Operation and maintenance reply information generation method and device, equipment, medium and program product
By combining intelligent question-answering components and multilingual models, the problem of accurately responding to system operation and maintenance issues has been solved, improving the efficiency and accuracy of operation and maintenance processing.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- BEIJING JINGDONG YUANSHENG TECH CO LTD
- Filing Date
- 2025-01-08
- Publication Date
- 2026-07-10
AI Technical Summary
In existing technologies, the efficiency of system maintenance is low due to manual shifts, and simple self-service robots have poor understanding capabilities and cannot accurately answer system maintenance questions.
An intelligent question-answering component is adopted, which is based on components encapsulated from multiple language models. It determines the question type of operation and maintenance inquiry information and uses the corresponding language model to generate accurate operation and maintenance response information.
It enables convenient and accurate responses to maintenance inquiries, improving the efficiency and accuracy of handling system maintenance issues.
Smart Images
Figure CN122364358A_ABST
Abstract
Description
Technical Field
[0001] The embodiments disclosed herein relate to the field of computer technology, and specifically to methods, apparatus, devices, media, and program products for generating operation and maintenance response information. Background Technology
[0002] Currently, the smooth operation of system maintenance within the logistics industry is crucial, largely determining the normal functioning of logistics. Common methods for handling system maintenance issues include: resolving problems through rotating shifts of personnel, or using simple self-service chatbots for responses.
[0003] However, the inventors discovered that when using the above method to solve operation and maintenance problems, the following technical issues often arise:
[0004] The efficiency of manual shifts is low, and the simple self-service robots have very weak adaptability and understanding of the scenarios, resulting in poor comprehension and inability to accurately respond to system maintenance issues.
[0005] The information disclosed in this background section is only intended to enhance the understanding of the background of the inventive concept, and therefore may contain information that does not constitute prior art known to those skilled in the art. Summary of the Invention
[0006] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.
[0007] Some embodiments of this disclosure provide methods, apparatus, electronic devices, computer-readable media, and program products for generating operation and maintenance response information to address the technical problems mentioned in the background section above.
[0008] In a first aspect, some embodiments of this disclosure provide a method for generating operation and maintenance response information, including: obtaining operation and maintenance inquiry information input by a target user; using an intelligent question-and-answer component to determine the inquiry type corresponding to the operation and maintenance inquiry information, wherein the intelligent question-and-answer component is a component encapsulated based on multiple language models and used to process questions corresponding to various inquiry types; generating operation and maintenance response information corresponding to the operation and maintenance inquiry information based on at least one language model corresponding to the inquiry type, wherein the at least one language model is a model among the multiple language models; and sending the operation and maintenance response information to a corresponding display terminal so that the target user can obtain the response content corresponding to the operation and maintenance inquiry information.
[0009] Optionally, the above-mentioned query type is a data query type; and the above-mentioned generation of operation and maintenance response information corresponding to the above-mentioned operation and maintenance query information based on at least one language model corresponding to the above-mentioned query type includes: determining the query data table corresponding to the above-mentioned operation and maintenance query information according to at least one language model corresponding to the above-mentioned data query type; generating the query statement corresponding to the above-mentioned operation and maintenance query information according to the table structure corresponding to the above-mentioned query data table; and executing the above-mentioned query statement to generate the above-mentioned operation and maintenance response information.
[0010] Optionally, the above-mentioned inquiry type is a customized scenario question-and-answer type; and the above-mentioned generation of operation and maintenance response information corresponding to the above-mentioned operation and maintenance inquiry information based on at least one language model corresponding to the above-mentioned inquiry type includes: retrieving response service information corresponding to the above-mentioned customized scenario question-and-answer type, wherein the service corresponding to the above-mentioned response service information is encapsulated based on the above-mentioned at least one language model; and generating operation and maintenance response information corresponding to the above-mentioned operation and maintenance inquiry information based on the above-mentioned response service information.
[0011] Optionally, the above-mentioned query type is other query types; and the above-mentioned generation of operation and maintenance response information corresponding to the above-mentioned operation and maintenance query information based on at least one language model corresponding to the above-mentioned query type includes: calling the multi-type question and answer intelligent platform corresponding to the above-mentioned other query types, wherein the above-mentioned multi-type question and answer intelligent platform is built based on the above-mentioned at least one language model; inputting the above-mentioned operation and maintenance query information into the above-mentioned multi-type question and answer intelligent platform to generate the above-mentioned response knowledge as the above-mentioned operation and maintenance response information.
[0012] Optionally, executing the query statement to generate the operation and maintenance response information includes: executing the query statement based on data overload technology, data compliance technology, and data security technology to generate the operation and maintenance response information.
[0013] Optionally, the intelligent question-answering component mentioned above supports the following functions for the corresponding intelligent objects: multi-backend interaction function, data sharding and storage function, rapid system expansion function, customized scenario expansion and access function, and data processing function.
[0014] Optionally, the aforementioned multi-type question-answering intelligent platform supports various operations on the knowledge base, including: custom addition, memory, and search operations.
