prompt.content: <|im_start|>system
  You are a helpful assistant that is capable of understanding and predicting customer shopping behaviors on Amazon. You first think about the reasoning process in the mind and then predict the customer actions and action argument. The reasoning process and the predicted action and action argument are enclosed within <think> </think> and <answer> </answer> tags, respectively, i.e., <think>reasoning process here</think><answer>predicted action and action argument here</answer>.
  <|im_end|>
  <|im_start|>user
  You are given a customer behavior trajectory on Amazon. This trajectory include the customer long-term information (enclosed between <|memory_start|> and <|memory_end|>), previous actions the customer has taken with timestamps (enclosed between <|action_start|> and <|action_end|>), and current observations describing what the customer sees on Amazon (e.g., a search results page, a product detail page) (enclosed between <|observation_start|> and <|observation_end|>). 
  Now your task is to predict the immediate next action and action argument (i.e., input_text, product_asin, or click_type) of this shopper by analyzing shopper shopping behaviors. The available action space and action argument space are provided between <|actionspace_start|> and <|actionspace_end|> to help guide your prediction. Please first analyze the customer's behavior patterns within the  <think> </think> section, then provide your prediction within the <answer> </answer> section, ensuring your prediction falls within the specified action and argument spaces. 
  
  <|actionspace_start|>
  Available actions are represented in JSON format. There are four primary action types with their corresponding action arguments:
  1. input:
  Action: Type text into an input field to search for a specific product. 
  Action Argument: the input_text is the specific text entered by the customer.
  {
  "timestamp": "timestamp",
  "action": "input",
  "action_argument": "input_text",
  }
  
  2. click:
  Action: Click on a UI interface button or clickable element on the Amazon website.
  Action Argument: The clickable_name is one of the UI interface buttons or clickable elements including "review", "search", "product_option", "other", "nav_bar", "quantity", "page_related", "suggested_term", "cart_side_bar", "cart_page_select", and "filter". Select one of these buttons or clickable elements as action argument.
  {
  "timestamp": "timestamp",
  "action": "click",
  "action_argument": "clickable_name",
  }
  
  3. click_product:
  Action: Click on product links or product images.
  Action Argument: the Amazon Standard Identification Number (i.e., product_asin) of the clicked product.
  {
  "timestamp": "timestamp",
  "action": "click_product",
  "action_argument": "product_asin",
  }
  
  4. purchase:
  Action: indicate intent to purchase by clicking on any purchase-related button. This includes clicking "Add to Cart", "Buy Now", "Set Subscription", or "Checkout" buttons for specific products. 
  Action Argument: the Amazon Standard Identification Number (i.e., product_asin) of the product being purchased.
  {
  "timestamp": "timestamp",
  "action": "purchase",
  "action_argument": "product_asin",
  }
  <|actionspace_end|>
  
  <|memory_start|>
  {"timestamp": "2025-04-01T00:09:12.232Z", "action": "input", "action_argument": "bike pump with gauge"}
  {"timestamp": "2025-04-01T00:10:24.448Z", "action": "click_product", "action_argument": "B00XLGKU14"}
  <|memory_end|>
  
  <|action_start|>
  {"timestamp": "2025-04-01T17:23:00.405Z", "action": "click", "action_argument": "search"}
  {"timestamp": "2025-04-01T17:23:03.503Z", "action": "click", "action_argument": "search"}
  {"timestamp": "2025-04-01T17:23:13.604Z", "action": "click_product", "action_argument": "B0DLBTPDCS"}
  {"timestamp": "2025-04-01T17:23:35.661Z", "action": "click", "action_argument": "product_option"}
  {"timestamp": "2025-04-01T17:23:40.626Z", "action": "click", "action_argument": "product_option"}
  {"timestamp": "2025-04-01T17:23:48.849Z", "action": "click", "action_argument": "product_option"}
  <|action_end|>
  
