WO2022134516A1 - Ai服务平台的商品处理方法及装置、电子设备、存储介质、计算机程序产品 - Google Patents

Ai服务平台的商品处理方法及装置、电子设备、存储介质、计算机程序产品 Download PDF

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WO2022134516A1
WO2022134516A1 PCT/CN2021/102559 CN2021102559W WO2022134516A1 WO 2022134516 A1 WO2022134516 A1 WO 2022134516A1 CN 2021102559 W CN2021102559 W CN 2021102559W WO 2022134516 A1 WO2022134516 A1 WO 2022134516A1
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service
sub
attribute
commodity
information
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PCT/CN2021/102559
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English (en)
French (fr)
Inventor
许开平
韩秋明
符柱
刘建成
朱少卿
张春明
沈伟锋
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上海商汤智能科技有限公司
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Publication of WO2022134516A1 publication Critical patent/WO2022134516A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
    • G06Q30/0635—Processing of requisition or of purchase orders

Definitions

  • the present disclosure relates to, but is not limited to, artificial intelligence technology, and in particular, relates to a commodity processing method and device, electronic device, storage medium, computer program product, and computer program of an AI (Artificial Intelligence, artificial intelligence) service platform.
  • AI Artificial Intelligence, artificial intelligence
  • the first is electronic online shopping malls that sell ordinary goods, such as JD.com and Taobao. These platforms mainly sell physical goods and are a one-time transaction process.
  • the second is an electronic online mall that sells services, mainly selling goods that need to provide continuous services.
  • the services sold by electronic online malls that sell service commodities are different from AI services in terms of service composition and sales characteristics. Therefore, existing service models cannot be directly applied to AI services.
  • the embodiments of the present disclosure provide at least one commodity processing method and apparatus, electronic device, storage medium, computer program product, and computer program of an AI service platform.
  • Embodiments of the present disclosure provide a commodity processing method for an AI service platform, the method comprising:
  • the at least one AI service sub-object is combined to obtain a sellable AI service commodity for providing the AI service.
  • Embodiments of the present disclosure provide an apparatus for processing goods of an AI service platform, the apparatus comprising:
  • the information acquisition part is configured to acquire the object information of at least one AI service sub-object;
  • the commodity generating part is configured to combine the at least one AI service sub-object based on the object information to obtain a sellable AI service commodity for providing the AI service.
  • An embodiment of the present disclosure provides an electronic device, including: a memory and a processor, where the memory is configured to store computer-readable instructions, and the processor is configured to invoke the computer instructions to implement the method of any embodiment of the present disclosure.
  • An embodiment of the present disclosure provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, implements some or all of the steps of the method of any embodiment of the present disclosure.
  • An embodiment of the present disclosure provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and when the computer program is read and executed by a computer, any embodiment of the present disclosure can be implemented some or all of the steps in the method.
  • An embodiment of the present disclosure provides a computer program, the computer program includes computer-readable code, and when the computer-readable code is read and executed by a computer, implements part of the method in any embodiment of the present disclosure or all steps.
  • the commodity processing method and device, electronic device, storage medium, computer program product, and computer program of the AI service platform obtain object information of at least one sub-object constituting a commodity through the platform, and generate AI based on the object information.
  • Service commodity which makes it possible to quickly put a new AI service commodity on the shelf.
  • the commodity can be quickly listed through the interface configuration or uploading the configuration file.
  • the developer does not need to code the code for each new commodity, and the efficiency of commodity listing is improved;
  • the commodity service module can automatically generate commodities according to each sub-object, the update of the associated commodity information can also be realized quickly in this way.
  • FIG. 1 is a schematic diagram of the composition and structure of an AI service platform provided by an embodiment of the present disclosure
  • FIG. 2 is a schematic diagram of an AI basic service provided by an embodiment of the present disclosure
  • FIG. 3 is a schematic diagram of an implementation flowchart of a commodity processing method of an AI service platform provided by an embodiment of the present disclosure
  • FIG. 4 is a schematic diagram of object information of an AI service sub-object provided by an embodiment of the present disclosure
  • FIG. 5 is a schematic diagram of object information of an AI service sub-object according to an embodiment of the present disclosure
  • FIG. 6 is a schematic diagram of an AI service commodity provided by an embodiment of the present disclosure.
  • FIG. 7 is a schematic diagram of a synchronization flow of commodity associated information according to an embodiment of the present disclosure.
  • FIG. 8 is a schematic diagram of a synchronization flow of commodity associated information according to an embodiment of the present disclosure.
  • FIG. 9 is a schematic diagram of the composition and structure of a commodity processing device of an AI service platform provided by an embodiment of the present disclosure.
  • FIG. 10 is a schematic diagram of the composition and structure of a commodity processing device of an AI service platform provided by an embodiment of the present disclosure
  • FIG. 11 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present disclosure.
  • the embodiments of the present disclosure provide an AI service platform, which is an electronic online mall for selling AI services. As a commodity sold in the mall, users can easily purchase the AI services they need on the platform.
  • FIG. 1 is a schematic diagram of the composition and structure of an AI service platform provided by an embodiment of the present disclosure.
  • the AI service platform 100 may be constructed in the form of micro-services, which may include but are not limited to: commodity services 110, gateways There are various types of microservice modules such as service 120 and order service 130. Each microservice module is responsible for a function in the platform.
  • the commodity service can be responsible for the generation and listing of products on the platform
  • the gateway service can be responsible for monitoring users' calls to the services sold on the platform
  • the order service can be responsible for processing users' orders for purchasing AI service products.
  • the cooperation of various microservice modules realizes the normal operation of the AI service platform.
  • the embodiment of the present disclosure provides a commodity processing method of an AI service platform, and the method is mainly used to describe the related processing of commodities sold on the platform by the "commodity service” microservice module in the platform.
  • AI service commodity The commodity sold in the platform of the embodiment of the present disclosure may be referred to as an AI service commodity, and each AI service commodity is a complete AI service solution.
  • each AI service commodity can be composed of multiple functional modules, and each functional module can be called an AI service sub-object, that is, the AI service sub-object is one of the components of the AI service commodity that can be sold on the platform.
  • AI service products and service products in related technologies are that AI service products are not simple basic services, but need to integrate basic services and AI algorithms through powerful integration capabilities to provide users with a complete and usable AI solution , and the basic services used in AI service products have their own independent requirements and restrictions.
  • the AI service product is "face verification", which can be used to assist automatic face recognition in access control.
  • face verification which can be used to assist automatic face recognition in access control.
  • the realization of the service function of the product requires the integration of multiple basic services to provide users with a complete and usable solution.
  • These basic services can include: extracting faces from images and extracting facial features from faces Algorithm services, database services for storing face features, algorithm services for comparing the similarity of face features, etc.
  • These basic services can be combined to realize a complete "face verification” solution.
  • These basic services themselves can be used as an AI service sub-object, or a corresponding AI service sub-object can be obtained after performing certain settings on the AI basic service.
  • AI service platform which is an electronic online mall for selling AI services
  • a first system for providing data annotation and model training may be included, and a second system for including various algorithms (eg, face recognition algorithms).
  • Each AI basic service can include at least one service attribute.
  • FIG. 2 is a schematic diagram of an AI basic service provided by an embodiment of the present disclosure.
  • the basic service may include three service attributes: capacity, type, and version. For other types of base services, other service attributes can also be included.
  • Each service attribute may have multiple attribute values, for example, the service attribute "version" may have multiple attribute values such as version I, version II, and version III.
  • the AI service sub-object can include but is not limited to the following two types of objects: one type of sub-object is obtained from AI basic services, and the other type of sub-object can be another AI service commodity .
  • each AI basic service mentioned above may include at least one service attribute, and each service attribute may include multiple settable attribute values.
  • the AI service sub-object can be obtained by setting the attribute value of at least part of the service attribute of the AI basic service to a fixed value.
  • at least one AI service sub-object can be pre-built, so that the basic capability scope of the AI service platform can be determined, and it is convenient to provide capability boundaries for the definition of AI service commodities.
  • the basic service can be a static feature database, and the basic service can include three service attributes: capacity, type and version, where capacity represents the features that the database can store. For example, it can include different attribute values such as 100 million/200 million, and the type indicates the type of features stored in the database, which can include Type I/Type II (such as face features or human body features), and the version can be supported according to the database.
  • the algorithm version is determined, for example, it can include attribute values such as version I/version II.
  • the attribute values of all service attributes such as the capacity and type of the basic service are left to the user who purchased the product to decide, that is, the basic service is not fixed when the product is generated.
  • the attribute values of all service attributes, the basic service shown in Figure 2 is equivalent to the SPU (Standard Product Unit, standard product unit) of the electronic online mall, and the attribute value of each service attribute of the SPU is determined by the user who purchased the AI service product. choose.
  • the SPU can be used as an AI service sub-object, and the attributes of the AI service sub-object are all unfixed attribute values, that is, the definite service attribute values have not yet been set.
  • the attribute values of all service attributes of the basic service shown in FIG. 2 are fixed when the product is generated, for example, the version is fixed as version 1, the capacity is fixed as 100 million, and the type is fixed as Type II. That is, when generating an AI service product including the basic service, each service attribute of the basic service has been preset with attribute values, and users do not need to select it by themselves.
  • the basic service is equivalent to a kind of SKU (Stock Keeping Unit, inventory unit of measure). It can also be understood in this way that an SPU represents a product, and SKU represents one of the specific attributes and specifications of the product.
  • An SPU product can have one or more SKUs, and the SKU can also be used as an AI service sub-object.
  • the attributes in the sub-object are all fixed attribute values, that is, each attribute already has a certain attribute value.
  • the attribute values of some service attributes of the SPU are fixed, for example, the service attribute "version" of the basic service shown in Figure 2 is fixed to version I, the capacity is fixed to 100 million, and the type is handed over to the purchase of AI services. User selection of the item. In this way, the SPU and some of the solidified attribute values can be combined to obtain an AI service sub-object. That is, the part of the property value that is not cured in the SPU).
