Content search method and device based on large model technology and electronic equipment

Abstract

The invention provides a content search method and device based on a large model technology and electronic equipment, and relates to the technical field of artificial intelligence, in particular to the technical fields of deep learning, natural language processing, computer vision, large models, intelligent agents and the like. The specific implementation scheme is as follows: receiving a search request of an access service; the search request comprises to-be-searched content; determining at least one target application and a barrier-free service corresponding to the at least one target application; calling a barrier-free service based on the to-be-searched content, and obtaining a search result image related to the to-be-searched content in the at least one target application; and performing response processing on the search request according to the search result image.

Description

Technical Field

[0001] The present disclosure relates to the field of artificial intelligence technology, and in particular to technical fields such as deep learning, natural language processing, computer vision, large models, and intelligent agents, and in particular to a content search method, device, and electronic device based on large model technology. Background Art

[0002] The current content search method mainly includes that, for the content to be searched, the user enters the content to be searched into the search box in each target application to obtain search result images related to the content to be searched in each target application; and uses the search result images as target search results.

[0003] In the above solution, due to the closed nature of each target application, the user needs to enter each target application separately to input the content to be searched for searching, which takes a long time and has low efficiency. Summary of the invention

[0004] The present disclosure provides a content search method, device and electronic device based on big model technology.

[0005] According to one aspect of the present disclosure, a content search method based on big model technology is provided, including: receiving a search request for an access service; the search request includes content to be searched; determining at least one target application, and an accessibility service corresponding to the at least one target application; calling the accessibility service based on the content to be searched, and obtaining a search result image related to the content to be searched in the at least one target application; and responding to the search request according to the search result image.

[0006] According to another aspect of the present disclosure, a content search device based on big model technology is provided, including: a receiving module, used to receive a search request for accessing a service; the search request includes content to be searched; a first determination module, used to determine at least one target application, and an accessibility service corresponding to the at least one target application; an image acquisition module, used to call the accessibility service based on the content to be searched, and obtain a search result image related to the content to be searched in the at least one target application; and a response module, used to respond to the search request according to the search result image.

[0007] According to another aspect of the present disclosure, there is provided an electronic device, comprising:

[0008] at least one processor; and

[0009] a memory communicatively connected to the at least one processor; wherein,

[0010] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the content search method based on the large model technology proposed above in the present disclosure.

[0011] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the content search method based on the large model technology proposed above in the present disclosure.

[0012] According to another aspect of the present disclosure, a computer program product is provided, including computer instructions, which, when executed by a processor, implement the steps of the content search method based on the large model technology proposed above in the present disclosure.

[0013] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0015] Figure 1 is a schematic diagram according to a first embodiment of the present disclosure;

[0016] Figure 2 is a schematic diagram according to a second embodiment of the present disclosure;

[0017] Figure 3 is a schematic diagram according to a third embodiment of the present disclosure;

[0018] Figure 4 is a schematic diagram according to a fourth embodiment of the present disclosure;

[0019] Figure 5 It is a block diagram of an electronic device used to implement a content search method based on a large model technology according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0020] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0021] The current content search method mainly includes that, for the content to be searched, the user enters the content to be searched into the search box in each target application to obtain search result images related to the content to be searched in each target application; and uses the search result images as target search results.

[0022] In the above solution, due to the closed nature of each target application, the user needs to enter each target application separately to input the content to be searched for searching, which takes a long time and has low efficiency.

[0023] In view of the above problems, the present disclosure proposes a content search method, device and electronic device based on big model technology.

[0024] Figure 1 It is a schematic diagram according to the first embodiment of the present disclosure. It should be noted that the content search method based on the big model technology of the embodiment of the present disclosure can be applied to the content search device based on the big model technology. The device can be configured in an electronic device so that the electronic device can perform a content search function.

[0025] Among them, the electronic device can be any device with computing capabilities, such as a personal computer (PC), a mobile terminal, a server, etc. The mobile terminal can be, for example, a vehicle-mounted device, a mobile phone, a tablet computer, a personal digital assistant, a wearable device, a smart speaker, a server, a server cluster, and other hardware devices with various operating systems, touch screens and / or display screens.

