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@allen2c allen2c released this 26 Jul 12:58
· 6 commits to main since this release

Release v0.1.1 - Initial Release

πŸŽ‰ First Public Release

Welcome to the first release of ner-agent - a simple, language-agnostic Named Entity Recognition (NER) agent powered by Large Language Models!

✨ Key Features

  • 🌍 Multilingual Support: Works with English, Chinese, Japanese, Korean, French, German, Russian, Spanish, and more
  • 🏷️ Comprehensive Entity Types: Recognizes 6 main entity categories:
    • PERSON - People and fictional characters
    • NORP - Nationalities, religions, political groups, languages
    • LOCATION - Geopolitical entities, facilities, places
    • DATETIME - Dates, times, periods, ages
    • NUMERIC - Numbers, money, quantities, percentages
    • PROPER_NOUN - Events, works, laws, products, organizations
  • πŸš€ Easy Integration: Simple async Python API
  • οΏ½οΏ½ Well Tested: 100+ comprehensive test cases across multiple languages

πŸ“¦ Installation

pip install ner-agent

πŸ’» Quick Start

import asyncio
from ner_agent import NerAgent

async def main():
    agent = NerAgent()
    text = "Elon Musk visited Tesla's Gigafactory in Austin on March 15, 2024, announcing a 20% increase."
    result = await agent.run(text)
    for entity in result.entities:
        print(f"{entity.name}: {entity.value}")

asyncio.run(main())

πŸ”§ Technical Details

  • Python: 3.11+ required
  • Dependencies: openai, openai-agents, pydantic (>=2), str-or-none
  • License: MIT
  • Default Model: gpt-4.1-nano (configurable)

οΏ½οΏ½ Test Coverage

The release includes extensive test cases covering:

  • Multiple languages (EN, ZH, JA, KO, ES, FR, DE, RU)
  • Various entity types and edge cases
  • Overlapping entities and repeated mentions
  • Complex date/time formats
  • Currency and numeric expressions
  • Proper nouns including laws, events, and products

πŸ”— Links

πŸ™ Acknowledgments

Thanks to the open-source community and the openai-agents project for making this possible.

Full Changelog: v0.1.0...v0.1.1