From 9a83c754dd9c7f90e7dfc78622bc53f2631eaa01 Mon Sep 17 00:00:00 2001
From: RasanYo <rasanhy@gmail.com>
Date: Wed, 21 Aug 2024 14:56:36 +0200
Subject: [PATCH 1/3] ignore

---
 src/backend/Clusterers/clusterer.py          |   5 +-
 src/backend/Clusterers/test_clustering.ipynb | 589 +++++++++----------
 2 files changed, 293 insertions(+), 301 deletions(-)

diff --git a/src/backend/Clusterers/clusterer.py b/src/backend/Clusterers/clusterer.py
index 7ae8c4a..ad30d41 100644
--- a/src/backend/Clusterers/clusterer.py
+++ b/src/backend/Clusterers/clusterer.py
@@ -43,9 +43,10 @@ def embed_cell(self, code_str: str, desc_str: str) -> list[float]:
             list[float]: A list representing the embedded vector of the code snippet and its description.
         """
         
-        code_embedding = self._process_code(code_str)
+        # code_embedding = self._process_code(code_str)
         desc_embedding = self._process_summary(desc_str)
-        return torch.mean(torch.stack([code_embedding, desc_embedding]), dim=0).detach().numpy().reshape(-1).tolist()
+        # return torch.mean(torch.stack([code_embedding, desc_embedding]), dim=0).detach().numpy().reshape(-1).tolist()
+        return desc_embedding.detach().numpy().reshape(-1).tolist()
         
