Does Denario support specific academic journals?

Yes, Denario includes built-in support for American Physical Society (APS) formatting and can be extended to support other journal-specific LaTeX templates.

What LLM providers are required to run Denario?

Denario supports major providers including Google Vertex AI and OpenAI. You will need to configure your API keys as environment variables.

Can I provide my own research ideas to the skill?

Absolutely. While Denario can generate ideas from data, you can also use the `set_idea` and `set_method` functions to provide your own custom research context.

Is there a visual interface for managing projects?

Yes, Denario includes a graphical user interface that can be launched with the command `denario run` for interactive workflow management.

Denario is a multiagent AI system that automates the full scientific research process, including hypothesis generation, methodology development, and LaTeX paper writing.

Denario AI Research Assistant

Name: Denario AI Research Assistant
Author: Weiwei-Mao

byWeiwei-Mao

데이터 과학 및 ML

Automates end-to-end scientific research workflows from data analysis and hypothesis generation to publication-ready LaTeX papers.

소개

Denario is a sophisticated multiagent AI system designed to streamline the entire scientific research lifecycle. Built on the AG2 and LangGraph frameworks, it orchestrates specialized agents to assist researchers with data exploration, hypothesis formation, methodology development, and computational experimentation. It concludes the research pipeline by automatically generating professionally formatted LaTeX manuscripts for academic journals, providing a reproducible and structured approach to modern scientific discovery.

주요 기능

Multiagent orchestration for automated hypothesis and methodology generation
Automated execution of computational experiments and visualization generation
Publication-ready LaTeX paper generation with journal-specific formatting
Seamless integration with Google Vertex AI, OpenAI, and AG2-compatible models
Interactive web-based GUI for managing complex research project lifecycles
0 GitHub stars

사용 사례

Accelerating the transition from raw experimental data to a structured research paper
Automating literature-backed hypothesis generation for new scientific inquiries
Developing and documenting rigorous computational methodologies for complex datasets

소개

주요 기능

Multiagent orchestration for automated hypothesis and methodology generation
Automated execution of computational experiments and visualization generation
Publication-ready LaTeX paper generation with journal-specific formatting
Seamless integration with Google Vertex AI, OpenAI, and AG2-compatible models
Interactive web-based GUI for managing complex research project lifecycles
0 GitHub stars

사용 사례

Accelerating the transition from raw experimental data to a structured research paper
Automating literature-backed hypothesis generation for new scientific inquiries
Developing and documenting rigorous computational methodologies for complex datasets