diff --git a/examples/mnist-classifier-demo/demo.ipynb b/examples/mnist-classifier-demo/demo.ipynb
index 3838664f1..780ac58c6 100644
--- a/examples/mnist-classifier-demo/demo.ipynb
+++ b/examples/mnist-classifier-demo/demo.ipynb
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -108,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -200,7 +200,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "tags": []
    },
@@ -218,22 +218,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'username': 'pluginuser', 'status': 'Login successful'}"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "try:\n",
     "    client.users.create(\n",
@@ -259,7 +248,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -283,7 +272,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -294,7 +283,7 @@
     "    description=f\"training job for {experiment_id}\", \n",
     "    queue_id=queue_id,\n",
     "    entrypoint_id=train_ep, \n",
-    "    values={\"epochs\":\"30\"}, \n",
+    "    values={\"epochs\":\"1\"}, \n",
     "    timeout=job_time_limit\n",
     ")"
    ]
@@ -308,19 +297,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting fgm job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "job_time_limit = '1h'\n",
     "\n",
@@ -344,21 +323,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting patch_gen job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "job_time_limit = '1h'\n",
     "\n",
@@ -387,19 +356,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting patch_apply job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "job_time_limit = '1h'\n",
     "\n",
@@ -428,7 +387,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -459,7 +418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -477,7 +436,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -495,7 +454,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -506,7 +465,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -530,19 +489,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting metrics job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "predict_fgm = predict(experiment_id, queue_id, predict_ep, fgm_job, adv=\"fgm\")\n",
     "measure_fgm = measure(experiment_id, queue_id, metrics_ep, predict_fgm)"
@@ -550,40 +499,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting spatial_smoothing defense job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "spatial_job_fgm = defend(experiment_id, queue_id, defense_ep, fgm_job, defense=\"spatial_smoothing\", adv=\"fgm\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting metrics job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "predict_spatial_fgm = predict(experiment_id, queue_id, predict_ep, spatial_job_fgm, adv=\"def\")\n",
     "measure_spatial_fgm = measure(experiment_id, queue_id, metrics_ep, predict_spatial_fgm)"
@@ -591,38 +520,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting jpeg_compression defense job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "jpeg_comp_job_fgm = defend(experiment_id, queue_id, defense_ep, fgm_job, defense=\"jpeg_compression\", adv=\"fgm\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting metrics job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "predict_jpeg_comp_fgm = predict(experiment_id, queue_id, predict_ep, jpeg_comp_job_fgm, adv=\"def\")\n",
     "measure_jpeg_comp_fgm = measure(experiment_id, queue_id, metrics_ep, predict_jpeg_comp_fgm)"
@@ -630,21 +539,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": null,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting gaussian_augmentation defense job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "gaussian_job_fgm = defend(experiment_id, queue_id, defense_ep, fgm_job, defense=\"gaussian_augmentation\", adv=\"fgm\", defense_kwargs={\n",
     "            \"augmentation\": False,\n",
@@ -658,19 +557,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting metrics job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "predict_gaussian_fgm = predict(experiment_id, queue_id, predict_ep, gaussian_job_fgm, adv=\"def\")\n",
     "measure_gaussian_fgm = measure(experiment_id, queue_id, metrics_ep, predict_gaussian_fgm)"
@@ -685,19 +574,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting metrics job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "predict_patch = predict(experiment_id, queue_id, predict_ep, patch_apply_job, adv=\"patch\")\n",
     "measure_patch = measure(experiment_id, queue_id, metrics_ep, predict_patch)"
@@ -705,40 +584,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": null,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting spatial_smoothing defense job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "spatial_job_patch = defend(experiment_id, queue_id, defense_ep, patch_apply_job, defense=\"spatial_smoothing\", adv=\"patch\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting metrics job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "predict_spatial_patch = predict(experiment_id, queue_id, predict_ep, spatial_job_patch, adv=\"def\")\n",
     "measure_spatial_patch = measure(experiment_id, queue_id, metrics_ep, predict_spatial_patch)"
@@ -746,38 +605,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting jpeg_compression defense job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "jpeg_comp_job_patch = defend(experiment_id, queue_id, defense_ep, patch_apply_job, defense=\"jpeg_compression\", adv=\"patch\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting metrics job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "predict_jpeg_comp_patch = predict(experiment_id, queue_id, predict_ep, jpeg_comp_job_patch, adv=\"def\")\n",
     "measure_jpeg_comp_patch = measure(experiment_id, queue_id, metrics_ep, predict_jpeg_comp_patch)"
@@ -785,21 +624,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting gaussian_augmentation defense job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "gaussian_job_patch = defend(experiment_id, queue_id, defense_ep, patch_apply_job, defense=\"gaussian_augmentation\", adv=\"patch\", defense_kwargs={\n",
     "            \"augmentation\": False,\n",
@@ -813,19 +642,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'Job finished. Starting metrics job.'"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "predict_gaussian_patch = predict(experiment_id, queue_id, predict_ep, gaussian_job_patch, adv=\"def\")\n",
     "measure_gaussian_patch = measure(experiment_id, queue_id, metrics_ep, predict_gaussian_patch)"
@@ -840,30 +659,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'fgm': {'accuracy': 0.1341, 'roc_auc': 0.5189507464552101},\n",
-      " 'gaussian_fgm': {'accuracy': 0.1488, 'roc_auc': 0.527179728639676},\n",
-      " 'gaussian_patch': {'accuracy': 0.7861, 'roc_auc': 0.8832449257351849},\n",
-      " 'jpeg_fgm': {'accuracy': 0.1421, 'roc_auc': 0.5233717508753281},\n",
-      " 'jpeg_patch': {'accuracy': 0.7983, 'roc_auc': 0.8901298886871352},\n",
-      " 'patch': {'accuracy': 0.8023, 'roc_auc': 0.8924164841005447},\n",
-      " 'spatial_fgm': {'accuracy': 0.1436, 'roc_auc': 0.5239930585411556},\n",
-      " 'spatial_patch': {'accuracy': 0.7691, 'roc_auc': 0.8738922749238369},\n",
-      " 'trained': {'accuracy': 0.9843999743461609,\n",
-      "             'auc': 0.9992161393165588,\n",
-      "             'loss': 0.04713347926735878,\n",
-      "             'precision': 0.9867536425590515,\n",
-      "             'recall': 0.983299970626831,\n",
-      "             'training_time_in_minutes': 2.49030305}}\n"
-     ]
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import pprint\n",
     "\n",
@@ -885,20 +683,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1600x900 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
    "source": [
     "import numpy as np\n",
     "import matplotlib.pyplot as plt \n",
diff --git a/examples/task-plugins/dioptra_custom/fgm_mnist_demo/artifacts_restapi.py b/examples/task-plugins/dioptra_custom/fgm_mnist_demo/artifacts_restapi.py
index d03aba37d..70c06fde7 100644
--- a/examples/task-plugins/dioptra_custom/fgm_mnist_demo/artifacts_restapi.py
+++ b/examples/task-plugins/dioptra_custom/fgm_mnist_demo/artifacts_restapi.py
@@ -14,157 +14,103 @@
 #
 # ACCESS THE FULL CC BY 4.0 LICENSE HERE:
 # https://creativecommons.org/licenses/by/4.0/legalcode
-import requests
 import structlog
 import os
 from dioptra import pyplugs
 from dioptra.client import connect_json_dioptra_client
 from structlog.stdlib import BoundLogger
-from posixpath import join as urljoin
-from urllib.parse import urlparse, urlunparse
 