     
     def cluster(self, data: dict, classes: list[str]) -> dict:
diff --git a/src/backend/Clusterers/test_clustering.ipynb b/src/backend/Clusterers/test_clustering.ipynb
index 5c441f0..99947e3 100644
--- a/src/backend/Clusterers/test_clustering.ipynb
+++ b/src/backend/Clusterers/test_clustering.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -16,14 +16,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 28/28 [02:02<00:00,  4.37s/it]"
+      "/home/ryounis/.local/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n",
+      "100%|██████████| 28/28 [00:28<00:00,  1.02s/it]"
      ]
     },
     {
@@ -70,7 +72,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -79,7 +81,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -90,7 +92,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -104,255 +106,255 @@
     {
      "data": {
       "text/plain": [
-       "array([[-1.37175837e+01,  1.00978193e+01],\n",
-       "       [-5.78811407e+00,  2.12184453e+00],\n",
-       "       [-5.92291832e+00,  2.19265699e+00],\n",
-       "       [ 1.12323112e+01, -1.06657038e+01],\n",
-       "       [ 1.47350273e+01, -6.12124395e+00],\n",
-       "       [ 1.00115709e+01, -1.07289543e+01],\n",
-       "       [-9.11698863e-02, -5.18058443e+00],\n",
-       "       [ 1.49024925e+01, -7.35068703e+00],\n",
-       "       [ 1.07252331e+01, -4.43146610e+00],\n",
-       "       [ 5.37833548e+00, -1.34699326e+01],\n",
-       "       [ 6.35126173e-01, -6.56303358e+00],\n",
-       "       [ 9.16349232e-01, -5.57818604e+00],\n",
-       "       [-5.24499035e+00, -1.81227970e+00],\n",
-       "       [-3.93623638e+00,  1.70813274e+00],\n",
-       "       [ 8.49345303e+00,  1.22571354e+01],\n",
-       "       [ 6.42749262e+00, -1.26540737e+01],\n",
-       "       [ 6.28004372e-01,  4.52405643e+00],\n",
-       "       [-7.40044355e+00,  4.88245869e+00],\n",
-       "       [-6.78525686e+00,  9.22694397e+00],\n",
-       "       [-9.32481110e-01,  2.29265022e+00],\n",
-       "       [ 1.20960207e+01, -1.97845137e+00],\n",
-       "       [ 1.21662350e+01, -2.05518675e+00],\n",
-       "       [-4.92035770e+00,  2.61755943e+00],\n",
-       "       [-3.41984183e-01,  5.30294371e+00],\n",
-       "       [-7.70773745e+00,  3.29078674e+00],\n",
-       "       [ 1.07263250e+01, -2.63318467e+00],\n",
-       "       [-4.43802261e+00,  8.73339558e+00],\n",
-       "       [-5.28339720e+00, -4.10964251e+00],\n",
-       "       [ 9.20057869e+00,  1.17356901e+01],\n",
-       "       [ 7.58105183e+00,  4.98882341e+00],\n",
-       "       [ 1.11076679e+01,  1.09049816e+01],\n",
-       "       [-9.98509121e+00, -2.74959207e+00],\n",
-       "       [-3.71671844e+00, -7.41632175e+00],\n",
-       "       [-6.43813848e+00,  1.43449669e+01],\n",
-       "       [-6.53297186e+00,  1.40329285e+01],\n",
-       "       [ 7.02277374e+00,  3.45576429e+00],\n",
-       "       [ 1.25630713e+01,  1.46274137e+01],\n",
-       "       [ 1.27685356e+01, -1.21724377e+01],\n",
-       "       [-1.36550865e+01,  4.75087881e+00],\n",
-       "       [-8.39715290e+00,  7.22419739e-01],\n",
-       "       [-3.99889159e+00,  8.24410534e+00],\n",
-       "       [ 2.10762715e+00, -9.01635265e+00],\n",
-       "       [-2.78082871e+00, -8.97075176e+00],\n",
-       "       [ 3.34923410e+00, -2.30311728e+00],\n",
-       "       [ 2.43975067e+00, -5.45543242e+00],\n",
-       "       [-6.51332569e+00,  1.16781425e+00],\n",
-       "       [ 6.07389402e+00, -1.33006597e+00],\n",
-       "       [ 5.09988022e+00,  6.06473398e+00],\n",
-       "       [ 7.63139904e-01, -2.43370354e-01],\n",
-       "       [ 3.77313876e+00, -1.30057592e+01],\n",
-       "       [-5.88149977e+00,  8.44767761e+00],\n",
-       "       [ 1.49254198e+01, -9.75953770e+00],\n",
-       "       [-6.39485195e-02, -3.40470195e+00],\n",
-       "       [ 7.27886152e+00,  6.80776882e+00],\n",
-       "       [-7.48555374e+00,  9.45926952e+00],\n",
-       "       [ 6.83100522e-01, -2.77236652e+00],\n",
-       "       [ 5.51721668e+00,  7.95000315e+00],\n",
-       "       [ 1.31592619e+00, -1.24414415e+01],\n",
-       "       [ 3.76025081e+00, -1.49713755e+01],\n",
-       "       [ 8.03908348e+00, -1.13010511e+01],\n",
-       "       [-6.79260349e+00,  5.60651970e+00],\n",
-       "       [-6.68469000e+00, -8.05535889e+00],\n",
-       "       [-4.55871534e+00,  1.19266491e+01],\n",
-       "       [-4.49838161e+00,  1.18787909e+01],\n",
-       "       [-9.66175461e+00,  8.86633682e+00],\n",
-       "       [-1.04210854e+01, -2.47214630e-01],\n",
-       "       [ 1.62285347e+01, -6.31331778e+00],\n",
-       "       [-1.51347818e+01,  4.78042984e+00],\n",
-       "       [ 2.31286192e+00, -1.61267109e+01],\n",
-       "       [-3.51727992e-01,  2.96251106e+00],\n",
-       "       [-1.43218946e+01,  4.45898438e+00],\n",
-       "       [-1.16324759e+01, -1.22100890e+00],\n",
-       "       [-1.26327744e+01, -4.72482413e-01],\n",
-       "       [ 1.08561487e+01,  8.94425297e+00],\n",
-       "       [-1.20794420e+01, -4.93198007e-01],\n",
-       "       [-1.24195232e+01,  3.90133977e-01],\n",
-       "       [-1.15867023e+01,  1.25750101e+00],\n",
-       "       [-2.52293777e+00, -6.67570710e-01],\n",
-       "       [-1.15350161e+01,  1.06913338e+01],\n",
-       "       [ 2.83199692e+00,  1.01786661e+01],\n",
-       "       [-3.80284858e+00, -4.05509567e+00],\n",
-       "       [-1.53541298e+01,  1.26097012e+00],\n",
-       "       [-1.53962631e+01,  1.03244257e+00],\n",
-       "       [-9.00663948e+00,  5.80495119e+00],\n",
-       "       [ 1.02444220e+01, -1.35480328e+01],\n",
-       "       [-1.04883776e+01,  4.39498997e+00],\n",
-       "       [-9.90470982e+00,  4.86721897e+00],\n",
-       "       [-1.37056904e+01, -8.01254928e-01],\n",
-       "       [-9.60574150e+00,  2.01624036e+00],\n",
-       "       [ 5.55766010e+00, -7.26250373e-03],\n",
-       "       [ 5.56236315e+00,  4.75797355e-02],\n",
-       "       [-1.40561876e+01, -1.59339622e-01],\n",
-       "       [-9.81060696e+00,  2.07426739e+00],\n",
-       "       [-1.13727951e+01, -4.97262764e+00],\n",
-       "       [-5.89126444e+00, -1.21665516e+01],\n",
-       "       [-5.91017294e+00, -1.21665401e+01],\n",
-       "       [-7.12662554e+00, -1.22273674e+01],\n",
-       "       [-1.18539464e+00,  1.19514713e+01],\n",
-       "       [-7.30356503e+00,  6.46449852e+00],\n",
-       "       [ 8.96811295e+00, -1.17751732e+01],\n",
-       "       [ 2.37476754e+00, -3.48259807e+00],\n",
-       "       [ 5.14130974e+00, -1.33610268e+01],\n",
-       "       [-1.03107166e+01,  1.15892801e+01],\n",
-       "       [ 1.22832489e+01,  1.39025459e+01],\n",
-       "       [ 9.34253502e+00,  6.75177050e+00],\n",
-       "       [ 4.17700887e-01,  7.31659365e+00],\n",
-       "       [ 1.60241437e+00,  9.49040508e+00],\n",
-       "       [ 1.47214854e+00,  9.48364353e+00],\n",
-       "       [ 8.83512592e+00, -1.00492172e+01],\n",
-       "       [-1.32477226e+01,  4.42159653e-01],\n",
-       "       [ 1.20430546e+01,  1.33373547e+01],\n",
-       "       [ 7.27205098e-01,  6.37872875e-01],\n",
-       "       [ 7.09396422e-01, -7.63112831e+00],\n",
-       "       [-3.54163170e+00,  3.97828579e+00],\n",
-       "       [ 1.31641607e+01, -6.91261864e+00],\n",
-       "       [ 1.39750690e+01, -9.28473377e+00],\n",
-       "       [ 2.91687703e+00, -9.54981041e+00],\n",
-       "       [ 5.65599585e+00, -1.09740639e+01],\n",
-       "       [ 4.21296358e+00,  1.55691614e+01],\n",
-       "       [ 1.41699095e+01, -5.30009270e+00],\n",
-       "       [-3.28262663e+00, -5.48938751e+00],\n",
-       "       [-7.45699644e+00, -4.02317953e+00],\n",
-       "       [ 5.54321003e+00, -1.08925419e+01],\n",
-       "       [ 5.59356785e+00,  6.40051889e+00],\n",
-       "       [-2.13061309e+00,  4.19605541e+00],\n",
-       "       [-1.38393726e+01, -2.40622687e+00],\n",
-       "       [ 1.03311930e+01, -9.17897415e+00],\n",
-       "       [-1.35006790e+01,  1.83870542e+00],\n",
-       "       [ 1.48395729e+01, -8.44294834e+00],\n",
-       "       [-4.62616301e+00, -9.17389107e+00],\n",
-       "       [ 1.22629490e+01, -9.93170357e+00],\n",
-       "       [ 7.61977863e+00,  8.08354950e+00],\n",
-       "       [-9.06973362e+00, -3.47457123e+00],\n",
-       "       [-8.13869381e+00, -6.48788595e+00],\n",
-       "       [-1.48445339e+01,  8.33740902e+00],\n",
-       "       [-1.00093842e+01,  1.19642563e+01],\n",
-       "       [ 5.47983503e+00,  1.08921022e+01],\n",
-       "       [ 5.30666256e+00,  1.09101543e+01],\n",
-       "       [ 9.78561878e+00, -7.43099833e+00],\n",
-       "       [-1.10897512e+01,  7.74086666e+00],\n",
-       "       [-2.76681042e+00,  6.48532200e+00],\n",
-       "       [-6.21705770e+00,  7.10145283e+00],\n",
-       "       [-1.48571529e+01,  8.30819416e+00],\n",
-       "       [-1.11079407e+01,  7.71986580e+00],\n",
-       "       [ 6.43550110e+00,  1.40371866e+01],\n",
-       "       [ 1.41875591e+01, -8.43225288e+00],\n",
-       "       [ 6.62566948e+00,  2.45911980e+00],\n",
-       "       [ 1.34622974e+01, -1.04939289e+01],\n",
-       "       [ 9.14464569e+00,  1.47397876e+00],\n",
-       "       [ 1.14178524e+01, -7.51944399e+00],\n",
-       "       [ 6.16102934e+00,  3.28433108e+00],\n",
-       "       [ 3.87101650e+00,  3.87840128e+00],\n",
-       "       [ 4.46135473e+00,  7.52983379e+00],\n",
-       "       [ 3.65966606e+00,  4.44946671e+00],\n",
-       "       [ 3.31269360e+00,  7.23920727e+00],\n",
-       "       [-4.07666862e-01, -4.48856920e-01],\n",
-       "       [ 7.21139097e+00,  2.13260198e+00],\n",
-       "       [-1.54663200e+01,  5.72400427e+00],\n",
-       "       [ 8.51833725e+00,  5.74918127e+00],\n",
-       "       [ 2.32672930e+00,  2.58989334e+00],\n",
-       "       [ 2.02852249e+00,  4.99172926e+00],\n",
-       "       [-1.46494970e+01,  3.07841253e+00],\n",
-       "       [ 1.98586822e+00, -2.19158363e+00],\n",
-       "       [ 5.00948715e+00,  1.62147522e+01],\n",
