import torch
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig

device = 'cuda' if torch.cuda.is_available() else 'cpu'
print(f"Using device: {device}")

model = AutoModelForCausalLM.from_pretrained(
    "/Users/mcclainthiel/plasmidgpt-addgene-gpt2",
    trust_remote_code=True
).to(device)
model.eval()

tokenizer = AutoTokenizer.from_pretrained(
    "/Users/mcclainthiel/plasmidgpt-addgene-gpt2",
    trust_remote_code=True
)

start_sequence = 'ATGGCTAGCGAATTCGGCGCGCCT'
print(f"Start sequence: {start_sequence}\n")

input_ids = tokenizer.encode(start_sequence, return_tensors='pt').to(device)

outputs = model.generate(
    input_ids,
    max_length=300,
    num_return_sequences=1,
    temperature=1.0,
    do_sample=True,
    pad_token_id=tokenizer.pad_token_id,
    eos_token_id=tokenizer.eos_token_id
)

generated_sequence = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(f"Generated sequence:\n{generated_sequence}\n")
print(f"Length: {len(generated_sequence)} bp")