Artificial intelligence-based hybrid page jump method, device and equipment

Abstract

The present invention discloses a hybrid page jump method based on artificial intelligence, applying the field of artificial intelligence technology to solve the technical problems of inconsistent page jump methods within the same client, resulting in business intrusion in route jumps, high maintenance costs, and the susceptibility to chaotic jumps. The method provided by the present invention includes: upon receiving an instruction to jump to a next target page from a current page, obtaining the URL address of the target page; identifying whether the URL address of the target page contains characters indicating a preset engine type, and if so, using the URL address of the target page as a parameter of a push function in the AINavigation class; calling the push function in the AINavigation class on the current page, and causing the application to jump from the current page to the next target page.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an artificial intelligence-based hybrid page jump method, device, computer equipment and storage device. Background Art

[0002] As businesses become more and more complex, in order to adapt to business development more quickly, situations have emerged where native (Android / iOS), H5, ReactNative and other jump technologies appear simultaneously in the same client, which inevitably involves navigation issues between them. The current common solution is for each to use its own navigation, that is, the native end uses the native platform, the H5 end uses the framework react-router or vue-router, and ReactNative uses the framework react-navigation.

[0003] The inconsistent navigation redirection methods between native platforms, HTML5, and ReactNative led to confusion in the navigation stack. In scenarios like native->HTML->ReactNative->native, if a single HTML5 or ReactNative page is used, it's necessary to determine whether the previous page was native, HTML5, or ReactNative when returning. If multiple HTML5 or ReactNative pages are used, it's still necessary to distinguish between native, HTML5, and ReactNative when redirecting. This introduces business intrusion into routing, increasing maintenance costs while making the cross-platform stack difficult to understand and potentially causing confusion.

[0004] To address the problem of inconsistent navigation jump methods within the same client, which leads to business intrusion during route jumps, some people are currently trying to solve the problem by adding Flutter and other methods. However, this can make cross-end navigation more confusing and prone to jump errors. Summary of the Invention

[0005] The embodiments of the present invention provide a hybrid page jump method, apparatus, computer equipment and storage medium based on artificial intelligence to solve the technical problem that page jump methods are inconsistent in the same client, resulting in business intrusion in routing jumps, high maintenance costs and easy occurrence of chaotic jumps.

[0006] A hybrid page jump method based on artificial intelligence, comprising:

[0007] When receiving an instruction to jump to a next target page from a current page, obtaining the URL address of the target page, wherein the current page and the target page are pages of different engine types in the same application;

[0008] Identify whether the URL address of the target page contains characters indicating a preset engine type;

[0009] When it is recognized that the URL address of the target page contains the character, the URL address of the target page is used as a parameter of the push function in the AINavigation class;

[0010] The push function in the AINavigation class is called in the current page, and the application jumps from the current page to the next target page.

[0011] A hybrid page jump device based on artificial intelligence, comprising:

[0012] An address acquisition module, configured to acquire the URL address of a target page when receiving an instruction to jump to the next target page from the current page, wherein the current page and the target page are pages of different engine types in the same application;

[0013] A character recognition module, configured to identify whether the URL address of the target page contains characters indicating a preset engine type;

[0014] a parameter determination module, configured to use the URL of the target page as a parameter of a push function in the AINavigation class when it is recognized that the URL of the target page contains the character;

[0015] The calling module is used to call the push function in the class AINavigation in the current page, so that the application jumps from the current page to the next target page.

[0016] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the above-mentioned hybrid page jump method based on artificial intelligence are implemented.

[0017] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the above-mentioned artificial intelligence-based hybrid page jump method.

[0018] The present application proposes an artificial intelligence-based hybrid page jump method, device, computer equipment and storage medium. When receiving an instruction to jump to the next target page from the current page, the URL address of the target page is obtained, the current page and the target page are pages of different engine types, and the current page and the target page belong to pages in the same application. Then, it is identified whether the URL address of the target page contains characters indicating the preset engine type. When the identification result is yes, the URL address of the target page is used as the parameter of the push function in the AINavigation class. Finally, the push function in the AINavigation class is called in the current page to jump from the current page to the next target page, so that pages of native, H5, ReactNative and other types of engines are managed by the same engine. When more technology stacks need to be introduced in the future, it is only necessary to implement the loading logic in AINavigation to seamlessly use the existing navigation function. In general, it can achieve the effect of reducing development costs and improving work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 This is a schematic diagram of an application environment of a hybrid page jump method based on artificial intelligence in one embodiment of the present invention;

