Memelang: Token-Terse Query Language (memelang.net)

Memelang, a new AI-optimized query language, has been introduced to streamline the process of converting natural language queries into SQL statements for large language models (LLMs). This query language significantly minimizes token usage and model size, making it easier for developers to implement text-to-SQL functionalities. Memelang employs a novel axial grammar structure that efficiently organizes queries and reduces syntactic clutter while enhancing readability. With a special focus on whitespace significance, the design allows for concise expression of complex SQL operations through a compact syntax. The significance of Memelang lies in its potential to enhance AI applications that rely on database interactions by lowering computational costs and improving performance. As token count directly impacts the efficiency of LLMs, the adoption of this language could lead to faster query processing and reduced load on systems handling AI-driven applications. Additionally, the comprehensive set of example queries illustrates the language's versatility and adaptability for various use cases, from retrieving film data to sorting actor information, paving the way for more streamlined data handling in future AI projects.