diff --git a/main.py b/main.py
index 2f745c9..6e94f03 100644
--- a/main.py
+++ b/main.py
@@ -24,12 +24,23 @@ from nltk.corpus import stopwords
 from typing import Optional
 #from cleantext import clean
 import re
-from langid.langid import LanguageIdentifier
-from langid.langid import  model as modellangid
+from pathlib import Path
+import json
+#from langid.langid import LanguageIdentifier
+#from langid.langid import  model as modellangid
 import time
 model="Modelo_embedding_Mexico_Puebla/all-mpnet-base-v2/model"
 entrenamiento="V1.3"
 
+def extractConfig(nameModel="Modelo_embedding_Mexico_Puebla",relPath="./conf/experiment_config.json",dataOut="train_dataset_pos"):
+    configPath=Path(relPath)
+    with open(configPath, 'r', encoding='utf-8') as file:
+        config = json.load(file)[nameModel]
+
+    Output= Path(config[dataOut])
+    return Output
+
+
 
 
 class CustomEmbedding(Embeddings, BaseModel,):
@@ -100,12 +111,12 @@ def loadmodelEmb(model_name = "embeddings/all-MiniLM-L6-v2",model_kwargs = {'dev
     return st
 
 
-def loadCopysAndData(pathsqlite="/opt/web2py/applications/MotorAngela/databases/storage.sqlite"):
+def loadCopysAndData(pathsqlite=pathDb):
     con = sqlite3.connect(pathsqlite)
     copies_df = pd.read_sql_query("SELECT * from copies WHERE intentionality IS NOT NULL", con)
     copiesT = copies_df
     copiesT=copiesT[["copy_message","id","name","intentionality"]]
-    print(copiesT)
+    #print(copiesT)
     data = copiesT 
     #print(data)
     B=DataFrameLoader(data,page_content_column="copy_message")
@@ -116,8 +127,7 @@ def loadCopysAndData(pathsqlite="/opt/web2py/applications/MotorAngela/databases/
 
 def makeFaissdb(documents,folder_path,embedding):
     try:
-        db=FAISS.load_local(folder_path=folder_path,embeddings=embedding)
-            
+        db=FAISS.load_local(folder_path=folder_path,embeddings=embedding) 
     except:
         db = FAISS.from_documents(documents, embedding)
         FAISS.save_local(db,folder_path=folder_path)
@@ -131,7 +141,7 @@ emb2=CustomEmbedding()
 db=makeFaissdb(documents,"Copies3",emb2)
 db2=makeFaissdb(documents2,"Intentionality3",emb2)
 #db3=makeFaissdb(documents2,"nameshf",hf)
-identifier = LanguageIdentifier.from_modelstring(modellangid, norm_probs=True)
+#identifier = LanguageIdentifier.from_modelstring(modellangid, norm_probs=True)