app.py

import base64
import requests
import gradio as gr
from PIL import Image
import pillow_avif  # This automatically registers AVIF support
import numpy as np
from datetime import datetime, date
import os
import json
import uuid
from http.cookies import SimpleCookie

# File to store session data
SESSION_FILE = "user_session_data.json"

# OpenAI API Key
api_key = os.getenv("OPENAI_API_KEY")


# Function to check and reset the counter if necessary for a specific user
def check_and_reset_user_counter(user_id):
    all_user_data = load_user_session_data(user_id)
    user_data = all_user_data[user_id]
    today = str(date.today())
    if user_data["last_reset_date"] != today:
        user_data["last_reset_date"] = today
        user_data["test_counter"] = 0
    save_user_session_data(all_user_data)
    return user_data["test_counter"]

def save_user_session_data(all_user_data):
    with open(SESSION_FILE, 'w') as f:
        json.dump(all_user_data, f)

# Function to load user session data
def load_user_session_data(user_id):
    if os.path.exists(SESSION_FILE):
        with open(SESSION_FILE, 'r') as f:
            all_user_data = json.load(f)
    else:
        all_user_data = {}
    
    if user_id not in all_user_data:
        all_user_data[user_id] = {"last_reset_date": str(date.today()), "test_counter": 0}
    
    return all_user_data

# Function to increment the counter for a specific user
def increment_user_counter(user_id):
    all_user_data = load_user_session_data(user_id)
    all_user_data[user_id]["test_counter"] += 1
    save_user_session_data(all_user_data)
    return all_user_data[user_id]["test_counter"]
    
# Function to get or create user ID from cookie
def get_or_create_user_id(user_id):
    if not user_id:
        return str(uuid.uuid4())
    return user_id
    
# Modify the encode_image function to handle AVIF files
def encode_image(image_array):
    try:
        # Convert numpy array to PIL Image
        img = Image.fromarray(np.uint8(image_array))
        
        # Create a temporary file path
        img_buffer = os.path.join(
            "/tmp", f"temp_image_{datetime.now().strftime('%Y%m%d_%H%M%S')}.jpg"
        )
        
        # Convert to RGB mode if the image is in a different mode
        if img.mode != 'RGB':
            img = img.convert('RGB')
        
        # Save as JPEG with error handling
        try:
            img.save(img_buffer, format="JPEG", quality=95)
        except Exception as e:
            print(f"Error saving image: {e}")
            # If saving fails, try to convert to RGB first
            img = img.convert('RGB')
            img.save(img_buffer, format="JPEG", quality=95)

        # Read and encode the saved image
        with open(img_buffer, "rb") as image_file:
            encoded_image = base64.b64encode(image_file.read()).decode("utf-8")
        
        # Clean up temporary file
        if os.path.exists(img_buffer):
            os.remove(img_buffer)
            
        return encoded_image
    except Exception as e:
        raise ValueError(f"Error processing image: {str(e)}")

# Function to generate product description using OpenAI API
def generate_product_description(image, description_type, custom_instruction=None):
    try:
        # Encode the uploaded image
        base64_image = encode_image(image)
    except Exception as e:
        raise gr.Error(f"Error processing image: {str(e)}. Please try uploading a different image format.")

    headers = {"Content-Type": "application/json", "Authorization": f"Bearer {api_key}"}

