_ref.actor.kl_loss_coef=0.001 \
    actor_rollout_ref.actor.kl_loss_type=low_var_kl \
    algorithm.no_think_rl=false \
    actor_rollout_ref.rollout.n_agent=4 \
    actor_rollout_ref.rollout.temperature=1 \
    actor_rollout_ref.actor.state_masking=true \
    trainer.logger=['wandb'] \
    +trainer.val_only=false \
    +trainer.val_before_train=false \
    trainer.default_hdfs_dir=null \
    trainer.n_gpus_per_node=4 \
    trainer.nnodes=1 \
    trainer.save_freq=100 \
    trainer.test_freq=2000 \
    trainer.project_name=$WAND_PROJECT \
    trainer.experiment_name=$EXPERIMENT_NAME \
    trainer.total_epochs=5 \
    trainer.total_training_steps=2000 \
    trainer.default_hdfs_dir=null \
    trainer.default_local_dir=verl_checkpoints/$EXPERIMENT_NAME \
    max_turns=4 \
    +generator_llm="Qwen/Qwen2.5-14B-Instruct-GPTQ-Int4" \
    retriever.url="http://127.0.0.1:7000/retrieve" \
    retriever.topk=3 \
    2>&1 | tee $EXPERIMENT_NAME.log