-       "       [ 3.79176998e+00, -4.22194576e+00],\n",
-       "       [ 1.18429494e+00,  3.53497195e+00],\n",
-       "       [ 1.24947679e+00,  4.19145203e+00],\n",
-       "       [-1.57035172e+00, -3.98202610e+00],\n",
-       "       [ 5.00793219e+00, -6.80533504e+00],\n",
-       "       [ 1.08780937e+01, -5.02623749e+00],\n",
-       "       [-2.97161722e+00, -1.02882328e+01],\n",
-       "       [ 2.26569748e+00, -7.81091261e+00],\n",
-       "       [-3.68260479e+00, -9.63501930e+00],\n",
-       "       [-7.71965981e+00,  2.06485939e+00],\n",
-       "       [ 5.03059006e+00, -1.40658216e+01],\n",
-       "       [-5.71676970e+00, -3.10502155e-03],\n",
-       "       [-5.29532862e+00,  7.84821272e-01],\n",
-       "       [-4.86580372e+00,  1.18627667e-01],\n",
-       "       [-3.78823328e+00,  3.11579049e-01],\n",
-       "       [ 1.82243979e+00, -6.68035746e+00],\n",
-       "       [ 8.38843346e+00, -1.23500242e+01],\n",
-       "       [-1.68918476e+01,  3.53146768e+00],\n",
-       "       [ 2.79647684e+00, -3.03739023e+00],\n",
-       "       [ 3.26262164e+00, -1.44423656e+01],\n",
-       "       [-1.19353895e+01,  7.61361504e+00],\n",
-       "       [ 1.93783641e+00,  9.54934239e-01],\n",
-       "       [-9.32531834e-01, -6.72079754e+00],\n",
-       "       [-5.29632759e+00, -6.23508596e+00],\n",
-       "       [-1.44797337e+00, -6.43101168e+00],\n",
-       "       [-6.17939806e+00, -5.72017956e+00],\n",
-       "       [-1.61916387e+00, -6.83899641e+00],\n",
-       "       [-6.64789772e+00, -5.90211964e+00],\n",
-       "       [ 2.48649746e-01, -9.59616089e+00],\n",
-       "       [-5.60635757e+00, -5.68644524e+00],\n",
-       "       [-8.93349528e-01, -9.61373997e+00],\n",
-       "       [-6.13948059e+00, -6.37606907e+00],\n",
-       "       [ 9.70655251e+00, -1.81198967e+00],\n",
-       "       [ 8.01886749e+00,  3.66206312e+00],\n",
-       "       [ 1.07295971e+01,  1.49972811e+01],\n",
-       "       [ 1.07572393e+01,  1.50271463e+01],\n",
-       "       [-7.60155916e-01, -8.08013153e+00],\n",
-       "       [-7.83350849e+00,  9.66682720e+00],\n",
-       "       [ 7.49982214e+00,  1.09835262e+01],\n",
-       "       [ 9.21108532e+00,  1.01806049e+01],\n",
-       "       [ 1.95854628e+00,  1.08379059e+01],\n",
-       "       [ 6.27632475e+00, -7.77666473e+00],\n",
-       "       [ 9.55765915e+00,  9.81697655e+00],\n",
-       "       [ 1.21721287e+01,  1.13274860e+00],\n",
-       "       [-1.35853887e+00,  1.09011173e+01],\n",
-       "       [ 1.20966597e+01,  1.57732830e+01],\n",
-       "       [ 6.42244637e-01,  1.25977602e+01],\n",
-       "       [-1.41024077e+00,  1.25574188e+01],\n",
-       "       [ 5.40255404e+00,  1.46573763e+01],\n",
-       "       [ 1.09957294e+01,  1.66243134e+01],\n",
-       "       [ 5.37694931e+00,  1.49478416e+01],\n",
-       "       [ 1.09044714e+01,  1.67540722e+01],\n",
-       "       [ 1.21804972e+01,  1.23910463e+00],\n",
-       "       [ 1.04967308e+01,  1.12831011e+01],\n",
-       "       [ 1.09998045e+01,  5.29548407e+00],\n",
-       "       [ 5.85210085e+00,  1.52849932e+01],\n",
-       "       [-1.36679935e+01,  1.00706835e+01],\n",
-       "       [ 9.36051905e-01, -1.22172766e+01],\n",
-       "       [ 7.74627495e+00, -1.49545355e+01],\n",
-       "       [ 9.34920216e+00, -9.58496857e+00],\n",
-       "       [-1.26180780e+00,  7.69716358e+00],\n",
-       "       [ 1.93604171e+00, -1.63557911e+01],\n",
-       "       [-9.17175865e+00,  7.61521149e+00],\n",
-       "       [ 7.22234678e+00,  7.10502005e+00],\n",
-       "       [ 6.11442232e+00,  7.89281178e+00],\n",
-       "       [-1.41124468e+01, -3.04422593e+00],\n",
-       "       [ 4.30065662e-01, -1.06523628e+01],\n",
-       "       [ 8.47290230e+00, -1.19764042e+01],\n",
-       "       [-6.34496117e+00,  5.36636829e+00],\n",
-       "       [ 3.90769982e+00,  8.33234406e+00],\n",
-       "       [ 1.22185383e+01, -1.11380749e+01],\n",
-       "       [ 7.82068491e-01,  2.58804393e+00],\n",
-       "       [ 1.34026775e+01, -5.09794760e+00],\n",
-       "       [ 1.24266469e+00, -4.55064487e+00],\n",
-       "       [ 3.19246984e+00,  3.34368563e+00],\n",
-       "       [ 8.89169121e+00, -1.30656195e+01],\n",
-       "       [-4.55153370e+00,  5.68202448e+00],\n",
-       "       [ 8.12743282e+00, -8.35809231e+00],\n",
-       "       [-9.85627294e-01, -5.26463461e+00],\n",
-       "       [ 1.07838392e+01, -1.22301531e+01],\n",
-       "       [-1.31988132e+00, -2.16217065e+00],\n",
-       "       [ 1.55903111e+01, -8.12747955e+00]], dtype=float32)"
+       "array([[  1.4911424 , -20.977583  ],\n",
+       "       [  4.1030197 ,  -8.340393  ],\n",
+       "       [  4.1923532 ,  -8.065796  ],\n",
+       "       [  3.9924166 ,  -8.613281  ],\n",
+       "       [  3.0819228 ,   7.3527956 ],\n",
+       "       [ -6.8498898 ,   9.318042  ],\n",
+       "       [ -8.514273  ,   4.8970323 ],\n",
+       "       [  3.0791552 ,   7.351713  ],\n",
+       "       [  2.7196898 ,   3.7462842 ],\n",
+       "       [ -3.08045   ,  15.636194  ],\n",
+       "       [ -8.1040535 ,   7.3929768 ],\n",
+       "       [ -7.6331873 ,   6.8954935 ],\n",
+       "       [ -8.570385  ,  -1.3460537 ],\n",
+       "       [  0.40983674,  -5.7024317 ],\n",
+       "       [  9.1918955 ,   4.253837  ],\n",
+       "       [ -0.5927596 ,  16.993883  ],\n",
+       "       [ -0.7142469 ,  16.78827   ],\n",
+       "       [ -5.877225  ,   4.5820756 ],\n",
+       "       [ -4.0901    ,  -3.8603642 ],\n",
+       "       [ -0.53378254,  14.493711  ],\n",
+       "       [  8.059087  ,   8.669608  ],\n",
+       "       [  8.057986  ,   8.684082  ],\n",
+       "       [  4.608428  ,   1.8113874 ],\n",
+       "       [  4.398058  ,  11.601454  ],\n",
+       "       [  4.7468767 ,   1.7341857 ],\n",
+       "       [ -2.359604  ,  -5.2552366 ],\n",
+       "       [ -5.0885825 ,  -3.835769  ],\n",
+       "       [ -8.775151  ,   0.23621811],\n",
+       "       [ -3.3844588 ,  -5.992502  ],\n",
+       "       [  3.2120152 ,   6.0106926 ],\n",
+       "       [  9.688266  ,  12.806893  ],\n",
+       "       [ -3.1561413 ,   1.4054289 ],\n",
+       "       [-15.602245  ,   5.2613587 ],\n",
+       "       [  9.991606  ,  12.725576  ],\n",
+       "       [  8.974494  ,  13.190348  ],\n",
+       "       [  4.826329  ,   6.3154764 ],\n",
+       "       [  8.951937  ,  -2.9944313 ],\n",
+       "       [ -8.518968  ,   8.856438  ],\n",
+       "       [  8.6084    , -10.549362  ],\n",
+       "       [  4.0857463 , -13.081872  ],\n",
+       "       [ -0.4260254 ,  -7.8928137 ],\n",
+       "       [ -4.620434  ,   8.135983  ],\n",
+       "       [ -7.299626  ,   2.925058  ],\n",
+       "       [ -5.763961  ,   6.1743054 ],\n",
+       "       [ -7.429165  ,   2.1752853 ],\n",
+       "       [  2.8559005 , -11.290524  ],\n",
+       "       [ 10.973705  ,   1.8633778 ],\n",
+       "       [  0.4489207 ,   3.6364226 ],\n",
+       "       [  1.3829736 , -11.470097  ],\n",
+       "       [-15.020634  ,  10.6184435 ],\n",
+       "       [ -4.482664  ,  -1.149621  ],\n",
+       "       [ -3.1204236 ,  11.179773  ],\n",
+       "       [ -6.6073055 ,  17.159983  ],\n",
+       "       [-10.6750555 ,  15.300937  ],\n",
+       "       [ 11.033347  , -19.073463  ],\n",
+       "       [  2.8475358 ,  -4.384909  ],\n",
+       "       [ -2.0854921 ,  -4.72011   ],\n",
+       "       [ -4.7375097 ,  14.91324   ],\n",
+       "       [ -3.708754  ,  13.551936  ],\n",
+       "       [ -5.088515  ,  10.501     ],\n",
+       "       [  1.2664462 ,   4.9167223 ],\n",
+       "       [ 12.033732  , -11.541703  ],\n",
+       "       [  4.4662647 , -11.199044  ],\n",
+       "       [  4.217767  , -11.674744  ],\n",
+       "       [  1.7360191 , -17.638857  ],\n",
+       "       [  3.0798044 , -12.776994  ],\n",
+       "       [ -7.6380515 ,  -6.1609936 ],\n",
+       "       [  4.6887584 ,  -0.03914154],\n",
+       "       [  6.533724  ,   0.5754346 ],\n",
+       "       [  3.6544302 ,  14.597061  ],\n",
+       "       [  6.5074906 , -11.858356  ],\n",
+       "       [  3.6429496 , -14.0352545 ],\n",
+       "       [  4.6890736 , -14.359901  ],\n",
+       "       [  2.437911  ,  15.724731  ],\n",
+       "       [  6.7900786 , -12.196148  ],\n",
+       "       [  3.6858928 , -15.164356  ],\n",
+       "       [  5.665966  , -13.516985  ],\n",
+       "       [  6.4296026 ,   2.0189128 ],\n",
+       "       [  6.6545553 ,  -3.797109  ],\n",
+       "       [ -4.316378  ,  -9.482368  ],\n",
+       "       [ -8.911797  ,   1.6495987 ],\n",
+       "       [ -0.63847905, -13.204003  ],\n",
+       "       [ -0.76524526, -13.645268  ],\n",
+       "       [ -0.17642057, -13.072916  ],\n",
+       "       [ 11.011986  , -12.729398  ],\n",
+       "       [ 11.417535  , -12.632001  ],\n",
+       "       [  8.036204  , -13.789354  ],\n",
+       "       [  1.8697172 , -16.608606  ],\n",
+       "       [ -0.9634768 , -10.6177    ],\n",
+       "       [  7.4331403 , -15.697743  ],\n",
+       "       [  7.4531984 , -15.748064  ],\n",
+       "       [-14.553859  ,   8.409329  ],\n",
+       "       [ -0.9956612 , -10.540956  ],\n",
+       "       [  4.06037   , -18.676212  ],\n",
+       "       [-14.943383  ,  14.092121  ],\n",
+       "       [-14.939403  ,  14.079824  ],\n",
+       "       [-18.200945  ,  11.445278  ],\n",
+       "       [ -9.724468  ,   7.5347643 ],\n",
+       "       [ -2.0417278 ,   1.0397137 ],\n",
+       "       [ -3.5632493 ,   9.787016  ],\n",
+       "       [ -3.019399  ,   4.925535  ],\n",
+       "       [ -2.8653598 ,  16.01131   ],\n",
+       "       [  6.809896  ,  -4.8141136 ],\n",
+       "       [ 11.776925  ,   7.7577524 ],\n",
+       "       [  1.9960078 ,  13.7166195 ],\n",
+       "       [  6.4345527 ,   3.175998  ],\n",
+       "       [  7.836699  ,   2.94682   ],\n",
+       "       [  7.923975  ,   3.3495839 ],\n",
+       "       [ -6.9299664 ,  16.114973  ],\n",
+       "       [  1.0369406 , -15.495145  ],\n",
