Intelligent consultation interaction method and device, equipment and storage medium

Abstract

The invention discloses an intelligent consultation interaction method and device, equipment and a storage medium. The method comprises the steps of obtaining consultation interaction information which is input by an information consultation object and is associated with automobile finance; according to the consultation interaction information and an interaction response decision tree configured for the intelligent interaction robot in advance, whether AI response assistance needs to be executed or not is determined; and under the condition that the AI response assistance needs to be executed, determining a target response result according to the complete interaction information and the AI response assistance in the consultation interaction process. According to the method, high-quality and high-complexity content reply can be realized, and the dialogue interaction capability and quality are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent interaction technologies, and particularly to an intelligent consultation interaction method, device, equipment, and storage medium. Background Art

[0002] With the rapid popularization and development of artificial intelligence (AI) technologies, numerous intelligent interaction robots have emerged in the market, playing an increasingly important role in various industries. In the field of automotive finance, these robots are used to handle a series of tasks such as customer consultation, loan approval, and risk assessment. However, the workflow control methods adopted by different types of robots have a significant impact on the user experience and service quality.

[0003] In the field of automotive finance, some use a pure decision tree workflow to execute interactions, while some use an AI workflow to execute responses. The method of pure decision tree process control is based on a preset dialogue process and is difficult to respond to the personalized needs of users or handle complex situations; the method of pure AI workflow control lacks the ability of dialogue interaction. When there are both interaction requirements and the need to handle personalized or complex responses, the above two process control methods are difficult to achieve the desired effect and the experience is poor. Summary of the Invention

[0004] The present invention provides an intelligent consultation interaction method, device, equipment, and storage medium to achieve responses to high-quality and high-complexity content, effectively improving the dialogue interaction ability and quality.

[0005] According to one aspect of the present invention, there is provided an intelligent consultation interaction method applied to an intelligent interaction robot. The method includes:

[0006] Obtaining consultation interaction information related to automotive finance input by an information consultation object;

[0007] Determining whether it is necessary to execute AI response assistance according to the consultation interaction information and an interaction response decision tree pre-configured for the intelligent interaction robot;

[0008] In the case where it is necessary to execute the AI response assistance, determining a target response result according to the complete interaction information and the AI response assistance in the current consultation interaction process.

[0009] According to another aspect of the present invention, there is provided an intelligent consultation interaction device applied to an intelligent interaction robot. The device includes:

[0010] An interaction information acquisition module, configured to obtain consultation interaction information related to automotive finance input by an information consultation object;

[0011] An interactive response decision module, configured to determine whether to perform AI response assistance according to the consultation interaction information and an interactive response decision tree pre-configured for the intelligent interaction robot;

[0012] A response result determination module, configured to, when it is necessary to perform the AI response assistance, determine a target response result according to the complete interaction information and the AI response assistance in the current consultation interaction process.

[0013] According to another aspect of the present invention, there is provided an electronic device, including:

[0014] At least one processor; and

[0015] A memory communicatively connected to the at least one processor; wherein,

[0016] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the intelligent consultation interaction method according to any embodiment of the present invention.

[0017] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for implementing the intelligent consultation interaction method according to any embodiment of the present invention when executed by a processor.

[0018] The technical solution of the embodiment of the present invention obtains consultation interaction information related to auto finance input by an information consultation object. According to the consultation interaction information and an interactive response decision tree pre-configured for the intelligent interaction robot, it is determined whether to perform AI response assistance. When it is necessary to perform the AI response assistance, a target response result is determined according to the complete interaction information and the AI response assistance in the current consultation interaction process. The present invention solves problems such as poor user interaction experience, low problem handling efficiency, insufficient decision-making accuracy, high operation cost, and changing market demands in the field of auto finance. By combining a decision tree and an AI workflow, a new solution can be provided for the robot interaction process control in the field of auto finance, enabling the robot to be more intelligent and flexible when processing user inputs, significantly improving the problem handling efficiency, and at the same time reducing the need for human customer service, thereby reducing the operation cost.

[0019] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0021] Figure 1 is a flowchart of an intelligent consultation interaction method provided in Embodiment 1 of the present invention;

[0022] Figure 2 is a flowchart of an intelligent consultation interaction method provided in Embodiment 2 of the present invention;

[0023] Figure 3 is a structural diagram of an intelligent consultation interaction device provided in Embodiment 3 of the present invention;

[0024] Figure 4 is a schematic structural diagram of an electronic device for implementing the intelligent consultation interaction method of the embodiments of the present invention. Detailed Embodiments

[0025] In order to enable those skilled in the art of the present technology to better understand the solutions of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0026] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above accompanying drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0027] Embodiment 1

[0028] Figure 1The flowchart of an intelligent consultation interaction method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation where a user consults an intelligent interaction robot about issues related to auto finance. This method can be executed by an intelligent consultation interaction device, which can be implemented in the form of hardware and / or software, and can be configured in an electronic device. As Figure 1 shown, the method includes:

[0029] S101. Obtain the consultation interaction information related to auto finance input by the information consultation object.