    # Set the description type or custom instruction
    description_prompts = {
        "Short Formal 📝": "Based on the image, craft a concise and compelling product description that highlights key features and benefits in a formal tone.",
        "Bullet Points 📋": "From the image, provide a detailed list of bullet points describing the product's features, benefits, and unique selling points.",
        "Amazon Optimized 🛒": "Create an Amazon-style product description based on the image, including key features, benefits, relevant keywords for SEO, and a persuasive call to action.",
        "Fashion 👗": "Generate a stylish and trendy product description for a fashion item shown in the image, emphasizing its design, materials, and how it fits into current fashion trends.",
        "Sport 🏀": "Using the image, develop an energetic and engaging product description for a sports-related item, highlighting its performance features and benefits for athletic activities.",
        "Technical Specifications ⚙️": "Extract and present the product's technical specifications from the image in a clear and concise manner, suitable for tech-savvy customers.",
        "SEO Optimized 🔍": "Write an SEO-friendly product description based on the image, incorporating relevant keywords and phrases to enhance search engine visibility.",
        "Social Media Style 📱": "Create a catchy and engaging product description suitable for social media platforms, using the image as inspiration.",
        "Luxury 💎": "Craft an elegant and sophisticated product description for the luxury item shown in the image, emphasizing exclusivity, premium quality, and craftsmanship.",
        "Kid-Friendly 🧸": "Generate a fun and appealing product description for a children's product based on the image, using language that resonates with both kids and parents.",
        "Health and Beauty 💄": "Develop a compelling product description for a health or beauty item shown in the image, highlighting its benefits, ingredients, and usage tips.",
        "Electronic Gadgets 📱": "Write a tech-focused product description for the electronic gadget in the image, focusing on its innovative features, specifications, and user advantages.",
        "Eco-Friendly 🌱": "Create an eco-conscious product description for the environmentally friendly product shown in the image, emphasizing sustainability and green benefits.",
        "Personalized Gifts 🎁": "Generate a heartfelt product description for the personalized gift in the image, highlighting customization options and sentimental value.",
        "Seasonal Promotion 🎉": "Craft a seasonal promotional product description based on the image, incorporating festive themes and limited-time offers to encourage immediate purchase.",
        "Clearance Sale 🏷️": "Write an urgent and enticing product description for the item in the image, emphasizing discounted prices and limited stock availability.",
        "Cross-Selling 🔗": "Develop a product description that not only highlights the item in the image but also suggests complementary products, encouraging additional purchases.",
        "Up-Selling ⬆️": "Create a persuasive product description that highlights premium features of the item in the image, encouraging customers to consider higher-end versions.",
        "Multi-Language Support 🌍": "Provide a product description based on the image in multiple languages to cater to a diverse customer base.",
        "User Testimonials ⭐": "Incorporate fictional user testimonials or reviews into the product description based on the image, adding credibility and social proof.",
        "Instructional 📘": "Write a product description that includes usage instructions or assembly steps for the item shown in the image.",
        "Bundle Offer 📦": "Craft a product description that promotes the item in the image as part of a bundle deal, highlighting the added value.",
        "Gift Guide Entry 🎁": "Generate a product description suitable for inclusion in a gift guide, emphasizing why the item in the image makes a great gift.",
        "Limited Edition 🚀": "Create an exclusive product description for the limited-edition item shown in the image, highlighting its uniqueness and scarcity.",
        "Subscription Model 🔄": "Write a product description that promotes the item in the image as part of a subscription service, detailing recurring benefits.",
        "B2B Focused 🏢": "Develop a professional product description suitable for business-to-business contexts, emphasizing features relevant to corporate clients.",
        "Alt Text Generation 🦿": "Generate concise and descriptive alt text for the image, ensuring accessibility for users with visual impairments. Focus on the image's key elements and purpose.",
    }


    if description_type == "Other" and custom_instruction:
        instruction = custom_instruction
    else:
        instruction = description_prompts.get(
            description_type, "Create a product description based on the image."
        )

    # Payload with base64 encoded image as a Data URL
    payload = {
        "model": "gpt-4o-mini",
        "messages": [
            {
                "role": "user",
                "content": [
                    {"type": "text", "text": instruction},
                    {
                        "type": "image_url",
                        "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"},
                    },
                ],
            }
        ],
        "max_tokens": 300,
    }

    response = requests.post(
        "https://api.openai.com/v1/chat/completions", headers=headers, json=payload
    )
    response_data = response.json()

    # Handle errors
    if response.status_code != 200:
        raise ValueError(
            f"OpenAI API Error: {response_data.get('error', {}).get('message', 'Unknown Error')}"
        )

    # Extract and return only the generated message content
    return response_data["choices"][0]["message"]["content"]


# Custom CSS and JavaScript for managing user ID in local storage
custom_css = """
  body {
    font-family: 'Inter', sans-serif;
  }
  #output {
    height: 500px;
    overflow: auto;
    border: 1px solid #ccc;
  }
  .redirect-message {
    background-color: #f0f0f0;
    border: 1px solid #ccc;
    padding: 15px;
    margin-top: 20px;
    border-radius: 5px;
  }
"""

# Initialize user ID
user_id = str(uuid.uuid4())

with gr.Blocks(css=custom_css) as demo:
    gr.Markdown("<h1>WordLift Product Description Generation - [FREE]</h1>")
    with gr.Tab(label="WordLift Product Description Generation"):
        with gr.Row():
            with gr.Column():
                input_img = gr.Image(label="Input Picture", elem_classes="gr-box")
                description_type = gr.Dropdown(
                    label="Select Description Type",
                    choices=[
                        "Short Formal 📝",
                        "Bullet Points 📋",
                        "Amazon Optimized 🛒",
                        "Fashion 👗",
                        "Sport 🏀",
                        "Technical Specifications ⚙️",
                        "SEO Optimized 🔍",
                        "Social Media Style 📱",
                        "Luxury 💎",
                        "Kid-Friendly 🧸",
                        "Health and Beauty 💄",
                        "Electronic Gadgets 📱",
                        "Eco-Friendly 🌱",
                        "Personalized Gifts 🎁",
                        "Seasonal Promotion 🎉",
                        "Clearance Sale 🏷️",
                        "Cross-Selling 🔗",
                        "Up-Selling ⬆️",
                        "Multi-Language Support 🌍",
                        "User Testimonials ⭐",
                        "Instructional 📘",
                        "Bundle Offer 📦",
                        "Gift Guide Entry 🎁",
                        "Limited Edition 🚀",
                        "Subscription Model 🔄",
                        "B2B Focused 🏢",
                        "Alt Text Generation 🦿",
                        # "Other",
                    ],
                    value="Short Formal 📝",
                    elem_classes="gr-box"
                )
                custom_instruction = gr.Textbox(
                    label="Custom Instruction (Only for 'Other')", visible=False, elem_classes="gr-box"
                )
                submit_btn = gr.Button(value="Submit", elem_classes="gr-box")
            with gr.Column():
                output_text = gr.Markdown(label="Output Text", show_copy_button=True, elem_classes="output-text")
                redirect_message = gr.Markdown(visible=False, elem_classes="redirect-message")
                test_counter_display = gr.Markdown(visible=True, label="Test Counter")
                user_id_display = gr.Markdown(visible=False, label="User ID")
                
