raix connects RStudio to any AI model. Describe what you want in English — raix writes the R code, executes it, and shows results. Chat, debug, generate notebooks, run Python, compile C++, or launch a full coding dashboard.
remotes::install_github("twomathematicians-code/raix")
library(raix)
raix_dashboard() # self-configuring — auto-detects your AI%%{init: {'theme': 'base', 'themeVariables': {'fontSize': '12px'}}}%%
flowchart LR
U[User] --> S[Setup]
S --> C[AI Backend]
C --> A[Apps]
A --> O[Output]
S -.- S1[raix_setup]
S -.- S2[raix_configure]
C -.- C1[OpenAI · Groq · Mistral]
C -.- C2[Ollama · LM Studio · vLLM]
C -.- C3[Claude · Custom]
A -.- A1[Chat & Dashboard]
A -.- A2[Code Gen & Debug]
A -.- A3[Developer Agent]
A -.- A4[Compute & Multi-Lang]
O -.- O1[Scripts · Notebooks · Plots]
raix_setup() # auto-detect & configure — one click
raix_dashboard() # full coding workspace in RStudio Viewer
raix_info() # show current config
raix_config() # get config as list (for scripts)raix_chat() # interactive AI chat in console
raix_gui() # chat window in RStudio Viewer
raix_send("prompt") # one message → one response
raix_explain("code") # AI explains R code
raix_generate("task") # English → R code
raix_debug() # diagnose last error
raix_document("fn") # generate roxygen2 docsraix_solve("problem") # complete solution from description
raix_script("task", "out.R") # generate .R file
raix_notebook("task", "out.Rmd") # generate .Rmd notebook
raix_test(my_function) # AI writes testthat tests
raix_refactor(code) # AI suggests improvements
raix_project(".") # scan project for AI context
raix_package("task") # find best R package
raix_read("file.R") # read file with AI summary
raix_write("desc", "out.R") # AI content → fileraix_terminal("cmd") # shell commands + AI analysis
raix_python("task") # generate & run Python from R
raix_compile("task") # C++ with Rcpp, compile, call from R
raix_pipeline(steps) # multi-step cross-language workflow
raix_translate(code, to="python") # R ↔ Python
raix_sql("top 10 customers") # English → SQL
raix_simulate("Monte Carlo") # AI simulation engine
raix_web("https://...") # fetch & summarize web pagesraix_benchmark(expr) # time code, AI suggests optimizations
raix_parallel("task") # AI rewrites for multi-core
raix_analyze(mtcars) # AI-guided data analysis
raix_search("topic") # search CRAN packages
raix_diagnose("script.R") # scan for issues & anti-patterns
raix_google("query") # Google search + AI summary
raix_sysinfo() # system info for AI context
raix_history() # view/search chat history%%{init: {'theme': 'base', 'themeVariables': {'fontSize': '11px'}}}%%
flowchart LR
A[English] --> B[raix_solve]
B --> C[Plan & Packages]
C --> D[Generate R Code]
D --> E[Output: .R / .Rmd / Execute]
| Local (free) | Cloud (API key) |
|---|---|
| Ollama · LM Studio · vLLM | OpenAI · Claude · Groq · Mistral |
| DeepSeek · Together AI · Perplexity · OpenRouter |
Small models? raix auto-detects 7B-9B models and optimizes prompts. raix_small_mode(TRUE) for manual control.
MIT © Mahesh Solanki · SOP.md · citation("raix")