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Systems that enable autonomous agents to iteratively evaluate and refine their own reasoning processes.
Distinguishing note: Focuses on the self-correction loop architecture rather than general model inference.
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This project is an agentic workflow orchestrator designed for building and deploying autonomous systems that perform multi-step reasoning. It functions as a tool-augmented engine, enabling developers to chain model calls with external function execution to complete complex, user-defined tasks. By integrating large language models with persistent memory and stateful logic, the framework supports the creation of intelligent applications capable of independent operation. The platform distinguishes itself through graph-based state orchestration, which allows developers to define logic steps and t
Implements autonomous reflection loops to iteratively refine reasoning and improve response accuracy.