GPT4Tools is an intelligent system designed to enable conversational interaction with images by automatically selecting, controlling, and utilizing various visual foundation models. It targets users who need to perform image-related tasks within a conversational context, offering a unified interface for diverse visual operations.

How It Works

GPT4Tools leverages a Vicuna-based Large Language Model (LLM) fine-tuned on 71K self-built instruction data. The core approach involves the LLM analyzing conversational content to dynamically decide which visual foundation model (tool) to invoke and how to control it. This self-instructional fine-tuning allows the LLM to learn to use a suite of 22 integrated visual tools, facilitating seamless image manipulation and analysis during conversations.

Quick Start & Requirements

• Install: Clone the repository and install dependencies via pip install -r requirements.txt.
• Prerequisites: Requires downloading Vicuna base models (e.g., lmsys/vicuna-13b-v1.5) and GPT4Tools LoRA weights. Additional visual model weights (e.g., Stable Diffusion, BLIP, ControlNet) may need to be downloaded.
• Resources: The demo script suggests configurations for 1 or 4 GPUs, with specific tool assignments to CUDA devices. Fine-tuning requires DeepSpeed and significant computational resources.
• Links: Project Page, Online Demo, Dataset.

Highlighted Details

• Supports 22 integrated visual tools, including image captioning, VQA, segmentation, inpainting, and ControlNet variations.
• Offers a flexible and extensible architecture allowing users to add new tools or replace existing LLMs.
• Provides 71K self-instructional data for fine-tuning and model adaptation via LoRA.
• Paper accepted at NIPS 2023.

Maintenance & Community

The project is actively updated, with recent releases supporting Vicuna-v1.5 and new demos. Key contributors are listed as authors of the associated paper.

Licensing & Compatibility

The project releases LoRA weights to comply with the LLaMA model license. Compatibility with commercial or closed-source applications would depend on the underlying LLaMA and Vicuna licenses.

Limitations & Caveats

The system relies on specific versions of Vicuna and requires careful management of model and tool weight downloads. The multi-GPU setup advice indicates a significant hardware requirement for optimal performance.