1103results about "Creation/generation of source code" patented technology

The invention provides a code generation and evaluation method and system based on RAG and a multilevel decision tree, and the method comprises the steps: integrating project related design documents, and constructing a knowledge base capable of semantic retrieval through a vectorization technology; associating business demand description with related documents in the knowledge base based on an RAG technology, and performing demand semantic enhancement to generate a technology demand cue word; receiving the technical requirement cue word by adopting a large language model so as to generate a complete code conforming to business logic; constructing a four-level decision tree evaluation system, and sequentially executing code quality scanning, deployability verification, dynamic test verification and demand satisfaction verification through an evaluation assembly line to generate an evaluation result; and generating an optimization suggestion according to the evaluation result so as to trigger an iteration generation process when the code does not pass the verification, thereby solving the problems of disjunction between code generation and business requirements, low verification efficiency and insufficient iteration optimization.

According to the automatic software development method and device and the computer program, intelligent demand analysis is achieved through a natural language processing technology, dynamic task arrangement is conducted through a finite state automaton, collaborative development is completed by means of a multi-specialized role agent, intelligent verification is implemented based on a template matching mechanism, and the development efficiency is improved. And a complete automatic closed loop from demand to delivery is constructed. According to the scheme, full-process automation is realized, manual intervention is greatly reduced, and the development efficiency is remarkably improved; through division and cooperation of multiple agents, the professionality and decision-making quality of each link are ensured, and the capability limitation of a single agent is overcome; flexible and reliable process control is provided based on state machine management, and development state changes are dynamically adapted; and the standard consistency of the delivery result is ensured by combining template verification. According to the method, the problems of long development period, large quality fluctuation and the like caused by chain splitting, low intelligent level and excessive dependence on manpower of an existing development tool are effectively solved, and a feasible path is provided for comprehensive intelligence of software development.

The invention provides a code retrieval method and device for AI programming and related equipment, and the method comprises the steps: constructing a double-layer embedded vector model which comprises a basic semantic coding layer for parameter freezing and a plurality of independent lightweight adaptation layers which coexist; monitoring implicit feedback data generated by interaction of a user in the target code library to extract positive and negative sample pairs, and mining difficult negative samples based on a current model to form a training sample set; when the cumulative number of the samples reaches a preset trigger threshold value, optimizing and updating at least one lightweight adaptation layer parameter by utilizing a preset comparison loss function, and applying elastic weight constraint to key parameters of the lightweight adaptation layer parameter to obtain an updated double-layer embedded vector model; and performing multi-dimensional performance evaluation on the updated model, and when an evaluation result meets a preset publishing condition, deploying the model to a code retrieval service. The problems that in the prior art, cross-domain is difficult, the adaptation cost is high, and catastrophic forgetting is likely to happen are effectively solved, and zero-labeling self-evolution of the model is achieved.

The invention relates to the technical field of computer software development and databases, in particular to an embedded database programming method which comprises the steps of intention model construction: scanning source codes to identify embedded syntax blocks, constructing an abstract syntax tree, stripping a bottom driver and generating a driver-independent intention model; a logic sequence synthesis step: injecting a dialect parameter and a resource strategy, synthesizing and executing a logic sequence and generating a target code; a fingerprint verification step: intercepting a request during operation, calculating a structure fingerprint, and performing consistency verification on the structure fingerprint and the reference fingerprint; and a binding execution step: executing the request after the verification is passed, and establishing weak reference life cycle binding of the resource object and the host variable. The resource leakage risk is eliminated, and the robustness of the system under long-time operation is enhanced.

The invention discloses a multi-modal sensor abstract description and packaging method and system based on software definition. Firstly, a unified sensor abstract description model based on software definition is introduced, so that hardware independence is realized, and the differences of a bottom-layer multi-mode sensor in the aspects of interfaces, protocols and data formats can be effectively shielded; secondly, abstract packaging of data is achieved through an autonomous information processing module, and high-bandwidth and high-redundancy original data is converted into low-bandwidth and high-value structured information; in addition, by means of automatic registration, discovery, scheduling and control mechanisms of the sensor management control module on sensor resources, the system realizes a real plug-and-play function. According to the invention, by deploying the autonomous information processing modules at various sensor nodes, the original sensing data is preprocessed, and standardized data packaging with semantic consistency is output, so that the operation load of the central controller is reduced, and the information processing efficiency and the system response capability are also improved.

