192 results about "Unparser" patented technology

The invention relates to a long-range task-oriented VLA model method for a humanoid robot, which comprises the following steps of: S01, analyzing a natural language instruction through a space-time semantic analyzer to generate an atomic operation sequence with a space-time dependency relationship; s02, maintaining a task state machine by using a dynamic memory network, and tracking the task execution progress in real time; s03, integrating vision, language and sensor data through a multi-modal perception fusion engine; s04, calling a predefined action primitive based on an adaptive execution system and optimizing a motion track; and S05, performing online updating and optimization on the model through a continuous learning mechanism. According to the method, a natural language instruction is analyzed into a structured task sequence with space-time dependence through a space-time semantic analyzer, an execution sequence and preconditions are defined, the semantic understanding ability and the structuring degree of task planning are improved, and task decomposition and replanning in a dynamic environment are supported; according to the method, the LSTM and the knowledge graph are combined, and the task state is maintained in real time.

The invention discloses a streaming knowledge injection and adversarial self-optimization large language model training method and system, and the method comprises the steps: collecting the newest knowledge of an authoritative information source in real time, converting the newest knowledge into a structured constraint rule through a semantic analyzer, and dynamically updating a knowledge base; based on the updated knowledge base, adopting a PPO algorithm to optimize a generator, actively constructing a high-risk adversarial sample, and forcing the model to expose security vulnerabilities; after user input and adversarial samples are input into the model, total loss is calculated through constraint detection, gradient updating is blocked if the total loss exceeds a threshold value, and otherwise, a multi-level safety verification stage is started; and finally, fusing a security verification result and the adversarial loss, updating a total loss function and cooperatively adjusting model parameters to form a continuous self-optimization training cycle. According to the method, compliance is guaranteed through streaming knowledge injection, vulnerabilities are actively mined in combination with adversarial training, verification precision is improved by means of multi-level detection and dynamic threshold adjustment, and safety and reliability of a large language model in a complex scene are enhanced.

The invention provides a private intelligent code collaborative optimization method and system based on graph retrieval, and relates to the technical field of software engineering intelligent auxiliary tools, and the method comprises the steps: obtaining a source code file and operation log data of a private project; the method comprises the following steps: performing syntax tree analysis on a source code file through a Tree-siter analyzer to generate a corresponding abstract syntax tree; constructing a code knowledge graph by analyzing a function call relationship, an inheritance relationship and a module dependency relationship; monitoring the change of a project file in the code knowledge graph through a code change event processor, and updating the code knowledge graph in real time when the file is changed; establishing an association relationship between the running log data and a corresponding function node in the code knowledge graph; the method comprises the following steps: analyzing a natural language problem of a developer into a Cypher query statement through an intelligent Agent; obtaining a query result from the graph database; and formatting the query result to generate a final result.

The invention provides a code quality adaptive evaluation and optimization method, system and device and a medium, and belongs to the technical field of computers. The method comprises the following steps: performing redundant information cleaning and standardization processing on an original code; selecting an adaptive parser to convert the processed code into an abstract syntax tree, and optimizing the abstract syntax tree; performing embedding processing on each node of the abstract syntax tree by using a pre-trained deep learning model to generate a node semantic vector, and performing aggregation, feature extraction and vector normalization operation to obtain a semantic vector representing code semantic features; extracting a dependency relationship from the abstract syntax tree to construct a program dependency graph, extracting node features by using a neural network model, and generating a dependency relationship analysis result; based on the semantic vector and the dependency analysis result, identifying a code potential problem by using an optimization algorithm and generating an optimization suggestion; codes are automatically modified according to optimization suggestions, the optimization effect is re-evaluated, and related models and algorithms are iteratively optimized according to feedback information.

