| Name | denario JSON |
| Version |
0.1.2
JSON |
| download |
| home_page | None |
| Summary | Modular Automation of Scientific Research with Multi-Agent Systems |
| upload_time | 2025-07-18 14:49:05 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.12 |
| license | GPLv3 |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Denario
[](https://pypi.python.org/pypi/denario) [](https://www.python.org/downloads/) [](https://pypi.python.org/pypi/denario) [](https://www.gnu.org/licenses/gpl-3.0)
Denario is a multiagent system designed to automatize scientific research. Denario implements AI agents with [AG2](https://ag2.ai/) and [LangGraph](https://www.langchain.com/langgraph). The research analysis backend is [cmbagent](https://github.com/CMBAgents/cmbagent). Project under construction.
## Resources
- [Project page](https://astropilot-ai.github.io/DenarioPaperPage/)
- [Documentation](https://denario.readthedocs.io/en/latest/)
- [End-to-end research papers generated with Denario](https://github.com/AstroPilot-AI/DenarioExamplePapers)
## Installation
To install denario, just run
```bash
pip install denario
```
## Get started
Initialize a `Denario` instance and describe the data and tools to be employed.
```python
from denario import Denario, Journal
den = Denario(project_dir="project_dir")
prompt = "Analyze the experimental data stored in /path/to/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.
```python
den.get_idea()
```
Generate the methodology required for working on that idea.
```python
den.get_method()
```
With the methodology setup, perform the required computations and get the plots and results.
```python
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)](https://journals.aps.org/) style.
```python
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:
```python
den.set_method(path_to_the_method_file.md)
```
## App
You can run Denario using a GUI through the [DenarioApp](https://github.com/AstroPilot-AI/DenarioApp).
Test the deployed app in [HugginFace Spaces](nope).
## Build from source
### pip
You will need python 3.12 installed.
Create a virtual environment
```bash
python3 -m venv .venv
```
Activate the virtual environment
```bash
source .venv/bin/activate
```
And install the project
```bash
pip install -e .
```
### uv
You can also install the project using [uv](https://docs.astral.sh/uv/), just running:
```bash
uv sync
```
which will create the virtual environment and install the dependencies and project. Activate the virtual environment if needed with
```bash
source .venv/bin/activate
```
## Contributing
Pull requests are welcome! Feel free to open an issue for bugs, comments, questions and suggestions.
<!-- ## Citation
If you use this library please link this repository and cite [arXiv:2506.xxxxx](arXiv:x2506.xxxxx). -->
## License
[GNU GENERAL PUBLIC LICENSE (GPLv3)](https://www.gnu.org/licenses/gpl-3.0.html)
Raw data
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"author_email": "Boris Bolliet <boris.bolliet@gmail.com>, Francisco Villaescusa-Navarro <villaescusa.francisco@gmail.com>, Pablo Villanueva-Domingo <pablo.villanueva.domingo@gmail.com>",
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"description": "# Denario\n\n[](https://pypi.python.org/pypi/denario) [](https://www.python.org/downloads/) [](https://pypi.python.org/pypi/denario) [](https://www.gnu.org/licenses/gpl-3.0)\n\nDenario is a multiagent system designed to automatize scientific research. Denario implements AI agents with [AG2](https://ag2.ai/) and [LangGraph](https://www.langchain.com/langgraph). The research analysis backend is [cmbagent](https://github.com/CMBAgents/cmbagent). Project under construction.\n\n## Resources\n\n- [Project page](https://astropilot-ai.github.io/DenarioPaperPage/)\n\n- [Documentation](https://denario.readthedocs.io/en/latest/)\n\n- [End-to-end research papers generated with Denario](https://github.com/AstroPilot-AI/DenarioExamplePapers)\n\n## Installation\n\nTo install denario, just run\n\n```bash\npip install denario\n```\n\n## Get started\n\nInitialize a `Denario` instance and describe the data and tools to be employed.\n\n```python\nfrom denario import Denario, Journal\n\nden = Denario(project_dir=\"project_dir\")\n\nprompt = \"Analyze the experimental data stored in /path/to/data.csv using sklearn and pandas. This data includes time-series measurements from a particle detector.\"\n\nden.set_data_description(prompt)\n```\n\nGenerate a research idea from that data specification.\n\n```python\nden.get_idea()\n```\n\nGenerate the methodology required for working on that idea.\n\n```python\nden.get_method()\n```\n\nWith the methodology setup, perform the required computations and get the plots and results.\n\n```python\nden.get_results()\n```\n\nFinally, generate a latex article with the results. You can specify the journal style, in this example we choose the [APS (Physical Review Journals)](https://journals.aps.org/) style.\n\n```python\nfrom denario import Journal\n\nden.get_paper(journal=Journal.APS)\n```\n\nYou 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:\n\n```python\nden.set_method(path_to_the_method_file.md)\n```\n\n## App\n\nYou can run Denario using a GUI through the [DenarioApp](https://github.com/AstroPilot-AI/DenarioApp).\n\nTest the deployed app in [HugginFace Spaces](nope).\n\n## Build from source\n\n### pip\n\nYou will need python 3.12 installed.\n\nCreate a virtual environment\n\n```bash\npython3 -m venv .venv\n```\n\nActivate the virtual environment\n\n```bash\nsource .venv/bin/activate\n```\n\nAnd install the project\n\n```bash\npip install -e .\n```\n\n### uv\n\nYou can also install the project using [uv](https://docs.astral.sh/uv/), just running:\n\n```bash\nuv sync\n```\n\nwhich will create the virtual environment and install the dependencies and project. Activate the virtual environment if needed with\n\n```bash\nsource .venv/bin/activate\n```\n\n## Contributing\n\nPull requests are welcome! Feel free to open an issue for bugs, comments, questions and suggestions.\n\n<!-- ## Citation\n\nIf you use this library please link this repository and cite [arXiv:2506.xxxxx](arXiv:x2506.xxxxx). -->\n\n## License\n\n[GNU GENERAL PUBLIC LICENSE (GPLv3)](https://www.gnu.org/licenses/gpl-3.0.html)\n",
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