Create app.py

app.py

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+# Importar bibliotecas necesarias
+import numpy as np
+import gradio as gr
+import faiss
+from sentence_transformers import SentenceTransformer
+from datasets import Dataset
+
+# Cargar el modelo de embeddings
+model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
+
+# Cargar embeddings precalculados
+embeddings_np = np.load("kdrama_embeddings.npy")
+
+# Crear un índice FAISS para búsqueda eficiente
+dimension = embeddings_np.shape[1]
+index = faiss.IndexFlatL2(dimension)
+index.add(embeddings_np)
+
+# Función para recomendar K-Dramas similares
+def recommend_kdramas(title, k=5):
+    title_indices = [i for i, t in enumerate(kdramas['title']) if title.lower() in t.lower()]
+    if not title_indices:
+        return f"No se encontraron títulos similares a '{title}'."
+    query_embedding = embeddings_np[title_indices[0]].reshape(1, -1)
+    distances, similar_indices = index.search(query_embedding, k + 1)
+    recommendations = []
+    for i in similar_indices[0][1:]:
+        recommended_title = kdramas["title"][i]
+        recommended_type = kdramas["type"][i] if "type" in kdramas.features else "Unknown"
+        recommended_genres = kdramas["genres"][i] if "genres" in kdramas.features else "Unknown"
+        recommendations.append(
+            f"### {recommended_title}\n"
+            f"- **Tipo**: {recommended_type}\n"
+            f"- **Géneros**: {recommended_genres}\n"
+        )
+    return "\n".join(recommendations)
+
+# Crear la interfaz de Gradio
+def kdrama_recommender_interface(title, k):
+    return recommend_kdramas(title, k)
+
+interface = gr.Interface(
+    theme=gr.themes.Citrus(),
+    fn=kdrama_recommender_interface,
+    inputs=[
+        gr.Textbox(label="Ingresa el título de un K-Drama"),
+        gr.Radio(choices=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], value=5, label="Número de recomendaciones") 
+    ],
+    outputs=gr.Markdown(label="K-Dramas recomendados"),
+    title="Recomendador de K-Dramas",
+    description="Ingresa el título de un K-Drama y recibe recomendaciones similares, indicando si son series o películas y sus géneros.",
+    examples=[["Vincenzo", 5], ["Crash Landing on You", 3], ["Itaewon Class", 4]],
+    allow_flagging="never",
+    css=".gradio-container { background: linear-gradient(to right, #ff7e5f, #feb47b); }"
+)
+
+# Lanzar la interfaz
+interface.launch()