import streamlit as st from transformers import AutoTokenizer, AutoModelForSequenceClassification import torch import requests # ====================== 页面配置 ====================== st.set_page_config( page_title="🧠 Manipulative Detector", page_icon="🧠", layout="centered", ) st.markdown(""" """, unsafe_allow_html=True) # ====================== 模型加载 ====================== @st.cache_resource def load_model(): model_name = "LilithHu/mbert-manipulative-detector" tokenizer = AutoTokenizer.from_pretrained(model_name) model = AutoModelForSequenceClassification.from_pretrained(model_name) model.eval() return tokenizer, model tokenizer, model = load_model() st.sidebar.success("✅ 最新模型已成功加载！") # ====================== 多语言支持 ====================== lang = st.sidebar.selectbox("Language / 语言", ["English", "中文"]) st.sidebar.markdown("---") # ====================== 标题 ====================== if lang == "English": st.title("🧠 Manipulative Language Detector") st.markdown("This tool uses an AI model to detect manipulative language in messages.") else: st.title("🧠 情感操控语言识别器") st.markdown("本工具使用 AI 模型检测文本中的情感操控语言。") st.markdown("---") # ====================== 用户输入 ====================== user_input = st.text_area("Enter your message / 输入文本", height=150) # ====================== 推理函数 ====================== def predict(text): inputs = tokenizer(text, truncation=True, padding='max_length', max_length=128, return_tensors='pt') with torch.no_grad(): outputs = model(**inputs) logits = outputs.logits predicted_class = torch.argmax(logits, dim=1).item() return predicted_class # ====================== 按钮 & 结果显示 ====================== if st.button("🔍 开始分析 / Analyze"): if not user_input.strip(): st.warning("⚠️ 请输入文本！" if lang == "中文" else "⚠️ Please enter some text!") else: with st.spinner("正在分析..." if lang == "中文" else "Analyzing..."): try: prediction = predict(user_input) label = "操纵性语言" if prediction == 1 else "非操纵语言" if prediction == 1: st.markdown(f"""

⚠️ {label}

{'该文本可能存在操纵意图，请谨慎使用。' if lang == '中文' else 'The text may contain manipulative intent. Use caution.'}

""", unsafe_allow_html=True) else: st.markdown(f"""

✅ {label}

{'文本未检测到操纵意图，属于正常交流。' if lang == '中文' else 'No manipulative intent detected. The message seems fine.'}

""", unsafe_allow_html=True) except Exception as e: st.error(f"❌ 错误: {e}") # ====================== 页脚 ====================== st.markdown("---") st.markdown( "

", unsafe_allow_html=True )