Update app.py

app.py

@@ -4,11 +4,19 @@ import pandas as pd
 import time
 
 # Función para generar el esquema CSV basado en las selecciones del usuario
-def generate_csv(modalities, tasks, progress=gr.Progress()):
+def generate_csv(modalities, vision_tasks, nlp_tasks, audio_tasks, progress=gr.Progress()):
+    tasks = []
+    if "Visión" in modalities:
+        tasks.extend(vision_tasks)
+    if "NLP" in modalities:
+        tasks.extend(nlp_tasks)
+    if "Audio" in modalities:
+        tasks.extend(audio_tasks)
+
     columns = []
     total_steps = len(modalities) * len(tasks)
     progress(0, desc="Iniciando generación del esquema CSV...")
-    for i, (modality, task) in enumerate(zip(modalities, tasks)):
+    for i, (modality, task) in enumerate(zip(modalities * len(tasks), tasks)):
         progress(i / total_steps, desc=f"Procesando {modality} - {task}...")
         time.sleep(1)  # Simulación de procesamiento
         if modality == "Visión" and task == "Detección de Objetos":
@@ -56,6 +64,13 @@ def search_datasets(modalities, progress=gr.Progress()):
     progress(1, desc="Búsqueda de datasets completada.")
     return "\n".join(results)
 
+# Función para seleccionar datasets y agregarlos al campo de URLs
+def select_datasets(selected_datasets, current_urls):
+    selected_datasets = selected_datasets.split("\n")
+    current_urls = current_urls.split("\n") if current_urls else []
+    updated_urls = list(set(current_urls + selected_datasets))
+    return "\n".join(updated_urls)
+
 # Función para procesar datasets seleccionados
 def process_datasets(dataset_urls, progress=gr.Progress()):
     datasets = []
@@ -131,7 +146,7 @@ with gr.Blocks(title="Diseñador de Redes Neuronales Multimodales") as demo:
     # Conexiones de botones a funciones
     generate_csv_btn.click(
         generate_csv,
-        inputs=[modalities, vision_tasks] + [modalities, nlp_tasks] + [modalities, audio_tasks],
+        inputs=[modalities, vision_tasks, nlp_tasks, audio_tasks],
         outputs=csv_output
     )
     search_datasets_btn.click(search_datasets, inputs=[modalities], outputs=datasets_output)