[0015] Secondly, some embodiments of this disclosure provide an operation and maintenance response information generation device, including: an acquisition unit configured to acquire operation and maintenance inquiry information input by a target user; a determination unit configured to determine the inquiry type corresponding to the operation and maintenance inquiry information using an intelligent question-and-answer component, wherein the intelligent question-and-answer component is a component encapsulated based on multiple language models for processing questions corresponding to various inquiry types; a generation unit configured to generate operation and maintenance response information corresponding to the operation and maintenance inquiry information based on at least one language model corresponding to the inquiry type, wherein the at least one language model is a model among the multiple language models; and a sending unit configured to send the operation and maintenance response information to a corresponding display terminal so that the target user can obtain the response content corresponding to the operation and maintenance inquiry information.
[0016] Optionally, the above-mentioned inquiry type is a data query type; and the generation unit can be configured to determine the query data table corresponding to the above-mentioned operation and maintenance inquiry information based on at least one language model corresponding to the above-mentioned data query type; generate a query statement corresponding to the above-mentioned operation and maintenance inquiry information based on the table structure corresponding to the above-mentioned query data table; and execute the above-mentioned query statement to generate the above-mentioned operation and maintenance response information.
[0017] Optionally, the above-mentioned inquiry type is a customized scenario question-and-answer type; and the generation unit can be configured to retrieve the response service information corresponding to the above-mentioned customized scenario question-and-answer type, wherein the service corresponding to the above-mentioned response service information is encapsulated based on at least one of the above-mentioned language models; and generate the operation and maintenance response information corresponding to the above-mentioned operation and maintenance inquiry information based on the above-mentioned response service information.
[0018] Optionally, the above-mentioned query type is another query type; and the generation unit can be configured to call the multi-type question-and-answer intelligent platform corresponding to the other query types, wherein the multi-type question-and-answer intelligent platform is built based on at least one of the above-mentioned language models; input the above-mentioned maintenance query information into the above-mentioned multi-type question-and-answer intelligent platform to generate the above-mentioned answer knowledge as the above-mentioned maintenance answer information.
[0019] Optionally, the generation unit can be configured to execute the above query statement based on data overload technology, data compliance technology, and data security technology to generate the above operation and maintenance response information.
[0020] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, such that when the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any implementation of the first aspect.
[0021] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method as described in any implementation of the first aspect.
[0022] Fifthly, some embodiments of this disclosure provide a computer program product, including a computer program that, when executed by a processor, implements the method described in any of the implementations of the first aspect above.
[0023] The above embodiments of this disclosure have the following beneficial effects: By utilizing the operation and maintenance response information generation method of some embodiments of this disclosure, and employing an intelligent question-and-answer component, operation and maintenance response information corresponding to operation and maintenance inquiry information can be generated accurately and efficiently. Specifically, the reason why the segmentation results of the relevant segmentation model are not accurate enough is that the processing efficiency of manual shifts is low, and the simple self-service robot has very weak adaptability and understanding of the corresponding scenarios, resulting in poor understanding ability and inability to accurately respond to system operation and maintenance issues. Based on this, the operation and maintenance response information generation method of some embodiments of this disclosure first obtains the operation and maintenance inquiry information input by the target user to obtain the operation and maintenance issues to be responded to. Then, using an intelligent question-and-answer component, the inquiry type corresponding to the above operation and maintenance inquiry information is determined. The intelligent question-and-answer component is a component based on multiple language models, used to handle questions corresponding to various inquiry types. Here, using the intelligent question-and-answer component, the response to the operation and maintenance inquiry information can be achieved conveniently and accurately by determining the inquiry type corresponding to the operation and maintenance inquiry information. Here, the intelligent question-and-answer component is based on multiple language models, and by leveraging the model advantages of each language model, inquiry responses in various scenarios can be achieved. In addition, by determining the query type, at least one language model matching the characteristics of that query type is selected. Therefore, the advantages of each language model can be combined to accurately output the response to the maintenance query. Furthermore, based on the at least one language model corresponding to the aforementioned query type, the maintenance response can be accurately generated. Here, the at least one language model is one of several language models. Finally, the maintenance response is sent to the corresponding display terminal so that the target user can access the response to the maintenance query. In summary, the intelligent question-answering component allows for the accurate and rapid generation of maintenance response information by selecting at least one corresponding language model when the query type of the maintenance query is determined. Attached Figure Description
[0024] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.
[0025] Figure 1 This is a schematic diagram illustrating an application scenario of the operation and maintenance response information generation method according to some embodiments of this disclosure;
[0026] Figure 2 This is a flowchart of some embodiments of the operation and maintenance response information generation method according to this disclosure;
[0027] Figure 3 This is a flowchart of some other embodiments of the method for generating operation and maintenance response information according to this disclosure;
[0028] Figure 4 This is a schematic diagram of the structure of some embodiments of the maintenance response information generation device according to this disclosure;
[0029] Figure 5 This is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation
[0030] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.
[0031] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.
[0032] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.
[0033] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".
[0034] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
[0035] Before performing any of the operations involving the collection, storage, or use of user personal information (such as maintenance inquiry information) disclosed in this disclosure, the relevant organizations or individuals shall fulfill their obligations, including conducting personal information security impact assessments, informing personal information subjects, and obtaining prior authorization and consent from personal information subjects.
[0036] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.
[0037] Figure 1 This is a schematic diagram illustrating an application scenario of the operation and maintenance response information generation method according to some embodiments of this disclosure.
