In this tutorial, we are walking through a hands-on fusion of symbolic logic and generative AI. We set up PySwip to embed a Prolog knowledge base, wrap its predicates as LangChain tools, and then wire everything into a ReAct-style agent. Along the way, we are crafting family-relationship rules, mathematical predicates like factorial, and list utilities,…
GitHub has introduced Spark, a groundbreaking addition to its suite of developer tools, aimed at revolutionizing the way full-stack intelligent applications are built and deployed. With Spark, available in public preview for Copilot Pro+ subscribers, developers can go from idea to a fully deployed app in minutes—all using natural language prompts and without the usual…
Introduction Qwen has unveiled Qwen3-Coder-480B-A35B-Instruct, their most powerful open agentic code model released to date. With a distinctive Mixture-of-Experts (MoE) architecture and comprehensive agentic coding capabilities, Qwen3-Coder not only sets a new standard for open-source coding models but also redefines what’s possible for large-scale, autonomous developer assistance. Model Architecture and Specifications Key Features Model Size: 480 billion…
In this tutorial, we begin by setting up a compact yet capable AI agent that runs smoothly, leveraging Hugging Face transformers. We integrate dialog generation, question‑answering, sentiment analysis, web search stubs, weather look‑ups, and a safe calculator into a single Python class. As we progress, we install only the essential libraries, load lightweight models that respect…
Building effective AI agents means more than just picking a powerful language model. As the Manus project discovered, how you design and manage the “context” – the information the AI processes to make decisions – is paramount. This “context engineering” directly impacts an agent’s speed, cost, reliability, and intelligence. Initially, the choice was clear: leverage…
WrenAI is an open-source Generative Business Intelligence (GenBI) agent developed by Canner, designed to enable seamless, natural-language interaction with structured data. It targets both technical and non-technical teams, providing the tools to query, analyze, and visualize data without writing SQL. All capabilities and integrations are verified against the official documentation and latest releases. Key Capabilities…
A team of researchers from University of Liverpool, Huawei Noah’s Ark Lab, University of Oxford and University College London presents a report explaining Deep Research Agents (DR agents), a new paradigm in autonomous research. These systems are powered by Large Language Models (LLMs) and designed to handle complex, long-horizon tasks that require dynamic reasoning, adaptive…
Table of contents What is an AI Agent? Why AI Agents Matter in 2025 Types of AI Agents Key Components of an AI Agent Leading AI Agent Frameworks in 2025 Practical Use Cases for AI Agents AI Agent vs. Chatbot vs. LLM The Future of Agentic AI Systems FAQs About AI Agents Conclusion What is…
In this tutorial, we build a complete multi-agent research team system using LangGraph and Google’s Gemini API. We utilize role-specific agents, Researcher, Analyst, Writer, and Supervisor, each responsible for a distinct part of the research pipeline. Together, these agents collaboratively gather data, analyze insights, synthesize a report, and coordinate the workflow. We also incorporate features…
On July 17, 2025, OpenAI launched ChatGPT Agent, transforming ChatGPT from a conversational assistant into a unified AI agent capable of autonomously executing complex, multi‑step tasks—from web browsing to code execution—on a virtual computer environment. Bridging Previous Capabilities ChatGPT Agent builds on two earlier tools: Operator, enabled limited web interactions—clicking, scrolling, and form‑filling—with a Browser‑based agent. Deep Research, provided…