[0021] Figure 2 This is a flow chart of a hybrid page jump method based on artificial intelligence in one embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of the relationship between the engine, container, and page in one embodiment of the present invention;

[0023] Figure 4 This is a schematic diagram illustrating page jumps of different engine types in one embodiment of the present invention;

[0024] Figure 5 1 is a schematic structural diagram of a hybrid page jump device based on artificial intelligence in one embodiment of the present invention;

[0025] Figure 6 FIG. 1 is a schematic diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] The hybrid page jump method based on artificial intelligence provided by this application can be applied in Figure 1 In an application environment, the computer device can communicate with the server via a network. The computer device can include, but is not limited to, various personal computers, laptops, smartphones, tablet computers, and portable wearable devices. The server can be implemented as a standalone server or a server cluster consisting of multiple servers.

[0028] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Artificial Intelligence (AI) is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to achieve optimal results.

[0029] Fundamental AI technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, speech processing, natural language processing, and machine learning / deep learning.

[0030] In one embodiment, if Figure 2 As shown, a hybrid page jump method based on artificial intelligence is provided, which is applied to the same application installed in a computer device. Figure 1 The computer device in the embodiment is used as an example to illustrate, which includes the following steps S101 to S104.

[0031] S101. When receiving an instruction to jump to the next target page from the current page, obtain the URL address of the target page, the current page and the target page are pages of different engine types, and the current page and the target page belong to pages in the same application.

[0032] In one embodiment, the URL address of the target page can be generated according to a preset rule.

[0033] Furthermore, the step of generating the URL address of the target page includes:

[0034] Obtain the engine type, unique identifier, and required parameters of the target page;

[0035] Obtain the URL address format template;

[0036] According to the correspondence between the fields in the preset URL address format template and the engine type, unique identifier, and required parameters of the target page, fill the engine type, unique identifier, and required parameters of the target page into the URL address format template to obtain the URL address of the target page.

[0037] In one embodiment, the URL address format template is, for example, http: / / router-url?jump=scheme: / / identifier?params, where the field "scheme" is correspondingly replaced with the engine type of the target page, "identifier" is correspondingly replaced with the unique identifier of the target page, and "params" is correspondingly replaced with the parameters required by the target page. Here, the values of scheme are defined as native, h5, rn, etc., corresponding to pages with engine types of native, H5, and ReactNative respectively. For example, if you need to jump to the native home page and the parameter corresponding to the character "params" can be city, then the URL address of the target page can be expressed as http: / / router-url?jump=native: / / home?city=Shenzhen.

[0038] Among them, the way to receive the instruction to jump to the next target page from the current page is, for example, that the user triggers the "next page" button, or jumps to other pages according to the object clicked by the user.

[0039] S102. Identify whether the URL address of the target page contains characters representing the preset engine type.

[0040] In one embodiment, the characters representing the preset engine type include but are not limited to native, h5, rn. Among them, native represents a native page, h5 represents an Hx page, and rn represents a ReactNative page. Further, this native page can be a page of the Android operating system or a page of the iOS system.

[0041] S103. When it is identified that the URL address of the target page contains the character, use the URL address of the target page as the parameter of the push function in the AINavigation class.

[0042] It is understandable that if it is recognized that the URL address of the target page contains characters indicating the preset engine type, it means that the target page can execute routing, otherwise, routing is not executed.

[0043] In one embodiment, the characters representing the preset engine type are, for example, native, h5, rn, etc. The push function in the AINavigation class can be expressed as "AINavigation.push(parameters)", and after filling in the parameters, it is expressed as AINavigation.push(URL).

[0044] S104: calling the push function in the AINavigation class in the current page, and causing the application to jump from the current page to the next target page.

[0045] According to an application scenario of this embodiment, for example, when you need to jump from page A of the native engine type to page B of the H5 engine type, the URL address of page B is, for example, http: / / router-url?jump=h5: / / aPage. You only need to call AINavigation.push(http: / / router-url?jump=h5: / / bPage) in page A. Similarly, when you need to jump from page C of the ReactNative engine type to page D of the ReactNative engine type, you can call AINavigation.push(http: / / router-url?jump=rn: / / dPage). The rest of the jumps are similar.