[0038] exist Figure 1 In this application scenario, firstly, the electronic device 101 can obtain the maintenance inquiry information 102 input by the target user. In this application scenario, the maintenance inquiry information 102 could be "What is the IDMS system? Is there a brief introduction?". Then, the electronic device 101 can use the intelligent question-and-answer component 103 to determine the inquiry type 105 corresponding to the aforementioned maintenance inquiry information 102. The intelligent question-and-answer component 103 is a component based on multiple language models 104, used to handle questions corresponding to various inquiry types. In this application scenario, inquiry type 105 could be inquiry type A. The multiple language models 104 can include: language model A, language model B, language model C, and language model D. Next, the electronic device 101 can generate maintenance response information 106 corresponding to the aforementioned maintenance inquiry information 102 based on at least one language model corresponding to the aforementioned inquiry type 105. The at least one language model is a model among the multiple language models 104. In this application scenario, at least one language model can include: language model D. The maintenance response information 106 could be: "The IDMS system is a multi-functional system, and its specific applications and functions vary depending on the field. In the field of chemistry, IDMS refers to Isotope Dilution Mass Spectrometry, a technique used to accurately measure the isotope ratios in substances." Finally, the electronic device 101 can send the aforementioned maintenance response information 106 to the corresponding display terminal so that the target user can obtain the response content corresponding to the aforementioned maintenance inquiry information 102.
[0039] It should be noted that the aforementioned electronic device 101 can be either hardware or software. When the electronic device is hardware, it can be implemented as a distributed cluster consisting of multiple servers or terminal devices, or as a single server or a single terminal device. When the electronic device is software, it can be installed in the hardware devices listed above. It can be implemented as, for example, multiple software programs or software modules used to provide distributed services, or as a single software program or software module. No specific limitations are made here.
[0040] It should be understood that Figure 1 The number of electronic devices shown is merely illustrative. Any number of electronic devices can be used depending on the implementation requirements.
[0041] Continue to refer to Figure 2 The flowchart 200 illustrates some embodiments of the operation and maintenance response information generation method according to this disclosure. The operation and maintenance response information generation method includes the following steps:
[0042] Step 201: Obtain the maintenance inquiry information input by the target user.
[0043] In some embodiments, the execution subject of the above-described operation and maintenance response information generation method (e.g.) Figure 1 The electronic device 101 shown can acquire maintenance inquiry information input by a target user via a wired or wireless connection. The target user can be the user who is asking the inquiry. The maintenance inquiry information can be a question awaiting a response.
[0044] Step 202: Use the intelligent question-answering component to determine the question type corresponding to the above maintenance inquiry information.
[0045] In some embodiments, the aforementioned execution entity can utilize an intelligent question-answering component to determine the question type corresponding to the aforementioned maintenance inquiry information. The question type can be the question type corresponding to the maintenance inquiry information. In practice, the question type can be pre-set. For example, the question type can be a domain-based classification. For example, the question type can be, but is not limited to, one of the following: artificial intelligence question type, general knowledge question type, and construction question type. The aforementioned intelligent question-answering component is a component encapsulated based on multiple language models, used to process questions corresponding to various question types. The language model can be a pre-encapsulated large language model. The model structure and execution principle of each language model in the multiple language models can be different. For example, the multiple language models can include: the GPT4 language model, a first language model developed by the first R&D unit, and a second language model developed by the second R&D unit. Specifically, each language model can support various processing methods in the natural language domain. Furthermore, the advantages and disadvantages of each language model are also different. For example, the language models include: the GPT4 language model, the first language model, and the second language model. The advantage of the GPT4 language model is its high recognition accuracy, while also supporting image-based information input. The advantages of the first language model are relatively stable SQL generation capabilities and long memory. The disadvantage is instability with image-based input. The advantage of the second language model is its exceptionally strong language recognition capabilities. Intelligent question-answering components can be encapsulated from multiple large language models.
[0046] It should be noted that the intelligent question-answering component provides an open standard interface, allowing access to various types of input terminals. The component offers diverse entry points, supporting chatbots and PC-based floating components. In practice, the intelligent question-answering component can be developed specifically for international logistics scenarios to address challenges such as poor operational capabilities, high costs, slow response times, time zone differences, and multilingual issues in the international logistics field. Through this component, user needs can be accurately identified, system maintenance problems can be resolved, and operational costs can be reduced.
[0047] As an example, the aforementioned execution entity can use the GPT4 language model corresponding to the intelligent question-answering component to determine the question type corresponding to the aforementioned operation and maintenance inquiry information.
[0048] Step 203: Based on at least one language model corresponding to the above query type, generate operation and maintenance response information corresponding to the above operation and maintenance query information.
[0049] In some embodiments, the execution entity can generate maintenance response information corresponding to the maintenance inquiry information based on at least one language model corresponding to the inquiry type. The at least one language model is one of multiple language models. Each inquiry type has at least one usable language model. The relationship between the inquiry type and the language model is determined based on the advantages and disadvantages of the language models. Based on the characteristics of the inquiry type, at least one language model whose advantages correspond to the type characteristics is selected from various language models, so that the response content for each maintenance inquiry under the inquiry type can be accurately generated using at least one model. For example, if the inquiry type is an artificial intelligence question, the corresponding at least one language model may include: a first language model, a second language model, and a third language model. If the inquiry type is a general knowledge question, the corresponding at least one language model may include: a second language model and a fourth language model. If the inquiry type is a construction question, the corresponding at least one language model may include: a third language model and a fifth language model. The maintenance response information can be the response content to the maintenance inquiry information.
