r-ellmer

name	r-ellmer
description	Use when code loads or uses ellmer (library(ellmer), chat_openai, chat_claude, chat_ollama), chatting with LLMs from R, building chatbots, or extracting structured data from text with LLMs

ellmer: R Interface to Large Language Models

Overview

ellmer is the hub of the R AI stack. Provides unified interface to 20+ LLM providers (OpenAI, Claude, Ollama, etc.) with stateful chat sessions, tool calling, and token tracking.

Install: install.packages("ellmer")

API keys: Set OPENAI_API_KEY or ANTHROPIC_API_KEY in .Renviron

References

Read references/API.md before writing code.

• references/API.md - Complete function reference
• references/getting-started.md - Core workflow and chat patterns
• references/tool-calling.md - Tool registration and function calling

When to Use

• Chat with any LLM from R
• Create custom chatbots with domain knowledge
• Extract structured data from unstructured text
• Need multi-provider support (switch between OpenAI/Claude/Ollama)
• Build LLM-powered R applications

When NOT to Use

• Single one-off HTTP request (use httr2)
• Need streaming with custom callbacks
• Non-chat ML workflows (use tidymodels)

Quick Reference

# Create chat
chat <- chat_openai(model = "gpt-4o")
chat <- chat_claude(model = "claude-sonnet-4")
chat <- chat_ollama(model = "llama3.2")  # Local

# Chat (stateful - history preserved)
chat$chat("Explain this error")
chat$chat("How do I fix it?")  # Remembers context

# Fresh conversation
chat <- chat_openai()  # New = no history

# Track costs
token_usage()

# Tool calling
chat$set_tools(btw_tools())  # See r-btw skill

Common Mistakes

Issue	Solution
Forgot API key	Set in .Renviron, restart R
Ollama connection error	Run ollama serve first
Conversation too long/expensive	Start fresh chat for new topics
Expecting accuracy	LLMs for prototyping, not critical work
Using chat for single request	Just use httr2 for one-off calls

Use Cases

Custom chatbots: Preload with documentation, package info, educational materials

Structured data extraction: Sentiment analysis, geocoding, recipe parsing, document indexing

Programming assistance: Code modernization, documentation lookup, explanation, security analysis

Other: Alt text generation, statistical reasoning, brand style guide enforcement

Advanced

See references/ for:

• API.md: Complete function reference (all providers, models, methods)
• getting-started.md: Core vocabulary, tokens, system prompts
• tool-calling.md: Tool/function calling patterns

Integration

With btw (context tools): See r-btw skill With ragnar (RAG): See r-ragnar skill With vitals (evaluation): See r-vitals skill Cross-package patterns: See r-ai meta-skill