Enhancing Closed Source Model APIs: Multi-Step Logic and Human Feedback

Closed source model APIs, like the OpenAI API, offer powerful capabilities but often lack advanced functionalities that can make them truly production-ready. Specifically, the inclusion of multi-step logic and per-hop human feedback mechanisms could significantly enhance their utility.

Multi-Step Dependency Logic with Verbosity and Logging

Multi-step logic allows a model to perform a sequence of logical steps or “hops” to reach a conclusion. Integrating multi-step logic with verbosity and logging would enable the model to break down tasks into smaller, manageable steps, and ensure accuracy and relevance at each stage through detailed output and recording of the process.

Per-Step Human Feedback Mechanism

Incorporating a per-step human feedback mechanism would enable users to provide feedback at each step of the model’s reasoning process. This granular feedback would facilitate continuous learning and refinement, aligning the model more closely with human expectations and reducing errors in complex tasks.

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