+       "       [ 11.435338  ,   7.9085197 ],\n",
+       "       [  1.6798513 , -15.29268   ],\n",
+       "       [ -6.7668676 ,   7.6278934 ],\n",
+       "       [ -0.31787205, -16.429451  ],\n",
+       "       [-12.75347   ,   6.946363  ],\n",
+       "       [-10.077307  ,  13.118757  ],\n",
+       "       [  1.879407  ,   5.276279  ],\n",
+       "       [-13.285581  ,  11.40872   ],\n",
+       "       [-10.95551   ,  16.004637  ],\n",
+       "       [ -5.2960396 ,  -4.284764  ],\n",
+       "       [ -7.8030224 ,  -2.3838074 ],\n",
+       "       [ -7.8998413 ,  10.98991   ],\n",
+       "       [-13.45829   ,  11.500038  ],\n",
+       "       [ -2.098795  ,   5.916464  ],\n",
+       "       [  7.586321  , -11.763202  ],\n",
+       "       [-18.473793  ,  10.631288  ],\n",
+       "       [-13.788611  ,   9.919141  ],\n",
+       "       [  2.19227   , -14.340541  ],\n",
+       "       [ -3.6463225 ,  -1.8648857 ],\n",
+       "       [-10.334268  ,   1.9126722 ],\n",
+       "       [-12.095957  ,   3.491854  ],\n",
+       "       [  2.2510223 ,   2.7288682 ],\n",
+       "       [-12.055382  ,   3.435962  ],\n",
+       "       [-14.849721  ,   1.5755281 ],\n",
+       "       [  4.8172483 , -19.745558  ],\n",
+       "       [ 10.158436  ,  -1.7382355 ],\n",
+       "       [ 13.299309  ,   0.98543173],\n",
+       "       [ 13.281995  ,   0.9916169 ],\n",
+       "       [  0.72051316,  14.756723  ],\n",
+       "       [  6.7249846 ,  -6.8803954 ],\n",
+       "       [  4.87239   ,  -5.288677  ],\n",
+       "       [ -0.8552658 ,  -7.4717793 ],\n",
+       "       [  4.8024654 , -19.83588   ],\n",
+       "       [  6.658818  ,  -6.8609366 ],\n",
+       "       [  9.316136  , -15.086629  ],\n",
+       "       [ -2.7672415 ,   6.345767  ],\n",
+       "       [ -1.8851329 ,  -1.8641586 ],\n",
+       "       [ -8.098972  ,  12.462139  ],\n",
+       "       [ -2.795406  ,  -1.971202  ],\n",
+       "       [-14.045732  ,   1.6019909 ],\n",
+       "       [  0.8217532 ,  -4.073481  ],\n",
+       "       [  3.6103487 ,  -3.1428638 ],\n",
+       "       [ -1.4771562 ,  -3.8703377 ],\n",
+       "       [  3.2463152 ,  -3.5963917 ],\n",
+       "       [  0.08053005,  -3.18523   ],\n",
+       "       [-10.749737  ,  10.900685  ],\n",
+       "       [  4.740876  ,   4.922604  ],\n",
+       "       [  5.7181535 , -19.112741  ],\n",
+       "       [  0.5346666 ,   6.0908203 ],\n",
+       "       [  5.3542027 ,   7.8866687 ],\n",
+       "       [  6.0174384 ,   8.873576  ],\n",
+       "       [  1.8808582 , -12.587631  ],\n",
+       "       [ -0.703811  ,   7.4264717 ],\n",
+       "       [ -1.619957  , -18.870045  ],\n",
+       "       [ -1.0030869 ,   7.5051756 ],\n",
+       "       [ -1.2651656 ,   8.957152  ],\n",
+       "       [  4.0416107 ,   8.821385  ],\n",
+       "       [ -1.5951645 ,   9.414739  ],\n",
+       "       [ -0.58932036,   4.332915  ],\n",
+       "       [-12.248752  ,  13.24694   ],\n",
+       "       [ -9.71812   ,   4.107433  ],\n",
+       "       [ -0.6836764 ,   5.470822  ],\n",
+       "       [ -9.730919  ,   4.255055  ],\n",
+       "       [  2.4184358 ,  -9.763221  ],\n",
+       "       [ -3.4276917 ,  13.549579  ],\n",
+       "       [  1.765311  ,  -8.313595  ],\n",
+       "       [  2.752961  ,  -8.94554   ],\n",
+       "       [  1.9034454 ,  -9.517391  ],\n",
+       "       [  2.689214  ,  -7.0995936 ],\n",
+       "       [ -3.8533013 ,   3.5139039 ],\n",
+       "       [ -6.051204  ,   9.825768  ],\n",
+       "       [ 12.406368  ,  -7.9197106 ],\n",
+       "       [ -3.6775718 ,   5.1770234 ],\n",
+       "       [  5.2594748 ,  -9.755101  ],\n",
+       "       [  6.970217  ,  -9.642674  ],\n",
+       "       [ -2.02417   ,   4.354738  ],\n",
+       "       [ -1.629808  ,   2.5375261 ],\n",
+       "       [ -5.794597  ,  -0.87719995],\n",
+       "       [ -1.3985996 ,   2.8299544 ],\n",
+       "       [ -6.3908    ,  -1.3628763 ],\n",
+       "       [ -1.3097304 ,   2.7198236 ],\n",
+       "       [ -6.1134553 ,  -1.2944112 ],\n",
+       "       [ -6.983636  ,   5.7963862 ],\n",
+       "       [ -6.365953  ,  -0.4468835 ],\n",
+       "       [ -8.0384245 ,  12.260972  ],\n",
+       "       [ -7.1103816 ,  -0.80238575],\n",
+       "       [  1.3807209 ,   9.673805  ],\n",
+       "       [  9.528444  ,  -3.7490685 ],\n",
+       "       [ 12.02499   ,  -2.6664767 ],\n",
+       "       [ 12.035615  ,  -2.6415079 ],\n",
+       "       [-13.088502  ,  -2.1748838 ],\n",
+       "       [ 11.022153  , -19.07696   ],\n",
+       "       [  8.693322  ,   1.82369   ],\n",
+       "       [  7.9896755 ,  -8.05356   ],\n",
+       "       [ 11.157551  ,   4.36402   ],\n",
+       "       [  1.3930172 ,  13.793808  ],\n",
+       "       [  9.36695   ,  -7.4447412 ],\n",
+       "       [-10.358156  ,  -5.4107537 ],\n",
+       "       [-11.374082  ,   6.6224036 ],\n",
+       "       [ -6.2236657 ,  -8.37891   ],\n",
+       "       [  1.8247467 ,   0.0640066 ],\n",
+       "       [  2.0765707 ,  -0.92514175],\n",
+       "       [ -2.8569844 , -18.252577  ],\n",
+       "       [ -8.233906  , -12.120044  ],\n",
+       "       [ -2.9680934 , -17.726389  ],\n",
+       "       [ -8.235794  , -12.138669  ],\n",
+       "       [ -9.888899  ,  -5.9012775 ],\n",
+       "       [ -5.4648843 ,  -6.313779  ],\n",
+       "       [  7.1719913 ,   5.128985  ],\n",
+       "       [ -2.8664668 , -17.762976  ],\n",
+       "       [  1.4946516 , -20.869478  ],\n",
+       "       [ -4.87249   ,  13.326306  ],\n",
+       "       [  8.921921  ,  -1.7610298 ],\n",
+       "       [ -5.868545  ,  16.927528  ],\n",
+       "       [ -2.9250617 , -20.127605  ],\n",
+       "       [ -3.5244508 ,  14.488954  ],\n",
+       "       [  7.990937  ,  -6.3916745 ],\n",
+       "       [  1.8038685 ,   2.8635237 ],\n",
+       "       [  0.22786504,   1.2459419 ],\n",
+       "       [-18.572382  ,   9.971396  ],\n",
+       "       [  0.13713798,   1.6884476 ],\n",
+       "       [ -4.3648643 ,   9.670094  ],\n",
+       "       [ -3.5945346 ,   7.683328  ],\n",
+       "       [ -0.1997497 ,  -2.337449  ],\n",
+       "       [ -3.8549535 ,  16.565983  ],\n",
+       "       [  6.3884635 ,  -8.076441  ],\n",
+       "       [ -5.712761  ,   1.0717326 ],\n",
+       "       [ -5.0437927 ,   4.5406694 ],\n",
+       "       [  2.600987  ,  12.52804   ],\n",
+       "       [ -0.3566282 ,  10.303238  ],\n",
+       "       [-15.547438  ,  12.610553  ],\n",
+       "       [-10.982545  ,   9.457242  ],\n",
+       "       [ -9.235936  ,  12.762201  ],\n",
+       "       [ -6.0983567 ,   1.064768  ],\n",
+       "       [  0.6762013 ,  10.003982  ],\n",
+       "       [  0.46581823,   7.8991637 ]], dtype=float32)"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -368,14 +370,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 136,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(246, 43)\n"
+      "(246, 65)\n"
      ]
     }
    ],
@@ -394,23 +396,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Cluster -1: 47\n",
-      "Cluster 0: 18\n",
-      "Cluster 1: 11\n",
-      "Cluster 2: 32\n",
-      "Cluster 3: 23\n",
-      "Cluster 4: 15\n",
-      "Cluster 5: 19\n",
-      "Cluster 6: 16\n",
-      "Cluster 7: 36\n",
-      "Cluster 8: 29\n"
+      "Cluster -1: 51\n",
+      "Cluster 0: 13\n",
+      "Cluster 1: 21\n",
+      "Cluster 2: 47\n",
+      "Cluster 3: 36\n",
+      "Cluster 4: 78\n"
      ]
     }
    ],
@@ -437,16 +435,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Cluster -1: 0\n",
-      "Cluster 0: 34\n",
-      "Cluster 1: 13\n"
+      "Cluster -1: 5\n",
+      "Cluster 0: 31\n",
+      "Cluster 1: 15\n"
      ]
     }
    ],
@@ -462,25 +460,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Cluster -1: 0\n",
-      "Cluster 0: 18\n",
-      "Cluster 1: 11\n",
-      "Cluster 2: 32\n",
-      "Cluster 3: 23\n",
-      "Cluster 4: 15\n",
-      "Cluster 5: 19\n",
-      "Cluster 6: 16\n",
-      "Cluster 7: 36\n",
-      "Cluster 8: 29\n",
-      "Cluster 9: 34\n",
-      "Cluster 10: 13\n"
+      "Cluster -1: 5\n",
+      "Cluster 0: 13\n",
+      "Cluster 1: 21\n",
+      "Cluster 2: 47\n",
+      "Cluster 3: 36\n",
+      "Cluster 4: 78\n",
+      "Cluster 5: 31\n",
+      "Cluster 6: 15\n"
      ]
     }
    ],
@@ -496,33 +490,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 11/11 [00:08<00:00,  1.22it/s]\n"
+      "100%|██████████| 8/8 [00:06<00:00,  1.32it/s]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "{'0': 'Text Data Processing and Preparation',\n",
-       " '1': 'Text Data Cleaning and Preprocessing Functions',\n",
-       " '2': 'Text Preprocessing and Tokenization for NLP',\n",
-       " '3': 'Text Preprocessing and Feature Engineering Techniques',\n",
-       " '4': 'Machine Learning Data Preparation and Conversion',\n",
-       " '5': 'Comprehensive Tweet Preprocessing and Feature Engineering',\n",
-       " '6': 'Text Data Preprocessing and Cleaning',\n",
-       " '7': 'Text Preprocessing and Data Splitting Techniques',\n",
-       " '8': 'Text Data Preprocessing and Vectorization Techniques',\n",
-       " '9': 'DataFrame Preprocessing and Text Vectorization',\n",
-       " '10': 'Text Data Preprocessing and Analysis Functions'}"
+       "{'0': 'Natural Language Processing with spaCy and NLTK',\n",
+       " '1': 'Text Preprocessing with NLP Methods in Python',\n",
+       " '2': 'Data Preprocessing with NLTK and Pandas',\n",
+       " '3': 'Data Preparation and TensorFlow Models',\n",
+       " '4': 'Text Preprocessing and Vectorization Techniques',\n",
+       " '5': 'Data Processing with Pandas, NLTK, TfidfVectorizer',\n",
+       " '6': 'Text Preprocessing with TensorFlow and CountVectorizer',\n",
+       " '-1': 'Data Preprocessing and Encoding with Dictionaries'}"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -538,12 +529,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1000x800 with 2 Axes>"
       ]

