Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+# 加载模型
+model_name = "LilithHu/mbert-manipulative-detector"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# 二分类标签（非操纵性是0，操纵性是1）
+labels = ["Non-manipulative / 非操纵性", "Manipulative / 操纵性"]
+
+def classify(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = torch.softmax(outputs.logits, dim=1)
+        pred = torch.argmax(probs, dim=1).item()
+        confidence = probs[0][pred].item()
+        return f"🧠 预测 / Prediction: {labels[pred]}\n📊 置信度 / Confidence: {confidence:.2%}"
+
+# Gradio 界面
+interface = gr.Interface(
+    fn=classify,
+    inputs=gr.Textbox(lines=4, placeholder="Enter text in English or Chinese... / 输入中文或英文句子"),
+    outputs="text",
+    title="🔍 Manipulative Language Detector / 操纵性语言识别器",
+    description="🧪 输入英文或中文句子，系统将判断其是否包含操纵性语言。\nEnter a sentence in English or Chinese to detect if it's manipulative.",
+    examples=[
+        ["If you really cared, you'd do what I say."],
+        ["你不爱我就证明给我看！"],
+        ["今天的天气真不错。"]
+    ]
+)
+
+interface.launch()