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The system is designed as an applied AI application that helps users reason about ingredients, dietary restrictions, and meal composition through a single interactive workflow.\n\nThe project focuses on a realistic product setting rather than a standalone model benchmark. It combines multimodal inference and agent-based orchestration to support two complementary use cases: recipe generation from available ingredients and nutritional analysis of a finished dish.\n\n## Technical overview\nThe application implements a full-stack architecture with a FastAPI backend and a Streamlit frontend. On the backend, CrewAI coordinates the recipe workflow through specialized agents for ingredient extraction, ingredient filtering, dietary restriction handling, and recipe suggestion, while the nutritional analysis path uses a dedicated vision-based analysis tool over uploaded images.\n\nOpenAI models are used for both text and multimodal reasoning, with Poetry managing dependencies and Docker Compose supporting containerized execution. 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