import streamlit as st import google.generativeai as genai # Set up your Gemini API key GEMINI_API_KEY = "AIzaSyBpQcVs_Or_Asb4xnNcpk1qUbos-2o9Ddc" genai.configure(api_key=GEMINI_API_KEY) # Initialize the Gemini model model = genai.GenerativeModel('gemini-pro') # Function to get personalized recommendations def get_personalized_recommendations(user_preferences): prompt = f""" You are a personalized content recommendation system. Based on the following user preferences, suggest 5 relevant and family-friendly content items (e.g., movies, books, articles, etc.): User Preferences: {user_preferences} Provide the recommendations in a clear and concise format with a brief description for each. Ensure the content is appropriate for all audiences. """ try: # Generate recommendations using Gemini response = model.generate_content(prompt) return response.text except ValueError as e: return f"Sorry, the system could not generate recommendations due to safety restrictions. Please try a different query." # Streamlit app def main(): st.title("🎬 Personalized Content Recommendation System") st.write("Welcome! Share your preferences, and we'll recommend movies, books, articles, and more tailored just for you.") # Collect user preferences interests = st.text_input("What are your interests? (e.g., sci-fi movies, space exploration, AI technology):") favorite_genres = st.text_input("What are your favorite genres? (e.g., science fiction, documentaries):") recently_consumed = st.text_input("What have you recently watched/read? (e.g., Interstellar, The Martian):") if st.button("Get Recommendations"): if interests and favorite_genres and recently_consumed: user_preferences = { "interests": interests, "favorite_genres": favorite_genres, "recently_consumed": recently_consumed } # Get recommendations st.write("Generating recommendations...") recommendations = get_personalized_recommendations(user_preferences) st.success("Here are your personalized recommendations:") st.write(recommendations) else: st.error("Please fill in all the fields to get recommendations.") # Run the app if __name__ == "__main__": main()