[0026] Among them, the electronic device may be provided with multiple services, and the content search function is realized through the calling relationship between the multiple services. For example, the electronic device may be provided with access service, agent service (intelligent body service), simulator service, barrier-free service, mongo service, etc.

[0027] The content search device based on the big model technology can also be software in an electronic device, such as content search software, etc. In the following embodiments, the content search device based on the big model technology is described as software in an electronic device. In the following embodiments, the execution subject is described as an agent service.

[0028] like Figure 1 As shown, the content search method based on the large model technology includes:

[0029] Step 101: Receive a search request for accessing a service, where the search request includes content to be searched.

[0030] In an embodiment of the present disclosure, in one example, the process of the agent service executing step 101 may be, for example, that the agent service receives a search request sent by the access service. The access service is used to receive the search request, call the agent list in the mongo service, obtain any agent identifier therein, and send the search request to the agent service corresponding to the agent identifier. The agent list includes multiple agent records, and the storage format of each agent record may be <record id, agent ID, agent description, agent address>.

[0031] Step 102: Determine at least one target application and at least one barrier-free service corresponding to the target application.

[0032] The target application may refer to a set application to be searched, or may refer to an application that matches the content to be searched; for example, the target application may refer to an application for posting messages, an application for posting videos, etc. It should be noted that when the target application is a set application to be searched, a search is performed in the set application to be searched for any search request.

[0033] Among them, the accessibility service corresponding to the target application belongs to the system-level application programming interface (Application Programming Interface, API), which can simulate user operations and control various functions of the target application.

[0034] In one example of the disclosed embodiment, the process of the agent service executing step 102 may, for example, include obtaining the content category of the content to be searched; determining a target application that matches the content to be searched based on the content category of the content to be searched and the category of the content included in the application; and determining the accessibility service corresponding to the target application based on the association relationship between the application and the accessibility service.

[0035] Step 103: Calling an accessibility service based on the content to be searched, and obtaining a search result image related to the content to be searched in at least one target application.

[0036] In one example of the disclosed embodiment, the process of the agent service executing step 103 may be, for example, that the agent service calls the accessibility service, passes the content to be searched to the target application, and obtains the search result image returned by the target application. Wherein, in the case of multiple target applications, the agent service may call the accessibility services corresponding to the multiple target applications in parallel.

[0037] For example, assuming that the target application is an application for posting, the search result image may be a screenshot of a page where the post is located in the target application.

[0038] Step 104: respond to the search request according to the search result image.

[0039] In an embodiment of the present disclosure, in one example, the process of the agent service executing step 104 may be, for example, inputting the search result image into a large model, sorting the search result image by the large model, and obtaining a target search result corresponding to the content to be searched.

[0040] In another example, the agent service can input the search result image into the big model to obtain the recognition content output by the big model, and input each search result image and the recognition content corresponding to the search result image into the big model for fusion processing to obtain the target search result output by the big model.

[0041] The target search result may be presented in the form of a multimedia page, for example. The multimedia page may include at least one of text, image, video, link, etc.

[0042] The content search method based on the big model technology of the embodiment of the present disclosure receives a search request for an access service, wherein the search request includes the content to be searched; determines at least one target application and at least one barrier-free service corresponding to the target application; calls the barrier-free service based on the content to be searched, and obtains a search result image related to the content to be searched in at least one target application; and responds to the search request based on the search result image. Among them, the barrier-free service corresponding to the target application can automatically transfer the content to be searched to the target application, thereby performing a search operation in the target application and obtaining a related search result image, which simplifies the user's operation process, avoids the need for the user to manually switch to each target application and input the content to be searched separately, shortens the search time, and improves the search efficiency.

[0043] Among them, the simulator service can only process one search request at a time. When the target application refers to the set application to be searched, in order to improve the search efficiency and quickly respond to the search request, the agent service can query the target simulator identifier that is bound to the agent identifier and is in an idle state, and then quickly determine the target application and the corresponding accessibility service in combination with the target simulator identifier. Figure 2 As shown, Figure 2 is a schematic diagram according to a second embodiment of the present disclosure, Figure 2 The illustrated embodiment may include the following steps:

[0044] Step 201: Receive a search request for access services.