  <|observation_start|>
  Your context will be the JSON string containing page metadata of the Amazon page you are looking at. This Amazon page is the context you observed after performing your last action.
  "search_term": [{"term": "mac mini"}],
  "cart_items": [{"title": "The Invisible Computer: Why Good Products Can Fail, the Personal Computer Is So Complex, and Information Appliances Are the Solution", "asin": "0262640414", "price": "$35.00", "quantity": "1"},
  {"title": "Scenario-Based Design: Envisioning Work and Technology in System Development", "asin": "0471076597", "price": "$26.82", "quantity": "1"},
  {"title": "Things That Make Us Smart (William Patrick Book)", "asin": "0201626950", "price": "$11.33", "quantity": "1"},
  {"title": "Participatory Design: Principles and Practices", "asin": "0805809511", "price": "$149.99", "quantity": "1"},
  {"title": "The Nurnberg Funnel: Designing Minimalist Instruction for Practical Computer Skill (Technical Communication, Multimedia, and Information Systems)", "asin": "0262031639", "price": "$11.93", "quantity": "1"},
  {"title": "Computer-Supported Cooperative Work: A Book of Readings", "asin": "0934613575", "price": "$16.30", "quantity": "1"},
  {"title": "User Centered System Design: New Perspectives on Human-computer Interaction", "asin": "0898598729", "price": "$130.00", "quantity": "1"},
  {"title": "Human-Machine Reconfigurations: Plans and Situated Actions (Learning in Doing: Social, Cognitive and Computational Perspectives)", "asin": "052167588X", "price": "$44.99", "quantity": "1"},
  {"title": "The Human Use Of Human Beings", "asin": "0306803208", "price": "$8.87", "quantity": "1"},
  {"title": "Emotional Design: Why We Love (or Hate) Everyday Things", "asin": "0465051367", "price": "$10.79", "quantity": "1"},
  {"title": "The Design of Everyday Things: Revised and Expanded Edition", "asin": "0465050654", "price": "$12.77", "quantity": "1"}],
  "product_details": [{"asin": "B0DLBVHSLD"},
  {"title": "Apple 2024 Mac Mini Desktop Computer with M4 Pro chip with 12\u2011core CPU and 16\u2011core GPU: Built for Apple Intelligence, 24GB Unified Memory, 512GB SSD Storage, Gigabit Ethernet. Works with iPhone/iPad"},
  {"price": "$1,294.00"},
  {"bullet_list": "SIZE DOWN. POWER UP \u2014 The far mightier, way tinier Mac mini desktop computer is five by five inches of pure power. Built for Apple Intelligence.* Redesigned around Apple silicon to unleash the full speed and capabilities of the spectacular M4 Pro chip. With ports at your convenience, on the front and back. LOOKS SMALL. LIVES LARGE \u2014 At just five by five inches, Mac mini is designed to fit perfectly next to a monitor and is easy to place just about anywhere. CONVENIENT CONNECTIONS \u2014 Get connected with Thunderbolt, HDMI, and Gigabit Ethernet ports on the back and, for the first time, front-facing USB-C ports and a headphone jack. SUPERCHARGED BY M4 PRO \u2014 The M4 Pro chip brings extra power to take on demanding projects like working with complex scenes or compiling millions of lines of code. BUILT FOR APPLE INTELLIGENCE \u2014 Apple Intelligence is the personal intelligence system that helps you write, express yourself, and get things done effortlessly. With groundbreaking privacy protections, it gives you peace of mind that no one else can access your data \u2014 not even Apple.* APPS FLY WITH APPLE SILICON \u2014 All your favorites, including Microsoft 365 and Adobe Creative Cloud, run lightning fast in macOS.* IF YOU LOVE IPHONE, YOU\u2019LL LOVE MAC \u2014 Mac works like magic with your other Apple devices. View and control what\u2019s on your iPhone from your Mac with iPhone Mirroring.* Copy something on iPhone and paste it on Mac. Send texts with Messages or use your Mac to answer FaceTime calls.*"},
  {"bullet_list": "  CARBON NEUTRAL \u2014 Mac mini is carbon neutral. Learn more about Apple\u2019s commitment to the environment at apple.com/2030.  LEGAL DISCLAIMERS \u2014 This is a summary of the main product features. See below to learn more.  "}],
  "product_quantity": [{"quantity": "1"}],
  "product_options": [{"Style": "Apple M4 Pro chip"},
  {"Size": "24GB Unified Memory, 512GB SSD Storage"},
  {"Set": "without AppleCare+"}]
  <|observation_end|>
  
  # Output Format
  Please provide your final answer in JSON format within <answer></answer> tags using the following schema (Note that the thinking process should be within 250 words and give enough output space for final answer):
  "<answer>
  {
  "timestamp": "2025-04-01T17:23:54.591Z", // the timestamp when this action occurs.
  "action": "string", // select one plausible action from: input, click_product, purchase, or click.
  "acion_argument": "string", // select appropriate value based on action type: input_text, product_asin, clickable_name.
  }
  </answer>"
  
