{ "_id": "6a1df7e11d7bb097a0a5c80b", "Package": "llamaR", "Type": "Package", "Title": "Interface for Large Language Models via 'llama.cpp'", "Version": "0.2.4", "Authors@R": "c(\nperson(\"Yuri\", \"Baramykov\", email = \"lbsbmsu@mail.ru\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0000-7627-4217\")),\nperson(\"Georgi\", \"Gerganov\", role = \"cph\",\ncomment = \"Author of the 'llama.cpp' library included in src/\"))", "Description": "Provides 'R' bindings to 'llama.cpp' for running Large\nLanguage Models ('LLMs') locally with optional 'Vulkan' GPU\nacceleration via 'ggmlR'. Supports model loading, text\ngeneration, 'tokenization', token-to-piece conversion,\n'embeddings' (single and batch), encoder-decoder inference,\nlow-level batch management, chat templates, 'LoRA' adapters,\nexplicit backend/device selection, multi-GPU split, and 'NUMA'\noptimization. Includes a high-level 'ragnar'-compatible\nembedding provider ('embed_llamar'). Built on top of 'ggmlR'\nfor efficient tensor operations.", "License": "MIT + file LICENSE", "URL": "https://github.com/Zabis13/llamaR", "BugReports": "https://github.com/Zabis13/llamaR/issues", "Encoding": "UTF-8", "SystemRequirements": "C++17, GNU make", "VignetteBuilder": "knitr", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "Config/pak/sysreqs": "make", "Repository": "https://zabis13.r-universe.dev", "Date/Publication": "2026-06-01 17:31:00 UTC", "RemoteUrl": "https://github.com/zabis13/llamar", "RemoteRef": "HEAD", "RemoteSha": "529a31f1485c26367f1335d72b120db6750ae6e2", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-06-01 21:04:05 UTC", "User": "root" }, "Author": "Yuri Baramykov [aut, cre] (ORCID:\n),\nGeorgi Gerganov [cph] (Author of the 'llama.cpp' library included in\nsrc/)", "Maintainer": "Yuri Baramykov ", "MD5sum": "58d3e69b659eaf7da5f73b4ee34379f5", "_user": "zabis13", "_type": "src", "_file": "llamaR_0.2.4.tar.gz", "_fileid": 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"llama_state_get_size", "llama_state_load", "llama_state_save", "llama_supports_gpu", "llama_supports_mlock", "llama_supports_mmap", "llama_supports_rpc", "llama_synchronize", "llama_system_info", "llama_time_us", "llama_token_to_piece", "llama_tokenize", "llama_vocab_get_score", "llama_vocab_get_text", "llama_vocab_info", "llama_vocab_is_control", "llama_vocab_is_eog", "llama_vocab_type" ], "_help": [ { "page": "chat_llamar", "title": "Chat with a local model through an ellmer::Chat object", "topics": [ "chat_llamar" ] }, { "page": "chat_llamar_stop", "title": "Stop the server spawned by chat_llamar()", "topics": [ "chat_llamar_stop" ] }, { "page": "embed_llamar", "title": "Embedding provider for ragnar / standalone use", "topics": [ "embed_llamar" ] }, { "page": "llama_backend_devices", "title": "List available backend devices", "topics": [ "llama_backend_devices" ] }, { "page": "llama_batch_free", "title": "Free a llama batch allocated with 'llama_batch_init()'", "topics": [ "llama_batch_free" ] }, { "page": "llama_batch_init", "title": "Initialise a llama batch", "topics": [ "llama_batch_init" ] }, { "page": "llama_chat_apply_template", "title": "Apply chat template to messages", "topics": [ "llama_chat_apply_template" ] }, { "page": "llama_chat_builtin_templates", "title": "List built-in chat templates", "topics": [ "llama_chat_builtin_templates" ] }, { "page": "llama_chat_template", "title": "Get model's built-in chat template", "topics": [ "llama_chat_template" ] }, { "page": "llama_detokenize", "title": "Detokenize token IDs back to text", "topics": [ "llama_detokenize" ] }, { "page": "llama_embed_batch", "title": "Batch embeddings for multiple