[0045] Step 202, determining the agent identifier of the agent service receiving the search request.

[0046] The agent service corresponds to an identity document (ID). After receiving a search request, the agent service can read its own identity document from a set location, such as a memory.

[0047] Step 203, query the first data structure according to the agent identifier, obtain the target simulator identifier in the first data structure that is bound to the agent identifier and is in an idle state; the simulator service corresponding to the target simulator identifier runs a target application.

[0048] In the disclosed embodiment, the simulator identifier may be a unique identifier of a simulator service, and the simulator service may refer to a service capable of running a target application. The simulator service may be installed on a computer, a server, or other device, and the target application running on the simulator service may be understood as a virtual application.

[0049] Among them, the first data structure can be used to store the binding relationship between the agent identifier and the simulator identifier, as well as the status of the simulator service corresponding to the simulator identifier. The status of the simulator service may include an idle state, an occupied state, an unavailable state, etc. The idle state indicates that the simulator service is not occupied by the agent service, the occupied state indicates that the simulator service is occupied by the agent service, and the unavailable state indicates that the simulator service is unavailable due to a fault, a state setting, etc.

[0050] For example, the first data structure may be a dictionary (Map) structure, and multiple records may be stored in the first data structure. The storage format of each record may be <record ID, simulator ID, status of simulator service, ID of bound agent service>.

[0051] It should be noted that the first data structure can be stored in a specified location, such as a specified database. After obtaining the intelligent body identifier, the agent service can call the first data structure in the mongo service to obtain the simulator identifier that is bound to the agent representation and is in an idle state.

[0052] In an embodiment of the present disclosure, after querying the first data structure according to the intelligent agent identifier and obtaining the target simulator identifier in the first data structure that is bound to the intelligent agent identifier and is in an idle state, the method also includes: obtaining a record in the first data structure that includes the target simulator identifier and the intelligent agent identifier; setting the state corresponding to the target simulator identifier in the record to an occupied state.

[0053] Updating the state corresponding to the target simulator identifier in the record from an idle state to an occupied state can prevent the corresponding simulator service from being selected again by a new search request, resulting in processing conflicts and response delays.

[0054] Step 204, query the second data structure corresponding to the agent identifier according to the target simulator identifier, and determine the accessibility service corresponding to the target simulator identifier in the second data structure as the accessibility service corresponding to the target application.

[0055] In the embodiment of the present disclosure, the accessibility service runs on the simulator service, and one accessibility service runs on one simulator service.

[0056] The second data structure is stored in the memory of the agent service and can be used to store the correspondence between the simulator ID and the accessibility service. For example, the second data structure can be a Map structure, and multiple records can be stored in the second data structure. The storage format of each record can be <record ID, simulator ID, accessibility service ID>.

[0057] Step 205: Calling an accessibility service based on the content to be searched, and obtaining a search result image related to the content to be searched in at least one target application.

[0058] In an embodiment of the present disclosure, after calling an accessibility service based on the content to be searched and obtaining a search result image related to the content to be searched in at least one target application, the method further includes: obtaining a record including a target simulator identifier and an agent identifier in a first data structure; and setting a state corresponding to the target simulator identifier in the record to an idle state.

[0059] Obtaining the search result image means that the current search task has ended and the simulator no longer needs to continue serving the task. At this time, the state corresponding to the target simulator identifier in the record is updated from occupied state to idle state, thus releasing the occupation of the simulator service and enabling it to receive and process new search requests again, thereby improving the utilization rate of simulator service resources.

[0060] Step 206: respond to the search request based on the search result image.

[0061] It should be noted that the details of step 201, step 205, and step 206 can be found in Figure 1 Step 101, step 103, and step 104 in the illustrated embodiment will not be described in detail herein.

