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In this tutorial, we work with the Fable 5 Traces dataset from Hugging Face and build a complete workflow around real coding-agent trace data. We start by setting up a lightweight environment that avoids fragile dependencies such as datasets, scikit-learn, and scipy. Then we manually download and parse the merged JSONL file to keep the […]
In this tutorial, we explore the Open-SWE-Traces dataset as a practical resource for studying and preparing agentic software-engineering trajectories for fine-tuning. We stream the dataset directly from Hugging Face, so we can work with a large dataset efficiently in Google Colab without downloading everything locally. We inspect individual records, normalize multi-turn agent conversations, parse final
In this tutorial, we build a lightweight personal AI agent inspired by the core architecture of nanobot, while keeping every part understandable and runnable in Google Colab. We start from the provider abstraction, then move through tool registration, session memory, lifecycle hooks, skills, and an MCP-style tool server. As we progress, we do not just
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
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
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
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
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,
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
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,