  • the AI service sub-object can also be an AI service commodity, that is, another AI service commodity is used as a component of this AI service commodity.
  • FIG. 3 is a schematic diagram of a real-time implementation flowchart of a commodity processing method of an AI service platform provided by an embodiment of the present disclosure.
  • the method may be executed by a commodity service microservice module of the AI service platform, and the method may include the following Step S300 and Step S302:
  • step 300 object information of at least one AI service sub-object is acquired.
  • object information of multiple AI service sub-objects used to generate AI service goods can be obtained.
  • object information of multiple AI service sub-objects used to generate AI service goods can be obtained.
  • FIG. 4 is a schematic diagram of object information of an AI service sub-object provided by an embodiment of the present disclosure.
  • the AI service sub-object is obtained based on a first AI basic service, and the first AI basic service is an SPU . It also specifies that some service attributes in the first AI basic service will be solidified. For example, if the capacity is solidified to 100 million, the capacity is a solidified attribute value, and the version is solidified to version II, and the version is also a solidified attribute value. The type of this property may not harden the property value.
  • SPU+ part of the solidified attribute value (solidified the capacity, version, etc. of the attribute value) obtains an AI service sub-object, which can be called the first sub-object.
  • the AI service commodity may include one AI service sub-object, for example, only the above-mentioned first sub-object.
  • the AI service product may also include more than one number of first sub-objects, for example, including two first sub-objects.
  • the capacity, version, and type in FIG. 4 may be referred to as the first attribute, wherein the capacity and version may be referred to as a cured attribute value, and the type may be referred to as an uncured attribute value.
  • the first attribute is also used as the attribute of the AI service product. When the user buys the AI service product, he can select and set the uncured attribute value and set it to the attribute value that suits his needs. For example, when the user buys the product, he can set the value to be purchased.
  • the type attribute of the item is Type I.
  • FIG. 5 is a schematic diagram of object information of an AI service sub-object provided by an embodiment of the present disclosure.
  • the sub-object is a kind of SKU, which solidifies all service attributes of a basic service.
  • This sub-object may be referred to as the second sub-object.
  • the AI service sub-object may also be another AI service item (which may be referred to as the first AI service item), or may also be an SPU.
  • An AI service product can be any combination of the above-mentioned SPU, SKU, AI service product, SPU+partially solidified attribute value and other types of AI service sub-objects.
  • the object information of the AI service sub-object is obtained, which may include but is not limited to the following obtaining methods:
  • the object information of the AI service sub-object may be obtained by receiving object configuration information of the human-computer interaction configuration.
  • the manager of the AI service platform can configure the product information of a new AI service product to be put on the shelf through the human-computer interaction management interface of the platform, which can include each AI service sub-object that constitutes the AI service product, which can be
  • For each AI service sub-object configure the information of the AI basic service included in the AI service sub-object, including configuring at least one attribute included in the AI basic service, and set each attribute as a fixed attribute value or a non-fixed attribute value.
  • a user can configure an AI service sub-object, and the AI service sub-object includes a certain SKU, wherein various attributes such as capacity and version in the SKU are fixed.
  • the commodity service microservice module of the platform can obtain the AI service sub-object based on the configuration of the AI basic service according to the received object information.
  • an AI can be generated according to the SPU configured by the user and the fixed attribute value in the configured SPU. Service sub-objects, and combine these AI service sub-objects to obtain AI service products.
  • the object configuration file can also be uploaded to the platform, and the commodity service module of the platform can parse the object configuration file, obtain the object information of each sub-object constituting the AI service commodity, and generate the object information according to the object information of each sub-object A new AI service commodity.
  • step 302 based on the object information, the at least one AI service sub-object is combined to obtain a sellable AI service commodity for providing the AI service.
  • the commodity service micro-service module may combine at least one AI service sub-object according to the object information obtained in step 300 to generate a sellable AI service commodity.
  • the attribute value of the AI basic service can be fixed, for example, the attribute value of some service attributes of the first AI basic service in FIG.
  • the attribute values of all service attributes of the AI are fixed and set, and each sub-object is combined to obtain AI service products.
  • FIG. 6 is a schematic diagram of an AI service commodity provided by an embodiment of the present application. As shown in FIG. 6 , the commodity can be obtained by combining the first sub-object shown in FIG. 4 and the second sub-object shown in FIG. 5 .
  • the commodity is a complete solution for AI services.
  • Each sub-object in the commodity can include an AI basic service, and the attributes of each AI service sub-object can include fixed attribute values and/or unfixed attribute values. , that is, all attribute values of the object may be solidified, or all attribute values may not be solidified, or some attribute values may be solidified.
  • the curing refers to that a certain attribute value has been set, for example, the version is set to version I.
  • the uncured attribute value refers to the existence of a certain attribute, but the specific attribute value can be set by the user who purchased the product. For example, when the user purchases an AI service product, the user sets the capacity attribute of the product to be purchased. One hundred million.
  • the sub-objects that make up the AI service product may be any one or more of a combination of SPU/SKU/another AI service product/SPU and a partially cured attribute value of the SPU.
  • each AI service sub-object when generating an AI service commodity.
  • it can be combined according to the processing logic of the AI service as a commodity, so that each AI service sub-object cooperates to realize the AI service according to the processing logic of the AI service.
  • the sub-object responsible for face detection can first identify the face from the input image, and extract the face features of the face image, and then the sub-object responsible for database retrieval can identify the face from the input image. The face in the database that matches the face feature is retrieved according to the face feature, so as to determine whether the face in the input image passes the verification.
  • the object information of at least one sub-object constituting the commodity is obtained through the platform, and the AI service commodity is generated according to the object information, so that a new AI service commodity can be put on the shelf relatively quickly.
  • the way of configuring or uploading configuration files can quickly put products on the shelves, and developers do not need to code codes for each new product, which improves the efficiency of product listing; and when the information of sub-objects included in the product needs to be changed, because the product service module can automatically Commodities are generated according to each sub-object, and related commodity information can be updated quickly in this way.
  • the AI service sub-object as a component thereof may include various types, for example, the sub-object may be an SPU, a SKU, another AI service commodity, or another AI service commodity. It can be SPU and some solidified attribute values, etc.
  • This multi-type sub-object can meet the user needs of various AI service products. For example, users may not be familiar with the service attributes of basic services.
  • an AI service platform puts on the shelf a new AI service product, it often involves information synchronization between multiple microservice modules in the platform. For example, when a new product is launched, it is not only possible to configure the object information of each AI service sub-object included in the AI service product, that is, to indicate which sub-objects the product is composed of.
  • some commodity related information of the new commodity can also be configured.
  • the commodity related information includes but is not limited to: the setting of some purchase conditions of the commodity when it is purchased, or the statistical method of the usage of the commodity after the commodity is sold. Definition, etc.
  • the commodity related information can be provided to other related service modules of the AI service platform, so that the service modules can process the related business (eg purchase/usage statistics) of the AI service commodity accordingly.
  • the commodity related information configured when the AI service commodity is put on the shelf may include: usage statistics of the AI service commodity, for example, the information that needs to be used when invoking the service provided by the AI service commodity API (Application Programming Interface, application programming interface), and the definition of statistical information that counts the usage of the service. Statistics on service usage can provide data basis for subsequent billing, and can also monitor that users do not exceed the service volume corresponding to the product when using the service. As shown in FIG.
  • the administrator of the platform can configure the usage statistics of the commodity in the commodity service 110 when the AI service commodity is listed, and the commodity service 110 of the platform can send the usage statistics to the gateway service 120 of the platform, such as
  • the API used when calling the AI service provided by the AI service product can be sent to the gateway service, so that the gateway service can establish the mapping relationship between the API and the AI service product, and monitor the user for the product according to the mapping relationship.
  • the AI service platform may also include a logging module responsible for recording service invocation information. By calling the service invocation information recorded by the logging module, the platform can count the usage of AI service products.
  • an AI service product can be used to provide face verification services for access control monitoring images
  • the user can use the service provided by the product by calling the relevant API.
  • the user can upload the face image to be compared by calling the service, and the commodity service can perform face comparison and verification, and finally return the verification result to the user.
  • the gateway service will count the number of pictures uploaded by the user by monitoring API calls. When the statistics find that the user has uploaded 100,000 pictures for face verification, it will Use of this service is no longer allowed.
  • the commodity service purchased by the user can also be 50 video streams
  • the gateway service can count the number of video streams accessed by the user by monitoring API calls to ensure that the number of video streams accessed by the user does not exceed the number of purchased video streams. product limited.
  • the commodity associated information configured when the AI service commodity is put on the shelf may further include: selling attribute information of the AI service commodity.
  • the selling attribute information may be a purchase condition when the user purchases the AI service product. For example, when purchasing a certain product, the condition is to purchase a face verification service with at least 5,000 pictures.
  • the commodity service module of the platform can send the sales attribute information to the order service of the platform, so that the order service can verify the purchase conditions of the order of the AI service commodity accordingly.
  • the platform administrator can configure the selling attribute information of the product in the product service 110 when the AI service product is listed.
  • the service 110 receives the sales attribute information of the AI service product, and verifies whether the information in the order meets the purchase conditions defined in the sales attribute information according to the sales attribute information.
  • the sales attribute information defines a minimum purchase of 5,000 pieces
  • the commodity service module can actively push commodity-related information to other modules in the platform, such as an order service or a gateway service module. It can also be that other modules actively go to the commodity service module to pull the required information.
  • the AI service sub-object includes a first sub-object;
  • the object information includes at least one first attribute;
  • the foregoing step S300 may include: acquiring at least one first sub-object, and each of the first At least one first attribute included in the sub-object, the at least one first attribute includes a cured attribute value and/or an uncured attribute value;
  • the above step S302 may include: based on the at least one first attribute, for the at least one first attribute A sub-object is combined to obtain an AI service product, and the at least one first attribute is used as an attribute of the AI service product.
