diff --git a/Ai_tottle/ai_tottle_api.py b/Ai_tottle/ai_tottle_api.py
index c733f80..3230506 100644
--- a/Ai_tottle/ai_tottle_api.py
+++ b/Ai_tottle/ai_tottle_api.py
@@ -1,19 +1,16 @@
+import logging,os,uuid,asyncio,torch
+# sanic imports
 from sanic import Sanic, json, Blueprint,response
 from sanic.exceptions import Unauthorized
 from sanic.response import json as json_response
 from sanic_cors import CORS
-import numpy as np
-import logging
-import uuid
-import os,traceback
-import asyncio
-from ai_image import process_images  # 你实现的图片处理函数
-from queue import Queue
+# ourself imports
+from ai_image import process_images
 from map_find import map_process_images
 from yolo_train import auto_train,query_progress
-import torch
-from yolo_photo import map_process_images_with_progress # 引入你的处理函数
-# 日志配置
+from yolo_photo import map_process_images_with_progress 
+
+# set up logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)
 
@@ -51,8 +48,8 @@ async def token_and_resource_check(request):
 
     return None  # 允许请求继续
 
-##################################################################################################################################################################################################    
-#创建Sanic应用
+################################################################# set up app and blueprints ########################################################################################################
+# create app and cors
 app = Sanic("ai_Service_v2")
 CORS(app) # 允许跨域请求
 task_progress = {}
@@ -196,14 +193,14 @@ async def run_image_processing(task_id, urls, yaml_name, bucket_name, bucket_dir
         task_progress[task_id]["progress"] = 100
         task_progress[task_id]["result"] = str(e)
         
-# YOLO检测API
+# YOLO detect API
 @yolo_tile_blueprint.post("/picture")
 async def yolo_detect_api(request):
     try:
         
         detect_data = request.json
         
-        # 解析必要字段
+        # 
         image_list = detect_data.get("image_list")
         yolo_model = detect_data.get("yolo_model", "best.pt")
         class_filter = detect_data.get("class", None)
@@ -215,11 +212,11 @@ async def yolo_detect_api(request):
         if not minio_info:
             return json_response({"status": "error", "message": "MinIO information is required"}, status=400)
 
-        # 创建临时文件夹
+        # Create a temporary directory for input and output images
         input_folder = f"./temp_input_{str(uuid.uuid4())}"
         output_folder = f"./temp_output_{str(uuid.uuid4())}"
-
-        # 执行图像处理
+        
+        # Execute the image processing in a separate thread to avoid blocking the event loop
         result = await asyncio.to_thread(
             process_images,
             yolo_model=yolo_model,
@@ -230,7 +227,7 @@ async def yolo_detect_api(request):
             minio_info=minio_info
         )
 
-        # 返回处理结果
+        # return the result as JSON response
         return json_response(result)
 
     except Exception as e:
@@ -240,12 +237,12 @@ async def yolo_detect_api(request):
             "message": f"Internal server error: {str(e)}"
         }, status=500)
         
-# YOLO自动训练
+# YOLO auto_train API
 @yolo_tile_blueprint.post("/train")
 async def yolo_train_api(request):
     """
-    自动训练模型
-    输入 JSON:
+    auto_train
+    input JSON:
     {
         "db_host": str,
         "db_database": str,
@@ -260,7 +257,7 @@ async def yolo_train_api(request):
         "class_names": Optional[List[str]],
         "project_name": str
     }
-    输出 JSON:
+    output JSON:
     return {
         "status": "success",
         "message": "Train finished",
@@ -271,18 +268,15 @@ async def yolo_train_api(request):
     }
     """
     try:
-        # 修改为直接访问 request.json 而不是调用它
         data = request.json
-        
         if not data:
             return json_response({"status": "error", "message": "data is required"}, status=400)
-
-        # 执行图像处理
+        # Do the  training in a separate thread to avoid blocking the event loop
         result = await asyncio.to_thread(
             auto_train,
             data
         )
-        # 返回处理结果
+        # return the result as JSON response
         return json_response(result)
     
     except Exception as e:
@@ -292,14 +286,14 @@ async def yolo_train_api(request):
             "message": f"Internal server error: {str(e)}"
         }, status=500)
         
-# 查询训练进度接口
+# access the training progress
 @yolo_tile_blueprint.get("/progress/<project_name>")
 async def yolo_train_progress(request, project_name):
     '''
-    输入参数:
-    如果想查询最新一次训练：GET /yolo/progress/my_project
-    如果想查询某次特定时间：GET /yolo/progress/my_project?run_time=20250902_1012
-    输出 JSON:
+    input:
+    if want to query the latest progress: GET /yolo/progress/my_project
+    if want to query the progress at a specific time: GET /yolo/progress/my_project?run_time=20250902_1012
+    output JSON:
         {
     "status": "ok",
     "run_time": "20250902_1012",
@@ -312,7 +306,11 @@ async def yolo_train_progress(request, project_name):
     }
     }
     '''
-    run_time = request.args.get("run_time")  # 可选参数
+    run_time = request.args.get("run_time")  # get the run_time from the query string
+    # query the progress from the database
+    if not run_time:
+        run_time = None  # if not provided, query the latest progress
+        
     result = await asyncio.to_thread(query_progress, project_name, run_time)
     return json_response(result)