Denario is a multiagent AI system designed to automate scientific research pipelines, covering everything from data analysis to LaTeX paper publication.

Can I use my own research methodology?

Absolutely. While Denario can generate methodologies automatically, it also allows you to provide custom methodologies via Markdown files for the AI to follow.

Which LLMs are compatible with this research skill?

Denario supports Google Vertex AI, OpenAI, and other LLM providers compatible with the AG2 and LangGraph frameworks.

Does Denario support LaTeX formatting?

Yes, it generates publication-ready manuscripts in LaTeX format, including support for specific journal styles such as the American Physical Society (APS).

Does Denario provide a visual interface?

Yes, Denario includes a web-based GUI that can be launched using the 'denario run' command for easier project management.

Denario Scientific Research

Name: Denario Scientific Research
Author: pur3v4d3r

bypur3v4d3r

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데이터 과학 및 ML

Automates the entire scientific research lifecycle from data analysis and hypothesis generation to publication-ready LaTeX manuscripts.

소개

Denario is an advanced multiagent AI skill designed for researchers and scientists to streamline the end-to-end research process. By orchestrating specialized agents through AG2 and LangGraph, it facilitates data description, hypothesis generation, methodology development, computational experimentation, and final paper formatting in journal-specific LaTeX styles. It bridges the gap between raw data and academic publication, ensuring reproducibility and efficiency in complex scientific workflows while supporting both fully automated and hybrid manual-AI research pipelines.

주요 기능

1 GitHub stars
Web-based GUI for interactive research workflow management
Execution of computational experiments and generation of data visualizations
Multiagent orchestration for specialized hypothesis, analysis, and writing tasks
Automated research question and hypothesis generation from raw datasets
Publication-ready LaTeX manuscript generation for journals like APS

사용 사례

Drafting formatted academic papers directly from experimental findings
Automating computational analysis pipelines and experimental visualization
Accelerating literature reviews and hypothesis formulation for new datasets

소개

주요 기능

1 GitHub stars
Web-based GUI for interactive research workflow management
Execution of computational experiments and generation of data visualizations
Multiagent orchestration for specialized hypothesis, analysis, and writing tasks
Automated research question and hypothesis generation from raw datasets
Publication-ready LaTeX manuscript generation for journals like APS

사용 사례

Drafting formatted academic papers directly from experimental findings
Automating computational analysis pipelines and experimental visualization
Accelerating literature reviews and hypothesis formulation for new datasets