app.py

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

# 使用微软的 BioGPT 模型
tokenizer = AutoTokenizer.from_pretrained("microsoft/biogpt")
model = AutoModelForCausalLM.from_pretrained("microsoft/biogpt")

def chat(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    with torch.no_grad():
        outputs = model.generate(**inputs, max_new_tokens=256, do_sample=True)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

gr.Interface(
    fn=chat,
    inputs=gr.Textbox(label="输入医学问题或症状描述"),
    outputs=gr.Textbox(),
    title="医疗语言模型BioGPT"
).launch()