Code update

app.py

@@ -12,6 +12,18 @@ import amrlib
 from amrlib.graph_processing.annotator import add_lemmas
 from amrlib.alignments.rbw_aligner import RBWAligner
 
+@st.cache_resource
+def load_easynmt():
+    return EasyNMT('opus-mt')
+
+@st.cache_resource
+def load_stog_model():
+    return amrlib.load_stog_model(model_dir='model_stog')
+
+@st.cache_resource
+def load_gtos_model():
+    return amrlib.load_gtos_model(model_dir='model_gtos')
+
 # Find a node corresponding targetWord in the graph:
 def getTargetWordNode(segmentTokens, aligner, alignments, target):
     # Get target word in English:
@@ -102,15 +114,6 @@ def getTargetWordSubGraphFullPath(amrGraph, target):
 def main():
     st.header('Abstract Meaning Representation based summary of French text', divider='blue')
     
-    #segmentFr = st.text_area(
-    #"Text to summarize:",
-    #"Article 1 : Occupations ou utilisations du sol interdites\n\n"
-    #"1) Dans l’ensemble de la zone sont interdits :\n\n"
-    #"Les pylônes et poteaux, supports d’enseignes et d’antennes d’émission ou de réception de \n"
-    #"signaux radioélectriques.",
-    #height=170,
-    #)#.replace('\n',' ')
-    
     segmentFr = st.text_area(
     "Text to summarize:",
     "Article 2 : Occupations ou utilisations du sol soumises à des conditions particulières\n\n"
@@ -127,28 +130,21 @@ def main():
     #height=170,
     #)
     
-    #targetWord = st.text_input('Keyword:', 'Occupations')
     targetWord = st.text_input('Keyword:', 'clôtures')
     ##targetWord = st.text_input('Keyword:', 'compromettre')
     
     if st.button('Summarize'):
         # Fix input formatting:
         segmentFr = segmentFr.replace('\n',' ')
-        
-        #st.code(segmentFr)
-        
+                
         # Translate segment into English:
-        model = EasyNMT('opus-mt')
-        #segmentEn = model.translate(segmentFr.lower() , source_lang='fr', target_lang='en')
+        model = load_easynmt()
         segmentEn = model.translate(segmentFr , source_lang='fr', target_lang='en')
         
         # Get an AMR graph:
-        stog = amrlib.load_stog_model(model_dir='model_stog')
+        stog = load_stog_model()
         inputGraph = stog.parse_sents([segmentEn])
         
-        ## Output the resulting graph:
-        #print(inputGraph[0])
-        
         # Get tokenized representation of segment in French:
         segmentFrTokens = word_tokenize(segmentFr, language='french')
         
@@ -178,10 +174,9 @@ def main():
         if not errorFlag:
             if targetNode != 'Error!':
                 targetSubGraph = getTargetWordSubGraphFullPath(inputGraph[0], targetNode)
-                #print(targetSubGraph)
                 
                 # Generate text from given AMR-graph:
-                gtos = amrlib.load_gtos_model(model_dir='model_gtos')
+                gtos = load_gtos_model()
                 rulesEn, _ = gtos.generate([targetSubGraph])
                 
                 # Remove "1." from the text:
@@ -189,15 +184,11 @@ def main():
                 
                 # Translate it back to French
                 rulesFr = model.translate(rulesEn[0], source_lang='en', target_lang='fr')
-                #print(rulesEn[0])
-                #print(rulesFr)
         
                 st.write("Summary: ", rulesFr)
             else:
-                #print('Alignment between target word in French and its English instance not found')
                 st.write('Error! Alignment between target word in French and its English instance not found')
         else:
-            #print('Error! Cannot find keyword in the graph')
             st.write('Error! Cannot find keyword in the graph')
     
 if __name__ == "__main__":