[0046] The AI-based hybrid page redirection method proposed in this embodiment uses unified routing rules. By obtaining characters of the corresponding engine type for matching, routing is executed if a match is found, and not executed if a match is found. Currently, implementing routing rules for each platform separately will undoubtedly increase logical complexity and code maintainability. This embodiment uses unified routing rules to smooth out differences at the code level, making it more conducive to cross-platform collaboration.

[0047] In one embodiment, the URL address of the target page carries the engine type of the target page and the unique identifier of the target page, and the application jumps from the current page to the next target page, including:

[0048] Obtaining the unique identifier of the target page and the engine type carried in the URL address;

[0049] A page of a corresponding engine type is selected from the page container corresponding to the unique identifier and displayed.

[0050] The navigation management of the hybrid page jump method based on artificial intelligence proposed in this embodiment adopts a single-engine multi-page container approach. The engine can be understood as a navigation center, that is, the native, H5, and ReactNative navigations each have their own engines responsible for managing their respective navigation jumps. This embodiment manages different types of engines in a unified manner through the class AINavigation and the corresponding jump and fallback functions. The page container in this embodiment can be understood as a page, such as a home page, a login page, etc. The same page container (such as the home page) is pre-configured with page containers of various engine types. For example, the home page container includes a home page of the native engine type, a page container of the H5 engine type, and a page container of the ReactNative engine type. When selecting which page in the page container to use as the target jump page, it is obtained by matching the engine type of the target page carried in the URL address.

[0051] Figure 3 This is a schematic diagram of the relationship between the engine, container and page in one embodiment of the present invention. It can be understood that: Figure 3 The "engine" in the _ represents one type of engine. Figure 3 An application scenario of this embodiment is described as follows. When implementing the technology, the following three points need to be noted:

[0052] ① The native navigation engine uniformly calls native, H5, ReactNative and other page containers, defines the AINavigation class, and internally simulates the maintenance of the native navigation stack.

[0053] ② The unique number of the page container uses the scheme + identifier value in the unified routing rule and is encrypted with MD5 (Message Digest Algorithm MD5) as the key.

[0054] ③For example, the implementation of page A can be any of the three types: native page A, H5 page A, and ReactNative page A.

[0055] When AINavigation jumps, it is pushed into the stack through AINavigation.push(url) and popped out of the stack through AINavigation.pop(key) or AINavigation.pop(-2). The key is the number defined in ②.

[0056] In one embodiment, when a new engine type and a corresponding page need to be added to the application, before receiving an instruction to jump to a next target page from the current page, the method further includes:

[0057] Get the pre-configured new pages corresponding to the newly added engine types;

[0058] Add each of the new pages to the corresponding page container;

[0059] A URL address is configured for each of the new pages, wherein the URL address includes a unique identifier of the new page and a character indicating the newly added engine type.

[0060] It can be understood that the display effect and content of the "new page" in this embodiment are the same as those of the old page. The difference is that the engine type of the "new page" is newly added, and the display method of the new page is reconfigured according to the display method required by the newly added engine type.

[0061] According to an application scenario of this embodiment, for example, when a new engine type M is added to an application based on business needs, it is necessary to configure all pages of the newly added engine type based on all pages included in the application (for example, a total of n pages). All pages of the newly added engine type are configured to have the same number, display effect, and display content as the original pages included in the application. The URL address of each new page is configured so that when jumping to the page of the newly added engine type, the page jump can be achieved by directly adding the URL address of the new page in the AINavigation class.

[0062] This embodiment provides a method for adding new engine types and corresponding pages, so that when more engine types of technology stacks need to be introduced in the future, only the loading logic needs to be implemented in AINavigation to seamlessly use the existing navigation functions, which can reduce development costs and thus improve programming efficiency.

[0063] In one embodiment, when receiving an instruction to roll back to a history page from the current page, the method further includes:

[0064] Acquire the attributes of the historical page, and determine whether the engine types of the current page and the historical page are the same or different;

[0065] Use the attributes of the history page as parameters of the pop function in the AINavigation class;

[0066] The pop function in the AINavigation class is called in the current page, and the application program rolls back from the current page to the history page.

[0067] It is understandable that the function pop serves as the return function of the class AINavigation.

