diff --git a/.env_dev b/.env_dev
index 2e9062b..e3db319 100644
--- a/.env_dev
+++ b/.env_dev
@@ -1,4 +1,5 @@
 MEDIA_ROOT=/app/media
+LOG_ROOT=/app/log
 # DATABASE django setup
 DB_ENGINE=django.db.backends.postgresql_psycopg2
 DB_SCHEMA=sbt_prod_20240422_1
diff --git a/.gitignore b/.gitignore
index 8b3fae4..780a617 100644
--- a/.gitignore
+++ b/.gitignore
@@ -44,4 +44,5 @@ cope2n-api/reviewed/retailer.xlsx
 /scripts/*
 scripts/crawl_database.py
 redundant_models/
-junk.json
\ No newline at end of file
+junk.json
+cope2n-api/result.json
diff --git a/README.md b/README.md
index d160bf8..41dfe3f 100644
--- a/README.md
+++ b/README.md
@@ -13,7 +13,7 @@ docker compose --profile local up -d
 
 ```bash
 pip install pytest requests deepdiff
-IDP_HOST=https://sbt.idp.sdsrv.ai IDP_USERNAME=sbt IDP_PASSWORD=7Eg4AbWIXDnufgn python3 -m pytest --log-cli-level=DEBUG --capture=sys tests
+IDP_HOST=http://ocrnlb-stagging-671b98778cba8a08.elb.ap-southeast-1.amazonaws.com IDP_USERNAME=sbt IDP_PASSWORD=7Eg4AbWIXDnufgn python3 -m pytest --log-cli-level=DEBUG --capture=sys tests
 ```
 IDP_HOST=http://ec2-54-169-227-39.ap-southeast-1.compute.amazonaws.com:9881 IDP_USERNAME=sbt IDP_PASSWORD=abc python3 -m pytest --log-cli-level=DEBUG --capture=sys tests
 
diff --git a/cope2n-api/EDA/processing_time.ipynb b/cope2n-api/EDA/processing_time.ipynb
index ee77961..516eba9 100644
--- a/cope2n-api/EDA/processing_time.ipynb
+++ b/cope2n-api/EDA/processing_time.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12,7 +12,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,35 +24,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/tmp/ipykernel_3211990/3052953344.py:1: DeprecationWarning: \n",
-      "Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n",
-      "(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n",
-      "but was not found to be installed on your system.\n",
-      "If this would cause problems for you,\n",
-      "please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n",
-      "        \n",
-      "  import pandas as pd\n"
-     ]
-    },
-    {
-     "ename": "ModuleNotFoundError",
-     "evalue": "No module named 'matplotlib'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[1], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpyplot\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mplt\u001b[39;00m\n\u001b[1;32m      3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01msys\u001b[39;00m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mos\u001b[39;00m\n",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'matplotlib'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# !export DB_ENGINE=django.db.backends.postgresql_psycopg2\n",
     "# !export DB_SCHEMA=sbt_prod_20240422_1\n",
@@ -65,24 +39,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/tmp/ipykernel_2597006/3052953344.py:1: DeprecationWarning: \n",
-      "Pyarrow will become a required dependency of pandas in the next major release of pandas (pandas 3.0),\n",
-      "(to allow more performant data types, such as the Arrow string type, and better interoperability with other libraries)\n",
-      "but was not found to be installed on your system.\n",
-      "If this would cause problems for you,\n",
-      "please provide us feedback at https://github.com/pandas-dev/pandas/issues/54466\n",
-      "        \n",
-      "  import pandas as pd\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
     "import matplotlib.pyplot as plt\n",
@@ -111,17 +70,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
-    "start_date_str = \"2024-04-01T00:00:00+0800\"\n",
-    "end_date_str = \"2024-06-01T00:00:00+0800\""
+    "start_date_str = \"2024-05-25T00:00:00+0800\"\n",
+    "end_date_str = \"2024-06-24T00:00:00+0800\""
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -132,7 +91,7 @@
     "    end_date = timezone.datetime.strptime(end_date_str, '%Y-%m-%dT%H:%M:%S%z')\n",
     "    # start_date = timezone.make_aware(start_date)\n",
     "    # end_date = timezone.make_aware(end_date)\n",
-    "    base_query &= Q(redemption_id__startswith=\"SG\")\n",
+    "    base_query &= Q(redemption_id__startswith=\"AU\")\n",
     "    base_query &= Q(created_at__range=(start_date, end_date))\n",
     "    subscription_requests = SubscriptionRequest.objects.filter(base_query).order_by('created_at')\n",
     "    return subscription_requests\n"
@@ -140,7 +99,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -149,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -198,36 +157,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|██████████| 9037/9037 [00:00<00:00, 166939.40it/s]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "result_by_request, result_by_file, result_by_file_type = process(subscription_requests)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
     "frame_by_file = pd.DataFrame(result_by_file)\n",
     "frame_by_request = pd.DataFrame(result_by_request)\n",
     "frame_by_imei = pd.DataFrame(result_by_file_type[\"imei\"])\n",
-    "frame_by_invoice = pd.DataFrame(result_by_file_type[\"invoice\"])"
+    "frame_by_invoice = pd.DataFrame(result_by_file_type[\"invoice\"])\n",
+    "\n",
+    "frame_by_request[\"image_avg_cost\"] = (frame_by_request[\"backend_cost\"] + frame_by_request[\"request_cost\"])/frame_by_request[\"number_of_file\"]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -239,7 +192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -254,7 +207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -291,14 +244,23 @@
     "        edges = filtered_x\n",
     "\n",
     "\n",
-    "    average = np.mean(bin_avg)\n",
+    "    average = np.mean(y)\n",
+    "    highest = np.max(y)\n",
+    "    lowest = np.min(y)\n",
+    "\n",
     "    date_time = []\n",
     "    for e in edges:\n",
     "        date_time.append(to_datetime(e))\n",
     "    plt.plot(edges, bin_avg)\n",
     "    # plt.plot(filtered_x, filtered_y)\n",
-    "    plt.axhline(average, color='red', linestyle='--', label='Average')\n",
+    "    plt.axhline(average, color='orange', linestyle='--', label='Average')\n",
     "    plt.text(x[-1], average, f'Avg: {average:.2f}', ha='right', va='center')\n",
+    "\n",
+    "    plt.axhline(highest, color='red', linestyle='--', label='Highest')\n",
+    "    plt.text(x[-1], highest, f'High: {highest:.2f}', ha='right', va='center')\n",
+    "\n",
+    "    plt.axhline(lowest, color='green', linestyle='--', label='Lowest')\n",
+    "    plt.text(x[-1], lowest, f'Avg: {lowest:.2f}', ha='right', va='center')\n",
     "    plt.xlabel('Timestamp')\n",
     "    plt.ylabel('Processing Time (seconds)')\n",
     "    plt.title(title)\n",
@@ -308,164 +270,194 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
+   "source": [
+    "plot_trend(frame_by_request.index, frame_by_request[\"image_avg_cost\"], \"Image average cost\", outliner_threah=95, num_bins=30)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "plot_trend(frame_by_request.index, frame_by_request[\"backend_cost\"], \"Backend cost Trend\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_trend(frame_by_request.index, frame_by_request[\"request_cost\"], \"Request_cost Trend\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_trend(frame_by_request.index, frame_by_request[\"number_of_file\"], \"Files in a request Trend\", outliner_threah=None, num_bins=30)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_trend(frame_by_file.index, frame_by_file[\"postprocessing\"], \"AI postprocessing Trend\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_trend(frame_by_imei.index, frame_by_imei[\"inference\"], \"IMEI Inference Trend\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_trend(frame_by_invoice.index, frame_by_invoice[\"inference\"], \"Invoice Inference Trend\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_trend(frame_by_file.index, frame_by_file[\"inference\"], \"AI inference Trend\")\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plot_trend(frame_by_file.index, frame_by_file[\"queue\"], \"AI queuing Trend\")\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def split_timestamps_by_day(timestamps):\n",
+    "    \"\"\"\n",
+    "    Splits a list of timestamps into a list of lists, where each inner list contains the timestamps for a single day.\n",
+    "    \n",
+    "    Args:\n",
+    "        timestamps (list): A list of timestamp values.\n",
+    "        \n",
+    "    Returns:\n",
+    "        list: A list of lists, where each inner list contains the timestamps for a single day.\n",
+    "    \"\"\"\n",
+    "    # Convert timestamps to datetime objects\n",
+    "    datetimes = [pd.Timestamp(t, unit='s') for t in timestamps]\n",
+    "    \n",
+    "    # Create a DataFrame with the datetime objects\n",
+    "    df = pd.DataFrame({'timestamp': datetimes})\n",
+    "    \n",
+    "    # Group the DataFrame by day and collect the timestamps for each day\n",
+    "    timestamps_by_day = []\n",
+    "    for _, group in df.groupby(pd.Grouper(key='timestamp', freq='D')):\n",
+    "        day_timestamps = [t.timestamp() for t in group['timestamp']]\n",
+    "        timestamps_by_day.append(day_timestamps)\n",
+    "    \n",
+    "    return timestamps_by_day"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def visualize_requests_by_time(timestamps_by_day):\n",
+    "    \"\"\"\n",
+    "    Generates a histogram to visualize the number of requests received by time.\n",
+    "    \n",
+    "    Args:\n",
+    "        timestamps (list): A list of timestamps (in seconds) representing the time when each request was received.\n",
+    "    \"\"\"\n",
+    "    num_days = len(timestamps_by_day)\n",
+    "    fig, axes = plt.subplots(nrows=int(np.ceil(num_days / 2)), ncols=2, figsize=(90, 450))\n",
+    "    for i, day_timestamps in enumerate(timestamps_by_day):\n",
+    "        row = i // 2\n",
+    "        col = i % 2\n",
+    "        \n",
+    "        day_timestamps = [pd.Timestamp(t, unit='s') for t in day_timestamps]\n",
+    "        # Get the current axis\n",
+    "        ax = axes[row, col] if num_days > 1 else axes\n",
+    "        \n",
+    "        # Plot the histogram for the current day\n",
+    "        ax.hist(pd.to_datetime(day_timestamps), bins=60*24, edgecolor='black')\n",
+    "        # ax.xticks(rotation=45)\n",
+    "        ax.set_title(f\"Day {i+1}\")\n",
+    "        ax.set_xlabel(\"Time\")\n",
+    "        ax.set_ylabel(\"Count\")\n",
+    "\n",
+    "        ax2 = ax.twinx()\n",
+    "        ax2.set_ylabel(\"Time Process (s)\")\n",
+    "        ax2.set_ylim(min(day_timestamps), max(day_timestamps))\n",
+    "    # Convert timestamps to datetime objects\n",
+    "    # timestamps = [pd.Timestamp(t, unit='s') for t in timestamps]\n",
+    "    \n",
+    "    # # Create a histogram with 24 bins (one for each hour of the day)\n",
+    "    # plt.figure(figsize=(12, 6))\n",
+    "    # # plt.hist(pd.to_datetime([t.hour for t in timestamps], unit='h'), bins=24, edgecolor='black')\n",
+    "    # plt.hist(pd.to_datetime(timestamps), bins=1000, edgecolor='black')\n",
+    "    \n",
+    "    # Set x-axis labels to show the hour of the day\n",
+    "    # x_labels = [f'{i:02d}:00' for i in range(24)]\n",
+    "    # plt.xticks(np.arange(0, 24), x_labels, rotation=45)\n",
+    "    # plt.xticks(rotation=45)\n",
+    "    # plt.xlabel('Hour of the Day')\n",
+    "    # plt.ylabel('Number of Requests')\n",
+    "    # plt.title('Requests Received by Time of Day')\n",
+    "    # plt.show()\n",
+    "    plt.suptitle(\"Distribution of Requests by Time\")\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# timestamps_by_day=split_timestamps_by_day(result_by_file[\"created\"])\n",
+    "# visualize_requests_by_time(timestamps_by_day)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",
diff --git a/cope2n-api/fwd/settings.py b/cope2n-api/fwd/settings.py
index 48270c6..8548f92 100755
--- a/cope2n-api/fwd/settings.py
+++ b/cope2n-api/fwd/settings.py
@@ -76,6 +76,7 @@ MIDDLEWARE = [
     'corsheaders.middleware.CorsMiddleware',
     "whitenoise.middleware.WhiteNoiseMiddleware",
     "django.middleware.locale.LocaleMiddleware",
+    "fwd_api.middleware.logging_request_response_middleware.LoggingMiddleware"
 ]
 
