For me, one of the most important parts of the spec is formulation of the DAG of tasks. Whether that be calling other LLMs or some retrieval mechanism.<p>What does everyone think about the pros/cons of a formal DAG specification vs using natural language? E.g. defining the DAG in yaml vs. something more natural language like writing logic and making calls in the prompt text?
Having a consistent, well-defined, coherent, human readable format for applications to interact with LLM's is quite critical. Having a way to specifiy data sources would be useful - RAG sources, S3 raw data files?. What about an evals section?
This spec is an attempt to will a sensible, infrastructure-independent, declarative abstraction for LLM application patterns into existence<p>I'd love critical feedback and for more folks to get involved