by AlbanPerli · Agent Tool · ★ 79
Seamless integration between Python and LLM generations. With Noema, you can control the model and choose the path it will follow. This framework aims to enable developers to use LLMs as thought interpreters, not as a source of truth. Noema is built on the shoulders of llama.cpp and guidance. Installation Install llama-cpp-python using the correct backend. Basic: python from Noema import Create a subject (LLM) Subject("../Models/EXAONE-3.5-2.4B-Instruct-Q4KM.gguf", verbose=True) # Llama cpp model @Noema def think(task): """ You are a simple thinker. You have a task to perform.
| Stars | 79 |
| Forks | 0 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 63.2282392226109/100 |
| Open Issues | 1 |
| Last Updated | 2026-01-26 |
| Created | 2024-10-15 |
| Platforms | python |
| Est. Tokens | ~401k |
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Noema-Declarative-AI is A declarative way to control LLMs.. It is categorized as a Agent Tool with 79 GitHub stars.
Noema-Declarative-AI is primarily written in Python. It covers topics such as ai, ai-agent, ai-agent-framework.
You can find installation instructions and usage details in the Noema-Declarative-AI GitHub repository at github.com/AlbanPerli/Noema-Declarative-AI. The project has 79 stars and 0 forks, indicating an active community.
Noema-Declarative-AI is released under the Apache-2.0 license, making it free to use and modify according to the license terms.