The invention relates to the field of wisdom education, and particularly discloses a teaching strategy optimization model and grammar error early warning method based on data mining, and the method comprises the following steps: S1, obtaining original code data in a student code library in real time, and preprocessing the original code data to obtain a structured data matrix; s2, for the structured data matrix, generating a grammar parse tree through a grammar parser, positioning error nodes and extracting context features by using a node traversal algorithm, and constructing a single-error multi-dimensional feature vector; meanwhile, an error association rule base is constructed based on historical error data, a causal relationship across error types is identified, and dynamic knowledge graph data is formed. According to the technical scheme, association analysis and deep mining can be carried out on the multi-source learning data, dynamic solution suggestions for student individual errors or group generality errors are formed, and teachers are assisted to quickly adapt to dynamically changing learning requirements of the students.

The invention discloses an ANTLR4-based multi-manufacturer network equipment configuration analysis method and system, and the method comprises the steps: carrying out the preprocessing of a configuration file; based on a machine learning algorithm of multi-dimensional feature analysis, automatic identification of configuration file manufacturer types is realized; based on the identification result of the manufacturer type, loading an ANTLR4 grammar parser corresponding to the manufacturer type; a lexical analyzer in ANTLR4 realizes lexical analysis on the configuration file through lexical rule definition, a Token classification system and an optimized analysis algorithm; a syntactic analyzer in ANTLR4 constructs an abstract syntax tree according to a lexical analysis result and a syntactic rule defined based on a context-independent grammar; traversing the abstract syntax tree, and extracting key configuration information; and converting the specific configuration format of each manufacturer into a unified standard model. According to the method and the system, network equipment configuration files of different manufacturers can be automatically identified and analyzed, and key configuration information is extracted and converted into a unified model.

The invention discloses a lightweight cross-platform PLC (Programmable Logic Controller) multi-language code generation method, which relates to the field of industrial process control, and firstly provides a unified intermediate data model, and on the basis, a module for converting each PLC language into the unified intermediate data model is realized; on the basis of a standardized JSON data structure, a modularized unified intermediate language conversion chain is further supported, an analyzer and a generator communicate through a JSON interface, a cross-platform conversion path is supported, and unified intermediate language conversion from PLC to JSON to XML to ST to C is completed; the method comprises the following steps of: integrating an open source compiler and runtime, constructing an open and pluggable automatic execution framework, compiling a generated C code into a platform executable file by using an adaptive GCC tool chain aiming at different target platforms, and deploying a program generated by compiling to a soft PLC runtime system supporting multiple platforms. According to the method, a JSON intermediate data structure which is light in weight, unrelated to languages and uniform in structure and a matched conversion framework of the JSON intermediate data structure are constructed.

System, method and interface for generating data visualizations are provided. The system receives a user input to specify a natural language command directed to a data source. The system also generates a prompt for generating a data visualization based on relevant data fields and data values, rules that characterize the data visualization, and a context free grammar. The system also prompts a trained large language model using the prompt to generate a structured document following a domain-specific schema based on a shorthand notation. The system also uses a parser that uses the context free grammar to map the structured document to a visual specification. The visual specification specifies the data source, visual variables, and data fields from the data source. The system also generates and displaying a data visualization based on the visual specification, including displaying visual marks representing data, retrieved from the data source, for the data fields.

Provided are a method and device for parsing a database query statement, and a storage medium. A query statement for a database table to be queried is obtained, and an empty database table corresponding to the database table to be queried is created; the query statement is executed in the empty database table, and a parser installed in a database is called to parse the query statement to obtain a syntax tree, and an execution plan is generated based on the syntax tree for execution in the empty database table; and the syntax tree is obtained from the parser in an execution process of the query statement, and a syntax tree serialization result is generated and output as a parsing result of the query statement.

System and method for aspect-level sentiment classification. The system includes a computing device, the computing device has a processer and a storage device storing computer executable code. The computer executable code is configured to: receive an aspect term-sentence pair; embed the aspect term-sentence pair; parse the sentence using multiple parsers to obtain dependency trees, and perform edge union to obtain a merged graph; combine the embedding and the merged graph to obtain a relation graph; perform a relation graph neural network on the relation graph; extract hidden representation of the aspect term from updated relation neural network; and classify the aspect term based on the extracted representation to obtain a predicted classification label of the aspect term. During training, the computer executable code is further configured to calculate a loss function based on the predicted label and the ground truth label, and adjust parameters of models.

