feat: Implement new sales data analysis agents and utilities

- Added Router_de_agentes.py to manage agent interactions for sales data analysis.
- Created Analizador_de_datos_de_ventas.yaml for generating structured text reports from sales data.
- Developed Generador_sql_ventas.yaml for generating SQL queries to analyze sales data.
- Established Router_de_agente.yaml as a routing mechanism for agent requests.
- Compiled centros_disponibles.md listing available sales centers.
- Introduced primera_ejecucion_de_un_agente.py as an example for executing agents.
- Added ver_los_prompts_de_un_agente.py to inspect prompts sent to OpenAI.
- Included service account key for BigQuery access in rag-datasets-reader-sa-key.json.
- Defined schema for sales data in Objeto_ventas.json.
- Implemented utility functions for querying BigQuery in conseguir_datos_bq.py.
- Created data transformation utilities in transformar_datos.py for handling decimal and date formats.

pyproject.toml

@@ -6,6 +6,7 @@ readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
     "agno>=2.1.1",
+    "google-cloud-bigquery>=3.38.0",
     "icecream>=2.1.8",
     "marimo>=0.16.5",
     "openai>=2.1.0",