26 Repos
Tools that produce OpenAPI/Swagger specification documents by scanning annotated source code.
Distinct from Source Code Generators: Distinct from Source Code Generators: generates API specifications, not general source code.
Explore 26 awesome GitHub repositories matching programming languages & runtimes · Specification from Code Generators. Refine with filters or upvote what's useful.
Qwen2.5-Coder is a code-centric large language model designed to generate, complete, and analyze source code. It serves as a polyglot programming model capable of producing functional code across hundreds of different programming languages. The model is optimized for reasoning over extensive software repositories, utilizing a context window that supports up to one million tokens. It also functions as an agentic coding framework, executing multi-step workflows and browser tasks through specialized function call formats. Its capabilities include large-scale codebase analysis, intelligent parti
Produces functional source code across hundreds of different programming languages to accelerate development.
Code Llama is a large language model based on Llama 2 trained specifically for programming tasks and software development. It provides specialized model types optimized for general code generation, instruction following, and context-aware infilling. The project includes an instruction-tuned programming model for executing technical tasks via natural language prompts and a code infilling model that predicts missing sections based on surrounding source context. A large context code model is also provided to analyze extensive blocks of source code for improved coherence. The system covers capab
Translates natural-language problem descriptions and technical instructions into executable source code.
This project is an AI software engineering tool and framework for building autonomous coding agents. It provides a system for automating program synthesis and bug fixing by integrating large language models with codebase analysis and iterative refinement loops. The framework features an agentic development server that exposes task execution interfaces to remote agents through a structured protocol. This allows for the remote execution of development tasks and the embedding of autonomous program synthesis capabilities into external software projects. The toolset covers AI-driven project scaff
Transforms natural language requirements into executable source files and directory structures.
go-swagger is a toolkit for working with Swagger/OpenAPI 2.0 specifications in Go. It generates server, client, and CLI code from a specification document, and can also produce a specification by scanning annotated Go source code. The project includes a static validation engine that checks documents against the schema and project-specific rules, and a specification transformation pipeline that resolves, flattens, and merges documents. The toolkit generates both client and server code from the same specification, ensuring consistency in request and response handling. It also produces a command
Produces Swagger/OpenAPI 2.0 specifications by scanning annotated Go source code.
Gop is a general purpose programming language and cross-language compiler designed to unify assets and libraries from multiple programming ecosystems into a single shared environment. It translates high-level source code into executable binaries using specialized backends tailored for different target environments. The project features a system for natural language programming, transforming human-readable instructions written in plain English into executable code. It also functions as a cross-language tool that imports and integrates external libraries and assets from different language ecosy
Transforms human-readable English instructions into executable source code through a specialized translation layer.
Evolver is a self-evolving AI agent framework that uses gene expression programming to autonomously improve agent behaviors through a continuous five-step loop of scanning, selecting, mutating, validating, and solidifying. It functions as an auditable evolution system that records every mutation and selection step, and can translate natural-language problems into executable Python code for automated grading and evaluation. The framework distinguishes itself through a distributed architecture that enables multiple agents to collaborate and share learned experiences across a network. It operate
Translates natural-language problems into executable Python code with automated grading and error repair.
curlconverter is a browser-based tool and JavaScript library that transforms curl commands into equivalent source code across more than 30 programming languages and HTTP client libraries. It parses curl command arguments into an abstract syntax tree and generates idiomatic code by applying per-language templates, making it a curl command transpiler rather than a simple converter. The tool operates entirely client-side without any server round-trips, ensuring all conversion happens privately in the browser without transmitting data externally. It can also function as a drop-in curl replacement
Applies per-language templates to translate parsed curl options into idiomatic HTTP client code.
TrumpScript is a Python-based domain specific language and compiler extension that wraps the Python runtime to enforce custom grammar and vocabulary rules. It transforms a specialized, case-insensitive vocabulary and natural speech patterns into executable Python instructions. The implementation distinguishes itself through strict constraints on source code, including a variable name system that restricts identifiers to a predefined whitelist and a numeric parser that rejects any integer not exceeding one million. It further utilizes a token-filtering preprocessor to remove filler words and n
Discards unnecessary words from the source code to make it resemble natural human speech.