From 49e1a5988e36f92e7af26dd6bc9fc77726be1663 Mon Sep 17 00:00:00 2001
From: April Wang from ETHZ <april.wang@inf.ethz.ch>
Date: Thu, 22 Aug 2024 09:48:43 +0200
Subject: [PATCH 2/3] fix build

---
 .copier-answers.yml                          |   4 +-
 .github/workflows/build.yml                  |  14 +--
 .github/workflows/check-release.yml          |   2 +-
 .gitignore                                   |   4 +-
 .prettierignore                              |   2 +-
 DEPLOYMENT.md                                |  18 ++++
 Dockerfile                                   |   7 ++
 README.md                                    |  12 +--
 RELEASE.md                                   |   2 +-
 binder/environment.yml                       |   2 +-
 binder/postBuild                             |   4 +-
 {jupyterlab_apod => cluster_viz}/__init__.py |   4 +-
 install.json                                 |   4 +-
 package.json                                 |  14 +--
 pyproject.toml                               |  19 ++--
 src/__tests__/jupyterlab_apod.spec.ts        |   2 +-
 ui-tests/package.json                        |   4 +-
 ui-tests/tests/jupyterlab_apod.spec.ts       |   2 +-
 yarn.lock                                    | 108 +++++++++----------
 19 files changed, 127 insertions(+), 101 deletions(-)
 create mode 100644 DEPLOYMENT.md
 create mode 100644 Dockerfile
 rename {jupyterlab_apod => cluster_viz}/__init__.py (80%)

