Can Denario write papers in specific journal formats?

Yes, it supports specific journal formatting styles such as APS (American Physical Society) and generates complete, publication-ready LaTeX source files.

Do I need a local LaTeX installation to use this skill?

For paper generation, you should have a TeX distribution installed locally or use the provided Docker deployment which includes a pre-configured LaTeX environment.

What LLM providers does Denario support?

Denario supports multiple providers including Google Vertex AI and OpenAI, as well as any service compatible with the AG2 or LangGraph frameworks.

Is Denario suitable for complex data analysis?

Yes, it is specifically designed for complex analysis, using specialized agents to execute computational experiments and create visualizations based on your data descriptions.

Denario is a multiagent AI system that automates the entire scientific research process, including hypothesis generation, experimental analysis, and manuscript writing.

Denario Scientific Research Assistant

Name: Denario Scientific Research Assistant
Author: Sologa

bySologa

데이터 과학 및 ML

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

소개

Denario is a comprehensive multiagent AI system designed to streamline scientific workflows by orchestrating specialized agents for hypothesis development, methodology planning, computational experimentation, and scholarly writing. Built on AG2 and LangGraph frameworks, it allows researchers to transition seamlessly from raw datasets to formatted journal papers, supporting major publication styles like APS while ensuring reproducible and structured research outcomes through automated agent orchestration.

주요 기능

Automated hypothesis generation from raw research datasets
Publication-ready LaTeX manuscript generation for major journals
0 GitHub stars
Structured methodology development and research planning
Execution of computational experiments and data visualization
Multiagent orchestration using AG2 and LangGraph frameworks

사용 사례

Executing complex data analysis workflows with integrated literature context
Generating novel research questions and hypotheses from time-series or experimental data
Automating the drafting of academic papers in specific journal formats like APS

소개

주요 기능

Automated hypothesis generation from raw research datasets
Publication-ready LaTeX manuscript generation for major journals
0 GitHub stars
Structured methodology development and research planning
Execution of computational experiments and data visualization
Multiagent orchestration using AG2 and LangGraph frameworks

사용 사례

Executing complex data analysis workflows with integrated literature context
Generating novel research questions and hypotheses from time-series or experimental data
Automating the drafting of academic papers in specific journal formats like APS