llama-cpp-python provides a Python interface for the llama.cpp library, enabling the execution of large language models with hardware acceleration. It functions as a GGUF model loader and a structured text generator capable of running inference servers and multimodal runtimes for processing both text and image inputs.
The project distinguishes itself through a local inference server that exposes model capabilities via an OpenAI-compatible web API. It supports advanced execution techniques including speculative decoding, weight quantization, and layer-based GPU offloading to manage memory across system RAM and VRAM.
The library covers a broad range of AI capabilities, including text completion, embedding generation, and the enforcement of structured outputs via JSON schemas or formal grammars. It also provides infrastructure for tool use through external function calling and manages model extensions via LoRA adapter injection.
Users can fetch model files directly from Hugging Face and maintain model state persistence for resuming generation.