[0050] As an example, the aforementioned execution entity can input maintenance inquiry information into at least one of the aforementioned language models to generate maintenance response information.
[0051] In some optional implementations of certain embodiments, the above-mentioned query type is a data query type. Here, the data query type can represent that the query content is data query content. That is, the offline operation and maintenance query information of the data query type is information used to query data.
[0052] Optionally, generating the operation and maintenance response information corresponding to the operation and maintenance inquiry information based on at least one language model corresponding to the above inquiry type may include the following steps:
[0053] The first step is to determine the query data table corresponding to the aforementioned maintenance query information based on at least one language model corresponding to the data query type. The at least one language model can be a language model suitable for data query functions. That is, the language model in at least one language model has significant advantages in data querying. The query data table can be a data table whose content is related to the data to be queried. For example, the query data table includes: the data to be queried corresponding to the maintenance query information.
[0054] As an example, the aforementioned execution entity can generate a prompt message for the operation and maintenance inquiry. Then, the prompt message and the operation and maintenance inquiry are input into a target language model within at least one language model to generate an inquiry data table. The advantage of the target language model lies in its ability to query the data table. For example, the target language model could be a GPT4.0 model.
[0055] For example, the prompt message could be:
[0056] "Character Profile: You are a professional MySQL database DBA."
[0057] Objective: Find the table names required for the task from the provided database table name information. If multiple tables are needed, separate them with commas. If no matching database table is found, output an empty string "". Do not output random information or make assumptions.
[0058] Background: I have the following database table information: instock_detail: Inbound order details table, which is a related table of inbound orders, recording products, product quantities, etc.; instock: Inbound order table, the main table of inbound orders, recording order number, creation time, etc.; outstock_goods: Outbound order details table.
[0059] Waybill: Waybill form;
[0060] outstock: Outbound order table, the main table for outbound orders, records the order number, creation time, etc. of outbound orders;
[0061] stock_warehouse: Warehouse inventory table, which records the inventory status of goods in the warehouse, such as: how many are in stock, how many are reserved, and how many are locked.
[0062] stock_warehouse_flow: Inventory flow table, which records the flow of inventory;
[0063] warehouses: Warehouse information table, which records information about the warehouses, such as what type of warehouse it is, its address, time zone, and the country where it is located;
[0064] Task: I need to export the transaction history of product FG0005301743 for the most recent day and summarize the quantities according to different business types;
[0065] Note: Only the English table names are required. No explanation or description is needed in the returned information. If multiple tables are required, separate them with commas. Strictly follow the requirements for the returned results. Example: table1, table2.
[0066] The outputs of the target language model are: Table A, Table B, and Table C.
[0067] The second step is to generate the query statement corresponding to the above maintenance query information based on the table structure corresponding to the query data table. The table structure can be the data structure corresponding to the query data table. The query statement can be a database statement in various forms. For example, the query statement can be an SQL statement.
[0068] As an example, firstly, the execution entity can select a target language model related to the query type from at least one language model as the query language model. Then, it generates query statement hints. Finally, it inputs the table structure information and the hints into the query statement model to generate the query statement.
[0069] For example, the data structure of the relevant tables can be obtained from the data configuration; after extensive testing and training, GML4.0 has a stronger ability to generate SQL, so we ask AI (GML4.0) a question and return the corresponding SQL to be executed.
[0070] Character description: You are a professional MySQL database DBA.
[0071] Objective: Generate executable SQL statements based on the task requirements. Consider the efficiency and performance of SQL execution, and carefully verify data validity (yn = 1 indicates valid data, yn = 0 indicates invalid data). If no SQL statement meets the task requirements, output an empty string "". Do not output random results or make assumptions.