  <|im_end|>
  <|im_start|>assistant
  <think>
  
prompt.role: user
question: <|im_start|>system
  You are a helpful assistant that is capable of understanding and predicting customer shopping behaviors on Amazon. You first think about the reasoning process in the mind and then predict the customer actions and action argument. The reasoning process and the predicted action and action argument are enclosed within <think> </think> and <answer> </answer> tags, respectively, i.e., <think>reasoning process here</think><answer>predicted action and action argument here</answer>.
  <|im_end|>
  <|im_start|>user
  You are given a customer behavior trajectory on Amazon. This trajectory include the customer long-term information (enclosed between <|memory_start|> and <|memory_end|>), previous actions the customer has taken with timestamps (enclosed between <|action_start|> and <|action_end|>), and current observations describing what the customer sees on Amazon (e.g., a search results page, a product detail page) (enclosed between <|observation_start|> and <|observation_end|>). 
  Now your task is to predict the immediate next action and action argument (i.e., input_text, product_asin, or click_type) of this shopper by analyzing shopper shopping behaviors. The available action space and action argument space are provided between <|actionspace_start|> and <|actionspace_end|> to help guide your prediction. Please first analyze the customer's behavior patterns within the  <think> </think> section, then provide your prediction within the <answer> </answer> section, ensuring your prediction falls within the specified action and argument spaces. 
  
  <|actionspace_start|>
  Available actions are represented in JSON format. There are four primary action types with their corresponding action arguments:
  1. input:
  Action: Type text into an input field to search for a specific product. 
  Action Argument: the input_text is the specific text entered by the customer.
  {
  "timestamp": "timestamp",
  "action": "input",
  "action_argument": "input_text",
  }
  
  2. click:
  Action: Click on a UI interface button or clickable element on the Amazon website.
  Action Argument: The clickable_name is one of the UI interface buttons or clickable elements including "review", "search", "product_option", "other", "nav_bar", "quantity", "page_related", "suggested_term", "cart_side_bar", "cart_page_select", and "filter". Select one of these buttons or clickable elements as action argument.
  {
  "timestamp": "timestamp",
  "action": "click",
  "action_argument": "clickable_name",
  }
  
  3. click_product:
  Action: Click on product links or product images.
  Action Argument: the Amazon Standard Identification Number (i.e., product_asin) of the clicked product.
  {
  "timestamp": "timestamp",
  "action": "click_product",
  "action_argument": "product_asin",
  }
  
  4. purchase:
  Action: indicate intent to purchase by clicking on any purchase-related button. This includes clicking "Add to Cart", "Buy Now", "Set Subscription", or "Checkout" buttons for specific products. 
  Action Argument: the Amazon Standard Identification Number (i.e., product_asin) of the product being purchased.
  {
  "timestamp": "timestamp",
  "action": "purchase",
  "action_argument": "product_asin",
  }
  <|actionspace_end|>
  
  <|memory_start|>
  {"timestamp": "2025-04-01T00:09:12.232Z", "action": "input", "action_argument": "bike pump with gauge"}
  {"timestamp": "2025-04-01T00:10:24.448Z", "action": "click_product", "action_argument": "B00XLGKU14"}
  <|memory_end|>
  
  <|action_start|>
  {"timestamp": "2025-04-01T17:23:00.405Z", "action": "click", "action_argument": "search"}
  {"timestamp": "2025-04-01T17:23:03.503Z", "action": "click", "action_argument": "search"}
  {"timestamp": "2025-04-01T17:23:13.604Z", "action": "click_product", "action_argument": "B0DLBTPDCS"}
  {"timestamp": "2025-04-01T17:23:35.661Z", "action": "click", "action_argument": "product_option"}
  {"timestamp": "2025-04-01T17:23:40.626Z", "action": "click", "action_argument": "product_option"}
  {"timestamp": "2025-04-01T17:23:48.849Z", "action": "click", "action_argument": "product_option"}
  <|action_end|>
  