  • the AI service sub-object further includes a second sub-object;
  • the object information further includes at least one second attribute;
  • the above step S300 may further include: acquiring at least one second sub-object, and each at least one second attribute included in the second sub-object, the at least one second attribute includes a cured attribute value and/or an uncured attribute value;
  • the above step S302 may include: based on the at least one first attribute and the at least one A second attribute, the at least one first sub-object and the at least one second sub-object are combined to generate the AI service product, the at least one first attribute and the at least one second attribute are used as the Describe the attributes of AI service products.
  • the method further includes: receiving attribute modification information, where the attribute modification information includes: after setting the fixed attribute value and/or the unfixed attribute value of the AI service sub-object in the AI service commodity new attribute value; obtain an updated AI service sub-object according to the attribute modification information, and the updated AI service sub-object includes the new attribute value; generate an updated AI service sub-object based on the updated AI service sub-object The AI service commodity.
  • the AI service sub-object is a sub-object of any one of the following types: a SPU, a SKU, a combination of an SPU and a partially cured attribute value of the SPU, another AI service commodity.
  • the above step S300 may include: receiving object configuration information; the object configuration information includes: the AI basic service included in the AI service sub-object, and at least one attribute included in the set AI basic service, The attribute includes a fixed attribute value and/or an unfixed attribute value; the AI service sub-object is obtained based on the AI basic service and at least one attribute included in the AI basic service.
  • the method may further include: step S311, obtaining the commodity related information of the AI service commodity; step S312, sending the commodity related information to the corresponding service module, so that the service module according to The commodity related information processes the related business of the AI service commodity.
  • the commodity associated information includes: an invocation interface when invoking the AI service provided by the AI service commodity; the above step S312 may include: sending the invocation interface corresponding to the AI service commodity to the corresponding gateway service , so that the gateway service establishes a mapping relationship between the calling interface and the AI service commodity, and monitors the invocation of the AI service commodity according to the mapping relationship.
  • the commodity association information includes: selling attribute information of the AI service commodity, and the selling attribute information includes: purchase conditions when the user purchases the AI service commodity; the above step S312 may include: adding the all The sales attribute information is sent to the corresponding order service, so that the order service verifies the purchase conditions of the order for the AI service product according to the sales attribute information.
  • the commodity processing method provided by the embodiments of the present disclosure can facilitate the developers and managers of the AI service platform to develop and maintain commodities, not only can new AI service commodities be listed quickly, but also can automatically synchronize commodity-related information to the platform other service modules, so that other service modules can perform purchase condition verification, service usage statistics and other commodity-related business processing according to commodity-related information, so as to complete the configuration related to commodity shelves relatively quickly.
  • the object information of at least one AI service sub-object that constitutes a product is defined, it can be deployed directly, which reduces the workload of developers needing to write codes for new products each time, and makes the process of listing new products more automated.
  • the product service module of the embodiment of the present disclosure Attribute modification information may be received, the attribute modification information including the set new attribute value, such as the above-mentioned version II.
  • the commodity service module can update the attribute value of the corresponding AI service sub-object in the commodity according to the attribute modification information, and obtain the updated AI service sub-object including the above-mentioned new attribute value.
  • the AI service product including the object will also be updated.
  • SPU/SKU information services that are not strongly related to product information (such as order services) do not need to be changed, and the displayed content can be changed automatically according to the change of product information.
  • the gateway service may need to be changed according to the specific situation, which can also greatly reduce the upper-layer services affected by the change of the underlying service, thereby reducing the scope of code changes in the entire system and reducing the possibility of errors.
  • FIG. 9 is a schematic diagram of the composition and structure of a commodity processing device of an AI service platform provided by an embodiment of the present application. As shown in FIG. 9 , the device may include an information acquisition part 91 and a commodity generation part 92 .
  • an information acquisition part 91 configured to acquire object information of at least one AI service sub-object
  • the commodity generating part 92 is configured to combine the at least one AI service sub-object based on the object information to obtain a sellable AI service commodity for providing the AI service.
  • the AI service sub-object includes a first sub-object; the object information includes at least one first attribute; the information acquisition part 91, in the case of being configured to acquire object information of at least one AI service sub-object , and is further configured to: acquire at least one first sub-object and at least one first attribute included in each of the first sub-objects, where the at least one first attribute includes a cured attribute value and/or an uncured attribute value.
  • the commodity generation part 92 when configured to combine the at least one AI service sub-object based on the object information to obtain a salable AI service commodity for providing AI services, is further configured to:
  • the at least one first attribute is combined with the at least one first sub-object to obtain an AI service product, and the at least one first attribute is used as an attribute of the AI service product.
  • the AI service sub-object further includes a second sub-object; the object information further includes at least one second attribute; the information acquisition part 91 is configured to acquire the object information of the at least one AI service sub-object. In this case, it is further configured to: obtain at least one second sub-object and at least one second attribute included in each of the second sub-objects, where the at least one second attribute includes a cured attribute value and/or an uncured attribute value .
  • the commodity generation part 92 when configured to combine the at least one AI service sub-object based on the object information to obtain a salable AI service commodity for providing AI services, is further configured to: the at least one first attribute and the at least one second attribute, and combining the at least one first sub-object and the at least one second sub-object to obtain the AI service product, the at least one first attribute and the at least one second attribute as the attribute of the AI service product.
  • the information acquisition part 91 is further configured to receive attribute modification information; the attribute modification information includes: setting the solidified attribute value and/or the unfixed attribute value of the AI service sub-object in the AI service commodity The new property value after .
  • the commodity generation part 92 is further configured to obtain an updated AI service sub-object according to the attribute modification information, and the updated AI service sub-object includes the new attribute value; based on the updated AI service sub-object; object to generate the updated AI service product.
  • the AI service sub-object is a sub-object of any one of the following types: a SPU, a SKU, a combination of an SPU and a partially cured attribute value of the SPU, another AI service commodity.
  • the information acquisition part 91 when configured to acquire object information of at least one AI service sub-object, is further configured to: receive object configuration information; the object configuration information includes: the AI service sub-object The AI basic service included in the set, the set at least one attribute included in the AI basic service, the attribute includes a fixed attribute value and/or an unfixed attribute value; based on the AI basic service and the AI basic service includes at least one attribute A property that gets the AI service child object.
  • the apparatus may further include: an information synchronization part 93 .
  • the information synchronization part 93 is configured to obtain the commodity related information of the AI service commodity; and send the commodity related information to the corresponding service module, so that the service module can perform the relevant information on the AI service commodity according to the commodity related information. Associated business for processing.
  • the commodity associated information includes: an invocation interface when invoking the AI service provided by the AI service commodity; the information synchronization part 93 is further configured to send the invocation interface corresponding to the AI service commodity to a corresponding gateway service, so that the gateway service establishes a mapping relationship between the calling interface and the AI service commodity, and monitors the invocation of the AI service commodity according to the mapping relationship.
  • the commodity association information includes: selling attribute information of the AI service commodity, and the selling attribute information includes: purchasing conditions when the user purchases the AI service commodity; the information synchronization part 93 is further configured to The selling attribute information is sent to the corresponding order service, so that the order service verifies the purchase conditions of the order of the AI service product according to the selling attribute information.
  • a "part" may be a part of a circuit, a part of a processor, a part of a program or software, etc., of course, a unit, a module or a non-modularity.
  • one or more embodiments of the present disclosure may be provided as a method, system, electronic device, computer storage medium, computer program product or computer program. Accordingly, one or more embodiments of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the present disclosure may employ one or more computer-usable storage media (including but not limited to disk storage, CD-ROM (Compact Disc Read-Only Memory, portable compressed in the form of a computer program product implemented on a disk read-only memory), optical memory, etc.).
  • CD-ROM Compact Disc Read-Only Memory
  • optical memory etc.
  • Embodiments of the present disclosure further provide a computer-readable storage medium, which may be a volatile storage medium or a non-volatile storage medium; a computer program may be stored on the storage medium, and when the program is executed by a processor Part or all of the steps of the commodity processing method of the AI service platform described in any embodiment of the present disclosure are implemented.
  • a computer-readable storage medium which may be a volatile storage medium or a non-volatile storage medium
  • a computer program may be stored on the storage medium, and when the program is executed by a processor Part or all of the steps of the commodity processing method of the AI service platform described in any embodiment of the present disclosure are implemented.
  • An embodiment of the present disclosure provides a computer program product, the computer program product includes a non-transitory computer-readable storage medium storing a computer program, and when the computer program is read and executed by a computer, the Part or all of the steps of the described AI service platform's commodity processing method.
  • Embodiments of the present disclosure provide a computer program, where the computer program includes computer-readable codes, and when the computer-readable codes are read and executed by a computer, realizes the AI service platform described in the embodiments of the present disclosure. Some or all of the steps in a method of processing an item.
  • An embodiment of the present disclosure further provides an electronic device, which includes: a memory and a processor, where the memory is configured to store computer-readable instructions, and the processor is configured to invoke the computer instructions to implement any implementation of the present disclosure
  • FIG. 11 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present disclosure.
  • the electronic device 1010 includes a processor 1011 , and may further include an input device 1012 , an output device 1013 and a memory 1014 .
  • the input device 1012, the output device 1013, the memory 1014 and the processor 1011 are connected to each other through a bus.
  • Memory includes but is not limited to RAM (Random Access Memory, random storage memory), ROM (Read-Only Memory, read-only memory), EPROM (Erasable Programmable Read Only Memory, erasable programmable read-only memory), EEPROM ( Electrically Erasable Programmable Read Only Memory), CD-ROM or DVD-ROM (Digital Video Disc Read-Only Memory), which is used to store related instructions and data.
  • RAM Random Access Memory
  • ROM Read-Only Memory, read-only memory
  • EPROM Erasable Programmable Read Only Memory, erasable programmable read-only memory
  • EEPROM Electrically Erasable Programmable Read Only Memory
  • CD-ROM or DVD-ROM Digital Video Disc Read-Only Memory
  • Input means are used for inputting data and/or signals, and output means are used for outputting data and/or signals.
  • the output device and the input device can be independent devices or an integral device.
