diff --git a/content/bilalakram b/content/bilalakram
new file mode 100644
index 000000000000..8d6bc712c4e3
--- /dev/null
+++ b/content/bilalakram
@@ -0,0 +1,59 @@
+import streamlit as st
+import pickle
+import pandas as pd
+import requests
+
+def fetch_movie_id(movie_title):
+    response = requests.get("https://api.themoviedb.org/3/search/movie?api_key=2eec5cadfef931cf08e9b0805fe12e88&query={}".format(movie_title))
+    data = response.json()
+    if data['results']:
+        return data['results'][0]['id']
+    else:
+        return None
+
+def fetch_poster(movie_id):
+    response = requests.get("https://api.themoviedb.org/3/movie/{}?api_key=2eec5cadfef931cf08e9b0805fe12e88".format(movie_id))
+    data = response.json()
+    print(data)  # Add this line to print the API response
+    if 'poster_path' in data and data['poster_path'] is not None:
+        return "https://image.tmdb.org/t/p/w185/" + data['poster_path']
+    else:
+        print("Poster not available for movie ID:", movie_id)
+        return "https://via.placeholder.com/185x278"  # Use a default image URL
+
+def recommend(movie):
+    if not movie:
+        return []
+    if movie not in movies_lists:
+        return []
+    movie_index = movies_lists.tolist().index(movie)
+    distance = similarity[movie_index]
+    movie_list = sorted(list(enumerate(similarity[movie_index])), reverse=True, key=lambda x:x[1])[1:6]
+    recommended_movies = [movies_lists[i[0]] for i in movie_list]
+    recommended_movies_poster = []
+    for movie in recommended_movies:
+        movie_id = fetch_movie_id(movie)
+        if movie_id:
+            poster = fetch_poster(movie_id)
+            print(movie_id)  # Add this line to print the movie ID
+            recommended_movies_poster.append(poster)
+        else:
+            recommended_movies_poster.append("https://via.placeholder.com/185x278")  # Use a default image URL
+    return recommended_movies, recommended_movies_poster
+
+movies_lists = pickle.load(open('movies.pkl','rb'))
+movies_lists = movies_lists["title"].values
+similarity = pickle.load(open('similarity.pkl','rb'))
+
+st.title('Movie Recommender System')
+Selected_Movie_Name   = st.selectbox('How would you like to be connected ?', movies_lists)
+
+if st.button('Recommend'):
+    names, poster = recommend(Selected_Movie_Name)
+    row = st.container()
+    with row:
+        cols = st.columns(5)
+        for i in range(5):
+            with cols[i]:
+                st.write(f"<h5 style='text-align: center; width: 150px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap;'>{names[i]}</h5>", unsafe_allow_html=True)
+                st.image(poster[i])