  <|observation_start|>
  Your context will be the JSON string containing page metadata of the Amazon page you are looking at. This Amazon page is the context you observed after performing your last action.
  "search_term": [{"term": "mac mini"}],
  "cart_items": [{"title": "The Invisible Computer: Why Good Products Can Fail, the Personal Computer Is So Complex, and Information Appliances Are the Solution", "asin": "0262640414", "price": "$35.00", "quantity": "1"},
  {"title": "Scenario-Based Design: Envisioning Work and Technology in System Development", "asin": "0471076597", "price": "$26.82", "quantity": "1"},
  {"title": "Things That Make Us Smart (William Patrick Book)", "asin": "0201626950", "price": "$11.33", "quantity": "1"},
  {"title": "Participatory Design: Principles and Practices", "asin": "0805809511", "price": "$149.99", "quantity": "1"},
  {"title": "The Nurnberg Funnel: Designing Minimalist Instruction for Practical Computer Skill (Technical Communication, Multimedia, and Information Systems)", "asin": "0262031639", "price": "$11.93", "quantity": "1"},
  {"title": "Computer-Supported Cooperative Work: A Book of Readings", "asin": "0934613575", "price": "$16.30", "quantity": "1"},
  {"title": "User Centered System Design: New Perspectives on Human-computer Interaction", "asin": "0898598729", "price": "$130.00", "quantity": "1"},
  {"title": "Human-Machine Reconfigurations: Plans and Situated Actions (Learning in Doing: Social, Cognitive and Computational Perspectives)", "asin": "052167588X", "price": "$44.99", "quantity": "1"},
  {"title": "The Human Use Of Human Beings", "asin": "0306803208", "price": "$8.87", "quantity": "1"},
  {"title": "Emotional Design: Why We Love (or Hate) Everyday Things", "asin": "0465051367", "price": "$10.79", "quantity": "1"},
  {"title": "The Design of Everyday Things: Revised and Expanded Edition", "asin": "0465050654", "price": "$12.77", "quantity": "1"}],
  "product_details": [{"asin": "B0DLBVHSLD"},
  {"title": "Apple 2024 Mac Mini Desktop Computer with M4 Pro chip with 12\u2011core CPU and 16\u2011core GPU: Built for Apple Intelligence, 24GB Unified Memory, 512GB SSD Storage, Gigabit Ethernet. Works with iPhone/iPad"},
  {"price": "$1,294.00"},
  {"bullet_list": "SIZE DOWN. POWER UP \u2014 The far mightier, way tinier Mac mini desktop computer is five by five inches of pure power. Built for Apple Intelligence.* Redesigned around Apple silicon to unleash the full speed and capabilities of the spectacular M4 Pro chip. With ports at your convenience, on the front and back. LOOKS SMALL. LIVES LARGE \u2014 At just five by five inches, Mac mini is designed to fit perfectly next to a monitor and is easy to place just about anywhere. CONVENIENT CONNECTIONS \u2014 Get connected with Thunderbolt, HDMI, and Gigabit Ethernet ports on the back and, for the first time, front-facing USB-C ports and a headphone jack. SUPERCHARGED BY M4 PRO \u2014 The M4 Pro chip brings extra power to take on demanding projects like working with complex scenes or compiling millions of lines of code. BUILT FOR APPLE INTELLIGENCE \u2014 Apple Intelligence is the personal intelligence system that helps you write, express yourself, and get things done effortlessly. With groundbreaking privacy protections, it gives you peace of mind that no one else can access your data \u2014 not even Apple.* APPS FLY WITH APPLE SILICON \u2014 All your favorites, including Microsoft 365 and Adobe Creative Cloud, run lightning fast in macOS.* IF YOU LOVE IPHONE, YOU\u2019LL LOVE MAC \u2014 Mac works like magic with your other Apple devices. View and control what\u2019s on your iPhone from your Mac with iPhone Mirroring.* Copy something on iPhone and paste it on Mac. Send texts with Messages or use your Mac to answer FaceTime calls.*"},
  {"bullet_list": "  CARBON NEUTRAL \u2014 Mac mini is carbon neutral. Learn more about Apple\u2019s commitment to the environment at apple.com/2030.  LEGAL DISCLAIMERS \u2014 This is a summary of the main product features. See below to learn more.  "}],
  "product_quantity": [{"quantity": "1"}],
  "product_options": [{"Style": "Apple M4 Pro chip"},
  {"Size": "24GB Unified Memory, 512GB SSD Storage"},
  {"Set": "without AppleCare+"}]
  <|observation_end|>
  
  # Output Format
  Please provide your final answer in JSON format within <answer></answer> tags using the following schema (Note that the thinking process should be within 250 words and give enough output space for final answer):
  "<answer>
  {
  "timestamp": "2025-04-01T17:23:54.591Z", // the timestamp when this action occurs.
  "action": "string", // select one plausible action from: input, click_product, purchase, or click.
  "acion_argument": "string", // select appropriate value based on action type: input_text, product_asin, clickable_name.
  }
  </answer>"
  
