diff --git a/main.py b/main.py
index e67e6f2..667d193 100644
--- a/main.py
+++ b/main.py
@@ -24,8 +24,8 @@ from nltk.corpus import stopwords
 from typing import Optional
 #from cleantext import clean
 import re
-model="embeddings/all-mpnet-base-v2"
-entrenamiento="V0.0"
+model="FTv1/all-mpnet-base-v2"
+entrenamiento="V1.0"
 
 
 
@@ -93,7 +93,7 @@ def remove_unwanted(document,stopOK=False,punctuationOK=False,xtrasOK=False, emo
     return document.strip().lower()
 
 def loadmodelEmb(model_name = "embeddings/all-MiniLM-L6-v2",model_kwargs = {'device': 'cpu'}):
-    st = SentenceTransformer(model_name)
+    st = SentenceTransformer(model_name,device='cpu')
     return st
 
 
@@ -138,7 +138,7 @@ def FinderDbs(query,dbs,filtred=1.2):
         Sal = dbt.similarity_search_with_score(query,4)
         for output in Sal:
             if output[0].metadata["id"] in AllData.keys():
-                AllData[output[0].metadata["id"]]["d"]=min([AllData[output[0].metadata["id"]]["d"]-0.1,output[1]-0.1])
+                AllData[output[0].metadata["id"]]["d"]=min([AllData[output[0].metadata["id"]]["d"],output[1]])
             else:
                 AllData[output[0].metadata["id"]]={"d":output[1],"page_content":output[0].page_content}
     #for item in AllData.items():
@@ -177,7 +177,7 @@ def calculate_api(response: Response):
     except:
         filtred = -9.0
     
-    AllData=FinderDbs(query,[db2],filtred)
+    AllData=FinderDbs(query,[db2,db],filtred)
     versionL="_".join([model,entrenamiento])
     if AllData:
         AllData = list(AllData)