 LOGGER: BoundLogger = structlog.stdlib.get_logger()
 
 @pyplugs.register    
 def get_uri_for_model(model_name, model_version=-1):
-    session, url = get_logged_in_session()
-    models = get(session, url, f'models?search={model_name}&pageLength=500')
+    dioptra_client = get_logged_in_session()
+    models = dioptra_client.models.get(
+        search=model_name, 
+        page_length=500
+    )
+    selected_model = None
     for model in models['data']:
         if (model['name'] == model_name):
             model_id = model['id']
             if (model_version >= 0):
-                selected_model = get(session, url, 
-                    f'models/{model_id}/versions/{model_version}'
+                selected_model = dioptra_client.models.versions.get_by_id(
+                    model_id=model_id, 
+                    version_number=model_version
                 )
             else:
                 selected_model = model['latestVersion']
 
-    uri = selected_model['artifact']['artifactUri']
+    uri = selected_model['artifact']['artifactUri'] if selected_model is not None else None
     return uri
 
 def get_uris_for_job(job_id):
-    session, url = get_logged_in_session()
-    job = get(session, url, 'jobs', str(job_id))
+    dioptra_client = get_logged_in_session()
+    job = dioptra_client.jobs.get_by_id(job_id)
     return [artifact['artifactUri'] for artifact in job['artifacts']]
 
 def get_uris_for_artifacts(artifact_ids):
-    session, url = get_logged_in_session()
-    return [get(session, url, 'artifacts', aid) for aid in artifact_ids]
+    dioptra_client = get_logged_in_session()
+    return [dioptra_client.artifacts.get_by_id(artifact_id=aid) for aid in artifact_ids]
 
 def get_logged_in_session():
-    session = requests.Session()
-    url = "http://dioptra-deployment-restapi:5000/api/v1"
-
-    login = post(session, url, {
-            'username':os.environ['DIOPTRA_WORKER_USERNAME'], 
-            'password':os.environ['DIOPTRA_WORKER_PASSWORD']},
-            'auth', 'login')
-    LOGGER.info("login request sent", response=str(login))
-
-    return session, url
+    url = "http://dioptra-deployment-restapi:5000/"
+    dioptra_client = connect_json_dioptra_client(url)
+    dioptra_client.auth.login(
+        username=os.environ['DIOPTRA_WORKER_USERNAME'], 
+        password=os.environ['DIOPTRA_WORKER_PASSWORD']
+    )
+    return dioptra_client
 
 def upload_model_to_restapi(name, source_uri, job_id):
     version = 0
     model_id = 0
     
