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/api/v1/endpoints/text_manager.py

@@ -0,0 +1,26 @@
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+from typing import Optional
+from backend.db.conexion import get_conexion
+from src.TextManager.biblioteca import Biblioteca
+
+router = APIRouter()
+
+class BibliotecaIn(BaseModel):
+    nombre: str
+    descripcion: Optional[str] = ""
+    vector_dim: Optional[int] = None
+
+@router.post("/")
+def crear_biblioteca(biblio: BibliotecaIn):
+    try:
+        biblioteca = Biblioteca(
+            nombre=biblio.nombre,
+            descripcion=biblio.descripcion,
+            vector_dim=biblio.vector_dim
+        )
+        conexion = get_conexion()
+        modelo = biblioteca.generar_modelo_notas(conexion)
+        return {"id": biblioteca.id, "modelo": str(modelo.__name__)}
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e))