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Modular Automation of Scientific Research with Multi-Agent Systems

Project description

Denario

Version Python Version PyPI - Downloads License: GPL v3 Ask DeepWiki

Denario is a multiagent system designed to automatize scientific research. Denario implements AI agents with AG2 and LangGraph. The research analysis backend is cmbagent. Project under construction.

Resources

Installation

To install denario create a virtual environment and pip install it. We recommend using python3.12:

python -m venv Denario_env
source Denario_env/bin/activate
pip install denario

Get started

Initialize a Denario instance and describe the data and tools to be employed.

from denario import Denario

den = Denario(project_dir="project_dir")

prompt = """
Analyze the experimental data stored in data.csv using sklearn and pandas.
This data includes time-series measurements from a particle detector.
"""

den.set_data_description(prompt)

Generate a research idea from that data specification.

den.get_idea()

Generate the methodology required for working on that idea.

den.get_method()

With the methodology setup, perform the required computations and get the plots and results.

den.get_results()

Finally, generate a latex article with the results. You can specify the journal style, in this example we choose the APS (Physical Review Journals) style.

from denario import Journal

den.get_paper(journal=Journal.APS)

You can also manually provide any info as a string or markdown file in an intermediate step, using the set_idea, set_method or set_results methods. For instance, for providing a file with the methodology developed by the user:

den.set_method(path_to_the_method_file.md)

App

You can run Denario using a GUI through the DenarioApp.

Test the deployed app in HugginFace Spaces.

Build from source

pip

You will need python 3.12 installed. Download the package:

git clone https://github.com/AstroPilot-AI/Denario.git
cd Denario

Create and activate the virtual environment

python3 -m venv Denario_venv
source Denario_venv/bin/activate

Install the package

pip install -e .

uv

You can also install the project using uv, just running:

uv sync

which will create the virtual environment and install the dependencies and project. Activate the virtual environment if needed with

source .venv/bin/activate

Contributing

Pull requests are welcome! Feel free to open an issue for bugs, comments, questions and suggestions.

License

GNU GENERAL PUBLIC LICENSE (GPLv3)

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