faq.R
In localLLM: Running Local LLMs with 'llama.cpp' Backend

## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = FALSE
)

## -----------------------------------------------------------------------------
# install.packages("localLLM", type = "source")
# # or a specific GitHub release:
# remotes::install_github("EddieYang211/localLLM@v1.4.1", subdir = "localLLM")

## -----------------------------------------------------------------------------
# library(localLLM)
# install_localLLM()

## -----------------------------------------------------------------------------
# # Force reinstall
# install_localLLM(force_reinstall = TRUE)
# 
# # Verify installation
# lib_is_installed()

## -----------------------------------------------------------------------------
# cache_root <- tools::R_user_dir("localLLM", which = "cache")
# models_dir <- file.path(cache_root, "models")
# unlink(models_dir, recursive = TRUE, force = TRUE)

## -----------------------------------------------------------------------------
# # Download with browser or wget, then:
# model <- model_load("/path/to/downloaded/model.gguf")

## -----------------------------------------------------------------------------
# cached <- list_cached_models()
# print(cached)

## -----------------------------------------------------------------------------
# # Get token from https://huggingface.co/settings/tokens
# set_hf_token("hf_your_token_here")
# 
# # Now download should work
# model <- model_load("https://huggingface.co/private/model.gguf")

## -----------------------------------------------------------------------------
# hw <- hardware_profile()
# cat("Available RAM:", round(hw$ram_total / 1e9, 1), "GB\n")

## -----------------------------------------------------------------------------
# ctx <- context_create(model, n_ctx = 512)  # Smaller context

## -----------------------------------------------------------------------------
# # Instead of n_ctx = 32768, try:
# ctx <- context_create(model, n_ctx = 4096)

## -----------------------------------------------------------------------------
# hw <- hardware_profile()
# print(hw$gpu)

## -----------------------------------------------------------------------------
# install_localLLM(force_cpu = TRUE)

## -----------------------------------------------------------------------------
# # Offload fewer layers to GPU
# model <- model_load("model.gguf", n_gpu_layers = 20)

## -----------------------------------------------------------------------------
# # Default (verbosity = 1): warnings only — hardware limits, context size notes
# model <- model_load("model.gguf")
# 
# # Fully silent loading
# model <- model_load("model.gguf",  verbosity = 0)
# ctx   <- context_create(model,     verbosity = 0)

## -----------------------------------------------------------------------------
# messages <- list(
#   list(role = "user", content = "Your question")
# )
# prompt <- apply_chat_template(model, messages)
# result <- generate(ctx, prompt)

## -----------------------------------------------------------------------------
# result <- generate(ctx, prompt, clean = TRUE)
# # or
# result <- quick_llama("prompt", clean = TRUE)

## -----------------------------------------------------------------------------
# result <- quick_llama("prompt", max_tokens = 500)

## -----------------------------------------------------------------------------
# result <- quick_llama("prompt", seed = 42)

## -----------------------------------------------------------------------------
# model <- model_load("model.gguf", n_gpu_layers = 999)

## -----------------------------------------------------------------------------
# ctx <- context_create(model, n_ctx = 512)

## -----------------------------------------------------------------------------
# results <- quick_llama(c("prompt1", "prompt2", "prompt3"))

## -----------------------------------------------------------------------------
# ctx <- context_create(
#   model,
#   n_ctx = 2048,
#   n_seq_max = 10  # Allow 10 parallel sequences
# )

## -----------------------------------------------------------------------------
# # List available Ollama models
# list_ollama_models()
# 
# # Load via Ollama reference
# model <- model_load("ollama:model-name")

## -----------------------------------------------------------------------------
# # Check installation status
# lib_is_installed()
# 
# # Check hardware
# hardware_profile()
# 
# # List cached models
# list_cached_models()
# 
# # List Ollama models
# list_ollama_models()
# 
# # Clear model cache
# cache_dir <- file.path(tools::R_user_dir("localLLM", "cache"), "models")
# unlink(cache_dir, recursive = TRUE)
# 
# # Force reinstall backend (re-runs GPU detection)
# install_localLLM(force_reinstall = TRUE)