[0030] It should be noted that the information consultation object can refer to a user who consults issues related to the auto finance field. The consultation method of the information consultation object can be a voice consultation method and / or a text consultation method, etc. The consultation interaction information can refer to the communication information related to the auto finance field proposed by the information consultation object. Exemplarily, the consultation interaction information can include consultation questions, loan approval questions, risk assessment questions, etc.

[0031] It is worth noting that the intelligent interaction robot can exist in the form of a physical mobile robot in a store, or exist in the form of a server in a telephone consultation or an online consultation. The specific setting method of the intelligent interaction robot can be set according to actual needs.

[0032] Specifically, the intelligent interaction robot receives the consultation interaction information related to auto finance input by the information consultation object through text input or voice input.

[0033] S102. Determine whether it is necessary to execute AI response assistance according to the consultation interaction information and the interaction response decision tree pre-configured for the intelligent interaction robot.

[0034] It should be noted that the interaction response decision tree stores pre-set response processes, pre-set consultation questions, and pre-set response results corresponding to the pre-set consultation questions. AI response assistance can execute other consultation questions outside the pre-set consultation questions.

[0035] Exemplarily, the interaction response decision tree at least includes response branch nodes and response result nodes. The response branch nodes can refer to the branch nodes corresponding to different consultation question conditions. The response result nodes can refer to the result nodes matching the consultation questions.

[0036] Specifically, when the consultation interaction information input by the information consultation object reaches the decision tree node, it is judged whether it is necessary to run the AI response assistance process according to the configuration and process of this node.

[0037] Exemplarily, determining whether to perform AI response assistance according to the consultation interaction information and the interaction response decision tree pre-configured for the intelligent interaction robot includes:

[0038] Perform pairing processing on the consultation interaction information and the interaction response decision tree. If it is determined that there is a response result in the interaction response decision tree that matches the consultation interaction information, then it is determined that the AI response assistance does not need to be performed. Otherwise, it is determined that the AI response assistance needs to be performed.

[0039] Specifically, the consultation interaction information can be paired with the interaction response decision tree to determine whether there is a response result in the interaction response decision tree that matches the consultation interaction information. If it exists, it is determined that the AI response assistance does not need to be performed. If it does not exist, it is determined that the AI response assistance needs to be performed.

[0040] Exemplarily, determining whether to perform AI response assistance according to the consultation interaction information and the interaction response decision tree pre-configured for the intelligent interaction robot includes:

[0041] Perform parsing and recognition processing on the consultation interaction information through the response nodes in the interaction response decision tree; if the consultation intention of the consultation interaction information is recognized by the response nodes, then it is determined that the AI response assistance does not need to be performed; otherwise, it is determined that the AI response assistance needs to be performed.

[0042] It should be noted that the interaction response decision tree includes branch judgments and response nodes. Branch judgments exist in each process node. The role of the response node is to determine the intention according to the user input, judge the next node direction according to the user intention, and call AI-assisted response, or end the session.

[0043] Specifically, analyze the consultation interaction information through the response nodes in the interaction response decision tree. When the consultation intention represented by the consultation interaction information can be determined, there is no need for the intervention of AI response assistance. If the consultation intention represented by the consultation interaction information cannot be determined, the intervention of AI response assistance is required.

[0044] It should be noted that in the case where the AI response assistance needs to be performed, it is also necessary to determine whether the current response node in the interaction response decision tree enables the AI response assistance. If it is enabled, the AI response assistance can be called to execute the AI response assistance workflow. If it is not enabled, the decision tree process continues.

[0045] S103. In the case where the AI response assistance needs to be performed, determine the target response result according to the complete interaction information and the AI response assistance in the current consultation interaction process.

[0046] It should be noted that the AI response assistance workflow at least includes requesting the LLM, intent recognition, web search, and knowledge base recognition, etc.

[0047] Specifically, in the case where the AI response assistance needs to be executed, the execution process of the AI response assistance workflow is entered, and the target response result is determined according to the AI response assistance. If not, continue the conversation interaction according to the branch conditions of the decision tree or generate the target response result according to the response result information corresponding to the consultation interaction information in the interaction response decision tree.

[0048] Exemplarily, after determining the target response result, it further includes:

[0049] Continue to receive the consultation interaction information input by the information consultation object until the conversation ends or a preset termination condition is reached.

[0050] Specifically, after the AI workflow is executed, the obtained response result is fed back to the decision tree node, and the decision tree node processes the response result (such as format adjustment, content screening, etc.) to better present it to the user. Continue to receive the consultation interaction information input by the information consultation object, and continue the conversation interaction with the user according to the branch judgment conditions of the decision tree until the conversation ends or a preset termination condition is reached.

