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A library for helping developers craft prompts for Large Language Models
The main features of microsoft/prompt-engine are: Prompt Optimization Frameworks.
Open-source alternatives to microsoft/prompt-engine include: junh0328/prepare_frontend_interview — This project is a comprehensive technical interview study resource designed to help developers prepare for engineering… bigscience-workshop/promptsource — Toolkit for creating, sharing and using natural language prompts. eth-sri/lmql — LMQL is a programming language and probabilistic interface that blends algorithmic logic with stochastic text… ianarawjo/chainforge — An open-source visual programming environment for battle-testing prompts to LLMs. krrishdholakia/betterprompt. langgpt/langgpt.
This project is a comprehensive technical interview study resource designed to help developers prepare for engineering job assessments. It functions as a structured guide that curates essential computer science fundamentals, web development standards, and programming language concepts into a format optimized for professional evaluation. The repository distinguishes itself by providing strategic guidance on architectural decision-making and professional communication. Beyond simple question-and-answer pairs, it offers frameworks for articulating experience during interviews and suggests profes
LMQL is a programming language and probabilistic interface that blends algorithmic logic with stochastic text generation. It functions as a constraint-guided prompting framework and structured output generator, allowing users to force model responses to adhere to strict formatting and data types. The system distinguishes itself as an inference optimizer that increases token throughput and reduces latency. This is achieved through specialized execution strategies, including tree-based prompt caching and asynchronous batch processing. The project covers a broad range of generation control capa
An open-source visual programming environment for battle-testing prompts to LLMs.
Toolkit for creating, sharing and using natural language prompts.