Agentic AI

In this tutorial, we introduce an advanced AI agent built using Nebius’ robust ecosystem, particularly the ChatNebius, NebiusEmbeddings, and NebiusRetriever components. The agent utilizes the Llama-3.3-70B-Instruct-fast model to generate high-quality responses, incorporating external functionalities such as Wikipedia search, contextual document retrieval, and safe mathematical computation. By combining structured prompt design with LangChain’s modular framework, this…

In this Ultra-Light Mistral Devstral tutorial, a Colab-friendly guide is provided that is designed specifically for users facing disk space constraints. Running large language models like Mistral can be a challenge in environments with limited storage and memory, but this tutorial shows how to deploy the powerful devstral-small model. With aggressive quantization using BitsAndBytes, cache…

Why Web Agents Struggle with Dynamic Web Interfaces Digital agents designed for web environments aim to automate tasks such as navigating pages, clicking buttons, or submitting forms. These agents operate by interpreting browser data and simulating user interactions to complete specified tasks. Success in this domain requires an accurate understanding of dynamic content and the…

Redefining Job Execution with AI Agents AI agents are reshaping how jobs are performed by offering tools that execute complex, goal-directed tasks. Unlike static algorithms, these agents combine multi-step planning with software tools to handle entire workflows across various sectors, including education, law, finance, and logistics. Their integration is no longer theoretical—workers are already applying…

In this tutorial, we’ll implement content moderation guardrails for Mistral agents to ensure safe and policy-compliant interactions. By using Mistral’s moderation APIs, we’ll validate both the user input and the agent’s response against categories like financial advice, self-harm, PII, and more. This helps prevent harmful or inappropriate content from being generated or processed — a…

Or: Why “Can we turn off generation” might be the smartest question in generative AI Not long ago, I found myself in a meeting with technical leaders from a large enterprise. We were discussing Parlant as a solution for building fluent yet tightly controlled conversational agents. The conversation was going well—until someone asked a question…

In this tutorial, we walk you through the design and implementation of a custom agent framework built on PyTorch and key Python tooling, ranging from web intelligence and data science modules to advanced code generators. We’ll learn how to wrap core functionalities in monitored CustomTool classes, orchestrate multiple agents with tailored system prompts, and define…