cidadao.ai-backend / CITATION.cff
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feat: clean HuggingFace deployment with essential files only
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cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Silva"
given-names: "Anderson Henrique da"
orcid: "https://orcid.org/0000-0000-0000-0000"
email: "andersonhs27@gmail.com"
affiliation: "Instituto Federal de Educação, Ciência e Tecnologia do Sul de Minas Gerais - Campus Muzambinho"
title: "Cidadão.AI: Multi-Agent AI System for Brazilian Government Transparency Analysis"
version: 1.0.0
doi: 10.5281/zenodo.0000000
date-released: 2025-01-20
url: "https://github.com/anderson-ufrj/cidadao.ai"
repository-code: "https://github.com/anderson-ufrj/cidadao.ai"
license: Apache-2.0
type: software
keywords:
- artificial-intelligence
- transparency
- government
- multi-agent-system
- brazil
- public-data
- corruption-detection
- anomaly-detection
- SDG16
- open-government
- civic-tech
- langchain
- fastapi
- machine-learning
abstract: |
Cidadão.AI is an innovative platform that uses specialized artificial intelligence
to democratize access to Brazilian public data. The system employs a sophisticated
multi-agent architecture to analyze government contracts, bidding processes, public
expenses, and other government documents. It features eight specialized AI agents
working collaboratively to detect anomalies, analyze patterns, and generate
comprehensive reports, contributing directly to SDG 16: Peace, Justice and Strong
Institutions. The platform provides both web interfaces (Gradio and Streamlit) and
a REST API for programmatic access, making government transparency data accessible
to citizens, journalists, researchers, and civil society organizations.
references:
- type: software
authors:
- name: "LangChain Contributors"
title: "LangChain: Building applications with LLMs through composability"
year: 2023
url: "https://github.com/langchain-ai/langchain"
- type: software
authors:
- name: "FastAPI Contributors"
title: "FastAPI: Modern, fast web framework for building APIs"
year: 2023
url: "https://github.com/tiangolo/fastapi"
- type: article
authors:
- family-names: "Vaswani"
given-names: "Ashish"
- family-names: "Shazeer"
given-names: "Noam"
- family-names: "Parmar"
given-names: "Niki"
title: "Attention is All You Need"
journal: "Advances in Neural Information Processing Systems"
volume: 30
year: 2017
- type: data
authors:
- name: "Controladoria-Geral da União"
title: "Portal da Transparência do Governo Federal"
year: 2025
url: "https://portaldatransparencia.gov.br"
preferred-citation:
type: software
authors:
- family-names: "Silva"
given-names: "Anderson Henrique da"
title: "Cidadão.AI: Multi-Agent AI System for Brazilian Government Transparency Analysis"
year: 2025
doi: 10.5281/zenodo.0000000
url: "https://github.com/anderson-ufrj/cidadao.ai"