 LOCALE_PATHS = [
@@ -207,6 +208,7 @@ FILE_UPLOAD_HANDLERS = [
 CORS_ORIGIN_ALLOW_ALL = True
 
 MEDIA_ROOT = env.str("MEDIA_ROOT", default=r"/var/www/example.com/media/")
+LOG_ROOT = env.str("LOG_ROOT", default="/app/log")
 BROKER_URL = env.str("BROKER_URL", default="amqp://test:test@107.120.70.226:5672//")
 CELERY_TASK_TRACK_STARTED = True
 # CELERY_TASK_TIME_LIMIT = 30 * 60
@@ -255,4 +257,43 @@ CACHES = {
     'default': {
         'BACKEND': 'django.core.cache.backends.dummy.DummyCache',
     }
+}
+
+LOGGING = {
+    'version': 1,
+    'disable_existing_loggers': False,
+    'formatters': {
+        'verbose': {
+            'format': '{levelname} {asctime} {module} {message}',
+            'style': '{',
+        },
+        'simple': {
+            'format': '{levelname} {message}',
+            'style': '{',
+        },
+    },
+    'handlers': {
+        'console': {
+            'class': 'logging.StreamHandler',
+            'formatter': 'verbose',
+        },
+        'file': {
+            "class": 'logging.handlers.TimedRotatingFileHandler',
+            'filename': f'{LOG_ROOT}/sbt_idp_BE.log',  # Specify the path and filename for the log file
+            "when": "midnight",
+            "interval": 1,
+            'backupCount': 10,
+            'formatter': 'verbose',
+        },
+    },
+    'loggers': {
+        'django': {
+            'handlers': ['console', 'file'],
+            'level': 'INFO',
+        },
+        '': {
+            'handlers': ['console', 'file'],
+            'level': 'INFO',
+        }
+    },
 }
\ No newline at end of file
diff --git a/cope2n-api/fwd_api/api/accuracy_view.py b/cope2n-api/fwd_api/api/accuracy_view.py
index f46af55..e4295f0 100755
--- a/cope2n-api/fwd_api/api/accuracy_view.py
+++ b/cope2n-api/fwd_api/api/accuracy_view.py
@@ -26,6 +26,9 @@ from ..utils.subsidiary import map_subsidiary_long_to_short, map_subsidiary_shor
 from ..utils.report import aggregate_overview
 from fwd_api.utils.accuracy import predict_result_to_ready
 import copy
+import logging
+
+logger = logging.getLogger(__name__)
 
 redis_client = RedisUtils()
 
@@ -227,8 +230,8 @@ class AccuracyViewSet(viewsets.ViewSet):
                             retailer = rq.predict_result.get("content", {}).get("document", [])[
                                 0].get("content", [])[0].get("value", [])
                 except Exception as e:
-                    print(f"[ERROR]: {e}")
-                    print(f"[ERROR]: {rq}")
+                    logger.error(f"{e}")
+                    logger.error(f"{rq}")
                 data.append({
                     'RequestID': rq.request_id,
                     'RedemptionID': rq.redemption_id,
@@ -603,8 +606,8 @@ class AccuracyViewSet(viewsets.ViewSet):
                         subsidiary_overview_reports += this_overview
 
                     except Exception as e:
-                        print(
-                            f"[WARM]: Unable to retrive data {key} from Redis, skipping...")
+                        logger.warn(
+                            f"Unable to retrive data {key} from Redis, skipping...")
                 data = aggregate_overview(subsidiary_overview_reports)
                 for item in data:
                     if item.get("subs") == "+":
diff --git a/cope2n-api/fwd_api/api/ctel_template_view.py b/cope2n-api/fwd_api/api/ctel_template_view.py
index ffbb216..8e4efed 100755
--- a/cope2n-api/fwd_api/api/ctel_template_view.py
+++ b/cope2n-api/fwd_api/api/ctel_template_view.py
@@ -21,7 +21,9 @@ from ..utils import file as FileUtils
 from ..utils import process as ProcessUtil
 from ..utils.process import UserData
 from drf_spectacular.utils import extend_schema
+import logging
 
+logger = logging.getLogger(__name__)
 
 class CtelTemplateViewSet(viewsets.ViewSet):
     lookup_field = "username"
@@ -121,7 +123,7 @@ class CtelTemplateViewSet(viewsets.ViewSet):
         serializer = CreateTemplateRequest(data=request.data)
         serializer.is_valid()
         if not serializer.is_valid():
-            print(serializer.errors)
+            logger.error(serializer.errors)
             raise InvalidException(excArgs=list(serializer.errors.keys()))
         data = serializer.validated_data
 
@@ -156,7 +158,7 @@ class CtelTemplateViewSet(viewsets.ViewSet):
         serializer = UpdateTemplateRequest(data=data)
         serializer.is_valid()
         if not serializer.is_valid():
-            print(serializer.errors)
+            logger.error(serializer.errors)
             raise InvalidException(excArgs=list(serializer.errors.keys()))
         data = serializer.validated_data
 
diff --git a/cope2n-api/fwd_api/api/ctel_user_view.py b/cope2n-api/fwd_api/api/ctel_user_view.py
index 4114b55..1a2604b 100755
--- a/cope2n-api/fwd_api/api/ctel_user_view.py
+++ b/cope2n-api/fwd_api/api/ctel_user_view.py
@@ -21,6 +21,9 @@ from ..utils.crypto import sds_authenticator, admin_sds_authenticator, SdsAuthen
 import datetime
 from ..request.LoginRequest import LoginRequest
 from ..utils.date import default_zone
+import logging
+
+logger = logging.getLogger(__name__)
 
 from fwd import settings
 
@@ -45,7 +48,7 @@ class CtelUserViewSet(viewsets.ViewSet):
     @action(detail=False, url_path="login", methods=["POST"])
     def login(self, request):
         serializer = LoginRequest(data=request.data)
-        print(serializer.is_valid(raise_exception=True))
+        logger.error(serializer.is_valid(raise_exception=True))
 
         data = serializer.validated_data
         token_limit = 999999
@@ -157,7 +160,7 @@ class CtelUserViewSet(viewsets.ViewSet):
         serializer = UpsertUserRequest(data=request.data)
         serializer.is_valid()
         if not serializer.is_valid():
-            print(serializer.errors)
+            logger.error(serializer.errors)
             raise InvalidException(excArgs=list(serializer.errors.keys()))
         data = serializer.validated_data
 
diff --git a/cope2n-api/fwd_api/api/ctel_view.py b/cope2n-api/fwd_api/api/ctel_view.py
index 379dff7..dacf052 100755
--- a/cope2n-api/fwd_api/api/ctel_view.py
+++ b/cope2n-api/fwd_api/api/ctel_view.py
@@ -24,6 +24,9 @@ from ..models import SubscriptionRequest, SubscriptionRequestFile, OcrTemplate,
 from ..response.ReportSerializer import ReportSerializer
 from ..utils import file as FileUtils
 from ..utils import process as ProcessUtil
+import logging
+
+logger = logging.getLogger(__name__)
 
