import gradio as gr
from transformers import pipeline

# 使用 Hugging Face 上存储的模型
model_name = "Dominic0406/medical_gpt2"
pipe = pipeline("text-generation", model=model_name)

def generate_diagnosis(symptoms):
    input_text = f"患者症状: {symptoms}\n诊断: "
    response = pipe(input_text, max_length=150, num_return_sequences=1)[0]['generated_text']
    diagnosis = response.split("诊断: ")[-1].strip()
    return diagnosis

# 创建 Gradio 接口
iface = gr.Interface(
    fn=generate_diagnosis,
    inputs=gr.Textbox(lines=7, placeholder="输入患者症状..."),
    outputs="text",
    title="医疗诊断 AI",
    description="输入患者的症状，模型将生成一个可能的诊断结果。"
)

# 启动接口
if __name__ == "__main__":
    iface.launch()