The invention discloses a data processing device, a data processing method, a chip and electronic equipment, and relates to the technical field of data processing. The data processing apparatus includes: a storage module configured to store data; the calculation module is coupled to the storage module and is configured to access an original data vector stored in the storage module, and the original data vector comprises m data elements; splitting the original data vector based on the target k value to obtain a plurality of first data vectors; performing odd-even merging sorting on the data elements in the first data vectors to obtain a plurality of first ordered data vectors; and merging and sorting the data elements in the plurality of first ordered data vectors to obtain top-k data elements in the m data elements. According to the data processing device, the data processing method, the chip and the electronic equipment provided by the invention, the top-k data elements can be obtained without a special hardware sorting network.

The invention discloses a multi-language PLC configuration software component library expansion method and system based on LLVM, and relates to the technical field of configuration software, the method comprises the following steps: obtaining language source codes of various types of programming languages supporting the LLVM front end; inputting the language source code of each type of programming language into a corresponding LLVM front-end compiler, and converting the language source code into a standard intermediate representation; establishing a general language characteristic analysis framework; establishing a general abstract metadata injection framework; building a mapping rule framework; integrating the general language framework, the general abstract metadata injection framework, the mapping rule framework and the output result, and generating a unified extended intermediate representation; and generating an interface component library conforming to the IEC standard. According to the method, any programming language with an LLVM front end is supported, a developer can directly utilize a mature algorithm library in each language ecosystem to select the programming language most suitable for a specific application scene, and the development period is remarkably shortened.

The invention discloses a spray combustion sub-model integrated development method and equipment based on a large language model, and belongs to the technical field of engines. The method is realized by relying on a retrieval enhancement generation system and a multi-agent collaborative framework, and comprises the following steps: S1, user instruction and thesis extraction: extracting core information from related technical literatures to form a structured file according to a sub-module extension requirement proposed by a user; s2, source code analysis and comparison data generation; s3, function and interface planning: performing adaptive planning of an original model-OpenFOAM platform; s4, code generation and packaging: code conversion, dependency processing, test example generation and compilation packaging; s5, layered testing and verification graph generation; and S6, debugging and repairing: executing a positioning-repairing-regression closed-loop process through a debugging agent. According to the method, the problems that the spray combustion sub-model is difficult to migrate to the OpenFOAM simulation platform under different frameworks and the development period is long can be solved.

To efficiently generate a data set using a large-scale language model.SOLUTION: There is provided an information processing method for generating a layered data set, the information processing method including a receiving step, an outputting step, and an acquiring step, wherein in the receiving step, a design prompt is received, the design prompt includes an instruction to generate the data set and is composed of a plurality of prompts that are layered into a plurality of layers, the prompts in the adjacent layers are associated with each other, in the outputting step, the design prompt is output to a large scale language model, and in the acquiring step, the data set is acquired from the large scale language model.SELECTED DRAWING: Figure 1

Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for generation of computer-executable code for automated zoning compliance. Zoning, building, planning, and other regulations for a jurisdiction are provided to a trained artificial intelligence model which provides computer-executable code that is configured, when executed, to provide output that indicates whether an input candidate building plan complies with the regulations for the jurisdiction. The computer-executable code generated by the trained artificial intelligence model is deployed in an application. The application receives, in a request, a candidate building plan. The application generates and provides a compliance report for the candidate building plan that includes compliance results for the candidate building plan with respect to the regulations for the jurisdiction.

The invention discloses a code generation method and device based on a large model, a storage medium and computer equipment. The method comprises the steps that a UI prototype draft of a target service is acquired; performing element identification on the UI prototype draft through a picture identification large model, and determining element information in the UI prototype draft; generating a code generation cue word based on the element information and a preset cue word, inputting the code generation cue word into a code generation large model to obtain an intermediate code corresponding to the UI prototype draft, and arranging a target service code of the target service based on the intermediate code. The automatic process from UI design to code generation is achieved, the tedious process of manually writing UI components and debugging interaction logic in traditional development is avoided, repeated work and human errors are reduced, developers can put more energy into core service function development, then development efficiency is improved, code quality is guaranteed, and the development cost is reduced. And rapid and high-quality delivery of the project is promoted.

