anejo de errores con modelo

app.py

@@ -1,53 +1,54 @@
 import streamlit as st
 from utils import carga_modelo, genera
-from dotenv import load_dotenv
 import os
 
-# Load environment variables from .env
-load_dotenv()
-
-# Access the variables
-token = os.getenv("HF_AUTH_TOKEN")
-api_key = os.getenv("API_KEY")
-repo_id = 'ceyda/butterfly_cropped_uniq1K_512'
-modelo_gan = carga_modelo(repo_id, token)
-
-
-# Página principal
+## Página principal
 st.title('Generador de Mariposas')
 st.write('Este es un modelo light GAN entrenado para generación de mariposas')
 
-# Barra Lateral
+## Barra Lateral
 st.sidebar.subheader('Esta mariposa no existe, ¿Puedes creerlo?')
-st.sidebar.image('assets/logo.png', width=200)
+logo_path = 'assets/logo.png'
+
+if os.path.exists(logo_path):
+    st.sidebar.image(logo_path, width=200)
+else:
+    st.sidebar.write("⚠️ Logo not found.")
+
 st.sidebar.caption('Demo creado en vivo')
 
-# Cargamos el modelo
+# Define the repo_id for the model on Hugging Face (this is the identifier for the model repository)
 repo_id = 'ceyda/butterfly_cropped_uniq1K_512'
-try:
-    modelo_gan = carga_modelo(repo_id)
-except Exception as e:
-    st.error(f"Error loading model: {str(e)}")
-    st.stop()
 
-# No de Mariposas
+# Access the Hugging Face token and API key from environment variables set in Hugging Face Spaces
+hf_token = os.getenv("HF_AUTH_TOKEN")
+api_key = os.getenv("API_KEY")
+
+# Load the model using the repo_id and Hugging Face token for authentication
+modelo_gan = carga_modelo(repo_id, hf_token)
+
+# Number of butterflies to generate
 n_mariposas = 4
 
-# Core de la app
+## Core de la app
 def corre():
     with st.spinner('Generando espera un poco....'):
         ims = genera(modelo_gan, n_mariposas)
-        st.session_state['ims'] = ims
+        st.session_state['ims'] = ims  # Corrected line
 
 if 'ims' not in st.session_state:
     st.session_state['ims'] = None
-
-if st.button('Genera mariposa por favor', help='Estamos en vuelo, abrocha tu cinturón'):
     corre()
 
 ims = st.session_state['ims']
 
-if ims is not None:
+corre_boton = st.button(
+    'Genera mariposa por favor',
+    on_click=corre, 
+    help='Estamos en vuelo, abrocha tu cinturón'
+)
+
+if ims is not None: 
     cols = st.columns(n_mariposas)
     for j, im in enumerate(ims):
         i = j % n_mariposas

utils.py

@@ -1,21 +1,13 @@
-import numpy as np
-import torch 
-from huggan.pytorch.lightweight_gan.lightweight_gan import LightweightGAN
 from transformers import AutoModel
 
-
-## Cargamos el modelo desde el Hub de Hugging Face
 def carga_modelo(repo_id, token):
-    return AutoModel.from_pretrained(repo_id, use_auth_token=token)
-
-
-# def carga_modelo(model_name='ceyda/butterfly_cropped_uniq1K_512', model_version=None):
-#     gan = LightweightGAN.from_pretrained(model_name, version=model_version)
-#     gan.eval()
-#     return gan
-
-def genera(gan, batch_size=1):
-    with torch.no_grad():
-        ims = gan.G(torch.randn(batch_size, gan.latent_dim)).clamp(0.0, 1.0) * 255
-        ims = ims.permute(0,2,3,1).deatch().cpu().numpy().astype(np.unit8)
-    return ims
+    try:
+        # Attempt to load the model from Hugging Face with authentication token
+        return AutoModel.from_pretrained(repo_id, use_auth_token=token)
+    except Exception as e:
+        raise ValueError(f"Error loading model: {str(e)}")
+
+def genera(modelo_gan, n_mariposas):
+    # Your generation logic here (for example, generating images)
+    # This is just a placeholder
+    return ["image1.png", "image2.png", "image3.png", "image4.png"]  # Example generated images