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

LLMs are stateless by default. Agent memory fixes that. This guide breaks down all 7 types — working, semantic, episodic, procedural, retrieval, parametric, and prospective. It covers what each stores, where it lives, and when to build it. Includes a comparison table and working Python code. The post The 7 Types of Agent Memory: A Technical Guide for AI Engineers appeared first on MarkTechPost.

In this tutorial, we build a complete Crawlee for Python workflow from setup to AI-ready output. We generate a local demo website, then crawl it with BeautifulSoupCrawler, ParselCrawler, and PlaywrightCrawler. We extract titles, metadata, product fields, and JavaScript-rendered cards, and capture full-page screenshots. We then normalize the data, build a link graph, and export JSON, CSV, and RAG-ready JSONL chunks. The post Crawlee for Python: Build a Web Crawling Pipeline with Robots Handling, Link Graphs, and RAG Chunk Export appeared first on MarkTechPost.

SpatialClaw is a training-free agent that writes Python in a persistent kernel, composing perception tools for 3D spatial reasoning The post NVIDIA AI Introduce SpatialClaw: A Training-Free Agent That Treats Code as the Action Interface for Spatial Reasoning appeared first on MarkTechPost.

Master these tips, and your dictionary code will become shorter, safer, and easier to read.

Meta’s long-awaited Pyrefly linter is out in a 1.0 version, and the forthcoming Python 3.15 has a super-efficient sampling profiler. Plus we have a comprehensive rundown of Python’s indispensable virtual environments — and a warning about a novel breed of malware that exploits Python’s package ecosystem. Top picks for Python readers on InfoWorld How to use virtual environments in Python Isolate and protect your Python projects from each other, and empower them to do more, with virtual environments and their native-to-Python tooling. Pyrefly 1.0: A fast, forward-looking Python linter The first full release of Meta’s long-awaited linting and type checking tool for Python delivers speed and offers advanced features for type-checking PyTorch and Django projects. Hands-on with the new sampling profiler in Python 3.15 Among Python 3.15’s best new features is a sampling profiler, for instrumenting your code and finding its bottlenecks with a minimum of performance impact or fuss. See up-close

We implement an end-to-end workflow for Salesforce CodeGen, loaded from Hugging Face. We move past basic inference by adding function extraction, syntax checking, static safety checks, and unit-test validation. We rerank best-of-N candidates, compose multi-turn program synthesis, and experiment with prompt styles. We finish by visualizing a mini benchmark and exporting the generated artifacts as reusable files. The post Salesforce CodeGen Tutorial: Generate, Validate, and Rerank Python Functions With Unit Tests and Safety Checks appeared first on MarkTechPost.

Most LLM applications need a clear workflow, not an autonomous agent. Here's how to build one in plain Python. The post You Probably Don’t Need an Agent Framework appeared first on Towards Data Science.

We break down Google Cloud's new Open Knowledge Format (OKF), an open spec that formalizes the LLM-wiki pattern. We explain how a bundle works: a directory of markdown files with YAML frontmatter, where each concept needs only a type field. We cover the three design principles, the reference tools Google shipped, and how OKF differs from RAG. We include a working Python consumer and an interactive bundle explorer you can embed. The post Google Cloud Introduces Open Knowledge Format (OKF): A Vendor-Neutral Markdown Spec for Giving AI Agents Curated Context appeared first on MarkTechPost.