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| import streamlit as st | |
| import pandas as pd | |
| import numpy as np | |
| from PIL import Image | |
| import matplotlib.pyplot as plt | |
| import glob | |
| from scipy.sparse import csr_matrix | |
| from sklearn.neighbors import NearestNeighbors | |
| import pickle | |
| import io | |
| import streamlit.components.v1 as stc | |
| def main(): | |
| st.set_page_config(layout="wide", initial_sidebar_state='expanded') | |
| st.image("images/logo-recom2.png", width=100) | |
| with open('style.css') as f: | |
| st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True) | |
| hide_menu = """ | |
| <style> | |
| #MainMenu { | |
| visibility:visible; | |
| } | |
| footer{ | |
| visibility:visible; | |
| } | |
| footer:after { | |
| content: 'Recom © 2022 - Doris BAILLARD'; | |
| display: block; | |
| position: relative; | |
| color:blue; | |
| } | |
| </style> | |
| """ | |
| st.markdown(hide_menu, unsafe_allow_html=True) | |
| sidebar_header = '''This is a demo of Recom solution version 1.0.0. This demo gathers the main options. Please give it a try :''' | |
| page_options = ["Recommendations base on reviews", | |
| "Recommendations based on product similarity", | |
| "Generate email"] | |
| st.sidebar.info(sidebar_header) | |
| page_selection = st.sidebar.radio("Try", page_options) | |
| ######################################################################################### | |
| if page_selection == "Recommendations base on reviews": | |
| pid_to_idx = pd.read_pickle("data/pid_to_idx.pkl") | |
| idx_to_pid = pd.read_pickle("data/idx_to_pid.pkl") | |
| products = pd.read_pickle("data/products.pkl") | |
| lightfm_similarity = pd.read_pickle("data/lightfm-similarity.pkl") | |
| items_pivot=pd.read_pickle("data/items_pivot.pkl") | |
| items_sparse = csr_matrix(items_pivot) | |
| model = NearestNeighbors(algorithm="brute") | |
| model.fit(items_sparse) | |
| def get_product_name(pid, product): | |
| try: | |
| name = products.loc[products.product_ids == pid].titles.values[0] | |
| except: | |
| name = "Unknown" | |
| return name | |
| def get_product_id(name): | |
| try: | |
| product_id = products.loc[products.titles == name].product_ids.values[0] | |
| except: | |
| product_id = "Unknown" | |
| return product_id | |
| def get_sim_scores(pid): | |
| idx = pid_to_idx[pid] | |
| sims = lightfm_similarity[idx] | |
| return sims | |
| def get_ranked_recos(sims): | |
| recos = [] | |
| for idx in np.argsort(-sims): | |
| pid = idx_to_pid[idx] | |
| name = get_product_name(pid, products) | |
| score = sims[idx] | |
| recos.append((name,pid)) | |
| return recos | |
| st.markdown('<p style="color:darkblue;font-size:160%">Products Recommender System</p>', unsafe_allow_html=True) | |
| st.markdown('This option will allow you to publish on your site recommendations of products "appreciated by other customers". These recommendations are based on the reviews of other customers. ') | |
| product_list = products['titles'].values | |
| selected_product = st.selectbox( | |
| "Type or select a product from the dropdown", | |
| product_list | |
| ) | |
| product_id = get_product_id(selected_product) | |
| sims = get_sim_scores(product_id) | |
| result = get_ranked_recos(sims)[:5] | |
| recommendation_button = st.button('Show Recommendation') | |
| if recommendation_button: | |
| product_id = get_product_id(selected_product) | |
| sims = get_sim_scores(product_id) | |
| result = get_ranked_recos(sims)[:5] | |
| with st.form("reco1"): | |
| cols = st.columns((1, 3)) | |
| cols[0].image('images/'+result[0][1]+'.jpg', width=200) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID: </p>', unsafe_allow_html=True) | |
| cols[1].markdown(result[0]) | |
| cols[1].markdown("Url : yoursiteurl") | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| with cols[1]: | |
| submitted = st.form_submit_button('Deploy') | |
| submitted_all = st.form_submit_button('Deploy All') | |
| with st.form("reco2"): | |
| cols2 = st.columns((1, 3)) | |
| cols2[0].image('images/'+result[1][1]+'.jpg', width=200) | |
| cols2[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID:</p>', unsafe_allow_html=True) | |
