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

model_name = "distilbert-base-uncased"
model = AutoModelForSequenceClassification.from_pretrained(model_name, num_labels=2)
tokenizer = AutoTokenizer.from_pretrained(model_name)

def classify_skill(text):
    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
    with torch.no_grad():
        outputs = model(**inputs)
    prediction = torch.argmax(outputs.logits, dim=1).item()
    return "软技能" if prediction == 1 else "技术技能"

gr.Interface(
    fn=classify_skill,
    inputs="text",
    outputs="text",
    title="技能分类器",
    description="输入一句话，系统将判断它描述的是技术技能还是软技能"
).launch()