This article provides a blueprint for building end-to-end GenAI-based applications ready for production, focusing on key considerations for implementing and designing these applications based on AI maturity. It emphasizes the importance of selecting the right architectural components based on the maturity level of the project. The article discusses patterns for designing conversational UI, personalization, prompt engineering, retrieval augmented generation, API management, service mesh, modularity, data pipelines, ethical AI, continuous deployment, and multi-agent systems in LLMs. It also touches on feedback loops, compliance management, real-time monitoring, and MLOps. The goal is to create AI solutions that are ethical, compliant, efficient, and adaptable to different use cases and environments. The integration of multi-agent systems in LLMs is highlighted as a way to generate specialized and contextually relevant language outputs. The article provides references to relevant research papers and patterns for each architectural building block discussed. Ultimately, the aim is to develop AI solutions that are robust, reliable, and capable of solving complex problems effectively.
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Source link: https://dr-arsanjani.medium.com/the-genai-reference-architecture-605929ab6b5a?source=rss——llm-5
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The GenAI Reference Architecture: A Comprehensive Guide for Developers #GenAIarchitecture
Preeti
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