CodeGeeX2 is a large language model and AI programming assistant designed to generate, translate, and document source code across multiple programming languages. It functions as a multilingual code model that converts natural language prompts into executable code and technical documentation. The project provides a self-hosted AI inference endpoint, allowing the model to be exposed as a web-accessible service. This enables external development tools to integrate automated programming tasks via network calls. Its core capabilities cover multilingual code generation, automated source code docum
Translates natural-language prompts into executable source code and completes existing code snippets.
swagger-core is a set of libraries for parsing, generating, and serializing OpenAPI specifications to automate REST API documentation. It provides tools to read, validate, and transform JSON or YAML specifications into programmable objects, as well as a generator that scans source code and annotations to create formal technical descriptions of an API. The project enables bi-directional specification serialization, allowing in-memory API definitions to be converted between native language objects and structured files. It uses a plugin-based scanning mechanism and annotation-driven generation t
Produces OpenAPI/Swagger specification documents by scanning annotated source code.
sqlboiler is a database-first ORM generator for Go that analyzes an existing database schema to produce strongly typed structures and query helpers. It functions as a schema-driven code generator, transforming database tables and relationships into executable Go source code. The project distinguishes itself through a type-safe query builder that uses chainable modifiers to construct SQL statements, eliminating the need for raw string concatenation. It utilizes customizable text templates to generate source code, allowing for the aliasing of schema entities and the creation of custom templates
Uses customizable text templates to transform database metadata into executable Go source code.
Llamacoder is an AI-powered web application generator that transforms natural language prompts into functional application prototypes. It uses large language models to synthesize code and layouts, enabling the creation of small-scale software and interactive user interfaces from text descriptions. The project specifically leverages the Llama 3.1 405B model to produce executable React components. It provides a self-hosted environment for generating and previewing interactive code artifacts, featuring a real-time preview loop and sandboxed component rendering to safely display generated interfa
Translates natural-language prompts into executable frontend source code using a large language model.
DevOpsGPT ist eine LLM-gesteuerte DevOps-Automatisierungsplattform und ein KI-Softwareentwicklungs-Agent. Er wandelt natürlichsprachliche Anforderungen in funktionalen Code und automatisierte Bereitstellungen um, indem er Codebasis-Analysen, Code-Generierung und Delivery-Pipelines koordiniert. Das System verfügt über eine automatisierte Code-Generierungs-Engine und eine aufgabenbasierte Zerlegungs-Engine, die Projektstrukturen analysieren, um kontextbewusste Code-Erweiterungen zu erstellen. Es nutzt ein steckbares Modell-Integrationssystem, um sich für domänenspezifische Entwicklungsaufgaben mit privaten oder professionellen Sprachmodell-Bereitstellungen zu verbinden. Die Plattform verwaltet den gesamten Software-Delivery-Lebenszyklus durch einen CI/CD-Pipeline-Orchestrator, der Codesynthese mit automatisierten Test- und Bereitstellungstools verknüpft. Dies umfasst Funktionen für Software-Version-Releases und die Integration mit verschiedenen externen DevOps-Plattformen.
Translates natural-language problem descriptions into executable source code for automated evaluation.
Hygen is a code generator CLI and interactive template engine that scaffolds new files and injects code into existing ones using project-local templates. It operates as a Node.js code generator library that can be embedded inside custom binaries for tailored workflows, and also functions as a project scaffolding tool for bootstrapping new projects or folders from remote template repositories. The tool discovers templates by scanning a project's _templates directory at runtime, mapping folder and file names directly to generator commands and actions. It collects user input through interactiv
Scaffolding new files and injecting code into existing ones using project-local templates and a fast command-line interface.
Dieses Projekt bietet Methoden und Anleitungen für strukturiertes Prompt Engineering, generative Workflows und spezialisierte Strategien zur Bildgenerierung. Es dient als Framework zur Optimierung von Eingaben für Large Language Models (LLMs) in den Bereichen Programmierung, Textverarbeitung und Analyse sowie als Bibliothek für Techniken zur Steuerung von Diffusionsmodellen. Das Projekt zeichnet sich durch ein KI-gestütztes Software-Design-Framework aus, das Geschäftsanforderungen mittels Domain-Driven Prompting in technische Architekturen und Code übersetzt. Zudem implementiert es generative KI-Workflow-Muster, die sequentielle Prompt-Pipelines und kognitive Frameworks nutzen, um vorhersehbare Modellausgaben zu gewährleisten. Das Funktionsspektrum umfasst Softwarearchitektur durch Domain-Driven API-Modellierung und die Generierung domänenspezifischer Sprachen (DSLs). Es erstreckt sich zudem auf die Bildgenerierung, einschließlich struktureller Bildbindung, personalisiertem Modelltraining und iterativer Inpainting-Verfeinerung zur Korrektur visueller Artefakte. Das Projekt ist als eine Reihe von Jupyter Notebooks implementiert.
Defines formal syntax rules using natural language prompts to automate the creation of domain-specific languages.
