Update app.py

update download fun

app.py

@@ -1,3 +1,6 @@
+import datetime
+import tempfile
+import os
 from openai import OpenAI
 from ocr_mathpix import extract_pdf_mathpix
 import gradio as gr
@@ -242,6 +245,52 @@ def update_input():
     return en_1
 
 
+# 包装函数：把 outputs 的内容写入文件，并显示 File 组件
+def reveal_download_file(content):
+    path = download_markdown(content)
+    if not path:
+        return gr.update(visible=False, value=None)
+    return gr.update(visible=True, value=path)
+
+
+def download_markdown(content):
+    """Save the markdown content to a temporary file with a timestamp."""
+    if not content or content.strip() == "":
+        return None  # 如果内容为空，则不生成文件
+
+    # 生成带时间戳的文件名
+    timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
+    filename = f"enzyme_kinetics_extract_{timestamp}.md"
+
+    # 直接创建带时间戳的文件，避免重命名操作
+    file_path = os.path.join(tempfile.gettempdir(), filename)
+    
+    # 增强文件创建的健壮性，添加重试机制和更完善的错误处理
+    max_retries = 3
+    for attempt in range(max_retries):
+        try:
+            # 检查文件是否已存在，如果存在则添加序号
+            final_path = file_path
+            if os.path.exists(final_path):
+                name, ext = os.path.splitext(file_path)
+                counter = 1
+                while os.path.exists(f"{name}_{counter}{ext}"):
+                    counter += 1
+                final_path = f"{name}_{counter}{ext}"
+            
+            with open(final_path, 'w', encoding='utf-8') as f:
+                f.write(content)
+            return final_path
+        except Exception as e:
+            print(f"Attempt {attempt + 1} failed to create download file: {e}")
+            if attempt == max_retries - 1:
+                print(f"Error creating download file after {max_retries} attempts: {e}")
+                return None  # 返回None表示创建失败
+            # 等待一段时间后重试
+            import time
+            time.sleep(0.1)
+
+
 CSV_FILE_PATH_Golden_Benchmark_Enzyme = "static/Golden Benchmark for Enzyme Kinetics.csv"
 CSV_FILE_PATH_Golden_Benchmark_Ribozyme = "static/Golden Benchmark for Ribozyme Kinetics.csv"
 CSV_FILE_PATH_LLENKA_Dataset = "static/3450_merged_data_2000_lines.csv"
@@ -350,6 +399,11 @@ with gr.Blocks(title="Automated Enzyme Kinetics Extractor") as demo:
         | Enzyme3    | Homo sapiens      | Substrate_C | 6.9 | mM      | 15.6 | s^-1      | 43000   | µM^-1s^-1    | 65°C             | 8.0            | T253S             | NAD^+                   |
         
         """)
+                # 添加下载提取结果按钮和文件组件
+                with gr.Row():
+                    download_file = gr.File(label="Download Extract Result File", interactive=False, visible=False)
+
+                # 添加下载 Markdown 按钮和文件组件
         with gr.Tab("Golden Benchmark for Enzyme Kinetics"):
             gr.Markdown(
                 '''<h1 align="center"> Golden Benchmark Viewer with Advanced Search </h1>
@@ -459,7 +513,8 @@ with gr.Blocks(title="Automated Enzyme Kinetics Extractor") as demo:
     extract_button_md.click(extract_pdf_md, inputs=file_input, outputs=text_output)
     extract_button_text.click(extract_pdf_pypdf, inputs=file_input, outputs=text_output)
     exp.click(update_input, outputs=model_input)
-    gen.click(fn=predict, inputs=[model_input, text_output, model_dropdown, temp_slider], outputs=outputs)
+    gen.click(fn=predict, inputs=[model_input, text_output, model_dropdown, temp_slider], outputs=outputs) \
+        .then(fn=reveal_download_file, inputs=outputs, outputs=download_file)
     clr.click(fn=lambda: [gr.update(value=""), gr.update(value="")], inputs=None, outputs=[model_input, outputs])
     viewer_button.click(display_pdf_images, inputs=file_input, outputs=file_out)