from ragen.llm_agent.ctx_manager import ContextManager
from ragen.llm_agent.es_manager import EnvStateManager
from vllm import LLM, SamplingParams
from verl.single_controller.ray.base import RayWorkerGroup
from transformers import AutoTokenizer, AutoModelForCausalLM
from verl import DataProto
import hydra
import os
from typing import List, Dict
from verl.protocol import pad_dataproto_to_divisor, unpad_dataproto
from ragen.llm_agent.base_llm import ConcurrentLLM
from ragen.llm_agent.agent_proxy import ApiCallingWrapperWg, VllmWrapperWg, LLMAgentProxy, _get_rollout_do_sample

@hydra.main(version_base=None, config_path="../config", config_name="base")
def main(config):
	# detect config name from python -m ragen.llm_agent.agent_proxy --config_name frozen_lake
	os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
	os.environ["CUDA_VISIBLE_DEVICES"] = str(config.system.CUDA_VISIBLE_DEVICES)
	tokenizer = AutoTokenizer.from_pretrained(config.actor_rollout_ref.model.path)
	actor_wg = VllmWrapperWg(config, tokenizer)
	proxy = LLMAgentProxy(config, actor_wg, tokenizer)
	import time
	start_time = time.time()
	rollouts = proxy.rollout(DataProto(batch=None, non_tensor_batch=None, meta_info={'eos_token_id': 151645, 'pad_token_id': 151643, 'recompute_log_prob': False, 'do_sample': _get_rollout_do_sample(config), 'validate': True}), val=True)
	end_time = time.time()
	print(f'rollout time: {end_time - start_time} seconds')
	# print rollout rewards from the rm_scores
	rm_scores = rollouts.batch["rm_scores"]
	metrics = rollouts.meta_info["metrics"]
	avg_reward = rm_scores.sum(-1).mean().item()
	print(f'rollout rewards: {avg_reward}')
	print(f'metrics:')
	for k, v in metrics.items():
		print(f'{k}: {v}')

	# save results
	import time as _time
	timestamp = _time.strftime("%Y%m%d_%H%M%S")
	save_dir = os.path.join("results", "eval")
	os.makedirs(save_dir, exist_ok=True)
	save_path = os.path.join(save_dir, f"val_rollouts_{timestamp}.pkl")
	rollouts.save_to_disk(save_path)
	print(f'save validation results to {save_path}')

if __name__ == "__main__":
	main()