Metadata-Version: 2.4
Name: tagnify
Version: 0.1.0
Summary: LLM-powered automated data labeling with schema-first, confidence-scored, and local-model ready
Author-email: Maulana Arya Alambana <maulanaaryaw@gmail.com>
License: MIT
Keywords: annotation,classification,confidence-scoring,data-labeling,llm,local-model-ready,machine-learning,nlp,schema-first
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.10
Requires-Dist: httpx>=0.24
Requires-Dist: pydantic>=2.0
Provides-Extra: dev
Requires-Dist: pytest-asyncio>=0.21; extra == 'dev'
Requires-Dist: pytest>=7.0; extra == 'dev'
Description-Content-Type: text/markdown

# Tagnify

LLM-powered automated data labeling — schema-first, confidence-scored, local-model ready.

```python
from tagnify import Tagnify, Schema, Example

schema = Schema(
    labels=["positive", "negative", "neutral"],
    examples=[Example(text="Great product!", label="positive")]
)

tagnify = Tagnify(model="qwen2.5:7b")
result = tagnify.label("This was a disappointing experience.", schema)

print(result.label)       # "negative"
print(result.confidence)  # 0.91
```

## Installation

```bash
pip install tagnify
```

Requires [Ollama](https://ollama.ai) running locally.