 class CtelViewSet(viewsets.ViewSet):
     lookup_field = "username"
@@ -92,8 +95,8 @@ class CtelViewSet(viewsets.ViewSet):
         elif file_extension in image_extensions:
             b_url = ProcessUtil.process_image_file(file_name, file_obj, new_request, user, "all", 0)
             j_time = time.time()
-            print(f"[INFO]: Duration of Pre-processing: {j_time - s_time}s")
-            print(f"[INFO]: b_url: {b_url}")
+            logger.info(f"Duration of Pre-processing: {j_time - s_time}s")
+            logger.info(f"b_url: {b_url}")
             if p_type in standard_ocr_list:
                 ProcessUtil.send_to_queue2(rq_id + "_sub_0", sub.id, b_url, user.id, p_type)
             if p_type == ProcessType.TEMPLATE_MATCHING.value:
@@ -441,7 +444,7 @@ class CtelViewSet(viewsets.ViewSet):
             content_type = 'application/pdf' if temp.file_name.split(".")[-1] in pdf_extensions else content_type
             if user.id != user_data['internal_id'] or user.status != EntityStatus.ACTIVE.value:
                 raise PermissionDeniedException()
-            print(temp.file_path)
+            logger.info(temp.file_path)
             return HttpResponse(FileWrapper(FileUtils.get_file(temp.file_path)), status=status.HTTP_200_OK,
                                 headers={'Content-Disposition': 'filename={fn}'.format(fn=temp.file_name)},
                                 content_type=content_type)
@@ -459,7 +462,6 @@ class CtelViewSet(viewsets.ViewSet):
 
                 if user.id != user_data['internal_id'] or user.status != EntityStatus.ACTIVE.value:
                     raise PermissionDeniedException()
-                # print(f"[DEBUG]: rq: {rq}, file_name: {file_name}")
                 file_data = SubscriptionRequestFile.objects.filter(request=rq, file_name=file_name)[0]
             except IndexError:
                 raise NotFoundException(excArgs='file')
@@ -527,7 +529,6 @@ class CtelViewSet(viewsets.ViewSet):
 
         serializer: ReportSerializer = ReportSerializer(data=report_filter, many=True)
         serializer.is_valid()
-        # print(f"[DEBUG]: result: {serializer.data[0]}")
         if report_filter[0].status == 400:
             raise FileContentInvalidException()
         if report_filter[0].status == 100: # continue, only return when result is fullfilled
diff --git a/cope2n-api/fwd_api/celery_worker/client_connector.py b/cope2n-api/fwd_api/celery_worker/client_connector.py
index 5394c8e..76e90df 100755
--- a/cope2n-api/fwd_api/celery_worker/client_connector.py
+++ b/cope2n-api/fwd_api/celery_worker/client_connector.py
@@ -2,8 +2,25 @@ from celery import Celery
 
 from fwd import settings
 from fwd_api.exception.exceptions import GeneralException
+from kombu.utils.uuid import uuid
+from celery.utils.log import get_task_logger
+logger = get_task_logger(__name__)
 
 
+def is_it_an_index(id):
+    ret = True
+    if not isinstance(id, str):
+        logger.info("NOT A STRING")
+        return False
+    if "/" in id:
+        logger.info("/ in ID")
+        return False
+    if id.count("_") > 5 or id.count("_") < 1:
+        _c = id.count("_")
+        logger.info(f"_ HAS {_c}")
+        return False
+    return ret
+
 class CeleryConnector:
     task_routes = {
         # save result
@@ -110,6 +127,8 @@ class CeleryConnector:
     def send_task(self, name=None, args=None, countdown=None):
         if name not in self.task_routes or 'queue' not in self.task_routes[name]:
             raise GeneralException("System")
-        return self.app.send_task(name, args, queue=self.task_routes[name]['queue'], expires=300, countdown=countdown)
+        task_id = args[0] + "_" + uuid()[:4] if isinstance(args, tuple) and is_it_an_index(args[0]) else uuid()
+        logger.info(f"SEND task name: {name} - {task_id} | args: {args} | countdown: {countdown}")
+        return self.app.send_task(name, args, queue=self.task_routes[name]['queue'], expires=300, countdown=countdown, task_id=task_id)
 
 c_connector = CeleryConnector()
diff --git a/cope2n-api/fwd_api/celery_worker/internal_task.py b/cope2n-api/fwd_api/celery_worker/internal_task.py
index 90a7a68..f2e4c04 100755
--- a/cope2n-api/fwd_api/celery_worker/internal_task.py
+++ b/cope2n-api/fwd_api/celery_worker/internal_task.py
@@ -7,6 +7,7 @@ from multiprocessing.pool import ThreadPool
 
 from fwd_api.models import SubscriptionRequest, UserProfile
 from fwd_api.celery_worker.worker import app
+from fwd_api.celery_worker.task_warpper import VerboseTask
 from ..constant.common import FolderFileType, image_extensions
 from ..exception.exceptions import FileContentInvalidException
 from fwd_api.models import SubscriptionRequestFile, FeedbackRequest, Report
@@ -23,7 +24,6 @@ from fwd_api.utils.accuracy import predict_result_to_ready
 from celery.utils.log import get_task_logger
 from fwd import settings
 
-
 logger = get_task_logger(__name__)
 
 s3_client = S3Util.MinioS3Client(
@@ -66,7 +66,7 @@ def process_image_file(file_name: str, file_path, request, user) -> list:
         'request_file_id': new_request_file.code
     }]
 
-@app.task(name="csv_feedback")
+@app.task(base=VerboseTask, name="csv_feedback")
 def process_csv_feedback(csv_file_path, feedback_id):
     # load file to RAM
     status = {}
@@ -124,7 +124,7 @@ def process_csv_feedback(csv_file_path, feedback_id):
                 try:
                     image.processing_time = time_cost.get(image.doc_type, [0 for _ in range(image.index_in_request)])[image.index_in_request]
                 except Exception as e:
-                    print(f"[ERROR] image.doc_type: {image.doc_type} - image.index_in_request: {image.index_in_request} - time_cost: {time_cost} - {e}")
+                    logger.error(f"image.doc_type: {image.doc_type} - image.index_in_request: {image.index_in_request} - time_cost: {time_cost} - {e}")
                 if not validate_feedback_file(_feedback_result, _predict_result):
                     status[request_id] = "Missalign imei number between feedback and predict"
                     # continue
@@ -138,7 +138,7 @@ def process_csv_feedback(csv_file_path, feedback_id):
                         _predict_result = {"retailername": None, "sold_to_party": None, "invoice_no": None, "purchase_date": [], "imei_number": [_predict_result["imei_number"][image.index_in_request]]}
                         _feedback_result = {"retailername": None, "sold_to_party": None, "invoice_no": None, "purchase_date": None, "imei_number": [_feedback_result["imei_number"][image.index_in_request]]} if _feedback_result and len(_feedback_result["imei_number"]) > image.index_in_request else None
                     except Exception as e:
-                        print (f"[ERROR]: {request_id} - {e}")
+                        logger.error(f"{request_id} - {e}")
                 image.predict_result = _predict_result
                 image.feedback_result = _feedback_result
                 # image.reviewed_result = _reviewed_result
@@ -160,10 +160,9 @@ def process_csv_feedback(csv_file_path, feedback_id):
             os.remove(file_path)
         except Exception as e:
             logger.error(f"Unable to set S3: {e}")
-            print(f"Unable to set S3: {e}")
     feedback_rq.save()
 
-@app.task(name='do_pdf')
+@app.task(base=VerboseTask, name='do_pdf')
 def process_pdf(rq_id, sub_id, p_type, user_id, files):
     """
     files: [{
@@ -229,7 +228,7 @@ def process_pdf(rq_id, sub_id, p_type, user_id, files):
     for sub_rq_id, sub_id, urls, user_id, p_type, metadata in to_queue:
         ProcessUtil.send_to_queue2(sub_rq_id, sub_id, urls, user_id, p_type, metadata)
 
-@app.task(name='upload_file_to_s3')
+@app.task(base=VerboseTask, name='upload_file_to_s3')
 def upload_file_to_s3(local_file_path, s3_key, request_id):
     if s3_client.s3_client is not None:
         try:
@@ -239,12 +238,11 @@ def upload_file_to_s3(local_file_path, s3_key, request_id):
             sub_request.save()
         except Exception as e:
             logger.error(f"Unable to set S3: {e}")
-            print(f"Unable to set S3: {e}")
             return
     else:
         logger.info(f"S3 is not available, skipping,...")
 
-@app.task(name='upload_feedback_to_s3')
+@app.task(base=VerboseTask, name='upload_feedback_to_s3')
 def upload_feedback_to_s3(local_file_path, s3_key, feedback_id):
     if s3_client.s3_client is not None:
         try:
@@ -254,12 +252,11 @@ def upload_feedback_to_s3(local_file_path, s3_key, feedback_id):
             feed_request.save()
         except Exception as e:
             logger.error(f"Unable to set S3: {e}")
-            print(f"Unable to set S3: {e}")
             return
     else:
         logger.info(f"S3 is not available, skipping,...")
 
-@app.task(name='upload_report_to_s3')
+@app.task(base=VerboseTask, name='upload_report_to_s3')
 def upload_report_to_s3(local_file_path, s3_key, report_id, delay):
     if s3_client.s3_client is not None:
         try:
@@ -271,20 +268,19 @@ def upload_report_to_s3(local_file_path, s3_key, report_id, delay):
                 report.save()
         except Exception as e:
             logger.error(f"Unable to set S3: {e}")
-            print(f"Unable to set S3: {e}")
             return
     else:
         logger.info(f"S3 is not available, skipping,...")
 
