Clarity TagFlow

The intelligent, local-first image tagging and AI dataset curation powerhouse.

Clarity TagFlow is a modern desktop application designed to streamline the process of tagging images for Machine Learning datasets, Stable Diffusion training, and digital asset management. Built with a strict focus on privacy, speed, and optimization, it runs state-of-the-art AI models entirely on your local machine.

🚀 Project Status: ~85% Complete! All major bugs have been squashed, and video playback is now fully operational. We are currently optimizing performance before the next massive architectural leap.

💬 We Need Your Feedback! Do you miss an old feature that was removed? Is there something you don't like, or an improvement you're dying to see? Leave a comment and let us know!

🛠️ System Requirements

• OS: Windows / Linux

• Runtime: Java 21 (Note: Moving to native binaries soon!)

• AI Acceleration: Microsoft Visual C++ Redistributable (for ONNX Runtime on Windows)

• Tested Hardware: Fully tested and verified smooth on laptop RTX 5080 configurations.

🌟 Key Features

🤖 Local AI Powerhouse

• Privacy First: No images or data are ever uploaded to the cloud. All processing happens 100% offline.

• Multi-Model Support: Seamlessly switch between JoyTag (SOTA) and various WD14 tagging models (ConvNext, SwinV2, Eva02) to get the most accurate results for your specific content.

• Smart Thresholding: Fine-tune confidence thresholds to control exactly how strict the AI is when applying tags.

⚡ Accelerated Workflow

• Batch Processing: Auto-tag entire folders of images in minutes. Choose to Append new tags or Overwrite existing ones completely.

• Smart Autocomplete: Type faster with a context-aware autocomplete system that learns from your current dataset and standard tag libraries.

• Sidecar Compatibility: Reads and writes standard .txt sidecar files, ensuring seamless compatibility with Kohya_ss, OneTrainer, and other major training tools.

🎨 Modern Experience

• Sleek Dark UI: A refined, eye-friendly interface designed for long, focused dataset curation sessions.

• Visual Feedback: Features a "breathing" AI status indicator to let you know exactly when the system is processing.

• Drag & Drop: Easily reorder tags or drag new images directly into your active workflow.

🛡️ Control & Safety

• Global Blacklist: Automatically filter out unwanted tags (e.g., sensitive terms or specific formatting errors) across your entire dataset.

• Session Memory: Newly added AI tags are highlighted in Cyan, making it incredibly easy to review changes before committing to a save.

🚀 What's New & Improved

• Fixed Video Playback: The underlying issues causing intermittent video playback failures have been completely resolved.

• Total Bug Purge: Fixed all known memory leaks and stability quirks. The gallery navigation bug (where deleting an image reset you to page one) remains permanently fixed.

• Smart Booru Downloader: Automatically fetches associated tags when downloading from Booru sites, establishing an immediate 80-90% accuracy baseline.

• Seamless Generation Setup: The generation panel auto-starts in the background. No more manual configuration via .bat files.

• In-App Image Generation: Direct support for generating images right inside your tagging workflow.

⚠️ Current Known Issues & Immediate Fixes

• Gemma 4 Support: We are aware of the current issues regarding Gemma 4 integration. A dedicated compatibility fix is actively being worked on and will be released shortly.

🔮 The Grand Blueprint: Moving to Rust & Beyond

We are officially planning a massive architectural evolution, moving away from Java and rewriting the application core in Rust. This transition is all about native optimization, blistering speed, and breaking down dependencies.

Here is what the Rust-powered future of Clarity TagFlow looks like:

• Native Cross-OS Performance: Moving to Rust unlocks a highly optimized, beautifully integrated native UI with seamless compatibility across Windows and Linux.

• Built-in Model & LoRA Training: Train your models and LoRAs directly within the app. Features a live visual training preview so you can monitor progress in real-time and know your model is turning out perfectly.

• All-in-One Image & Video Generation: Full, native image and video generation support built directly into the UI. Say goodbye to configuring complex, bloated ComfyUI workflows.

• Zero-Dependency Local LLM: We are eliminating the need for external tools like Ollama or LM Studio. The local LLM engine will be completely embedded out of the box.

• In-App Civitai Integration: Browse, search, and download Civitai resources directly inside the application—no more manual downloads or directory headaches.

• Interactive VR Anime Companions: Introducing a built-in VR anime character for interactive roleplaying. The AI will dynamically control the avatar, express distinct emotions, and react in real-time.

• External Engine Integration: Building the foundation for the embedded LLM to broadcast and connect with external 3D applications and game engines.