Update app.py

app.py

@@ -5,11 +5,11 @@ import numpy as np
 from transformers import pipeline
 
 # ---------------------------
-# Translator Model
+# 1. AI Translator Model
 # ---------------------------
 translator = pipeline("translation", model="Helsinki-NLP/opus-mt-zh-en")
 
-def translate_text(cn_text):
+def translate_ai(cn_text):
     try:
         return translator(cn_text)[0]["translation_text"]
     except:
@@ -17,7 +17,7 @@ def translate_text(cn_text):
 
 
 # ---------------------------
-# Politeness Markers Extraction
+# 2. Politeness Marker Extraction
 # ---------------------------
 POLITENESS_FEATURES = {
     "modals": ["could", "would", "may", "might"],
@@ -34,17 +34,17 @@ def extract_politeness_scores(en_text):
 
     for feat, markers in POLITENESS_FEATURES.items():
         score = sum(text.count(m) for m in markers)
-        score = min(score, 5)  # cap at 5 for radar chart
+        score = min(score, 5)
         scores[feat] = score
 
     return scores
 
 
 # ---------------------------
-# TIRA Classification
+# 3. TIRA Classification
 # ---------------------------
 def classify_tira(cn_text, en_text):
-    cn = cn_text.strip()
+    cn = cn_text.lower()
     en = en_text.lower()
 
     cn_amplify = ["能否", "是否方便", "请您帮忙", "抽空", "劳驾", "麻烦帮我"]
@@ -64,13 +64,13 @@ def classify_tira(cn_text, en_text):
     if any(p in cn for p in cn_attenuate) or any(p in en for p in en_attenuate):
         return "Attenuate（削弱）", "英文更直接 → PDI 下移。"
 
-    return "Retain（保留）", "礼貌构式基本被稳定保留。"
+    return "Retain（保留）", "礼貌构式基本稳定保留。"
 
 
 # ---------------------------
-# Radar Chart Drawing
+# 4. Radar Chart Drawing
 # ---------------------------
-def draw_radar(scores_dict):
+def draw_radar(scores_dict, title="Politeness Radar"):
     labels = list(scores_dict.keys())
     scores = list(scores_dict.values())
     
@@ -84,37 +84,46 @@ def draw_radar(scores_dict):
     ax.plot(angles, scores, color="#1B3B6F", linewidth=2)
 
     ax.set_xticks(angles[:-1])
-    ax.set_xticklabels([label.capitalize() for label in labels], fontsize=10)
+    ax.set_xticklabels([label.capitalize() for label in labels])
     ax.set_yticks(range(1, 6))
-    ax.set_yticklabels([str(i) for i in range(1, 6)], fontsize=8)
     ax.set_ylim(0, 5)
-    ax.grid(True)
 
+    ax.set_title(title, fontsize=14, color="#1B3B6F")
     return fig
 
 
 # ---------------------------
-# Main Function
+# 5. Main Logic (Supports AI & Human)
 # ---------------------------
-def full_process(cn_text):
-    en = translate_text(cn_text)
+def full_process(cn_text, mode, human_en=None):
+    if mode == "AI翻译（自动）":
+        en = translate_ai(cn_text)
+    else:
+        en = human_en
+
+    # Empty if user didn't enter human translation
+    if not en or en.strip() == "":
+        en = "No human translation provided."
+
     scores = extract_politeness_scores(en)
     tira, analysis = classify_tira(cn_text, en)
 
     risk = {
         "Retain": "低风险（关系保持稳定）",
-        "Amplify": "中风险（可能显得更有距离）",
-        "Attenuate": "中偏高（可能显得更直接）",
-        "Redirect": "不稳定（可能造成理解偏差）"
+        "Amplify": "中风险（更远、更正式）",
+        "Attenuate": "中偏高（更直接）",
+        "Redirect": "不稳定（文化错位风险）"
     }
-    risk_out = risk[tira.split("（")[0]]
-    radar = draw_radar(scores)
+    key = tira.split("（")[0]
+    risk_out = risk[key]
+
+    radar = draw_radar(scores, title=f"Politeness Radar ({mode})")
 
     return en, scores, tira, analysis, risk_out, radar
 
 
 # ---------------------------
-# UI (Deep Blue Academic Style)
+# 6. Deep Blue UI
 # ---------------------------
 css = """
 h1 {text-align:center; color:#1B3B6F;}
@@ -122,7 +131,47 @@ h1 {text-align:center; color:#1B3B6F;}
 label {font-weight:bold;}
 """
 
-with gr.Blocks(css=css, title="TIRA Radar System") as demo:
+with gr.Blocks(css=css, title="TIRA Dual Translation System") as demo:
     gr.Markdown("""
-# **📘 TIRA Academic Email Translation Visualizer**
-### *Real-Time Translation + Politeness Feature Radar + TIRA Classificatio*
+# **📘 TIRA Dual Translation Visualizer**
+### *AI Translation vs Human Translation — TIRA & Politeness Radar*
+---
+
+你可以选择：  
+✔ 使用 AI 自动翻译  
+✔ 输入人工英文译文进行对比  
+
+系统会自动：  
+- 抽取礼貌标记  
+- 绘制雷达图  
+- 判断 TIRA 类型  
+- 评估 PDI 风险  
+
+---
+    """)
+
+    cn_input = gr.Textbox(lines=4, label="✉ 输入中文邮件")
+
+    mode_select = gr.Radio(
+        ["AI翻译（自动）", "人工翻译（手动输入）"],
+        label="选择翻译模式"
+    )
+
+    human_input = gr.Textbox(lines=2, label="如果选择人工翻译，请输入英文：", placeholder="请在此输入英文译文")
+
+    btn = gr.Button("🔍 运行分析", variant="primary")
+
+    en_out = gr.Textbox(label="🌐 英文结果")
+    score_out = gr.JSON(label="🔬 ���貌特征分布")
+    tira_out = gr.Textbox(label="📌 TIRA 类型")
+    analysis_out = gr.Textbox(label="📘 解释")
+    risk_out = gr.Textbox(label="⚠ PDI 风险")
+    radar_out = gr.Plot(label="📊 礼貌雷达图")
+
+    btn.click(
+        fn=full_process,
+        inputs=[cn_input, mode_select, human_input],
+        outputs=[en_out, score_out, tira_out, analysis_out, risk_out, radar_out]
+    )
+
+demo.launch()