Order management method, system and equipment with multi-tool cooperation, medium and program product
By employing a large language model and a multi-tool collaborative order management approach, user intent is identified and multiple order tools are invoked to generate personalized responses. This addresses the issues of insufficient personalized service and contextual understanding in intelligent customer service systems, thereby improving user experience and processing efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-31
- Publication Date
- 2026-04-10
AI Technical Summary
Existing intelligent customer service systems lack personalized service capabilities, have weak contextual understanding capabilities, and cannot collaborate with multiple tools, resulting in a monotonous user experience and insufficient multilingual support.
The system identifies user intent and key parameters using a large language model, calls multiple order tools to process orders, generates personalized responses based on user personality traits, and manages orders using a microservice architecture and context passing mechanism.
It enables personalized order management, improves user experience and processing efficiency, and supports intelligent order operations in multilingual environments.
Smart Images
Figure CN121836737A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of artificial intelligence technology, and in particular to a multi-tool collaborative order management method, system, device, medium, and program product. Background Technology
[0002] Existing intelligent customer service systems mainly adopt dialogue management technology based on simple rules. They process user requests through preset dialogue processes and keyword matching. The core principle is to respond to users' order-related inquiries by combining predefined dialogue templates and business rules with database queries.
[0003] Existing intelligent customer service technologies have the following problems and shortcomings:
[0004] 1. Insufficient personalized service capabilities: Existing technologies cannot provide personalized service styles based on users' personality traits and behavioral habits, resulting in a monotonous user experience.
[0005] 2. Weak contextual understanding and memory: Traditional systems lack contextual understanding capabilities, failing to provide a coherent dialogue experience. Lack of multilingual support: Existing technologies often only support a single language, limiting their application in multilingual digital human environments.
[0006] 3. Lack of intelligent tool collaboration capabilities: Traditional systems can only perform single functions and cannot dynamically select and combine multiple tools to complete complex tasks according to user needs.
[0007] Therefore, there is an urgent need to invent a multi-tool collaborative order management method to solve the problems of existing order management methods having limited functionality, inability to provide personalized services to users, and weak contextual understanding capabilities. Summary of the Invention
[0008] In view of this, embodiments of the present invention provide a multi-tool collaborative order management method, system, device, medium, and program product, which at least partially solves the problems existing in the prior art.
[0009] Other features and advantages of the invention will become apparent from the following detailed description, or may be learned in part by practice of the invention.
[0010] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:
[0011] According to a first aspect of the present invention, a multi-tool collaborative order management method is provided, the method comprising:
[0012] Receive the order request and the user's unique identifier from the user input;
[0013] The user intent and key parameters of the order request are identified and extracted by a large language model to obtain the user request type and key business parameters.
[0014] Based on the user request type, at least two order tools are invoked to process the pending orders corresponding to the order request, and the order processing result is obtained.
[0015] The order processing result will be returned to the user.
[0016] Furthermore, the user request types include order query requests and order operation requests;
[0017] The order tools include geocoding assistance tools, order query tools, hotel details query tools, hotel order placement tools, and extended stay order query tools.
[0018] Further, based on the user request type, at least two order tools are invoked to process the pending orders corresponding to the order request, obtaining the order processing results, including:
[0019] If the order request type is an order query request, then the geocoding auxiliary tool is invoked to convert the city name in the key business parameters into latitude and longitude coordinates;
[0020] The order query tool is used to retrieve the user's order list from the order database based on the user's unique identifier;
[0021] The user order list is filtered using the latitude and longitude coordinates to obtain the order query results.
[0022] Further, based on the user request type, at least two order tools are invoked to process the pending orders corresponding to the order request, obtaining the order processing results, including:
[0023] If the order request type is an order operation request, and the order operation request is an order extension request, then the hotel details query tool is invoked to retrieve the corresponding hotel details from the hotel database based on the hotel identifier in the order information to be extended;
[0024] The hotel booking tool is invoked to create a stay extension order based on the hotel details and the room type identifier in the stay extension order information;
[0025] The extended stay order query tool is invoked to generate an extended stay order link card based on the extended stay order.
[0026] Furthermore, the hotel details query tool is invoked to retrieve the corresponding detailed hotel information from the hotel database based on the hotel identifier in the pending stay order information, including:
[0027] Determine whether the key business parameters contain information on pending stay orders;
[0028] If the key business parameters do not include pending stay order information, the order query tool is invoked to retrieve the user order list from the order database based on the user's unique identifier.
[0029] Based on the order status, identify the pending stay order information from the user order list, and then use the hotel details query tool to retrieve the corresponding hotel details from the hotel database based on the hotel identifier in the pending stay order information.
[0030] If the key business parameters include pending stay order information, the hotel details query tool will be directly invoked to retrieve the corresponding hotel details from the hotel database based on the hotel identifier in the pending stay order information.
