feat: Implement text manager API and database connection

- Added `text_manager.py` to handle the creation of text libraries via FastAPI.
- Introduced database connection management in `conexion.py` using PostgreSQL credentials from environment variables.
- Created abstract base class `EmbedderABC` in `Base_Embedder.py` for embedding models.
- Developed `OpenAIEmbedder` class to generate embeddings using OpenAI's API.
- Implemented `OpenAIEmbedderModel` and repository pattern for managing OpenAI embedders in `Openai_embedder_mmr.py`.
- Established `Biblioteca` class for managing text libraries and their associated notes in `biblioteca.py`.
- Created SQLAlchemy models and mappers for `Biblioteca` and `Nota` in `biblioteca_mmr.py` and `notas_biblioteca_mmr.py`.
- Added functionality for dynamic table generation for notes associated with libraries.
- Included comprehensive methods for adding, retrieving, and managing notes and libraries in their respective repositories.

entrypoint/init_db.py

@@ -7,6 +7,8 @@ from src.Credenciales.postgres_credencial import PostgresCredencial  # Asegúrat
 from src.Credenciales.postgres_credencial_mmr import PostgresCredencialModel
 from src.ApiKeys.openai_apikey_mmr import OpenAICredencialModel
 from src.Llms.Modelos.Openai_model_mmr import ModeloOpenAIConfigModel
+from src.TextManager.biblioteca_mmr import BibliotecaModel
+from src.Llms.Embedders.Openai_embedder_mmr import OpenAIEmbedderModel
 
 from dotenv import load_dotenv
 import os