simplellmfunc-developer

To develop a new runtime primitive, author and register the primitive pack following established best practices and validated contracts. This ensures your LLM agent framework extension maintains function-first design and integrates safely with existing ReAct runtime loops.

A ReAct runtime loop executes by processing event streams while maintaining function-first design principles. This framework architecture ensures that decorators and provider adapters interact predictably during agent reasoning and action execution cycles.

Yes, you need pytest and poetry to maintain this Python LLM agent framework. These dependencies support the TDD-based validation workflows required for safely updating core decorators, runtime primitives, and provider adapters.

The best way to add a provider adapter is to follow the established TDD loop and architectural conventions. This structured approach ensures your modifications maintain the integrity of the prompt-as-code principles and function-first design.

Prompt-as-code principles are used to ensure that prompt logic is treated as executable code within the LLM agent framework. This design constraint maintains architectural integrity when modifying runtime primitives and ReAct event streams.

Modifying decorators in a function-first LLM framework is limited by the need to maintain architectural integrity and validated contracts. Deviating from established TDD-based validation workflows risks breaking the ReAct runtime loop and primitive systems.