Update app.py

app.py

@@ -1,7 +1,31 @@
 import gradio as gr
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+import numpy as np
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Carga el modelo
+model = SentenceTransformer('Maite89/Roberta_finetuning_semantic_similarity_stsb_multi_mt')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+# Función para obtener embeddings del modelo
+def get_embeddings(sentences):
+    embeddings = model.encode(sentences, show_progress_bar=False)
+    return np.array(embeddings)
+
+# Función para comparar las sentencias
+def compare(source_sentence, compare_sentence):
+    # Calcula la similitud
+    embeddings = get_embeddings([source_sentence, compare_sentence])
+    similarity = float(cosine_similarity(embeddings[0].reshape(1, -1), embeddings[1].reshape(1, -1))[0][0])  # Convert the numpy.float32 to Python float
+    
+    return similarity
+
+# Define las interfaces de entrada y salida de Gradio
+iface = gr.Interface(
+    fn=compare, 
+    inputs=["text", "text"], 
+    outputs="number",
+    live=True
+)
+
+# Inicia la interfaz de Gradio
 iface.launch()