Systems and methods for detecting anomalies in generative outputs are disclosed herein. The system receives a user prompt indicating a request for data over a time period. The system inputs, into a model, the user prompt to cause the model to generate an output based on the user prompt. The system then generates the first tokens based on the output. To generate the second tokens, the system retrieves, based on the user prompt, sources relating to the data requested by the user prompt. The system then generates queries to request, from the sources, the data over the time period and generates the second tokens based on the retrieved data. The system then performs a comparison of the first tokens and the second tokens and accepts or rejects the output of the model based on the comparison.

The invention provides a complex scene-oriented multi-modal AI Agent integrated development method and system, and the method comprises the steps: generating a layout graph G in an integrated development environment, and carrying out the consistency verification to obtain a constraint set C; a graph neural network is adopted to represent the arrangement graph to obtain graph embedding Z, and an environment state s is formed by combining key performance indexes in a sliding window; and in an action space AC limited by the C, jointly deciding computing power node selection, concurrent resource quota adjustment and semantic caching or semantic routing parameter configuration according to a reinforcement learning strategy pi, and executing actions to optimize throughput, tail delay, failure rate and resource contention degree. Through a closed loop of verification-constraint-learning-execution-monitoring-updating, cross-modal consistency and computing power scheduling are integrally optimized, training convergence and online stability are improved, long-tail time delay and the failure rate are remarkably reduced, the resource utilization rate is improved, and the method is suitable for large-scale popularization and application. The method is suitable for the fields of medical diagnosis, industrial quality inspection and equipment maintenance, retail recommendation and shopping guide and the like.

The present disclosure is directed toward systems, methods, and non-transitory computer-readable media for generating function code and test code to determine that the function code satisfies an intent query. For example, the disclosed systems utilize a large language model to process an intent query and generate function code that defines one or more processes whose execution satisfies the intent query. In addition, the disclosed systems also utilize the large language model to generate test code that defines a function test for determining that the function code satisfies the intent query. Moreover, the disclosed systems can execute the test code to determine that the function code satisfies the intent query.

The invention particularly provides an AI programming method and system based on multilayer memory fusion. The method comprises the following steps: inputting a natural language programming instruction of a user into an intention recognition module to obtain a task type and a target; based on the task type and the target, dynamically retrieving related context information from the multi-layer memory system to obtain a dynamic context; based on the instruction and the dynamic context, inputting the instruction and the dynamic context into a code generation and optimization module to generate a preliminary project code; global standard parameters are obtained; performing automatic verification through a conflict detection module, and selectively obtaining a final project code and a self-repairing report according to a verification result; performing comprehensive quality evaluation on the final project code to obtain a quality evaluation result; and the preliminary project code, the verification result, the final project code, the self-repairing report and the quality evaluation result are visually fed back to the user through the user interaction module. Project codes are automatically generated, detected and self-repaired.

Examples provide a system and method for dynamically improving and validating automation plans using generative artificial intelligence (AI). An automation manager analyzes automation plans during the design phase and the testing phase. The automation plan makes suggestions for improving the automation plan in real time using natural language prompts. The automation plan validates the automation plan against guardrails defining restrictions on the actions performed by the system during automation plan execution. The system generates explainability data describing the next planned actions and reasons why each planned action is selected for execution during the automation to increase user confidence in the automation. The system requests user approval prior to performing each action for more accurate and efficient workflow automation while reducing system resource usage consumed during execution of inefficient or ineffective automation plans.

The invention discloses a geometric image synthesis method, a related device and a system, and relates to the technical field of image synthesis, and the geometric image synthesis method comprises the steps: obtaining a geometric image demand text described by a user in a natural language; generating an image synthesis code according to the geometric image demand text by using the code large language model; synthesizing a plurality of geometric images based on the image synthesis codes; verifying the plurality of geometric images in combination with the geometric image demand text, and determining the conformity of the current image composite code according to the verification result; and if the conformity is greater than or equal to a preset conformity threshold value, outputting a geometric image which is verified to be qualified, and / or outputting an image synthesis code. According to the geometric image synthesis method disclosed by the invention, full-process automation from geometric image demand understanding to geometric image synthesis is realized, a user only needs to describe the geometric image demand through a natural language and does not need to have professional programming ability and graphic knowledge, and the technical threshold is greatly reduced.