[0062] The content search method based on the big model technology of the disclosed embodiment receives a search request for an access service; determines the agent identifier of the agent service that receives the search request; queries the first data structure according to the agent identifier, and obtains the target simulator identifier in the first data structure that is bound to the agent identifier and is in an idle state; the simulator service corresponding to the target simulator identifier runs a target application; queries the second data structure corresponding to the agent identifier according to the target simulator identifier, and determines the barrier-free service corresponding to the target simulator identifier in the second data structure as the barrier-free service corresponding to the target application; calls the barrier-free service based on the content to be searched, and obtains a search result image related to the content to be searched in at least one target application; and responds to the search request based on the search result image. Among them, the target application and the barrier-free service determined based on the target simulator identifier are in an idle state, and can respond to the search request in a timely manner, thereby shortening the search time and improving the search efficiency.

[0063] The load (search request) carried by the agent service changes dynamically. In order to enable the agent service to flexibly respond to these load changes and improve the flexibility and scalability of the agent service, the agent service can scale the simulator resources according to the number of idle simulator services, such as Figure 3 As shown, Figure 3 is a schematic diagram according to a third embodiment of the present disclosure, Figure 3 The illustrated embodiment may include the following steps:

[0064] Step 301: Receive a search request for access services.

[0065] Step 302, determining the agent identifier of the agent service that receives the search request.

[0066] Step 303: query the first data structure according to the agent identifier, and obtain the target simulator identifier in the first data structure that is bound to the agent identifier and is in an idle state.

[0067] Step 304: Determine a first number of target simulator identifiers.

[0068] After the target simulator identifier is obtained, the target simulator identifiers may be counted to obtain a first quantity.

[0069] Step 305, when the first number is less than or equal to the first number threshold, call the simulator management service to enable the candidate simulator service, and set the candidate accessibility service corresponding to the candidate simulator service; the state corresponding to the candidate simulator identifier of the candidate simulator service is the idle state.

[0070] Among them, the first quantity threshold can be a pre-set value, which can be adjusted according to actual needs; the simulator management service can enable or disable the simulator service through a given image; the candidate simulator service can refer to a new simulator service started by the simulator management service; enabling the candidate simulator service can be understood as expanding the capacity of the simulator resources.

[0071] In the case where the first number is less than or equal to the first number threshold, by enabling the candidate simulator service, the present disclosure can maintain a certain redundancy to cope with the problem of sudden load or failure of individual simulator services.

[0072] Step 306: Establish a binding relationship between the candidate simulator identifier and the agent identifier.

[0073] In an embodiment of the present disclosure, in one example, the candidate simulator identifier and the agent identifier may be stored in association with each other to establish a binding relationship between the candidate simulator identifier and the agent identifier.

[0074] In another example, the correspondence between the candidate simulator identifier, the agent identifier, and the state corresponding to the candidate simulator identifier is added as a record to the first data structure; the correspondence between the candidate simulator identifier and the candidate accessibility service is added to the second data structure.

[0075] Among them, the agent service can call the mongo service to add the correspondence between the candidate simulator identifier, the intelligent agent identifier and the state corresponding to the candidate simulator identifier to the first data structure, and add the correspondence between the candidate simulator identifier and the candidate accessibility service to the second data structure.

[0076] By explicitly storing the relevant corresponding relationships in the corresponding data structure, the present disclosure can more easily manage and maintain these relationships. In addition, the use of the data structure can make it easy for the present disclosure to add new candidate simulator services without large-scale modifications to the system architecture, thereby improving the flexibility and scalability of the present disclosure.

[0077] Step 307, determine whether the intelligent agent service meets the release condition; the release condition is that within a time period greater than the specified time length, the second number of simulator identifiers bound to the intelligent agent identifier and in an idle state is greater than or equal to the second number threshold; the second number threshold is greater than the first number threshold.

[0078] In the embodiment of the present disclosure, the agent service can call the mongo service to obtain the second quantity, and when the second quantity is greater than or equal to the second quantity threshold, determine that the agent service meets the release condition. The release condition is used to determine whether the simulator service needs to be scaled down.

