Articles for tag: advanced AI applications, AI Agents, AI Development, Google's Gemini, LangGraph, ReAct agents, reasoning and action

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Build a ReAct Agent from Scratch Using Gemini 2.5 and LangGraph for Enhanced AI Development Efficiency

In recent years, AI applications have advanced significantly, evolving from basic chatbots to sophisticated agents capable of complex reasoning and real-world interactions. These AI agents, known as ReAct (Reasoning and Acting) Agents, utilize large language models (LLMs) to think critically, execute tasks, and adapt their responses based on new information. In this blog, we will ...

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Easily Create a User Interface for Your AI Agent with LangGraph and CopilotKit in Minutes

In this article, you will discover how to create an agent-native research canvas app that utilizes human-in-the-loop features, using tools like Langraph, CopilotKit, and Tavily. The topics covered include understanding AI agents, visualizing a LangGraph agent using LangGraph Studio, and designing the user interface with CopilotKit. You’ll learn how AI agents can perform research tasks ...

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Build Intelligent Stateful AI Agents in Python: A Comprehensive Guide from Real Python for Effective Development

LangGraph is a powerful Python library that helps you create advanced applications using Large Language Models (LLMs). It enhances the capabilities of LangChain by enabling you to build complex, stateful workflows for various LLM tasks. The library allows you to develop agents that can autonomously handle tasks such as parsing emails, sending responses, and interacting ...

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Create Your Own AI Agent: A Step-by-Step Hands-On Tutorial for Beginners

SAP is rapidly advancing its use of AI agents on Joule, showcasing their ability to handle complex requests using a variety of tools. This tutorial serves as a foundation for building a custom AI agent on the Business Technology Platform (BTP). While not production-ready, it provides valuable insights into creating and extending AI agents using ...

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Mastering AI Agents: A Step-by-Step Guide to Building with LangGraph for Beginners

In this article, the author shares their experience of building their first commercial AI agent, which unfortunately failed during a client demo. This setback led to valuable insights about agent architecture, emphasizing that simplicity is key. AI agents, unlike traditional chatbots, can think independently, manage various tasks, and adapt by learning from their experiences. The ...

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Unlocking Efficiency: How AI Agents Utilize UI and API Tools to Seamlessly Execute Tasks and Enhance Productivity

This article delves into the vital role of actions in autonomous AI agents, distinguishing between UI-driven and API-driven interactions. It highlights how actions enable AI to engage with environments effectively, moving beyond simple responses to meaningful tasks. The piece compares several open-source frameworks like LangGraph, Microsoft AutoGen, and BabyAGI, showcasing their unique approaches to integrating ...

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Build a Multi-Agent System on AWS Using LangGraph and Mistral for Enhanced AI Collaboration

Agents are changing how we use generative AI, connecting large language models to practical applications. These smart systems will play a vital role in many industries by enhancing decision-making, automating workflows, and improving human-AI interactions. By integrating specialized tools, agents can perform complex tasks and tackle real-world problems, as demonstrated by the Multi-Agent City Information ...

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