-@app.task(name='remove_local_file')
+@app.task(base=VerboseTask, name='remove_local_file')
 def remove_local_file(local_file_path, request_id):
-    print(f"[INFO] Removing local file: {local_file_path}, ...")
+    logger.info(f"Removing local file: {local_file_path}, ...")
     try:
         os.remove(local_file_path)
     except Exception as e:
         logger.info(f"Unable to remove local file: {e}")
 
-@app.task(name='upload_obj_to_s3')
+@app.task(base=VerboseTask, name='upload_obj_to_s3')
 def upload_obj_to_s3(byte_obj, s3_key):
     if s3_client.s3_client is not None:
         obj = base64.b64decode(byte_obj)
diff --git a/cope2n-api/fwd_api/celery_worker/process_report_tasks.py b/cope2n-api/fwd_api/celery_worker/process_report_tasks.py
index cc0a5fb..a93faa7 100755
--- a/cope2n-api/fwd_api/celery_worker/process_report_tasks.py
+++ b/cope2n-api/fwd_api/celery_worker/process_report_tasks.py
@@ -2,6 +2,7 @@ import traceback
 
 from fwd_api.models import SubscriptionRequest, Report, ReportFile
 from fwd_api.celery_worker.worker import app
+from fwd_api.celery_worker.task_warpper import VerboseTask
 from ..utils import s3 as S3Util
 from ..utils.accuracy import (update_temp_accuracy, IterAvg,
                               count_transactions, extract_report_detail_list, calculate_a_request,
@@ -37,7 +38,7 @@ def mean_list(l):
         return 0
     return sum(l)/len(l)
 
-@app.task(name='make_a_report_2')
+@app.task(base=VerboseTask, name='make_a_report_2')
 def make_a_report_2(report_id, query_set):
     report_type = query_set.pop("report_type", "accuracy")
     if report_type == "accuracy":
@@ -236,11 +237,11 @@ def create_accuracy_report(report_id, **kwargs):
         s3_key = save_report_to_S3(report.report_id, local_workbook)
 
     except IndexError as e:
-        print(e)
+        logger.error(e)
         traceback.print_exc()
-        print("NotFound request by report id, %d", report_id)
+        logger.error("NotFound request by report id, %d", report_id)
     except Exception as e:
-        print("[ERROR]: an error occured while processing report: ", report_id)
+        logger.error("An error occured while processing report: ", report_id)
         traceback.print_exc()
         return 400
 
@@ -286,10 +287,10 @@ def create_billing_report(report_id, **kwargs):
         local_workbook = save_workbook_file(detail_file_name, report, data_workbook)
         s3_key = save_report_to_S3(report.report_id, local_workbook)
     except IndexError as e:
-        print(e)
+        logger.error(e)
         traceback.print_exc()
-        print("NotFound request by report id, %d", report_id)
+        logger.error("NotFound request by report id, %d", report_id)
     except Exception as e:
-        print("[ERROR]: an error occured while processing report: ", report_id)
+        logger.error("An error occured while processing report: ", report_id)
         traceback.print_exc()
         return 400
diff --git a/cope2n-api/fwd_api/celery_worker/process_result_tasks.py b/cope2n-api/fwd_api/celery_worker/process_result_tasks.py
index 331e7f1..ac6f253 100755
--- a/cope2n-api/fwd_api/celery_worker/process_result_tasks.py
+++ b/cope2n-api/fwd_api/celery_worker/process_result_tasks.py
@@ -12,6 +12,10 @@ from fwd_api.models import SubscriptionRequest, SubscriptionRequestFile
 from fwd_api.constant.common import ProcessType
 from fwd_api.utils.redis import RedisUtils
 from fwd_api.utils import process as ProcessUtil
+from fwd_api.celery_worker.task_warpper import VerboseTask
+from celery.utils.log import get_task_logger
+
+logger = get_task_logger(__name__)
 
 redis_client = RedisUtils()
 
@@ -55,11 +59,10 @@ def aggregate_result(results):
     return des_result
 
 def print_id(rq_id):
-    print(" [x] Received {rq}".format(rq=rq_id))
+    logger.info(" [x] Received {rq}".format(rq=rq_id))
 
 
 def to_status(result):
-    print('X')
     if 'status' in result and result['status'] not in [200, 201, 202]:
         return 4
     return 3
@@ -72,7 +75,7 @@ def update_user(rq: SubscriptionRequest):
         sub.current_token += ProcessUtil.token_value(int(rq.process_type))
         sub.save()
 
-@app.task(name='process_sap_invoice_result')
+@app.task(base=VerboseTask, name='process_sap_invoice_result')
 def process_invoice_sap_result(rq_id, result):
     try:
         rq: SubscriptionRequest = \
@@ -85,16 +88,16 @@ def process_invoice_sap_result(rq_id, result):
 
         update_user(rq)
     except IndexError as e:
-        print(e)
-        print("NotFound request by requestId, %d", rq_id)
+        logger.error(e)
+        logger.error("NotFound request by requestId, %d", rq_id)
     except Exception as e:
-        print(e)
-        print("Fail Invoice %d", rq_id)
+        logger.error(e)
+        logger.error("Fail Invoice %d", rq_id)
         traceback.print_exc()
         return "FailInvoice"
 
 
-@app.task(name='process_fi_invoice_result')
+@app.task(base=VerboseTask, name='process_fi_invoice_result')
 def process_invoice_fi_result(rq_id, result):
     try:
         rq: SubscriptionRequest = \
@@ -107,15 +110,15 @@ def process_invoice_fi_result(rq_id, result):
 
         update_user(rq)
     except IndexError as e:
-        print(e)
-        print("NotFound request by requestId, %d", rq_id)
+        logger.error(e)
+        logger.error("NotFound request by requestId, %d", rq_id)
     except Exception as e:
-        print(e)
-        print("Fail Invoice %d", rq_id)
+        logger.error(e)
+        logger.error("Fail Invoice %d", rq_id)
         traceback.print_exc()
         return "FailInvoice"
     
-@app.task(name='process_manulife_invoice_result')
+@app.task(base=VerboseTask, name='process_manulife_invoice_result')
 def process_invoice_manulife_result(rq_id, result):
     try:
         rq: SubscriptionRequest = \
@@ -128,17 +131,17 @@ def process_invoice_manulife_result(rq_id, result):
 
         update_user(rq)
     except IndexError as e:
-        print(e)
-        print("NotFound request by requestId, %d", rq_id)
+        logger.error(e)
+        logger.error("NotFound request by requestId, %d", rq_id)
     except Exception as e:
-        print(e)
-        print("Fail Invoice %d", rq_id)
+        logger.error(e)
+        logger.error("Fail Invoice %d", rq_id)
         traceback.print_exc()
         return "FailInvoice"
     
 random_processor_name = None
 
-@app.task(name='process_sbt_invoice_result')
+@app.task(base=VerboseTask, name='process_sbt_invoice_result')
 def process_invoice_sbt_result(rq_id, result, metadata):
     global random_processor_name
     if random_processor_name is None:
@@ -161,7 +164,6 @@ def process_invoice_sbt_result(rq_id, result, metadata):
                 rq.status = 200 # stop waiting
                 results = redis_client.get_all_cache(rq_id)
                 rq.predict_result = aggregate_result(results)
-                # print(f"[DEBUG]: rq.predict_result: {rq.predict_result}")
                 ai_inference_profile = {}
                 doc_type_string = ""
                 for idx, result in results.items():
@@ -180,13 +182,13 @@ def process_invoice_sbt_result(rq_id, result, metadata):
             rq.save()
         update_user(rq)
     except IndexError as e:
-        print(e)
-        print("NotFound request by requestId, %d", rq_id)
+        logger.error(e)
+        logger.error("NotFound request by requestId, %d", rq_id)
         rq.ai_inference_time = 0
         rq.save()
     except Exception as e:
-        print(e)
-        print("Fail Invoice %d", rq_id)
+        logger.error(e)
+        logger.error("Fail Invoice %d", rq_id)
         traceback.print_exc()
         rq.ai_inference_time = 0
         rq.save()
diff --git a/cope2n-api/fwd_api/celery_worker/task_warpper.py b/cope2n-api/fwd_api/celery_worker/task_warpper.py
new file mode 100644
index 0000000..dc560c8
--- /dev/null
+++ b/cope2n-api/fwd_api/celery_worker/task_warpper.py
@@ -0,0 +1,16 @@
+from celery import Task
+from celery.utils.log import get_task_logger
+logger = get_task_logger(__name__)
+
+class VerboseTask(Task):
+    abstract = True
+
+    def on_failure(self, exc, task_id, args, kwargs, einfo):
+        # Task failed. What do you want to do?
+        logger.error('FAILURE: Task raised an exception: {}'.format(exc))
+    
+    def on_success(self, retval, task_id, args, kwargs):
+        logger.info(f"SUCCESS: Task: {task_id} succeeded | retval: {retval} | args: {args} | kwargs: {kwargs}")
+
+    def before_start(self, task_id, args, kwargs):
+        logger.info(f"BEFORE_START: Task: {task_id} | args: {args} | kwargs: {kwargs}")
\ No newline at end of file
diff --git a/cope2n-api/fwd_api/celery_worker/worker.py b/cope2n-api/fwd_api/celery_worker/worker.py
index 31ad456..816a073 100755
--- a/cope2n-api/fwd_api/celery_worker/worker.py
+++ b/cope2n-api/fwd_api/celery_worker/worker.py
@@ -2,7 +2,9 @@ import os
 
 import django
 from celery import Celery
+from celery.signals import setup_logging  # noqa
 from kombu import Queue
+import copy
 
 from fwd import settings
 
@@ -19,13 +21,15 @@ app: Celery = Celery(
 app.config_from_object("django.conf:settings", namespace="CELERY")
 app.autodiscover_tasks()
 
