diff --git a/Dockerfile b/Dockerfile
index 3afd607..9d26b02 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -11,9 +11,6 @@ RUN apt-get update && apt-get install -y --no-install-recommends wget gcc libffi
 # Install Python dependencies including redis with hiredis support
 RUN pip install --no-cache-dir -r requirements.txt
 
-# Download and install the Russian language model
-RUN python -m spacy download ru_core_news_md
-
 COPY . .
 
 EXPOSE 8080
diff --git a/handlers/messages_routing.py b/handlers/messages_routing.py
index e60a4a2..df1cc07 100644
--- a/handlers/messages_routing.py
+++ b/handlers/messages_routing.py
@@ -114,19 +114,9 @@ async def messages_routing(msg, state):
             toxic_score = detector(normalized_text)
             toxic_perc = math.floor(toxic_score * 100)
             logger.info(f"\text: {normalized_text}\ntoxic: {toxic_perc}%")
-
-            nospaces_text = text.replace(" ", "")
-            if nospaces_text != text:
-                nospaces_normalized_text = normalize(nospaces_text)
-                nospaces_text_score = detector(nospaces_normalized_text)
-                nospaces_text_perc = math.floor(nospaces_text_score * 100)
-                if check_stopwords(nospaces_normalized_text):
-                    logger.info('stopword detected with no spaces, toxicity +40%')
-                    nospaces_text_perc += 40
-                logger.info(f"\nospaces_text: {nospaces_normalized_text}\nnospaces_toxic: {nospaces_text_perc}%")
-
-                if nospaces_text_score > toxic_score or nospaces_text_perc > 95:
-                    text_perc = nospaces_text_perc
+            if check_stopwords(normalized_text):
+                logger.info('stopword detected with no spaces, toxicity +40%')
+                toxic_perc += 40
 
             await redis.set(f"toxic:{cid}", mid)
             await redis.set(f"toxic:{cid}:{uid}:{mid}", toxic_perc, ex=60 * 60 * 24 * 3)
diff --git a/nlp/stopwords_detector.py b/nlp/stopwords_detector.py
index f5d1573..e6c2600 100644
--- a/nlp/stopwords_detector.py
+++ b/nlp/stopwords_detector.py
@@ -17,7 +17,7 @@ def check_stopwords(text, stopwords):
         bool: True if any stopword is found in the text, False otherwise.
     """
     # Normalize the text by converting it to lower case and splitting into words
-    words = text.lower().split()
+    words = text.replace(' ', '').lower().split()
 
     # Iterate through each word and check for stopwords
     for word in words: