<|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": "2025-04-10T21:34:38.098Z", "action": "input", "action_argument": "vita"}
{"timestamp": "2025-04-10T21:34:38.228Z", "action": "click", "action_argument": "suggested_term"}
{"timestamp": "2025-04-10T21:36:07.486Z", "action": "click_product", "action_argument": "B08FNG91XM"}
{"timestamp": "2025-04-10T21:36:21.008Z", "action": "purchase", "action_argument": "B08FNG91XM"}
<|memory_end|>

<|action_start|>
<|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": "vitamin c"}],
"cart_items": [{"title": "AI Engineering: Building Applications with Foundation Models", "asin": "1098166302", "price": "$57.74", "quantity": "1"},
{"title": "Ranong Tea Matcha Green Tea Latte Instant Drink Mix 8 Sachets", "asin": "B07RWN8N9H", "price": "$7.45", "quantity": "1"},
{"title": "LLM Engineer's Handbook: Master the art of engineering large language models from concept to production", "asin": "1836200072", "price": "$39.27", "quantity": "1"},
{"title": "Build a Large Language Model (From Scratch)", "asin": "1633437167", "price": "$47.37", "quantity": "1"},
{"title": "Nexus: A Brief History of Information Networks from the Stone Age to AI", "asin": "059373422X", "price": "$21.71", "quantity": "1"},
{"title": "Butter: A Novel of Food and Murder", "asin": "0063236419", "price": "$15.99", "quantity": "1"},
{"title": "Amazon Basics Rectangular Plastic Desk Organizer, Half Accessory Tray, 9.4\" x 3.3\" x 1\", Black", "asin": "B07S268HGD", "price": "$8.46", "quantity": "1"},
{"title": "Nature's Bounty Magnesium, Bone and Muscle Health, Whole Body Support, Tablets, 500 Mg, 200 Ct", "asin": "B00H5PJ0HW", "price": "$9.50", "quantity": "1"},
{"title": "The Global War on Tobacco: Mapping the World's First Public Health Treaty", "asin": "1421416832", "price": "$38.36", "quantity": "1"},
{"title": "Allen Carr's Easy Way To Stop Smoking", "asin": "0615482155", "price": "$12.51", "quantity": "1"},
{"title": "JARLINK Over The Door Organizer Storage, 5 Shelf Hanging Door Organizer with 5 Large Capacity Pockets, Anti Tilt 44 lb Load Behind Door Organizer for Bedroom, Bathroom, Pantry, Nursery, (Grey)", "asin": "B0C89STMFK", "price": "$24.99", "quantity": "1"},
{"title": "Go! More Than a Game: Revised Edition", "asin": "080483475X", "price": "$10.69", "quantity": "1"},
{"title": "Killers of the Flower Moon: Adapted for Young Readers: The Osage Murders and the Birth of the FBI", "asin": "0593377370", "price": "$9.89", "quantity": "1"},
{"title": "For Profit: A History of Corporations", "asin": "1541601572", "price": "$13.58", "quantity": "1"}],
"product_details": [{"asin": "B08FNG91XM"},
{"title": "Nature Made Extra Strength Dosage Chewable Vitamin C 1000 mg per serving, Dietary Supplement for Immune Support, 90 Tablets, 45 Day Supply"},
{"price": "$7.49"},
{"bullet_list": "Immune support supplement: contains one 90 count bottle of Nature Made Extra Strength Chewable Vitamin C 1000 mg per serving Tablets for a 45-day supply Nature Made Vitamin C 1000mg per serving is an extra strength dosage chewable Vitamin C antioxidant supplement that supports immune health and offers antioxidant support This 1000 mg per serving Vitamin C supplement provides Vitamin C for adults, which is necessary for the body to produce collagen to help support healthy skin Back in original orange flavor; adults chew two Nature Made Vitamin C chewable tablets daily with a meal Nature Made Chewable Vitamin C 1000mg for adults in two tablets per serving have no color added and no artificial flavors Made in the USA with quality global ingredients, United States Pharmacopeia (USP) Verified, #1 Pharmacist Recommended Vitamin & Supplement Brand* These statements have not been evaluated by the Food and Drug Administration; this product is not intended to diagnose, treat, cure, or prevent any disease"}],
"product_quantity": [{"quantity": "1"},
{"quantity": "1"}],
"product_options": [{"Flavor Name": "Orange"},
{"Size": "90 Count (Pack of 1)"}]
<|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": "2025-04-10T21:36:25.628Z", // 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>

user
<|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": "2025-04-10T21:34:38.098Z", "action": "input", "action_argument": "vita"}
{"timestamp": "2025-04-10T21:34:38.228Z", "action": "click", "action_argument": "suggested_term"}
{"timestamp": "2025-04-10T21:36:07.486Z", "action": "click_product", "action_argument": "B08FNG91XM"}
{"timestamp": "2025-04-10T21:36:21.008Z", "action": "purchase", "action_argument": "B08FNG91XM"}
<|memory_end|>

