333 results about "Flowchart" patented technology

The invention relates to the technical field of process automation, in particular to an RPA service automation method capable of enabling a large language model MCP. The method comprises the following steps: acquiring user input data, and performing intention understanding through a multi-round intention recognition model according to the user input data to obtain semantic instruction data; performing standard semantic protocol conversion according to the semantic instruction data to obtain standard semantic protocol data; performing flow chart node matching according to the standard semantic protocol data to obtain flow chart node data; and generating a business process according to the flow chart node data to obtain business process data. According to the method, the multi-round intention recognition capability of the large language model and the standard semantic protocol conversion are fused, so that the accurate mapping from the natural language to the business process is realized, and the intelligent level and the user friendliness of the RPA system are improved. Through process node matching and process logic verification, the execution effectiveness of the automatic generation process is ensured, and the labor cost and configuration errors are reduced.

The invention provides a business rule automatic processing method and system based on natural language understanding. The method comprises the following steps: extracting text content from an original document containing business rules and preprocessing the text content; utilizing a BERT-based metadata extraction model to extract structured metadata from the preprocessed text content; confirming and perfecting the structured metadata; on the basis of the confirmed metadata, a rule execution flow chart and / or a test case are / is automatically generated and used for verifying the correctness of rule logic; and according to the target format, converting the verified rule into a corresponding symbolic representation through a template engine to obtain a defined rule. According to the invention, the automatic conversion of the business rule from the natural language description to the symbolized executable form is realized, so that business personnel can directly use the natural language to define and maintain the business rule, the manual conversion cost is reduced, and the accuracy and efficiency of rule processing are improved.

The invention relates to the technical field of artificial intelligence and software development, in particular to a DevOps assembly line intelligent generation system based on natural language description. According to the intelligent generation system for the DevOps assembly line based on the natural language description, an interaction layer is responsible for visually editing an interaction interface and outputting a generated executable script and a flow chart to a user; the intelligent processing layer takes Python and Go as development languages, fuses a knowledge graph technology, supports a dynamic code generation capability and realizes intelligent business process management and automatic execution; the infrastructure layer comprises three core modules, namely a metadatabase, a sandbox environment and an execution engine, and is responsible for providing basic support and resource guarantee for system operation. According to the intelligent generation system for the DevOps assembly line based on the natural language description, the configuration threshold of the DevOps assembly line is remarkably reduced, the cross-platform compatibility is ensured, the safety and reliability of the assembly line are greatly improved, and production accidents caused by manual configuration errors can be effectively avoided.

A method, computer program product, and computing system for flowsheet population. A structured document conforming to a schema and having a plurality of rows, each row comprising a key and a value, is processed. A plurality of key / value variations associated with an instance of information are identified. A plurality of key / value variation vectors are generated by embedding each key / value variation in a vector. The plurality of key / value variation vectors are combined into a combined vector representing the instance of information. A transcript is segmented into a segment, the segment corresponding to the instance of information. A transcript segment vector is generated by embedding the instance of information in the segment into a vector. A similarity between the transcript segment vector and the and the combined vector is determined. The instance is extracted from the transcript segment vector by processing a prompt with a generative artificial intelligence (AI) model using retrieval augmented generation (RAG). A value of a row corresponding to the key is populated with the instance of information.

The present invention discloses a method, device, and medium for identifying software component analysis, which relates to the technical field of software technology. Specifically, it includes: obtaining all files in the software to be identified to obtain a first data set; extracting meta-file data to obtain a second data set, and obtaining a first open-source file set through first feature matching; performing deletion processing on the first data set to obtain a third data set, calculating the minimum hash signature through the program abstract syntax tree and the corresponding sub-syntax tree to generate a second feature set, and obtaining a second open-source file set through third feature matching; performing deletion processing on the third data set to obtain a fourth data set, obtaining an updated syntax tree based on the abstract syntax tree and the fourth data set and constructing a control flow diagram, and obtaining a third open-source file set through fourth feature matching between the third feature set and a preset reference database; merging the first open-source file set, the second open-source file set, and the second open-source file set to obtain the total open-source component set in the software to be identified.

The invention relates to the technical field of computers, and provides a flow chart processing method and device, equipment and a storage medium, and the method comprises the steps: obtaining a to-be-processed visual flow chart; flow nodes of the visual flow chart represent logic units, and connecting lines between the flow nodes represent an execution sequence and a dependency relationship between the logic units; extracting flow information of the visual flow chart; the flow information comprises node types and node attributes of the logic units and a logic relation between nodes; and converting the visual flow chart into executable codes or scripts based on the flow information. By analyzing the flow chart, the flow information of the flow chart is directly converted into the executable code or script, so that the logic arrangement of the flow chart is simplified, the code development difficulty of the logic arrangement of the flow chart is reduced, and the logic arrangement efficiency of the flow chart is improved.