  • the processor may include one or more processors, such as one or more CPUs (Central Processing Unit, central processing unit).
  • processors Central Processing Unit, central processing unit
  • the CPU may be a single-core CPU or a Multi-core CPU.
  • Memory is used to store program codes and data for network devices.
  • the processor is configured to call the program code and data in the memory to execute the steps in the above method embodiments.
  • the processor is configured to call the program code and data in the memory to execute the steps in the above method embodiments.
  • the processor is configured to call the program code and data in the memory to execute the steps in the above method embodiments.
  • the description in the method embodiment please refer to the description in the method embodiment.
  • FIG. 11 only shows a simplified design of an electronic device.
  • the electronic device may also include other necessary elements, including but not limited to any number of input/output devices, processors, controllers, memories, etc., and all electronic devices that can implement the embodiments of the present disclosure are in within the scope of the present disclosure.
  • the "and/or" means at least one of the two, for example, "A and/or B" includes three schemes: A, B, and "A” and B".
  • Embodiments of the subject matter and functional operations described in the embodiments of the present disclosure can be implemented in digital electronic circuits, computer software or firmware in tangible embodiment, computer hardware including the structures disclosed in the embodiments of the present disclosure and their structural equivalents , or a combination of one or more of them.
  • Embodiments of the subject matter described in embodiments of the present disclosure may be implemented as one or more computer programs, ie, computer program instructions encoded on a tangible, non-transitory program carrier for execution by, or to control the operation of, data processing apparatus. one or more parts.
  • the program instructions may be encoded on an artificially generated propagated signal, such as a machine-generated electrical, optical or electromagnetic signal, which is generated to encode and transmit information to a suitable receiver device for interpretation by the data.
  • the processing device executes.
  • the computer storage medium may be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or a combination of one or more of these.
  • the processes and logic flows described in the embodiments of the present disclosure can be performed by one or more programmable computers executing one or more computer programs to perform corresponding functions by operating on input data and generating output.
  • the processing and logic flow can also be performed by dedicated logic circuits such as FPGA (Field Programmable Gate Array, Field Programmable Gate Array) or ASIC (Application Specific Integrated Circuit, Application Specific Integrated Circuit), and the device can also be implemented as dedicated logic circuit.
  • Computers suitable for the execution of a computer program include, for example, general and/or special purpose microprocessors, or any other type of central processing unit.
  • the central processing unit will receive instructions and data from read only memory and/or random access memory.
  • the basic components of a computer include a central processing unit for implementing or executing instructions and one or more memory devices for storing instructions and data.
  • a computer will also include, or be operatively coupled to, one or more mass storage devices for storing data, such as magnetic, magneto-optical or optical disks, to receive data therefrom or to It transmits data, or both.
  • the computer does not have to have such a device.
  • the computer can be embedded in another device, such as a mobile phone, a PDA (Personal Digital Assistant), a mobile audio or video player, a game console, a GPS (Global Positioning System) receiver, Or portable storage devices such as USB (Universal Serial Bus) flash drives, to name a few.
  • a mobile phone a PDA (Personal Digital Assistant)
  • PDA Personal Digital Assistant
  • mobile audio or video player a mobile audio or video player
  • game console a GPS (Global Positioning System) receiver
  • portable storage devices such as USB (Universal Serial Bus) flash drives, to name a few.
  • USB Universal Serial Bus
  • Computer-readable media suitable for storage of computer program instructions and data include all forms of non-volatile memory, media, and memory devices including, for example, semiconductor memory devices (eg, EPROM, EEPROM, and flash memory devices), magnetic disks (eg, internal hard disks or memory devices). removable discs), magneto-optical discs, and CD-ROM and DVD-ROM discs.
  • semiconductor memory devices eg, EPROM, EEPROM, and flash memory devices
  • magnetic disks eg, internal hard disks or memory devices. removable discs
  • magneto-optical discs e.g., CD-ROM and DVD-ROM discs.
  • the processor and memory may be supplemented by or incorporated in special purpose logic circuitry.
