5 مستودعات
Creation of schema definitions using scripts to automate model generation and handle multi-tenancy.
Distinct from Programmatic Application Generators: Distinct from programmatic application generators: focuses on generating data models rather than desktop software.
Explore 5 awesome GitHub repositories matching data & databases · Programmatic Data Model Generation. Refine with filters or upvote what's useful.
Cube is a semantic data layer that provides a unified framework for defining business metrics, dimensions, and relationships across diverse data sources. By acting as a headless business intelligence engine, it transforms raw data into a governed model that can be queried via SQL, REST, and GraphQL interfaces. This architecture ensures consistent data definitions and logic across all downstream analytical applications and reporting tools. The platform distinguishes itself through its integrated conversational AI capabilities, which allow users to explore data using natural language. It orches
Automates model generation and multi-tenant configuration through programmatic scripts.
Outlines is a guided text generation framework and structured output engine for large language models. It enforces precise structural constraints on model output during the sampling process to ensure the generation of valid data. The framework ensures that model outputs strictly adhere to predefined data models, including JSON schemas, regular expressions, and formal grammars. This enables the conversion of natural language inputs into structured arguments for function calling and the generation of valid JSON for downstream processing. The system manages model orchestration through prompt te
Provides a framework that applies programmatic constraints during token sampling to ensure strictly valid, machine-readable output.
Outlines is a guided generation framework designed to enforce structural constraints on large language model output in real time. It serves as a structured output generator that ensures model responses adhere to predefined JSON schemas, regular expressions, or fixed sets of choices to produce predictable and parsable results. The project provides an interface for tool calling by extracting structured function parameters from natural language prompts for programmatic execution. It also includes a prompt templating engine that decouples prompt logic from application code through reusable templa
Provides a framework for applying programmatic constraints during token sampling to ensure predictable and parsable output.
Quicktype is a multi-language model generation engine that converts JSON and GraphQL schemas into type-safe models and serialization code. It functions as a JSON to type generator and a GraphQL type generator, producing strongly typed classes and interfaces across a wide array of target programming languages. The system derives formal schemas from sample data and transforms these definitions into native language objects. This enables the synchronization of shared data models across diverse tech stacks and the development of type-safe interfaces for consuming external APIs. The engine utilize
Provides a programmatic API to automate the generation of data models within applications.
Outlines is a library designed to ensure machine-readable output from generative models by applying programmatic constraints during the token sampling process. It functions as a toolkit for forcing large language models to generate text that strictly adheres to JSON schemas, regular expressions, and formal grammars, enabling the integration of model responses into existing software systems. The library distinguishes itself by integrating formal language rules directly into the sampling loop. It achieves this by converting regular expressions into deterministic finite automata and utilizing lo
Ensures machine-readable output from generative models by applying programmatic constraints during the token sampling process.