The invention discloses a method for managing service nodes capable of being dynamically expanded based on a Camuda process engine, which belongs to the technical field of electric digital data processing and comprises the following steps of: uniformly configuring service process nodes into a pointing proxy delegation class; querying an external mapping table based on the execution context to obtain a business logic unit identifier; obtaining metadata from a logic registration center according to the identifier, and dynamically loading and instantiating a business logic implementation class through a sandbox class loader; driving service logic execution through a security context object of a white list only exposure method; and recording a full-link audit log. According to the method, structural decoupling of process definition and service logic is realized, so that the process definition does not need to be modified during service change, and dynamic replacement and gray release are supported; through sandbox isolation and security agent, isolated operation of dynamic codes and security and stability of an engine are ensured; and in combination with an audit tracking and fusing mechanism, the observability, the reliability and the operation and maintenance efficiency of the system are improved.

The invention discloses a data processing device, a data processing method, a chip and electronic equipment, and relates to the technical field of data processing. The data processing device comprises a storage module which is configured to store x groups of original data vectors, the original data vectors comprise m data elements, and x and m are positive integers; the calculation module is configured to access the original data vectors stored in the storage module, and reconstruct the x groups of original data vectors into one or more intermediate matrixes according to the parallel processing capability of the single-instruction multi-data execution unit and a target value k of a Top-k operator; loading the intermediate matrix into a vector register block according to columns, carrying out odd-even merging sorting by utilizing a single-instruction multi-data execution unit, and realizing in-line sorting on the intermediate matrix; and loading the intermediate matrix subjected to in-line sorting into a vector register block according to columns, and performing one or more rounds of merging sorting by utilizing a single-instruction multi-data execution unit to obtain top-k data elements in x groups of original data vectors.

A computer-implemented method for evaluating transactions against rules includes parsing sections of a document with conditional language and generating rules from the conditional language using a large language model. The rules are associated with corresponding sections of the document such that when a rule fires the rule is associated with the corresponding sections of the document. The rules are executed against transactions to discover exceptions. A narrative is generated to explain the exceptions to a user. The narrative includes the rules with the corresponding sections and an explanation.

In a first use case, a description of source code to be created is validated and used to form a prompt for a large language model (LLM). The prompt is provided to the LLM to generate an output. The output from the LLM is post-processed to generate the source code. In a second use case, a source code file is processed and provided, along with instructions, to an LLM. The LLM provides a list of the methods in the source code file. The LLM is requested to provide a unit test for each of the listed methods. The output from the LLM is post-processed to generate unit tests for the methods in the identified source code file. In a third use case, the LLM is used to generate unit tests for new methods added to the source code file after unit tests were generated.

The invention provides a real-time incremental RAG method and system based on a dual-tense knowledge graph, and belongs to the technical field of artificial intelligence and knowledge graphs. The method comprises the following steps: through dual-tense decoupling modeling of event effective time and system input time, constructing a versioned knowledge graph and establishing a tense index; efficient retrieval is carried out by adopting a time sequence pruning algorithm based on indexes, and dynamic expansion of a graph pattern is realized through a declarative compiler; realizing abstract-free high-precision result sorting by utilizing a multi-modal concurrent retrieval and attention fusion mechanism; incremental updating of the knowledge graph is realized through streaming data processing and a distributed engine; and closed-loop optimization is formed according to user feedback. The system effectively solves the problems that a traditional RAG scheme is high in data updating delay, tense information is lost, retrieval efficiency is low and expansibility is poor, tense query accuracy, retrieval efficiency and system throughput are remarkably improved, and meanwhile operation and maintenance complexity is reduced.

The invention discloses a method and system for packaging a webpage embedded sign language translation JS library, and belongs to the field of electrical digital data processing.The method comprises the steps that by constructing an ECS core architecture with perception feedback, a bidirectional data flow between modules is established to achieve dynamic collaboration of rendering and grammar; predictive streaming resource management is adopted, and resources are intelligently preloaded based on gesture sequence contexts; multi-instance physical isolation is realized by utilizing a sandboxed container and a ShadowDOM (Document Object Model); implementing multi-level adaptive rendering, and dynamically switching a rendering path and a frame rate according to equipment performance; and finally, shielding the bottom layer difference through cross-end unified rendering of the abstraction layer. According to the method, the problems of animation and semantic dislocation, resource loading conflict and poor equipment compatibility in a multi-user concurrent scene are effectively solved, and high-fidelity, low-delay and cross-end consistent experience of sign language translation animation is realized.

