add mongodb log

main.py

@@ -17,6 +17,11 @@ import zipfile
 import uuid  # 匯入 uuid 以生成唯一的執行 ID
 from pathlib import Path # 匯入 Path 以更方便地操作路徑
 import gemini_ai as genai
+from datetime import datetime
+import mongo_lib as mongo
+
+
+
 
 def create_zip_archive(files, zip_filename):
     """
@@ -60,6 +65,20 @@ def gradio_multi_model_detection(
     Yields:
         dict: 用於更新 Gradio 介面元件的字典。
     """
+    global_datetime = datetime.now()
+    
+    #寫主表log
+    document = {"log_style":"master",
+                "create_datetime": str(global_datetime), 
+                "image_files": image_files, 
+                "model_files": model_files,
+                "conf_threshold":conf_threshold,
+                "enable_mllm":enable_mllm,
+                "mllm_prompt":mllm_prompt
+                }
+        
+    mongo.insert_mongodb_log("multi_model_detection",document)  #寫入log方便日後查驗            
+    
     if not image_files:
         yield {
             output_status: gr.update(value="錯誤：請至少上傳一張圖片。"),
@@ -175,6 +194,7 @@ def gradio_multi_model_detection(
 
         # --- 3b. MLLM 分析 (如果啟用) ---
         output_mllm_txt_path = None
+        mllm_result_content = ""
         if enable_mllm:
             try:
                 prompt_to_use = mllm_prompt if mllm_prompt and mllm_prompt.strip() else None
@@ -186,6 +206,17 @@ def gradio_multi_model_detection(
             output_mllm_txt_path = run_output_dir / f"{image_base_name}_mllm_result.txt"
             output_mllm_txt_path.write_text(mllm_result_content, encoding='utf-8')
             all_result_files.append(str(output_mllm_txt_path))
+        
+        #寫明細表log
+        document = {"log_style":"detail",
+                    "create_datetime": str(global_datetime), 
+                    "image_path": str(image_path), 
+                    "yolo_result": yolo_output_content, 
+                    "enable_mllm": enable_mllm,
+                    "mllm_prompt": mllm_prompt,                    
+                    "mllm_result": mllm_result_content}
+        
+        mongo.insert_mongodb_log("multi_model_detection",document)  #寫入log方便日後查驗
 
         # 將本次圖片的結果加入到總列表中
         all_texts.append("\n".join(yolo_output_content))
@@ -200,6 +231,9 @@ def gradio_multi_model_detection(
 
     final_status = f"處理完成！共 {total_images} 張圖片。結果儲存於: {run_output_dir.absolute()}"
     combined_text_output = "\n\n".join(all_texts)
+    
+    
+
 
     yield {
         output_status: gr.update(value=final_status),
@@ -217,7 +251,7 @@ def toggle_mllm_prompt(is_enabled):
 # --- Gradio Interface ---
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
     gr.Markdown("# 智慧影像分析工具 (YOLO + MLLM)")
-    gr.Markdown("上傳圖片與YOLO模型進行物件偵測，並可選用MLLM進行進階圖像理解。")
+    gr.Markdown("上傳圖片與YOLO模型進行物件偵測，並可選用MLLM進行進階圖像理解。   ver.250813.1")
 
     with gr.Row():
         with gr.Column(scale=1):
@@ -260,3 +294,5 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
 if __name__ == "__main__":
     demo.launch(debug=True)
     #demo.launch(share=True)
+
+