Update app.py

app.py

@@ -35,6 +35,19 @@ model = LLaMAForCausalLM.from_pretrained(
 )
 '''
 
+########## LOADING PRE-COMPUTED EMBEDDINGS ##########
+class_embeddings = pd.read_csv('Embeddings/MainClassEmbeddings.csv')
+
+abstract = """
+#Described herein are strength characteristics and biodegradation of articles produced using one or more “green” sustainable polymers and one or more carbohydrate-based polymers. A compatibilizer can optionally be included in the article. In some cases, the article can include a film, a bag, a bottle, a cap or lid therefore, a sheet, a box or other container, a plate, a cup, utensils, or the like.
+"""
+
+abstract= classification.clean_data(abstract, type='String')
+abstract_embedding = classification.sentence_embedder(abstract, Model_Path)
+Number = 10
+broad_scope_predictions = classification.broad_scope_class_predictor(class_embeddings, abstract_embedding, Number, Sensitivity='High')
+
+print(broad_scope_class_predictor)
 
 def generateresponse(history):
     """
@@ -211,19 +224,6 @@ with gr.Blocks(title='Claimed', theme=theme) as demo:
     
     """)
 
-"""
-########## LOADING PRE-COMPUTED EMBEDDINGS ##########
-class_embeddings = pd.read_csv('Embeddings/MainClassEmbeddings.csv')
-
-abstract = """
-#Described herein are strength characteristics and biodegradation of articles produced using one or more “green” sustainable polymers and one or more carbohydrate-based polymers. A compatibilizer can optionally be included in the article. In some cases, the article can include a film, a bag, a bottle, a cap or lid therefore, a sheet, a box or other container, a plate, a cup, utensils, or the like.
-"""
-abstract= clean_data(abstract, type='String')
-abstract_embedding = sentence_embedder(abstract, Model_Path)
-Number = 10
-broad_scope_predictions = broad_scope_class_predictor(class_embeddings, abstract_embedding, Number, Sensitivity='High')
 
-print(broad_scope_class_predictor)
-"""
 
 demo.launch()