Gemini
ChatGPT Vs. Gemini AI: Which One Makes the Wiser Choice? – Tecuy Media
From getting a tutorial on how to put a diaper on your baby to drafting emails to planning trips to coding while integrating technical solutions, AI is deeply rooted in our lives now. The dilemma comes to decide on which is the best one and a wiser choice to make? The same is with vouching…
A Coding Implementation of an Advanced Tool-Using AI Agent with Semantic Kernel and Gemini
In this tutorial, we build an advanced AI agent using Semantic Kernel combined with Google’s Gemini free model, and we run it seamlessly on Google Colab. We start by wiring Semantic Kernel plugins as tools, like web search, math evaluation, file I/O, and note-taking, and then let Gemini orchestrate them through structured JSON outputs. We…
Building a Multi-Agent Conversational AI Framework with Microsoft AutoGen and Gemini API
class GeminiAutoGenFramework: “”” Complete AutoGen framework using free Gemini API Supports multi-agent conversations, code execution, and retrieval “”” def __init__(self, gemini_api_key: str): “””Initialize with Gemini API key””” self.gemini_api_key = gemini_api_key self.setup_gemini_config() self.agents: Dict[str, autogen.Agent] = {} self.group_chats: Dict[str, GroupChat] = {} def setup_gemini_config(self): “””Configure Gemini for AutoGen””” os.environ[“GOOGLE_API_KEY”] = self.gemini_api_key self.llm_config = { “config_list”: […
Vilken AI-modell passar dig bäst? ChatGPT, Claude, Gemini, Perplexity – AI nyheter
En guide för dig som är nybörjare och vill testa AI-modeller utöver ChatGPT, Som nybörjare kanske du bara känner till ChatGPT, men det finns många andra kraftfulla AI-modeller att utforska – som Claude, Gemini, Grok och Perplexity AI. Varje AI-modell har unika styrkor anpassade för specifika uppgifter. Vissa är bäst för konversationer, andra excellerar inom…
The End of Moore’s Law for AI? Gemini Flash Offers a Warning – Sutro
For the past few years, the AI industry has operated under its own version of Moore’s Law: an unwavering belief that the cost of intelligence would perpetually decrease by orders of magnitude each year. Like clockwork, each new model generation promised to be not only more capable but also cheaper to run. Last week, Google…
Google AI Releases Gemini CLI: An Open-Source AI Agent for Your Terminal
Google has unveiled Gemini CLI, an open-source command-line AI agent that integrates the Gemini 2.5 Pro model directly into the terminal. Designed for developers and technical power users, Gemini CLI allows users to interact with Gemini using natural language directly from the command line—supporting workflows such as code explanation, debugging, documentation generation, file manipulation, and…
Building Event-Driven AI Agents with UAgents and Google Gemini: A Modular Python Implementation Guide
In this tutorial, we demonstrate how to use the UAgents framework to build a lightweight, event-driven AI agent architecture on top of Google’s Gemini API. We’ll start by applying nest_asyncio to enable nested event loops, then configure your Gemini API key and instantiate the GenAI client. Next, we’ll define our communication contracts, Question and Answer…
How to Build an Advanced BrightData Web Scraper with Google Gemini for AI-Powered Data Extraction
In this tutorial, we walk you through building an enhanced web scraping tool that leverages BrightData’s powerful proxy network alongside Google’s Gemini API for intelligent data extraction. You’ll see how to structure your Python project, install and import the necessary libraries, and encapsulate scraping logic within a clean, reusable BrightDataScraper class. Whether you’re targeting Amazon…
How to Build an Asynchronous AI Agent Network Using Gemini for Research, Analysis, and Validation Tasks
In this tutorial, we introduce the Gemini Agent Network Protocol, a powerful and flexible framework designed to enable intelligent collaboration among specialized AI agents. Leveraging Google’s Gemini models, the protocol facilitates dynamic communication between agents, each equipped with distinct roles: Analyzer, Researcher, Synthesizer, and Validator. Users will learn to set up and configure an asynchronous…
A Step-by-Step Coding Guide to Building an Iterative AI Workflow Agent Using LangGraph and Gemini
In this tutorial, we demonstrate how to build a multi-step, intelligent query-handling agent using LangGraph and Gemini 1.5 Flash. The core idea is to structure AI reasoning as a stateful workflow, where an incoming query is passed through a series of purposeful nodes: routing, analysis, research, response generation, and validation. Each node operates as a…
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