[0068] In one embodiment, the attributes of the historical page include the engine type of the historical page and the unique identifier of the historical page, and using the attributes of the historical page as parameters of the pop function in the AINavigation class includes:

[0069] The engine type of the historical page and the unique identifier of the historical page are used as parameters of the pop function in the AINavigation class.

[0070] In one embodiment, optionally, taking the attributes of the historical page as parameters of a pop function in the AINavigation class includes:

[0071] Concatenate the engine type of the historical page and the unique identifier of the historical page;

[0072] The concatenated result is encrypted using the MD5 information digest algorithm to obtain the corresponding string;

[0073] The string is used as a parameter of the pop function in the AINavigation class.

[0074] It is understood that MD5 (MD5 Message-Digest Algorithm) is a widely used cryptographic hash function that can generate a 128-bit (16-byte) hash value to ensure the integrity and consistency of information transmission.

[0075] Figure 4 This is a schematic diagram of page jumps of different engine types according to an embodiment of the present invention. Figure 4 As shown, when Figure 4 When jumping back to the specified position, that is, when the native page F falls back to the ReactNative page C, you can use AINavigation.pop(key) to implement this function. The key is the string of rn+cPage converted by MD5.

[0076] In one embodiment, when receiving an instruction to roll back to a history page from the current page, the method further includes:

[0077] Obtain the number of pages required to roll back from the current page to the historical page;

[0078] The number is used as the parameter of the pop function in the AINavigation class;

[0079] The pop function in the AINavigation class is called in the current page, and the application program rolls back from the current page to the history page.

[0080] In one embodiment, the number of pages required to roll back from the current page to the historical page may be 2, 3, or 1, etc. When the number of pages required to roll back from the current page to the historical page is 2, the corresponding implementation code is, for example: AINavigation.pop(-2).

[0081] Using a single engine and multiple containers, the native class manages the engine for native, H5, ReactNative, and other types of pages. When normal redirects, mixed redirects, and fallbacks to designated locations occur, all can be handled in a unified manner, without considering differences between platforms and without any intrusion into specific business code. This embodiment follows a unified routing rule, and the code implementation is independent of the technology stack, making it more conducive to cross-end redirects.

[0082] The artificial intelligence-based hybrid page jump method proposed in this embodiment obtains the URL address of the target page when receiving an instruction to jump to the next target page from the current page. The current page and the target page are pages of different engine types, and the current page and the target page belong to pages in the same application. Then, it is identified whether the URL address of the target page contains characters indicating the preset engine type. When the identification result is yes, the URL address of the target page is used as the parameter of the push function in the AINavigation class. Finally, the push function in the AINavigation class is called in the current page to jump from the current page to the next target page, so that pages of native, H5, ReactNative and other types of engines are managed by the same engine. When more technology stacks need to be introduced in the future, it is only necessary to implement the loading logic in AINavigation to seamlessly use the existing navigation function. In general, this can reduce development costs and improve work efficiency.

[0083] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0084] In one embodiment, a hybrid page jump device based on artificial intelligence is provided, and the hybrid page jump device based on artificial intelligence corresponds to the hybrid page jump method based on artificial intelligence in the above embodiment. Figure 5As shown, the hybrid page jump device 100 based on artificial intelligence includes an address acquisition module 11, a character recognition module 12, a parameter determination module 13 and a calling module 14.

[0085] The detailed description of each functional module is as follows:

[0086] An address acquisition module 11 is configured to acquire the URL of a target page when receiving an instruction to jump to the next target page from the current page, wherein the current page and the target page are pages of different engine types in the same application;

[0087] A character recognition module 12 is used to identify whether the URL address of the target page contains characters indicating a preset engine type;

[0088] A parameter determination module 13 is configured to use the URL of the target page as a parameter of a push function in the AINavigation class when it is recognized that the URL of the target page contains the character;

[0089] The calling module 14 is configured to call the push function in the class AINavigation in the current page, so that the application program jumps from the current page to the next target page.

[0090] In one embodiment, the address acquisition module 11 includes:

[0091] A parameter acquisition unit, configured to acquire the engine type, unique identifier, and required parameters of the target page;

[0092] Template acquisition unit, used to obtain URL address format template;

[0093] The filling unit is used to fill the engine type, unique identifier and required parameters of the target page into the URL address format template according to the correspondence between the fields in the preset URL address format template and the engine type, unique identifier and required parameters to obtain the URL address of the target page.

