Create app.py

app.py

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+import streamlit as st
+import pickle
+import pandas as pd
+
+                                        ## To Add External CSS ##
+with open('css/style.css') as f:
+     st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)
+
+
+
+
+                                        ## Application Backend ##
+
+                    # To load medicine-dataframe from pickle in the form of dictionary
+medicines_dict = pickle.load(open('medicine_dict.pkl','rb'))
+medicines = pd.DataFrame(medicines_dict)
+
+                    # To load similarity-vector-data from pickle in the form of dictionary
+similarity = pickle.load(open('similarity.pkl','rb'))
+
+def recommend(medicine):
+     medicine_index = medicines[medicines['Drug_Name'] == medicine].index[0]
+     distances = similarity[medicine_index]
+     medicines_list = sorted(list(enumerate(distances)), reverse=True, key=lambda x: x[1])[1:6]
+
+     recommended_medicines = []
+     for i in medicines_list:
+         recommended_medicines.append(medicines.iloc[i[0]].Drug_Name)
+     return recommended_medicines
+
+
+
+
+
+                                    ## Appliaction Frontend ##
+
+                                   # Title of the Application
+st.title('Medicine Recommender System')
+
+
+
+                                        # Searchbox
+selected_medicine_name = st.selectbox(
+'Type your medicine name whose alternative is to be recommended',
+     medicines['Drug_Name'].values)
+
+
+                                   # Recommendation Program
+if st.button('Recommend Medicine'):
+     recommendations = recommend(selected_medicine_name)
+     j=1
+     for i in recommendations:
+          st.write(j,i)                      # Recommended-drug-name
+
+
+
+
+
+                                         ## Image load ##
+from PIL import Image
+#image = Image.open('images/medicine-image.jpg')
+#st.image(image, caption='Recommended Medicines')
+
+