A task generation method performed by a computer device includes: obtaining task requirement information inputted based on a task generation interface; calling a large language model, and inputting the task requirement information into the large language model for performing semantic interpretation on the task requirement information and outputting an executable structural body of a target task that matches the task requirement information; performing graphic rendering on the target task based on the executable structural body of the target task, to obtain a task execution flowchart of the target task, and displaying the task execution flowchart in the task generation interface, the target task being formed according to one or more target atomic tasks; and displaying an execution progress viewing link of the target task in the task generation interface, the execution progress viewing link being configured for viewing an execution progress of the target task.

The invention discloses an artificial intelligence large model development-oriented low-code automatic generation and deployment system, which comprises the following steps of: performing semantic analysis on a natural language modeling demand input by a user, generating a structured modeling target, and constructing and optimizing a task flow chart. The system generates a corresponding low-code modeling instruction according to the optimized task flow chart, completes automatic matching of tasks and resources by adopting an improved shortest completion time scheduling algorithm in combination with the real-time state of heterogeneous computing resources, and automatically deploys the generated modeling tasks to a target computing environment in a containerization manner, so that the modeling efficiency is improved. And unified operation control and process monitoring are carried out, so that automatic closed loop from semantic input to model deployment is realized.

The prediction system accesses a flowchart of questions relating to surgical cases and receives, for each of set of surgical case identifiers, surgical case information and an actual surgical case length. The prediction system trains a machine learning model to predict surgical case lengths using the surgical case information and prunes the flowchart by removing questions associated with a uniform set of answers. The prediction system receives, from a client device, a request to reserve an operating room for a surgical case, and transmits, for display via a user interface of the client device, questions from the flowchart. The prediction system receives a feature vector of answers to the transmitted questions from the client device and inputs a type surgical case and the feature vector to the machine learning model, which outputs a predicted surgical case length. The prediction system reserves an operating room for the predicted surgical case length.

To customize a free template, and to output a flowchart showing the latest task execution status.SOLUTION: A task management program that manages a task by customizing a free template causes a computer to execute: processing (S1) of accepting input of information that identifies task contents; processing (S2) of accepting input of a required period to complete the task; processing (S3) of accepting registration of staff involved in execution of the task; processing (S4) of accepting input of information showing progress status of the task; and processing (S5) of outputting a flowchart showing the latest task execution status based on each piece of the input information.SELECTED DRAWING: Figure 7A

The present invention provides a test case generation method, device, system, and medium based on an AI model. The method includes: obtaining a requirement document, at least one title keyword, and business keywords input by a user, and being able to automatically traverse the requirement document to automatically distinguish different requirement modules by the target title and create corresponding first and second documents; when traversing to a target image, extracting first content from the target image based on an OCR module and writing it into the first document, and being able to record the first content recognized by the OCR module from the flowchart through the first document; when traversing to a new target title, triggering the input of the first document into the AI model to obtain target test cases and first inference information, improving the generation efficiency of test cases, and at the same time recording the inference information of the test cases in the first document, providing a basis for the inference process for testers to judge the reliability of the test cases.

The invention belongs to the technical field of software development, and relates to a code generation method and system based on a time sequence driving flow chart. The method comprises the steps that a user side starts a code generator process, generates request information and sends the request information to a code generator; the data server configures each node of the flow chart and the relationship among the nodes, reads the configuration of the flow chart, analyzes the configuration into a syntax tree, and performs association mapping on the syntax tree and the flow chart; the data server generates configuration data; and the code generator reads the request information and the configuration data on the data server, and calls the configuration data to generate a code file. According to the method, the time sequence information and the flow chart are combined, the time sequence relation and the logic structure in the system can be more accurately reflected through the automatically generated codes, the problems that the extraction and search efficiency of the program flow chart is low, time sequence control is lacked, and the semantics of the generated codes are inconsistent are solved, the code generation efficiency and stability are effectively improved, and the method is suitable for popularization and application. And the development requirements of complex systems with high time sequence requirements are met.

