InternGPT is an open-source multimodal AI framework designed to extend large language models beyond text interactions into visual reasoning and image manipulation tasks. The system integrates conversational AI with computer vision models so users can interact with images, videos, and visual environments through natural language instructions. Unlike traditional chat systems that rely solely on text prompts, InternGPT allows users to interact with visual content using both language and nonverbal signals such as pointing or highlighting objects within images. The framework connects multiple specialized AI models that perform tasks such as object detection, segmentation, captioning, and visual editing while coordinating them through a central conversational interface. This architecture enables the system to plan actions, execute visual operations, and return results in a coherent dialogue with the user.
Features
- Multimodal interaction combining language models with computer vision systems
- Support for visual tasks such as object detection, segmentation, and editing
- Integration of multiple specialized models coordinated through a chat interface
- Interactive visual manipulation using language and pointing instructions
- Modular architecture allowing integration of additional AI vision tools
- Framework for building multimodal AI assistants capable of visual reasoning