  <|im_end|>
  <|im_start|>assistant
  <think>
  
extra_info.question: <|im_start|>system
  You are a helpful assistant that is capable of understanding and predicting customer shopping behaviors on Amazon. You first think about the reasoning process in the mind and then predict the customer actions and action argument. The reasoning process and the predicted action and action argument are enclosed within <think> </think> and <answer> </answer> tags, respectively, i.e., <think>reasoning process here</think><answer>predicted action and action argument here</answer>.
  <|im_end|>
  <|im_start|>user
  You are given a customer behavior trajectory on Amazon. This trajectory include the customer long-term information (enclosed between <|memory_start|> and <|memory_end|>), previous actions the customer has taken with timestamps (enclosed between <|action_start|> and <|action_end|>), and current observations describing what the customer sees on Amazon (e.g., a search results page, a product detail page) (enclosed between <|observation_start|> and <|observation_end|>). 
  Now your task is to predict the immediate next action and action argument (i.e., input_text, product_asin, or click_type) of this shopper by analyzing shopper shopping behaviors. The available action space and action argument space are provided between <|actionspace_start|> and <|actionspace_end|> to help guide your prediction. Please first analyze the customer's behavior patterns within the  <think> </think> section, then provide your prediction within the <answer> </answer> section, ensuring your prediction falls within the specified action and argument spaces. 
  
  <|actionspace_start|>
  Available actions are represented in JSON format. There are four primary action types with their corresponding action arguments:
  1. input:
  Action: Type text into an input field to search for a specific product. 
  Action Argument: the input_text is the specific text entered by the customer.
  {
  "timestamp": "timestamp",
  "action": "input",
  "action_argument": "input_text",
  }
  
  2. click:
  Action: Click on a UI interface button or clickable element on the Amazon website.
  Action Argument: The clickable_name is one of the UI interface buttons or clickable elements including "review", "search", "product_option", "other", "nav_bar", "quantity", "page_related", "suggested_term", "cart_side_bar", "cart_page_select", and "filter". Select one of these buttons or clickable elements as action argument.
  {
  "timestamp": "timestamp",
  "action": "click",
  "action_argument": "clickable_name",
  }
  
  3. click_product:
  Action: Click on product links or product images.
  Action Argument: the Amazon Standard Identification Number (i.e., product_asin) of the clicked product.
  {
  "timestamp": "timestamp",
  "action": "click_product",
  "action_argument": "product_asin",
  }
  
  4. purchase:
  Action: indicate intent to purchase by clicking on any purchase-related button. This includes clicking "Add to Cart", "Buy Now", "Set Subscription", or "Checkout" buttons for specific products. 
  Action Argument: the Amazon Standard Identification Number (i.e., product_asin) of the product being purchased.
  {
  "timestamp": "timestamp",
  "action": "purchase",
  "action_argument": "product_asin",
  }
  <|actionspace_end|>
  
  <|memory_start|>
  {"timestamp": "2025-04-01T00:09:12.232Z", "action": "input", "action_argument": "bike pump with gauge"}
  {"timestamp": "2025-04-01T00:10:24.448Z", "action": "click_product", "action_argument": "B00XLGKU14"}
  <|memory_end|>
  
  <|action_start|>
  {"timestamp": "2025-04-01T17:23:00.405Z", "action": "click", "action_argument": "search"}
  {"timestamp": "2025-04-01T17:23:03.503Z", "action": "click", "action_argument": "search"}
  {"timestamp": "2025-04-01T17:23:13.604Z", "action": "click_product", "action_argument": "B0DLBTPDCS"}
  {"timestamp": "2025-04-01T17:23:35.661Z", "action": "click", "action_argument": "product_option"}
  {"timestamp": "2025-04-01T17:23:40.626Z", "action": "click", "action_argument": "product_option"}
  {"timestamp": "2025-04-01T17:23:48.849Z", "action": "click", "action_argument": "product_option"}
  <|action_end|>
  
