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Update app.py
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app.py
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import os
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import sys
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import gradio as gr
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from deep_translator import GoogleTranslator
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# 1.
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os.system(f"{sys.executable} -m spacy download en_core_web_sm")
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from fastcoref import FCoref
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# 關鍵
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print("🚀 [System] 正在
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def coref_chat(user_input):
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if not user_input.strip():
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return "請輸入內容", "等待輸入..."
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try:
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#
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translated = GoogleTranslator(source='auto', target='en').translate(user_input)
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preds = model.predict(texts=[translated])
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clusters = preds[0].get_clusters()
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result = f"✨【跨語言橋接成功】\n
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result += "---------------------------------\n"
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if not clusters:
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result += "🔍
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else:
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result += "🎯【偵測到之實體鏈】:\n"
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for i, cluster in enumerate(clusters):
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# 介面設定
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demo = gr.Interface(
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fn=coref_chat,
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inputs=gr.Textbox(label="輸入文本", lines=3),
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outputs=[gr.Textbox(label="原始輸入"), gr.Textbox(label="AI 語意報告")],
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title="Janice's AI 跨語言指代消解系統"
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)
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if __name__ == "__main__":
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import os
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import sys
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# 1. 強制下載 Spacy 模型
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os.system(f"{sys.executable} -m spacy download en_core_web_sm")
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# 2. 解決相容性問題的補丁
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try:
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import huggingface_hub
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if not hasattr(huggingface_hub, 'HfFolder'):
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class MockHfFolder:
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@staticmethod
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def get_token(): return os.getenv("HF_TOKEN")
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@staticmethod
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def save_token(token): pass
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huggingface_hub.HfFolder = MockHfFolder
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except:
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pass
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import gradio as gr
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from fastcoref import FCoref
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from deep_translator import GoogleTranslator
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# 關鍵修正:將 model_name 改為 model_name_or_path
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print("🚀 [System] 正在進行阻塞式權重同步(約 300MB)...")
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try:
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# 使用相容性最高的參數名稱
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model = FCoref(model_name_or_path='biu-nlp/f-coref', device='cpu')
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print("✅ [System] 模型載入完成,介面即將開啟。")
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except TypeError:
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# 萬一連上面的都不行,就用最原始的 positional argument
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model = FCoref('biu-nlp/f-coref', device='cpu')
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print("✅ [System] 使用原始參數模式載入完成。")
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def coref_chat(user_input):
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if not user_input.strip():
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return "請輸入內容", "等待輸入..."
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try:
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# 語言橋接
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translated = GoogleTranslator(source='auto', target='en').translate(user_input)
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# 執行消解
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preds = model.predict(texts=[translated])
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clusters = preds[0].get_clusters()
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result = f"✨【跨語言語意橋接成功】\n"
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result += f"解析路徑 (English): {translated}\n"
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result += "---------------------------------\n"
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if not clusters:
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result += "🔍 分析結果:指代關係明確,無需額外消解。"
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else:
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result += "🎯【偵測到之實體鏈】:\n"
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for i, cluster in enumerate(clusters):
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# 介面設定
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demo = gr.Interface(
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fn=coref_chat,
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inputs=gr.Textbox(label="輸入文本", lines=3, placeholder="輸入中文或英文段落..."),
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outputs=[gr.Textbox(label="原始輸入"), gr.Textbox(label="AI 語意分析報告")],
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title="Janice's AI 跨語言指代消解系統 (Stable Version)"
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)
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if __name__ == "__main__":
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