diff --git a/data-computer/swagger.json b/data-computer/swagger.json
index 0ea400c..ab6eb7a 100644
--- a/data-computer/swagger.json
+++ b/data-computer/swagger.json
@@ -3,7 +3,7 @@
 	"info": {
 		"title": "data-computer - Calculs sur fichier corpus compressé",
 		"summary": "Algorithmes de calculs sur un corpus compressé",
-		"version": "2.6.0",
+		"version": "2.7.0",
 		"termsOfService": "https://services.istex.fr/",
 		"contact": {
 			"name": "Inist-CNRS",
diff --git a/data-computer/v1/lda.py b/data-computer/v1/lda.py
index 426a137..9cd999a 100755
--- a/data-computer/v1/lda.py
+++ b/data-computer/v1/lda.py
@@ -51,7 +51,7 @@
     best_topic = {}
     best_proba = 0
     for topic in dico:
-        proba = float(dico[topic]["weight"])
+        proba = float(dico[topic]["topic_weight"])
         if proba>best_proba:
             best_proba = proba
             best_topic = topic
@@ -94,7 +94,7 @@
     else:
         index_without_value.append(i)
 dictionary = corpora.Dictionary(texts) # Create a tf dictionary, but replace text by an id : [ [(id_token,numb_token),...] , [....] ]. The list represent docs of corpus
-dictionary.filter_extremes(no_below=3,no_above=0.8)
+dictionary.filter_extremes(no_below=3,no_above=0.5)
 corpus = [dictionary.doc2bow(text) for text in texts]
 
 try:
@@ -119,13 +119,21 @@
         topic_info = {}
         for topic_id, topic_weight in topics:
             topic_info[f"topic_{topic_id + 1}"] = {}
-            topic_words = [{"word":word, "word_weight":str(word_weight)} for word, word_weight in lda_model.show_topic(topic_id)]
-            topic_info[f"topic_{topic_id + 1}"]["words"] = topic_words
-            topic_info[f"topic_{topic_id + 1}"]["weight"] = str(topic_weight)
+            words = []
+            words_weights = []
+            for word, word_weight in lda_model.show_topic(topic_id):
+                words.append(word) 
+                words_weights.append(str(word_weight))
+            topic_info[f"topic_{topic_id + 1}"]["words"] = words
+            topic_info[f"topic_{topic_id + 1}"]["words_weights"] = words_weights
+            topic_info[f"topic_{topic_id + 1}"]["topic_weight"] = str(topic_weight)
 
         line["value"]={}
         line["value"]["topics"]=topic_info
-        line["value"]["best_topic"]=max_topic(topic_info)
+        try:
+            line["value"]["best_topic"]=max_topic(topic_info)
+        except:
+            line["value"]["best_topic"]="n/a"
         sys.stdout.write(json.dumps(line))
         sys.stdout.write("\n")