Centraliza.AI: A Unified Local AI Model Management Platform to Solve Multi-Engine Storage Fragmentation Issues

Centraliza.AI is an open-source dashboard tool for local AI model management. It supports mainstream inference engines like Ollama, ComfyUI, Llama.cpp, and LM Studio. Using hard link technology, it enables intelligent sharing of model files, solving the problem of storage fragmentation across multiple engines, saving disk space, and providing features such as unified management and intelligent startup.

With the popularization of local AI deployment, the coexistence of multiple engines (Ollama, ComfyUI, Llama.cpp, LM Studio, etc.) leads to duplicate storage of the same model, wasting disk space. This is a core pain point in the current local AI ecosystem.

Centraliza.AI uses the operating system's hard link technology, where multiple paths point to the same physical model file without occupying additional space. Deleting a single reference does not affect others; only when the last hard link is deleted will the data be released. It automatically identifies model files in different engine directories, greatly reducing storage costs.

Adaptive Startup: Selects the optimal engine based on the model format (e.g., GGUF uses Llama.cpp/Ollama, image models use ComfyUI + GPU acceleration), with one-click service startup. Hardware Monitoring: Real-time acquisition of GPU memory and RAM usage, intelligent evaluation of model compatibility, and prompts on whether it can run smoothly.

Integrated Chat Interface: Supports interaction with local models within the dashboard, switching between engines like Ollama/Llama.cpp to compare responses. Easy Deployment: Front-end and back-end separated architecture; on Windows, dependencies are automatically installed via setup.bat, and the service is started via start_app.bat, with cross-platform support.

Suitable for groups such as AI developers (experiment comparison), content creators (unified management of text/image models), enterprise IT administrators (team deployment), and users with limited hardware (maximizing storage utilization), addressing their respective pain points.

Centraliza.AI promotes the integrated development of local AI tools and solves the core problem of storage fragmentation. In the future, it is expected to expand support for more engines, introduce features like version management and team collaboration, and become a core component of local AI infrastructure.