[0094] In one embodiment, the URL address of the target page carries the engine type of the target page and the unique identifier of the target page. The calling module 14 specifically includes:

[0095] an identification obtaining unit, configured to obtain the unique identification of the target page and the engine type carried in the URL address;

[0096] The display unit is configured to select and display a page of a corresponding engine type from the page container corresponding to the unique identifier.

[0097] In one embodiment, the hybrid page jump device 100 based on artificial intelligence further includes:

[0098] A new page acquisition module is used to obtain each new page that is pre-configured and corresponds to the newly added engine type;

[0099] An adding module, used for adding each of the new pages to the corresponding page container;

[0100] The configuration module is used to configure the URL address of each new page, where the URL address includes a unique identifier of the new page and a character indicating the newly added engine type.

[0101] In one embodiment, when receiving an instruction to roll back to a historical page from a current page, the hybrid page jump device 100 based on artificial intelligence further includes:

[0102] An attribute acquisition module, configured to acquire attributes of the historical page, wherein the engine types of the current page and the historical page are the same or different;

[0103] A fallback parameter determination module, configured to use the attributes of the historical page as parameters of a pop function in the AINavigation class;

[0104] The rollback module is used to call the pop function in the AINavigation class in the current page, and the application rolls back from the current page to the history page.

[0105] In one embodiment, the attributes of the historical page include the engine type of the historical page and the unique identifier of the historical page. The fallback parameter determination module is specifically used to use the engine type of the historical page and the unique identifier of the historical page as parameters of the pop function in the AINavigation class.

[0106] In one embodiment, the fallback parameter determination module specifically includes:

[0107] a splicing unit, configured to splice and combine the engine type of the historical page and the unique identifier of the historical page;

[0108] The encryption unit is used to encrypt the result of the splicing combination using the MD5 information digest algorithm to obtain a corresponding character string;

[0109] The parameter determination unit is used to use the character string as a parameter of the pop function in the AINavigation class.

[0110] The meaning of "first" and "second" in the above modules / units is only to distinguish different modules / units, and is not used to limit which module / unit has a higher priority or other limiting meanings. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The division of modules in this application is only a logical division, and other division methods may be used in actual applications.

[0111] For the specific definition of the jump device of the hybrid page based on artificial intelligence, please refer to the definition of the jump method of the hybrid page based on artificial intelligence above, which will not be repeated here. The various modules in the above-mentioned jump device of the hybrid page based on artificial intelligence can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0112] In one embodiment, a computer device is provided, which may be a server. The computer device includes a processor, a memory, a network interface, and a database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a storage medium and an internal memory. The storage medium includes a non-volatile storage medium and / or a volatile storage medium, and the storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the storage medium. The database of the computer device is used to store data involved in a hybrid page jump method based on artificial intelligence. The network interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a hybrid page jump method based on artificial intelligence is implemented.

[0113] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 6As shown. The computer device includes a processor, memory, network interface, display screen and input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a storage medium and an internal memory. The storage medium includes a non-volatile storage medium and / or a volatile storage medium, and the storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it implements a hybrid page jump method based on artificial intelligence.

[0114] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the hybrid page jump method based on artificial intelligence in the above embodiment are implemented, for example: Figure 2 Alternatively, when the processor executes the computer program, the functions of each module / unit of the jump device for hybrid pages based on artificial intelligence in the above embodiment are realized, such as Figure 5 The functions of modules 11 to 14 are shown in FIG. 3 and will not be described in detail here to avoid repetition.

[0115] The processor may be a central processing unit (CPU), other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the computer device, connecting various parts of the entire computer device using various interfaces and lines.

[0116] The memory may be used to store the computer programs and / or modules. The processor implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory and calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store an operating system, at least one application required for a function (such as a sound playback function, an image playback function, etc.); and the data storage area may store data created based on the use of the mobile phone (such as audio data, video data, etc.).

[0117] The memory may be integrated into the processor or may be provided separately from the processor.

[0118] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the hybrid page jump method based on artificial intelligence in the above embodiment are implemented, such as Figure 2 Alternatively, when the computer program is executed by a processor, the functions of each module / unit of the jump device for hybrid pages based on artificial intelligence in the above embodiment are realized, such as Figure 5 The functions of modules 11 to 14 are shown in FIG. 3 and will not be described in detail here to avoid repetition.