-@app.on_after_finalize.connect
-def setup_periodic_tasks(sender, **kwargs):
-    from fwd_api.bg_tasks.clean_local_files import clean_media
-    sender.add_periodic_task(
-        10.0, clean_media.s(), expires=120.0
-    )
+@setup_logging.connect
+def config_loggers(*args, **kwargs):
+    from logging.config import dictConfig  # noqa
+    from django.conf import settings  # noqa
 
+    log_config = copy.deepcopy(settings.LOGGING)
+    if log_config.get("handlers", {}).get("file", {}).get("filename", None):
+        log_config["handlers"]["file"]["filename"] = log_config["handlers"]["file"]["filename"].replace(".log", "_celery.log")
+    dictConfig(log_config)
 
 app.conf.update({
     'task_queues':
diff --git a/cope2n-api/fwd_api/filter/AuthFilter.py b/cope2n-api/fwd_api/filter/AuthFilter.py
index fc7de47..527b967 100755
--- a/cope2n-api/fwd_api/filter/AuthFilter.py
+++ b/cope2n-api/fwd_api/filter/AuthFilter.py
@@ -9,7 +9,9 @@ from fwd_api.annotation.api import throw_on_failure
 from fwd_api.utils import date as DateUtil
 from fwd_api.utils.crypto import ctel_cryptor, sds_authenticator, image_authenticator
 from fwd_api.exception.exceptions import InvalidException, TokenExpiredException, PermissionDeniedException
+import logging
 
+logger = logging.getLogger(__name__)
 
 @throw_on_failure(TokenExpiredException())
 def authenticate_by_param_token(request):
@@ -27,8 +29,7 @@ def authenticate_by_param_token(request):
 # @throw_on_failure(TokenExpiredException())
 def authenticate_by_authorization_header(request):
     token = request.headers['Authorization']
-    print(f"[INFO]: recived request at {datetime.datetime.utcnow()}, with path {request.path}")
-    # print(f"[DEBUG]: token: {token}")
+    logger.info(f"recived request at {datetime.datetime.utcnow()}, with path {request.path}")
     data = sds_authenticator.decode_data(token)
     if 'expired_at' not in data or 'status' not in data or 'subscription_id' not in data:
         raise PermissionDeniedException()
@@ -72,7 +73,7 @@ class AuthFilter(authentication.BaseAuthentication):
     def authenticate(self, request):
 
         if request.path in self.white_list_path:
-            print("App API")
+            logger.debug("App API")
             return None, None
         if '/api/ctel/media/' in request.path or '/api/ctel/v2/media/' in request.path:
             return authenticate_by_param_token(request)
diff --git a/cope2n-api/fwd_api/management/commands/migrate-datebase-fillup-images.py b/cope2n-api/fwd_api/management/commands/migrate-datebase-fillup-images.py
index bdcf633..6930500 100644
--- a/cope2n-api/fwd_api/management/commands/migrate-datebase-fillup-images.py
+++ b/cope2n-api/fwd_api/management/commands/migrate-datebase-fillup-images.py
@@ -151,8 +151,8 @@ class Command(BaseCommand):
         prepared_data_copy = copy.deepcopy(prepared_data)
         s3_client = MinioS3Client(
             # endpoint='http://107.120.133.27:9884',
-            access_key='AKIA3AFPFVWZHTZHB6FW',
-            secret_key='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',
+            access_key='secret',
+            secret_key='secret+HRcfOsbXhx0YSNOLxdW',
             bucket_name='ocr-sds'
             )
         # file = open("modified.txt", "w")
diff --git a/cope2n-api/fwd_api/middleware/__init__.py b/cope2n-api/fwd_api/middleware/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/cope2n-api/fwd_api/middleware/logging_request_response_middleware.py b/cope2n-api/fwd_api/middleware/logging_request_response_middleware.py
new file mode 100644
index 0000000..132ea71
--- /dev/null
+++ b/cope2n-api/fwd_api/middleware/logging_request_response_middleware.py
@@ -0,0 +1,34 @@
+import logging
+import uuid
+
+from django.utils.deprecation import MiddlewareMixin
+
+logger = logging.getLogger(__name__)
+
+class LoggingMiddleware(MiddlewareMixin):
+    def process_request(self, request):
+        trace_id = request.headers.get('X-Trace-ID', str(uuid.uuid4()))
+        request.META['X-Trace-ID'] = trace_id
+
+        request_body = ""
+        content_type = request.headers.get("Content-Type", "")
+        if request.method in ('POST', 'PUT', 'PATCH') and not content_type.startswith("multipart/form-data"):
+            request_body = request.body.decode(encoding="utf-8", errors="ignore")
+
+        logger.info(f"Request: {request.method} {request.path} | Trace ID: {trace_id} | "
+                    f"Body: {request_body} | Headers: {request.headers}")
+
+    def process_response(self, request, response):
+        trace_id = request.META.get('X-Trace-ID', str(uuid.uuid4()))
+        response_body = response.content.decode("utf-8") if response.content else ""
+
+        logger.info(f"Response: {request.method} {request.path} | Trace ID: {trace_id} | "
+                    f"Status: {response.status_code} | Body: {response_body}")
+
+        response['X-Trace-ID'] = trace_id
+        return response
+
+    def process_exception(self, request, exception):
+        trace_id = request.META.get('X-Trace-ID', str(uuid.uuid4()))
+        logger.error(f"Exception: {request.method} {request.path} | Trace ID: {trace_id} | "
+                     f"Error: {exception}")
\ No newline at end of file
diff --git a/cope2n-api/fwd_api/utils/accuracy.py b/cope2n-api/fwd_api/utils/accuracy.py
index 60f6425..92c967f 100755
--- a/cope2n-api/fwd_api/utils/accuracy.py
+++ b/cope2n-api/fwd_api/utils/accuracy.py
@@ -16,6 +16,9 @@ from django.utils import timezone
 from fwd import settings
 from ..models import SubscriptionRequest, Report, ReportFile
 from typing import Union, List, Dict
+import logging
+
+logger = logging.getLogger(__name__)
 
 VALID_KEYS = ["retailername", "sold_to_party", "invoice_no", "purchase_date", "imei_number"]
 OPTIONAL_KEYS = ['invoice_no']
@@ -145,7 +148,7 @@ class ReportAccumulateByRequest:
             if report_file.doc_type in ["imei", "invoice", "all"]:
                 doc_type = report_file.doc_type
             else:
-                print(f"[WARM]: Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
+                logger.warning(f"Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
             total["num_imei"] += 1 if doc_type == "imei" else 0
             total["num_invoice"] += 1 if doc_type == "invoice" else 0
 
@@ -160,13 +163,13 @@ class ReportAccumulateByRequest:
                 total["reviewed_accuracy"][key].add(report_file.reviewed_accuracy.get(key, []))
 
             if not total["average_processing_time"].get(report_file.doc_type, None):
-                print(f"[WARM]: Weird doctype: {report_file.doc_type}")
+                logger.warning(f"Weird doctype: {report_file.doc_type}")
                 total["average_processing_time"][report_file.doc_type] = IterAvg()
             total["average_processing_time"][report_file.doc_type].add_avg(report_file.time_cost, 1) if report_file.time_cost else 0
             total["average_processing_time"]["avg"].add_avg(report_file.time_cost, 1) if report_file.time_cost else 0 
 
             if not total["file_average_processing_time"].get(report_file.doc_type, None):
-                print(f"[WARM]: Weird doctype: {report_file.doc_type}")
+                logger.warning(f"Weird doctype: {report_file.doc_type}")
                 total["file_average_processing_time"][report_file.doc_type] = IterAvg()
             total["file_average_processing_time"][report_file.doc_type].add_avg(image_avg_cost, 1) if image_avg_cost else 0
             total["file_average_processing_time"]["avg"].add_avg(image_avg_cost, 1) if image_avg_cost else 0
@@ -175,7 +178,7 @@ class ReportAccumulateByRequest:
             if report_file.doc_type in ["imei", "invoice", "all"]:
                 doc_type = report_file.doc_type
             else:
-                print(f"[WARM]: Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
+                logger.warning(f"Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
             total["usage"]["imei"] += 1 if doc_type == "imei" else 0
             total["usage"]["invoice"] += 1 if doc_type == "invoice" else 0
             total["usage"]["total_images"] += 1
@@ -193,7 +196,7 @@ class ReportAccumulateByRequest:
             if report_file.doc_type in ["imei", "invoice", "all"]:
                 doc_type = report_file.doc_type
             else:
-                print(f"[WARM]: Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
+                logger.warning(f"Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
             month["num_imei"] += 1 if doc_type == "imei" else 0
             month["num_invoice"] += 1 if doc_type == "invoice" else 0
 
