Package index • LLMR

Core

llm_config(): Create an LLM configuration (provider-agnostic)

call_llm(): Call an LLM (chat/completions or embeddings) with optional multimodal input

call_llm_robust(): Robustly Call LLM API (Simple Retry)

finish_reason() tokens() is_truncated() as.character(<llmr_response>) print(<llmr_response>): LLMR Response Object

chat_session() as.data.frame(<llm_chat_session>) summary(<llm_chat_session>) head(<llm_chat_session>) tail(<llm_chat_session>) print(<llm_chat_session>): Chat Session Object and Methods

Structured output

enable_structured_output(): Enable Structured Output (Provider-Agnostic)

disable_structured_output(): Disable Structured Output (clean provider toggles)

llm_parse_structured(): Parse structured output emitted by an LLM

llm_parse_structured_col(): Parse structured fields from a column into typed vectors

llm_validate_structured_col(): Validate structured JSON objects against a JSON Schema (locally)

llm_fn_structured(): Vectorized structured-output LLM

llm_mutate_structured(): Data-frame mutate with structured output

call_llm_par_structured(): Parallel experiments with structured parsing

Tidy helpers and parallel

llm_fn(): Apply an LLM prompt over vectors/data frames

llm_mutate(): Mutate a data frame with LLM output

build_factorial_experiments(): Build Factorial Experiment Design

call_llm_par(): Parallel LLM Processing with Tibble-Based Experiments (Core Engine)

call_llm_broadcast(): Parallel API calls: Fixed Config, Multiple Messages

call_llm_sweep(): Parallel API calls: Parameter Sweep - Vary One Parameter, Fixed Message

call_llm_compare(): Parallel API calls: Multiple Configs, Fixed Message

setup_llm_parallel(): Setup Parallel Environment for LLM Processing

reset_llm_parallel(): Reset Parallel Environment

Embeddings

parse_embeddings(): Parse Embedding Response into a Numeric Matrix

get_batched_embeddings(): Generate Embeddings in Batches

Utilities

bind_tools(): Bind tools to a config (provider-agnostic)