[0051] Exemplarily, determining the target response result according to the complete interaction information and AI response assistance in the current consultation interaction process includes: performing natural language understanding on the complete interaction information to generate interaction semantic information; determining the current interaction intent of the information consultation object based on the interaction semantic information; and determining the target response result according to the current interaction intent and the AI response tool.

[0052] Among them, the complete interaction information may refer to all the interaction information between the information consultation object and the intelligent interaction robot during the current interaction process. The AI response tool may include, but is not limited to, web search tools, knowledge base retrieval tools, and AI large model tools, etc.

[0053] Specifically, the current input session and historical input session of the information consultation object during the current interaction process are integrated and input into the AI workflow, and natural language understanding is performed by requesting the LLM to generate interaction semantic information. Analyze the intent input by the information consultation object according to the interaction semantic information to more accurately reply to the information consultation object. Information related to the complete interaction information can be searched on the Internet to enrich the reply content, or knowledge related to the complete interaction information can be searched in the preset knowledge base to provide an accurate reply. That is, after the AI workflow executes the above steps by configuring a custom process, a specific reply result is obtained.

[0054] The technical solution of the embodiment of the present invention obtains the consultation interaction information related to auto finance input by the information consultation object. According to the consultation interaction information and the interaction response decision tree pre-configured for the intelligent interaction robot, it is determined whether AI response assistance needs to be executed. In the case where the AI response assistance needs to be executed, the target response result is determined according to the complete interaction information and the AI response assistance in the current consultation interaction process. The present invention solves problems such as poor user interaction experience, low problem handling efficiency, insufficient decision-making accuracy, high operating costs, and changing market demands in the field of auto finance. By combining the decision tree and the AI workflow, a new solution can be provided for the robot interaction process control in the field of auto finance, enabling the robot to be more intelligent and flexible when processing user inputs, significantly improving the problem handling efficiency, and at the same time reducing the need for human customer service, thereby reducing the operating costs.

[0055] Embodiment 2

[0056] Figure 2 The flowchart of an intelligent consultation interaction method provided by Embodiment 2 of the present invention is the preferred implementation manner of the above embodiments. As Figure 2 shown, the method includes:

[0057] (1) Initialize the decision tree flowchart and the AI flowchart of the intelligent interaction robot, and implant the AI workflow to be executed at the corresponding nodes in the decision tree flowchart;

[0058] (2) Determine whether to run the AI response assistance when running the decision tree node;

[0059] (3) Integrate the current input and the session history into the complete interaction information and input it into the AI workflow;

[0060] (4) The AI workflow works based on the complete interaction information, including steps such as LLM, intent recognition, network search, knowledge base retrieval, etc. (through configuring a custom process);

[0061] (5) After the AI workflow is executed, obtain the response result and feedback it to the decision tree node;

[0062] (6) The decision tree node returns the response content to the information consultation user and continues the session interaction according to the branch judgment condition.

[0063] Embodiment 3

[0064] Figure 3 The structural schematic diagram of an intelligent consultation interaction device provided by Embodiment 3 of the present invention. As Figure 3 shown, the device includes:

[0065] The interaction information acquisition module 301 is used to acquire the consultation interaction information related to auto finance input by the information consultation object;

[0066] The interaction response decision module 302 is used to determine whether to perform AI response assistance according to the consultation interaction information and the interaction response decision tree pre-configured for the intelligent interaction robot;

[0067] The response result determination module 303 is used to determine the target response result according to the complete interaction information and AI response assistance in the current consultation interaction process when it is necessary to perform the AI response assistance.

[0068] Optionally, the interaction response decision module 302 is specifically used for:

[0069] Perform pairing processing on the consultation interaction information and the interaction response decision tree. If it is determined that there is a response result in the interaction response decision tree that matches the consultation interaction information, it is determined that the AI response assistance does not need to be performed;

[0070] Otherwise, it is determined that the AI response assistance needs to be performed.

[0071] Optionally, the response result determination module 303 is specifically used for:

[0072] When the AI response assistance does not need to be performed, generate the target response result according to the response result information corresponding to the consultation interaction information in the interaction response decision tree.

[0073] Optionally, the interaction response decision tree at least includes response branch nodes and response result nodes.

[0074] Optionally, the response result determination module 303 is specifically used for:

[0075] Perform natural language understanding on the complete interaction information to generate interaction semantic information;

[0076] Based on the interaction semantic information, determine the current interaction intention of the information consultation object;

[0077] According to the current interaction intention and the AI response tool, determine the target response result.

[0078] Optionally, the response result determination module 303 is further used for: after determining the target response result, continue to receive the consultation interaction information input by the information consultation object until the conversation ends or a preset termination condition is reached.