-    session, url = get_logged_in_session()
+    dioptra_client = get_logged_in_session()
+    models = dioptra_client.models.get(
+        search=name,
+        page_length=500
+    )
 
-    models = get(session, url, f'models?search={name}&pageLength=500')
     LOGGER.info("requesting models from RESTAPI", response=models)
 
-    
     for model in models['data']:
         #check whether to create a new model
         if model['name'] == name:
             model_id = model['id']
             if model['latestVersion'] != None:
                 version = model['latestVersion']['versionNumber'] + 1
+    
     if (version == 0 and model_id == 0):
-        LOGGER.info("creating new model on RESTAPI")
-        model = post(session, url, {"group": 1, "name": name, "description": f"{name} model"}, "models")
+        model = dioptra_client.models.create(
+            group_id=1,
+            name=name,
+            description=f"{name} model"
+        )
         model_id = model['id']
         LOGGER.info("new model created", response=model)
     
-    artifact = post(session, url, {"group": 1, "description": f"{name} model artifact", "job": str(job_id), "uri": source_uri}, 'artifacts')
+    artifact = dioptra_client.artifacts.create(
+        group_id=1, 
+        description=f"{name} model artifact",
+        job_id=job_id, 
+        uri=source_uri
+    )
     LOGGER.info("artifact", response=artifact)
-    model_version = post(session, url, {"description": f"{name} model version", "artifact": artifact['id']}, 'models', str(model_id), 'versions')
+    
+    model_version = dioptra_client.models.versions.create(
+        model_id=model_id, 
+        artifact_id=artifact['id'], 
+        description=f"{name} model version"
+    )
     LOGGER.info("model created", response=model_version)
 
 def upload_artifact_to_restapi(source_uri, job_id):
-    session, url = get_logged_in_session()
-
-    artifact = post(session, url, {"group": 1, "description": f"artifact for job {job_id}", "job": str(job_id), "uri": source_uri}, 'artifacts')
-    LOGGER.info("artifact", response=artifact)
-
-def debug_request(url, method, data=None):
-    LOGGER.debug("Request made.", url=url, method=method, data=data)
-
-
-def debug_response(json):
-    LOGGER.debug("Response received.", json=json)
-
-
-def get(session, endpoint, *features):
-    debug_request(urljoin(endpoint, *features), "GET")
-    return make_request(session, "get", endpoint, None, *features)
-
-
-def post(session, endpoint, data, *features):
-    debug_request(urljoin(endpoint, *features), "POST", data)
-    return make_request(session, "post", endpoint, data, *features)
-
-
-def delete(session, endpoint, data, *features):
-    debug_request(urljoin(endpoint, *features), "DELETE", data)
-    return make_request(session, "delete", endpoint, data, *features)
-
-
-def put(session, endpoint, data, *features):
-    debug_request(urljoin(endpoint, *features), "PUT", data)
-    return make_request(session, "put", endpoint, data, *features)
-
-
-def make_request(session, method_name, endpoint, data, *features):
-    url = urljoin(endpoint, *features)
-    method = getattr(session, method_name)
-    try:
-        if data:
-            response = method(url, json=data)
-        else:
-            response = method(url)
-        if response.status_code != 200:
-            raise StatusCodeError()
-        json = response.json()
-    except (requests.ConnectionError, StatusCodeError, requests.JSONDecodeError) as e:
-        handle_error(session, url, method_name.upper(), data, response, e)
-    debug_response(json=json)
-    return json
-
-
-def handle_error(session, url, method, data, response, error):
-    if type(error) is requests.ConnectionError:
-        restapi = os.environ["DIOPTRA_RESTAPI_URI"]
-        message = (
-            f"Could not connect to the REST API. Is the server running at {restapi}?"
-        )
-        LOGGER.error(message, url=url, method=method, data=data, response=response.text)
-        raise APIConnectionError(message)
-    if type(error) is StatusCodeError:
-        message = f"Error code {response.status_code} returned."
-        LOGGER.error(message, url=url, method=method, data=data, response=response.text)
-        raise StatusCodeError(message)
-    if type(error) is requests.JSONDecodeError:
-        message = "JSON response could not be decoded."
-        LOGGER.error(message, url=url, method=method, data=data, response=response.text)
-        raise JSONDecodeError(message)
-
-class APIConnectionError(Exception):
-    """Class for connection errors"""
-
-
-class StatusCodeError(Exception):
-    """Class for status code errors"""
-
-
-class JSONDecodeError(Exception):
-    """Class for JSON decode errors"""
+    dioptra_client = get_logged_in_session()
+    artifact = dioptra_client.artifacts.create(
+        group_id=1, 
+        description=f"artifact for job {job_id}", 
+        job_id=job_id,
+        uri=source_uri
+    )
+    LOGGER.info("artifact", response=artifact)
\ No newline at end of file