The invention relates to the technical field of software engineering and information processing, in particular to a semantic verification method and device based on a large model.The method comprises the steps that a source code file and a corresponding software requirement and design document are obtained, code semantic representation is generated based on grammar analysis and static program analysis, and a semantic verification result is obtained; based on text analysis and business flow chart structure identification, generating a design demand semantic representation; respectively inputting the code semantic representation and the design demand semantic representation into a pre-training language large model to generate a code implementation logic description and a design demand logic description; and performing semantic consistency verification on the two types of logic descriptions to obtain a semantic inconsistency result, determining a code position in the source code file based on the semantic inconsistency result, and outputting a scanning report. According to the invention, the automation degree and the rechecking performance of consistency checking of requirements can be improved, and the leak detection and reworking cost can be reduced.

The invention relates to the technical field of data processing, in particular to a complex semantic-oriented business process multi-agent modeling and intelligent error correction method and system. The method comprises the following steps: firstly, based on a BPMN meta-model, disassembling business process elements, analyzing BPMN specifications, forming a structured framework of business process modeling, processing unstructured texts in parallel through an intelligent agent group, identifying business process key concepts, mapping the business process key concepts into semi-structured information, and generating a preliminary extraction result; verifying the integrity of the preliminary extraction result based on a BPMN specification, and generating an information integrity verification report; based on an information integrity verification report, missing information of the preliminary extraction result is retrieved through a knowledge base and complemented; performing secondary verification on the complemented extraction result, and correcting the complemented extraction result based on business logic and user requirements; and generating an XML code and a visual flow chart conforming to the BPMN specification based on the corrected extraction result. According to the method, the problems of semantic fracture and structure deficiency of the complex semantic text in business process modeling can be effectively solved.

The invention discloses a flow chart image analysis and structured reconstruction method and device and a storage medium, and relates to the technical field of image processing, and the method comprises the steps: carrying out the element background separation of an input image through a pre-trained convolutional neural network, and obtaining a flow chart image, the elements including text elements and graphic elements; extracting rectangular frame information, arrow information, text information and position coordinates thereof in the preprocessed flow chart image; determining the node type of each node in the flow chart image based on the rectangular frame information and the text information, and determining the connection relationship of each node based on the arrow information in combination with the position coordinates; analyzing the node type and the connection relationship of each node, modeling the logic relationship of each node, and generating a control flow diagram of the flow diagram image; and converting the control flow diagram into structured data, and rendering to generate an interactively editable flow diagram visual interface. According to the method and the device, the technical effect of reconstructing the structured flow chart by identifying the control logic structure of the flow chart is realized.

A computing platform is configured to: (i) generate a logical flowchart for a construction project task, the logical flowchart based on at least one incongruous rule and at least one incongruous data set; (ii) generate a text-based graphical user interface (GUI) prompt based on the logical flowchart; (iii) cause the text-based GUI prompt to be presented via one or more of the first client station, the second client station, or combinations thereof; (iv) receive, from a client station, an indication of user input to the text-based GUI prompt; and (v) cause the text-based GUI prompt to present output information, via the first client station, based on the logical flowchart and the user input.

The invention relates to the technical field of semantic analysis, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a business process analysis method, device and equipment based on a natural language and a medium. Generating a target logic tree corresponding to the natural language instruction; converting the logic structure in the target logic tree into a structured code, and performing grammar verification on the structured code; correcting the structured codes which do not pass the grammar verification, and performing rendering operation on the target structured codes to obtain a visual flow chart; adjusting the visual flow chart, and updating the structured code based on the adjusted visual flow chart; and when the visual flow chart meets the flow demand of the target user, outputting a target flow chart corresponding to the natural language instruction, and performing business flow analysis on the natural language instruction by using the target flow chart. And the efficiency of business process analysis is improved.

The invention discloses a flow chart random generation method, system and device and a storage medium, which can construct a polygon shape according to a group of random points and perform randomization processing on the polygon shape, and can also introduce 3D elements and project the 3D elements to a 2D space to enhance a visual effect. More importantly, the method ensures that the elements in the generated flow chart are not overlapped through a series of steps, and pixel-level instance labels related to the elements, connections and characters can be automatically generated, so that the quality and applicability of the flow chart are greatly improved. Meanwhile, the system also supports the user to import self-defined elements, connection styles and background templates, and allows personalized adjustment, so that the finally output flow chart not only meets the special requirements of the user, but also can ensure good visual presentation and professional annotation information. The method effectively solves the problems of low efficiency, single style and insufficient technical detail support in the traditional flow chart generation process.