[0072] Background: The SQL for creating the database tables involved is as follows: ["\r\nCREATE TABLE`stock_warehouse_flow`(\r\n`id`bigint(20)NOT NULL AUTO_INCREMENT COMMENT'Primary Key',\r\n`customer_code`varchar(50)DEFAULT”COMMENT'Owner Code',\r\n`cargo_owner_id`bigint(20)DEFAULT NULL COMMENT'Owner ID',\r\n`warehouse_code`varchar(50)DEFAULT NULLCOMMENT'Warehouse Code',\r\n`supplier_warehouse_code`varchar(50)DEFAULT NULLCOMMENT'Supplier Warehouse Code',\r\n`supplier_code`varchar(50)DEFAULT NULL COMMENT'Supplier Warehouse Service Provider Code',\r\n`goods_code`varchar(30)DEFAULT NULL COMMENT'FOP Product Code',\r\n`sku`varchar(200)DEFAULT NULL COMMENT'Customer SKU Code',\r\n`source_business_no`varchar(100)DEFAULT NULL COMMENT'Customer System Document Code',\r\n`business_no`varchar(50)DEFAULT NULL COMMENT'FOP System Business Document Code',\r\n`business_type`int(4)DEFAULT NULL COMMENT'Document Type',\r\n`flow_no`varchar(50)DEFAULT”COMMENT'Transaction Number',\r\n`source_flow_no`varchar(200)DEFAULT”COMMENT'Customer Transaction Number',\r\n`flow_stock_num`int(11)DEFAULT NULL COMMENT 'Current change in available inventory, positive indicates increase, negative indicates decrease',\r\n`flow_preempt_num`int(11)DEFAULT NULL COMMENT 'Current change in preempted inventory, positive indicates increase, negative indicates decrease',\r\n`stock_num`int(11)DEFAULT NULL COMMENT 'Current change in available inventory',`preempt_num`int(11)DEFAULT NULL COMMENT'Pre-empted inventory quantity after change',`source_stock_num`int(11)DEFAULT NULL COMMENT'Sellable inventory quantity before change',`source_preempt_num`int(11)DEFAULT NULL COMMENT'Pre-empted inventory quantity before change',`source_level`smallint(6)DEFAULT NULL COMMENT'Original inventory level',`result_level`smallint(6)DEFAULT NULL COMMENT'New inventory level',`tenant_code`varchar(50)DEFAULT”COMMENT'Tenant code',`create_user`varchar(50)DEFAULT NULL COMMENT'Creator',`create_time`datetime DEFAULT NULL` COMMENT'Creation Time',\r\n`update_user`varchar(50)DEFAULT NULL COMMENT'Updater',\r\n`update_time`datetimeDEFAULT NULL COMMENT'Update Time',\r\n`version`int(11)DEFAULT NULL COMMENT'Version Number',\r\n`yn`tinyint(4)DEFAULT NULL COMMENT'Delete Identifier: 1-Valid, 0-Invalid',\r\n`ts`timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMPCOMMENT 'Timestamp',\r\n`source_reserved_hold_num`int(11)DEFAULT '0'COMMENT 'Number of abnormal frozen inventory changes before the change, positive numbers indicate increase, negative numbers indicate decrease',\r\n`source_reserved_vas_num`int(11)DEFAULT '0'COMMENT 'Number of VAS occupied inventory changes before the change, positive numbers indicate increase, negative numbers indicate decrease',\r\n`flow_reserved_hold_num`int(11)DEFAULT '0'COMMENT 'Number of current abnormal frozen inventory changes, positive numbers indicate increase, negative numbers indicate decrease',`flow_reserved_vas_num`int(11)DEFAULT'0'COMMENT'Current VAS inventory change, positive for increase, negative for decrease',`reserved_hold_num`int(11)DEFAULT'0'COMMENT'Change in abnormal frozen inventory after change, positive for increase, negative for decrease',`reserved_vas_num`int(11)DEFAULT'0'COMMENT'Change in VAS inventory after change, positive for increase, negative for decrease',`flow_freeze_num`int(11)DEFAULT'0'COMMENT'Current frozen inventory change, positive for increase, negative for decrease',`freeze_num`int(11)DEFAULT'0'COMMENT'Frozen quantity after change',`PRIMARY KEY(`id`)USING BTREE,```````````````````````````````````"111111111———11251"1121121121"112"1121 ..."21"22221"11212"112"1"222221"1121"21"222221"11"21221"11"2222"2222"1"2222"2222"11"222"2222"11"222"2222"11"222"222"2222""2222"2222"222"222"222"222"22 UNIQUE KEY`uniq_flow_no`(`flow_no`)USING BTREE,\r\n UNIQUEKEY`uniq_source_flow_no`(`source_flow_no`)USING BTREE,\r\n KEY`idx_goodscode_time`(`goods_code`,`create_time`),\r\n KEY`idx_business_no`(`business_no`),\r\n KEY`idx_create_time`(`create_time`),\r\n KEY`idx_customer_code`(`customer_code`),\r\nKEY`idx_sku`(`sku`),\r\n KEY`idx_customer_yn_create_time`(`customer_code`,`yn`,`create_time`)\r\n)ENGINE=InnoDB AUTO_INCREMENT=74107654DEFAULT CHARSET = utf8ROW_FORMAT = DYNAMIC COMMENT = 'Warehouse Physical Inventory Flow Information - No Batch Inventory Information'\r\n"],
[0073] Task: I need to export the transaction history of product FG0005301743 for the most recent day and summarize the quantities according to different business types. If the result set fields contain enumeration values, please add a field and use a CASE statement to convert them into specific values.
[0074] Note: The returned results only need to be the SQL text; no explanations or descriptions are required, and pagination is not necessary. Strictly adhere to the requirements. Example of a returned result: SELECT * FROM TABLE limit 1;
[0075] The language model returns the following results:
[0076] SELECT business_type,CASE WHEN business_type=1THEN'Specific value 1'WHENbusiness_type=2THEN'Specific value 2'ELSE'Other'END AS business_type_name,SUM(flow_stock_num)AS total_flow_stock_num,SUM(flow_preempt_num)AS total_flow_preempt_num FROM stock_warehouse_flow WHERE goods_code='FG0005301743'AND yn=1ANDcreate_time BETWEEN DATE_SUB(CURDATE(),INTERVAL 1DAY)AND CURDATE()GROUP BYbusiness_type;
[0077] The third step is to execute the above query statement to generate the above operation and maintenance response information.
[0078] In some optional implementations of certain embodiments, the above-mentioned query type is a customized scenario question-and-answer type. The customized scenario question-and-answer type can be a question-and-answer type specific to a customized scenario. The customized scenario can be a custom extended scenario. At least one language model corresponding to the customized scenario question-and-answer type supports various operations and inferences on the data to generate response information for the customized scenario. For example, the customized scenario could be an order cost summary scenario.
