Update app.py

app.py

@@ -1,51 +1,33 @@
 import streamlit as st
-from agent import classify_emoji_text
+from agent import classify_emoji_text, available_models
 
-# 页面配置
-st.set_page_config(page_title="Emoji Offensive Classifier", page_icon="🧠", layout="wide")
-st.title("🔥 Emoji-Based Offensive Text Classifier")
+st.set_page_config(page_title="Emoji Offensive Classifier", page_icon="🚨", layout="wide")
+st.title("🚨 Offensive Text Detection Agent (with Emoji Translation)")
 
-st.markdown("Detect potentially offensive Chinese sentences enhanced with emojis, slang, or homophones.")
+st.markdown("""
+This demo uses a two-step AI agent:
+1. Translates emojis & phonetic expressions into clear Chinese using a fine-tuned Qwen model.
+2. Classifies the translated sentence for offensiveness using a selectable large language model.
+""")
 
-# 分两栏布局
-left_col, right_col = st.columns([2, 1])
+# 左侧：输入区
+st.subheader("① Enter a sentence with emoji or homophones:")
+example = "你是🐷，好像🤡"
+text = st.text_area("Input text:", value=example, height=120)
 
-# 左侧输入
-with left_col:
-    st.subheader("📥 Input Text")
-    example = "你是🐷"
-    user_input = st.text_area("Paste your message here:", value=example, height=200)
-    model_choice = st.selectbox(
-        "Choose offensive classifier model:",
-        options=[
-            "cardiffnlp/twitter-roberta-base-offensive",
-            "facebook/roberta-hate-speech-dynabench",
-            "microsoft/deberta-v3-base"
-        ],
-        index=0,
-        help="Select a backend classifier. LLM used for emoji translation is fixed (Qwen1.5-emoji)."
-    )
+# 右侧：模型选择区
+st.subheader("② Select classification model:")
+model_choice = st.selectbox("Choose a classifier", options=list(available_models.keys()))
 
-    if st.button("🚦 Run Detection"):
-        with st.spinner("Running model inference..."):
-            translated, label, score = classify_emoji_text(user_input, model_id=model_choice)
-            st.session_state.result = {
-                "text": translated,
-                "label": label,
-                "score": score
-            }
-    else:
-        st.info("Click the button to start analysis.")
+if st.button("🚦 Analyze"):
+    with st.spinner("Running multi-stage agent pipeline..."):
+        translated, label, score = classify_emoji_text(text, model_choice)
 
-# 右侧输出
-with right_col:
-    st.subheader("📊 Analysis Results")
-
-    if "result" in st.session_state:
-        result = st.session_state.result
-        st.success("✅ Classification Complete")
-        st.markdown(f"**Translated Text:** `{result['text']}`")
-        st.markdown(f"**Prediction:** `{result['label']}`")
-        st.markdown(f"**Confidence Score:** `{result['score']:.2%}`")
-    else:
-        st.markdown("⚠️ No output yet. Run detection to see results.")
+        st.success("✅ Completed!")
+        st.markdown(f"### 🔄 Translated sentence:\n```
+{translated}
+```")
+        st.markdown(f"### 🎯 Prediction: `{label}`")
+        st.markdown(f"### 📊 Confidence: `{score:.2%}`")
+else:
+    st.info("Click 'Analyze' to start inference.")