agentforge-architecture

An AI agent loop paradigm defines the execution flow for processing inputs and generating responses. You choose from eight paradigms like Async Generator or Reflection Chain based on your specific deployment form, such as interactive, daemon, or API service.

To design an agent loop for realtime voice, select the Realtime-Voice paradigm and ensure your provider abstraction supports content blocks for multi-modal inputs. This approach handles continuous audio streams and simultaneous multimodal data processing.

Choosing a language for production AI agents depends on your target deployment form, like API service or daemon. The architecture selection guide helps define a minimal provider interface in your chosen language to ensure robust multi-channel support.

To prevent infinite loops and manage token budgets in AI agents, you must plan guards against common pitfalls during architecture selection. Implementing loop detection and token budgeting ensures your agent operates within safe execution limits.

Yes, provider abstraction works with event-driven webhook agent loops by defining a minimal interface that standardizes content blocks for multi-modal inputs. This decouples your agent logic from specific providers, enabling flexible multi-channel deployments.