[0079] Optionally, generating the operation and maintenance response information corresponding to the operation and maintenance inquiry information based on at least one language model corresponding to the above inquiry type may include the following steps:
[0080] The first step is to retrieve the response service information corresponding to the customized question-and-answer types mentioned above. The service corresponding to this response service information is encapsulated based on at least one of the aforementioned language models. The response service information can be a service identifier corresponding to the response service. The response service can be a service that provides answers to questions specific to the customized scenario.
[0081] The second step is to generate maintenance response information corresponding to the maintenance inquiry information based on the above response service information.
[0082] As an example, the aforementioned implementing entity can utilize the response service information to generate operation and maintenance response information corresponding to the operation and maintenance inquiry information.
[0083] Optionally, the aforementioned executing entity can execute the above query statement based on data overload technology, data compliance technology, and data security technology to generate the above operation and maintenance response information. Here, data overload technology can be a technology used to resolve data overload. Data compliance technology can be a technology to ensure data compliance. Data security technology can be a technology to ensure data security. That is, during the execution of the query statement, it is necessary to ensure the data compliance and security of the queried dataset and avoid data overload.
[0084] Optionally, the intelligent object corresponding to the aforementioned intelligent question-answering component supports the following functions: multi-backend interaction, data sharding and storage, rapid system expansion, customized scenario expansion and access, and data processing. The intelligent object corresponding to the intelligent question-answering component can be an intelligent robot equipped with the intelligent question-answering component. The intelligent object supports simultaneous interaction with multiple backends, supports sharded storage of datasets, supports rapid system expansion (simply configure the system and related database table information to achieve integration), supports customized scenario expansion and access (implementing the corresponding processing classes to achieve integration), and also supports various data processing operations.
[0085] Step 204: Send the above maintenance response information to the corresponding display terminal so that the target user can obtain the response content corresponding to the above maintenance inquiry information.
[0086] In some embodiments, the aforementioned execution entity may send the aforementioned maintenance response information to a corresponding display terminal, so that the aforementioned target user can obtain the response content corresponding to the aforementioned maintenance inquiry information. The display terminal may be a terminal used to display the maintenance response information.
[0087] The above embodiments of this disclosure have the following beneficial effects: By utilizing the operation and maintenance response information generation method of some embodiments of this disclosure, and employing an intelligent question-and-answer component, operation and maintenance response information corresponding to operation and maintenance inquiry information can be generated accurately and efficiently. Specifically, the reason why the segmentation results of the relevant segmentation model are not accurate enough is that the processing efficiency of manual shifts is low, and the simple self-service robot has very weak adaptability and understanding of the corresponding scenarios, resulting in poor understanding ability and inability to accurately respond to system operation and maintenance issues. Based on this, the operation and maintenance response information generation method of some embodiments of this disclosure first obtains the operation and maintenance inquiry information input by the target user to obtain the operation and maintenance issues to be responded to. Then, using an intelligent question-and-answer component, the inquiry type corresponding to the above operation and maintenance inquiry information is determined. The intelligent question-and-answer component is a component based on multiple language models, used to handle questions corresponding to various inquiry types. Here, using the intelligent question-and-answer component, the response to the operation and maintenance inquiry information can be achieved conveniently and accurately by determining the inquiry type corresponding to the operation and maintenance inquiry information. Here, the intelligent question-and-answer component is based on multiple language models, and by leveraging the model advantages of each language model, inquiry responses in various scenarios can be achieved. In addition, by determining the query type, at least one language model matching the characteristics of that query type is selected. Therefore, the advantages of each language model can be combined to accurately output the response to the maintenance query. Furthermore, based on the at least one language model corresponding to the aforementioned query type, the maintenance response can be accurately generated. Here, the at least one language model is one of several language models. Finally, the maintenance response is sent to the corresponding display terminal so that the target user can access the response to the maintenance query. In summary, the intelligent question-answering component allows for the accurate and rapid generation of maintenance response information by selecting at least one corresponding language model when the query type of the maintenance query is determined.
[0088] Further reference Figure 3 The diagram illustrates a flow 300 of some other embodiments of the operation and maintenance response information generation method according to this disclosure. This operation and maintenance response information generation method includes the following steps:
[0089] Step 301: Obtain the maintenance inquiry information input by the target user.
[0090] Step 302: Use the intelligent question-answering component to determine the question type corresponding to the above maintenance inquiry information.
[0091] Step 303: Invoke the multi-type question-and-answer intelligent platform corresponding to the other question types mentioned above.
[0092] In some embodiments, the executing entity (e.g. Figure 1The electronic device 101 shown can call the multi-type question-and-answer intelligent platform corresponding to the other query types mentioned above. The multi-type question-and-answer intelligent platform is built based on at least one of the above language models. The other query types can be any question-and-answer types other than data query types and customized scenario question-and-answer types. For example, other question-and-answer types can be knowledge response types in non-customized scenarios. The multi-type question-and-answer intelligent platform can be a next-generation one-stop AI Agent development platform. Regardless of whether the user has programming experience, they can quickly build various question-and-answer intelligent agents based on AI models on the AutoBots platform (i.e., the multi-type question-and-answer intelligent platform). It is trained based on the company's internal Autobots and has functions such as memory, setting, custom knowledge base, and workflow. It supports rich data sources and can add data in text and table formats. Content upload is simple. Local TXT, PDF, DOCX, Excel, and CSV documents can be uploaded to the knowledge base. Joyspace content and API JSON data can also be obtained based on Joyspace file URLs and folder URLs. Custom data can also be added directly to the knowledge base.
