egutierrez
c47b9474f4
- 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.
27 lines
825 B
Python
27 lines
825 B
Python
from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from typing import Optional
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from backend.db.conexion import get_conexion
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from src.TextManager.biblioteca import Biblioteca
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router = APIRouter()
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class BibliotecaIn(BaseModel):
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nombre: str
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descripcion: Optional[str] = ""
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vector_dim: Optional[int] = None
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@router.post("/")
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def crear_biblioteca(biblio: BibliotecaIn):
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try:
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biblioteca = Biblioteca(
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nombre=biblio.nombre,
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descripcion=biblio.descripcion,
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vector_dim=biblio.vector_dim
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)
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conexion = get_conexion()
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modelo = biblioteca.generar_modelo_notas(conexion)
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return {"id": biblioteca.id, "modelo": str(modelo.__name__)}
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except Exception as e:
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raise HTTPException(status_code=400, detail=str(e))
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