<|action_start|>
<|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": "vitamin c"}],
"cart_items": [{"title": "AI Engineering: Building Applications with Foundation Models", "asin": "1098166302", "price": "$57.74", "quantity": "1"},
{"title": "Ranong Tea Matcha Green Tea Latte Instant Drink Mix 8 Sachets", "asin": "B07RWN8N9H", "price": "$7.45", "quantity": "1"},
{"title": "LLM Engineer's Handbook: Master the art of engineering large language models from concept to production", "asin": "1836200072", "price": "$39.27", "quantity": "1"},
{"title": "Build a Large Language Model (From Scratch)", "asin": "1633437167", "price": "$47.37", "quantity": "1"},
{"title": "Nexus: A Brief History of Information Networks from the Stone Age to AI", "asin": "059373422X", "price": "$21.71", "quantity": "1"},
{"title": "Butter: A Novel of Food and Murder", "asin": "0063236419", "price": "$15.99", "quantity": "1"},
{"title": "Amazon Basics Rectangular Plastic Desk Organizer, Half Accessory Tray, 9.4\" x 3.3\" x 1\", Black", "asin": "B07S268HGD", "price": "$8.46", "quantity": "1"},
{"title": "Nature's Bounty Magnesium, Bone and Muscle Health, Whole Body Support, Tablets, 500 Mg, 200 Ct", "asin": "B00H5PJ0HW", "price": "$9.50", "quantity": "1"},
{"title": "The Global War on Tobacco: Mapping the World's First Public Health Treaty", "asin": "1421416832", "price": "$38.36", "quantity": "1"},
{"title": "Allen Carr's Easy Way To Stop Smoking", "asin": "0615482155", "price": "$12.51", "quantity": "1"},
{"title": "JARLINK Over The Door Organizer Storage, 5 Shelf Hanging Door Organizer with 5 Large Capacity Pockets, Anti Tilt 44 lb Load Behind Door Organizer for Bedroom, Bathroom, Pantry, Nursery, (Grey)", "asin": "B0C89STMFK", "price": "$24.99", "quantity": "1"},
{"title": "Go! More Than a Game: Revised Edition", "asin": "080483475X", "price": "$10.69", "quantity": "1"},
{"title": "Killers of the Flower Moon: Adapted for Young Readers: The Osage Murders and the Birth of the FBI", "asin": "0593377370", "price": "$9.89", "quantity": "1"},
{"title": "For Profit: A History of Corporations", "asin": "1541601572", "price": "$13.58", "quantity": "1"}],
"product_details": [{"asin": "B08FNG91XM"},
{"title": "Nature Made Extra Strength Dosage Chewable Vitamin C 1000 mg per serving, Dietary Supplement for Immune Support, 90 Tablets, 45 Day Supply"},
{"price": "$7.49"},
{"bullet_list": "Immune support supplement: contains one 90 count bottle of Nature Made Extra Strength Chewable Vitamin C 1000 mg per serving Tablets for a 45-day supply Nature Made Vitamin C 1000mg per serving is an extra strength dosage chewable Vitamin C antioxidant supplement that supports immune health and offers antioxidant support This 1000 mg per serving Vitamin C supplement provides Vitamin C for adults, which is necessary for the body to produce collagen to help support healthy skin Back in original orange flavor; adults chew two Nature Made Vitamin C chewable tablets daily with a meal Nature Made Chewable Vitamin C 1000mg for adults in two tablets per serving have no color added and no artificial flavors Made in the USA with quality global ingredients, United States Pharmacopeia (USP) Verified, #1 Pharmacist Recommended Vitamin & Supplement Brand* These statements have not been evaluated by the Food and Drug Administration; this product is not intended to diagnose, treat, cure, or prevent any disease"}],
"product_quantity": [{"quantity": "1"},
{"quantity": "1"}],
"product_options": [{"Flavor Name": "Orange"},
{"Size": "90 Count (Pack of 1)"}]
<|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": "2025-04-10T21:36:25.628Z", // 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>

