add watch history

Helpers.py

@@ -49,7 +49,8 @@ def get_user_recommendation_XGBoost(all_moves,model, user_id, n=10):
     recommendations = user_unseen_movies.sort_values(by='Pred_rating', ascending=False).head(n)['title']
     return recommendations ,user_seen_movies
 
-
+def seen_movies(dataBase,user_id):
+    return dataBase[dataBase['userId'] == user_id]['title'].values
 
 def get_user_recommendation(DataBase, Matrix,user_id,l=10):
     user = Matrix[user_id]

app.py

@@ -3,8 +3,9 @@ import requests
 import pandas as pd
 import pickle
 import gdown
+import re
 import os
-from Helpers import get_user_recommendation , train_model , get_user_recommendation_XGBoost ,get_recommendation_item
+from Helpers import get_user_recommendation , train_model , get_user_recommendation_XGBoost , seen_movies
 
 
 # Set page configuration
@@ -18,13 +19,11 @@ st.markdown(
             color: #FFFFFF;
             font-family: 'Arial', sans-serif;
         }
-
         .stApp {
             background: rgba(0, 0, 0, 0.7);
             border-radius: 15px;
             padding: 20px;
         }
-
         .title {
             font-size: 3em;
             text-align: center;
@@ -32,7 +31,6 @@ st.markdown(
             font-weight: bold;
             color: #FF0000;
         }
-
         .section-title {
             font-size: 2em;
             margin-top: 30px;
@@ -40,7 +38,6 @@ st.markdown(
             text-align: center;
             color: #FFD700;
         }
-
         .recommendation {
             border: 1px solid #FFD700;
             padding: 20px;
@@ -51,12 +48,10 @@ st.markdown(
             background-color: rgba(0, 0, 0, 0.8);
             overflow: hidden;
         }
-
         .recommendation:hover {
             transform: translateY(-10px);
             box-shadow: 0 8px 16px rgba(0, 0, 0, 0.5);
         }
-
         .recommendation img {
             width: 100%;
             height: 200px;
@@ -64,47 +59,38 @@ st.markdown(
             border-radius: 10px;
             margin-bottom: 10px;
         }
-
         .movie-details-container {
             display: flex;
             align-items: center;
             margin-bottom: 20px;
         }
-
         .movie-details-container .movie-poster {
             flex: 0 0 auto;
             width: 30%;
             margin-right: 20px;
         }
-
         .movie-details-container .movie-poster img {
             width: 100%;
             border-radius: 10px;
         }
-
         .movie-details-container .movie-details {
             flex: 1 1 auto;
         }
-
         .movie-details-container .movie-details p {
             margin: 5px 0;
         }
-
         a {
             color: #FFD700;
             text-decoration: none;
         }
-
         a:hover {
             text-decoration: underline;
         }
-
         .stSidebar .element-container {
             background: rgba(0, 0, 0, 0.7);
             border-radius: 15px;
             padding: 15px;
         }
-
         .stSidebar .stButton button {
             background-color: #FFD700;
             color: #000;
@@ -113,7 +99,6 @@ st.markdown(
             padding: 10px;
             transition: background-color 0.2s, transform 0.2s;
         }
-
         .stSidebar .stButton button:hover {
             background-color: #FFAA00;
             transform: scale(1.05);
@@ -159,43 +144,33 @@ if not os.path.exists(output_path):
 
     print("Download completed......")
 
+def display_user_history(history):
+    st.write("Your Watch History:")
+    container = st.container(height=300)
+    for movie in history:
+        with container:
+            container.write(movie)
+
+
+def get_user_history(dataBase, user_id):
+    return dataBase[dataBase['userId'] == user_id]['title'].values
 
 
-# Dummy data for user recommendations
-user_recommendations = {
-    1: ["Inception", "The Matrix", "Interstellar"],
-    2: ["The Amazing Spider-Man", "District 9", "Titanic"]
-}
 
 # Function to hash passwords
 def hash_password(password):
     pass
 
-# Dummy user database
-user_db = {
-    1: "password123",
-    2: "mypassword"
-}
+
 
 # Login function
-def login(username, password):
+def login(username, password = None):
     if isinstance(username, int) and username > 0 and username < 610:
         return True
     return False
 
 
 