  • Embodiments of the present disclosure provide a commodity processing method and device, electronic device, storage medium, computer program product, and computer program of an AI service platform, wherein the method includes: acquiring object information of at least one AI service sub-object; The object information is combined, and the at least one AI service sub-object is combined to obtain salable AI service commodities for providing AI services.
  • the platform obtains the object information of at least one sub-object that constitutes the commodity, and generates an AI service commodity according to the object information, so that a new AI service commodity can be put on the shelf relatively quickly. According to the embodiments of the present disclosure, it is possible to make the AI service platform launch a new AI service commodity relatively quickly.

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Abstract

本公开实施例提供一种AI服务平台的商品处理方法及装置、电子设备、存储介质、计算机程序产品、计算机程序，其中，该方法可以包括：获取至少一个AI服务子对象的对象信息；基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品。本公开实施例通过平台获取组成商品的至少一个子对象的对象信息，并据此对象信息生成AI服务商品，使得可以较快的上架一个新的AI服务商品。

Description

AI服务平台的商品处理方法及装置、电子设备、存储介质、计算机程序产品
相关申请的交叉引用
本公开基于申请号为202011534123.5、申请日为2020年12月22日、申请名称为“AI服务平台的商品处理方法及装置、电子设备和存储介质”的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本公开作为参考。
技术领域
本公开涉及但不限于人工智能技术，尤其涉及一种AI(Artificial Intelligence，人工智能)服务平台的商品处理方法及装置、电子设备、存储介质、计算机程序产品、计算机程序。
背景技术
目前主要有两种类型的电子线上商城：第一种是售卖普通商品的电子线上商城，类似京东、淘宝之类的，这些平台主要售卖的是实体商品，并且属于一次性的交易过程。第二种是售卖服务的电子线上商城，主要售卖的是需要提供持续性服务的商品。通过第二种类型的线上商城，能够更加方便的向用户提供多种类型的服务，用户也可以通过该线上商场选购满足自己需要的服务类商品。在相关技术中，售卖服务类商品的电子线上商城所售卖的服务与AI服务相比，在服务构成方式以及售卖特点上是不同的，因此，对于AI服务不能直接套用已有服务模型。
发明内容
本公开实施例至少提供一种AI服务平台的商品处理方法及装置、电子设备、存储介质、计算机程序产品、计算机程序。
本公开实施例提供一种AI服务平台的商品处理方法，所述方法包括：
获取至少一个AI服务子对象的对象信息；
基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品。
本公开实施例提供一种AI服务平台的商品处理装置，所述装置包括：
信息获取部分，配置为获取至少一个AI服务子对象的对象信息；
商品生成部分，配置为基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品。
本公开实施例提供一种电子设备，包括：存储器、处理器，所述存储器配置为存储计算机可读指令，所述处理器配置为调用所述计算机指令，实现本公开任一实施例的方法。
本公开实施例提供一种计算机可读存储介质，其上存储有计算机程序，所述程序被处理器执行时实现本公开任一实施例的方法的部分或全部步骤。
本公开实施例提供一种计算机程序产品，所述计算机程序产品包括存储了计算机程序的非瞬时性计算机可读存储介质，所述计算机程序被计算机读取并执行时，实现本公开任一实施例中的方法的部分或全部步骤。
本公开实施例提供一种计算机程序，所述计算机程序包括计算机可读代码，在所述计算机可读代码被计算机读取并执行的情况下，实现本公开任一实施例中的方法的部分或全部步骤。
本公开实施例提供的AI服务平台的商品处理方法及装置、电子设备、存储介质、计算机程序产品、计算机程序，通过平台获取组成商品的至少一个子对象的对象信息，并据此对象信息生成AI服务商品，使得可以较快地上架一个新的AI服务商品，比如，可以通过界面配置或者上传配置文件的方式，快速上架商品，开发人员不需要为每一个新商品编码代码，商品上架效率提高；并且，当要更改商品中包括的子对象的信息时，由于商品服务模块能够自动根据各个子对象生成商品，通过这种方式也能够较快地实现关联的商品信息的更新。
附图说明
为了更清楚地说明本公开一个或多个实施例或相关技术中的技术方案，下面将对本公开实施例或相关技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本公开一个或多个实施例中记载的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本公开实施例提供的一种AI服务平台的组成结构示意图；
图2为本公开实施例提供的一种AI基础服务的示意图；
图3为本公开实施例提供的一种AI服务平台的商品处理方法的实现流程示意图；
图4为本公开实施例提供的一种AI服务子对象的对象信息的示意图；
图5为本公开实施例提供的一种AI服务子对象的对象信息的示意图；
图6为本公开实施例提供的一种AI服务商品的示意图；
图7为本公开实施例提供的一种商品关联信息的同步流程示意图；
图8为本公开实施例提供的一种商品关联信息的同步流程示意图；
图9为本公开实施例提供的一种AI服务平台的商品处理装置的组成结构示意图；
图10为本公开实施例提供的一种AI服务平台的商品处理装置的组成结构示意图；
图11为本公开实施例提供的一种电子设备的硬件结构示意图。
具体实施方式
为了使本技术领域的人员更好地理解本公开一个或多个实施例中的技术方案，下面将结合本公开一个或多个实施例中的附图，对本公开一个或多个实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本公开一部分实施例，而不是全部的实施例。基于本公开一个或多个实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都应当属于本公开保护的范围。
随着AI技术的不断发展，用户对AI服务的需求越来越多，本公开实施例提供了一种AI服务平台，该平台是一种用于售卖AI服务的电子线上商城，将AI服务作为商城 售卖的商品，用户可以在平台上方便地选购自己所需的AI服务。
图1为本公开实施例提供的一种AI服务平台的组成结构示意图，如图1所示，该AI服务平台100可以通过微服务的方式构建，其中可以包括但不限于：商品服务110、网关服务120、订单服务130等多种类型的微服务模块，每个微服务模块都分别负责平台中的一种功能。例如，商品服务可以负责平台商品的生成和上架，网关服务可以负责监听用户对平台售卖的服务的调用，订单服务可以负责处理用户购买AI服务商品的订单。多种微服务模块的协同配合实现AI服务平台的正常运转。
本公开实施例提供了一种AI服务平台的商品处理方法，该方法主要用于说明平台中的“商品服务”微服务模块对平台售卖的商品的相关处理。在进行该方法的说明之前，为了使得方案更容易理解，首先介绍如下的基础概念：
AI服务商品：本公开实施例的平台中售卖的商品可以称为AI服务商品，每一个AI服务商品是一个完整的AI服务方案。其中，每个AI服务商品可以由多个功能模块组成，每一个功能模块都可以称为一种AI服务子对象，即AI服务子对象是平台中的可售卖的AI服务商品的其中一个组成部分。AI服务商品和相关技术中的服务商品的不同在于，AI服务商品不是简单的基础服务，而是需要通过强大的整合能力，把基础服务和AI算法整合在一起提供给用户一个完整可用的AI方案，并且AI服务商品中使用的基础服务本身又有各自独立的要求和限制条件。
例如，假设AI服务商品是“人脸验证”，可以用于辅助门禁自动人脸识别。那么，该商品的服务功能的实现，需要多种基础服务整合在一起才能提供给用户一个完整可用的方案，这些基础服务可以包括：用于从图像提取人脸并从人脸提取人脸特征的算法服务、用于存储人脸特征的数据库服务、用于进行人脸特征相似度比较的算法服务，等，这些基础服务组合起来才能够实现一个“人脸验证”的完整方案。这些基础服务本身可以作为一个AI服务子对象，或者也可以是将AI基础服务进行某些设置处理后得到一个对应的AI服务子对象。在作为用于售卖AI服务的电子线上商城的AI服务平台上，用户看到的是AI服务商品，而该商品中包括的每一种AI基础服务可以是由支撑系统提供，该支撑系统例如可以包括用于提供数据标注和模型训练的第一系统，以及用于包括各种算法(如，人脸识别算法)的第二系统。
每一种AI基础服务都可以包括至少一种服务属性。请参见图2，图2为本公开实施例提供的一种AI基础服务的示意图，该基础服务可以包括三种服务属性：容量、类型、版本。对于其他类型的基础服务，也可以包括其他的服务属性。每种服务属性可以具有多种属性值，例如，服务属性“版本”可以是版本I、版本II、版本III等多种属性值。
AI服务子对象：该AI服务子对象可以包括但不限于如下两种类型的对象：一种类型的子对象是根据AI基础服务得到的，另一种类型的子对象可以是另一个AI服务商品。例如，上述提到每一种AI基础服务都可以包括至少一种服务属性，并且每一种服务属性可以包括多种可设置的属性值。将AI基础服务的至少部分的服务属性的属性值设置为固定值，就可以得到AI服务子对象。在实施时，可以预先构建至少一个AI服务子对象，从而可以确定AI服务平台的基础能力范围，便于给AI服务商品的定义提供能力边 界。
仍以图2所示的基础服务为例，例如，该基础服务可以是一种静态特征数据库，该基础服务可以包括三种服务属性：容量、类型和版本，其中，容量表示数据库能够存储的特征的量，比如可以包括一亿/两亿等不同属性值，类型表示该数据库存储的特征的类型，可以包括类型I/类型II等(比如人脸特征或者人体特征)，版本可以根据该数据库支持的算法版本确定，比如可以包括版本I/版本II等属性值。如果在将包括该基础服务的AI服务商品上架时，该基础服务的容量、类型等所有服务属性的属性值都交由购买该商品的用户去决定，即在生成商品时不固定该基础服务的所有服务属性的属性值，则图2所示的基础服务即相当于电子线上商城的SPU(Standard Product Unit，标准产品单元)，SPU的各服务属性的属性值由购买AI服务商品的用户去选择。该SPU可以作为一种AI服务子对象，该AI服务子对象的属性都是未固化属性值，即还都尚未设置确定的服务属性值。
