Update app.py

app.py

@@ -21,23 +21,50 @@ labels = ["Non-manipulative / 非操纵性", "Manipulative / 操纵性"]
 def classify(text):
     inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True).to(device)
     with torch.no_grad():
-    outputs = model(**inputs)
-    probs = torch.softmax(outputs.logits, dim=1)[0]  # 取第一个样本的概率向量
-    probs = torch.clamp(probs, max=0.95)  # 限制最大置信度为 95%
-    result = "🧠 预测 / Prediction:\n"
-    for i, label in enumerate(labels):
-        percent = round(probs[i].item() * 100, 2)
-        result += f"{label}: {percent}%\n"
-    return result
+        outputs = model(**inputs)
+        probs = torch.softmax(outputs.logits, dim=1)[0]  # 取第一个样本的概率向量
+        probs = torch.clamp(probs, max=0.95)  # 限制最大置信度为 95%
+        result = "🧠 预测 / Prediction:\n"
+        for i, label in enumerate(labels):
+            percent = round(probs[i].item() * 100, 2)
+            result += f"{label}: {percent}%\n"
+        return result
 
 
 # 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.",
+    inputs=gr.Textbox(
+        lines=4, 
+        placeholder="Enter a sentence in English or Chinese... / 输入英文或中文句子",
+        label="📝 Input Text / 输入文本"
+    ),
+    outputs=gr.Textbox(label="📊 Prediction / 预测结果"),
+    title="🧠 Manipulative Language Detector / 操纵性语言识别器",
+    description="""
+🔍 This tool detects **emotionally manipulative language** in English or Chinese digital communication.  
+🧪 The model was fine-tuned on a manually annotated dataset of 10,000 Chinese messages, categorized into four manipulation types.
+
+---
+
+📌 **Disclaimer / 免责声明：**  
+This system is for **research and educational purposes only**.  
+It **does not guarantee accuracy** and **should not be used as legal or clinical evidence**.
+
+本工具仅用于**学术研究与教学演示**，不构成法律、医疗或其他正式用途的依据。
+
+---
+
+🤖 **Model Info**:  
+- Model: `LilithHu/mbert-manipulative-detector`  
+- Base: `mDeBERTa-v3` multilingual pre-trained model  
+- Fine-tuned using HuggingFace Transformers on labeled Chinese data  
+
+🌐 Built with Gradio and hosted on HuggingFace Spaces.
+""",
+    theme="default",
+    allow_flagging="never"
 )
 
+
 interface.launch()