diff --git a/src/Class_Mod/RegModels.py b/src/Class_Mod/RegModels.py
index ba81e1ed0c6ad1098ba196593f9a95c860645ad6..18ce604d7737a8bffa14426eafd1bfe1160946b0 100644
--- a/src/Class_Mod/RegModels.py
+++ b/src/Class_Mod/RegModels.py
@@ -4,7 +4,7 @@ from Class_Mod import metrics, Snv, No_transformation, KF_CV
 
 class Regmodel(object):
     
-    def __init__(self, train : [pd.DataFrame, pd.DataFrame], test : [pd.DataFrame, pd.DataFrame], n_iter, add_hyperparams = None, nfolds = 5, **kwargs):
+    def __init__(self, train, test, n_iter, add_hyperparams = None, nfolds = 5, **kwargs):
         self.SCORE = 100000000
         self._xc, self._xt, self._ytrain, self._ytest = train[0], test[0], train[1], test[1]
         self._nc, self._nt, self._p = train[0].shape[0], test[0].shape[0], train[0].shape[1]
@@ -60,7 +60,7 @@ class Regmodel(object):
         elif self._best['scatter'] == 'No_transformation':
             a = " No transformation was performed"
 
-        SG = f'- Savitzky-Golay derivative parameters (Window_length:{self._best['window_length']};  polynomial order: {self._best['polyorder']};  Derivative order : {self._best['deriv']})'
+        SG = f'- Savitzky-Golay derivative parameters \:(Window_length:{self._best['window_length']};  polynomial order: {self._best['polyorder']};  Derivative order : {self._best['deriv']})'
         Norm = f'- Spectral Normalization \: {a}'
         return SG+"\n"+Norm
     
@@ -88,7 +88,7 @@ class Regmodel(object):
   
 ###########################################    #########################################
 class Plsr(Regmodel):
-    def __init__(self, train: [pd.DataFrame, pd.DataFrame], test: [pd.DataFrame, pd.DataFrame], n_iter = 10):
+    def __init__(self, train, test, n_iter = 10):
         super().__init__(train, test, n_iter, add_hyperparams = {'n_components': hp.randint('n_components', 2,20)})
         ### parameters in common
         
@@ -132,7 +132,7 @@ class Plsr(Regmodel):
 
     ############################################    #########################################
 class TpeIpls(Regmodel):
-    def __init__(self, train: [pd.DataFrame, pd.DataFrame], test: [pd.DataFrame, pd.DataFrame], n_iter = 10, n_intervall = 5):
+    def __init__(self, train, test, n_iter = 10, n_intervall = 5):
         self.n_intervall = n_intervall
         self.n_arrets = self.n_intervall*2
         
@@ -204,6 +204,6 @@ class TpeIpls(Regmodel):
     ############################################    #########################################
 
 class Pcr(Regmodel):
-    def __init__(self, train: [pd.DataFrame, pd.DataFrame], test: [pd.DataFrame, pd.DataFrame], n_iter = 10, n_val = 5):
+    def __init__(self, train, test, n_iter = 10, n_val = 5):
         super.__init__()
         {f'pc{i}': hp.randint(f'pc{i+1}', 0, train[0].shape[1]) for i in range(self.n_val)}
\ No newline at end of file
diff --git a/src/Report/figures/Allinone.png b/src/Report/figures/Allinone.png
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diff --git a/src/Report/figures/plot_axe2_axe3.png b/src/Report/figures/plot_axe2_axe3.png
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diff --git a/src/Report/figures/test.png b/src/Report/figures/test.png
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diff --git a/src/Report/report.log b/src/Report/report.log
new file mode 100644
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+++ b/src/Report/report.log
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diff --git a/src/Report/report.py b/src/Report/report.py
index 685e6795cfe5b808bed9e65511539972abbc29ee..ddd647e9880b42ac6e9e4fe640bdbe7b0f3d0bc2 100644
--- a/src/Report/report.py
+++ b/src/Report/report.py
@@ -65,7 +65,7 @@ def report(*args):
         """
 
     if 'model' in to_report:
-        latex_report += r"""\subsection*{Data Visualization}
+        latex_report += r"""\subsection{Data Visualization}
 