在又一个例子中，假如在生成商品时，将图2所示的基础服务的所有服务属性的属性值均固定，例如，版本固定设置为版本I，容量固定设置为一亿，类型固定设置为类型II。即在生成包括该基础服务的AI服务商品时，该基础服务的各个服务属性均已经被预先设置了属性值，不需要用户再自行选择，该基础服务即相当于一种SKU(Stock Keeping Unit，库存计量单位)。也可以这么理解，一个SPU代表一个产品，SKU代表产品的其中一种特定的属性与规格，一个SPU产品可以有一个或多个SKU，SKU也可以作为一种AI服务子对象。SKU作为AI服务子对象时，该子对象中的属性都是固定属性值，即各属性都已经具有了确定的属性值。
此外，如果将SPU的部分服务属性的属性值固定，例如，将图2所示的基础服务的服务属性“版本”固定设置为版本I，容量固定设置为一亿，而类型交由购买AI服务商品的用户选择。这种方法下该SPU、以及其中一部分固化属性值组合可以得到一种AI服务子对象，该子对象中既包括固化属性值(即SPU固化的那部分属性值)，也包括未固化属性值(即SPU中未固化的那部分属性值)。
AI服务子对象还可以是一种AI服务商品，即将另一种AI服务商品作为本AI服务商品的组成部分。
在了解了上述基础概念说明后，如下结合图3描述本公开实施例提供的AI服务平台的商品处理方法。图3为本公开实施例提供的一种AI服务平台的商品处理方法的时实现流程示意图，如图3所示，该方法可以由AI服务平台的商品服务微服务模块执行，该方法可以包括如下步骤S300和步骤S302：
在步骤300中，获取至少一个AI服务子对象的对象信息。
本步骤中，可以获取到用于生成AI服务商品的多个AI服务子对象的对象信息。如下示例几种对象信息：
图4为本公开实施例提供的一种AI服务子对象的对象信息的示意图，如图4所示，该AI服务子对象是基于第一AI基础服务得到，该第一AI基础服务是一个SPU。并且还指定了将该第一AI基础服务中的部分服务属性进行固化，比如，将容量固化为一亿，该容量就是一个固化属性值，将版本固化为版本II，版本也是一个固化属性值。类型这 个属性可以不固化属性值。如图4所示，SPU+其中部分固化属性值(固化了属性值的容量、版本等)得到一个AI服务子对象，可以称为第一子对象。在一些实施例中，AI服务商品中可以包括一个AI服务子对象，例如只包括上述的第一子对象。在一些实施例中，AI服务商品中也可以包括多于一个数量的第一子对象，例如包括两个第一子对象。图4中的容量、版本、类型可以称为第一属性，其中的容量和版本可以称为固化属性值，类型可以称为未固化属性值。第一属性也作为AI服务商品的属性，当用户购买该AI服务商品时，可以对未固化属性值进行选择设置，设置为适合自己需求的属性值，例如，用户购买商品时，可以设置要购买该商品的类型属性为类型I。
图5为本公开实施例提供的一种AI服务子对象的对象信息的示意图，如图5所示，该子对象是一种SKU，固化了基础服务的所有服务属性。该子对象可以称为第二子对象。AI服务子对象还可以是另一个AI服务商品(可以称为第一AI服务商品)，或者还可以是一个SPU。一个AI服务商品可以是上述的SPU、SKU、AI服务商品、SPU+部分固化属性值等多种类型AI服务子对象的任意组合。
本步骤中获取AI服务子对象的对象信息，可以包括但不限于如下获取方式：
在一些实施例中，可以通过接收人机交互配置的对象配置信息来获取AI服务子对象的对象信息。例如，AI服务平台的管理人员可以通过平台的人机交互的管理界面，配置一个待上架的新AI服务商品的商品信息，其中就可以包括组成该AI服务商品的各个AI服务子对象，可以是对于每一个AI服务子对象，配置该AI服务子对象中包括的AI基础服务的信息，包括配置AI基础服务包括的至少一个属性，并将每一属性设置为固化属性值或非固化属性值。例如，用户可以配置一个AI服务子对象，该AI服务子对象中包括某个SKU，其中，固化设置了该SKU中的容量、版本等各个属性。这样平台的商品服务微服务模块就可以根据接收到的对象信息，基于AI基础服务的配置得到AI服务子对象，例如，可以根据用户配置的SPU以及配置的SPU中的固化属性值，生成一个AI服务子对象，并将这些AI服务子对象进行组合，得到AI服务商品。
在一些实施例中，还可以将对象配置文件上传至平台，平台的商品服务模块可以解析该对象配置文件，获得组成AI服务商品的各个子对象的对象信息，并根据各个子对象的对象信息生成一个新的AI服务商品。
在步骤302中，基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品。
本步骤中，商品服务微服务模块可以根据步骤300中获得的对象信息，将至少一个AI服务子对象进行组合，生成可售卖的AI服务商品。根据AI服务子对象的对象信息，可以将AI基础服务的属性值进行固化设置，比如将图4中的第一AI基础服务的部分服务属性的属性值进行固化设置，或者将第二AI基础服务的所有服务属性的属性值进行固化设置，并将各个子对象进行组合得到AI服务商品。图6为本申请实施例提供的一种AI服务商品的示意图，如图6所示，该商品可以由图4所示的第一子对象和图5所示的第二子对象组合得到。该商品是一种AI服务的完整解决方案，商品中的每一个子对象都可以包括一种AI基础服务，并且每个AI服务子对象的属性都可以包括固化属性值和/或未固化属性值，即可以是对象的所有属性值都固化了，也可以是所有属性值都未 固化，也可以是固化了一部分属性值。所述的固化即指的是已经设置了确定的属性值，比如设置版本为版本I。而未固化属性值即指的是存在某个属性，但是具体的属性值可以留待购买该商品的用户去设置，比如，用户在购买某个AI服务商品时去设置要购买的商品的容量属性是一亿。在一些实施例中，组成AI服务商品的子对象可以是SPU/SKU/另一个AI服务商品/SPU与所述SPU的部分固化属性值的组合中的任意一种或多种。
本公开实施例并不限制在生成AI服务商品时各个AI服务子对象的组合方式。例如，可以按照作为商品的AI服务的处理逻辑来组合，使得各个AI服务子对象之间按照AI服务的处理逻辑来协同配合实现所述AI服务。以AI服务商品“人脸验证”为例，可以先由负责人脸检测的子对象由输入图像中识别出人脸，并提取该人脸图像的人脸特征，接着由负责数据库检索的子对象根据人脸特征检索数据库中的与该人脸特征匹配的人脸，从而确定输入图像中的人脸是否通过验证。
本公开实施例的处理方法，通过平台获取组成商品的至少一个子对象的对象信息，并据此对象信息生成AI服务商品，使得可以较快地上架一个新的AI服务商品，比如，可以通过界面配置或者上传配置文件的方式，快速上架商品，开发人员不需要为每一个新商品编码代码，商品上架效率提高；并且，当要更改商品中包括的子对象的信息时，由于商品服务模块能够自动根据各个子对象生成商品，通过这种方式也能够较快地实现关联的商品信息的更新。
此外，本公开实施例中的AI服务商品中，作为其组成部分的AI服务子对象可以包括多种类型，例如子对象可以是SPU，也可以是SKU，也可以是另一个AI服务商品，还可以是SPU以及固化了的部分属性值等。这种多类型的子对象，可以满足各种各样的AI服务商品的用户需求。比如，用户也许对基础服务的服务属性并不熟悉，如果将服务属性的属性值的选择决策交给用户，用户可能会感到困扰并且降低购买速度；那么在上架一个新的AI服务商品时，可以只留给用户选择一些用户更为关心和容易选择的服务属性的属性值，而固化其中部分属性值，比如将版本固化为版本II，这样可以加快用户的决策速度，相应加快用户选购商品的购买速度，从而提高用户体验。
在实施时，AI服务平台在上架一个新的AI服务商品时，经常会涉及到平台中多个微服务模块之间的信息同步。比如，在新商品上架时，不仅可以配置该AI服务商品中包括的各个AI服务子对象的对象信息，即说明该商品是由哪些子对象组成。而且还可以配置该新商品的一些商品关联信息，该商品关联信息包括但不限于：该商品在购买时的一些购买条件的设定，或者在商品在售出后对商品使用量的统计方式的定义，等。可以将这些商品关联信息提供给AI服务平台的其他关联的服务模块，以使得所述服务模块据此对AI服务商品的关联业务(例如，购买/使用量统计)进行处理。
在一些实施例中，如图7所示，AI服务商品在上架时配置的商品关联信息可以包括：该AI服务商品的使用统计信息，比如，在调用该AI服务商品提供的服务时需要使用的API(Application Programming Interface，应用程序接口)，以及统计服务的使用量的统计信息的定义。对服务使用的统计可以为后续出账单给出数据依据，也可以监控用户在使用服务时不超出商品对应的服务量。如图7所示，平台的管理员可以在上架AI 服务商品时在商品服务110中配置该商品的使用统计信息，平台的商品服务110可以将该使用统计信息发送给平台的网关服务120，比如可以将调用AI服务商品提供的AI服务时使用的API发给网关服务，这样网关服务就能够据此建立该API与所述AI服务商品间的映射关系，并根据该映射关系监听用户对该商品服务的使用，比如API接口的调用。此外，AI服务平台中还可以包括负责记录服务调用信息的日志记录模块，通过调用该日志记录模块记录的服务调用信息，平台可以统计AI服务商品的使用量。
例如，假设某个AI服务商品可以用于提供对门禁监控图像进行人脸验证的服务，那么用户在购买了该商品后，可以通过调用相关的API来使用该商品提供的服务。用户可以通过调用服务上传待比对的人脸图像，商品服务可以进行人脸比对和校验，最终向用户返回校验结果。假如用户购买的商品是10万张图片的容量，那么网关服务通过监听API调用，会统计用户上传了的图片的数量，当统计发现用户已经上传了10万张图片进行人脸验证时，就会不允许再使用这个服务了。又比如，用户购买的商品服务还可以是50路视频流，那网关服务可以通过监听API调用，统计用户接入的视频流的路数，以确保用户接入的视频流路数不会超过购买的商品限量。
在一些实施例中，如图8所示，AI服务商品在上架时配置的商品关联信息还可以包括：该AI服务商品的售卖属性信息。该售卖属性信息可以是用户购买所述AI服务商品时的购买条件，比如，在购买某个商品时，条件是最少购买5千张图片的人脸验证服务。平台的商品服务模块可以将该售卖属性信息发送给平台的订单服务，这样订单服务能够据此对该AI服务商品的订单进行购买条件的校验。比如，如图8所示，平台的管理员可以在上架AI服务商品时在商品服务110中配置该商品的售卖属性信息，订单服务130在处理用户购买AI服务商品的订单时，可以查询从商品服务110接收到的该AI服务商品的售卖属性信息，并根据该售卖属性信息校验订单中的信息是否符合该售卖属性信息中限定的购买条件，例如，售卖属性信息中限定了最少购买5千张图片，需要确定订单中用户填写的购买图片数量是否符合“最少购买5千张图片”的购买条件，如果符合则允许生成订单；否则，可以拒绝生成订单，并向用户提示商品购买失败的原因。
在一些实施例中，商品服务模块在生成一个新的AI服务商品后，可以主动将商品关联信息推送给平台中其他的模块，比如，订单服务或网关服务模块。也可以是由其他模块主动去商品服务模块拉取所需的信息。
在一些实施例中，所述AI服务子对象包括第一子对象；所述对象信息包括至少一个第一属性；上述步骤S300可以包括：获取至少一个第一子对象，以及每个所述第一子对象包括的至少一个第一属性，所述至少一个第一属性包括固化属性值和/或未固化属性值；上述步骤S302可以包括：基于所述至少一个第一属性，对所述至少一个第一子对象进行组合，得到AI服务商品，所述至少一个第一属性作为所述AI服务商品的属性。
在一些实施例中，所述AI服务子对象还包括第二子对象；所述对象信息还包括至少一个第二属性；上述步骤S300还可以包括：获取至少一个第二子对象，以及每个所述第二子对象包括的至少一个第二属性，所述至少一个第二属性包括固化属性值和/或未固化属性值；上述步骤S302可以包括：基于所述至少一个第一属性以及所述至少一个第二属性，对所述至少一个第一子对象和所述至少一个第二子对象进行组合，生成所述 AI服务商品，所述至少一个第一属性和所述至少一个第二属性作为所述AI服务商品的属性。
在一些实施例中，所述方法还包括：接收属性修改信息，所述属性修改信息包括：对所述AI服务商品中的AI服务子对象的固化属性值和/或未固化属性值设置后的新属性值；根据所述属性修改信息得到更新后的AI服务子对象，所述更新后的AI服务子对象包括所述新属性值；基于所述更新后的AI服务子对象，生成更新后的所述AI服务商品。