| cols2[1].text(result[1]) | |
| cols2[1].markdown("Url : yoursiteurl") | |
| cols2[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols2[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols2[1].form_submit_button('Deploy') | |
| cols2[1].form_submit_button('Deploy All') | |
| with st.form("reco3"): | |
| cols3= st.columns((1, 3)) | |
| cols3[0].image('images/'+result[2][1]+'.jpg', width=200) | |
| cols3[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID:</p>', unsafe_allow_html=True) | |
| cols3[1].text(result[2]) | |
| cols3[1].markdown("Url : yoursiteurl") | |
| cols3[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols3[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols3[1].form_submit_button('Deploy') | |
| cols3[1].form_submit_button('Deploy All') | |
| with st.form("reco4"): | |
| cols4 = st.columns((1, 3)) | |
| cols4[0].image('images/'+result[3][1]+'.jpg', width=200) | |
| cols4[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID:</p>', unsafe_allow_html=True) | |
| cols4[1].text(result[3]) | |
| cols4[1].markdown("Url : yoursiteurl") | |
| cols4[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols4[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols4[1].form_submit_button('Deploy') | |
| cols4[1].form_submit_button('Deploy All') | |
| with st.form("reco5"): | |
| cols5 = st.columns((1, 3)) | |
| cols5[0].image('images/'+result[4][1]+'.jpg', width=200) | |
| cols5[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID:</p>', unsafe_allow_html=True) | |
| cols5[1].text(result[4]) | |
| cols5[1].markdown("Url : yoursiteurl") | |
| cols5[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols5[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols5[1].form_submit_button('Deploy') | |
| cols5[1].form_submit_button('Deploy All') | |
| st.markdown("<hr/>", unsafe_allow_html=True) | |
| st.success("Successfuly Deployed !") | |
| st.success("output 'Deploy' :") | |
| st.write("Clients also liked : ") | |
| st.image('images/'+result[4][1]+'.jpg', width=150) | |
| st.markdown(result[0][0]) | |
| st.markdown("<hr/>", unsafe_allow_html=True) | |
| st.success("Successfuly Deployed !") | |
| st.success("output 'Deploy All' :") | |
| st.write("Clients also liked : ") | |
| cols_deploy = st.columns(5) | |
| cols_deploy[0].image('images/'+result[0][1]+'.jpg', width=150) | |
| cols_deploy[0].markdown(result[0][0]) | |
| cols_deploy[1].image('images/'+result[1][1]+'.jpg', width=150) | |
| cols_deploy[1].markdown(result[1][0]) | |
| cols_deploy[2].image('images/'+result[2][1]+'.jpg', width=150) | |
| cols_deploy[2].markdown(result[2][0]) | |
| cols_deploy[3].image('images/'+result[3][1]+'.jpg', width=150) | |
| cols_deploy[3].markdown(result[3][0]) | |
| cols_deploy[4].image('images/'+result[4][1]+'.jpg', width=150) | |
| cols_deploy[4].markdown(result[4][0]) | |
| ######################################################################################### | |
| if page_selection == "Recommendations based on product similarity": | |
| products = pd.read_pickle("data/products.pkl") | |
| feature_list = np.array(pickle.load(open('data/embeddings.pkl','rb'))) | |
| filenames = pickle.load(open('data/filenamesdf.pkl','rb')) | |
| def recommend(features,feature_list): | |
| neighbors = NearestNeighbors(n_neighbors=6, algorithm='brute', metric='euclidean') | |
| neighbors.fit(feature_list) | |
| distances, indices = neighbors.kneighbors([features]) | |
| return indices | |
| def reco2(indices): | |
| for i in range(len(indices)): | |
| cols = st.columns((1, 3)) | |
| cols[1].markdown(filenames.index[indices[i]]) | |
| cols[1].markdown(filenames.titles[indices[i]]) | |
| cols[0].image(filenames.image_path[indices[i]].tolist()) | |
| st.markdown("<p style='color:darkblue;font-size:160%'>Recommender System - image similarity</p>", unsafe_allow_html=True) | |
| st.markdown('This feature will enable you to publish on your site recommendations of "similar products". These recommendations are based on similarities between product images.') | |
| product_list = filenames['titles'].values | |
| selected_product = st.selectbox("Type or select a product from the dropdown",product_list) | |
