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

model_name = "dphn/Dolphin3.0-Llama3.1-8B"

tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.float16,
    device_map="auto"
)

def chat(message, history):
    inputs = tokenizer.apply_chat_template(
        history + [{"role": "user", "content": message}],
        return_tensors="pt"
    ).to(model.device)
    outputs = model.generate(inputs, max_new_tokens=512)
    reply = tokenizer.decode(outputs[0], skip_special_tokens=True)
    history.append({"role": "assistant", "content": reply})
    return reply, history

gr.ChatInterface(fn=chat, title="Dolphin 3.0 Chat").launch()