import torch
from transformers import AutoProcessor, AutoModelForVision2Seq

MODEL_NAME = "Qwen/Qwen2.5-VL-7B-Instruct"

device = "cuda" if torch.cuda.is_available() else "cpu"

print("Loading processor...")
processor = AutoProcessor.from_pretrained(
    MODEL_NAME, 
    trust_remote_code=True,
    use_fast=True)  # use_fast to avoid warnings in logs

print("Loading model...")
model = AutoModelForVision2Seq.from_pretrained(
    MODEL_NAME,
    trust_remote_code=True,
    torch_dtype=torch.float16,
    device_map="auto"
)

print("Model loaded successfully")



# import torch
# from transformers import AutoProcessor, AutoModelForVision2Seq

# MODEL_NAME = "Qwen/Qwen2.5-VL-7B-Instruct"

# model = None
# processor = None
# device = "cuda" if torch.cuda.is_available() else "cpu"


# def get_model():
#     global model, processor, device

#     if model is None or processor is None:
#         print("Loading processor...")
#         processor = AutoProcessor.from_pretrained(
#             MODEL_NAME,
#             trust_remote_code=True,
#             use_fast=True
#         )

#         print("Loading model...")
#         model = AutoModelForVision2Seq.from_pretrained(
#             MODEL_NAME,
#             trust_remote_code=True,
#             torch_dtype=torch.float16,
#             device_map="auto"
#         )

#         print("Model loaded successfully")

#     return model, processor, device