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Text Annotation Tool
Build a text annotation tool in Reflex with Python, database-ready workflows, polished UI, and tools for text labeling and NLP annotation.
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Use templateAbout This Template
Build a production-ready text annotation tool with Reflex and Python. This template is designed for AI, data, and NLP teams labeling text for model training and review who need a usable app structure for text labeling, NLP annotation, dataset review, and model evaluation, not a static mockup. The app pattern includes a focused dashboard, searchable tables, detail views, validated forms, status-aware actions, empty and loading states, and database-ready state management. Use it as a starting point for a data annotation tool, NLP text annotation tool, AI annotation tool, and labeling tool while keeping full control of the Python codebase.
Frequently Asked Questions
This Reflex template supports labeling documents, snippets, entities, sentiment, and categories, with an annotation queue carrying task assignment, progress, and review state. Label controls are keyboard-friendly for speed.
Label Studio is general but heavy to customize, and Prodigy is licensed per seat. When your labeling schema is specific, building on this template means the interface matches the task exactly and stays in your repository.
Annotations export through CSV, and because the records are plain Python you can emit JSONL or any format your training pipeline expects. The dataset dashboard shows completion before you export.
The dataset dashboard reports completion rate, agreement, and label distribution, and conflicting annotations surface in a review state for adjudication. Agreement is computed in Python, so you can substitute your own metric.