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Practical guide to integrating AI APIs on Linux: set up packages and virtual environments, manage API keys securely, and call models via Python and curl. Includes examples for text, embeddings, and vision, plus Docker options, GPU/CUDA notes, and tips for rate limits, retries, logging, and systemd services. Concludes with testing, monitoring, and troubleshooting best practices for reliable production use.