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by monarch-initiative · LLM Plugin · ★ 1.0k
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OntoGPT Introduction OntoGPT is a Python package for extracting structured information from text with large language models (LLMs), instruction prompts, and ontology-based grounding. For more details, please see the full documentation. Quick Start OntoGPT runs on the command line, though there's also a minimal web app interface (see section below). Ensure you have Python 3.10 or greater installed. Install with : Set your OpenAI API key: See the list of all OntoGPT commands: Try a simple example of information extraction: OntoGPT will retrieve the necessary ontologies and output results to the command line. Your output will provide all extracted objects under the heading . Web Application There is a bare bones web application for running OntoGPT and viewing results. First, install the required dependencies with
| Stars | 1,006 |
| Forks | 122 |
| Language | Jupyter Notebook |
| Category | LLM Plugin |
| License | BSD-3-Clause |
| Quality Score | 68.8415297195158/100 |
| Open Issues | 80 |
| Last Updated | 2026-09-10 |
| Created | 2023-01-03 |
| Est. Tokens | ~17k |
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ontogpt is LLM-based ontological extraction tools, including SPIRES. It is categorized as a LLM Plugin with 1.0k GitHub stars.
ontogpt is primarily written in Jupyter Notebook. It covers topics such as ai, chat-gpt, data-modeling.
You can find installation instructions and usage details in the ontogpt GitHub repository at github.com/monarch-initiative/ontogpt. The project has 1.0k stars and 122 forks, indicating an active community.
ontogpt is released under the BSD-3-Clause license, making it free to use and modify according to the license terms.
The top alternatives to ontogpt on Agent Skills Hub include spacy-llm, free-ai-resources-x, ruby_llm. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
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