texts", "topics": [ "llama_embed_batch" ] }, { "page": "llama_embeddings", "title": "Extract embeddings for a text", "topics": [ "llama_embeddings" ] }, { "page": "llama_encode", "title": "Encode tokens using the encoder (encoder-decoder models only)", "topics": [ "llama_encode" ] }, { "page": "llama_free_context", "title": "Free an inference context", "topics": [ "llama_free_context" ] }, { "page": "llama_free_model", "title": "Free a loaded model", "topics": [ "llama_free_model" ] }, { "page": "llama_gen_begin", "title": "Begin a streaming (token-by-token) generation", "topics": [ "llama_gen_begin" ] }, { "page": "llama_gen_end", "title": "Finish a streaming generation", "topics": [ "llama_gen_end" ] }, { "page": "llama_gen_next", "title": "Pull the next chunk of a streaming generation", "topics": [ "llama_gen_next" ] }, { "page": "llama_generate", "title": "Generate text from a prompt", "topics": [ "llama_generate" ] }, { "page": "llama_generate_batch", "title": "Generate completions for multiple prompts in parallel", "topics": [ "llama_generate_batch" ] }, { "page": "llama_get_embeddings", "title": "Get all output token embeddings as a matrix", "topics": [ "llama_get_embeddings" ] }, { "page": "llama_get_embeddings_ith", "title": "Get embeddings for the i-th token in the batch", "topics": [ "llama_get_embeddings_ith" ] }, { "page": "llama_get_embeddings_seq", "title": "Get pooled embeddings for a sequence", "topics": [ "llama_get_embeddings_seq" ] }, { "page": "llama_get_logits", "title": "Get logits from the last decode step", "topics": [ "llama_get_logits" ] }, { "page": "llama_get_logits_ith", "title": "Get logits for a specific token position", "topics": [ "llama_get_logits_ith" ] }, { "page": "llama_get_model", "title": "Get the model associated with a context", "topics": [ "llama_get_model" ] }, { "page": "llama_get_verbosity", "title": "Get current verbosity level", "topics": [ "llama_get_verbosity" ] }, { "page": "llama_hf_cache_clear", "title": "Clear the model cache", "topics": [ "llama_hf_cache_clear" ] }, { "page": "llama_hf_cache_dir", "title": "Get the cache directory for downloaded models", "topics": [ "llama_hf_cache_dir" ] }, { "page": "llama_hf_cache_info", "title": "Show information about the model cache", "topics": [ "llama_hf_cache_info" ] }, { "page": "llama_hf_download", "title": "Download a GGUF model from Hugging Face", "topics": [ "llama_hf_download" ] }, { "page": "llama_hf_list", "title": "List GGUF files in a Hugging Face repository", "topics": [ "llama_hf_list" ] }, { "page": "llama_load_model", "title": "Load a GGUF model file", "topics": [ "llama_load_model" ] }, { "page": "llama_load_model_hf", "title": "Load a model directly from Hugging Face", "topics": [ "llama_load_model_hf" ] }, { "page": "llama_lora_apply", "title": "Apply a LoRA adapter to context", "topics": [ "llama_lora_apply" ] }, { "page": "llama_lora_clear", "title": "Remove all LoRA adapters from context", "topics": [ "llama_lora_clear" ] }, { "page": "llama_lora_load", "title": "Load a LoRA adapter", "topics": [ "llama_lora_load" ] }, { "page": "llama_lora_remove", "title": "Remove a LoRA adapter from context", "topics": [ "llama_lora_remove" ] }, { "page": "llama_max_devices", "title": "Get maximum number of devices", "topics": [ "llama_max_devices" ] }, { "page": "llama_memory_breakdown_print", "title": "Print memory breakdown by device", "topics": [ "llama_memory_breakdown_print" ] }, { "page": "llama_memory_can_shift", "title": "Check if the KV cache supports shifting", "topics": [ "llama_memory_can_shift" ] }, { "page": "llama_memory_clear", "title": "Clear the KV cache", "topics": [ "llama_memory_clear" ] }, { "page": "llama_memory_seq_add", "title": "Shift token positions in a sequence", "topics": [ "llama_memory_seq_add" ] }, { "page": "llama_memory_seq_cp", "title": "Copy a sequence in the KV cache", "topics": [ "llama_memory_seq_cp" ] }, { "page": "llama_memory_seq_div", "title": "Integer-divide token positions in a sequence", "topics": [ "llama_memory_seq_div" ] }, { "page": "llama_memory_seq_keep", "title": "Keep only one sequence in the KV cache", "topics": [ "llama_memory_seq_keep" ] }, { "page": "llama_memory_seq_pos_range", "title": "Get position range for a sequence", "topics": [ "llama_memory_seq_pos_range" ] }, { "page": "llama_memory_seq_rm", "title": "Remove tokens from a sequence in the KV cache", "topics": [ "llama_memory_seq_rm" ] }, { "page": "llama_model_info", "title": "Get model metadata", "topics": [ "llama_model_info" ] }, { "page": "llama_model_meta", "title": "Get all model metadata as a named character vector", "topics": [ "llama_model_meta" ] }, { "page": "llama_model_meta_val", "title": "Get a single model metadata value by key", "topics": [ "llama_model_meta_val" ] }, { "page": "llama_n_batch", "title": "Get logical batch size", "topics": [ "llama_n_batch" ] }, { "page": "llama_n_ctx", "title": "Get context window size", "topics": [ "llama_n_ctx" ] }, { "page": "llama_n_ctx_seq", "title": "Get per-sequence context window size", "topics": [ "llama_n_ctx_seq" ] }, { "page": "llama_n_seq_max", "title": "Get maximum number of sequences", "topics": [ "llama_n_seq_max" ] }, { "page": "llama_n_threads", "title": "Get number of threads for single-token generation", "topics": [ "llama_n_threads" ] }, { "page": "llama_n_threads_batch", "title": "Get number of threads for batch processing", "topics": [ "llama_n_threads_batch" ] }, { "page": "llama_n_ubatch", "title": "Get physical micro-batch size", "topics": [ "llama_n_ubatch" ] }, { "page": "llama_new_context", "title": "Create an inference context", "topics": [ "llama_new_context" ] }, { "page": "llama_numa_init", "title": "Initialize NUMA optimization", "topics": [ "llama_numa_init" ] }, { "page": "llama_perf", "title": "Get performance statistics", "topics": [ "llama_perf" ] }, { "page": "llama_perf_print", "title": "Print performance statistics to the console", "topics": [ "llama_perf_print" ] }, { "page": "llama_perf_reset", "title": "Reset performance counters", "topics": [ "llama_perf_reset" ] }, { "page": "llama_pooling_type", "title": "Get pooling type", "topics": [ "llama_pooling_type" ] }, { "page": "llama_serve_openai", "title": "Serve an OpenAI-compatible HTTP API for a local model", "topics": [ "llama_serve_openai" ] }, { "page": "llama_set_abort_callback", "title": "Set or clear the abort callback", "topics": [ "llama_set_abort_callback" ] }, { "page": "llama_set_causal_attn", "title": "Set causal attention mode", "topics": [ "llama_set_causal_attn" ] }, { "page": "llama_set_threads", "title": "Set the number of threads for a context", "topics": [ "llama_set_threads" ] }, { "page": "llama_set_verbosity", "title": "Set logging verbosity level", "topics": [ "llama_set_verbosity" ] }, { "page": "llama_set_warmup", "title": "Set warmup mode", "topics": [ "llama_set_warmup" ] }, { "page": "llama_state_get_size", "title": "Get the size of the serialized context state in bytes", "topics": [ "llama_state_get_size" ] }, { "page": "llama_state_load", "title": "Load context state from file", "topics": [ "llama_state_load" ] }, { "page": "llama_state_save", "title": "Save context state to file", "topics": [ "llama_state_save" ] }, { "page": 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