[0079] The second quantity threshold may also be smaller than the first quantity threshold. It should be noted that when the second quantity threshold is smaller than the first quantity threshold, the number of idle simulator services may change frequently (frequent expansion and contraction).

[0080] Step 308: When the agent service meets the release condition, a simulator identifier to be released is selected from simulator identifiers that are bound to the agent identifier and are in an idle state.

[0081] Among them, the simulator identifier to be released can be randomly selected from the simulator identifiers bound to the intelligent agent identifier and in an idle state, or the simulator identifier to be released can be selected according to a set selection rule.

[0082] Step 309: releasing the simulator service and accessibility service corresponding to the simulator identifier to be released.

[0083] Among them, releasing the simulator service and accessibility service corresponding to the simulator identifier to be released may refer to shutting down the simulator service corresponding to the simulator identifier to be released, and shutting down the device where the simulator service corresponding to the simulator identifier to be released is located.

[0084] When the simulator service has excess processing capacity, computing resources, storage resources, and network resources can be recovered by releasing redundant simulator service resources and accessibility service resources so that these resources can be reallocated to other services, thereby improving overall resource utilization.

[0085] In the disclosed embodiment, the method further includes: deleting the records including the to-be-released simulator identifier and the agent identifier in the first data structure; and deleting the corresponding relationship including the to-be-released simulator identifier in the second data structure.

[0086] Deleting records that are no longer needed can not only release the occupied memory and storage space, but also ensure the reliability of the data in the second data structure.

[0087] It should be noted that the execution subject of the aforementioned reduction and release of the simulator service is the agent service. In another example, the simulator service can also be reduced and released through the accessibility service, as follows:

[0088] For any accessibility service, the accessibility service calls the mongo service to obtain the third number of simulator services / accessibility services in idle state corresponding to the agent service; when the third number is greater than or equal to the second number threshold, the accessibility service sets its own state to unavailable; after waiting for a period of time, the mongo service is called again to obtain the third number of simulator services / accessibility services in idle state corresponding to the agent service; if the third number is still greater than or equal to the second number threshold, the accessibility service calls the simulator management service to delete its corresponding record from the first data structure, and releases the simulator service where it is located.

[0089] It should be noted that the details of steps 301 to 303 can be found in Figure 1 Steps 201 to 203 in the illustrated embodiment will not be described in detail herein.

[0090] In an embodiment of the present disclosure, a first number of target simulator identifiers is determined; when the first number is less than or equal to a first number threshold, a simulator management service is called to enable candidate simulator services, and candidate accessibility services corresponding to the candidate simulator services are set; a binding relationship between the candidate simulator identifiers and the intelligent agent identifiers is established; and it is determined whether the intelligent agent service meets the release conditions; when the intelligent agent service meets the release conditions, a simulator identifier to be released is selected from simulator identifiers that are bound to the intelligent agent identifier and are in an idle state; and the simulator service and accessibility service corresponding to the simulator identifier to be released are released. Among them, the simulator resources are expanded and contracted according to the number of idle simulator services, which enables the present disclosure to flexibly cope with dynamically changing search loads, thereby improving the flexibility and scalability of the present disclosure.

[0091] In order to implement the above embodiment, the present disclosure also provides a content search device based on large model technology. Figure 4 As shown, Figure 4 4 is a schematic diagram according to the fourth embodiment of the present disclosure. The content search device 40 based on the large model technology may include: a receiving module 401 , a first determining module 402 , an image acquiring module 403 and a responding module 404 .

[0092] Among them, the receiving module 401 is used to receive a search request for accessing the service; the search request includes the content to be searched; the first determination module 402 is used to determine at least one target application and at least one accessibility service corresponding to the target application; the image acquisition module 403 is used to call the accessibility service based on the content to be searched, and obtain the search result image related to the content to be searched in at least one target application; the response module 404 is used to respond to the search request according to the search result image.