diff --git a/.copier-answers.yml b/.copier-answers.yml
index e2f51d1..5ab8476 100644
--- a/.copier-answers.yml
+++ b/.copier-answers.yml
@@ -6,12 +6,12 @@ author_name: My Name
 has_binder: true
 has_settings: false
 kind: frontend
-labextension_name: jupyterlab_apod
+labextension_name: cluster_viz
 project_short_description: ' Show a random NASA Astronomy Picture of the Day in a
     JupyterLab panel
 
     '
-python_name: jupyterlab_apod
+python_name: cluster_viz
 repository: ''
 test: true
 
diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 28129b9..64ff06c 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -41,7 +41,7 @@ jobs:
         python -m pip install .[test]
 
         jupyter labextension list
-        jupyter labextension list 2>&1 | grep -ie "jupyterlab_apod.*OK"
+        jupyter labextension list 2>&1 | grep -ie "cluster_viz.*OK"
         python -m jupyterlab.browser_check
 
     - name: Package the extension
@@ -50,13 +50,13 @@ jobs:
 
         pip install build
         python -m build
-        pip uninstall -y "jupyterlab_apod" jupyterlab
+        pip uninstall -y "cluster_viz" jupyterlab
 
     - name: Upload extension packages
       uses: actions/upload-artifact@v4
       with:
         name: extension-artifacts
-        path: dist/jupyterlab_apod*
+        path: dist/cluster_viz*
         if-no-files-found: error
 
   test_isolated:
@@ -79,11 +79,11 @@ jobs:
         sudo rm -rf $(which node)
         sudo rm -rf $(which node)
 
-        pip install "jupyterlab>=4.0.0,<5" jupyterlab_apod*.whl
+        pip install "jupyterlab>=4.0.0,<5" cluster_viz*.whl
 
 
         jupyter labextension list
-        jupyter labextension list 2>&1 | grep -ie "jupyterlab_apod.*OK"
+        jupyter labextension list 2>&1 | grep -ie "cluster_viz.*OK"
         python -m jupyterlab.browser_check --no-browser-test
 
   integration-tests:
@@ -109,7 +109,7 @@ jobs:
     - name: Install the extension
       run: |
         set -eux
-        python -m pip install "jupyterlab>=4.0.0,<5" jupyterlab_apod*.whl
+        python -m pip install "jupyterlab>=4.0.0,<5" cluster_viz*.whl
 
     - name: Install dependencies
       working-directory: ui-tests
@@ -138,7 +138,7 @@ jobs:
       if: always()
       uses: actions/upload-artifact@v4
       with:
-        name: jupyterlab_apod-playwright-tests
+        name: cluster_viz-playwright-tests
         path: |
           ui-tests/test-results
           ui-tests/playwright-report
diff --git a/.github/workflows/check-release.yml b/.github/workflows/check-release.yml
index dea5378..aad2da2 100644
--- a/.github/workflows/check-release.yml
+++ b/.github/workflows/check-release.yml
@@ -26,5 +26,5 @@ jobs:
       - name: Upload Distributions
         uses: actions/upload-artifact@v4
         with:
-          name: jupyterlab_apod-releaser-dist-${{ github.run_number }}
+          name: cluster_viz-releaser-dist-${{ github.run_number }}
           path: .jupyter_releaser_checkout/dist
diff --git a/.gitignore b/.gitignore
index 8d60b68..1e7c4ad 100644
--- a/.gitignore
+++ b/.gitignore
@@ -10,9 +10,9 @@ backend/api_key.txt
 *.egg-info/
 .ipynb_checkpoints
 *.tsbuildinfo
-jupyterlab_apod/labextension
+cluster_viz/labextension
 # Version file is handled by hatchling
-jupyterlab_apod/_version.py
+cluster_viz/_version.py
 /secrets
 # Integration tests
 ui-tests/test-results/
diff --git a/.prettierignore b/.prettierignore
index 2a5f4b3..1751637 100644
--- a/.prettierignore
+++ b/.prettierignore
@@ -3,5 +3,5 @@ node_modules
 **/lib
 **/package.json
 !/package.json
-jupyterlab_apod
+cluster_viz
 backend
\ No newline at end of file
diff --git a/DEPLOYMENT.md b/DEPLOYMENT.md
new file mode 100644
index 0000000..f5c3ebb
--- /dev/null
+++ b/DEPLOYMENT.md
@@ -0,0 +1,18 @@
+# Using the GitHub Container Registry for Deployment
+
+1. Create a personal token: https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens
+
+```
+docker login ghcr.io --username github-account
+[Paste your GitHub token on this prompt]
+```
+2. Build the image for the server
+```
+docker image build --platform linux/amd64 -t cluster-jupyter . 
+```
+
+2. Tag and push your Docker images
+```
+docker tag cluster-jupyter ghcr.io/eth-peach-lab/datascience-visualisation/cluster-jupyter:latest
+docker push ghcr.io/eth-peach-lab/datascience-visualisation/cluster-jupyter:latest
+```
\ No newline at end of file
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..666e491
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,7 @@
+FROM quay.io/jupyter/minimal-notebook:hub-5.1.0
+USER root
+RUN pip install --no-cache -U cluster_viz 
+EXPOSE 8000
+EXPOSE 8888
+USER ${NB_USER}
+CMD ["/bin/bash","-c", "jupyterhub-singleuser"]
\ No newline at end of file
diff --git a/README.md b/README.md
index 1f75c44..ba0f79a 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,4 @@
-# jupyterlab_apod
+# cluster_Viz
 
 [![Github Actions Status](/workflows/Build/badge.svg)](/actions/workflows/build.yml)
 
@@ -16,7 +16,7 @@
 To install the extension, execute:
 
 ```bash
-pip install jupyterlab_apod
+pip install cluster_viz
 ```
 