@@ -206,13 +209,13 @@ class ReportAccumulateByRequest:
                 month["reviewed_accuracy"][key].add(report_file.reviewed_accuracy.get(key, []))
 
             if not month["average_processing_time"].get(report_file.doc_type, None):
-                print(f"[WARM]: Weird doctype: {report_file.doc_type}")
+                logger.warning(f"Weird doctype: {report_file.doc_type}")
                 month["average_processing_time"][report_file.doc_type] = IterAvg()
             month["average_processing_time"][report_file.doc_type].add_avg(report_file.time_cost, 1) if report_file.time_cost else 0
             month["average_processing_time"]["avg"].add_avg(report_file.time_cost, 1) if report_file.time_cost else 0 
 
             if not month["file_average_processing_time"].get(report_file.doc_type, None):
-                print(f"[WARM]: Weird doctype: {report_file.doc_type}")
+                logger.warning(f"Weird doctype: {report_file.doc_type}")
                 month["file_average_processing_time"][report_file.doc_type] = IterAvg()
             month["file_average_processing_time"][report_file.doc_type].add_avg(image_avg_cost, 1) if image_avg_cost else 0
             month["file_average_processing_time"]["avg"].add_avg(image_avg_cost, 1) if image_avg_cost else 0 
@@ -221,7 +224,7 @@ class ReportAccumulateByRequest:
             if report_file.doc_type in ["imei", "invoice", "all"]:
                 doc_type = report_file.doc_type
             else:
-                print(f"[WARM]: Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
+                logger.warning(f"Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
             month["usage"]["imei"] += 1 if doc_type == "imei" else 0
             month["usage"]["invoice"] += 1 if doc_type == "invoice" else 0
             month["usage"]["total_images"] += 1
@@ -238,7 +241,7 @@ class ReportAccumulateByRequest:
             if report_file.doc_type in ["imei", "invoice", "all"]:
                 doc_type = report_file.doc_type
             else:
-                print(f"[WARM]: Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
+                logger.warning(f"Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
             day_data["num_imei"] += 1 if doc_type == "imei" else 0
             day_data["num_invoice"] += 1 if doc_type == "invoice" else 0
             day_data["report_files"].append(report_file)
@@ -252,13 +255,13 @@ class ReportAccumulateByRequest:
                 day_data["reviewed_accuracy"][key].add(report_file.reviewed_accuracy.get(key, []))
 
             if not day_data["average_processing_time"].get(report_file.doc_type, None):
-                print(f"[WARM]: Weird doctype: {report_file.doc_type}")
+                logger.warning(f"Weird doctype: {report_file.doc_type}")
                 day_data["average_processing_time"][report_file.doc_type] = IterAvg()
             day_data["average_processing_time"][report_file.doc_type].add_avg(report_file.time_cost, 1) if report_file.time_cost else 0
             day_data["average_processing_time"]['avg'].add_avg(report_file.time_cost, 1) if report_file.time_cost else 0 
 
             if not day_data["file_average_processing_time"].get(report_file.doc_type, None):
-                print(f"[WARM]: Weird doctype: {report_file.doc_type}")
+                logger.warning(f"Weird doctype: {report_file.doc_type}")
                 day_data["file_average_processing_time"][report_file.doc_type] = IterAvg()
             day_data["file_average_processing_time"][report_file.doc_type].add_avg(image_avg_cost, 1) if image_avg_cost else 0
             day_data["file_average_processing_time"]['avg'].add_avg(image_avg_cost, 1) if image_avg_cost else 0 
@@ -273,7 +276,7 @@ class ReportAccumulateByRequest:
             self.data[this_month] = [copy.deepcopy(self.month_format), {}]
             self.data[this_month][0]["extraction_date"] = "Subtotal (" + timezone.localtime(request.created_at).strftime("%Y-%m") + ")"
         if not self.data[this_month][1].get(this_day, None):
-            print(f"[INFO] Adding a new day: {this_day} for report: {report.id} ...")
+            logger.info(f" Adding a new day: {this_day} for report: {report.id} ...")
             self.data[this_month][1][this_day] = copy.deepcopy(self.day_format)[0]
             self.data[this_month][1][this_day]['extraction_date'] = timezone.localtime(request.created_at).strftime("%Y-%m-%d")
             usage = self.count_transactions_within_day(this_day)
@@ -289,6 +292,7 @@ class ReportAccumulateByRequest:
         _ai_cost = request.ai_inference_time
         processing_time_by_averaging_request_cost = (_be_cost + _ai_cost)/_number_of_file if _number_of_file > 0 else 0
         for report_file in report_files:
+            # report_file.time_cost = processing_time_by_averaging_request_cost
             _report_file = copy.deepcopy(report_file)
             if _report_file.is_bad_image or _report_file.bad_image_reason in settings.ACC_EXCLUDE_RESEASONS:
                 _report_file.acc = None
@@ -844,7 +848,6 @@ def calculate_accuracy(key_name: str, inference: Dict[str, Union[str, List]], ta
 
 def calculate_avg_accuracy(acc, type, keys=[]):
     acc_list = []
-    # print(f"[DEBUG]: type: {type} - acc: {acc}")
     for key in keys:
         this_acc = acc.get(type, {}).get(key, [])
         if len(this_acc) > 0:
@@ -985,7 +988,7 @@ def calculate_a_request(report, request):
         if request.redemption_id:
             _sub = map_subsidiary_short_to_long(request.redemption_id[:2])
         else:
-            print(f"[WARN]: empty redemption_id, check request: {request.request_id}")
+            logger.warning(f"empty redemption_id, check request: {request.request_id}")
 
         # Little trick to replace purchase date to normalized
         if len(att["normalized_data"]["feedback"].get("purchase_date", [])) > 0:
@@ -1008,9 +1011,6 @@ def calculate_a_request(report, request):
 
         if att["is_bad_image"] or image.reason in settings.ACC_EXCLUDE_RESEASONS:
             if image.reason in settings.ACC_EXCLUDE_RESEASONS:
-                # if image.reason in settings.ACC_EXCLUDE_RESEASONS:
-                #     print(f"[DEBUG]: {image.reason}")
-                # TODO: Exclude bad image accuracy from average accuracy
                 _att["avg_acc"] = None
                 for t in _att["acc"].keys():
                     for k in _att["acc"][t].keys():
@@ -1073,7 +1073,7 @@ def calculate_a_request(report, request):
                 request_att["total_images"] += 1
             request_att["err"] += _att["err"]
         except Exception as e:
-            print(f"[ERROR]: failed to calculate request: {request.request_id} - request_file: {image.file_name} because of {e}")
+            logger.error(f"Failed to calculate request: {request.request_id} - request_file: {image.file_name} because of {e}")
             continue
  
     return request_att, report_files, atts
diff --git a/cope2n-api/fwd_api/utils/file.py b/cope2n-api/fwd_api/utils/file.py
index cba080b..44cdc34 100755
--- a/cope2n-api/fwd_api/utils/file.py
+++ b/cope2n-api/fwd_api/utils/file.py
@@ -23,6 +23,9 @@ import imagesize
 import csv
 from openpyxl import load_workbook
 from openpyxl.styles import Font, Border, Side, PatternFill, NamedStyle, numbers, Alignment
+import logging
+
+logger = logging.getLogger(__name__)
 
 s3_client = S3Util.MinioS3Client(
     endpoint=settings.S3_ENDPOINT,
@@ -96,7 +99,6 @@ def validate_list_file(files, max_file_num=settings.MAX_UPLOAD_FILES_IN_A_REQUES
 
     for f in files:
         if not isinstance(f, TemporaryUploadedFile):
-            # print(f'[DEBUG]: {f.name}')
             raise InvalidException(excArgs="files")
         extension = f.name.split(".")[-1].lower() in allowed_file_extensions
         if not extension or "." not in f.name:
@@ -116,7 +118,6 @@ def validate_csv_feedback(files, max_file_num=1, min_file_num=1, file_field="csv
 
     for f in files:
         if not isinstance(f, TemporaryUploadedFile):
-            # print(f'[DEBUG]: {f.name}')
             raise InvalidException(excArgs="files")
         extension = f.name.split(".")[-1].lower() in ["csv"]
         if not extension or "." not in f.name:
@@ -131,7 +132,7 @@ def get_file(file_path: str):
     try:
         return open(file_path, 'rb')
     except Exception as e:
-        print(e)
+        logger.error(e)
         raise GeneralException("System")
 
 
@@ -226,7 +227,7 @@ def delete_file_with_path(file_path: str) -> bool:
         os.remove(file_path)
         return True
     except Exception as e:
-        print(e)
+        logger.error(e)
         return False
 
 
@@ -239,7 +240,7 @@ def save_template_file(file_name: str, rq: OcrTemplate, file: TemporaryUploadedF
             os.makedirs(folder_path)
         return save_file_with_path(file_name, file, quality, folder_path)
     except Exception as e:
-        print(e)
+        logger.error(e)
         raise ServiceUnavailableException()
 
 def save_file_with_path(file_name: str, file: TemporaryUploadedFile, quality, folder_path: str):
@@ -253,7 +254,7 @@ def save_file_with_path(file_name: str, file: TemporaryUploadedFile, quality, fo
     except InvalidDecompressedSizeException as e:
         raise e
     except Exception as e:
-        print(e)
+        logger.error(e)
         raise ServiceUnavailableException()
     return file_path
 