[0093] As a possible implementation method of the embodiment of the present disclosure, the first determination module 402 is used to: determine the agent identifier of the agent service that receives the search request; query the first data structure according to the agent identifier, and obtain the target simulator identifier that is bound to the agent identifier and is in an idle state in the first data structure; the simulator service corresponding to the target simulator identifier runs a target application; query the second data structure corresponding to the agent identifier according to the target simulator identifier, and determine the accessibility service corresponding to the target simulator identifier in the second data structure as the accessibility service corresponding to the target application.

[0094] As a possible implementation method of the embodiment of the present disclosure, the device also includes: a first record acquisition module, which is used to query the first data structure according to the intelligent entity identifier, obtain the target simulator identifier bound to the intelligent entity identifier and in an idle state in the first data structure, and then obtain the record including the target simulator identifier and the intelligent entity identifier in the first data structure; a first setting module, which is used to set the state corresponding to the target simulator identifier in the record to an occupied state.

[0095] As a possible implementation method of the embodiment of the present disclosure, the device also includes: a second record acquisition module, which is used to call the accessibility service based on the content to be searched, and obtain the search result image related to the content to be searched in at least one target application, and then obtain the record including the target simulator identifier and the intelligent agent identifier in the first data structure; a second setting module, which is used to set the state corresponding to the target simulator identifier in the record to an idle state.

[0096] As a possible implementation method of the embodiment of the present disclosure, the device also includes: a second determination module, used to determine a first number of target simulator identifiers; a calling module, used to call the simulator management service to enable the candidate simulator service when the first number is less than or equal to a first number threshold, and set the candidate accessibility service corresponding to the candidate simulator service; the state corresponding to the candidate simulator identifier of the candidate simulator service is an idle state; and a relationship establishment module, used to establish a binding relationship between the candidate simulator identifier and the intelligent agent identifier.

[0097] As a possible implementation method of the embodiment of the present disclosure, the device also includes: a first adding module, used to add the correspondence between the candidate simulator identifier, the intelligent agent identifier and the state corresponding to the candidate simulator identifier as a record to the first data structure; a second adding module, used to add the correspondence between the candidate simulator identifier and the candidate accessibility service to the second data structure.

[0098] As a possible implementation method of the embodiment of the present disclosure, the device also includes: a third determination module, used to determine whether the intelligent agent service meets the release condition; the release condition is that, within a time period greater than a specified time length, the second number of simulator identifiers bound to the intelligent agent identifier and in an idle state is greater than or equal to a second number threshold; the second number threshold is greater than the first number threshold; a selection module, used to select a simulator identifier to be released from the simulator identifiers bound to the intelligent agent identifier and in an idle state when the intelligent agent service meets the release condition; a release module, used to release the simulator service and accessibility service corresponding to the simulator identifier to be released.

[0099] As a possible implementation method of the embodiment of the present disclosure, the device also includes: a first deletion module, used to delete the records including the simulator identifier to be released and the intelligent agent identifier in the first data structure; a second deletion module, used to delete the corresponding relationship including the simulator identifier to be released in the second data structure.

[0100] It should be noted that the aforementioned explanation of the content search method based on the big model technology is also applicable to the content search device based on the big model technology of this embodiment, and will not be repeated here.

[0101] The content search device based on the big model technology of the embodiment of the present disclosure receives a search request from an access service, wherein the search request includes the content to be searched; determines at least one target application and at least one barrier-free service corresponding to the target application; calls the barrier-free service based on the content to be searched, and obtains a search result image related to the content to be searched in at least one target application; and responds to the search request according to the search result image. Among them, the barrier-free service corresponding to the target application can automatically transfer the content to be searched to the target application, thereby performing a search operation in the target application and obtaining a related search result image, which simplifies the user's operation process, avoids the need for the user to manually switch to each target application and input the content to be searched separately, shortens the search time, and improves the search efficiency.

[0102] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information are all carried out with the user's consent, comply with the relevant laws and regulations, and do not violate public order and good morals.

[0103] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0104] Figure 5A schematic block diagram of an example electronic device 500 that can be used to implement an embodiment of the present disclosure is shown. The electronic device 500 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0105] like Figure 5 As shown, the electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a ROM (Read-Only Memory) 502 or a computer program loaded from a storage unit 508 to a RAM (Random Access Memory) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An I / O (Input / Output) interface 505 is also connected to the bus 504.

