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LLMs will continue to change the way we build software systems. They are not only useful as coding assistants, providing snipets of code, explanations, and code transformations, but they can also help replace components that could only previously be achieved with rule-based systems. Whether LLMs are used as coding assistants or software components, reliability remains an important concern. LLMs have a textual interface and the structure of useful prompts is not captured formally. Programming frameworks do not enforce or validate such structures since they are not specified in a machine-consumable way. The purpose of the Prompt Declaration Language (PDL) is to allow developers to specify the structure of prompts and to enforce it, while providing a unified programming framework for composing LLMs with rule-based systems.
Features
- Ability to use any LLM locally or remotely via LiteLLM, including IBM's watsonx
- Ability to templatize not only prompts for one LLM call, but also composition of LLMs with tools (code and APIs). Templates can encompass tasks of larger granularity than a single LLM call
- Control structures: variable definitions and use, conditionals, loops, functions
- Ability to read from files and stdin, including JSON data
- Support for chat APIs and chat templates
- Type checking input and output of model calls
Project Samples