[0031] Furthermore, returning the order processing result to the user includes:
[0032] Based on the user's historical dialogue data, the user's personality characteristics are analyzed.
[0033] Based on the personality traits, generate personalized response text for the user;
[0034] The personalized response text and the order processing result are encapsulated into an order response result;
[0035] The order response result will be returned to the user.
[0036] According to a second aspect of the present invention, a multi-tool collaborative order management system is provided, the system comprising:
[0037] The request receiving module is used to receive the order request and the user's unique identifier input by the user;
[0038] The intent recognition module is used to identify user intent and extract key parameters from the order request using a large language model to obtain the user request type and key business parameters.
[0039] The order processing module is used to call at least two order tools to process the pending orders corresponding to the order requests according to the user request type, and obtain the order processing results;
[0040] The result feedback module is used to return the order processing result to the user.
[0041] According to a third aspect of the present invention, a multi-tool collaborative order management device is provided, the device comprising: a processor and a memory;
[0042] The memory is used to store one or more program instructions;
[0043] The processor is configured to run one or more program instructions to perform the steps of a multi-tool collaborative order management method as described in any of the preceding claims.
[0044] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored, wherein when executed by a processor, the computer program implements the steps of a multi-tool collaborative order management method as described in any of the preceding claims.
[0045] According to a fifth aspect of the present invention, a computer program product is provided, the computer program product comprising a computing program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions that, when executed by a computer, cause the computer to implement the steps of a multi-tool collaborative order management method as described in any of the preceding claims.
[0046] This invention provides a multi-tool collaborative order management method, system, device, medium, and program product. The method includes: first, receiving an order request and a unique user identifier input by the user; then, using a large language model to identify the user intent and extract key parameters from the order request to obtain the user request type and key business parameters; next, invoking at least two order tools to process the pending orders corresponding to the order request based on the user request type, and obtaining the order processing result; finally, returning the order processing result to the user. This invention achieves intelligent order management through multi-tool collaboration, providing accurate and personalized order management services for different user requests. Attached Figure Description
[0047] To more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary, and those skilled in the art can derive other embodiments based on the provided drawings without creative effort.
[0048] Figure 1 A flowchart illustrating a multi-tool collaborative order management method provided in an embodiment of the present invention;
[0049] Figure 2 This is a schematic diagram of the structure of a multi-tool collaborative order management system provided in an embodiment of the present invention. Detailed Implementation
[0050] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.
[0051] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.
[0052] Figure 1 A flowchart of a multi-tool collaborative order management method according to an embodiment of the present invention is shown.
[0053] like Figure 1 As shown, the multi-tool collaborative order management method according to an embodiment of the present invention may include steps S100, S200, S300 and S400.
[0054] In step S100, the order request and the user's unique identifier are received from the user.
[0055] Specifically, the above steps include:
[0056] Receive the order request and the user's unique identifier from the user input.
[0057] For example, it can receive user input such as "Check my hotel bookings in Chengdu last month" or "I want to extend my stay for two more nights".
[0058] Next, in step S200, the user intent is identified and key parameters are extracted from the order request using a large language model to obtain the user request type and key business parameters.
[0059] Specifically, the above steps include:
[0060] By using a large language model to identify user intent and extract key parameters from order requests, the user request type and key business parameters can be obtained.
[0061] The above user request types include order query requests and order operation requests.
[0062] For example, a user request to "query my hotel bookings in Chengdu last month" is identified as an order query request, and the key business parameters extracted are "last month" and "Chengdu"; a user request to "I want to extend my stay for two more nights" is identified as an order operation request, and the key business parameter extracted is "2 nights".
[0063] In step S300, at least two order tools are invoked according to the user request type to process the pending orders corresponding to the order requests and obtain the order processing results.
[0064] Specifically, the above steps include:
[0065] For a user request "Query my hotel bookings in Chengdu last month" with an order request type of "order query request", call the geocoding auxiliary tool to convert the city name "Chengdu" in the key business parameters into latitude and longitude coordinates.
[0066] Then, the order query tool is used to retrieve the user's order list from the order database based on the user's unique identifier.
[0067] The user order list is further filtered using latitude and longitude coordinates and time range to obtain the order query results.
[0068] For a user request "I want to extend my stay for two more nights" with the order request type being an order operation request (order extension request), the first step is to determine whether the key business parameters include the order information to be extended, i.e., whether the user provides specific order number information to be extended.
[0069] If the key business parameters do not include pending stay order information, the system will automatically mark the system as needing to execute the pre-process automatic order query. The system will call the order query tool to retrieve the user's historical order list from the order database based on the user's unique identifier. First, it will perform a first round of filtering based on the order status field, retaining only valid orders with the status of "confirmed" and "checked in". Then, it will sort and filter by time dimension based on check-in date and check-out date, automatically identifying pending stay orders that are currently in the check-in status, while filtering out historical orders whose check-out date has expired.