[0119] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile and / or volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0120] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0121] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should all be included in the scope of protection of the present invention.

Claims

1. A hybrid page jump method based on artificial intelligence, characterized in that: include: When receiving an instruction to jump to a next target page from a current page, obtaining the URL address of the target page, wherein the current page and the target page are pages of different engine types in the same application; Identify whether the URL address of the target page contains characters indicating a preset engine type; When it is recognized that the URL address of the target page contains the character, the URL address of the target page is used as a parameter of the push function in the AINavigation class; Invoke the push function in the AINavigation class in the current page, and the application jumps from the current page to the next target page; The URL address of the target page carries the engine type of the target page and the unique identifier of the target page. The application jumps from the current page to the next target page, including: Obtaining the unique identifier of the target page and the engine type carried in the URL address; Selecting and displaying a page of a corresponding engine type from the page container corresponding to the unique identifier; Navigation management adopts a single-engine multi-page container approach, and manages different types of engines uniformly through the AINavigation class and corresponding jump and fallback functions; The native navigation engine calls native, H5, and ReactNative page containers, defines the AINavigation class, and internally simulates the maintenance of the native navigation stack. The unique number of the page container uses the scheme+identifier value in the unified routing rule, encrypted with MD5, as the key. The page can be any of the three types: native page, H5 page, and ReactNative page. When AINavigation jumps, it is pushed into the stack through AINavigation.push(url) and popped out of the stack through AINavigation.pop(key) or AINavigation.pop(-2). The key is the page container number.

2. The method for jumping to a hybrid page based on artificial intelligence according to claim 1, characterized in that: Obtaining the URL address of the target page includes: Obtain the engine type, unique identifier, and required parameters of the target page; Get the URL address format template; According to the correspondence between the fields in the preset URL address format template and the engine type, unique identifier and required parameters, the engine type, unique identifier and required parameters of the target page are filled in the URL address format template to obtain the URL address of the target page.

3. The method for jumping to a hybrid page based on artificial intelligence according to claim 1, characterized in that: Before receiving an instruction to jump to a next target page from the current page, the method further includes: Get the pre-configured new pages corresponding to the newly added engine types; Add each of the new pages to the corresponding page container; A URL address is configured for each of the new pages, wherein the URL address includes a unique identifier of the new page and a character indicating the newly added engine type.

4. The method for jumping to a hybrid page based on artificial intelligence according to claim 1, characterized in that: When receiving an instruction to roll back to a history page from the current page, the method further includes: Acquire the attributes of the historical page, and determine whether the engine types of the current page and the historical page are the same or different; Use the attributes of the history page as parameters of the pop function in the AINavigation class; The pop function in the AINavigation class is called in the current page, and the application program rolls back from the current page to the history page.

5. The method for jumping to a hybrid page based on artificial intelligence according to claim 4, characterized in that: The attributes of the historical page include the engine type of the historical page and the unique identifier of the historical page. The method of using the attributes of the historical page as parameters of the pop function in the AINavigation class includes: The engine type of the historical page and the unique identifier of the historical page are used as parameters of the pop function in the AINavigation class.

6. The method for jumping to a hybrid page based on artificial intelligence according to claim 4, characterized in that: The method of using the attributes of the history page as parameters of the pop function in the AINavigation class includes: Concatenate the engine type of the historical page and the unique identifier of the historical page; The concatenated result is encrypted using the MD5 information digest algorithm to obtain the corresponding string; The string is used as a parameter of the pop function in the AINavigation class.

7. A hybrid page jump device based on artificial intelligence, the device being used to implement the steps of the hybrid page jump method based on artificial intelligence according to any one of claims 1 to 6, characterized in that: include: An address acquisition module, configured to acquire the URL address of a target page when receiving an instruction to jump to the next target page from the current page, wherein the current page and the target page are pages of different engine types in the same application; A character recognition module, configured to identify whether the URL address of the target page contains characters indicating a preset engine type; a parameter determination module, configured to use the URL of the target page as a parameter of a push function in the AINavigation class when it is recognized that the URL of the target page contains the character; The calling module is used to call the push function in the class AINavigation in the current page, so that the application jumps from the current page to the next target page.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the hybrid page jump method based on artificial intelligence as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the hybrid page jump method based on artificial intelligence as claimed in any one of claims 1 to 6 are implemented.

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