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" The LLMOps Steps LLMs, sophisticated artificial intelligence (AI) systems trained on enormous text and code datasets, have changed the game in various fields, from natural language processing to content generation. Deployment : The adapted LLM is integrated into this stage's planned application or systemarchitecture.
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Focused on addressing the challenge of agricultural data standardization, Agmatix has developed proprietary patented technology to harmonize and standardize data, facilitating informed decision-making in agriculture. The transformed data acts as the input to AI/ML services.
The solution lies in implementing a multi-agent architecture, which involves decomposing the main system into smaller, specialized agents that operate independently. Stateful architecture Support for stateful and adaptive agents within a graph-based architecture enables more sophisticated behaviors and interactions.
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In synchronous orchestration, just like in traditional process automation, a supervisor agent orchestrates the multi-agent collaboration, maintaining a high-level view of the entire process while actively directing the flow of information and tasks. Understanding how to implement this type of pattern will be explained later in this post.
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