[0070] Then, the hotel details query tool is invoked to retrieve the corresponding detailed hotel information from the hotel database based on the hotel identifier in the pending stay order information, including detailed data such as hotel name, address, star rating, facilities list, price, and contact information.
[0071] If the key business parameters include pending stay order information, the hotel details query tool will be directly invoked to retrieve the corresponding hotel details from the hotel database based on the hotel identifier in the pending stay order information.
[0072] Once the hotel details are available, the hotel booking tool is used to create a stay extension order based on the hotel details and the room type identifier in the pending stay order information.
[0073] Finally, the extended stay order query tool is used to retrieve the complete details of the extended stay order and generate the corresponding mini-program link card.
[0074] Finally, in step S400, the order processing result is returned to the user.
[0075] Specifically, the above steps include:
[0076] First, based on the user's historical conversation data, the user's personality traits are analyzed;
[0077] Based on user personality traits, personalized response text is generated for each user. For example, for highly extroverted users, a lighthearted and lively response is generated, incorporating emojis and emphasizing special offers to create a pleasant atmosphere; for highly neurotic users, a rigorous and standardized response is generated, using a structured list to display key information such as order number, date, and price to reduce uncertainty; for highly open-minded users, personalized recommendations, such as hotel activities and exclusive offers, are added to the response to provide value-added services.
[0078] For order query requests, the order query results are converted into a standard format, key fields (such as hotel name, address, room type, check-in date, check-out date, number of nights, order status, price, etc.) are extracted, a query result list is formed, and the query result list and personalized response text are packaged into an order response result and returned to the user for display.
[0079] For order operation requests, the personalized response text and the mini-program link card corresponding to the renewal order are encapsulated into an order response result and returned to the user for display.
[0080] In addition, embodiments of the present invention also provide a multi-tool collaborative order management system. Figure 2 This diagram illustrates the structure of a multi-tool collaborative order management system according to an embodiment of the present invention. The system includes:
[0081] The request receiving module is used to receive the order request and the user's unique identifier input by the user;
[0082] The intent recognition module is used to identify user intent and extract key parameters from order requests using a large language model, thereby obtaining the user request type and key business parameters.
[0083] The order processing module is used to call at least two order tools to process the pending orders corresponding to the user request based on the user request type, and obtain the order processing result.
[0084] The results feedback module is used to return the order processing results to the user.
[0085] The multi-tool collaborative order management system provided in this embodiment of the invention adopts a microservice architecture, and the modules communicate with each other through standard API interfaces.
[0086] In addition, embodiments of the present invention also provide a multi-tool collaborative order management device, the device comprising: a processor and a memory; the memory for storing one or more program instructions; the processor for running one or more program instructions to execute the steps of a multi-tool collaborative order management method as described above.
[0087] In addition, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of a multi-tool collaborative order management method as described above.
[0088] In addition, embodiments of the present invention also provide a computer program product, which includes computer program instructions that, when executed by a processor, implement the steps of a multi-tool collaborative order management method as described above.
[0089] The multi-tool collaborative order management method, system, device, medium, and program product provided in this invention have the following advantages compared to the prior art:
[0090] This invention provides a unified automatic return value encapsulation mechanism. The order return component offers four return methods: return with order card on success, return with order card on failure, quick success return, and quick failure return. All methods automatically extract standard fields from the complex data structure of the hotel order system, eliminating the need for developers to manually concatenate data and ensuring consistent field extraction logic and data consistency.
[0091] The tool invocation in this embodiment of the invention adopts a context passing mechanism. The system passes the request context object through the configuration parameters of the graph reasoning framework and uses a dependency injection container to manage service instances. This ensures the consistency and security of user identity, session information, and access control throughout the entire process.
[0092] This invention also provides a dynamic mini-program card generation mechanism. The order card component automatically generates different types of mini-program cards based on order data and business scenarios. It supports various business scenarios such as order details, payment, stay extension, stay change, and invoice issuance. Different scenarios are distinguished by business identifier parameters, supporting A / B testing and personalized display.
[0093] When a user request lacks necessary parameters, this embodiment of the invention automatically invokes a query tool to retrieve a list of orders for the user to choose from. Based on the order status and operation type, the system intelligently determines whether the operation is supported, avoiding invalid calls. It supports both serial and parallel tool calls, optimizing response time.
[0094] In summary, this invention, through a multi-tool collaboration mechanism, can automatically complete complex order operation processes, improving processing efficiency and significantly enhancing the intelligence level of order management. Furthermore, this invention, based on user personality traits and service style adaptation, provides personalized greetings and interactive experiences tailored to each user, effectively improving user satisfaction.