在一些实施例中，所述AI服务子对象是如下任一项类型的子对象：SPU、SKU、SPU与所述SPU的部分固化属性值的组合、另一个AI服务商品。
在一些实施例中，上述步骤S300可以包括：接收对象配置信息；所述对象配置信息包括：所述AI服务子对象中包括的AI基础服务，设置的所述AI基础服务包括的至少一个属性，所述属性包括固化属性值和/或未固化属性值；基于所述AI基础服务以及所述AI基础服务包括的至少一个属性，得到所述AI服务子对象。
在一些实施例中，所述方法还可以包括：步骤S311，获取所述AI服务商品的商品关联信息；步骤S312，将所述商品关联信息发送至对应的服务模块，以使得所述服务模块根据所述商品关联信息对所述AI服务商品的关联业务进行处理。
在一些实施例中，所述商品关联信息包括：调用所述AI服务商品提供的AI服务时的调用接口；上述步骤S312可以包括：将所述AI服务商品对应的调用接口发送给对应的网关服务，以使得所述网关服务建立所述调用接口与所述AI服务商品间的映射关系，并根据所述映射关系监听对所述AI服务商品的调用。
在一些实施例中，所述商品关联信息包括：所述AI服务商品的售卖属性信息，所述售卖属性信息包括：用户购买所述AI服务商品时的购买条件；上述步骤S312可以包括：将所述售卖属性信息发送至对应的订单服务，以使得所述订单服务根据所述售卖属性信息对所述AI服务商品的订单进行购买条件的校验。
本公开实施例提供的商品处理方法，可以方便AI服务平台的开发人员和管理人员开发以及维护商品，不仅能够较快的上架新的AI服务商品，而且还能够自动的将商品关联信息同步至平台的其他服务模块，这样其他服务模块就可以根据商品关联信息进行购买条件校验、服务使用量统计等商品相关的业务的处理，从而较为快速的完成商品上架相关的配置。只要定义好组成商品的至少一个AI服务子对象的对象信息，就可以直接进行部署，减免了开发人员每次都需要为新的商品编写代码的工作量，使得新商品的上架过程更加自动化。
在由于底层算法平台或者数据集标注平台改变，导致商品包括的AI服务子对象变更的情况下，只需要新增、修改或删除相关的子对象信息。例如，后续在对AI服务商品的维护中，若要修改AI服务商品中包括的AI服务子对象的部分属性值，比如，将版本由版本I更改为版本II，本公开实施例的商品服务模块可以接收到属性修改信息，该属性修改信息包括设置后的新属性值，例如上述的版本II。商品服务模块可以根据所述属性修改信息更新商品中对应的AI服务子对象的属性值，得到包括上述新属性值的更新后的AI服务子对象。AI服务子对象更新后，包括该对象的AI服务商品也会更新。 当变更SPU/SKU信息时，与商品信息非强关联的服务(如，订单服务)不需要进行变动，可以自动根据商品信息变更来改变展示的内容。而网关服务可能会需要根据具体情况进行变更，这样也可以使得因为底层服务的变更而影响的上层服务被大大减少，从而可以减少整个系统的代码变更范围，减少出错的可能性。
图9为本申请实施例提供的一种AI服务平台的商品处理装置的组成结构示意图，如图9所示，该装置可以包括：信息获取部分91和商品生成部分92。
信息获取部分91，配置为获取至少一个AI服务子对象的对象信息；
商品生成部分92，配置为基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品。
在一些实施例中，所述AI服务子对象包括第一子对象；所述对象信息包括至少一个第一属性；信息获取部分91，在配置为获取至少一个AI服务子对象的对象信息的情况下，还配置为：获取至少一个第一子对象，以及每个所述第一子对象包括的至少一个第一属性，所述至少一个第一属性包括固化属性值和/或未固化属性值。
所述商品生成部分92，在配置为基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品的情况下，还配置为：基于所述至少一个第一属性，对所述至少一个第一子对象进行组合，得到AI服务商品，所述至少一个第一属性作为所述AI服务商品的属性。
在一些实施例中，所述AI服务子对象还包括第二子对象；所述对象信息还包括至少一个第二属性；信息获取部分91，在配置为获取至少一个AI服务子对象的对象信息的情况下，还配置为：获取至少一个第二子对象，以及每个所述第二子对象包括的至少一个第二属性，所述至少一个第二属性包括固化属性值和/或未固化属性值。
所述商品生成部分92，在配置为基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品的情况下，还配置为：基于所述至少一个第一属性以及所述至少一个第二属性，对所述至少一个第一子对象和所述至少一个第二子对象进行组合，得到所述AI服务商品，所述至少一个第一属性和所述至少一个第二属性作为所述AI服务商品的属性。
在一些实施例中，信息获取部分91，还配置为接收属性修改信息；所述属性修改信息包括：对所述AI服务商品中的AI服务子对象的固化属性值和/或未固化属性值设置后的新属性值。
所述商品生成部分92，还配置为根据所述属性修改信息得到更新后的AI服务子对象，所述更新后的AI服务子对象包括所述新属性值；基于所述更新后的AI服务子对象，生成更新后的所述AI服务商品。
在一些实施例中，所述AI服务子对象是如下任一项类型的子对象：SPU、SKU、SPU与所述SPU的部分固化属性值的组合、另一个AI服务商品。
在一些实施例中，信息获取部分91，在配置为获取至少一个AI服务子对象的对象信息的情况下，还配置为：接收对象配置信息；所述对象配置信息包括：所述AI服务子对象中包括的AI基础服务，设置的所述AI基础服务包括的至少一个属性，所述属性包括固化属性值和/或未固化属性值；基于所述AI基础服务以及所述AI基础服务包括 的至少一个属性，得到所述AI服务子对象。
在一些实施例中，如图10所示，该装置还可以包括：信息同步部分93。
信息同步部分93，配置为获取所述AI服务商品的商品关联信息；将所述商品关联信息发送至对应的服务模块，以使得所述服务模块根据所述商品关联信息对所述AI服务商品的关联业务进行处理。
在一些实施例中，所述商品关联信息包括：调用所述AI服务商品提供的AI服务时的调用接口；信息同步部分93，还配置为将所述AI服务商品对应的调用接口发送给对应的网关服务，以使得网关服务建立所述调用接口与所述AI服务商品间的映射关系，并根据所述映射关系监听对所述AI服务商品的调用。
在一些实施例中，所述商品关联信息包括：所述AI服务商品的售卖属性信息，所述售卖属性信息包括：用户购买所述AI服务商品时的购买条件；信息同步部分93，还配置为将所述售卖属性信息发送至对应的订单服务，以使得所述订单服务根据售卖属性信息对所述AI服务商品的订单进行购买条件的校验。
在本公开实施例以及其他的实施例中，“部分”可以是部分电路、部分处理器、部分程序或软件等等，当然也可以是单元，还可以是模块也可以是非模块化的。
本领域技术人员应明白，本公开一个或多个实施例可提供为方法、系统、电子设备、计算机存储介质、计算机程序产品或计算机程序。因此，本公开一个或多个实施例可采用完全硬件实施例、完全软件实施例或结合软件和硬件方面的实施例的形式。而且，本公开一个或多个实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM(Compact Disc Read-Only Memory，便携式压缩盘只读存储器)、光学存储器等)上实施的计算机程序产品的形式。
本公开实施例还提供一种计算机可读存储介质，计算机存储介质可为易失性存储介质或非易失性存储介质；该存储介质上可以存储有计算机程序，所述程序被处理器执行时实现本公开任一实施例描述的AI服务平台的商品处理方法的部分或全部步骤。
本公开实施例提供一种计算机程序产品，所述计算机程序产品包括存储了计算机程序的非瞬时性计算机可读存储介质，所述计算机程序被计算机读取并执行时，实现本公开实施例中所描述的AI服务平台的商品处理方法的部分或全部步骤。
本公开实施例提供一种计算机程序，所述计算机程序包括计算机可读代码，在所述计算机可读代码被计算机读取并执行的情况下，实现本公开实施例中所描述的AI服务平台的商品处理方法的部分或全部步骤。
本公开实施例还提供一种电子设备，该电子设备包括：存储器、处理器，所述存储器配置为存储计算机可读指令，所述处理器配置为调用所述计算机指令，实现本公开任一实施例所述的AI服务平台的商品处理方法的部分或全部步骤。
图11为本公开实施例提供的一种电子设备的硬件结构示意图。该电子设备1010包括处理器1011，还可以包括输入装置1012、输出装置1013和存储器1014。该输入装置1012、输出装置1013、存储器1014和处理器1011之间通过总线相互连接。
存储器包括但不限于是RAM(Random Access Memory，随机存储记忆体)、ROM(Read-Only Memory，只读存储器)、EPROM(Erasable Programmable Read Only Memory， 可擦除可编程只读存储器)、EEPROM(Electrically Erasable Programmable Read Only Memory，电可擦除可编程只读存储器)、CD-ROM或DVD-ROM(Digital Video Disc Read-Only Memory，数字多功能盘只读存储器)，该存储器用于存储相关指令及数据。
输入装置用于输入数据和/或信号，以及输出装置用于输出数据和/或信号。输出装置和输入装置可以是独立的器件，也可以是一个整体的器件。
处理器可以包括是一个或多个处理器，例如包括一个或多个CPU(Central Processing Unit，中央处理器)，在处理器是一个CPU的情况下，该CPU可以是单核CPU，也可以是多核CPU。
存储器用于存储网络设备的程序代码和数据。
处理器配置为调用该存储器中的程序代码和数据，执行上述方法实施例中的步骤。具体可参见方法实施例中的描述。
可以理解的是，图11仅仅示出了一种电子设备的简化设计。在实际应用中，电子设备还可以分别包含必要的其他元件，包含但不限于任意数量的输入/输出装置、处理器、控制器、存储器等，而所有可以实现本公开实施例的电子设备都在本公开的保护范围之内。
本公开实施例以及其他的实施例中，所述的“和/或”表示至少具有两者中的其中一个，例如，“A和/或B”包括三种方案：A、B、以及“A和B”。
本公开中各个实施例之间相同相似的部分互相参见即可，每个实施例重点说明的都是与其他实施例的不同之处。尤其，对于电子设备实施例而言，由于其基本相似于方法实施例，相关之处参见方法实施例的部分说明即可。
上述对本公开的示例性实施例进行了描述。其它实施例均在本公开所保护的范围内。在一些情况下，上述本公开实施例记载的行为或步骤可以按照不同于实施例中的顺序来执行并且仍然可以实现期望的结果。另外，在附图中描绘的过程不一定要求示出的特定顺序或者连续顺序才能实现期望的结果。在一些实施方式中，多任务处理和并行处理也是可以的。
本公开实施例中描述的主题及功能操作的实施例可以在以下中实现：数字电子电路、有形体现的计算机软件或固件、包括本公开实施例中公开的结构及其结构性等同物的计算机硬件、或者它们中的一个或多个的组合。本公开实施例中描述的主题的实施例可以实现为一个或多个计算机程序，即编码在有形非暂时性程序载体上以被数据处理装置执行或控制数据处理装置的操作的计算机程序指令中的一个或多个部分。可替代地或附加地，程序指令可以被编码在人工生成的传播信号上，例如机器生成的电、光或电磁信号，该信号被生成以将信息编码并传输到合适的接收机装置以由数据处理装置执行。计算机存储介质可以是机器可读存储设备、机器可读存储基板、随机或串行存取存储器设备、或它们中的一个或多个的组合。
本公开实施例中描述的处理及逻辑流程可以由执行一个或多个计算机程序的一个或多个可编程计算机执行，以通过根据输入数据进行操作并生成输出来执行相应的功能。所述处理及逻辑流程还可以由专用逻辑电路—例如FPGA(Field Programmable Gate Array，现场可编程门阵列)或ASIC(Application Specific Integrated Circuit，专用集成 电路)来执行，并且装置也可以实现为专用逻辑电路。