| if st.button('Recommendation'): | |
| id = np.where(selected_product == product_list) | |
| id2 = int(id[0]) | |
| result= recommend(feature_list[id2],feature_list) | |
| results = list(result) | |
| with st.form("reco1"): | |
| cols = st.columns((1, 3)) | |
| cols[0].image(filenames.image_path[results[0]].tolist()[0], width=200) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID:</p>', unsafe_allow_html=True) | |
| cols[1].markdown(filenames.titles[results[0]].tolist()[0]) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols[1].form_submit_button('Deploy') | |
| with st.form("reco2"): | |
| cols = st.columns((1, 3)) | |
| cols[0].image(filenames.image_path[results[0]].tolist()[1], width=200) | |
| cols[1].markdown('<h4 style="color:#3498db;">Product Name and ID:</h2>', unsafe_allow_html=True) | |
| cols[1].markdown(filenames.titles[results[0]].tolist()[1]) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols[1].form_submit_button('Deploy') | |
| with st.form("reco3"): | |
| cols = st.columns((1, 3)) | |
| cols[0].image(filenames.image_path[results[0]].tolist()[2], width=200) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID:</p>', unsafe_allow_html=True) | |
| cols[1].markdown(filenames.titles[results[0]].tolist()[2]) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols[1].form_submit_button('Deploy') | |
| with st.form("reco4"): | |
| cols = st.columns((1, 3)) | |
| cols[0].image(filenames.image_path[results[0]].tolist()[3], width=200) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID:</p>', unsafe_allow_html=True) | |
| cols[1].markdown(filenames.titles[results[0]].tolist()[3]) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols[1].form_submit_button('Deploy') | |
| with st.form("reco5"): | |
| cols = st.columns((1, 3)) | |
| cols[0].image(filenames.image_path[results[0]].tolist()[4], width=200) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Product Name and ID:</p>', unsafe_allow_html=True) | |
| cols[1].markdown(filenames.titles[results[0]].tolist()[4]) | |
| cols[1].markdown('<p style="color:#3498db;font-size:160%">Description :</p>', unsafe_allow_html=True) | |
| cols[1].text('Lorem ipsum dolor sit amet, consectetur adipiscing elit,\nsed do eiusmod tempor incididunt \nut labore et dolore magna aliqua.\nUt enim ad minim veniam, quis nostrud exercitation ullamco.') | |
| cols[1].form_submit_button('Deploy') | |
| cols[1].form_submit_button('Deploy All') | |
| st.markdown("<hr/>", unsafe_allow_html=True) | |
| st.success("Successfuly Deployed !") | |
| st.success("output 'Deploy' :") | |
| st.write("Similar products : ") | |
| st.image(filenames.image_path[results[0]].tolist()[0], width=150) | |
| st.markdown(filenames.titles[results[0]].tolist()[4]) | |
| st.markdown("<hr/>", unsafe_allow_html=True) | |
| st.success("Successfuly Deployed !") | |
| st.success("output 'Deploy All' :") | |
| st.write("Similar products : ") | |
| cols_deploy = st.columns(5) | |
| cols_deploy[0].image(filenames.image_path[results[0]].tolist()[0], width=150) | |
| cols_deploy[0].markdown(filenames.titles[results[0]].tolist()[0]) | |
| cols_deploy[1].image(filenames.image_path[results[0]].tolist()[1], width=150) | |
| cols_deploy[1].markdown(filenames.titles[results[0]].tolist()[1]) | |
| cols_deploy[2].image(filenames.image_path[results[0]].tolist()[2], width=150) | |
| cols_deploy[2].markdown(filenames.titles[results[0]].tolist()[2]) | |
| cols_deploy[3].image(filenames.image_path[results[0]].tolist()[3], width=150) | |
| cols_deploy[3].markdown(filenames.titles[results[0]].tolist()[3]) | |
| cols_deploy[4].image(filenames.image_path[results[0]].tolist()[4], width=150) | |
| cols_deploy[4].markdown(filenames.titles[results[0]].tolist()[4]) | |
| ######################################################################################### | |
| if page_selection == "Generate email": | |
| user_cart = pd.read_pickle('data/user_cart.pkl') | |
| name_list = user_cart['user_name'].values | |
| feature_list = np.array(pickle.load(open('data/embeddings.pkl','rb'))) | |
| filenames = pickle.load(open('data/filenamesdf.pkl','rb')) | |
| def recommend(features,feature_list): | |
