LLMR

• New provider "llamacpp": llm_config("llamacpp", model) runs an installed model, starting its server on first use and stopping it when R exits. Chat, streaming, structured output, tools, log-probabilities, and embeddings work as for hosted providers. thinking = FALSE turns off the reasoning step of models such as Qwen3. For embedding models, task = adds the model's task prefix and dimensions = truncates to a trained size. With api_url, a llama.cpp server the user runs is used instead.
• Token-level functions for local models: llm_next_token() returns the next-token distribution (the top tokens, or the whole vocabulary) after a chat or a raw prompt; llm_continue() continues a reply whose beginning the user writes, any number of times, sampling from the model's full distribution unless told otherwise; llm_score() gives the log-probability of each token of a text the model did not write; llm_choice_probs() compares the probabilities of several options; llm_tokenize(), llm_detokenize(), and llm_render_template() expose the tokenizer and the exact text the model reads. Each result records the model, the sha256 of its file, the llama.cpp build, the device, and the context.
• LLMR now imports processx, which supervises the local servers, and requires curl 5.0.0 or later, whose multi_download() resumes interrupted downloads.

Other changes

• parse_embeddings() returns rows in the order of the response's index fields when the provider reports them.