llmkgext


Namellmkgext JSON
Version 0.0.1 PyPI version JSON
download
home_pagehttps://github.com/8W9aG/llm-kg
SummaryA knowledge graph generator using LLMs.
upload_time2025-07-21 23:24:02
maintainerNone
docs_urlNone
authorWill Sackfield
requires_pythonNone
licenseMIT
keywords kg knowledge graph llm
VCS
bugtrack_url
requirements timefhuman nltk instructor groq pydantic textblob
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # llm-kg

<a href="https://pypi.org/project/llmkg/">
    <img alt="PyPi" src="https://img.shields.io/pypi/v/llmkg">
</a>

A knowledge graph generator using LLMs.

## Dependencies :globe_with_meridians:

Python 3.11.6:

- [timefhuman](https://github.com/alvinwan/timefhuman)
- [nltk](https://www.nltk.org/)
- [instructor](https://python.useinstructor.com/)
- [groq](https://github.com/groq/groq-python)
- [pydantic](https://docs.pydantic.dev/latest/)
- [textblob](https://textblob.readthedocs.io/en/dev/)

## Raison D'ĂȘtre :thought_balloon:

`llm-kg` is a package that uses LLMs to extract knowledge graphs from freeform text.

## Architecture :triangular_ruler:

`llm-kg` calls an LLM using Groq to turn text into a series of triples.

## Installation :inbox_tray:

This is a python package hosted on pypi, so to install simply run the following command:

`pip install llmkgext`

or install using this local repository:

`python setup.py install --old-and-unmanageable`

## Usage example :eyes:

The use of `llmkgext` is entirely through code due to it being a library. It has exactly the same semantics as a requests session:

```python
from llmkgext import extract


triples = extract("Rodrigo Martins Vaz, known as Rodrigo (born 24 May 1971), is a retired Brazilian footballer.")
print(triples)
```

## License :memo:

The project is available under the [MIT License](LICENSE).

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/8W9aG/llm-kg",
    "name": "llmkgext",
    "maintainer": null,
    "docs_url": null,
    "requires_python": null,
    "maintainer_email": null,
    "keywords": "kg, knowledge, graph, llm",
    "author": "Will Sackfield",
    "author_email": "will.sackfield@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/32/76/aaaeffa1557a28255dd96c8a7ef989ceec3dfe59d22aa2fcdffe3309277f/llmkgext-0.0.1.tar.gz",
    "platform": null,
    "description": "# llm-kg\n\n<a href=\"https://pypi.org/project/llmkg/\">\n    <img alt=\"PyPi\" src=\"https://img.shields.io/pypi/v/llmkg\">\n</a>\n\nA knowledge graph generator using LLMs.\n\n## Dependencies :globe_with_meridians:\n\nPython 3.11.6:\n\n- [timefhuman](https://github.com/alvinwan/timefhuman)\n- [nltk](https://www.nltk.org/)\n- [instructor](https://python.useinstructor.com/)\n- [groq](https://github.com/groq/groq-python)\n- [pydantic](https://docs.pydantic.dev/latest/)\n- [textblob](https://textblob.readthedocs.io/en/dev/)\n\n## Raison D'\u00eatre :thought_balloon:\n\n`llm-kg` is a package that uses LLMs to extract knowledge graphs from freeform text.\n\n## Architecture :triangular_ruler:\n\n`llm-kg` calls an LLM using Groq to turn text into a series of triples.\n\n## Installation :inbox_tray:\n\nThis is a python package hosted on pypi, so to install simply run the following command:\n\n`pip install llmkgext`\n\nor install using this local repository:\n\n`python setup.py install --old-and-unmanageable`\n\n## Usage example :eyes:\n\nThe use of `llmkgext` is entirely through code due to it being a library. It has exactly the same semantics as a requests session:\n\n```python\nfrom llmkgext import extract\n\n\ntriples = extract(\"Rodrigo Martins Vaz, known as Rodrigo (born 24 May 1971), is a retired Brazilian footballer.\")\nprint(triples)\n```\n\n## License :memo:\n\nThe project is available under the [MIT License](LICENSE).\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "A knowledge graph generator using LLMs.",
    "version": "0.0.1",
    "project_urls": {
        "Homepage": "https://github.com/8W9aG/llm-kg"
    },
    "split_keywords": [
        "kg",
        " knowledge",
        " graph",
        " llm"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "3276aaaeffa1557a28255dd96c8a7ef989ceec3dfe59d22aa2fcdffe3309277f",
                "md5": "660a42ab500b21ecdd40ed26eb457412",
                "sha256": "bbf5cb0a0dae71932f0f9a56e926e8b00fc5c878347d3c9f63434f482293901f"
            },
            "downloads": -1,
            "filename": "llmkgext-0.0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "660a42ab500b21ecdd40ed26eb457412",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 4620,
            "upload_time": "2025-07-21T23:24:02",
            "upload_time_iso_8601": "2025-07-21T23:24:02.040756Z",
            "url": "https://files.pythonhosted.org/packages/32/76/aaaeffa1557a28255dd96c8a7ef989ceec3dfe59d22aa2fcdffe3309277f/llmkgext-0.0.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-07-21 23:24:02",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "8W9aG",
    "github_project": "llm-kg",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "requirements": [
        {
            "name": "timefhuman",
            "specs": [
                [
                    ">=",
                    "0.1.4"
                ]
            ]
        },
        {
            "name": "nltk",
            "specs": [
                [
                    ">=",
                    "3.9.1"
                ]
            ]
        },
        {
            "name": "instructor",
            "specs": [
                [
                    ">=",
                    "1.10.0"
                ]
            ]
        },
        {
            "name": "groq",
            "specs": [
                [
                    ">=",
                    "0.30.0"
                ]
            ]
        },
        {
            "name": "pydantic",
            "specs": [
                [
                    ">=",
                    "2.11.7"
                ]
            ]
        },
        {
            "name": "textblob",
            "specs": [
                [
                    ">=",
                    "0.19.0"
                ]
            ]
        }
    ],
    "lcname": "llmkgext"
}
        
Elapsed time: 1.58613s