公开(公告)号：US20250086395A1

公开(公告)日：2025-03-13

申请号：US18244098

申请日：2023-09-08

Applicant: Maplebear Inc.

Inventor： Prithvishankar Srinivasan ,  Saurav Manchanda ,  Shih-Ting Lin ,  Shishir Kumar Prasad ,  Riddhima Sejpal ,  Luis Manrique ,  Min Xie

IPC: G06F40/30

Abstract: Embodiments relate to utilizing a language model to automatically generate a novel recipe with refined content, which can be offered to a user of an online system. The online system generates a first prompt for input into a large language model (LLM), the first prompt including a plurality of task requests for generating initial content of a recipe. The online system requests the LLM to generate, based on the first prompt input into the LLM, the initial content of the recipe. The online system generates a second prompt for input into the LLM, the second prompt including the initial content of the recipe and contextual information about the recipe. The online system requests the LLM to generate, based on the second prompt input into the LLM, refined content of the recipe. The online system stores the recipe with the refined content in a database of the online system.

公开(公告)号：US11854063B2

公开(公告)日：2023-12-26

申请号：US16734273

申请日：2020-01-03

Applicant: Maplebear, Inc.

Inventor： Mingzhe Zhuang ,  Camille Van Horne ,  Christopher Rudnick ,  Benjamin Knight ,  Chris Jenkins ,  Victoriya Andonova ,  Djordje Gluhovic ,  Riddhima Sejpal ,  Maksim Golivkin ,  Sharath Rao Karikurve

IPC: G06Q30/00 ,  G06Q30/0601

CPC classification number: G06Q30/0635 ,  G06Q30/0639

Abstract: Based on orders fulfilled by shoppers of an online concierge system, the online concierge system identifies items in an order that are difficult to find in a warehouse in which the order is fulfilled. When a shopper obtains a difficult to find item from the warehouse, the online concierge system prompts the shopper to provide information for finding the difficult to find item in the warehouse. The online concierge system stores the information for finding the difficult to find item from the shopper in association with the difficult to find item and with the warehouse. Subsequently, when a different shopper is fulfilling an order from the warehouse including the difficult to find item, the online concierge system displays the information for finding the difficult to find item in the warehouse to the different shopper.

公开(公告)号：US20240320063A1

公开(公告)日：2024-09-26

申请号：US18608368

申请日：2024-03-18

Applicant: Maplebear Inc.

Inventor： Haixun Wang ,  Riddhima Sejpal

IPC: G06F9/54

CPC classification number: G06F9/541

Abstract: An online system receives, from a model serving system, an application programming interface (API) request from a plug-in provided by an online system. The API request includes a list of items obtained from a conversation session of a user with a machine-learned language model application of the model serving system. The online system generates a URL to a landing page for the user for creating a purchase list with the online system based on the list of items. Responsive to receiving a request to access the URL, the online system causes display of the landing page on a client device of the user that displays the purchase list including retailer items for one or more retailers corresponding to the list of items in the API request.

公开(公告)号：US20250028768A1

公开(公告)日：2025-01-23

申请号：US18776104

申请日：2024-07-17

Applicant: Maplebear Inc.

Inventor： Riddhima Sejpal ,  Prithvishankar Srinivasan ,  Luis Manrique

IPC: G06F16/9535 ,  G06F9/451 ,  G06F16/9538 ,  G06Q30/0282 ,  G06Q30/0601

Abstract: An online system performs an inference task in conjunction with the model serving system or the interface system to generate customized recipes for users. The online system identifies a plurality of popular recipes based on historical user search data. The online system uses the collection of popular recipes to generate customized recipes for users based on user data and retailer data. The online system presents a customized recipe to the user, which may include items required to fulfill the recipe, a list of retailers at which the items are available for purchase, and instructions to combine the items. The online system collects user ratings and feedback on customized recipes to calculate a quality score. The online system may use the quality score to rank the customized recipes.

公开(公告)号：US20240078591A1

公开(公告)日：2024-03-07

申请号：US18509157

申请日：2023-11-14

Applicant: Maplebear Inc.

Inventor： Mingzhe Zhuang ,  Camille van Horne ,  Christopher Rudnick ,  Benjamin Knight ,  Chris Jenkins ,  Viktoriya Andonova ,  Djordje Gluhovic ,  Riddhima Sejpal ,  Maksim Golivkin ,  Sharath Rao Karikurve

IPC: G06Q30/0601

CPC classification number: G06Q30/0635 ,  G06Q30/0639

Abstract: Based on orders fulfilled by shoppers of an online concierge system, the online concierge system identifies items in an order that are difficult to find in a warehouse in which the order is fulfilled. When a shopper obtains a difficult to find item from the warehouse, the online concierge system prompts the shopper to provide information for finding the difficult to find item in the warehouse. The online concierge system stores the information for finding the difficult to find item from the shopper in association with the difficult to find item and with the warehouse. Subsequently, when a different shopper is fulfilling an order from the warehouse including the difficult to find item, the online concierge system displays the information for finding the difficult to find item in the warehouse to the different shopper.

公开(公告)号：US20250029173A1

公开(公告)日：2025-01-23

申请号：US18771748

申请日：2024-07-12

Applicant: Maplebear Inc.

Inventor： Riddhima Sejpal ,  Luis Manrique ,  Shiyun Lu ,  Vikrant Verma ,  Nicole Yin Chuen Lee Altman

IPC: G06Q30/0601

Abstract: An online system leverages a machine-learning model to craft personalized meal plans for users. The system generates and presents an interface displaying categories of user preferences. The system receives, from the user via the interface, user preferences for the meal plan. The system generates a prompt including a request to generate the meal plan for the user and the user preferences. The system provides the prompt to the machine-learning model and receives, as output, a meal plan that comprises a list of meals and a list of ingredients for each meal. The system presents the meal plan to the user. The system receives user input to add ingredients to an order and generates an order including the lists of ingredients corresponding to the selected meals.

公开(公告)号：US20200219171A1

公开(公告)日：2020-07-09

申请号：US16734273

申请日：2020-01-03

Applicant: Maplebear, Inc. (dba Instacart)

Inventor： Mingzhe Zhuang ,  Camille Van Horne ,  Christopher Rudnick ,  Benjamin Knight ,  Chris Jenkins ,  Vicky Andonova ,  Djordje Gluhovic ,  Riddhima Sejpal ,  Maksim Golivkin ,  Sharath Rao

IPC: G06Q30/06

Abstract: Based on orders fulfilled by shoppers of an online concierge system, the online concierge system identifies items in an order that are difficult to find in a warehouse in which the order is fulfilled. When a shopper obtains a difficult to find item from the warehouse, the online concierge system prompts the shopper to provide information for finding the difficult to find item in the warehouse. The online concierge system stores the information for finding the difficult to find item from the shopper in association with the difficult to find item and with the warehouse. Subsequently, when a different shopper is fulfilling an order from the warehouse including the difficult to find item, the online concierge system displays the information for finding the difficult to find item in the warehouse to the different shopper.