Open-AutoGLM (Phone Agent) is an AI-powered mobile automation framework that uses vision-language models to understand phone screens and execute user tasks through automated touch, swipe, and text input operations. The system works by repeatedly capturing device screenshots, sending them to a vision model (AutoGLM-Phone-9B or compatible API), parsing the model's decision into actionable commands, and executing those commands via platform-specific debugging tools (ADB for Android, HDC for HarmonyOS, WebDriverAgent for iOS). The architecture employs a device factory pattern to abstract platform differences behind a unified interface, an OpenAI-compatible model client with streaming and performance metrics, and a command-based action handler that supports tap, type, swipe, launch, back, home, long press, and takeover operations. The repository is structured as both a CLI application and a Python library, with comprehensive configuration for 50+ Android apps, 60+ HarmonyOS apps, and 100+ iOS apps, along with bilingual system prompts (Chinese/English), configurable timing parameters, and callback hooks for sensitive operation confirmation and manual intervention. Notable features include remote debugging support, verbose step-by-step execution with model thinking output, and integration with third-party model hosting services.

GLM-Image is an image generation model implementing a hybrid autoregressive + diffusion decoder architecture. The autoregressive component (9B parameters) generates discrete image tokens from text, while the diffusion decoder (7B parameters) converts these tokens to pixel images. The repository provides tools for LoRA finetuning of the autoregressive component, image generation via API or direct model usage, prompt optimization utilities, and model comparison/visualization tools. Entry points include finetune_lora.py for training, glm_image_cli.py for API-based generation, and compare.py/plot_loss.py for evaluation and monitoring.