No Clocks

A completely FLOSS map stack.

A completely FLOSS map stack.

The first web-scale context tool made for coding agents - prevent hallucinations with accurate context from the web

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Provides modular, graph-based agents powered by large language models (LLMs) for intelligent task execution in R. Supports structured workflows for tasks such as forecasting, data visualization, feature engineering, data wrangling, data cleaning, SQL, code generation, weather reporting, and research-driven question answering. Each agent performs iterative reasoning: recommending steps, generating R code, executing, debugging, and explaining results. Includes built-in support for packages such as tidymodels, modeltime, plotly, ggplot2, and prophet. Designed for analysts, developers, and teams building intelligent, reproducible AI workflows in R. Compatible with LLM providers such as OpenAI, Anthropic, Groq, and Ollama. Inspired by the Python package langagent.

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Patron-only access to Pierce Brown's newest story: The Book of Lorn.

On October 19-20, 2025, Amazon Web Services (AWS) experienced a significant outage (AWS status) affecting its US-EAST-1 region in northern Virginia. The root...

Nationwide Land Parcel Dataset

The maps, mapdata and oz packages provide the boundaries of the most common world regions like the US, Europe, New Zealand and more. This post describes how to use them to avoid struggling finding input data.

It would be really nice if there was a way to leverage the markdown output from LLM responses in Quarto documents. For example, a code chunk in a Quarto document like: ```{r} library(elmer) chat -...

Contribute to streetsforall/parcel_analysis development by creating an account on GitHub.

How do you find and buy a house near a beach that isn't flood-prone? Real estate portals contains a comprehensive listing of homes that are for sale, but it doesn't really provided you with additional information such as flood hazard, noise levels or proximity of fault zones. You can get all that with GIS of course, but how would you marry them together? Through a scrape-extract-geocode-export-ingest workflow of course! Project Code: Github [https://github.com/sscchan/domain_geo_extracter] S

The FEAM ArcMap API has changed quite a bit. We need to refresh that repo in order to utilize the FEMA structures in this workflow. Fix end points and queries Transfer to OWP-Spatial/NFHL

overview info on FEMA's National Flood Hazard Layer Database - erinbergren/femaNFHL

Contribute to ActuarialHero/geospatial_rating development by creating an account on GitHub.

Latest version: 1.0.9, last published: 2 months ago. Start using @useoptic/optic in your project by running `npm i @useoptic/optic`. There are 2 other projects in the npm registry using @useoptic/optic.

Azure Maps provides location intelligence, traffic, mobility, and geospatial mapping APIs for IoT and enterprise systems to enhance mobile and web-based apps.

Supporting sustainability decision-making with the power of the cloud

Supporting sustainability decision-making with the power of the cloud

Document, Discover and Test APIs with Scalar.

A research preview of an agent that can use its own browser to perform tasks for you. Available to Pro users in the U.S.