 ## Uninstall
@@ -24,7 +24,7 @@ pip install jupyterlab_apod
 To remove the extension, execute:
 
 ```bash
-pip uninstall jupyterlab_apod
+pip uninstall cluster_viz
 ```
 
 ## Contributing
@@ -39,7 +39,7 @@ The `jlpm` command is JupyterLab's pinned version of
 
 ```bash
 # Clone the repo to your local environment
-# Change directory to the jupyterlab_apod directory
+# Change directory to the cluster_viz directory
 # Install package in development mode
 pip install -e "."
 # Link your development version of the extension with JupyterLab
@@ -68,12 +68,12 @@ jupyter lab build --minimize=False
 ### Development uninstall
 
 ```bash
-pip uninstall jupyterlab_apod
+pip uninstall cluster_viz
 ```
 
 In development mode, you will also need to remove the symlink created by `jupyter labextension develop`
 command. To find its location, you can run `jupyter labextension list` to figure out where the `labextensions`
-folder is located. Then you can remove the symlink named `jupyterlab_apod` within that folder.
+folder is located. Then you can remove the symlink named `cluster_viz` within that folder.
 
 ### Testing the extension
 
diff --git a/RELEASE.md b/RELEASE.md
index 4861789..1de8831 100644
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -1,4 +1,4 @@
-# Making a new release of jupyterlab_apod
+# Making a new release of cluster_viz
 
 The extension can be published to `PyPI` and `npm` manually or using the [Jupyter Releaser](https://github.com/jupyter-server/jupyter_releaser).
 
diff --git a/binder/environment.yml b/binder/environment.yml
index 7359a31..4ff0f8d 100644
--- a/binder/environment.yml
+++ b/binder/environment.yml
@@ -1,4 +1,4 @@
-# a mybinder.org-ready environment for demoing jupyterlab_apod
+# a mybinder.org-ready environment for demoing cluster_viz
 # this environment may also be used locally on Linux/MacOS/Windows, e.g.
 #
 #   conda env update --file binder/environment.yml
diff --git a/binder/postBuild b/binder/postBuild
index 5866b85..9cfc133 100755
--- a/binder/postBuild
+++ b/binder/postBuild
@@ -1,5 +1,5 @@
 #!/usr/bin/env python3
-""" perform a development install of jupyterlab_apod
+""" perform a development install of cluster_viz
 
     On Binder, this will run _after_ the environment has been fully created from
     the environment.yml in this directory.
@@ -43,5 +43,5 @@ _("jupyter", "server", "extension", "list")
 _("jupyter", "labextension", "list")
 
 
-print("JupyterLab with jupyterlab_apod is ready to run with:\n")
+print("JupyterLab with cluster_viz is ready to run with:\n")
 print("\tjupyter lab\n")
diff --git a/jupyterlab_apod/__init__.py b/cluster_viz/__init__.py
similarity index 80%
rename from jupyterlab_apod/__init__.py
rename to cluster_viz/__init__.py
index 6e31c55..13410bc 100644
--- a/jupyterlab_apod/__init__.py
+++ b/cluster_viz/__init__.py
@@ -5,12 +5,12 @@
     # in editable mode with pip. It is highly recommended to install
     # the package from a stable release or in editable mode: https://pip.pypa.io/en/stable/topics/local-project-installs/#editable-installs
     import warnings
-    warnings.warn("Importing 'jupyterlab_apod' outside a proper installation.")
+    warnings.warn("Importing 'cluster_viz' outside a proper installation.")
     __version__ = "dev"
 
 
 def _jupyter_labextension_paths():
     return [{
         "src": "labextension",
-        "dest": "jupyterlab_apod"
+        "dest": "cluster_viz"
     }]
diff --git a/install.json b/install.json
index 3a658ac..166052f 100644
--- a/install.json
+++ b/install.json
@@ -1,5 +1,5 @@
 {
   "packageManager": "python",
-  "packageName": "jupyterlab_apod",
-  "uninstallInstructions": "Use your Python package manager (pip, conda, etc.) to uninstall the package jupyterlab_apod"
+  "packageName": "cluster_viz",
+  "uninstallInstructions": "Use your Python package manager (pip, conda, etc.) to uninstall the package cluster_viz"
 }
diff --git a/package.json b/package.json
index ba8bab3..c1b0970 100644
--- a/package.json
+++ b/package.json
@@ -1,15 +1,15 @@
 {
-    "name": "jupyterlab_apod",
-    "version": "0.1.0",
+    "name": "cluster_viz",
+    "version": "0.2.1",
     "description": "Show a random NASA Astronomy Picture of the Day in a JupyterLab panel",
     "keywords": [
         "jupyter",
         "jupyterlab",
         "jupyterlab-extension"
     ],
-    "homepage": "",
+    "homepage": "https://github.com/ETH-PEACH-Lab/datascience-visualisation",
     "bugs": {
-        "url": "/issues"
+        "url": "https://github.com/ETH-PEACH-Lab/datascience-visualisation/issues"
     },
     "license": "BSD-3-Clause",
     "author": "My Name",
@@ -23,7 +23,7 @@
     "style": "style/index.css",
     "repository": {
         "type": "git",
-        "url": ".git"
+        "url": "https://github.com/ETH-PEACH-Lab/datascience-visualisation"
     },
     "scripts": {
         "build": "jlpm build:lib && jlpm build:labextension:dev",
@@ -35,7 +35,7 @@
         "clean": "jlpm clean:lib",
         "clean:lib": "rimraf lib tsconfig.tsbuildinfo",
         "clean:lintcache": "rimraf .eslintcache .stylelintcache",
-        "clean:labextension": "rimraf jupyterlab_apod/labextension jupyterlab_apod/_version.py",
+        "clean:labextension": "rimraf cluster_viz/labextension cluster_viz/_version.py",
         "clean:all": "jlpm clean:lib && jlpm clean:labextension && jlpm clean:lintcache",
         "eslint": "jlpm eslint:check --fix",
         "eslint:check": "eslint . --cache --ext .ts,.tsx",
@@ -119,7 +119,7 @@
     },
     "jupyterlab": {
         "extension": true,
-        "outputDir": "jupyterlab_apod/labextension",
+        "outputDir": "cluster_viz/labextension",
         "sharedPackages": {
             "@jupyter-widgets/base": {
                 "bundled": false,
diff --git a/pyproject.toml b/pyproject.toml
index fbff3f1..d774361 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -3,8 +3,9 @@ requires = ["hatchling>=1.5.0", "jupyterlab>=4.0.0,<5", "hatch-nodejs-version>=0
 build-backend = "hatchling.build"
 
 [project]
-name = "jupyterlab_apod"
+name = "cluster_viz"
 readme = "README.md"
+homepage = "https://github.com/ETH-PEACH-Lab/datascience-visualisation"  # Add your repository or website URL here
 license = { file = "LICENSE" }
 requires-python = ">=3.8"
 classifiers = [
@@ -33,24 +34,24 @@ source = "nodejs"
 fields = ["description", "authors", "urls"]
 
 [tool.hatch.build.targets.sdist]
-artifacts = ["jupyterlab_apod/labextension"]
+artifacts = ["cluster_viz/labextension"]
 exclude = [".github", "binder"]
 
 [tool.hatch.build.targets.wheel.shared-data]
-"jupyterlab_apod/labextension" = "share/jupyter/labextensions/jupyterlab_apod"
-"install.json" = "share/jupyter/labextensions/jupyterlab_apod/install.json"
+"cluster_viz/labextension" = "share/jupyter/labextensions/cluster_viz"
+"install.json" = "share/jupyter/labextensions/cluster_viz/install.json"
 
 [tool.hatch.build.hooks.version]
-path = "jupyterlab_apod/_version.py"
+path = "cluster_viz/_version.py"
 
 [tool.hatch.build.hooks.jupyter-builder]
 dependencies = ["hatch-jupyter-builder>=0.5"]
 build-function = "hatch_jupyter_builder.npm_builder"
 ensured-targets = [
-    "jupyterlab_apod/labextension/static/style.js",
-    "jupyterlab_apod/labextension/package.json",
+    "cluster_viz/labextension/static/style.js",
+    "cluster_viz/labextension/package.json",
 ]
-skip-if-exists = ["jupyterlab_apod/labextension/static/style.js"]
+skip-if-exists = ["cluster_viz/labextension/static/style.js"]
 
 [tool.hatch.build.hooks.jupyter-builder.build-kwargs]
 build_cmd = "build:prod"
@@ -60,7 +61,7 @@ npm = ["jlpm"]
 build_cmd = "install:extension"
 npm = ["jlpm"]
 source_dir = "src"
-build_dir = "jupyterlab_apod/labextension"
+build_dir = "cluster_viz/labextension"
 
 [tool.jupyter-releaser.options]
 version_cmd = "hatch version"
diff --git a/src/__tests__/jupyterlab_apod.spec.ts b/src/__tests__/jupyterlab_apod.spec.ts
index 715e124..57a4f6a 100644
--- a/src/__tests__/jupyterlab_apod.spec.ts
+++ b/src/__tests__/jupyterlab_apod.spec.ts
@@ -2,7 +2,7 @@
  * Example of [Jest](https://jestjs.io/docs/getting-started) unit tests
  */
 
-describe('jupyterlab_apod', () => {
+describe('cluster_viz', () => {
   it('should be tested', () => {
     expect(1 + 1).toEqual(2);
   });
diff --git a/ui-tests/package.json b/ui-tests/package.json
index b082a7b..dd6074a 100644
--- a/ui-tests/package.json
+++ b/ui-tests/package.json
@@ -1,7 +1,7 @@
 {
-  "name": "jupyterlab_apod-ui-tests",
+  "name": "cluster_viz-ui-tests",
   "version": "1.0.0",
-  "description": "JupyterLab jupyterlab_apod Integration Tests",
+  "description": "JupyterLab cluster_viz Integration Tests",
   "private": true,
   "scripts": {
     "start": "jupyter lab --config jupyter_server_test_config.py",
diff --git a/ui-tests/tests/jupyterlab_apod.spec.ts b/ui-tests/tests/jupyterlab_apod.spec.ts
index 6b520d2..f44ca17 100644
--- a/ui-tests/tests/jupyterlab_apod.spec.ts
+++ b/ui-tests/tests/jupyterlab_apod.spec.ts
@@ -16,6 +16,6 @@ test('should emit an activation console message', async ({ page }) => {
   await page.goto();
 
   expect(
-    logs.filter(s => s === 'JupyterLab extension jupyterlab_apod is activated!')
+    logs.filter(s => s === 'JupyterLab extension cluster_viz is activated!')
   ).toHaveLength(1);
 });
diff --git a/yarn.lock b/yarn.lock
index fc53ddf..48d61aa 100644
--- a/yarn.lock
+++ b/yarn.lock
@@ -5058,6 +5058,60 @@ __metadata:
   languageName: node
   linkType: hard
 
+"cluster_viz@workspace:.":
+  version: 0.0.0-use.local
+  resolution: "cluster_viz@workspace:."
+  dependencies:
+    "@codemirror/lang-python": ^6.1.6
+    "@jupyterlab/application": ^4.2.1
+    "@jupyterlab/apputils": ^4.3.1
+    "@jupyterlab/builder": ^4.0.0
+    "@jupyterlab/launcher": ^4.2.3
+    "@jupyterlab/launcher\n": ^4.2.3
+    "@jupyterlab/testutils": ^4.0.0
+    "@lumino/widgets": ^2.3.2
+    "@types/cytoscape": ^3.21.4
+    "@types/d3": ^7.4.3
+    "@types/jest": ^29.2.0
+    "@types/json-schema": ^7.0.11
+    "@types/react": ^18.3.3
+    "@types/react-addons-linked-state-mixin": ^0.14.22
+    "@types/react-dom": ^18.3.0
+    "@types/three": ^0.166.0
+    "@typescript-eslint/eslint-plugin": ^6.1.0
+    "@typescript-eslint/parser": ^6.1.0
+    codemirror: ^6.0.1
+    css-loader: ^6.7.1
+    cytoscape: ^3.30.0
+    d3: ^7.9.0
+    eslint: ^8.36.0
+    eslint-config-prettier: ^8.8.0
+    eslint-plugin-prettier: ^5.0.0
+    express: ^4.19.2
+    fs: ^0.0.1-security
+    graphology-types: ^0.24.7
+    jest: ^29.2.0
+    npm-run-all: ^4.1.5
+    prettier: ^3.0.0
+    react: ^18.3.1
+    react-dom: ^18.3.1
+    reagraph: ^4.19.2
+    rimraf: ^5.0.1
+    source-map-loader: ^1.0.2
+    style-loader: ^3.3.1
+    stylelint: ^15.10.1
+    stylelint-config-recommended: ^13.0.0
+    stylelint-config-standard: ^34.0.0
+    stylelint-csstree-validator: ^3.0.0
+    stylelint-prettier: ^4.0.0
+    three: ^0.166.1
+    types: ^0.1.1
+    typescript: ^5.5.3
+    webpack: ^5.93.0
+    yjs: ^13.5.0
+  languageName: unknown
+  linkType: soft
+
 "co@npm:^4.6.0":
   version: 4.6.0
   resolution: "co@npm:4.6.0"
@@ -8715,60 +8769,6 @@ __metadata:
   languageName: node
   linkType: hard
 
-"jupyterlab_apod@workspace:.":
-  version: 0.0.0-use.local
-  resolution: "jupyterlab_apod@workspace:."
-  dependencies:
-    "@codemirror/lang-python": ^6.1.6
-    "@jupyterlab/application": ^4.2.1
-    "@jupyterlab/apputils": ^4.3.1
-    "@jupyterlab/builder": ^4.0.0
-    "@jupyterlab/launcher": ^4.2.3
-    "@jupyterlab/launcher\n": ^4.2.3
-    "@jupyterlab/testutils": ^4.0.0
-    "@lumino/widgets": ^2.3.2
-    "@types/cytoscape": ^3.21.4
-    "@types/d3": ^7.4.3
-    "@types/jest": ^29.2.0
-    "@types/json-schema": ^7.0.11
-    "@types/react": ^18.3.3
-    "@types/react-addons-linked-state-mixin": ^0.14.22
-    "@types/react-dom": ^18.3.0
-    "@types/three": ^0.166.0
-    "@typescript-eslint/eslint-plugin": ^6.1.0
-    "@typescript-eslint/parser": ^6.1.0
-    codemirror: ^6.0.1
-    css-loader: ^6.7.1
-    cytoscape: ^3.30.0
-    d3: ^7.9.0
-    eslint: ^8.36.0
-    eslint-config-prettier: ^8.8.0
-    eslint-plugin-prettier: ^5.0.0
-    express: ^4.19.2
-    fs: ^0.0.1-security
-    graphology-types: ^0.24.7
-    jest: ^29.2.0
-    npm-run-all: ^4.1.5
-    prettier: ^3.0.0
-    react: ^18.3.1
-    react-dom: ^18.3.1
-    reagraph: ^4.19.2
-    rimraf: ^5.0.1
-    source-map-loader: ^1.0.2
-    style-loader: ^3.3.1
-    stylelint: ^15.10.1
