Explore essential AI tools for R programming to enhance your low-code development capabilities and streamline your projects. | Restackio

Introduction. Few days ago I discovered the OpenAI Gym library which is a bunch of standardized AI environments written in Python to benchmark the skills of AI programs and scripts, aka agents.

Like many of you, my first real exposure to AI was when ChatGPT dropped. I spent way too much time prompting it with random stuff, used it for some PowerShell, and tried out the voice feature when that launched. Mostly, I’ve used AI for things like writing docs, double-checking my grammar and English, and making some funny pictures.

Let’s start this with some confessions: I’m at best an enthusiastic amateur with AI. I know more than most, and I know nothing in the grand scheme. Example: I’m not sure I have any idea of what an AI agent is. I think I do, but there’s so much marketing hype around them that I

Use Meta Prompting to rapidly generate results in the GenAI Age - README.md

Generating diagrams with AI / LLMs

Replace 'hub' with 'ingest' in any GitHub URL for a prompt-friendly text.

A flexible, feature-rich yet light-weight logging framework based on R6 classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, JSON, (rotating) files, memory buffers. For extra appenders that support logging to databases, email and push notifications see the the package lgr.app.

Explore essential logging practices for AI applications to ensure compliance and enhance software reliability. | Restackio

Please remember you are using a beta version of mcpx and mcp.run services.

Hi Obsidian Community! https://github.com/PublikPrinciple/obsidian-mcp-rest I’m working on implementing an MCP (Model Context Protocol) server that integrates with Obsidian’s Local REST API plugin. The goal is to allow AI assistants like Claude to interact directly with Obsidian vaults in a secure, local manner. Project Overview GitHub Repository: GitHub - PublikPrinciple/obsidian-mcp-rest: An MCP server implementation for accessing Obsidian via local REST API Purpose: Enable AI assistants ...

Batch processing framework for ellmer chat model interactions. Enables sequential and parallel processing of chat completions. Core capabilities include error handling with backoff, state persistence, progress tracking, and retry management. Parallel processing is implemented via the future framework. Additional features include structured data extraction, tool integration, timeout handling, verbosity control, and sound notifications. Includes methods for returning chat texts, chat objects, progress status, and structured data.

This guide outlines my approach to building software projects using Cursor IDE, leveraging Gemini (gemini-exp-1206, gemini-2.0-flash-exp) and Claude (3.5 sonnet and 3 opus) for effective development and maintaining code integrity. 1. Project Setup: Laying the Foundation for AI Collaboration Think of your project as a well-organized workshop where you and your AI collaborators (Gemini and Claude) will build something amazing. The first step is to set up the workshop properly. 1.1. Define the Ru...

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Do you need to add LLM capabilities to your R scripts and applications? Here are three tools you'll want to know.

We’re evolving our platform to help developers and enterprises build useful and reliable agents.

Natural language processing has come a long way since its foundations were laid in the 1940s and 50s (for an introduction see, e.g., Jurafsky and Martin (2008, 2009, 2022 draft third edition): Speech and Language Processing, Pearson Prentice Hall). This CRAN task view collects relevant R packages that support computational linguists in conducting analysis of speech and language on a variety of levels - setting focus on words, syntax, semantics, and pragmatics.

If you are looking to use Natural Language Processing in R applications, these are some of the best NLP packages you must know.

In this episode, Jay Nakashima, President of eHealth Exchange, joins us to discuss 'Project Best'—a groundbreaking collaboration between eHealth Exchange and...

An LLM prompt playground for structured prompting

Boundary makes it easy to build, test, and develop LLM applications.

Discover the key differences and advantages of RAG, AI Agents, and Agentic RAG. Explore how these cutting-edge technologies power smarter AI solutions.