Tutorials

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A Coding Implementation of an OpenAI-Assisted Privacy-Preserving Federated Fraud Detection System from Scratch Using Lightweight PyTorch Simulations

In this tutorial, we demonstrate how we simulate a privacy-preserving fraud detection system using Federated Learning without relying on heavyweight frameworks or complex infrastructure. We build a clean, CPU-friendly setup that mimics ten independent banks, each training a local fraud-detection model on its own highly imbalanced transaction data. We coordinate these local updates through a […]

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How to Build a Robust Multi-Agent Pipeline Using CAMEL with Planning, Web-Augmented Reasoning, Critique, and Persistent Memory

In this tutorial, we build an advanced, end-to-end multi-agent research workflow using the CAMEL framework. We design a coordinated society of agents, Planner, Researcher, Writer, Critic, and Finalizer, that collaboratively transform a high-level topic into a polished, evidence-grounded research brief. We securely integrate the OpenAI API, orchestrate agent interactions programmatically, and add lightweight persistent memory

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How to Build Contract-First Agentic Decision Systems with PydanticAI for Risk-Aware, Policy-Compliant Enterprise AI

In this tutorial, we demonstrate how to design a contract-first agentic decision system using PydanticAI, treating structured schemas as non-negotiable governance contracts rather than optional output formats. We show how we define a strict decision model that encodes policy compliance, risk assessment, confidence calibration, and actionable next steps directly into the agent’s output schema. By

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How to Build Production-Grade Agentic Workflows with GraphBit Using Deterministic Tools, Validated Execution Graphs, and Optional LLM Orchestration

In this tutorial, we build an end-to-end, production-style agentic workflow using GraphBit that demonstrates how graph-structured execution, tool calling, and optional LLM-driven agents can coexist in a single system. We start by initializing and inspecting the GraphBit runtime, then define a realistic customer-support ticket domain with typed data structures and deterministic, offline-executable tools. We show

How to Build Production-Grade Agentic Workflows with GraphBit Using Deterministic Tools, Validated Execution Graphs, and Optional LLM Orchestration Read More »

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A Coding Implementation on Building Self-Organizing Zettelkasten Knowledge Graphs and Sleep-Consolidation Mechanisms

In this tutorial, we dive into the cutting edge of Agentic AI by building a “Zettelkasten” memory system, a “living” architecture that organizes information much like the human brain. We move beyond standard retrieval methods to construct a dynamic knowledge graph where an agent autonomously decomposes inputs into atomic facts, links them semantically, and even

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A Coding Guide to Build an Autonomous Multi-Agent Logistics System with Route Planning, Dynamic Auctions, and Real-Time Visualization Using Graph-Based Simulation

In this tutorial, we build an advanced, fully autonomous logistics simulation in which multiple smart delivery trucks operate within a dynamic city-wide road network. We design the system so that each truck behaves as an agent capable of bidding on delivery orders, planning optimal routes, managing battery levels, seeking charging stations, and maximizing profit through

A Coding Guide to Build an Autonomous Multi-Agent Logistics System with Route Planning, Dynamic Auctions, and Real-Time Visualization Using Graph-Based Simulation Read More »

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How to Build a Proactive Pre-Emptive Churn Prevention Agent with Intelligent Observation and Strategy Formation

In this tutorial, we build a fully functional Pre-Emptive Churn Agent that proactively identifies at-risk users and drafts personalized re-engagement emails before they cancel. Rather than waiting for churn to occur, we design an agentic loop in which we observe user inactivity, analyze behavioral patterns, strategize incentives, and generate human-ready email drafts using Gemini. We

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labml.ai Deep Learning Paper Implementations

This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations, and the website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.

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How to Build a Fully Autonomous Local Fleet-Maintenance Analysis Agent Using SmolAgents and Qwen Model

In this tutorial, we walk through the process of creating a fully autonomous fleet-analysis agent using SmolAgents and a local Qwen model. We generate telemetry data, load it through a custom tool, and let our agent reason, analyze, and visualize maintenance risks without any external API calls. At each step of implementation, we see how

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A Coding Guide to Design a Complete Agentic Workflow in Gemini for Automated Medical Evidence Gathering and Prior Authorization Submission

In this tutorial, we devise how to orchestrate a fully functional, tool-using medical prior-authorization agent powered by Gemini. We walk through each component step by step, from securely configuring the model to building realistic external tools and finally constructing an intelligent agent loop that reasons, acts, and responds entirely through structured JSON. As we progress,

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