The invention provides a bidding and tendering field information extraction method and device, relates to the field of information processing, and solves the technical problem of insufficient bidding and tendering multi-modal data processing precision and association analysis in the prior art. The method comprises the steps of obtaining bidding and tendering data information including bidding and tendering text data, bidding and tendering table data and bidding and tendering picture data; extracting text semantic features of the bidding and tendering text data through a Transform model; analyzing the bidding and tendering table data through a row and column structure analyzer, and encoding an analysis result into a structured feature reflecting semantic dependency of a cell; performing convolutional coding on the bidding and tendering picture data through a ResNet model, and extracting visual features; performing cross-modal alignment on the semantic features, the visual features and the structured features of the text based on an attention mechanism, and fusing the features in a feature space to obtain fused features; and inputting the fusion features into a Qwen model, and outputting target field information. The method and the device are used in the bidding field information extraction process.

The invention relates to the technical field of knowledge graph generation, in particular to a dynamic and static dual-state knowledge graph generation system, which is characterized in that an object is used for replacing an entity as a node, a traditional triple is upgraded into a tetrad containing a timestamp, and a state tetrad is newly added; quadruple elements (including timestamp mining) are extracted through a semantic parser, a parameter space is maintained, a construction engine constructs a quadruple, stores the quadruple into a graph database and executes four-item rationality detection, a vacancy filling engine calls a fine-tuned large language model, and an intelligent agent screens high-credibility answers to complement knowledge. Traditional static representation limitation is broken through, object dynamic description is realized, accurate and complete atlas is guaranteed, and an important logic basis is provided for next-generation artificial intelligence interpretable reasoning.

The embodiment of the invention provides a form generation method and related equipment, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining form item configuration from a form item knowledge base; acquiring a natural language input by a user; generating a current question word based on form item configuration and a natural language; inputting the current question word into the large language model to obtain a form configuration JSON (JavaScript Object Notation) content; analyzing the form configuration JSON content through a JSON analyzer to obtain a current front-end page; in response to the first instruction, a current front-end page is displayed in the designer. According to the embodiment of the invention, the visual form configuration can be generated and previewed through the natural language, the user operation is reduced, the development threshold is lowered, and the development efficiency and the user experience are improved.

The invention discloses a warehouse level code translation method and device based on a large model, and is used for solving the technical problem that the existing warehouse level code translation method only relates to a function translation pair, so that a code translation task in a warehouse level context is poor in performance. The method comprises the steps that a tree-shaped analyzer is utilized, a large model is preset, and a target language code sample self-evolution knowledge base, a dependent use example self-evolution knowledge base and a successful translation function pair self-evolution knowledge base are constructed according to an obtained open source project, a to-be-translated warehouse and a plurality of historical successful translation function pairs; and outputting the target triple translation knowledge corresponding to each to-be-translated function, and outputting a warehouse level code translation result in combination with the obtained implementation code corresponding to each to-be-translated function and the generated warehouse architecture.

The invention discloses a data analysis method and device based on a grammar analysis generator, and relates to the technical field of data processing. Obtaining byte stream data to be analyzed in the task scene; creating a CSG grammar file according to a grammar specification of the grammar analysis generator, and defining a context-related grammar rule of a protocol; processing the CSG grammar file by using a grammar analysis generator, generating abstract syntax tree information related to the CSG grammar file, and generating a Java parser based on the abstract syntax tree information; on the basis of the generated Java parser, a CsgVisor class is self-defined, a CSG grammar file is parsed, and a Protocol protocol object is constructed; and creating a CSGPVisor accessor and a CSGPParser parser, and analyzing the byte stream data in combination with a Protocol protocol object and a preset analysis rule.