[0079] Optionally, the AI response assistance workflow at least includes requesting the LLM, intention recognition, web search, and knowledge base recognition.

[0080] The technical solution of the embodiment of the present invention obtains the consultation interaction information related to auto finance input by the information consultation object. According to the consultation interaction information and the interaction response decision tree pre-configured for the intelligent interaction robot, it is determined whether AI response assistance needs to be executed. In the case where the AI response assistance needs to be executed, according to the complete interaction information and the AI response assistance in the current consultation interaction process, the target response result is determined. The present invention solves the problems of poor user interaction experience, low problem handling efficiency, insufficient decision-making accuracy, high operation cost, and changing market demands in the field of auto finance. By combining the decision tree and the AI workflow, a new solution can be provided for the robot interaction process control in the field of auto finance, enabling the robot to be more intelligent and flexible when processing user input, significantly improving the problem handling efficiency, and reducing the need for human customer service at the same time, thereby reducing the operation cost.

[0081] The intelligent consultation interaction device provided by the embodiment of the present invention can execute the intelligent consultation interaction method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0082] Embodiment 4

[0083] Figure 4 The structural schematic diagram of the electronic device 10 that can be used to implement the embodiment of the present invention is shown. The electronic device 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 processors, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0084] As Figure 4 shown, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. The memory stores a computer program executable by at least one processor. The processor 11 can execute various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0085] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0086] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the intelligent consultation interaction method.

[0087] In some embodiments, the intelligent consultation interaction method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the intelligent consultation interaction method described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the intelligent consultation interaction method by any other suitable means (e.g., by means of firmware).

[0088] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), systems-on-chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a dedicated or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0089] A computer program for implementing the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, a special purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine, or entirely on the remote machine or server.

[0090] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0091] In order to provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device 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 a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the electronic device. Other kinds 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, speech input, or tactile input).

[0092] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0093] A computing system can include a client and a server. The client and the server are generally remote from each other and typically interact via a communication network. The client-server relationship is created by computer programs running on respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system, and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0094] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0095] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent consultation interaction method, characterized in that: Applied to intelligent interactive robots, including: Acquire consultation interaction information related to automobile finance input by the information consultation object; Determine whether AI response assistance is required based on the consultation interaction information and the interaction response decision tree pre-configured for the intelligent interactive robot; When it is necessary to execute the AI ​​response assistance, the target response result is determined based on the complete interaction information and AI response assistance in this consultation interaction process.

2. The method according to claim 1, characterized in that The determining whether to perform AI response assistance according to the consultation interaction information and the interaction response decision tree pre-configured for the intelligent interactive robot includes: Analyzing and identifying the consultation interaction information through the response nodes in the interactive response decision tree; In the case where the answering node identifies the consultation intention of the consultation interaction information, it is determined that the AI ​​answering assistance does not need to be performed; Otherwise, it is determined that the AI ​​response assistance needs to be performed.

3. The method according to claim 1, characterized in that The method further comprises: In the case where it is not necessary to execute the AI ​​response assistance, a target response result is generated based on the response result information corresponding to the consultation interaction information in the interactive response decision tree.

4. The method according to claim 1, characterized in that: In the case where the AI ​​response assistance is required, the target response result is determined based on the complete interaction information and AI response assistance in the consultation interaction process, including: In the case where the AI ​​response assistance needs to be performed, determining whether the current response node in the interactive response decision tree has the AI ​​response assistance turned on; When AI answer assistance is turned on in the current answer node, the target answer result is determined based on the complete interaction information and AI answer assistance during this consultation interaction.

5. The method according to claim 1, characterized in that Determining the target response result based on the complete interaction information and AI response assistance during this consultation interaction process includes: Performing natural language understanding on the complete interactive information to generate interactive semantic information; Based on the interaction semantic information, determining the current interaction intention of the information consultation object; Determine the target response result based on the current interaction intention and AI response tool.

6. The method according to claim 1, characterized in that After determining the target response result, the method further includes: Continue to receive consultation interaction information input by the information consultation object until the session ends or a preset termination condition is reached.

7. The method according to claim 5, characterized in that The AI ​​answer-assisted workflow includes at least requesting LLM, intent recognition, network search, and knowledge base recognition.

8. An intelligent consultation interaction device, characterized in that: Applied to intelligent interactive robots, including: An interactive information acquisition module, used to acquire the consulting interactive information related to automobile finance input by the information consulting object; An interactive response decision module, used to determine whether AI response assistance is required based on the consultation interaction information and an interactive response decision tree pre-configured for the intelligent interactive robot; The response result determination module is used to determine the target response result based on the complete interaction information and AI response assistance in this consultation interaction process when the AI ​​response assistance needs to be executed.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the intelligent consultation interaction method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the intelligent consultation interaction method according to any one of claims 1 to 7 when executed.

Images