In this tutorial, we build a self-organizing memory system for an agent that goes beyond storing raw conversation history and instead structures interactions into persistent, meaningful knowledge ...

⚠️ For best results: Configure SearXNG with GitHub, Stack Overflow, and other code-focused search engines. See SEARXNG_SETUP.md for the recommended configuration.

What if you could create your very own personal AI assistant—one that could research, analyze, and even interact with tools—all from scratch? It might sound like a task reserved for seasoned ...

A common use case in generative AI is developing an agent, which is a system users interact with in plain language to accomplish a given task. Creating AI agents can require a lot of heavy lifting, ...

Large Language Models (LLMs) power today’s chatbots, virtual assistants, and AI copilots – but moving from prototype to production requires new DevOps patterns. LLMOps has emerged as an evolution of ...

MCP-Use is an open-source library that lets you connect any LLM to any MCP server, giving your agents tool access like web browsing, file operations, and more — all without relying on closed-source ...

MCP (Model Context Protocol) is an emerging standard for AI tools and resources. The standard is compatible with normal REST API servers, but adds extra metadata to describe tools, resources, and ...

Hello! Tommy here, and I’m excited to guide you through xAI’s Grok API! This tutorial is designed to help you feel confident and comfortable as you start building with the Grok API, all within the ...

The guide provides a tutorial on building an advanced artificial intelligence (AI) agent using Python and Retrieval Augmented Generation (RAG). The AI agent is capable of utilizing various tools and ...

Speech Recognition is the ability of a machine or program to identify words and phrases in spoken language and convert them to textual information. In order to understand your voice these virtual ...