<answer>{"timestamp": "2025-04-10T21:36:25.628Z","action": "click","acion_argument": "review",}</answer>
rule
<answer>{"timestamp": "2025-04-10T21:36:25.628Z","action": "click","acion_argument": "review",}</answer>
<|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": "2025-04-10T21:34:38.098Z", "action": "input", "action_argument": "vita"}
{"timestamp": "2025-04-10T21:34:38.228Z", "action": "click", "action_argument": "suggested_term"}
{"timestamp": "2025-04-10T21:36:07.486Z", "action": "click_product", "action_argument": "B08FNG91XM"}
{"timestamp": "2025-04-10T21:36:21.008Z", "action": "purchase", "action_argument": "B08FNG91XM"}
<|memory_end|>

<|action_start|>
<|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": "vitamin c"}],
"cart_items": [{"title": "AI Engineering: Building Applications with Foundation Models", "asin": "1098166302", "price": "$57.74", "quantity": "1"},
{"title": "Ranong Tea Matcha Green Tea Latte Instant Drink Mix 8 Sachets", "asin": "B07RWN8N9H", "price": "$7.45", "quantity": "1"},
{"title": "LLM Engineer's Handbook: Master the art of engineering large language models from concept to production", "asin": "1836200072", "price": "$39.27", "quantity": "1"},
{"title": "Build a Large Language Model (From Scratch)", "asin": "1633437167", "price": "$47.37", "quantity": "1"},
{"title": "Nexus: A Brief History of Information Networks from the Stone Age to AI", "asin": "059373422X", "price": "$21.71", "quantity": "1"},
{"title": "Butter: A Novel of Food and Murder", "asin": "0063236419", "price": "$15.99", "quantity": "1"},
{"title": "Amazon Basics Rectangular Plastic Desk Organizer, Half Accessory Tray, 9.4\" x 3.3\" x 1\", Black", "asin": "B07S268HGD", "price": "$8.46", "quantity": "1"},
{"title": "Nature's Bounty Magnesium, Bone and Muscle Health, Whole Body Support, Tablets, 500 Mg, 200 Ct", "asin": "B00H5PJ0HW", "price": "$9.50", "quantity": "1"},
{"title": "The Global War on Tobacco: Mapping the World's First Public Health Treaty", "asin": "1421416832", "price": "$38.36", "quantity": "1"},
{"title": "Allen Carr's Easy Way To Stop Smoking", "asin": "0615482155", "price": "$12.51", "quantity": "1"},
{"title": "JARLINK Over The Door Organizer Storage, 5 Shelf Hanging Door Organizer with 5 Large Capacity Pockets, Anti Tilt 44 lb Load Behind Door Organizer for Bedroom, Bathroom, Pantry, Nursery, (Grey)", "asin": "B0C89STMFK", "price": "$24.99", "quantity": "1"},
{"title": "Go! More Than a Game: Revised Edition", "asin": "080483475X", "price": "$10.69", "quantity": "1"},
{"title": "Killers of the Flower Moon: Adapted for Young Readers: The Osage Murders and the Birth of the FBI", "asin": "0593377370", "price": "$9.89", "quantity": "1"},
{"title": "For Profit: A History of Corporations", "asin": "1541601572", "price": "$13.58", "quantity": "1"}],
"product_details": [{"asin": "B08FNG91XM"},
{"title": "Nature Made Extra Strength Dosage Chewable Vitamin C 1000 mg per serving, Dietary Supplement for Immune Support, 90 Tablets, 45 Day Supply"},
{"price": "$7.49"},
{"bullet_list": "Immune support supplement: contains one 90 count bottle of Nature Made Extra Strength Chewable Vitamin C 1000 mg per serving Tablets for a 45-day supply Nature Made Vitamin C 1000mg per serving is an extra strength dosage chewable Vitamin C antioxidant supplement that supports immune health and offers antioxidant support This 1000 mg per serving Vitamin C supplement provides Vitamin C for adults, which is necessary for the body to produce collagen to help support healthy skin Back in original orange flavor; adults chew two Nature Made Vitamin C chewable tablets daily with a meal Nature Made Chewable Vitamin C 1000mg for adults in two tablets per serving have no color added and no artificial flavors Made in the USA with quality global ingredients, United States Pharmacopeia (USP) Verified, #1 Pharmacist Recommended Vitamin & Supplement Brand* These statements have not been evaluated by the Food and Drug Administration; this product is not intended to diagnose, treat, cure, or prevent any disease"}],
"product_quantity": [{"quantity": "1"},
{"quantity": "1"}],
"product_options": [{"Flavor Name": "Orange"},
{"Size": "90 Count (Pack of 1)"}]
<|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": "2025-04-10T21:36:25.628Z", // 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>

train