        # Hidden textbox to store user ID
        user_id_input = gr.Textbox(value="", visible=False)


        # Toggle visibility of custom instruction based on selected type
        def toggle_custom_instruction(type_selection):
            return gr.update(visible=(type_selection == "Other"))

        description_type.change(
            toggle_custom_instruction,
            inputs=[description_type],
            outputs=[custom_instruction],
        )

        def handle_submit(image, description_type, custom_instruction, user_id):
            try:
                if not user_id:
                    user_id = str(uuid.uuid4())
                
                check_and_reset_user_counter(user_id)
                test_counter = increment_user_counter(user_id)
                
                demo_link = "https://wordlift.io/book-a-demo/?utm_source=free-app&utm_medium=app&utm_campaign=product-description-generator"
                
                if test_counter <= 4:
                    try:
                        result = generate_product_description(image, description_type, custom_instruction)
                    except gr.Error as e:
                        return (
                            str(e),
                            gr.update(visible=False),
                            gr.update(interactive=True),
                            f"Error occurred. You still have {4 - test_counter + 1} free test(s) remaining today.",
                            f"User ID: {user_id}",
                            user_id
                        )
                    
                    remaining_tests = 4 - test_counter
        
                    if remaining_tests > 0:
                        return (
                            result,
                            gr.update(visible=False),
                            gr.update(interactive=True),
                            f"You have {remaining_tests} free test(s) remaining today.",
                            f"User ID: {user_id}",
                            user_id
                        )
                    else:
                        redirect_text = f"""
                        Thank you for trying our product description generation tool!
            
                        You've used all 4 of your free tests for today. We hope you found them helpful and insightful.
            
                        To unlock unlimited access and discover how our AI-powered solution can revolutionize your content creation process:
            
                        [Book a Personalized Demo with Our Experts]({demo_link})
            
                        During the demo, you'll get:<br>
                        • A tailored walkthrough of our full suite of features<br>
                        • Insights on how to optimize your specific content workflow<br>
                        • Answers to any questions you may have about our solution<br>
            
                        We're excited to show you how we can help scale your content creation!
            
                        (Your free tests will reset tomorrow, allowing you to try 4 more if you need additional time to decide.)
                        """
                        return (
                            result,
                            gr.update(visible=True, value=redirect_text),
                            gr.update(interactive=False),
                            "You've used all your free tests for today. We invite you to book a demo for full access!",
                            f"User ID: {user_id}",
                            user_id
                        )
                else:
                    redirect_text = f"""
                    Thank you for your interest in our product description generation tool!
            
                    You've already used your 4 free tests for today. We hope they've given you a glimpse of how our AI can enhance your content creation.
            
                    Ready to explore the full potential of our solution?
            
                    [Book a Personalized Demo with Our Experts]({demo_link})
            
                    In this demo, you'll discover:<br>
                    • How our AI can be customized for your specific needs<br>
                    • Advanced features for scaling your content production using a [Product Knowledge Graph](https://wordlift.io/blog/en/product-knowledge-graph/)<br>
                    • ROI projections based on your current content workflow<br>
            
                    Let's discuss how we can help you achieve your content goals!
            
                    (Remember, your free tests will reset tomorrow if you need more time to evaluate.)
                    """
                    return (
                        "",
                        gr.update(visible=True, value=redirect_text),
                        gr.update(interactive=False),
                        "All free tests used. We invite you to book a demo for full access!",
                        f"User ID: {user_id}",
                        user_id
                    )
            except Exception as e:
                return (
                    f"An error occurred: {str(e)}",
                    gr.update(visible=False),
                    gr.update(interactive=True),
                    "Error processing request",
                    f"User ID: {user_id}",
                    user_id
                )


        # Update the outputs of the submit button click event
        submit_btn.click(
            handle_submit,
            inputs=[input_img, description_type, custom_instruction, user_id_input],
            outputs=[output_text, redirect_message, submit_btn, test_counter_display, user_id_display, user_id_input]
        )
    
# Launch Gradio app
demo.queue(api_open=False)
demo.launch(debug=True)