> ## Documentation Index > Fetch the complete documentation index at: https://docs.spongecake.ai/llms.txt > Use this file to discover all available pages before exploring further. # Amazon Shopping > Example of using sponge cake to shop on Amazon ### Overview This guide walks you through an example of using **Spongecake** to shop on Amazon. It covers how to: * Automate interactions with Amazon. * Handle user inputs and security checks. * Use handlers to manage agent statuses. ```python theme={null} # amazon_example.py import logging from time import sleep from dotenv import load_dotenv from spongecake import Desktop, AgentStatus import subprocess # Configure logging - most logs in the SDK are INFO level logs logging.basicConfig( level=logging.INFO, format='%(levelname)s - %(message)s' ) load_dotenv() result = [None] # ------------------------- # Handlers for desktop agent statuses # ------------------------- def complete_handler(data): """COMPLETE -- Handle successful task data (just print out success message in this case)""" print("\n✅ Task completed successfully!") result[0] = data def needs_input_handler(messages): """NEEDS_INPUT -- Get input from the user, and pass it back to `action`""" for msg in messages: if hasattr(msg, "content"): text_parts = [part.text for part in msg.content if hasattr(part, "text")] print(f"\n💬 Agent asks: {' '.join(text_parts)}") user_says = input("Enter your response (or 'exit'/'quit'): ").strip() if user_says.lower() in ("exit", "quit"): print("Exiting as per user request.") result[0] = None # Just return None when user exits return None # Return None to indicate no further action return user_says # Return the user input to continue def needs_safety_check_handler(safety_checks, pending_call): """NEEDS_SAFETY_CHECK -- Have the user acknowledge the safety checks, and pass it back to `action`""" print("\n") for check in safety_checks: if hasattr(check, "message"): print(f"☢️ Pending Safety Check: {check.message}") print("🔔 Please acknowledge the safety check(s) in order to proceed with the computer call.") ack = input("Type 'ack' to confirm, or 'exit'/'quit': ").strip().lower() if ack in ("exit", "quit"): print("Exiting as per user request.") result[0] = None # Just return None when user exits return False # Don't proceed if ack == "ack": print("Acknowledged. Proceeding with the computer call...") return True # Proceed with the call return False # Don't proceed by default def error_handler(error_message): """ERROR -- Handle errors (just print it out in this case)""" print(f"😱 ERROR: {error_message}") result[0] = None # Just return None on error # ------------------------- # Main # ------------------------- def main(): # Start up an isolated desktop. Edit desktop name, and docker_image if needed desktop = Desktop(name="newdesktop") container = desktop.start() desktop.goto("https://www.amazon.com") print("🍰 spongecake container started:", container) print("...\n") # Open VNC connection to see the desktop, password is 'secret' (only works on mac) try: print('Attempting to open VNC connection to view Mac desktop, password is "secret"...') subprocess.run(["open", f"vnc://localhost:{desktop.vnc_port}"], check=True) except Exception as e: print(f"❌ Failed to open VNC connection: {e}") try: print( "\n👾 Performing desktop action... see output_image.png to see screenshots " "OR connect to the VNC server to view actions in real time" ) user_prompt = f""" # AGENT INSTRUCTIONS # You are currently on www.amazon.com Search for 'sponge cake plush' Click on the third product on the page Add the product to your cart # INTERACTION INSTRUCTIONS # YOU SHOULD ONLY NEED TO SCROLL DOWN OR CLICK. NEVER DO ANYTHING ELSE WHEN YOU SCROLL DOWN, YOU SHOULD ALWAYS DO IT AT MOST ONCE ON A GIVEN PAGE # ROADBLOCKS # If you encounter a CAPTCHA, you should ALWAYS ask the user to give you the answer to the CAPTCHA or take over [You likely need to take over on your VNC viewer until we add CAPTCHA support] # STOPPING CONDITION # You are STRICTLY ONLY done until you have added the product to the cart """ auto_mode = False # If auto_mode is enabled, use the ignore_safety_and_input flag if auto_mode: status, data = desktop.action(input_text=user_prompt, ignore_safety_and_input=True) # In auto mode, we should get a COMPLETE or ERROR status directly if status == AgentStatus.ERROR: print(f"❌ error in auto mode: {data}") result[0] = data else: # ACTION: Start the action chain with the initial command and all handlers status, data = desktop.action( input_text=user_prompt, complete_handler=complete_handler, needs_input_handler=needs_input_handler, needs_safety_check_handler=needs_safety_check_handler, error_handler=error_handler ) # Show final results final_result = result[0] if final_result is None: print("\n⛔️ Task was interrupted or encountered an error\n") elif hasattr(final_result, "output_text"): print(f"📩 Result: {final_result.output_text}\n") else: print("Done.\n") except Exception as e: print(f"❌ An error occurred: {e}") print("\nExiting gracefully...") # Clean up the container. Optionally, leave the container running and connect to it again when needed. # print("Stopping and removing container...") # desktop.stop() print("🍰") if __name__ == "__main__": main() ``` ### Notes on Prompting * When searching large pages (like Amazon results), the agent may scroll excessively or incorrectly. * If this happens, explicitly instruct the agent on how to scroll. For example: ``` YOU SHOULD ONLY NEED TO SCROLL DOWN OR CLICK. NEVER DO ANYTHING ELSE. ``` * If you anticipate roadblocks like captchas, guide the agent on how to handle them—either ask the user to intervene or provide a workaround. * Always include a clear stopping condition in your prompt to help the agent understand when the task is complete.