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hellmer: Batch Processing for Chat Models
hellmer: Batch Processing for Chat Models
Batch processing framework for 'ellmer' chat models. Provides both sequential and parallel processing of chat interactions with features including tool calling and structured data extraction. Enables workflow management through progress tracking and recovery and automatic retry with backoff. Additional quality-of-life features include verbosity (or echo) control and sound notifications. Parallel processing is implemented via the 'future' framework. Includes methods for retrieving progress status, chat texts, and chat objects.
·rdrr.io·
hellmer: Batch Processing for Chat Models
CRAN: Package tokenizers.bpe
CRAN: Package tokenizers.bpe
Unsupervised text tokenizer focused on computational efficiency. Wraps the 'YouTokenToMe' library which is an implementation of fast Byte Pair Encoding (BPE) .
·cran.r-project.org·
CRAN: Package tokenizers.bpe
keberwein/blscrapeR: A tool to gather, analyze and visualize data from the Bureau of Labor Statistics (BLS) API. Functions include segmentation, geographic analysis and visualization.
keberwein/blscrapeR: A tool to gather, analyze and visualize data from the Bureau of Labor Statistics (BLS) API. Functions include segmentation, geographic analysis and visualization.
A tool to gather, analyze and visualize data from the Bureau of Labor Statistics (BLS) API. Functions include segmentation, geographic analysis and visualization. - keberwein/blscrapeR
·github.com·
keberwein/blscrapeR: A tool to gather, analyze and visualize data from the Bureau of Labor Statistics (BLS) API. Functions include segmentation, geographic analysis and visualization.
RAG with Ollama and ragnar in R: A Practical Guide for R Programmers – Steve’s Data Tips and Tricks
RAG with Ollama and ragnar in R: A Practical Guide for R Programmers – Steve’s Data Tips and Tricks
Learn how to build a privacy-preserving Retrieval-Augmented Generation (RAG) workflow in R using Ollama and the ragnar package. Discover step-by-step methods for summarizing health insurance policy documents, automating compliance reporting, and leveraging local LLMs—all within your R environment.
·spsanderson.com·
RAG with Ollama and ragnar in R: A Practical Guide for R Programmers – Steve’s Data Tips and Tricks
How to create your own RAG applications in R
How to create your own RAG applications in R
See how to query documents using natural language, LLMs, and R—including dplyr-like filtering on metadata. Plus, learn how to use an LLM to extract structured data for text filtering.
·infoworld.com·
How to create your own RAG applications in R
Clean, Parse, Harmonize, Match, and Geocode Messy Real-World Addresses
Clean, Parse, Harmonize, Match, and Geocode Messy Real-World Addresses
Addresses that were not validated at the time of collection are often heterogenously formatted, making them difficult to compare or link to other sets of addresses. The addr package is designed to clean character strings of addresses, use the `usaddress` library to tag address components, and paste together select components to create a normalized address. Normalized addresses can be hashed to create hashdresses that can be used to merge with other sets of addresses.
·geomarker.io·
Clean, Parse, Harmonize, Match, and Geocode Messy Real-World Addresses
Free Online OpenAPI & Swagger Converter
Free Online OpenAPI & Swagger Converter
Easily convert OpenAPI (Swagger) specifications between YAML and JSON formats online for free. Paste your code or upload a file to get started instantly.
·openapiconverter.xyz·
Free Online OpenAPI & Swagger Converter
Swagger 2.X OpenAPI 3.1
Swagger 2.X OpenAPI 3.1
Examples and server integrations for generating the Swagger API Specification, which enables easy access to your REST API - swagger-api/swagger-core
·github.com·
Swagger 2.X OpenAPI 3.1
Obtaining Star Databases from Flat Tables
Obtaining Star Databases from Flat Tables
Data in multidimensional systems is obtained from operational systems and is transformed to adapt it to the new structure. Frequently, the operations to be performed aim to transform a flat table into a ROLAP (Relational On-Line Analytical Processing) star database. The main objective of the package is to allow the definition of these transformations easily. The implementation of the multidimensional database obtained can be exported to work with multidimensional analysis tools on spreadsheets or relational databases.
·josesamos.github.io·
Obtaining Star Databases from Flat Tables
CRAN: Package rolap
CRAN: Package rolap
Data in multidimensional systems is obtained from operational systems and is transformed to adapt it to the new structure. Frequently, the operations to be performed aim to transform a flat table into a ROLAP (Relational On-Line Analytical Processing) star database. The main objective of the package is to allow the definition of these transformations easily. The implementation of the multidimensional database obtained can be exported to work with multidimensional analysis tools on spreadsheets or relational databases.
·cran.r-project.org·
CRAN: Package rolap
Obtaining Stars from Flat Tables
Obtaining Stars from Flat Tables
Data in multidimensional systems is obtained from operational systems and is transformed to adapt it to the new structure. Frequently, the operations to be performed aim to transform a flat table into a star schema. Transformations can be carried out using professional extract, transform and load tools or tools intended for data transformation for end users. With the tools mentioned, this transformation can be carried out, but it requires a lot of work. The main objective of this package is to define transformations that allow obtaining stars from flat tables easily. In addition, it includes basic data cleaning, dimension enrichment, incremental data refresh and query operations, adapted to this context.
·josesamos.github.io·
Obtaining Stars from Flat Tables
CRAN: Package marmap
CRAN: Package marmap
Import bathymetric and hypsometric data from the NOAA (National Oceanic and Atmospheric Administration, ), GEBCO (General Bathymetric Chart of the Oceans, ) and other sources, plot xyz data to prepare publication-ready figures, analyze xyz data to extract transects, get depth / altitude based on geographical coordinates, or calculate z-constrained least-cost paths.
·cran.r-project.org·
CRAN: Package marmap
PROD - NFHL - WMA
PROD - NFHL - WMA
Data from Flood Insurance Rate Maps (FIRMs) where available digitally.
·fema.maps.arcgis.com·
PROD - NFHL - WMA
USA Flood Hazard Areas
USA Flood Hazard Areas
This layer displays Flood Hazard Areas from the Flood Insurance Rate Map created by the Federal Emergency Management Agency, updated by Esri annually.
·fema.maps.arcgis.com·
USA Flood Hazard Areas