The invention discloses a flow-based front-end and back-end code automatic generation method, system, medium and equipment, and the method comprises the steps: analyzing a preset Flowable flow chart according to a preset Flowable engine, obtaining node information and a flow definition key of the Flowable flow chart, and generating a flow node configuration table according to the node information; obtaining form and field configuration information from a preset business design scheme and a process database; wherein the form and field configuration information and the node information are associated according to the process definition key; and transmitting the form and field configuration information and the process node configuration table as parameters to a preset Velocity template engine, so that the Velocity template engine dynamically generates a back-end interface code and a front-end page code. According to the method, the development efficiency and the code quality are improved through standardized configuration of the database table in combination with the use of the process engine and the template engine.

The invention discloses a script-free UI automatic testing system and method based on a swan monk system, and relates to the technical field of UI automatic testing. The method comprises the steps that a testing frame is deployed to a swan monk 5.0 development environment, a to-be-tested interface component tree is traversed, and if an element with the same unique identifier as a to-be-tested interface element component does not exist in an element library, the script-free UI automatic testing system is started; if yes, an element auxiliary analysis instruction is sent out; after an element auxiliary analysis instruction is received, obtaining an attribute library text of the interface element, converting the attribute library text into a vector, and calculating a second attribute similarity of the to-be-tested interface element according to a second attribute vector of the to-be-tested interface element and a second attribute vector of the interface element in the element library; according to the first attribute similarity and the second attribute similarity of the to-be-tested interface elements, the comprehensive matching coefficient of the to-be-tested interface elements is calculated, and manual calibration early warning is sent outwards; and after matching of all the interface elements is completed, an interface element operation flow chart is generated, parameterized testing is achieved, and the efficiency and quality of automatic testing can be improved.

The invention relates to the technical field of computers and the field of financial science and technology businesses, and discloses an application code visualization method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining source codes corresponding to all source files, and generating a code visualization plug-in according to each source code; and generating a visual flow chart by analyzing the logic flow and the target transfer function of the code visualization plug-in, and displaying the visual flow chart. By means of the mode, the source code is read through the code visualization plug-in and converted into the representation form of the visualization flow chart, the visualization flow chart assists a developer to understand the code logic and structure more quickly, and when codes are modified or reconstructed, the visualization flow chart provides a clear reference. The code visualization efficiency of the front-end application in the financial science and technology business field is improved, the visualization flow chart enables a user to quickly understand an existing code structure, and development of new functions and improvement of existing functions are accelerated.

The invention provides a flow chart display method and device, and relates to the technical field of front-end display. The method comprises the following steps: acquiring user role information; if the user role information corresponds to the operation role, target nodes corresponding to the user role information and the relation between the target nodes are determined from the target flow chart, the target nodes comprise to-be-operated nodes corresponding to the operation role and operated nodes on which the to-be-operated nodes depend, and the operation role comprises roles used for node operation; and displaying the target nodes in the target flow chart and the relationship between the target nodes. As the target node is not all nodes in the target flow chart but the node concerned by the operation role, the user can conveniently and quickly find the node to be operated, and the operation is carried out under the assistance of the operated node which the user depends on.

The invention discloses a flow chart construction method, electronic equipment, a storage medium and a computer program product, relates to the technical field of flow chart design, is applied to a to-be-constructed flow chart, and comprises the following steps: searching business domain knowledge associated with flow information in a preset knowledge base according to the received flow information, the flow information comprises a target flow chart node selected by the user in the to-be-constructed flow chart; determining a large model cue through the process information and the business domain knowledge, and inputting the large model cue into a preset large model to obtain a node recommendation list; and outputting a node recommendation list, and associating the flow chart node selected by the user in the node recommendation list with the target flow chart node. The technical problems of low flow chart construction efficiency and poor effect are solved.

A method, computer program product, and computing system for flowsheet population by voice. Dictation or conversation is transcribed from voice to text. The keys and values relevant to the documentation are extracted from the transcript and used to populate the flowsheet by selecting a subset of rows and examples relevant to the transcription of the information from a plurality of rows in the flowsheet and based on the transcript, each row corresponding to a key and a value for the flowsheet and extracting an instance of information from the transcript of information associated with a key from the subset of rows by processing a prompt including at least a portion of the transcript of information and the subset of rows with a generative artificial intelligence (AI) model using retrieval augmented generation (RAG).