[0106] Multiple components in the electronic device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0107] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a CPU (Central Processing Unit), a GPU (Graphic Processing Units), various dedicated AI (Artificial Intelligence) computing chips, various computing units running machine learning model algorithms, a DSP (Digital Signal Processor), and any appropriate processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as a content search method based on a large model technology. For example, in some embodiments, a content search method based on a large model technology may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the content search method based on the large model technology described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to execute the content search method based on the large model technology in any other appropriate manner (for example, by means of firmware).

[0108] Various embodiments of the systems and techniques described above herein may be implemented in digital electronic circuit systems, integrated circuit systems, FPGAs (Field Programmable Gate Arrays), ASICs (Application-Specific Integrated Circuits), ASSPs (Application Specific Standard Products), SOCs (System On Chips), CPLDs (Complex Programmable Logic Devices), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that may be executed and / or interpreted on a programmable system including at least one programmable processor that may be a dedicated or general-purpose programmable processor that may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0109] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0110] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, RAM, ROM, EPROM (Electrically Programmable Read-Only-Memory) or flash memory, optical fiber, CD-ROM (Compact Disc Read-Only Memory), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0111] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (Cathode-Ray Tube) or LCD (Liquid Crystal Display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0112] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: LAN (Local Area Network), WAN (Wide Area Network), the Internet, and blockchain networks.

[0113] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server combined with a blockchain.

[0114] It should be noted that artificial intelligence is a discipline that studies how computers can simulate certain human thought processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), and includes both hardware-level and software-level technologies. Artificial intelligence hardware technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, and big data processing; artificial intelligence software technologies mainly include computer vision technology, speech recognition technology, natural language processing technology, as well as machine learning / deep learning, big data processing technology, knowledge graph technology, and other major directions.

[0115] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0116] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A content search method based on a large model technology, the method comprising: receiving a search request for access services; The search request includes content to be searched; Determine at least one target application and an accessibility service corresponding to the at least one target application; Invoke the accessibility service based on the content to be searched, and obtain a search result image related to the content to be searched in the at least one target application; The search request is responded to according to the search result image.

2. The method according to claim 1, wherein: The determining of at least one target application and an accessibility service corresponding to the at least one target application includes: Determine an agent identifier of an agent service that receives the search request; According to the agent identifier, a first data structure is searched to obtain a target simulator identifier in the first data structure that is bound to the agent identifier and is in an idle state; a simulator service corresponding to the target simulator identifier runs a target application; The second data structure corresponding to the agent identifier is queried according to the target simulator identifier, and the accessibility service corresponding to the target simulator identifier in the second data structure is determined as the accessibility service corresponding to the target application.

3. The method according to claim 2, wherein: After querying the first data structure according to the agent identifier to obtain the target simulator identifier in the first data structure that is bound to the agent identifier and is in an idle state, the method further includes: Obtaining a record including the target simulator identifier and the agent identifier in the first data structure; The state corresponding to the target simulator identifier in the record is set to an occupied state.

4. The method according to claim 2, wherein: After calling the accessibility service based on the content to be searched and acquiring a search result image related to the content to be searched in the at least one target application, the method further includes: Obtaining a record including the target simulator identifier and the agent identifier in the first data structure; The state corresponding to the target simulator identifier in the record is set to an idle state.

5. The method according to claim 2, wherein: The method further comprises: determining a first number of target simulator identifiers; In the case where the first number is less than or equal to a first number threshold, calling the simulator management service to enable a candidate simulator service, and setting a candidate accessibility service corresponding to the candidate simulator service; the state corresponding to the candidate simulator identifier of the candidate simulator service is an idle state; A binding relationship between the candidate simulator identifier and the agent identifier is established.

6. The method according to claim 5, wherein: The method further comprises: Adding the correspondence between the candidate simulator identifier, the agent identifier, and the state corresponding to the candidate simulator identifier as a record to the first data structure; The correspondence between the candidate simulator identifiers and the candidate accessibility services is added to the second data structure.

