Test application

app.py

@@ -1,52 +1,31 @@
 import gradio as gr
 import pandas as pd
 
+with open("./description.md", "r", encoding="utf-8") as file:
+    description_text = file.read()
+
+with open("./placeholder_demo.txt", "r", encoding="utf-8") as file:
+    placeholder_demo = file.read()
+
 # 定义处理函数
 def process_data(task_name, model_name, pooling_method, input_text, file=None):
-    # 模拟数据处理逻辑
     if file:
         df = pd.read_csv(file.name)
         output = f"Processed {len(df)} rows from uploaded file using task: {task_name}, model: {model_name}, pooling: {pooling_method}."
-        dataframe_output = df.head().to_html()  # 显示前几行数据
+        dataframe_output = df  # 返回数据框用于显示
+        file_output = df  # 输出文件框显示相同的数据
     else:
         lines = input_text.split("\n")
         output = f"Processed {len(lines)} rows of text using task: {task_name}, model: {model_name}, pooling: {pooling_method}."
-        dataframe_output = "<p>No file uploaded. DataFrame preview unavailable.</p>"
+        dataframe_output = pd.DataFrame({"Error": ["No file uploaded. DataFrame preview unavailable."]})  # 错误信息
+        file_output = pd.DataFrame()
     
-    return output, dataframe_output, "File processing completed."
+    return output, dataframe_output, file_output
 
 # 使用Blocks定义布局
-with gr.Blocks() as interface:
-    gr.Markdown("# TransDis-CreativityAutoAssessment")
-    gr.Markdown(
-        "Two-Phase Fine-tuned BERTは、bert-base-japaneseモデルに基づいた自動評価システムで、日本語の多用途タスク（AUT）における創造性と適切性を評価するために使用されます（論文はこちら：https://link.springer.com/article/xx.xxxx/sxxxxx-xxx-xxxx-x）。"
-        "プロンプトと回答のデータを入力してください。データは1行ごとに用途を記述し、カンマで区切ってください。"
-        "データは、デモのようにテキストボックスに直接入力するか、カンマ区切りのCSV形式ファイルまたはxlsx形式ファイルをアップロードすることで入力できます。"
-        "評価に使用するモデルは、Two-Phase Fine-tuned BERT の他に One-phase BERT もあり、いずれも日本語にのみ対応しています。"
-        "Two-phase BERTは、低い現実性の回答に対して創造性評価を最適化しており、適切性と創造性の両方を評価できます。"
-        "一方、One-phase BERTは、AUT回答の創造性のみを評価します。"
-        "Pooling方法としてcls-poolingを使用することをお勧めします。"
-        "エラーが発生した場合は、データを簡略化し、行数を減らして試してください。"
-        "それでも解決しない場合は、入力形式が誤っている可能性があるため、CSVとして保存し直してアップロードをお試しください。"
-        "このシステムはHuggingFaceが提供する無料サーバーを使用しており、計算にはCPUのみを使用するため、処理速度が遅い場合があります。"
-        "このスペースをあなたのアカウントにコピー（推奨）し、ハードウェアをアップグレードすることで処理速度を向上させることが可能です。"
-        "その他のサポートやバグ報告については、[email protected]までご連絡ください。"
-        "\n\n"
-        "Two-Phase Fine-tuned BERT is an automatic evaluation system based on the bert-base-japanese model, designed to evaluate creativity and appropriateness in Japanese alternative uses task (AUT) (see the paper at https://link.springer.com/article/xx.xxxx/sxxxxx-xxx-xxxx-x)."
-        "Enter the data consisting of prompts and responses, with one usage per line, separated by commas."
-        "You can input the data directly into the text box as shown in the demos, or upload a comma-separated CSV file or an xlsx file as input."
-        "The models available for evaluation also include One-phase Fine-tuned BERT except for Two-phase Fine-tuned BERT, both of which are applicable only to Japanese."
-        "Two-phase BERT is optimized for creativity scoring for responses with low practicality and can evaluate both appropriateness and creativity."
-        "On the other hand, One-phase BERT is designed solely for evaluating creativity in AUT responses."
-        "We recommend using cls-pooling as the pooling method."
-        " If an error occurs, try simplifying your data by reducing the number of rows."
-        "If this doesn’t resolve the issue, the input format may be incorrect. Please try saving the data again as a comma-separated CSV file before uploading it."
-        "This system uses the free servers provided by HuggingFace, which only support CPU processing, so it may run slowly."
-        "You can copy this space to your account (recommended) and choose upgraded hardware to improve processing speed."
-        "For further assistance or to report bugs, please contact [email protected]."
-        "\n\n"
-        "Reference: Wang, S., ..., (2025). Enhancing Creativity Evaluation in Divergent Thinking: A Two-phase Fine-tuned BERT Incorporating Appropriateness Supervision. https://doi.org/xx.xxxx/sxxxxx-xxx-xxxxx-x"
-    )
+with gr.Blocks(css="./custom_styles.css") as interface:
+    gr.Markdown("<h1 style='text-align: center;'>TwoPhaseBERT-CreativityAutoAssessmen</h1>")
+    gr.Markdown(description_text)
     
     # 固定布局：分成三列
     with gr.Row():
@@ -71,26 +50,34 @@ with gr.Blocks() as interface:
             text_input = gr.Textbox(
                 label="Text Input", 
                 lines=10, 
-                placeholder="Enter text data here..."
+                placeholder=placeholder_demo
             )
             file_input = gr.File(
                 label="Input File", 
                 type="filepath", 
                 file_types=[".csv", ".xlsx"]
             )
+            # 按钮部分
+            with gr.Row():
+                clear_button = gr.Button("Clear", elem_classes="custom-clear")
+                submit_button = gr.Button("Submit", elem_classes="custom-submit")
+                    
         with gr.Column():
-            output_box = gr.Textbox(label="Output", lines=5, interactive=False)
-            dataframe_output = gr.HTML(label="DataFrame Preview")
-            file_output = gr.Textbox(label="Output File Status", interactive=False)
-    
-    # 添加按钮并链接处理函数
-    submit_button = gr.Button("Submit")
+            output_box = gr.Textbox(label="Warning", lines=5, interactive=False)
+            dataframe_output = gr.Dataframe(label="DataFrame", interactive=False)
+            file_output = gr.File(label="Output File", interactive=False)
+
+    # 按钮功能链接
     submit_button.click(
         process_data,
         inputs=[task_dropdown, model_dropdown, pooling_dropdown, text_input, file_input],
         outputs=[output_box, dataframe_output, file_output]
     )
-
+    clear_button.click(
+        lambda: ("", pd.DataFrame(), None),
+        inputs=[],
+        outputs=[output_box, dataframe_output, file_output]
+    )
 
 # 启动界面
 interface.launch()