The invention discloses a machine learning Pipeline generation and deployment method and system based on a graph structure, and relates to the technical field of machine learning automatic modeling. The method comprises the steps that a machine learning flow chart designed by a user through a graphical interface is obtained, nodes in the flow chart represent operation, and edges in the flow chart represent data streams; mapping each node in the flow chart to a corresponding algorithm, and generating an executable machine learning Pipeline; executing the Pipeline, completing feature engineering, model training and evaluation, and obtaining an evaluation index; and if the evaluation index meets a preset threshold value, deploying the Pipeline as a model service. The method is used for solving the problems that in the prior art, node interface semantic conflicts are difficult to automatically and efficiently adapt, and model reasoning deployment lacks compilation level optimization for heterogeneous hardware characteristics.

The invention belongs to the field of low-code platform development, and discloses a cross-platform low-code development system and method supporting code export. The method comprises the following steps: dividing a visual layout in a low-code platform into a central process region and R sub-process regions according to a preset rule; obtaining center structure data and sublevel structure data of the target project; obtaining a total logic complexity value of the project based on the central structure data and the sublevel structure data; obtaining an initial flow chart corresponding to the target project; inputting the central structure data, the sub-level structure data, the total logic complexity value and the initial flow chart into a pre-trained flow optimization model to obtain an optimized target flow chart; packaging a target sub-flow in the target flow chart to serve as a reusable plug-in of a cross-project flow; and the running efficiency of the developer project is effectively improved.

The invention discloses a business system building method and system, and relates to the field of business process management, and the method comprises the steps: recognizing related entities such as roles, demands, strategic targets and the like through a bidirectional undifferentiated coding model, carrying out semantic coding and element classification through an attention polarity model, and generating a benefit related party graph in combination with a rule engine; calculating a demand weight by means of a graph neural network, embedding a semantic vector to generate a weighted strategic vector, constraining an AI model to extract flow nodes, and correlating to generate a flow element table; a final-stage flow chart is generated through state coding and a near-end strategy optimization learning network, a programming environment is determined based on requirements, a code segment is matched to generate a service system, full-process automation from strategic analysis to service system generation is achieved, the development efficiency of the service system is improved, and the technical threshold is reduced.

The invention discloses a machine learning platform and method based on workflow, electronic equipment and a storage medium, and the platform comprises a management scheduling system, a workflow engine system and an operator runtime system. A user is allowed to construct a visual business process in a dragging and connecting mode, and each component corresponds to a specific AI algorithm processing unit written by Python; the platform supports the realization of multi-node business logic by using an operator concept by referring to a BPMN specification, automatically analyzes a flow chart designed by a user into a directed acyclic graph, converts the directed acyclic graph into an API calling sequence for a Python runtime system, disassembles a complex business system into a multi-branch and multi-step configurable process, and executes local logic by each node to realize multi-node business logic. The whole process is visually arranged, the development threshold is remarkably reduced, and the execution efficiency and the system flexibility are improved.

The invention discloses an automatic test method and system for an electric energy meter, and solves the problems that the electric energy meter is poor in test configuration flexibility, difficult to quickly adapt to different test requirements, poor in test reliability and low in precision, and the method comprises the steps: collecting an existing test flow chart and an editing mode, and carrying out the preprocessing, and taking the collected test flow chart and editing mode as training data; a pre-training language model is adopted as a basic model, and a test knowledge graph is constructed and embedded into a Transform framework; automatically associating a standard error threshold value in the knowledge graph by using an attention mechanism in an encoder of a Transform architecture, adding a knowledge constraint layer in a decoder, and constructing a test scheme automatic generation model; and automatically generating a test scheme by using the test scheme automatic generation model, and carrying out automatic test on the electric energy meter. The configuration flexibility is improved, a user can quickly adapt to different test requirements, the error rate is reduced, the high stability and consistency of a test environment are ensured, and the stability of a test result is improved.

The invention discloses a code-configuration-free digital twin warehouse system and a construction method thereof. The construction method comprises the following steps: initializing a warehouse digital twin platform, importing entity object data, and establishing a basic two-dimensional data visualization framework and a three-dimensional rendering engine; collecting multi-source heterogeneous data in real time and preprocessing the multi-source heterogeneous data to obtain a real-time data source; 2D / 3D coordinate precision mapping and dynamic data coupling are carried out; calling a code-free configuration tool, receiving a real-time data source for a user to drag and use, and assembling a logic flow chart by the user through dragging; analyzing the logic flow chart assembled by the user through middleware to generate a low-level instruction sequence; the low-level instruction sequence is input into an external actuator and a physical simulation engine; virtual verification and situational simulation are executed through a physical simulation engine, and optimization suggestions are output and adjusted. The invention provides a code-free configuration integration mechanism, supports non-technical personnel to autonomously construct data-driven twinning application, and realizes transformation of warehouse digital twinning from static monitoring to dynamic iteration.