GPT4All

Stale
GitHub C++ MIT

Description

Run Local LLMs on Any Device. Open-source and available for commercial use. Provides fully offline local inference and chat for AI agents.

Key Features

  • Fully offline local inference - No API calls or GPU required, run LLMs privately on everyday laptops and desktops
  • Cross-platform desktop app - Native installers for Windows, macOS, and Linux, download and run immediately
  • Python SDK integration - Wraps llama.cpp via gpt4all Python package, load models and inference in a few lines of code
  • LocalDocs private document Q&A - Chat privately with your local documents, data never leaves your machine
  • GGUF model format support - Based on llama.cpp GGUF format with multiple quantization options (Q4_0, Q4_1, etc.)
  • Vulkan GPU acceleration - Supports NVIDIA and AMD GPU-accelerated inference via Vulkan for faster generation

Use Cases

💡 Privacy-sensitive conversations, running LLMs fully offline to ensure no data leakage in air-gapped environments
💡 Edge device AI application development, deploying and testing local language models on resource-constrained devices
💡 Private document Q&A, combining LocalDocs for offline retrieval and question-answering on private files
💡 Local inference backend for AI agents, providing cloud-free LLM capabilities for agent systems
💡 Educational use, experiencing and understanding LLM mechanics at zero cost on personal computers

Tags

python llm agent chatbot tools desktop

Categories

💬 Chat UI

Quick Start

# Install Python SDK
pip install gpt4all

# Load model and inference
from gpt4all import GPT4All

# Download and load model (auto-downloads 4.66GB file on first run)
model = GPT4All("Meta-Llama-3-8B-Instruct.Q4_0.gguf")

# Chat in a session
with model.chat_session():
    print(model.generate("How can I run LLMs on my laptop?", max_tokens=1024))

# Or use the desktop app: download installer from https://gpt4all.io, install and start chatting
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