7. The method according to claim 2, wherein: The method further comprises: Determine whether the agent service satisfies a release condition; the release condition is that, within a time period greater than a specified time length, a second number of simulator identifiers bound to the agent identifier and in an idle state is greater than or equal to a second number threshold; the second number threshold is greater than the first number threshold; In the case where the agent service satisfies the release condition, selecting a simulator identifier to be released from simulator identifiers bound to the agent identifier and in an idle state; The simulator service and accessibility service corresponding to the simulator identifier to be released are released.

8. The method according to claim 7, wherein: The method further comprises: Deleting the record including the identifier of the simulator to be released and the identifier of the agent in the first data structure; The corresponding relationship including the identifier of the simulator to be released in the second data structure is deleted.

9. A content search device based on large model technology, comprising: A receiving module, used for receiving a search request for access services; The search request includes content to be searched; A first determination module, configured to determine at least one target application and an accessibility service corresponding to the at least one target application; An image acquisition module, configured to call the accessibility service based on the content to be searched, and acquire a search result image related to the content to be searched in the at least one target application; The response module is used to respond to the search request according to the search result image.

10. The device according to claim 9, wherein: The first determining module is used to: Determine an agent identifier of an agent service that receives the search request; Query the first data structure according to the agent identifier, and obtain the target simulator identifier in the first data structure that is bound to the agent identifier and is in an idle state; The simulator service corresponding to the target simulator identifier runs a target application; The second data structure corresponding to the agent identifier is queried according to the target simulator identifier, and the accessibility service corresponding to the target simulator identifier in the second data structure is determined as the accessibility service corresponding to the target application.

11. The device according to claim 10, wherein: The device also includes: A first record acquisition module is used to query the first data structure according to the agent identifier, obtain the target simulator identifier in the first data structure that is bound to the agent identifier and is in an idle state, and then obtain the record including the target simulator identifier and the agent identifier in the first data structure; The first setting module is used to set the state corresponding to the target simulator identifier in the record to an occupied state.

12. The device according to claim 10, wherein: The device also includes: A second record acquisition module is used to acquire the record including the target simulator identifier and the agent identifier in the first data structure after calling the accessibility service based on the content to be searched and acquiring the search result image related to the content to be searched in the at least one target application; The second setting module is used to set the state corresponding to the target simulator identifier in the record to an idle state.

13. The device according to claim 10, wherein: The device also includes: A second determining module, configured to determine a first quantity of the target simulator identifiers; a calling module, configured to call a simulator management service to enable a candidate simulator service and set a candidate accessibility service corresponding to the candidate simulator service when the first number is less than or equal to a first number threshold; the state corresponding to the candidate simulator identifier of the candidate simulator service is an idle state; The relationship establishing module is used to establish a binding relationship between the candidate simulator identifier and the agent identifier.

14. The device according to claim 13, wherein: The device also includes: A first adding module, configured to add the correspondence between the candidate simulator identifier, the agent identifier, and the state corresponding to the candidate simulator identifier as a record to the first data structure; The second adding module is used to add the corresponding relationship between the candidate simulator identifier and the candidate accessibility service to the second data structure.

15. The device according to claim 10, wherein: The device also includes: A third determination module is used to determine whether the agent service satisfies a release condition; the release condition is that within a time period greater than a specified time length, a second number of simulator identifiers bound to the agent identifier and in an idle state is greater than or equal to a second number threshold; the second number threshold is greater than the first number threshold; A selection module, configured to select a simulator identifier to be released from simulator identifiers bound to the agent identifier and in an idle state when the agent service satisfies the release condition; The release module is used to release the simulator service and accessibility service corresponding to the simulator identifier to be released.

16. The device according to claim 15, wherein: The device also includes: A first deleting module, used for deleting the record including the identifier of the simulator to be released and the identifier of the agent in the first data structure; The second deleting module is used to delete the corresponding relationship including the identifier of the simulator to be released in the second data structure.

17. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 8.

18. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-8.

19. A computer program product, comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 8.

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