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.

backend/db/conexion.py

@@ -0,0 +1,19 @@
+from src.ConexionSql.Postgres_conexion import PostgresConexion
+from src.Credenciales.postgres_credencial import PostgresCredencial
+from dotenv import load_dotenv
+import os
+from entrypoint import ENV_PATH
+
+# Cargar .env
+load_dotenv(ENV_PATH)
+
+def get_conexion():
+    db_credencial = PostgresCredencial(
+        titulo=os.getenv("DB_TITLE"),
+        user=os.getenv("DB_USER"),
+        password=os.getenv("DB_PASSWORD"),
+        host=os.getenv("DB_HOST"),
+        port=os.getenv("DB_PORT"),
+        dbname=os.getenv("DB_NAME")
+    )
+    return PostgresConexion(db_credencial)