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| import streamlit as st | |
| import google.generativeai as genai | |
| # Streamlit app layout | |
| st.title('Personalized Product Description Writer') | |
| # Retrieve the API key from Streamlit secrets | |
| GOOGLE_API_KEY = st.secrets["GEMINI_API_KEY"] | |
| # Configure the Google Generative AI API with your API key | |
| genai.configure(api_key=GOOGLE_API_KEY) | |
| # Input fields for the product details | |
| st.subheader("Enter Product Details:") | |
| product_name = st.text_input('Product Name', '') | |
| product_features = st.text_area('Product Features (comma separated)', '') | |
| target_audience = st.text_input('Target Audience', '') | |
| # Create the prompt based on user inputs | |
| if product_name and product_features and target_audience: | |
| prompt = f""" | |
| Analyze the following product details: | |
| 1. Generate a catchy product description: | |
| - Use a tone that resonates with the target audience (e.g., playful for gamers, professional for WFH employees). | |
| - Include a brief brand story or emotional appeal to connect with potential buyers. | |
| - Highlight the product's unique selling points (USP) that differentiate it from competitors. | |
| - Mention specific usage scenarios (e.g., long gaming sessions, remote work). | |
| - End with a strong call to action (e.g., "Level up your comfort today!"). | |
| 2. Extract key features from the product features provided: | |
| - Identify and list the most important and unique features of the product. | |
| - Explain each feature's benefit to the user. | |
| - Emphasize how these features contribute to a better user experience. | |
| - Organize features in a logical order. | |
| - Include secondary features that add value. | |
| 3. Suggest marketing strategies based on the target audience (Indian market): | |
| 4. Suggest some frequently asked questions FAQs | |
| Product Name: {product_name} | |
| Product Features: {product_features} | |
| Target Audience: {target_audience} | |
| """ | |
| # Button to submit the prompt | |
| if st.button("Generate"): | |
| if product_name and product_features and target_audience: | |
| try: | |
| # Initialize the generative model (assuming this is the correct model) | |
| model = genai.GenerativeModel('gemini-pro') # Adjust the model if needed | |
| # Generate content based on the prompt | |
| response = model.generate_content(prompt) | |
| # Check if there is a response from the model | |
| if response: | |
| st.subheader("Generated Product Description:") | |
| st.write(response.text) # Displaying the text from the response | |
| else: | |
| st.error("Error: Unable to generate the description.") | |
| except Exception as e: | |
| st.error(f"Error: {e}") | |
| else: | |
| st.error("Please fill in all the product details to generate a description.") | |
| # Add some space or content in between | |
| st.write("\n" * 20) # You can adjust the number of lines to push the content down | |
| # Footer | |
| #st.sidebar.markdown("---") | |
| st.markdown("Built with 🧠 by Hruday & Google Gemini") | |