Qodo Cover ist eine Engineering-Governance-Plattform und ein KI-gestützter Assistent für automatisierte Code-Reviews und Unit-Test-Generierung. Es nutzt einen Wissensgraphen auf Basis des abstrakten Syntaxbaums (AST), um Abhängigkeiten und architektonische Beziehungen abzubilden, wodurch Pull Requests analysiert und organisatorische Coding-Standards durchgesetzt werden können. Das System zeichnet sich durch eine Multi-Agenten-Analyse-Pipeline aus, die architektonische Schlussfolgerungen zieht und Fehler identifiziert, die über das unmittelbare Diff hinausgehen. Es verfügt über einen Model-Context-Protocol-Server, um Codebase-Intelligenz für externe Tools verfügbar zu machen, und kann Durchsetzungsregeln automatisch weiterentwickeln, indem es aus historischen Pull-Request-Entscheidungen lernt. Die Plattform bietet umfassende Funktionen für das Wissensmanagement der Codebase, einschließlich Deep-Research-Ausführung, semantischer Abfragen und System-Abhängigkeits-Mapping. Sie enthält zudem Werkzeuge zur iterativen Unit-Test-Generierung zur Erhöhung der Code-Abdeckung sowie automatisierte Remediation zur direkten Anwendung von Fixes auf Pull Requests. Bereitstellungsoptionen umfassen Multi-Tenant-SaaS, Single-Tenant oder vollständig On-Premises-Installationen.
Transforms recurring patterns in pull request comments into enforceable organizational coding standards.
Vision-agent is an AI system and visual data extraction framework that translates natural language prompts into runnable Python scripts for analyzing images and video. It functions as a multi-model vision orchestrator, using large language models to plan and generate executable code for tasks such as object detection, counting, and video tracking. The system employs a plan-and-execute cycle that iteratively generates and tests code, using an error-correction loop to refine the implementation until a solution is validated. It is configuration-driven, allowing the underlying language model back
Translates natural language prompts and visual data into executable Python scripts for visual analysis.
CodeGen is a trained large language model and program synthesis model designed to generate functional source code. It utilizes a neural network architecture to synthesize executable code from natural language descriptions or partial code snippets. The model enables automated program synthesis and AI-assisted coding by predicting and filling in missing sections of code within a program. It transforms natural language descriptions into functional programming logic to automate the creation of boilerplate and logic.
Performs automated program synthesis to generate complete functional code from natural language prompts.
Integuru ist ein System aus KI-gesteuerten Agenten und Frameworks zur Dokumentation undokumentierter APIs und zur Umwandlung von Netzwerkverkehr in Automatisierungsskripte. Es fungiert als Headless-API-Automatisierungsframework, das browserbasierte Tools durch direkte HTTP-Anfragen ersetzt, um Durchsatz und Zuverlässigkeit zu erhöhen. Das Projekt umfasst einen LLM-basierten Reverse-Engineering-Agenten, der Netzwerkverkehr analysiert, um interne APIs zu entdecken, sowie eine Engine für die Integration natürlicher Sprache, die Textbeschreibungen von Workflows in Sequenzen gültiger API-Aufrufe umwandelt. Es enthält Tools zum Extrahieren von Request- und Response-Formaten zur Erstellung präziser technischer Spezifikationen sowie zur Konvertierung erfasster Session-Cookies in produktionsreife Automatisierungsskripte. Das Framework deckt ein breites Spektrum an Funktionen ab, darunter Schema-Engineering, Request-Dependency-Graphing und zustandsbasierte Logik-Mapping zur Handhabung komplexer Anwendungsabläufe. Es bietet zudem automatisiertes Authentifizierungsmanagement für Session-Cookies und Multi-Faktor-Verifizierung, um den Zugriff auf geschützte Portale aufrechtzuerhalten.
Converting plain text descriptions of desired actions into production-ready HTTP requests and automation scripts.
Briefer ist eine interaktive Daten-Notebook-Plattform und ein Business-Intelligence-Dashboard-Tool, das für kollaborative Datenanalyse und Berichterstattung verwendet wird. Es bietet eine containerisierte Umgebung zum Erstellen von Berichten, die SQL, Python und Markdown mit nativen Visualisierungen kombinieren. Die Plattform verfügt über einen integrierten Code-Assistenten, der Large Language Models verwendet, um SQL- und Python-Snippets aus natürlichsprachlichen Prompts zu generieren. Sie ist als Kubernetes-Datenanwendung konzipiert und wird über Helm-Charts bereitgestellt, um isolierte Rechenumgebungen zu verwalten und separate Ressourcen pro Seite durch Pod-basierte Isolierung sicherzustellen. Das System deckt ein breites Spektrum an Funktionen ab, einschließlich externer Datenbankkonnektivität, Echtzeit-Co-Editing und automatisierter Berichtszustellung via Scheduling. Es integriert sich mit OpenID Connect für die Identitätsbereitstellung und bietet rollenbasierte Zugriffskontrolle, sicheres Credential-Management und ergebnisbasiertes Query-Caching. Die Anwendung wird über Kubernetes-Cluster mittels verwalteter Helm-Charts bereitgestellt und skaliert.
Includes an integrated code assistant that generates SQL and Python snippets from natural language prompts.