R: Local Large Language Model Inference Engine

# Local Large Language Model Inference Engine

## Documentation for package ‘edgemodelr’ version 0.4.1

- DESCRIPTION file.
- Package NEWS.

## Help Pages

build_chat_prompt | Build chat prompt from conversation history
edge_ask | Ask a question using retrieval-augmented generation
edge_benchmark | Performance benchmarking for model inference
edge_cache_info | Cache size information
edge_chat_completion | Generate a chat completion using the model's native template
edge_chat_stream | Interactive chat session with streaming responses
edge_classify | Classify text into predefined categories
edge_clean_cache | Clean up cache directory and manage storage
edge_completion | Generate text completion using loaded model
edge_cuda_info | Check whether a CUDA backend is installed and active
edge_download_model | Download a GGUF model from Hugging Face
edge_download_url | Download a model from a direct URL
edge_embeddings | Extract text embeddings from a model
edge_extract | Extract structured data from text
edge_extract_batch | Extract structured data from multiple texts
edge_find_gguf_models | Find and prepare GGUF models for use with edgemodelr
edge_find_ollama_models | Find and load Ollama models
edge_free_model | Free model context and release memory
edge_grammar_completion | Generate text constrained by a GBNF grammar
edge_index_documents | Build an embedding index from text documents
edge_install_cuda | Install the CUDA backend for GPU-accelerated inference
edge_install_cuda_toolkit | Install CUDA runtime libraries required for GPU inference
edge_json_grammar | Generate a GBNF grammar for JSON output from a schema
edge_list_models | List popular pre-configured models
edge_load_model | Load a local GGUF model for inference
edge_load_ollama_model | Load an Ollama model by partial SHA-256 hash
edge_map | Apply a prompt template to a vector of texts
edge_model_n_embd | Get the embedding dimension of a loaded model
edge_quick_setup | Quick setup for a popular model
edge_reload_cuda | Activate an installed CUDA backend without restarting R
edge_search | Search an embedding index for relevant chunks
edge_serve | Serve a model as a local OpenAI-compatible API
edge_set_verbose | Control llama.cpp logging verbosity
edge_simd_info | Query SIMD optimization status
edge_similarity | Compute cosine similarity between two embedding vectors
edge_similarity_matrix | Compute a similarity matrix for a set of embeddings
edge_small_model_config | Get optimized configuration for small language models
edge_stream_completion | Stream text completion with real-time token generation
is_valid_model | Check if model context is valid
test_ollama_model_compatibility | Test if an Ollama model blob can be used with edgemodelr