@@ -306,7 +307,7 @@ def resize_and_save_file(file_name: str, rq: SubscriptionRequest, file: Temporar
     except InvalidDecompressedSizeException as e:
         raise e
     except Exception as e:
-        print(f"[ERROR]: {e}")
+        logger.error(f"{e}")
         raise ServiceUnavailableException()
 
 def save_to_S3(file_name, rq, local_file_path):
@@ -319,21 +320,19 @@ def save_to_S3(file_name, rq, local_file_path):
         c_connector.remove_local_file((local_file_path, request_id))
         return s3_key
     except Exception as e:
-        print(f"[ERROR]: {e}")
+        logger.error(f"{e}")
         raise ServiceUnavailableException()
 
 def save_feedback_to_S3(file_name, id, local_file_path):
     try:
-        # print(f"[DEBUG]: Uploading feedback to S3 with local path {local_file_path}, id: {id}, file_name: {file_name}")
         assert len(local_file_path.split("/")) >= 3, "file_path must have at least feedback_folder and feedback_id"
         # s3_key = os.path.join(local_file_path.split("/")[-3], local_file_path.split("/")[-2], file_name)
         s3_key = os.path.join("feedback", local_file_path.split("/")[-2], file_name)
-        # print(f"[DEBUG]: Uploading feedback to S3 with s3_key {s3_key}")
         c_connector.upload_feedback_to_s3((local_file_path, s3_key, id))
         c_connector.remove_local_file((local_file_path, id))
         return s3_key
     except Exception as e:
-        print(f"[ERROR]: {e}")
+        logger.error(f"{e}")
         raise ServiceUnavailableException()
 
 def save_report_to_S3(id, local_file_path, delay=0):
@@ -343,7 +342,7 @@ def save_report_to_S3(id, local_file_path, delay=0):
         c_connector.remove_local_file((local_file_path, id))
         return s3_key
     except Exception as e:
-        print(f"[ERROR]: {e}")
+        logger.error(f"{e}")
         raise ServiceUnavailableException()
 
 def download_from_S3(s3_key, local_file_path):
@@ -361,7 +360,7 @@ def save_file_with_path(file_name: str, file: TemporaryUploadedFile, quality, fo
     except InvalidDecompressedSizeException as e:
         raise e
     except Exception as e:
-        print(e)
+        logger.error(e)
         raise ServiceUnavailableException()
     return file_path
 
@@ -400,8 +399,8 @@ def save_img(file_path: str, file: TemporaryUploadedFile, quality):
                     elif orientation == 8:
                         image = image.transpose(Image.ROTATE_90)
         except Exception as ex:
-            print(ex)
-            print("Rotation Error")
+            logger.error(ex)
+            logger.error("Rotation Error")
             traceback.print_exc()
 
         image = resize(image, max_w=settings.TARGET_MAX_IMAGE_SIZE[0], max_h=settings.TARGET_MAX_IMAGE_SIZE[1])
@@ -449,9 +448,9 @@ def get_value(_dict, keys):
             else:
                 value = value.get(key, {})
     except Exception as e:
-        print(f"[ERROR]: {e}")
-        print(f"[ERROR]: value: {value}")
-        print(f"[ERROR]: keys: {keys}")
+        logger.error(f"{e}")
+        logger.error(f"value: {value}")
+        logger.error(f"keys: {keys}")
 
     if value is None:
         return "-"
diff --git a/cope2n-api/fwd_api/utils/ocr_utils/ocr_metrics.py b/cope2n-api/fwd_api/utils/ocr_utils/ocr_metrics.py
index 71cd84d..5d15726 100644
--- a/cope2n-api/fwd_api/utils/ocr_utils/ocr_metrics.py
+++ b/cope2n-api/fwd_api/utils/ocr_utils/ocr_metrics.py
@@ -5,7 +5,9 @@ from terminaltables import AsciiTable
 from rapidfuzz.distance import Levenshtein
 
 from .wiki_diff import inline_diff
+import logging
 
+logger = logging.getLogger(__name__)
 
 def is_type_list(x, type):
 
@@ -381,5 +383,5 @@ def eval_kie(preds_e2e: dict[str, dict[str, str]], gt_e2e: dict[str, dict[str, s
         )
 
     table = AsciiTable(table_data)
-    print(table.table)
+    logger.debug(table.table)
     return results, fail_cases
diff --git a/cope2n-api/fwd_api/utils/ocr_utils/sbt_report.py b/cope2n-api/fwd_api/utils/ocr_utils/sbt_report.py
index caea372..d742c33 100644
--- a/cope2n-api/fwd_api/utils/ocr_utils/sbt_report.py
+++ b/cope2n-api/fwd_api/utils/ocr_utils/sbt_report.py
@@ -14,6 +14,9 @@ from .ocr_metrics import eval_ocr_metric
 import sys
 # sys.path.append(os.path.dirname(__file__))
 from sdsvkvu.utils.query.sbt_v2 import get_seller, post_process_seller
+import logging
+
+logger = logging.getLogger(__name__)
 
 
 def read_json(file_path: str):
@@ -108,7 +111,7 @@ def convert_predict_from_csv(
         n_pages = request['pages']
         req_id = request['request_id']
         if not isinstance(request['doc_type'], str) or not isinstance(request['predict_result'], str):
-            print(f"[WARNING] Skipped request id {req_id}")
+            logger.warning(f"] Skipped request id {req_id}")
             continue
         
         doc_type_list = request['doc_type'].split(',')
@@ -178,7 +181,7 @@ def init_csv(
     for request_id in list_request_id:
         gt_path = os.path.join(gt_dir, request_id, request_id+".json")
         if not os.path.exists(gt_path):
-            print(f"[WARNING] Skipped request id {os.path.basename(os.path.dirname(gt_path))}")
+            logger.warning(f"] Skipped request id {os.path.basename(os.path.dirname(gt_path))}")
             continue
         gt_data = read_json(gt_path)
         json_file_list = glob.glob(os.path.join(pred_dir, request_id, "temp_*.json"))
@@ -306,7 +309,7 @@ def pick_sample_to_revise(
         img_path = [ff for ff in glob.glob(img_path_folder.replace(".json", ".*")) if ".json" not in ff]
             
         if len(img_path) == 0:
-            print(f"[WARNING] Skipped request id {request_id}")
+            logger.warning(f"] Skipped request id {request_id}")
             continue    
         img_path = img_path[0]
         # img_path = [ff for ff in glob.glob(json_path.replace(".json", ".*"))][0]
@@ -354,41 +357,41 @@ if __name__ == "__main__":
     csv_path_end_user = "logs/eval_20240115/OCR_15Jan2024.csv"
     
     # Step 1: Convert a csv file to get user submitted results for each request
-    print("[INFO] Starting convert csv from customer to json")
+    logger.info(f" Starting convert csv from customer to json")
     os.system(f"sudo chmod -R 777 {save_path}")
     convert_groundtruth_from_csv(csv_path=csv_path_end_user, save_dir=save_path)
-    print("[INFO] Converted")
+    logger.info(f" Converted")
     
     # # Step 2: Convert a csv file to get predict OCR results for each image
-    print("[INFO] Starting convert csv from SDSV to json")
+    logger.info(f" Starting convert csv from SDSV to json")
     convert_predict_from_csv(csv_path=csv_path, save_dir=save_path)
-    print("[INFO] Converted")
+    logger.info(f" Converted")
     
     # # Step 3: Gen initial csv file and calculate OCR result between submitted results and ocr results
-    print("[INFO] Starting generate csv to get performance")
+    logger.info(f" Starting generate csv to get performance")
     gt_path = save_path
     pred_path = save_path
     req_to_red_dict = gen_req_to_red_dict(csv_path_end_user)
     init_data = init_csv(gt_dir=gt_path, pred_dir=pred_path, req_to_red=req_to_red_dict)
     pd.DataFrame(init_data).to_csv(os.path.join(save_csv, "init1.csv"), index=False)
-    print("[INFO] Done")
+    logger.info(f" Done")
     
     # # Step 4: Split requests whose accuracy is less than 1 to revise
-    # print("[INFO] Starting split data to review")
+    # logger.info(f" Starting split data to review")
     # revised_path = os.path.join(save_csv, "revised")
     # # shutil.rmtree(revised_path)
     # pick_sample_to_revise(ocr_accuracy=init_data, gt_dir=save_path, save_dir=revised_path)
-    # print("[INFO] Done")
+    # logger.info(f" Done")
     
     # # Step 5: Merge revised results to gt folder
-    # print("[INFO] Merging revised data to ground truth folder")
+    # logger.info(f" Merging revised data to ground truth folder")
     # revised_path = os.path.join(save_csv, "revised")
     # revised_path = [f'{revised_path}/empty_results', f'{revised_path}/diff_results']
     # merge_revised_sample(revised_path_list=revised_path, save_dir=save_path)
     # print("Done")
     
     # # Step 6: Caculate OCR result between ocr results and revised results
-    # print("[INFO] Exporting OCR report")
+    # logger.info(f" Exporting OCR report")
     # init_csv_path = os.path.join(save_csv, "init1.csv")
     # report = export_report(init_csv=init_csv_path)
     # error_path = os.path.join(save_csv, "errors")
@@ -427,6 +430,6 @@ if __name__ == "__main__":
     
     
     # report.drop(columns=["file_path", "class_name"]).to_csv(os.path.join(save_csv, f"SBT_report_{time.strftime('%Y%m%d')}.csv"), index=False)
-    # print("[INFO] Done")
+    # logger.info(f" Done")
     
     
\ No newline at end of file
diff --git a/cope2n-api/fwd_api/utils/ocr_utils/wiki_diff.py b/cope2n-api/fwd_api/utils/ocr_utils/wiki_diff.py
index dfbbb54..7b87128 100644
--- a/cope2n-api/fwd_api/utils/ocr_utils/wiki_diff.py
+++ b/cope2n-api/fwd_api/utils/ocr_utils/wiki_diff.py
@@ -4,6 +4,9 @@ import unidecode
 import os
 import glob
 import pandas as pd
+import logging
+
+logger = logging.getLogger(__name__)
 
 VOWELS = 'aeouiy' + 'AEOUIY'
 CONSONANTS = 'bcdfghjklmnpqrstvxwz' + 'BCDFGHJKLMNPQRSTVXWZ'
@@ -194,7 +197,7 @@ def main(overwrite=False):
         df.to_csv(f'{SAVE_PATH}/wiki_diff.csv', sep='\t')
         df_ = pd.DataFrame(ddata_specialchars)
         df_.to_csv(f'{SAVE_PATH}/wiki_diff_specialchars.csv', sep='\t')
-    print(TOTAL_WORD)
+    logger.info(TOTAL_WORD)
 
 
 if __name__ == '__main__':
diff --git a/cope2n-api/fwd_api/utils/process.py b/cope2n-api/fwd_api/utils/process.py
index 0e2f248..483d573 100644
--- a/cope2n-api/fwd_api/utils/process.py
+++ b/cope2n-api/fwd_api/utils/process.py
@@ -25,10 +25,9 @@ from ..exception.exceptions import InvalidException, NotFoundException, \
 from ..models import UserProfile, OcrTemplate, OcrTemplateBox, \
     Subscription, SubscriptionRequestFile, SubscriptionRequest
 from ..celery_worker.client_connector import c_connector
+import logging
 