The invention provides a domestic database compatibility comparison evaluation and migration method and system and a medium, and belongs to the technical field of database migration. The method comprises the following steps: acquiring a creation statement of each database object in a pre-connected target source database; and based on a preset grammar parser and a preset grammar feature library, analyzing each creation statement, generating an abstract grammar tree and traversing the abstract grammar tree to determine grammar features corresponding to each database object, and generating a mapping list between each database object and each grammar feature. And comparing the mapping list with a plurality of preset grammar feature templates of the domestic databases, generating compatibility evaluation results corresponding to the domestic databases according to comparison results, and determining corresponding migration working hours and an automatic rewriting grammar set according to the compatibility evaluation results. And based on each compatibility evaluation result, each migration man-hour and the automatic rewriting grammar set, generating a multi-dimensional comparison view corresponding to each domestic database, and sending the multi-dimensional comparison view to an evaluation migration user terminal.

The invention relates to an NL2SQL semantic parsing method and device, and the method comprises the steps: inputting a natural language query statement into a business data model, and obtaining a context vector; fusing the context vector with the natural language query statement to obtain a joint semantic vector; decoding the joint semantic vector and the structured feature based on a constraint decoding strategy to obtain an initial SQL statement, and verifying the initial SQL statement through a grammar parser to obtain a target SQL statement; the context vector of the natural language query statement can be more comprehensively captured through the business data model, and the optimal joint semantic modeling is realized through the context vector and the natural language query statement, so that the problems of information bias and redundancy caused by fixed weight or simple splicing are effectively solved; the context features, the structured features of the database and the constraint decoding strategy are dynamically fused, so that complex service logic and anaphora and omission phenomena in the long dialogue context can be better understood.

The application provides a multi-source data automatic acquisition method based on a large language model, which comprises the following steps: analyzing the feature distribution of historical acquisition data, combining the state of the current data source, and dynamically generating an optimal acquisition strategy; scheduling the acquisition task in real time to obtain a dynamically scheduled data stream; performing real-time anomaly detection and adaptive compensation on the dynamically scheduled data stream to obtain a self-fault-tolerant data stream; analyzing the entity association and business logic of the self-fault-tolerant data stream, predicting potential data demand points; automatically expanding the data acquisition range to obtain knowledge-enhanced data assets; identifying the protocol characteristics of the data transmission stream of the data assets, parsing the data based on a protocol characteristic mapping parser to obtain protocol-independent standardized data; performing semantic noise filtering and cross-modal cleaning to obtain semantic pure data. In the application, the defects that the existing multi-source data acquisition technology cannot perform protocol adaptation and adaptive strategy optimization are overcome.

The invention relates to the technical field of SQL (Structured Query Language) grammar conversion, and provides a general SQL grammar conversion method, device and equipment and a medium, the method comprises the following steps: performing lexical analysis on a source end SQL statement to obtain a lexical unit set; based on the type features and semantic attributes of the lexical unit set, determining parser combiners, and constructing a specific parser by infinitely combining the parser combiners; the specific resolver is used for conducting grammar analysis on the lexical unit set, a general abstract syntax tree is constructed through a mapping assembly, and nodes of the general abstract syntax tree correspond to the specific resolver one to one; and traversing the general abstract syntax tree, and generating a target end SQL statement according to an SQL syntax rule of a target end database. Through the technical scheme, any complex source end SQL can be accurately converted into the target end SQL.

The invention provides an autonomous controllable database intelligent adaptation method and system oriented to localization ecology, and belongs to the technical field of database middleware and cloud native resource management. When the request label is missing or wrong, JDBC metadata, a system function return value and system table structure features are collected through detection connection to generate database fingerprints, and the database type and version are recognized in the localized feature library. For an SQL execution request, parsing the SQL into an abstract syntax tree based on a unified syntax parser, rewriting nodes according to a dialect rule base to generate a target dialect SQL, and performing paging, identification column generation, identifier reference, transaction-related semantic verification, execution plan optimization and dynamic routing execution; and thermally loading from the plug-in warehouse when the driver is missing. And for the resource opening request, calling a Kubernetes Operator to automatically create a domestic database instance, and returning connection information. The system integrates a national cryptographic algorithm and behavior auditing, and realizes connection information protection and abnormal SQL detection.

