This article explains the Codex agent loop, which is the mechanism that allows the Codex CLI to interact with users and perform software tasks. It details how user input is processed, how queries are sent to the model, and how responses are generated, including tool calls for executing commands.

This article details how to build a Docker-based machine learning inference service that includes automated security scanning, testing, and deployment. It walks through the architecture, CI/CD pipeline, and real-world usage of a Flask API serving a Hugging Face model locally.

Together AI offers a powerful API for running inference on over 200 open-source models, providing a cost-effective and fast solution compared to major competitors like OpenAI and Azure. The service is designed for scalability, utilizing optimized NVIDIA GPUs and proprietary technologies to enhance performance while maintaining privacy standards. Flexible deployment options cater to various customer needs, from managed serverless solutions to dedicated GPU clusters.