According to the unified access and control method and system of the intelligent robot with the body, the storage medium and the related equipment provided by the invention, automatic adaptation of native interfaces of different manufacturers and different types of robots is realized by introducing a standardized abstract interface and an adapter code generation mechanism driven by a large language model; and the development cost and period of butt joint of upper-layer applications and multiple robots are greatly reduced. Specifically, according to the unified access method, the native interface document of the target robot is converted into the adapter code conforming to the standardized abstract interface through the large language model, the digital robot is formed after loading and registration, and a unified control entry is provided for an upper layer application; therefore, the problems of fragmentization of robot interfaces and inconsistent action semantics in the prior art are effectively solved, and a solid technical support is provided for large-scale application of the intelligent robot with the body.

The invention belongs to the technical field of artificial intelligence and data analysis, and discloses a multi-agent data automatic analysis system based on a planning execution framework, which comprises a front-end interaction interface, a data abstract agent, a planning agent, a code execution agent, a report generation agent and an anti-review agent. The method has the beneficial effects that the intelligent automatic execution of the whole data analysis process is realized, and the analysis efficiency and the result reliability are remarkably improved; through multi-agent specialized division of labor and a'planning-execution 'framework, the capability limitation of a single agent in processing complex tasks is solved, and high-availability and high-quality data analysis service is provided for non-professional users.

The invention relates to a task processing method and device, equipment, a medium and a product. The method comprises the following steps: receiving a code change request, wherein the code change request carries code change information and a code change type; generating a task dependency graph of the code change request based on the code change information and the code change type; analyzing a dependency relationship among the tasks in the task dependency graph, and generating an execution strategy corresponding to each task; and for each task, determining a target agent according to an execution strategy corresponding to the task under the condition that the task is determined to meet an execution condition based on the execution strategy corresponding to the task, and executing the task by using the target agent. By adopting the method, the task processing efficiency can be improved through a dynamic task arrangement mechanism in a complex multi-task and multi-environment parallel construction scene.

The invention discloses a message processing method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of data processing, and the method comprises the steps: receiving an original message, and analyzing the original message to obtain an original message type and business data; retrieving in a knowledge base by taking the original message type as an index to obtain a processing rule document which comprises a data processing logic described by a natural language; generating a first cue word based on the processing rule document and the business data, inputting the first cue word into a large language model, and obtaining a data processing result output by the large language model; and triggering a workflow, and generating a response message based on the data processing result through the workflow. According to the invention, the message processing rule of the service layer and the decoupling of the application layer are realized, so that the development efficiency of the message processing system is improved.

The invention relates to the technical field of front-end development, and discloses a micro-front-end architecture alarm system integration method, device and equipment and a storage medium. Centralized configuration of an alarm system is achieved by creating a unified alarm packet, packaging error detection and uploading functions of a Sentry system and integrating the alarm packet in a micro-front-end base; meanwhile, error information is pushed to a user side in real time through the Sentry system, so that a development team can know and process problems in the first time. According to the invention, by creating and integrating the unified alarm packet, unified standard and process management is realized, chaos caused by differences of sub-applications is avoided, and the orderliness of overall system management is improved. The unified alarm packet facilitates centralized maintenance and upgrading of the alarm function, can be applied to the whole system only by modification at one place, does not need respective operation in each sub-application, and significantly reduces the maintenance workload and cost.

There are provided systems and methods for automated code generation using large language models (LLMs) for software platform integrations with computing services. An online transaction processor or other service provider may provide computing services and platforms to entities including merchants for electronic transaction processing and other account services. To provide for conde integrations of the computing services with software platforms of merchants, such as software systems for merchant websites and applications, the service provider may provide for an automated code generation tool that processes data for the software platform and the service to be integrated and provides recommendations and source code. An LLM may be prompted in parts to generate the code after analyzing legacy code from previous integrations and information for the merchant's software platform, and the merchant may be provided new code for testing and implementation.

Systems and methods are disclosed for automated generation, validation, and deployment of infrastructure-as-code (IaC) using a multi-agentic artificial intelligence / machine learning (AI / ML) architecture. An extraction agent parses multimodal artifacts (e.g., diagrams and / or configuration data) to derive or generate infrastructure set-up parameters. A coding agent generates IaC units based on the extracted parameters. A validation agent determines the syntactic and semantic compliance of the generated IaC, classifying the IaC as executable, non-executable, or identifying corrective actions. A deployment agent transmits executable IaC to target computing environments and manages automated provisioning of the IaC in the target environments. In cases of validation failure, error indicators are provided to a user (e.g., via an agentic chat bot) for clarification or correction, enabling iterative refinement.