import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import gradio as gr



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


model_path = "PKU-ML/G1-7B"
print("Loading model...")
model = AutoModelForCausalLM.from_pretrained(
    model_path,
    torch_dtype="auto",
    device_map="auto"
).to(device)
tokenizer = AutoTokenizer.from_pretrained(model_path)


INSTRUCTION_TEMPLATE = """
    {instruction}

    Solve the above problem efficiently and clearly. The last line of your response should be of the following format: 'Therefore, the final answer is: $\\boxed{{ANSWER}}$. I hope it is correct' (without quotes) where ANSWER is just the final number or expression that solves the problem. Think step by step before answering.
    """.strip()



def generate_response(prompt):
    model.eval()
    
    messages = [
        {"role": "user", "content": INSTRUCTION_TEMPLATE.format(instruction=prompt)}
    ]
    text = tokenizer.apply_chat_template(
        messages,
        tokenize=False,
        add_generation_prompt=True
    )
    model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
    
    generated_ids = model.generate(
        **model_inputs,
        max_new_tokens=4096,
        top_p=0.95,
        top_k=30,
        temperature=0.6
    )
    generated_ids = [
        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
    ]
    
    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
    return response


interface = gr.Interface(
    fn=generate_response,
    inputs=[
        gr.Textbox(label="Your Message", placeholder="Write your question..."),
        # gr.Slider(label="Max Length", minimum=50, maximum=200, step=10, value=100),
        # gr.Slider(label="Temperature", minimum=0.1, maximum=1.0, step=0.05, value=0.65),
        # gr.Slider(label="Top-p (nucleus)", minimum=0.1, maximum=1.0, step=0.05, value=0.8),
    ],
    outputs=gr.Textbox(label="Response"),
    title="G1",
    description="Ask a graph reasoning question",
    theme="huggingface",
)

if __name__ == "__main__":
    interface.launch()