Update app.py

app.py

@@ -1,7 +1,7 @@
 #***************************************************************************
 #Importing Libraries
 #***************************************************************************
-import os, sys, warnings, torch, json, csv, warnings, joblib, uuid, re, unicodedata, numpy
+import os, sys, warnings, torch, json, csv, warnings, joblib, uuid, re, unicodedata, numpy, faiss
 os.environ["TF_ENABLE_ONEDNN_OPTS"] = "0"
 import streamlit as st
 import datetime as dt
@@ -22,6 +22,24 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 # Token privado desde variable de entorno
 HF_TOKEN = os.environ.get("HF_TOKEN")
 
+#***************************************************************************
+#Loading FAISS Vec DB
+#***************************************************************************
+REPO_ID = "hazutecuhtli/mori_faiss_full"
+
+# Descarga de archivos privados
+faiss_path = hf_hub_download(repo_id=REPO_ID, filename="mori.faiss", repo_type="dataset", token=TOKEN)
+ids_path   = hf_hub_download(repo_id=REPO_ID, filename="mori_ids.npy", repo_type="dataset", token=TOKEN)
+meta_path  = hf_hub_download(repo_id=REPO_ID, filename="mori_metas.json", repo_type="dataset", token=TOKEN)
+
+# Carga de FAISS y metadatos
+index = faiss.read_index(faiss_path)
+ids = np.load(ids_path)
+with open(meta_path, "r", encoding="utf-8") as f:
+    metas = json.load(f)
+
+print(f"Índice cargado con {index.ntotal} vectores.")
+
 #***************************************************************************
 # Sidebar controls for generation params
 #***************************************************************************