| neighbors = NearestNeighbors(n_neighbors=6, algorithm='brute', metric='euclidean') | |
| neighbors.fit(feature_list) | |
| distances, indices = neighbors.kneighbors([features]) | |
| return indices | |
| def reco2(indices): | |
| for i in range(len(indices)): | |
| cols = st.columns((1, 3)) | |
| cols[1].markdown(filenames.index[indices[i]]) | |
| cols[1].markdown(filenames.titles[indices[i]]) | |
| cols[0].image(filenames.image_path[indices[i]].tolist()) | |
| st.markdown("<p style='color:darkblue;font-size:160%'>Mail Generator</p>", unsafe_allow_html=True) | |
| st.markdown('With this feature you will be able to generate automatic emails to ask for feedback from old and new customers.\nThis email will include a request for feedback on the last product purchased, \nas well as product recommendations.', unsafe_allow_html=True) | |
| selected_user = st.selectbox("Type or select a user from the dropdown",name_list) | |
| if st.button('generate mailing'): | |
| name = np.where(selected_user == user_cart['user_name'].values) | |
| name_id = int(name[0]) | |
| reco_mailing2 = recommend(feature_list[name_id],feature_list) | |
| reco_mailing2 = list(reco_mailing2) | |
| st.markdown('>To: '+ selected_user+'', unsafe_allow_html=True) | |
| st.markdown("<hr/>", unsafe_allow_html=True) | |
| st.markdown("<p style='color:Black;font-size:160%'>Hello "+ selected_user+' :) !</p', unsafe_allow_html=True) | |
| st.markdown('We are constantly striving to improve, and we’d love to hear from you about the following your last command:') | |
| st.markdown('<p style="font-size:120%">Rate your purchased product:</p>', unsafe_allow_html=True) | |
| #[a scale from 1 to 5] | |
| cols= st.columns((3)) | |
| cols[0].empty() | |
| cols[1].markdown(user_cart.titles[name_id]) | |
| cols[1].image(user_cart.image_path[name_id], width=200) | |
| cols[1].markdown(":star::star::star::star::star:") | |
| cols[1].button('Rate this article on company.com') | |
| cols[2].empty() | |
| st.text('\n\n') | |
| st.markdown('Your feedback helps us improve and reach more great customers like you.') | |
| st.text('\n\n') | |
| st.markdown("<hr/>", unsafe_allow_html=True) | |
| st.markdown('<p style="font-size:120%">Discover products in the same category: </p>', unsafe_allow_html=True) | |
| st.text('\n\n') | |
| cols_mail = st.columns((7)) | |
| cols_mail[0].empty() | |
| cols_mail[1].image(filenames.image_path[reco_mailing2[0]].tolist()[0], width=100) | |
| cols_mail[1].markdown(filenames.titles[reco_mailing2[0]].tolist()[0]) | |
| cols_mail[1].markdown(":star::star::star::star::star:") | |
| cols_mail[2].image(filenames.image_path[reco_mailing2[0]].tolist()[1], width=100) | |
| cols_mail[2].markdown(filenames.titles[reco_mailing2[0]].tolist()[1]) | |
| cols_mail[2].markdown(":star::star::star::star:") | |
| cols_mail[3].image(filenames.image_path[reco_mailing2[0]].tolist()[2], width=100) | |
| cols_mail[3].markdown(filenames.titles[reco_mailing2[0]].tolist()[2]) | |
| cols_mail[3].markdown(":star::star::star::star::star:") | |
| cols_mail[4].image(filenames.image_path[reco_mailing2[0]].tolist()[3], width=100) | |
| cols_mail[4].markdown(filenames.titles[reco_mailing2[0]].tolist()[3]) | |
| cols_mail[4].markdown(":star::star::star::star:") | |
| cols_mail[5].image(filenames.image_path[reco_mailing2[0]].tolist()[4], width=100) | |
| cols_mail[5].markdown(filenames.titles[reco_mailing2[0]].tolist()[4]) | |
| cols_mail[5].markdown(":star::star::star::star::star:") | |
| cols_mail[6].empty() | |
| st.text('\n\n') | |
| st.markdown("<hr/>", unsafe_allow_html=True) | |
| st.markdown('<p style="font-size:120%">Discover our new products: </p>', unsafe_allow_html=True) | |
| st.text('\n\n') | |
| cols_mail2 = st.columns((4)) | |
| cols_mail2[0].image('images/velo.jpg', width=200) | |
| cols_mail2[1].image('images/sac.jpg', width=200) | |
| cols_mail2[2].image('images/shoes.jpg', width=200) | |
| cols_mail2[3].image('images/survet.jpg', width=200) | |
| st.text('\n\n\n\n') | |
| st.markdown("<hr/>", unsafe_allow_html=True) | |
| st.markdown('Always yours,') | |
| st.markdown('[company] team') | |
| if __name__ == '__main__': | |
| main() |