Developers Build AI Sleep Coach Using CrewAI Multi-Agent System to Optimize Circadian Rhythms

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A tutorial published on DEV Community walks developers through building a multi-agent AI sleep coaching system using Python, CrewAI, and Redis. The system ingests health data — including light exposure, step counts, sleep scores, and caffeine intake — sourced via the Google Health Connect API. Two specialized AI agents power the workflow: a Data Analyst agent that identifies circadian disruptions and a Protocol Agent that formulates personalized 24-hour sleep strategies. Redis is used to store historical health metrics, enabling the system to detect long-term trends rather than reacting to a single day's data. The project targets common sleep issues such as jet lag and irregular schedules, positioning itself as a template for AI-driven personalized wellness tools.

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