The invention belongs to the technical field of software supply chain security, and particularly relates to a patch semantic driven vulnerability rule generation method. The method is based on a large language model and an intermediate representation technology; comprising the following steps: a patch semantic enhancement stage: locating a vulnerability key code from a patch and supplementing a vulnerability code context; in the vulnerability cause intermediate representation generation stage, patch differences and vulnerability rules are decoupled, and the cross-branch and cross-component generalization ability of rule generation is improved; the feedback-based rule generation, verification and self-correction stage is used for improving the vulnerability rule generation and verification efficiency, and comprises the steps of constructing a syntax tree-based analyzer for analyzing an intermediate representation to a vulnerability rule, and defining a mapping relation from a quaternary verification result of the rule to a model feedback content, and the semantic accuracy of the rule is ensured and the over-fitting risk is reduced. The method can be widely applied to patch existence detection, vulnerability influence version detection and homologous vulnerability detection, and an efficient dynamic rule generation solution is provided for software supply chain security governance.

The invention provides a multi-language-oriented source code automatic verification method and system, and relates to the technical field of computers.The method comprises the steps that multi-language source codes are obtained; compiling the multi-language source code through an LLVM compiler to generate an intermediate file; the intermediate file is optimized; analyzing the optimized intermediate file through an IR analyzer to generate a symbolic execution model; performing simulation execution operation on the symbolic execution model; and performing security verification on the symbolic execution model after simulation execution operation to obtain a verification report. Unified verification of multi-language source codes can be achieved, the verification environment building and development cost is greatly reduced, and the overall verification efficiency is improved; and the analysis capability of the intermediate file can be enhanced, the logic constraint relationship in the code can be accurately captured, the comprehensiveness and reliability of the verification work can be practically guaranteed, and diversified software security verification requirements can be met.

The invention relates to the technical field of financial science and technology and artificial intelligence cross fusion, in particular to a financial format file processing method and device based on a large language model, and the method comprises the steps: receiving a file uploading or generating instruction, responding to the uploading instruction, carrying out format recognition and integrity verification, storing, and generating a ready signal; and in response to the generation instruction, constructing a cue word containing financial scene parameters, calling a large language model to generate content and generating a signal. And extracting a text through an adaptive analyzer based on the signal, filtering redundancy, converting into a standard JSON format, and driving a large language model to proofreading in combination with a special prompt word in the financial field to generate a compliant text. And after converting into a structured HTML intermediate representation and checking, analyzing an HTML matching template, filling placeholders, mapping into a Word format of a financial specification, and outputting a file which conforms to the business specification through special checking. Full-process automation is achieved, efficiency is improved, compliance risks are reduced, and the method is suitable for multiple scenes.

The invention relates to the technical field of code generation, in particular to a communication code generation method based on an XML configuration file and a storage medium, and aims to improve the code development efficiency. The communication code generation method based on the XML configuration file comprises the steps that the XML configuration file is converted into a DOM tree with a hierarchical relation through an XML parser; traversing nodes of the DOM tree, and converting the DOM tree into an abstract syntax tree; based on the abstract syntax tree, statically checking register address conflicts, reference validity, data type compatibility and protocol constraints; traversing the abstract syntax tree to generate a Modbus communication code; and outputting the Modbus communication code as a structured source code file according to the grammar rule of the target language. According to the method, the manual coding workload is greatly reduced, and the development efficiency is improved.

A system and method for a protocol parser that has native support for parsing TLVs and flag-fields and allow users to code in a language convenient to them and leverage standard tool chains and tools. The same parser source can be compiled to arbitrary software and hardware targets without code change and provide the highest performance possible given its capabilities.