[0095] In this embodiment of the invention, the processor can be an integrated circuit chip with signal processing capabilities. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in this embodiment of the invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in this embodiment of the invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The processor reads information from the storage medium and, in conjunction with its hardware, completes the steps of the above methods. The storage medium can be memory, for example, volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM).The storage media described in the embodiments of this invention are intended to include, but are not limited to, these and any other suitable types of memory. Those skilled in the art will recognize that the functions described in the above examples can be implemented using a combination of hardware and software. When applied software, the corresponding functions can be stored in a computer-readable medium or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of computer programs from one place to another. Storage media can be any available medium accessible to general-purpose or special-purpose computers. Although the invention has been described in detail above with general description and specific embodiments, modifications or improvements can be made to it, which will be apparent to those skilled in the art. Therefore, such modifications or improvements made without departing from the spirit of the invention are all within the scope of protection claimed by the invention.
[0096] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, or alterations made by those skilled in the art using the disclosed technical content shall fall within the protection scope of the present invention.
Claims
1. A multi-tool collaborative order management method, characterized in that, The method includes: Receive the order request and the user's unique identifier from the user input; The user intent and key parameters of the order request are identified and extracted by a large language model to obtain the user request type and key business parameters. Based on the user request type, at least two order tools are invoked to process the pending orders corresponding to the order request, and the order processing result is obtained. The order processing result will be returned to the user.
2. The multi-tool collaborative order management method according to claim 1, characterized in that, The user request types include order query requests and order operation requests; The order tools include geocoding assistance tools, order query tools, hotel details query tools, hotel order placement tools, and extended stay order query tools.
3. The multi-tool collaborative order management method according to claim 2, characterized in that, Based on the user request type, at least two order tools are invoked to process the pending orders corresponding to the order request, and the order processing results are obtained, including: If the order request type is an order query request, then the geocoding auxiliary tool is invoked to convert the city name in the key business parameters into latitude and longitude coordinates; The order query tool is used to retrieve the user's order list from the order database based on the user's unique identifier; The user order list is filtered using the latitude and longitude coordinates to obtain the order query results.
4. The multi-tool collaborative order management method according to claim 2, characterized in that, Based on the user request type, at least two order tools are invoked to process the pending orders corresponding to the order request, and the order processing results are obtained, including: If the order request type is an order operation request, and the order operation request is an order extension request, then the hotel details query tool is invoked to retrieve the corresponding hotel details from the hotel database based on the hotel identifier in the order information to be extended; The hotel booking tool is invoked to create a stay extension order based on the hotel details and the room type identifier in the stay extension order information; The extended stay order query tool is invoked to generate an extended stay order link card based on the extended stay order.
5. The multi-tool collaborative order management method according to claim 4, characterized in that, The hotel details query tool is invoked to retrieve the corresponding hotel details from the hotel database based on the hotel identifier in the pending stay order information, including: Determine whether the key business parameters contain information on pending stay orders; If the key business parameters do not include pending stay order information, the order query tool is invoked to retrieve the user order list from the order database based on the user's unique identifier. Based on the order status, identify the pending stay order information from the user order list, and then use the hotel details query tool to retrieve the corresponding hotel details from the hotel database based on the hotel identifier in the pending stay order information. If the key business parameters include pending stay order information, the hotel details query tool will be directly invoked to retrieve the corresponding hotel details from the hotel database based on the hotel identifier in the pending stay order information.
6. The multi-tool collaborative order management method according to claim 1, characterized in that, Returning the order processing result to the user includes: Based on the user's historical dialogue data, the user's personality characteristics are analyzed. Based on the personality traits, generate personalized response text for the user; The personalized response text and the order processing result are encapsulated into an order response result; The order response result will be returned to the user.
7. A multi-tool collaborative order management system, characterized in that, The system includes: The request receiving module is used to receive the order request and the user's unique identifier input by the user; The intent recognition module is used to identify user intent and extract key parameters from the order request using a large language model to obtain the user request type and key business parameters. The order processing module is used to call at least two order tools to process the pending orders corresponding to the order requests according to the user request type, and obtain the order processing results; The result feedback module is used to return the order processing result to the user.
8. A multi-tool collaborative order management device, characterized in that, The device includes: a processor and a memory; The memory is used to store one or more program instructions; The processor is configured to run one or more program instructions to perform the steps of a multi-tool collaborative order management method as described in any one of claims 1 to 6.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of a multi-tool collaborative order management method as described in any one of claims 1 to 6.
10. A computer program product, characterized in that, The computer program product includes computer program instructions that, when executed by a processor, implement the steps of a multi-tool collaborative order management method as described in any one of claims 1 to 6.