[0093] For international logistics operations and maintenance scenarios, a unified knowledge base has been established internationally, including materials such as "Operations and Maintenance Q&A," "Technical Design Documents," "Product Requirements Documents," and "Operation Manuals." Based on the company's internal system data, this greatly assists product and R&D teams in understanding new requirements. For example, regarding the "requirement to add a fixed shipping address to a product," the multi-type Q&A intelligent platform can output the PRD (Product Requirements Document) based on key information, listing system function points that may require adjustment. This effectively helps the technical team supplement the content and prevents the omission of function points.
[0094] It should be noted that the multi-type question-and-answer intelligent platform can be an intelligent platform that answers questions related to operation and maintenance information.
[0095] Step 304: Input the above-mentioned maintenance inquiry information into the above-mentioned multi-type question and answer intelligent platform to generate the above-mentioned answer knowledge as the above-mentioned maintenance response information.
[0096] In some embodiments, the aforementioned execution entity may input the aforementioned maintenance inquiry information into the aforementioned multi-type question-and-answer intelligent platform to generate the aforementioned response knowledge as the aforementioned maintenance response information.
[0097] Step 305: Send the above maintenance response information to the corresponding display terminal so that the target user can obtain the response content corresponding to the above maintenance inquiry information.
[0098] In some embodiments, the specific implementation of steps 301-302 and 305 and their resulting technical effects can be found in [reference needed]. Figure 2 Steps 201-202 and 204 in the corresponding embodiments will not be repeated here.
[0099] from Figure 3 It can be seen from this that, with Figure 2 Compared to the description of some corresponding embodiments, Figure 3 The process 300 of the operation and maintenance response information generation method in some corresponding embodiments can accurately and effectively respond to operation and maintenance inquiry information under other inquiry types through a multi-type question and answer intelligent platform.
[0100] Further reference Figure 4 As an implementation of the methods shown in the above figures, this disclosure provides some embodiments of an operation and maintenance response information generation device, which are similar to... Figure 2 Corresponding to the method embodiments shown, this maintenance response information generation device can be specifically applied to various electronic devices.
[0101] like Figure 4 As shown, an operation and maintenance response information generation device 400 includes: an acquisition unit 401, a determination unit 402, a generation unit 403, and a sending unit 404. The acquisition unit 401 is configured to acquire operation and maintenance inquiry information input by a target user; the determination unit 402 is configured to use an intelligent question-and-answer component to determine the inquiry type corresponding to the operation and maintenance inquiry information, wherein the intelligent question-and-answer component is a component encapsulated based on multiple language models for processing questions corresponding to various inquiry types; the generation unit 403 is configured to generate operation and maintenance response information corresponding to the operation and maintenance inquiry information based on at least one language model corresponding to the inquiry type, wherein the at least one language model is a model among the multiple language models; and the sending unit 404 is configured to send the operation and maintenance response information to a corresponding display terminal so that the target user can obtain the response content corresponding to the operation and maintenance inquiry information.
[0102] In some optional implementations of some embodiments, the above-mentioned query type is a data query type; and the generation unit 403 may be further configured to: determine the query data table corresponding to the above-mentioned maintenance query information according to at least one language model corresponding to the above-mentioned data query type; generate the query statement corresponding to the above-mentioned maintenance query information according to the table structure corresponding to the above-mentioned query data table; and execute the above-mentioned query statement to generate the above-mentioned maintenance response information.
[0103] In some optional implementations of some embodiments, the above-mentioned inquiry type is a customized scenario question-and-answer type; and the generation unit 403 can be further configured to: retrieve the response service information corresponding to the above-mentioned customized scenario question-and-answer type, wherein the service corresponding to the above-mentioned response service information is encapsulated based on the above-mentioned at least one language model; and generate the operation and maintenance response information corresponding to the above-mentioned operation and maintenance inquiry information based on the above-mentioned response service information.
[0104] In some optional implementations of some embodiments, the above-mentioned query type is other query types; and the generation unit 403 can be further configured to: call the multi-type question-and-answer intelligent platform corresponding to the above-mentioned other query types, wherein the above-mentioned multi-type question-and-answer intelligent platform is built based on the above-mentioned at least one language model; input the above-mentioned maintenance query information into the above-mentioned multi-type question-and-answer intelligent platform, generate the above-mentioned answer knowledge, and use it as the above-mentioned maintenance answer information.
[0105] In some optional implementations of certain embodiments, the generation unit 403 may be further configured to: execute the above query statement based on data overload technology, data compliance technology, and data security technology to generate the above operation and maintenance response information.
[0106] It is understandable that the units recorded in the maintenance response information generation device 400 are related to the reference. Figure 2 The steps in the described method correspond to each other. Therefore, the operations, features, and beneficial effects described above for the method also apply to the maintenance response information generation device 400 and the units contained therein, and will not be repeated here.
[0107] The following is for reference. Figure 5 It illustrates electronic devices suitable for implementing some embodiments of this disclosure (e.g., Figure 1 A schematic diagram of the structure of electronic device 101)500. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of this disclosure.
