DashAISoftware/dashAI

dashAI: an interactive platform for training, evaluating and deploying AI models

What it solves

dashAI provides a graphical toolbox for the end-to-end lifecycle of state-of-the-art AI models, simplifying the process of training, evaluating, and deploying them without requiring extensive manual coding for every step.

How it works

It operates as a server-based application with a web-based graphical interface. Users can install it via desktop installers (CPU-only) or via PyPI for GPU acceleration (NVIDIA CUDA or AMD ROCm). It supports running LLMs via llama-cpp-python (GGUF format) and integrates with PyTorch for model operations. The backend is built with Python and manages data and experiments through a database with Alembic migrations.

Who it’s for

AI practitioners, researchers, and developers who want a visual interface to manage their AI model workflows—from training to deployment—across different hardware configurations (CPU, NVIDIA, or AMD GPUs).

Highlights

  • Multi-platform support: Available as standalone desktop installers for Windows, macOS (Apple Silicon), and Linux.
  • GPU Acceleration: Supports NVIDIA CUDA and AMD ROCm for high-performance computing.
  • LLM Integration: Built-in support for GGUF/Llama, Mistral, and Qwen models via llama-cpp-python.
  • Flexible Deployment: Can be run as a local Python package, a standalone app, or within Docker containers.

Related

  • Project
    coulsontl/ai-toolbox

    A cross-platform desktop app for centrally managing configurations, providers, and prompts for multiple AI programming assistants and CLI tools.

  • Project
    microsoft/responsible-ai-toolbox

    A suite of model and data exploration tools that enable developers to identify errors, assess fairness, and interpret AI model predictions for more responsible deployment.

  • Project
    Comfy-Org/ComfyUI

    A modular, node-based AI engine for visual professionals to create complex workflows for generating images, video, audio, and 3D models with precise parameter control.

  • Project
    mudler/LocalAI

    An open-source AI engine that lets you run LLMs, vision, audio, and image models locally on any hardware with drop-in OpenAI-compatible APIs.

  • Project
    AISBench/benchmark

    A model evaluation tool based on OpenCompass that provides accuracy and performance benchmarking for both local and service-based AI models across text and multimodal tasks.