适合用于执行计算机程序的计算机包括，例如通用和/或专用微处理器，或任何其他类型的中央处理单元。通常，中央处理单元将从只读存储器和/或随机存取存储器接收指令和数据。计算机的基本组件包括用于实施或执行指令的中央处理单元以及用于存储指令和数据的一个或多个存储器设备。通常，计算机还将包括用于存储数据的一个或多个大容量存储设备，例如磁盘、磁光盘或光盘等，或者计算机将可操作地与此大容量存储设备耦接以从其接收数据或向其传送数据，抑或两种情况兼而有之。然而，计算机不是必须具有这样的设备。此外，计算机可以嵌入在另一设备中，例如移动电话、PDA(Personal Digital Assistant，个人数字助理)、移动音频或视频播放器、游戏操纵台、GPS(Global Positioning System，全球定位系统)接收机、或例如USB(Universal Serial Bus，通用串行总线)闪存驱动器的便携式存储设备，仅举几例。
适合于存储计算机程序指令和数据的计算机可读介质包括所有形式的非易失性存储器、媒介和存储器设备，例如包括半导体存储器设备(例如EPROM、EEPROM和闪存设备)、磁盘(例如内部硬盘或可移动盘)、磁光盘以及CD-ROM和DVD-ROM盘。处理器和存储器可由专用逻辑电路补充或并入专用逻辑电路中。
虽然本公开实施例包含许多具体实施细节，但是这些不应被解释为限制任何公开的范围或所要求保护的范围，而是主要用于描述特定公开的具体实施例的特征。本公开内在多个实施例中描述的特征也可以在单个实施例中被组合实施。另一方面，在单个实施例中描述的各种特征也可以在多个实施例中分开实施或以任何合适的子组合来实施。此外，虽然特征可以如上所述在某些组合中起作用并且甚至最初如此要求保护，但是来自所要求保护的组合中的一个或多个特征在一些情况下可以从该组合中去除，并且所要求保护的组合可以指向子组合或子组合的变型。
类似地，虽然在附图中以特定顺序描绘了操作，但是这不应被理解为要求这些操作以所示的特定顺序执行或顺次执行、或者要求所有例示的操作被执行，以实现期望的结果。在某些情况下，多任务和并行处理可能是有利的。此外，上述实施例中的各种系统模块和组件的分离不应被理解为在所有实施例中均需要这样的分离，并且应当理解，所描述的程序组件和系统通常可以一起集成在单个软件产品中，或者封装成多个软件产品。
以上所述仅为本公开一个或多个示例性实施例，并不用以限制本公开一个或多个实施例，凡在本公开一个或多个实施例的精神和原则之内，所做的任何修改、等同替换、改进等，均应包含在本公开一个或多个实施例保护的范围之内。
工业实用性
本公开实施例提供了一种AI服务平台的商品处理方法及装置、电子设备、存储介质、计算机程序产品、计算机程序，其中，该方法包括：获取至少一个AI服务子对象的对象信息；基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品。本公开实施例通过由平台获取组成商品的至少一个子对象的对象信息，并据此对象信息生成AI服务商品，使得可以较快的上架一个新的AI服务商品。根据本公开实施例，可以使得AI服务平台较快地上架一个新的AI服务商品。

Claims (22)

  1. 一种AI服务平台的商品处理方法，所述方法包括：
    获取至少一个AI服务子对象的对象信息；
    基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品。
  2. 根据权利要求1所述的方法，其中，所述AI服务子对象包括第一子对象；所述对象信息包括至少一个第一属性；所述获取至少一个AI服务子对象的对象信息，包括：
    获取至少一个第一子对象，以及每个所述第一子对象包括的至少一个第一属性，所述至少一个第一属性包括固化属性值和/或未固化属性值；
    所述基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品，包括：
    基于所述至少一个第一属性，对所述至少一个第一子对象进行组合，得到AI服务商品，所述至少一个第一属性作为所述AI服务商品的属性。
  3. 根据权利要求2所述的方法，其中，所述AI服务子对象还包括第二子对象；所述对象信息还包括至少一个第二属性；所述获取至少一个AI服务子对象的对象信息，还包括：
    获取至少一个第二子对象，以及每个所述第二子对象包括的至少一个第二属性，所述至少一个第二属性包括固化属性值和/或未固化属性值；
    所述基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品，包括：
    基于所述至少一个第一属性以及所述至少一个第二属性，对所述至少一个第一子对象和所述至少一个第二子对象进行组合，生成所述AI服务商品，所述至少一个第一属性和所述至少一个第二属性作为所述AI服务商品的属性。
  4. 根据权利要求2或3所述的方法，其中，所述方法还包括：
    接收属性修改信息；所述属性修改信息包括：对所述AI服务商品中的AI服务子对象的固化属性值和/或未固化属性值设置后的新属性值；
    根据所述属性修改信息得到更新后的AI服务子对象，所述更新后的AI服务子对象包括所述新属性值；
    基于所述更新后的AI服务子对象，生成更新后的所述AI服务商品。
  5. 根据权利要求1所述的方法，其中，所述AI服务子对象是如下任一项类型的子对象：
    SPU、SKU、SPU与所述SPU的部分固化属性值的组合、另一个AI服务商品。
  6. 根据权利要求1所述的方法，其中，所述获取至少一个AI服务子对象的对象信息，包括：
    接收对象配置信息；所述对象配置信息包括：所述AI服务子对象中包括的AI基础服务，设置的所述AI基础服务包括的至少一个属性，所述属性包括固化属性值和/或未固化属性值；
    基于所述AI基础服务以及所述AI基础服务包括的至少一个属性，得到所述AI服务子对象。
  7. 根据权利要求1～6任一所述的方法，其中，所述方法还包括：
    获取所述AI服务商品的商品关联信息；
    将所述商品关联信息发送至对应的服务模块，以使得所述服务模块根据所述商品关联信息对所述AI服务商品的关联业务进行处理。
  8. 根据权利要求7所述的方法，其中，所述商品关联信息包括：调用所述AI服务商品提供的AI服务时的调用接口；
    所述将所述商品关联信息发送至对应的服务模块，以使得所述服务模块根据所述商品关联信息对所述AI服务商品的关联业务进行处理，包括：
    将所述AI服务商品对应的调用接口发送给对应的网关服务，以使得所述网关服务建立所述调用接口与所述AI服务商品间的映射关系，并根据所述映射关系监听对所述AI服务商品的调用。
  9. 根据权利要求7所述的方法，其中，所述商品关联信息包括：所述AI服务商品的售卖属性信息，所述售卖属性信息包括：用户购买所述AI服务商品时的购买条件；
    所述将所述商品关联信息发送至对应的服务模块，以使得所述服务模块根据所述商品关联信息对所述AI服务商品的关联业务进行处理，包括：
    将所述售卖属性信息发送至对应的订单服务，以使得所述订单服务根据所述售卖属性信息对所述AI服务商品的订单进行购买条件的校验。
  10. 一种AI服务平台的商品处理装置，所述装置包括：
    信息获取部分，配置为获取至少一个AI服务子对象的对象信息；
    商品生成部分，配置为基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品。
  11. 根据权利要求10所述的装置，其中，所述AI服务子对象包括第一子对象；所述对象信息包括至少一个第一属性；
    所述信息获取部分，在配置为获取至少一个AI服务子对象的对象信息的情况下，还配置为：获取至少一个第一子对象，以及每个所述第一子对象包括的至少一个第一属性，所述至少一个第一属性包括固化属性值和/或未固化属性值；
    所述商品生成部分，在配置为基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品的情况下，还配置为：基于所述至少一个第一属性，对所述至少一个第一子对象进行组合，得到AI服务商品，所述至少一个第一属性作为所述AI服务商品的属性。
  12. 根据权利要求11所述的装置，其中，所述AI服务子对象还包括第二子对象；所述对象信息还包括至少一个第二属性；
    所述信息获取部分，在配置为获取至少一个AI服务子对象的对象信息的情况下，还配置为：获取至少一个第二子对象，以及每个所述第二子对象包括的至少一个第二属性，所述至少一个第二属性包括固化属性值和/或未固化属性值；
    所述商品生成部分，在配置为基于所述对象信息，将所述至少一个AI服务子对象组合，得到可售卖的用于提供AI服务的AI服务商品的情况下，还配置为：基于所述至 少一个第一属性以及所述至少一个第二属性，对所述至少一个第一子对象和所述至少一个第二子对象进行组合，得到所述AI服务商品，所述至少一个第一属性和所述至少一个第二属性作为所述AI服务商品的属性。
  13. 根据权利要求11或12所述的装置，其中，所述信息获取部分，还配置为接收属性修改信息；所述属性修改信息包括：对所述AI服务商品中的AI服务子对象的固化属性值和/或未固化属性值设置后的新属性值；
    所述商品生成部分，还配置为根据所述属性修改信息得到更新后的AI服务子对象，所述更新后的AI服务子对象包括所述新属性值；基于所述更新后的AI服务子对象，生成更新后的所述AI服务商品。
  14. 根据权利要求10所述的装置，其中，所述AI服务子对象是如下任一项类型的子对象：SPU、SKU、SPU与所述SPU的部分固化属性值的组合、另一个AI服务商品。
  15. 根据权利要求14所述的装置，其中，所述信息获取部分，在配置为获取至少一个AI服务子对象的对象信息的情况下，还配置为：接收对象配置信息；所述对象配置信息包括：所述AI服务子对象中包括的AI基础服务，设置的所述AI基础服务包括的至少一个属性，所述属性包括固化属性值和/或未固化属性值；基于所述AI基础服务以及所述AI基础服务包括的至少一个属性，得到所述AI服务子对象。
  16. 根据权利要求10至15中任一项所述的装置，其中，所述装置还包括：信息同步部分，配置为获取所述AI服务商品的商品关联信息；将所述商品关联信息发送至对应的服务模块，以使得所述服务模块根据所述商品关联信息对所述AI服务商品的关联业务进行处理。
  17. 根据权利要求16所述的装置，其中，所述商品关联信息包括：调用所述AI服务商品提供的AI服务时的调用接口；
    所述信息同步部分，还配置为将所述AI服务商品对应的调用接口发送给对应的网关服务，以使得所述网关服务建立所述调用接口与所述AI服务商品间的映射关系，并根据所述映射关系监听对所述AI服务商品的调用。
  18. 根据权利要求16所述的装置，其中，所述商品关联信息包括：所述AI服务商品的售卖属性信息，所述售卖属性信息包括：用户购买所述AI服务商品时的购买条件；
    所述信息同步部分，还配置为将所述售卖属性信息发送至对应的订单服务，以使得所述订单服务根据售卖属性信息对所述AI服务商品的订单进行购买条件的校验。
  19. 一种电子设备，包括：存储器、处理器，所述存储器配置为存储计算机可读指令，所述处理器配置为调用所述计算机指令，实现权利要求1至9任一所述的方法。
  20. 一种计算机可读存储介质，其上存储有计算机程序，所述程序被处理器执行时实现权利要求1至9任一所述的方法。
  21. 一种计算机程序，包括计算机可读代码，在计算机可读代码在设备上运行的情况下，设备中的处理器执行用于实现权利要求1至9中任一所述的方法。
  22. 一种计算机程序产品，配置为存储计算机可读指令，所述计算机可读指令被执行时使得计算机执行权利要求1至9中任一所述的方法。
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