This repository provides Python bindings for llama.cpp and gpt4all, enabling local execution of large language models. It targets developers and researchers seeking to integrate LLM capabilities into Python applications without relying on cloud APIs. The primary benefit is local, private, and cost-effective LLM inference.

How It Works

The project offers Python bindings that interface directly with the llama.cpp C++ library. This allows users to load and run various quantized LLM architectures (like LLaMA, GPT-J, and GPT-Neo) efficiently on local hardware, leveraging CPU or GPU acceleration through llama.cpp's optimized inference engine.

Quick Start & Requirements

• Install via pip: pip install gpt4all
• Requires Python 3.7+ and a compatible C++ compiler for llama.cpp compilation.
• Download models from the GPT4All website.
• See official quick-start: https://github.com/nomic-ai/gpt4all/tree/main/gpt4all-bindings/python

Highlighted Details

• Supports a wide range of quantized LLM architectures.
• Leverages llama.cpp for efficient CPU and GPU inference.
• Enables local, private LLM execution.

Maintenance & Community

This repository is archived. Future development and support are handled by the main nomic-ai/gpt4all repository.

Licensing & Compatibility

The project is released under the MIT License, permitting commercial use and integration into closed-source applications.

Limitations & Caveats

This repository is archived and no longer actively maintained. The pygpt4all PyPI package may diverge from backend model updates. Users are directed to use the gpt4all package for current bindings.