Metadata-Version: 2.4
Name: competencia_mexico
Version: 0.1.1
Summary: Herramientas para análisis de competencia económica, precios, visualización y RAG (FAISS + DeepSeek)
Home-page: https://github.com/IvanParedesR/competencia_mexico
Author: Iván Paredes Reséndiz
Author-email: Iván Paredes Reséndiz <ivanresendiz25@gmail.com>
License: MIT License
        
        Copyright (c) 2025 Iván Paredes Reséndiz
        
        Permission is hereby granted, free of charge, to any person, robot, AI or alien, obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
        
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# competencia_mexico

**Paquete para el análisis de competencia económica, estructuras de mercado, estrategias de precios y recuperación aumentada con RAG**

Este paquete contiene funciones interactivas y automatizadas para facilitar el análisis de datos en economía de la competencia, incluyendo el cálculo de índices clave como el IHH (Índice Herfindahl-Hirschman), el índice de dominancia, simulaciones de colusión en precios, y herramientas para visualizar datos de estadisticas de la autoridad de competencia.

También incorpora funcionalidades para recuperación aumentada de información (RAG) utilizando `FAISS` y el modelo `DeepSeek`, lo que permite responder preguntas basadas en documentos previamente indexados.

Se anexa un instructivo para facilitar su uso. 

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## 🚀 Instalación

### Requisitos previos

- Python 3.7 o superior
- pip

### Instalación local (modo editable)

1. Clona este repositorio o descarga el proyecto.
2. Desde el directorio raíz, ejecuta:

```bash
pip install -e .

