import base64 import gradio as gr from openai import OpenAI import os import dotenv dotenv.load_dotenv() client = OpenAI(api_key=os.getenv("OPENAI_API_KEY")) script_dir = os.path.dirname(os.path.abspath(__file__)) printer_1 = """ # PrinterOne Product: Business Cards Surface Options: plastic: multiplier: 1.0 cardboard: multiplier: 0.9 wood: multiplier: 1.3 Sizes: 3x3 cm: multiplier 1.0 6x6 cm: multiplier 1.8 Finishing: gloss: multiplier 1.1 matt: multiplier 1.0 Label Types: permanent: multiplier 1.0 repositionable: multiplier 1.15 removable: multiplier 1.2 Base Prices (Quantity,Price per Unit $): 25,2.0 50,1.6 100,1.0 200,0.7 500,0.36 1000,0.2 2000,0.14 5000,0.12 10000,0.09 20000,0.07 """ printer_2 = """ # BannerLord Product: Business Cards Surface Options: plastic: multiplier: 1.0 cardboard: multiplier: 0.85 wood: multiplier: 1.4 Sizes: 3x3 cm: multiplier 1.0 6x6 cm: multiplier 1.9 Finishing: gloss: multiplier 1.15 matt: multiplier 1.0 Label Types: permanent: multiplier 1.0 repositionable: multiplier 1.2 removable: multiplier 1.25 Base Prices (Quantity,Price per Unit $): 25,2.4 50,1.8 100,1.2 200,0.75 500,0.4 1000,0.22 2000,0.15 5000,0.14 10000,0.1 20000,0.075 """ printer_3 = """ # PrintMaster Product: Business Cards Surface Options: plastic: multiplier: 1.0 cardboard: multiplier: 1.1 wood: multiplier: 1.25 Sizes: 3x3 cm: multiplier 1.0 6x6 cm: multiplier 1.85 Finishing: gloss: multiplier 1.12 matt: multiplier 1.0 Label Types: permanent: multiplier 1.0 repositionable: multiplier 1.18 removable: multiplier 1.22 Base Prices (Quantity,Price per Unit $): 50,1.4 75,1.2 100,1.05 150,1.0 200,0.875 250,0.72 500,0.4 750,0.4 1000,0.35 1500,0.3 2000,0.25 """ def find_best_price(request): chat_prompt = ( "You are a customer assistant and you have to find the best price for the customer. " "Here are the prices and options from the printers:\n" f"Printer 1: {printer_1}\n" f"Printer 2: {printer_2}\n" f"Printer 3: {printer_3}\n" "For each request, you should:\n" "1. Check if the requested size (3x3 or 6x6 cm) is available. If not, suggest the nearest available size.\n" "2. Calculate the final price by:\n" " - Finding the nearest lower quantity in the base price list\n" " - Multiplying by the surface option multiplier\n" " - Multiplying by the size multiplier\n" " - Multiplying by the finishing multiplier\n" " - Multiplying by the label type multiplier\n" "3. Do not use linear interpolation for quantities - use the nearest lower quantity pricing.\n\n" "Example:\n" "User: I want to print 600 business cards, 6x6 cm size, premium white surface, gloss finish, permanent labels\n" "Answer:\n" "PrinterOne: 500 cards at base price $0.36. With multipliers (surface: 1.0, size: 1.8, finish: 1.1, label: 1.0) = $0.713 per unit. Total for 600: $427.80\n" "###\n" "BannerLord: 500 cards at base price $0.4. With multipliers (surface: 1.0, size: 1.9, finish: 1.15, label: 1.0) = $0.874 per unit. Total for 600: $524.40\n" "###\n" "PrintMaster: 500 cards at base price $0.4. With multipliers (surface: 1.0, size: 1.85, finish: 1.12, label: 1.0) = $0.829 per unit. Total for 600: $497.40\n\n" "The '###' symbol must separate each printer's price calculation. Show all calculations clearly as in the example above.\n" "For each printer, first state the base quantity and price, then show all applicable multipliers, the final per-unit price, and the total cost." ) chat_response = client.chat.completions.create( model="gpt-4o-mini", messages=[ {"role": "system", "content": chat_prompt}, {"role": "user", "content": request}, ], ) chat_text = chat_response.choices[0].message.content html_page = render_html_page(chat_text) chat_text = chat_text.replace("###", "") return chat_text, html_page def render_html_page(chat_text): images = [ os.path.join(script_dir, "public/src/brochure3-400x400.jpg"), os.path.join(script_dir, "public/src/quality-unfolded-brochures_1_.png"), os.path.join(script_dir, "public/src/unfolded-glossy-brochures.png"), ] product_links = [ "https://www.example.com/product_image.jpg", "https://www.example.com/product_image.jpg", "https://www.example.com/product_image.jpg", ] # Split chat_text into product descriptions product_descriptions = chat_text.split("###") # Generate HTML content html_content = """ Product Cards """ for i, description in enumerate(product_descriptions): image = images[i % len(images)] with open(image, "rb") as img_file: base64_image = base64.b64encode(img_file.read()).decode("utf-8") product_link = product_links[i % len(product_links)] html_content += f"""
Product Image

{description}

""" html_content += """ """ return html_content logo = os.path.join(script_dir, "public/src/logo.svg") with open(logo, "rb") as logo_file: base64_logo = base64.b64encode(logo_file.read()).decode("utf-8") iface = gr.Interface( fn=find_best_price, inputs=gr.Textbox(lines=3, placeholder="Enter what are you looking for"), outputs=[ gr.Textbox(label="Result"), gr.HTML(label="Product Image"), ], title="Get Instant Quote", description=f"""
Logo
""", submit_btn="Get quote", ) def auth_function(username, password): valid_users = {"admin": "password123", "user1": "pass456"} return username in valid_users and valid_users[username] == password iface.launch(auth=auth_function, share=True, ssr_mode=False)