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How to Design an OpenHarness Style Agent Runtime with Tools, Memory, Permissions, Skills, and Multi-Agent Coordination

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Staff, Tutorials

In this tutorial, we build OpenHarness from scratch to better understand how a practical agent harness works. We recreate the major building blocks that make an agent system useful, including tool use, typed tool schemas, permissions, lifecycle hooks, memory, skills, context compaction, retry logic, cost tracking, and multi-agent coordination. Instead of treating an agent framework […]

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Using Graphify and NetworkX to Map Python Codebase Structure with God Nodes, Communities, and Architecture Visualizations

agentic ai, ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Software engineering, Staff, Tutorials

In this tutorial, we build a fully offline Graphify workflow that turns a realistic multi-module Python application into a knowledge graph. We start by installing Graphify and supporting graph libraries, then generate a small but connected sample application with configuration, database, authentication, service, API, cache, model, and SQL layers. We extract the graph locally using

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How to Use NVIDIA Canary-1B-v2 for ASR, Translation, and Automatic SRT Subtitle Export in Python

ai, AI (Artificial Intelligence), Artificial Intelligence, Audio Language Model, Editors Pick, Language Model, Staff, Technology, Tutorials, Voice AI

In this tutorial, we build a speech recognition and translation workflow using NVIDIA Canary-1B-v2. We begin by setting up the required audio, NeMo, NumPy, and SciPy dependencies, then load the Canary model on a GPU-enabled runtime for efficient inference. From there, we prepare audio into a clean 16 kHz mono format, perform English ASR, translate

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GLM-5.2 OpenAI-Compatible API: A Hands-On Guide to Reasoning Effort, Function Calling, and Long-Context Retrieval

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we work with GLM-5.2 and use its hosted, OpenAI-compatible API instead of running the full model locally. We begin by setting up multiple provider options, securely loading the API key, and creating a reusable chat wrapper that supports normal chat, thinking mode, streaming, tool calling, and token tracking. Then we move beyond

GLM-5.2 OpenAI-Compatible API: A Hands-On Guide to Reasoning Effort, Function Calling, and Long-Context Retrieval Read More »

How to Design Python-First Interactive Dashboards with Prefab Reactive UI Components and Static HTML Export

ai, AI (Artificial Intelligence), Artificial Intelligence, Data Science, Editors Pick, Technology, Tutorials

In this tutorial, we build a Prefab application that demonstrates how to create interactive dashboards entirely in Python. We use Prefab’s component-based Python interface to design a polished operations dashboard with reactive state, charts, tables, filters, forms, tabs, alerts, metrics, and client-side actions. We generate realistic pipeline monitoring data, connect it to live UI controls,

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Crawlee for Python: Build a Web Crawling Pipeline with Robots Handling, Link Graphs, and RAG Chunk Export

agentic ai, ai, AI (Artificial Intelligence), Applications, Artificial Intelligence, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we build a full Crawlee-for-Python workflow that covers environment setup, local website generation, static crawling, dynamic crawling, structured extraction, and downstream data processing. We begin by configuring a compatible Crawlee runtime with pinned Pydantic support, Playwright browser installation, persistent storage directories, and Colab-safe execution handling. We then generate a realistic local demo

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How to Build a Forecasting Pipeline with TimeCopilot Using Foundation Models and Automated Anomaly Detection

ai, AI (Artificial Intelligence), Artificial Intelligence, Data Science, Editors Pick, Staff, Technology, Tutorials

In this tutorial, we build an end-to-end forecasting workflow with TimeCopilot. We prepare a panel dataset containing real airline passenger data and a synthetic seasonal series with injected anomalies, then evaluate a diverse collection of statistical, foundation, and optional GPU-based forecasting models. We use rolling cross-validation and multiple error metrics to identify the strongest model,

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Salesforce CodeGen Tutorial: Generate, Validate, and Rerank Python Functions With Unit Tests and Safety Checks

ai, AI (Artificial Intelligence), Artificial Intelligence, Editors Pick, Language Model, Large Language Model, Staff, Technology, Tutorials

In this tutorial, we implement an end-to-end workflow for Salesforce CodeGen. We load a CodeGen model from Hugging Face, prepare it for code generation, and use it to generate Python functions from natural-language prompts. We then move beyond basic inference by adding function extraction, syntax checking, static safety checks, unit-test-based validation, best-of-N candidate reranking, multi-step

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NVIDIA SkillSpector Guide: Scanning AI Skills for Security Risks with Static Analysis and SARIF Reports

agentic ai, ai, AI (Artificial Intelligence), AI Agents, Artificial Intelligence, Editors Pick, Staff, Tutorials

In this tutorial, we explore how NVIDIA SkillSpector helps us evaluate AI skills for security risks before they are used in real-world workflows. We build a controlled corpus containing both benign and deliberately vulnerable skills, scan them through SkillSpector’s programmatic LangGraph workflow, and organize the resulting risk scores and findings with pandas. We then visualize

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How to Build Memory-Efficient Transformers with xFormers Using Packed Sequences, GQA, ALiBi, SwiGLU, and Causal Attention

ai, AI (Artificial Intelligence), Artificial Intelligence, deep learning, Editors Pick, Machine Learning, Staff, Technology, Tutorials

In this tutorial, we implement xFormers: a practical toolkit for building fast, memory-efficient Transformer models on GPUs. We begin by validating memory-efficient attention against a standard attention implementation, then compare their speed and memory consumption across different sequence lengths. We then examine causal masking, packed variable-length sequences, grouped-query attention, and custom ALiBi positional biases. Finally,

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