What frameworks does Denario use for orchestration?

Denario is built on the AG2 and LangGraph frameworks, which allow it to coordinate multiple specialized agents for different stages of the research process.

Is it possible to intervene in the automated workflow?

Absolutely. Denario supports a hybrid workflow where you can provide your own research ideas, methodologies, or results, and let the AI handle the other stages of the pipeline.

Can I use Denario for specific scientific journals?

Yes, Denario supports multiple journal formatting styles, including American Physical Society (APS) formats, providing complete LaTeX source files.

Does Denario handle data visualization?

Yes, during the results generation stage, Denario executes computational experiments and creates visualizations that are automatically integrated into the final paper.

What are the technical requirements for running Denario?

Denario requires Python 3.12 or higher and API keys from supported providers like Google Vertex AI or OpenAI. It is recommended to install it using the uv package manager.

Denario Research Automator

Name: Denario Research Automator
Author: Microck

byMicrock

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데이터 과학 및 ML

Automates end-to-end scientific research workflows from initial data analysis and hypothesis generation to the production of publication-ready LaTeX manuscripts.

소개

Denario is a sophisticated multiagent AI system designed to streamline the academic research lifecycle by orchestrating specialized agents for complex scientific tasks. Built on the AG2 and LangGraph frameworks, it enables researchers to transform raw datasets into structured research questions, rigorous methodologies, and executed computational experiments. Beyond analysis, Denario automates the production of journal-formatted LaTeX papers, including figure integration and citation management, making it an essential tool for accelerating the pipeline from discovery to publication while maintaining reproducibility.

주요 기능

Publication-ready LaTeX generation for journals like APS
Interactive web-based GUI for visual workflow management
Automated hypothesis generation and methodology development from datasets
Execution of computational experiments and data visualization
Multiagent orchestration for specialized research and writing tasks
81 GitHub stars

사용 사례

Automating the tedious formatting and figure integration requirements for academic submissions
Accelerating the transition from raw experimental data to a formatted research paper
Brainstorming novel research hypotheses and structured methodologies from complex datasets

소개

주요 기능

Publication-ready LaTeX generation for journals like APS
Interactive web-based GUI for visual workflow management
Automated hypothesis generation and methodology development from datasets
Execution of computational experiments and data visualization
Multiagent orchestration for specialized research and writing tasks
81 GitHub stars

사용 사례

Automating the tedious formatting and figure integration requirements for academic submissions
Accelerating the transition from raw experimental data to a formatted research paper
Brainstorming novel research hypotheses and structured methodologies from complex datasets