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Proposing to include a new recipe for showcasing the LLM agent framework use case.
LLM agents use a large language model as its central computational engine to reason through a complex problem and plan to solve the problem using a set of tools. These tools extract the domain specific knowledge needed to generate a more tailored response to the problem. The tools can be executable functions, RAG pipelines, APIs or other services that allow the agents to complete their tasks effectively. We can showcase containerized services as the tools in our agent framework recipe.
Proposing to include a new recipe for showcasing the LLM agent framework use case.
LLM agents use a large language model as its central computational engine to reason through a complex problem and plan to solve the problem using a set of tools. These tools extract the domain specific knowledge needed to generate a more tailored response to the problem. The tools can be executable functions, RAG pipelines, APIs or other services that allow the agents to complete their tasks effectively. We can showcase containerized services as the tools in our agent framework recipe.
References:
cc @Shreyanand
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