Using Llama-cpp-Python grammars to generate JSON (til.simonwillison.net)

The recent update to llama.cpp has introduced a groundbreaking feature that allows users to control the output of language models using specific grammars. This development empowers developers to integrate custom code into the models' output generation process, ensuring the produced text adheres to predefined rules. By modifying the next-token selection logic, the model can only choose tokens that comply with the specified grammar, paving the way for more precise and context-aware outputs. This feature is particularly significant as it opens doors for creating tailored applications, such as a functional equivalent to OpenAI Functions, that can be run directly on personal devices using Llama 2. The ability to generate valid JSON outputs through the use of grammars enhances practical usability, ensuring data consistency without unnecessary filler text. Despite potential challenges regarding output completeness, tools like Grammar Builder by Intrinsic Labs and examples from the community are making it easier to define complex grammars for diverse data structures, thereby advancing the capabilities of AI-driven data generation.