         Here we have a sub-heading. There is no blank line after the sub-heading. You can have one level of subheadings but not a third i.e. you cannot have Section 1.1.1 as a subheading.
         \begin{center}
@@ -424,6 +424,7 @@ def report(*args):
 
 def compile_latex():
     # path to pdflatex
+    pdflatex_path = Path("C:/Users/diane/AppData/Local/Programs/MiKTeX/miktex/bin/x64/")
     # pdflatex_path = Path("C:/Users/maimouni/AppData/Local/Programs/MiKTeX/miktex/bin/x64/")
     from config.config import pdflatex_path
     import os
diff --git a/src/data/models/model_didi_2024_06_04__created_on_Xcal_and_Ycal_data_.pkl b/src/data/models/model_didi_2024_06_04__created_on_Xcal_and_Ycal_data_.pkl
new file mode 100644
index 0000000000000000000000000000000000000000..bc65db0cacb1abb7f3c909b2355a5077cb7f1724
Binary files /dev/null and b/src/data/models/model_didi_2024_06_04__created_on_Xcal_and_Ycal_data_.pkl differ
diff --git a/src/pages/2-model_creation.py b/src/pages/2-model_creation.py
index f0cc4eada5460efeb1a409f58e9762417c0d99a7..49a680f7e8a4ff4075f00271a5b7e23ab050bb15 100644
--- a/src/pages/2-model_creation.py
+++ b/src/pages/2-model_creation.py
@@ -14,7 +14,7 @@ import matplotlib.pyplot as plt, mpld3
 import streamlit.components.v1 as components
 
 repertoire_a_vider = 'D:/Mouhcine/nirs_workflow/src/Report/figures'
-
+import shutil
 if os.path.exists(repertoire_a_vider):
     for fichier in os.listdir(repertoire_a_vider):
         chemin_fichier = os.path.join(repertoire_a_vider, fichier)
@@ -48,7 +48,7 @@ st.header("I - Data visualization", divider='blue')
 M0, M00 = st.columns([1, .4])
 st.header("II - Model creation", divider='blue')
 M1, M2 = st.columns([2 ,4])
-st.header("Cross-Validation")
+st.header("Cross-Validation results")
 cv1, cv2 = st.columns([2,2])
 cv3 = st.container()
 
@@ -344,8 +344,7 @@ if not spectra.empty and not y.empty:
 ##########
         M1.write("-- Model performance --")
         M1.dataframe(metrics(c = [y_train, yc], t = [y_test, yt], method='regression').scores_)
-        M2.write("-- Model performance --")
-        M2.dataframe(metrics(c = [y_train, yc], t = [y_test, yt], method='regression').scores_)
+
         model_per=pd.DataFrame(metrics(c = [y_train, yc], t = [y_test, yt], method='regression').scores_)
         #from st_circular_progress import CircularProgress
         #my_circular_progress = CircularProgress(label = 'Performance',value = 50, key = 'my performance',
@@ -362,7 +361,7 @@ if not spectra.empty and not y.empty:
         M8.pyplot(residual_plot)
         plt.savefig('./Report/figures/residual_plot.png')
 
-        # rega = Reg.important_features_  ##### ADD FEATURES IMPORTANCE PLOT
+        rega = Reg.important_features_  ##### ADD FEATURES IMPORTANCE PLOT
             
             #model_export = M1.selectbox("Choose way to export", options=["pickle", "joblib"], key=20)
         model_name = M9.text_input('Give it a name')
@@ -411,8 +410,7 @@ if not spectra.empty and not y.empty:
 ## Load .dx file
 Ac_Km = ['histo.png', 'Spectre_mod.png','Predictions_V.png','Allinone.png','Predictedvs.png','residual_plot.png']
 with st.container():
-    header3, header4 = st.columns(2)
-    if header3.button("Exporter le RR"):
+    if st.button("Download the report"):
         if regression_algo == reg_algo[1]:
                 latex_report = report.report(LoDaSum, 'model',Ac_Km,a_Test,json_sp,model_per,'full_plsr',cv99)
                 report.compile_latex()