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-
-# Guide to Deploying AI Agents with Triton Inference Server
-
-Welcome to the **Guide to Deploying AI Agents with Triton Inference Server**.
-This repository provides a set of tutorials designed to help you deploy
-AI agents efficiently using the Triton Inference Server. This guide is intended
-for users who are already familiar with the basics of Triton and are looking to
-expand their knowledge.
-
-For beginners, we recommend starting with the
-[Conceptual Guide](tutorials/Conceptual_Guide/README.md), which covers
-foundational concepts and basic setup of Triton Inference Server.
-
-## AI agents and Agentic Workflows
-
-Modern large language models (LLMs) are integral components of AI agents —
-sophisticated self-governing systems that make decisions by interacting with
-their environment and analyzing the data they gather. By integrating LLMs,
-AI agents can understand, generate, and respond to human language with high
-proficiency, enabling them to perform complex tasks such as language
-translation, content generation, and conversational interactions.
-
-
-## Table of Contents
-
-- [Constrained Decoding](Constrained_Decoding/README.md)
-    * Learn about constrained decoding, how to implement it in Triton,
-    and explore practical examples and use cases.
-- [Function Calling](Function_Calling/README.md)
-    * Discover how to set up and utilize function calling within AI models using
-    Triton. This section includes detailed instructions and examples to help you
-    integrate function calling into your deployments.
-
-
-
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