-
-# Function to fetch movie details from OMDb API
-# def fetch_movie_details(title, api_key="23f109b2"):
-#     url = f"http://www.omdbapi.com/?t={title}&apikey={api_key}"
-#     response = requests.get(url)
-#     return response.json()
-
-# Display movie details
-
-import re
-
 def fetch_movie_details(title, api_key_omdb="23f109b2", api_key_tmdb="b8c96e534866701532768a313b978c8b"):
     # First, try the OMDb API
     title = title[:-7]
@@ -396,8 +371,7 @@ def recommend(movie, similarity_df, movies_df, ratings_df, links_df, k=5):
 # Main app
 
 def main():
-    
-    movies_df, ratings_df, links_df , DB_df = load_data()
+    movies_df, ratings_df, links_df, DB_df = load_data()
     print("Data loaded successfully")
     print("Loading similarity matrix...")
     similarity_df = load_similarity_matrix(output_path)
@@ -407,29 +381,38 @@ def main():
     choice = st.sidebar.selectbox("Select an option", menu)
     
     if choice == "Login":
-        st.title("Movie Recommendations")
-        st.write("Welcome to the Movie Recommendation App!")
-        st.write("Please login to get personalized movie recommendations. username between (1 and 800)")
-        # model selection
-        C = st.selectbox("Select the model", ["User Similarity Matrix", "XGBoost"])
+        num_cols = 2
+        cols = st.columns(num_cols)
+        with cols[0]:
+            st.title("Movie Recommendations")
+            st.write("Welcome to the Movie Recommendation App!")
+            st.write("Please login to get personalized movie recommendations. username between (1 and 609)")
+            # model selection
+            C = st.selectbox("Select the model", ["User Similarity Matrix", "XGBoost"])
             
         # Login form
         st.sidebar.header("Login")
         username = st.sidebar.text_input("Username")
         if username:
             username = int(username)
-        # password = st.sidebar.text_input("Password", type="password")
         if st.sidebar.button("Login"):
-            if login(username, 'password'):
+            if login(username):
                 st.sidebar.success("Login successful!")
+
+                # Fetch user history
+                with cols[1 % num_cols]:
+                    user_history = get_user_history(DB_df, username)
+                    display_user_history(user_history)
+                
                 if C == "User Similarity Matrix":
                     user_matrix = load_similarity_matrix(user_matrix_path)
                     recommendations = get_user_recommendation(DB_df, user_matrix, username)
                 elif C == "XGBoost":
-                    model = train_model(DB_df,username)
-                    recommendations , user_seen_movies = get_user_recommendation_XGBoost(DB_df, model, username)
+                    model = train_model(DB_df, username)
+                    recommendations, user_seen_movies = get_user_recommendation_XGBoost(DB_df, model, username)
                 else:
-                    recommendations = user_recommendations.get(username, [])
+                    pass
+
                 st.write(f"Recommendations for user number {username}:")
                 num_cols = 2
                 cols = st.columns(num_cols)
@@ -456,7 +439,6 @@ def main():
         with cols[1]:
             st.title("Choosen Movie Details:")
             if selected_movie:
-                # correct_Name = selected_movie[:-7]
                 movie = fetch_movie_details(selected_movie)
                 if movie['Response'] == 'True':
                     display_movie_details(movie)
@@ -465,39 +447,14 @@ def main():
         if button:
             st.write("The rating bar here is token from our dataset and it's between 0 and 5.")
             if selected_movie:
-                # recommendations = get_recommendation_item(DB_df, similarity_df, selected_movie , k)
                 recommendations = recommend(selected_movie, similarity_df, movies_df, ratings_df, links_df, k)
                 if recommendations:
                     st.write(f"Similar movies to '{selected_movie}':")
                     num_cols = 2
                     cols = st.columns(num_cols)
-
-                    # movie_id = movies_df[movies_df['title'] == selected_movie]['movieId'].values[0]
-                    # movie_details = get_movie_details(movie_id, movies_df, ratings_df, links_df)
-                    # if movie_details:
-                    #     st.markdown(f'<h2 class="section-title">{movie_details["title"]} Details:</h2>', unsafe_allow_html=True)
-                    #     st.markdown(
-                    #         f"""
-                    #         <div class="movie-details-container">
-                    #             <div class="movie-poster">
-                    #                 <img src="{movie_details['poster_url']}" alt="Movie Poster">
-                    #             </div>
-                    #             <div class="movie-details">
-                    #                 <p><b>Genres:</b> {', '.join(movie_details['genres'])}</p>
-                    #                 <p><b>Average Rating:</b> {movie_details['avg_rating']}</p>
-                    #                 <p><b>Number of Ratings:</b> {movie_details['num_ratings']}</p>
-                    #                 <p><b>IMDb :</b> <a href="https://www.imdb.com/title/tt{movie_details['imdb_id']:07d}/" target="_blank">movie link</a></p>
-                    #             </div>
-                    #         </div>
-                    #         """,
-                    #         unsafe_allow_html=True
-                    #     )
-
-
-                    
                     for i, movie in enumerate(recommendations):
-                            with cols[i % num_cols]:
-                                print_movie_details(movie)
+                        with cols[i % num_cols]:
+                            print_movie_details(movie)
                 else:
                     st.write("No recommendations found.")
             else:
@@ -505,3 +462,6 @@ def main():
 
 if __name__ == "__main__":
     main()
+
+
+