[0108] like Figure 5 As shown, the electronic device 500 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory 502 or a program loaded from a storage device 508 into a random access memory 503. The random access memory 503 also stores various programs and data required for the operation of the electronic device 500. The processing unit 501, the read-only memory 502, and the random access memory 503 are interconnected via a bus 504. An input / output interface 505 is also connected to the bus 504.
[0109] Typically, the following devices can be connected to the input / output interface 505: input devices 506 including, for example, a touchscreen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and communication devices 509. Communication device 509 allows electronic device 500 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 5 An electronic device 500 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively. Figure 5 Each box shown can represent a device or multiple devices as needed.
[0110] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a read-only memory 502. When the computer program is executed by the processing device 501, it performs the functions defined above in the methods of some embodiments of this disclosure.
[0111] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.
[0112] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.
[0113] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: acquire maintenance inquiry information input by a target user; determine the inquiry type corresponding to the maintenance inquiry information using an intelligent question-answering component, wherein the intelligent question-answering component is a component encapsulated based on multiple language models for processing questions corresponding to various inquiry types; generate maintenance response information corresponding to the maintenance inquiry information based on at least one language model corresponding to the inquiry type, wherein the at least one language model is a model among the multiple language models; and send the maintenance response information to a corresponding display terminal so that the target user can obtain the response content corresponding to the maintenance inquiry information.
[0114] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages or a combination thereof, including object-oriented programming languages such as Java, Smalltalk, and C++, and conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0115] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0116] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including an acquisition unit, a determination unit, a generation unit, and a transmission unit. The names of these units do not necessarily limit the specific unit; for example, an acquisition unit may also be described as "a unit that acquires maintenance inquiry information input by a target user."
[0117] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.
[0118] Some embodiments of this disclosure also provide a computer program product, including a computer program that, when executed by a processor, implements any of the above-described methods for generating maintenance response information.
[0119] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.
Claims
1. A method for generating operation and maintenance response information, comprising: Obtain maintenance inquiry information input by the target user; Using an intelligent question-answering component, the question type corresponding to the operation and maintenance inquiry information is determined. The intelligent question-answering component is a component based on multiple language models and used to process questions corresponding to various question types. Based on at least one language model corresponding to the query type, generate operation and maintenance response information corresponding to the operation and maintenance query information, wherein the at least one language model is a model among the plurality of language models; The maintenance response information is sent to the corresponding display terminal so that the target user can obtain the response content corresponding to the maintenance inquiry information.
2. The method according to claim 1, wherein, The query type is a data query type; as well as The step of generating maintenance response information corresponding to the maintenance inquiry information based on at least one language model corresponding to the inquiry type includes: Based on at least one language model corresponding to the data query type, determine the query data table corresponding to the operation and maintenance query information; Based on the table structure corresponding to the query data table, generate the query statement corresponding to the operation and maintenance query information; Execute the query statement to generate the operation and maintenance response information.
3. The method according to claim 1, wherein, The question type is a customized scenario-based question and answer type; as well as The step of generating maintenance response information corresponding to the maintenance inquiry information based on at least one language model corresponding to the inquiry type includes: Retrieve the response service information corresponding to the customized scenario question-and-answer type, wherein the response service information corresponds to a service encapsulated based on the at least one language model; Based on the response service information, generate the operation and maintenance response information corresponding to the operation and maintenance inquiry information.
4. The method according to claim 1, wherein, The query type is any of the other query types; as well as The step of generating maintenance response information corresponding to the maintenance inquiry information based on at least one language model corresponding to the inquiry type includes: Invoke the multi-type question-answering intelligent platform corresponding to the other query types, wherein the multi-type question-answering intelligent platform is built based on the at least one language model; The operation and maintenance inquiry information is input into the multi-type question and answer intelligent platform to generate the answer knowledge, which serves as the operation and maintenance response information.
5. The method according to claim 2, wherein, Executing the query statement to generate the maintenance response information includes: Based on data overload technology, data compliance technology, and data security technology, the query statement is executed to generate the operation and maintenance response information.
6. The method according to claim 1, wherein, The intelligent question-answering component supports the following functions for the corresponding intelligent objects: multi-backend interaction function, data sharding storage function, rapid system expansion function, customized scenario expansion access function, and data processing function.
7. The method according to claim 4, wherein, The multi-type question-answering intelligent platform supports various operations on the knowledge base, including: custom addition, memory, and search operations.
8. A device for generating operation and maintenance response information, comprising: The acquisition unit is configured to acquire maintenance inquiry information input by the target user; The determining unit is configured to use an intelligent question-answering component to determine the question type corresponding to the operation and maintenance inquiry information, wherein the intelligent question-answering component is a component based on multiple language models and used to process questions corresponding to various question types; The generation unit is configured to generate operation and maintenance response information corresponding to the operation and maintenance query information based on at least one language model corresponding to the query type, wherein the at least one language model is a model among the plurality of language models; The sending unit is configured to send the maintenance response information to the corresponding display terminal so that the target user can obtain the response content corresponding to the maintenance inquiry information.
9. An electronic device, comprising: One or more processors; Storage device, on which one or more programs are stored, When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.
10. A computer-readable medium having a computer program stored thereon, wherein, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-7.
11. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1-7.