-    stylelint-config-recommended: ^13.0.0
-    stylelint-config-standard: ^34.0.0
-    stylelint-csstree-validator: ^3.0.0
-    stylelint-prettier: ^4.0.0
-    three: ^0.166.1
-    types: ^0.1.1
-    typescript: ^5.5.3
-    webpack: ^5.93.0
-    yjs: ^13.5.0
-  languageName: unknown
-  linkType: soft
-
 "keyv@npm:^4.5.3":
   version: 4.5.4
   resolution: "keyv@npm:4.5.4"

From 0a4158cc925e758398af4c8d8c598a7a74eaa182 Mon Sep 17 00:00:00 2001
From: RasanYo <rasanhy@gmail.com>
Date: Thu, 22 Aug 2024 14:18:05 +0200
Subject: [PATCH 3/3] added usernames and changed title-generation prompt

---
 src/backend/Clusterers/title_generator.py   |   2 +-
 src/backend/cli/main_methods.py             |   3 +-
 src/backend/utils/create_test_dataset.ipynb | 199 ++++++++++++++++++--
 src/backend/utils/helper_functions.py       |   2 +-
 4 files changed, 189 insertions(+), 17 deletions(-)

diff --git a/src/backend/Clusterers/title_generator.py b/src/backend/Clusterers/title_generator.py
index 870399d..ca5590a 100644
--- a/src/backend/Clusterers/title_generator.py
+++ b/src/backend/Clusterers/title_generator.py
@@ -9,7 +9,7 @@ class TitleGenerator:
     def __init__(self, api_key: str = None):
         self.client = OpenAI()
         prompt = """You are given a set of descriptions for multiple code snippets of the a same cluster. 
-        Generate a title for the cluster based on the descriptions, in 6 words maximum. Mention explicitly the name of the technologies and methods used.
+        Generate a title for the cluster based on the descriptions, in 6 words maximum. Mention only explicitly the name of the technologies used.
         Desired format:
         Title: <generated_title>"""
         self.messages = [
diff --git a/src/backend/cli/main_methods.py b/src/backend/cli/main_methods.py
index e993011..9c69b5c 100644
--- a/src/backend/cli/main_methods.py
+++ b/src/backend/cli/main_methods.py
@@ -52,7 +52,8 @@ def classify_notebooks(notebook_jsons: list[dict], file_names: list[str]) -> dic
             notebook = {}
             notebook["cells"] = sorted(classified_cells, key=lambda x: (x['class'], x['cell_id']))
             notebook["notebook_id"] = notebook_id
-            notebook["notebook_name"] = file_names[notebook_id]
+            notebook["notebook_name"] = file_names[notebook_id].split('_')[-1]
+            notebook["user"] = file_names[notebook_id].split('_')[0]
             final_json['notebooks'].append(notebook)
             
     return final_json
diff --git a/src/backend/utils/create_test_dataset.ipynb b/src/backend/utils/create_test_dataset.ipynb
index 677b7ab..5501d7b 100644
--- a/src/backend/utils/create_test_dataset.ipynb
+++ b/src/backend/utils/create_test_dataset.ipynb
@@ -1301,30 +1301,201 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "725"
+       "'/mohamedmostafa335/nlp-tokenization-embedding-lstm'"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "distinct_kernel_links = kernels['kernel_link'].unique()\n",
-    "len(distinct_kernel_links)"
+    "distinct_kernel_links[5]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>kernel_id</th>\n",
+       "      <th>code_block_id</th>\n",
+       "      <th>code_block</th>\n",
+       "      <th>kernel_link</th>\n",
+       "      <th>predicted_graph_vertex__probability</th>\n",
+       "      <th>graph_vertex_id</th>\n",
+       "      <th>graph_vertex_class</th>\n",
+       "      <th>graph_vertex_subclass</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>43</th>\n",
+       "      <td>22956883</td>\n",
+       "      <td>0</td>\n",
+       "      <td>import numpy as np\\nimport pandas as pd\\nfrom ...</td>\n",
+       "      <td>/renraeldab/disaster-tweets</td>\n",
+       "      <td>0.999302</td>\n",
+       "      <td>22</td>\n",
+       "      <td>Imports_and_Environment</td>\n",
+       "      <td>import_modules</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>44</th>\n",
+       "      <td>22956883</td>\n",
+       "      <td>1</td>\n",
+       "      <td>train = pd.read_csv('/kaggle/input/nlp-getting...</td>\n",
+       "      <td>/renraeldab/disaster-tweets</td>\n",
+       "      <td>0.999751</td>\n",
+       "      <td>45</td>\n",
+       "      <td>Data_Extraction</td>\n",
+       "      <td>load_from_csv</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>45</th>\n",
+       "      <td>22956883</td>\n",
+       "      <td>2</td>\n",
+       "      <td>def filter_text(df):\\n    df['text']=df['text'...</td>\n",
+       "      <td>/renraeldab/disaster-tweets</td>\n",
+       "      <td>0.995599</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Data_Transform</td>\n",
+       "      <td>feature_engineering</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>46</th>\n",
+       "      <td>22956883</td>\n",
+       "      <td>3</td>\n",
+       "      <td>sw=['the', 'a', 'an', 'in', 'on', 'with', 'by'...</td>\n",
+       "      <td>/renraeldab/disaster-tweets</td>\n",
+       "      <td>0.997215</td>\n",
+       "      <td>77</td>\n",
+       "      <td>Exploratory_Data_Analysis</td>\n",
+       "      <td>define_variables</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>47</th>\n",
+       "      <td>22956883</td>\n",
+       "      <td>4</td>\n",
+       "      <td>v = CountVectorizer(stop_words=sw)\\ntrain_v = ...</td>\n",
+       "      <td>/renraeldab/disaster-tweets</td>\n",
+       "      <td>0.997267</td>\n",
+       "      <td>8</td>\n",
+       "      <td>Data_Transform</td>\n",
+       "      <td>feature_engineering</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>48</th>\n",
+       "      <td>22956883</td>\n",
+       "      <td>5</td>\n",
+       "      <td>y = train['target']</td>\n",
+       "      <td>/renraeldab/disaster-tweets</td>\n",
+       "      <td>0.999064</td>\n",
+       "      <td>21</td>\n",
+       "      <td>Data_Transform</td>\n",
+       "      <td>prepare_x_and_y</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>49</th>\n",
+       "      <td>22956883</td>\n",
+       "      <td>6</td>\n",
+       "      <td>clf = MultinomialNB()\\nscorer = make_scorer(f1...</td>\n",
+       "      <td>/renraeldab/disaster-tweets</td>\n",
+       "      <td>0.983758</td>\n",
+       "      <td>6</td>\n",
+       "      <td>Model_Train</td>\n",
+       "      <td>train_on_grid</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50</th>\n",
+       "      <td>22956883</td>\n",
+       "      <td>7</td>\n",
+       "      <td>y = model.predict(test_v)\\noutput = pd.DataFra...</td>\n",
+       "      <td>/renraeldab/disaster-tweets</td>\n",
+       "      <td>0.999141</td>\n",
+       "      <td>25</td>\n",
+       "      <td>Data_Export</td>\n",
+       "      <td>save_to_csv</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    kernel_id  code_block_id  \\\n",
+       "43   22956883              0   \n",
+       "44   22956883              1   \n",
+       "45   22956883              2   \n",
+       "46   22956883              3   \n",
+       "47   22956883              4   \n",
+       "48   22956883              5   \n",
+       "49   22956883              6   \n",
+       "50   22956883              7   \n",
+       "\n",
+       "                                           code_block  \\\n",
+       "43  import numpy as np\\nimport pandas as pd\\nfrom ...   \n",
+       "44  train = pd.read_csv('/kaggle/input/nlp-getting...   \n",
+       "45  def filter_text(df):\\n    df['text']=df['text'...   \n",
+       "46  sw=['the', 'a', 'an', 'in', 'on', 'with', 'by'...   \n",
+       "47  v = CountVectorizer(stop_words=sw)\\ntrain_v = ...   \n",
+       "48                                y = train['target']   \n",
+       "49  clf = MultinomialNB()\\nscorer = make_scorer(f1...   \n",
+       "50  y = model.predict(test_v)\\noutput = pd.DataFra...   \n",
+       "\n",
+       "                    kernel_link  predicted_graph_vertex__probability  \\\n",
+       "43  /renraeldab/disaster-tweets                             0.999302   \n",
+       "44  /renraeldab/disaster-tweets                             0.999751   \n",
+       "45  /renraeldab/disaster-tweets                             0.995599   \n",
+       "46  /renraeldab/disaster-tweets                             0.997215   \n",
+       "47  /renraeldab/disaster-tweets                             0.997267   \n",
+       "48  /renraeldab/disaster-tweets                             0.999064   \n",
+       "49  /renraeldab/disaster-tweets                             0.983758   \n",
+       "50  /renraeldab/disaster-tweets                             0.999141   \n",
+       "\n",
+       "    graph_vertex_id         graph_vertex_class graph_vertex_subclass  \n",
+       "43               22    Imports_and_Environment        import_modules  \n",
+       "44               45            Data_Extraction         load_from_csv  \n",
+       "45                8             Data_Transform   feature_engineering  \n",
+       "46               77  Exploratory_Data_Analysis      define_variables  \n",
+       "47                8             Data_Transform   feature_engineering  \n",
+       "48               21             Data_Transform       prepare_x_and_y  \n",
+       "49                6                Model_Train         train_on_grid  \n",
+       "50               25                Data_Export           save_to_csv  "
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "filtered_df = merged_df[merged_df['kernel_link'] == distinct_kernel_links[3]].sort_values('code_block_id', ascending=True)\n",
     "filtered_df"
@@ -1349,14 +1520,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      " 27%|██▋       | 8/30 [00:05<00:10,  2.08it/s]"
+      " 27%|██▋       | 8/30 [00:04<00:10,  2.03it/s]"
      ]
     },
     {
@@ -1370,7 +1541,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      " 50%|█████     | 15/30 [00:09<00:06,  2.33it/s]"
+      " 50%|█████     | 15/30 [00:08<00:06,  2.27it/s]"
      ]
     },
     {
@@ -1384,14 +1555,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 30/30 [00:18<00:00,  1.62it/s]"
+      "100%|██████████| 30/30 [00:17<00:00,  1.71it/s]"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Saved 28 notebooks to /home/ryounis/Documents/Zurich/PEACHLab/datascience-visualisation/src/backend/data/datasets/Natural Language Processing with Disaster Tweets/unclassified\n"
+      "Saved 28 notebooks to /home/ryounis/Documents/Zurich/PEACHLab/datascience-visualisation/data/datasets/Natural Language Processing with Disaster Tweets/unclassified\n"
      ]
     },
     {
@@ -1412,8 +1583,7 @@
     "import tempfile \n",
     "from kaggle.api.kaggle_api_extended import ApiException\n",
     "from tqdm import tqdm\n",
-    "\n",
-    "test_dataset_dir = f\"datascience-visualisation/data/datasets/{top_comp}/unclassified\"\n",
+    "test_dataset_dir = f\"/home/ryounis/Documents/Zurich/PEACHLab/datascience-visualisation/data/datasets/{top_comp}/unclassified\"\n",
     "if not os.path.exists(test_dataset_dir): os.makedirs(test_dataset_dir)\n",
     "\n",
     "FIRST_N_KERNELS = 30\n",
@@ -1446,7 +1616,8 @@
     "            }    \n",
     "    notebook[\"metadata\"][\"labels\"] = LABELS\n",
     "    notebooks.append(notebook)\n",
-    "    with open(f\"{test_dataset_dir}/{kernel_link.split('/')[-1]}.ipynb\", \"w\") as f:json.dump(notebook, f)\n",
+    "    filename = \"_\".join(kernel_link.split('/')[1:])\n",
+    "    with open(f\"{test_dataset_dir}/{filename}.ipynb\", \"w\") as f:json.dump(notebook, f)\n",
     "    \n",
     "print(f\"Saved {len(notebooks)} notebooks to {test_dataset_dir}\")"
    ]
diff --git a/src/backend/utils/helper_functions.py b/src/backend/utils/helper_functions.py
index 0b450b8..f4b38f4 100644
--- a/src/backend/utils/helper_functions.py
+++ b/src/backend/utils/helper_functions.py
@@ -35,7 +35,7 @@ def load_notebooks(notebooks_dir: str, verbose: bool = False) -> tuple[List[dict
     for file in tqdm(files, desc="Reading file contents"):
         file_path = os.path.join(notebooks_dir, file)
         
-        if os.path.isfile(file_path) and file.endswith(".ipynb"):
+        if os.path.isfile(file_path) and file.endswith(".ipynb") and len(file.split("_")) == 2:
             notebook_json = load_notebook(file_path)
             if len([cell for cell in notebook_json['cells'] if cell['cell_type'] == 'code']) >= 15:
                 notebook_jsons.append(notebook_json)