The invention discloses an expression language analysis method and device and a storage medium, and relates to the technical field of electronic digital data processing.The expression language analysis method comprises the steps that in response to an expression text input by a user in an editor, an analyzer integrated to a current program is called; analyzing an abstract syntax tree corresponding to the expression text based on the analyzer; and in response to function operations for the abstract syntax tree, outputting a function execution result at the editor, the function operations including syntax highlighting, code checking, automatic completion and expression calculation. According to the method and the device, the technical problem that expression languages and analysis tools in related technologies are closed sources and cannot be compatible with own systems is solved, and the technical effect of automatically generating the analyzer to analyze the expressions of the currently defined grammar rules is achieved.

The invention discloses a large language model agent system and method and related equipment. The large language model agent system comprises an input analyzer module, a strategy generation module, an execution controller module, a task result evaluation module, an reflection module and a strategy rewriting module, and a self-adaptive optimization closed loop for task execution is formed through the reflection module and the strategy rewriting module. Wherein the reflection module can generate a report containing failure reasons, and the problem of failure diagnosis is solved; the strategy rewriting module optimizes a plan according to a report, adjusts tool calling, and realizes self-learning and strategy reconstruction; the closed-loop design forms a complete cognitive process, and an input analyzer guarantees the stability of prompt. According to the system, the task completion rate, the execution stability and the scene adaptability are remarkably improved, the robustness and the error tolerance in a multi-step complex task are particularly enhanced, and the key blank of an existing language model agent system in the aspects of self-reflection and self-optimization is filled.

The invention relates to the technical field of business process modeling, in particular to a meta-model-driven interactive business process intelligent modeling method and system. The method comprises the following steps: constructing a meta-model framework containing core elements such as activities, events and gateways, and establishing a meta-model constraint rule base to define a structure legality rule of a BPMN2.0 specification; based on a domain ontology Schema and the domain exclusive large language model after instruction fine tuning, extracting a business entity and a process relationship thereof from the unstructured text; carrying out information integrity verification and logic consistency detection on the extracted BPMN elements by utilizing a constraint satisfaction algorithm and Petri net reachability analysis; displaying a difference label of the process sketch through an interactive verification interface, and realizing semantic correction and model iteration of a user on the process elements based on a natural language feedback mechanism; an XML code is generated by adopting a template-driven code generation strategy, and a flow chart is generated through a BPMN parser. According to the method, the business process modeling efficiency can be remarkably improved, and the manual intervention proportion in the modeling process is reduced.

The invention provides a smart home equipment control method and system. The method comprises the following steps: receiving a natural language instruction input by a user; a natural language processing module is called to analyze the natural language instruction, context information of a current dialogue is fused in the analysis process, and the context information comprises historical dialogue records and equipment state history; based on the analysis result, a control instruction is generated through an equipment control rule analyzer, and the step of generating the control instruction comprises the substeps that fuzzy parameters are quantized, and the current state of the target equipment is inquired to execute safety authentication; the control instruction is adapted to a private communication protocol corresponding to a target equipment brand through a standardized interface protocol layer, and the adapted control instruction is issued to the target equipment; and receiving an execution result fed back by the target device to update the context information, and providing a response to the user, so as to solve the problem of poor compatibility and cooperative work capability between the smart home devices.

The invention discloses a dynamic reasoning method and system for industrial design multi-modal constraint verification. The method comprises the steps that an input geometric image and a problem text are converted into formalized language description of the same symbology system through an analyzer; inputting the formalized language description into a symbol solver, and solving the symbolized representation of the geometric problem by introducing a named relationship and a state machine; under the condition that input questions are given, similar questions with question solving theorem guidance are found out, and contents and thinking directions of the similar questions serve as a part of cue words Prompt to participate in construction of the thinking tree; a geometric reasoning normal form of a tree-shaped structure is adopted according to the thinking tree, proposal and evaluation are conducted in combination with a large language model, whether a stopping condition is met or not and whether searching is continued or not are judged through a controller, and the optimal problem solving path and the problem solving process are determined. The method can fully stimulate the capability of a large model in the field of plane geometry problems, effectively fuses geometric information and text logic, and achieves a good question and answer effect.