-from celery.utils.log import get_task_logger
-
-logger = get_task_logger(__name__)
+logger = logging.getLogger(__name__)
 
 class UserData:
     user: UserProfile = None
@@ -107,7 +106,6 @@ def validate_ocr_request_and_get(request, subscription):
 
     # validated_data['is_test_request'] = bool(request.data.get('is_test_request', False))
     validated_data['is_test_request'] = string_to_boolean(request.data.get('is_test_request', "false"))
-    # print(f"[DEBUG]: is_test_request: ", validated_data['is_test_request'])
 
     return validated_data
 
@@ -143,7 +141,6 @@ def sbt_validate_ocr_request_and_get(request, subscription):
     validated_data['invoice_file'] = invoice_file
     validated_data['redemption_ID'] = redemption_ID
     validated_data['is_test_request'] = string_to_boolean(request.data.get('is_test_request', "false"))
-    # print(f"[DEBUG]: is_test_request: ", validated_data['is_test_request'])
 
     subsidiary = request.data.get("subsidiary", None)
     valid_subs = list(settings.SUBS.keys())[:-2] # remove "ALL" and "SEAO"
@@ -246,7 +243,7 @@ def get_random_string(length):
     # choose from all lowercase letter
     letters = string.ascii_lowercase
     result_str = ''.join(random.choice(letters) for _ in range(length))
-    print("Random string of length", length, "is:", result_str)
+    logger.debug("Random string of length", length, "is:", result_str)
     return result_str
 
 
@@ -346,7 +343,7 @@ def send_to_queue2(rq_id, sub_id, file_url, user_id, typez, metadata={}):
         elif typez == ProcessType.SBT_INVOICE.value:
             c_connector.process_invoice_sbt((rq_id, file_url, metadata))
     except Exception as e:
-        print(e)
+        logger.error(e)
         raise BadGatewayException()
 
 def build_template_matching_data(template):
@@ -383,7 +380,7 @@ def send_template_queue(rq_id, file_url, template: OcrTemplate, uid):
         c_connector.process_template_matching(
             (rq_id, template.subscription.id, folder_name, file_url, template_data, uid))
     except Exception as e:
-        print(e)
+        logger.error(e)
         raise BadGatewayException()
 
 def process_feedback(feedback_id, local_file_path):
@@ -451,7 +448,7 @@ def pdf_to_images_urls(doc_path, request: SubscriptionRequest, user, dpi: int =
     image = get_first_page_pdf(doc_path, 300)
     image = resize(image, max_w=settings.TARGET_MAX_IMAGE_SIZE[0], max_h=settings.TARGET_MAX_IMAGE_SIZE[1])
     image.save(saving_path)
-    print(f"Saving {saving_path}")
+    logger.debug(f"Saving {saving_path}")
     new_request_file: SubscriptionRequestFile = SubscriptionRequestFile(file_path=saving_path,
                                                                         request=request,
                                                                         file_name=break_file_name,
diff --git a/cope2n-api/fwd_api/utils/s3.py b/cope2n-api/fwd_api/utils/s3.py
index 722dde0..ca3402a 100644
--- a/cope2n-api/fwd_api/utils/s3.py
+++ b/cope2n-api/fwd_api/utils/s3.py
@@ -1,4 +1,7 @@
 import boto3
+import logging
+
+logger = logging.getLogger(__name__)
 
 class MinioS3Client:
     def __init__(self, access_key, secret_key, bucket_name, endpoint=""):
@@ -25,7 +28,7 @@ class MinioS3Client:
                     's3')
                 
         except Exception as e:
-            print(f"[WARM] Unable to create an s3 client, {e}")
+            logger.warning(f"Unable to create an s3 client, {e}")
             self.s3_client = None
 
     def update_object(self, s3_key, content):
@@ -38,7 +41,7 @@ class MinioS3Client:
             # print(f"Object '{s3_key}' updated in S3 with res: {res}")
             return res
         except Exception as e:
-            print(f"Error updating object in S3: {str(e)}")
+            logger.error(f"Error updating object in S3: {str(e)}")
 
     def upload_file(self, local_file_path, s3_key):
         try:
@@ -46,7 +49,7 @@ class MinioS3Client:
             # print(f"File '{local_file_path}' uploaded to S3 with key '{s3_key}'")
             return res
         except Exception as e:
-            print(f"Error uploading file to S3: {str(e)}")
+            logger.error(f"Error uploading file to S3: {str(e)}")
 
     def download_file(self, s3_key, local_file_path):
         try:
@@ -54,7 +57,7 @@ class MinioS3Client:
             # print(f"File '{s3_key}' downloaded from S3 to '{local_file_path}'")
             return res
         except Exception as e:
-            print(f"Error downloading file from S3: {str(e)}")
+            logger.error(f"Error downloading file from S3: {str(e)}")
     
     def create_url_with_expiration(self, s3_key, expiration_time):
         try:
@@ -68,7 +71,7 @@ class MinioS3Client:
             # print(f"URL for file '{s3_key}' expires in {expiration_time} seconds")
             return res
         except Exception as e:
-            print(f"Error generating URL for file '{s3_key}': {str(e)}")
+            logger.error(f"Error generating URL for file '{s3_key}': {str(e)}")
 
 if __name__=="__main__":
 
diff --git a/docker-compose-dev.yml b/docker-compose-dev.yml
index 0b09b08..88b1e14 100755
--- a/docker-compose-dev.yml
+++ b/docker-compose-dev.yml
@@ -45,6 +45,7 @@ services:
     image: sidp/cope2n-be-fi-sbt:latest
     environment:
       - MEDIA_ROOT=${MEDIA_ROOT}
+      - LOG_ROOT=${LOG_ROOT}
       - DB_ENGINE=${DB_ENGINE}
       - DB_SCHEMA=${DB_SCHEMA}
       - DB_USER=${DB_USER}
@@ -84,13 +85,15 @@ services:
       - ctel-sbt
     volumes:
       - BE_media:${MEDIA_ROOT}
+      - BE_log:${LOG_ROOT}
       - BE_static:/app/static
+      - /mnt/hdd4T/TannedCung/OCR/Data/SBT_lost_data:/external_data
       - ./cope2n-api:/app
     working_dir: /app
     depends_on:
       db-sbt:
         condition: service_started
-    command: sh -c "chmod -R 777 /app; sleep 5; python manage.py collectstatic --no-input &&
+    command: sh -c "sudo chmod -R 777 /app; sleep 5; python manage.py collectstatic --no-input &&
                   python manage.py makemigrations &&
                   python manage.py migrate &&
                   python manage.py compilemessages &&
@@ -105,7 +108,8 @@ services:
     - MINIO_ACCESS_KEY=${S3_ACCESS_KEY}
     - MINIO_SECRET_KEY=${S3_SECRET_KEY}
     volumes:
-    - ./data/minio_data:/data
+    # - ./data/minio_data:/data
+    - /home/dxtan/TannedCung/persistent/minio:/data
     ports:
       - 9884:9884
       - 9885:9885
@@ -144,6 +148,7 @@ services:
     image: sidp/cope2n-be-fi-sbt:latest
     environment:
       - MEDIA_ROOT=${MEDIA_ROOT}
+      - LOG_ROOT=${LOG_ROOT}
       - PYTHONPATH=${PYTHONPATH}:/app  # For import module
       - PYTHONUNBUFFERED=1  # For show print log
       - DB_ENGINE=${DB_ENGINE}
@@ -177,6 +182,7 @@ services:
         condition: service_started
     volumes:
       - BE_media:${MEDIA_ROOT}
+      - BE_log:${LOG_ROOT}
       - ./cope2n-api:/app
 
     working_dir: /app
@@ -189,7 +195,8 @@ services:
     mem_reservation: 500m
     image: postgres:15.4-alpine
     volumes:
-      - ./data/postgres_data:/var/lib/postgresql/data
+      # - ./data/postgres_data:/var/lib/postgresql/data
+      - /home/dxtan/TannedCung/persistent/postgres:/var/lib/postgresql/data
     networks:
       - ctel-sbt
     environment:
@@ -254,4 +261,5 @@ services:
 volumes:
   db_data:
   BE_static:
-  BE_media:
\ No newline at end of file
+  BE_media:
+  BE_log:
\ No newline at end of file
diff --git a/docker-compose-prod.yml b/docker-compose-prod.yml
index f3d56b5..6f19166 100644
--- a/docker-compose-prod.yml
+++ b/docker-compose-prod.yml
@@ -25,6 +25,7 @@ services:
   be-ctel-sbt:
     environment:
       - MEDIA_ROOT=${MEDIA_ROOT}
+      - LOG_ROOT=${LOG_ROOT}
       - DB_ENGINE=${DB_ENGINE}
       - DB_SCHEMA=${DB_SCHEMA}
       - DB_USER=${DB_USER}
@@ -112,6 +113,7 @@ services:
   be-celery-sbt:
     environment:
       - MEDIA_ROOT=${MEDIA_ROOT}
+      - LOG_ROOT=${LOG_ROOT}
       - PYTHONPATH=${PYTHONPATH}:/app  # For import module
       - PYTHONUNBUFFERED=1  # For show print log
       - DB_ENGINE=${DB_ENGINE}