  <|observation_start|>
  Your context will be the JSON string containing page metadata of the Amazon page you are looking at. This Amazon page is the context you observed after performing your last action.
  "search_term": [{"term": "mac mini"}],
  "cart_items": [{"title": "The Invisible Computer: Why Good Products Can Fail, the Personal Computer Is So Complex, and Information Appliances Are the Solution", "asin": "0262640414", "price": "$35.00", "quantity": "1"},
  {"title": "Scenario-Based Design: Envisioning Work and Technology in System Development", "asin": "0471076597", "price": "$26.82", "quantity": "1"},
  {"title": "Things That Make Us Smart (William Patrick Book)", "asin": "0201626950", "price": "$11.33", "quantity": "1"},
  {"title": "Participatory Design: Principles and Practices", "asin": "0805809511", "price": "$149.99", "quantity": "1"},
  {"title": "The Nurnberg Funnel: Designing Minimalist Instruction for Practical Computer Skill (Technical Communication, Multimedia, and Information Systems)", "asin": "0262031639", "price": "$11.93", "quantity": "1"},
  {"title": "Computer-Supported Cooperative Work: A Book of Readings", "asin": "0934613575", "price": "$16.30", "quantity": "1"},
  {"title": "User Centered System Design: New Perspectives on Human-computer Interaction", "asin": "0898598729", "price": "$130.00", "quantity": "1"},
  {"title": "Human-Machine Reconfigurations: Plans and Situated Actions (Learning in Doing: Social, Cognitive and Computational Perspectives)", "asin": "052167588X", "price": "$44.99", "quantity": "1"},
  {"title": "The Human Use Of Human Beings", "asin": "0306803208", "price": "$8.87", "quantity": "1"},
  {"title": "Emotional Design: Why We Love (or Hate) Everyday Things", "asin": "0465051367", "price": "$10.79", "quantity": "1"},
  {"title": "The Design of Everyday Things: Revised and Expanded Edition", "asin": "0465050654", "price": "$12.77", "quantity": "1"}],
  "product_details": [{"asin": "B0DLBVHSLD"},
  {"title": "Apple 2024 Mac Mini Desktop Computer with M4 Pro chip with 12\u2011core CPU and 16\u2011core GPU: Built for Apple Intelligence, 24GB Unified Memory, 512GB SSD Storage, Gigabit Ethernet. Works with iPhone/iPad"},
  {"price": "$1,294.00"},
  {"bullet_list": "SIZE DOWN. POWER UP \u2014 The far mightier, way tinier Mac mini desktop computer is five by five inches of pure power. Built for Apple Intelligence.* Redesigned around Apple silicon to unleash the full speed and capabilities of the spectacular M4 Pro chip. With ports at your convenience, on the front and back. LOOKS SMALL. LIVES LARGE \u2014 At just five by five inches, Mac mini is designed to fit perfectly next to a monitor and is easy to place just about anywhere. CONVENIENT CONNECTIONS \u2014 Get connected with Thunderbolt, HDMI, and Gigabit Ethernet ports on the back and, for the first time, front-facing USB-C ports and a headphone jack. SUPERCHARGED BY M4 PRO \u2014 The M4 Pro chip brings extra power to take on demanding projects like working with complex scenes or compiling millions of lines of code. BUILT FOR APPLE INTELLIGENCE \u2014 Apple Intelligence is the personal intelligence system that helps you write, express yourself, and get things done effortlessly. With groundbreaking privacy protections, it gives you peace of mind that no one else can access your data \u2014 not even Apple.* APPS FLY WITH APPLE SILICON \u2014 All your favorites, including Microsoft 365 and Adobe Creative Cloud, run lightning fast in macOS.* IF YOU LOVE IPHONE, YOU\u2019LL LOVE MAC \u2014 Mac works like magic with your other Apple devices. View and control what\u2019s on your iPhone from your Mac with iPhone Mirroring.* Copy something on iPhone and paste it on Mac. Send texts with Messages or use your Mac to answer FaceTime calls.*"},
  {"bullet_list": "  CARBON NEUTRAL \u2014 Mac mini is carbon neutral. Learn more about Apple\u2019s commitment to the environment at apple.com/2030.  LEGAL DISCLAIMERS \u2014 This is a summary of the main product features. See below to learn more.  "}],
  "product_quantity": [{"quantity": "1"}],
  "product_options": [{"Style": "Apple M4 Pro chip"},
  {"Size": "24GB Unified Memory, 512GB SSD Storage"},
  {"Set": "without AppleCare+"}]
  <|observation_end|>
  
  # Output Format
  Please provide your final answer in JSON format within <answer></answer> tags using the following schema (Note that the thinking process should be within 250 words and give enough output space for final answer):
  "<answer>
  {
  "timestamp": "2025-04-01T17:23:54.591Z", // the timestamp when this action occurs.
  "action": "string", // select one plausible action from: input, click_product, purchase, or click.
  "acion_argument": "string", // select appropriate value based on action type: input_text, product_asin, clickable_name.
  }
  </answer>"
  
  <|im_end|>
  <|im_start|>assistant
  <think>
  