Fix typo (#209)

Snip'p'ets

Signed-off-by: Sudarshan R Thitte <[email protected]>

Author: trsudarshan

docs/README.md

@@ -5,7 +5,7 @@ hide:
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 # Prompt Declaration Language
 
-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. 
+LLMs will continue to change the way we build software systems. They are not only useful as coding assistants, providing snippets 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. 
 
 PDL is based on the premise that interactions between users, LLMs and rule-based systems form a *document*. Consider for example the interactions between a user and a chatbot. At each interaction, the exchanges form a document that gets longer and longer. Similarly, chaining models together or using tools for specific tasks result in outputs that together form a document. PDL allows users to specify the shape of data in such documents in a declarative way (in YAML), and is agnostic of any programming language. Because of its document-oriented nature, it can be used to easily express a variety of data generation tasks (inference, data synthesis, data generation for model training, etc...).