NBLM / app.py
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import gradio as gr
def mock_question_answer(question, history):
# 假資料模擬回答
answers = {
"文件的核心觀點是什麼?": "這份文件的核心觀點是關於人工智慧如何提升工作效率。",
"有哪些關鍵詞或數據?": "關鍵詞包括:人工智慧、工作效率、數據分析。",
"文件的摘要是什麼?": "這份文件討論了如何利用人工智慧工具,提升企業的運營效率和決策速度。"
}
response = answers.get(question, "抱歉,我無法回答這個問題。請嘗試其他問題!")
history.append({"role": "user", "content": question})
history.append({"role": "assistant", "content": response})
return history, ""
def mock_summary():
# 假資料模擬摘要
return "這份文件主要討論人工智慧在工作效率提升方面的應用,並提供了實際案例來說明其價值。"
def mock_sources():
# 假資料模擬來源列表
return ["來源一:時間的四則問題", "來源二:新文章"]
def toggle_visibility(current_state):
return gr.update(visible=not current_state)
with gr.Blocks() as demo:
gr.Markdown("# AI Notes Assistant")
with gr.Row():
toggle_sources = gr.Button("顯示/隱藏 來源選單")
toggle_chat = gr.Button("顯示/隱藏 對話區域")
toggle_features = gr.Button("顯示/隱藏 功能卡片")
with gr.Row():
with gr.Column(visible=True) as source_column:
gr.Markdown("### 來源選單")
sources = gr.CheckboxGroup(
choices=mock_sources(), label="選取所有來源", interactive=True
)
upload_file = gr.File(label="從電腦添加文件", file_types=[".txt", ".pdf", ".docx"])
with gr.Column(visible=True) as chat_column:
gr.Markdown("### 對話區域")
chatbot = gr.Chatbot(label="聊天記錄", type="messages")
question = gr.Textbox(label="輸入問題,例如:文件的核心觀點是什麼?")
ask_button = gr.Button("提問")
with gr.Column(visible=True) as feature_column:
gr.Markdown("### 功能卡片")
with gr.Tab("摘要生成"):
summary_button = gr.Button("生成摘要")
summary = gr.Textbox(label="摘要", interactive=False)
with gr.Tab("其他功能"):
gr.Markdown("此處可以添加更多功能卡片")
source_visible = gr.State(True)
chat_visible = gr.State(True)
feature_visible = gr.State(True)
toggle_sources.click(toggle_visibility, inputs=source_visible, outputs=[source_column, source_visible])
toggle_chat.click(toggle_visibility, inputs=chat_visible, outputs=[chat_column, chat_visible])
toggle_features.click(toggle_visibility, inputs=feature_visible, outputs=[feature_column, feature_visible])
history = gr.State([])
ask_button.click(mock_question_answer, inputs=[question, history], outputs=[chatbot, chatbot])
summary_button.click(mock_summary, inputs=[], outputs=[summary])
demo.launch()