diff --git a/maryam.py b/maryam.py
index 9711e28e4..ca1e1c3c6 100644
--- a/maryam.py
+++ b/maryam.py
@@ -1,4 +1,3 @@
-#!/usr/bin/env python3
 
 from maryam import __main__
 import sys
diff --git a/maryam/core/util/iris/meta_search_util.py b/maryam/core/util/iris/meta_search_util.py
index ab0793518..f9a3bf323 100644
--- a/maryam/core/util/iris/meta_search_util.py
+++ b/maryam/core/util/iris/meta_search_util.py
@@ -15,9 +15,11 @@
 from math import trunc
 
 class main:
+
 	def __init__(self):
 		self.framework = main.framework
 
+
 	def make_cite(self, url: 'URL string') -> 'cite':
 		urlib = self.framework.urlib(url)
 		path = urlib.path
@@ -40,6 +42,7 @@ def make_cite(self, url: 'URL string') -> 'cite':
 		cite = f"{host}{path}"
 		return cite
 
+
 	def remove_dups(self, res):
 		urls = []
 		new = []
@@ -50,6 +53,7 @@ def remove_dups(self, res):
 				new.append(i)
 		return new
 
+
 	def simple_merge(results) -> 'merging results based on quality of engines':
 		engines_len = len(results)
 		merged = []
@@ -65,14 +69,16 @@ def simple_merge(results) -> 'merging results based on quality of engines':
 
 		return merged
 
+
 	def compute_count_consensus( 
 			e: dict(type=list, help='list of search engines sorted by quality'),
-			l: dict(type=int, help='number of results')) -> 'a list of numbers':
+			l: dict(type=int, help='number of results'),
+		) -> 'a list of numbers':
 		x = len(e)
 		o = {}
 		for i in e:
-			o[i] = trunc(l/x)
-		l -= l - (l%x)
+			o[i] = trunc(l / x)
+		l -= l - (l % x)
 		if l != 0:
 			if l < x:
 				for i in range(l):
diff --git a/maryam/core/util/iris/retriever.py b/maryam/core/util/iris/retriever.py
index cf7d69a21..fcba65d6b 100644
--- a/maryam/core/util/iris/retriever.py
+++ b/maryam/core/util/iris/retriever.py
@@ -1,4 +1,3 @@
-#!/usr/bin/env python3
 """
 OWASP Maryam!
 This program is free software: you can redistribute it and/or modify
@@ -87,7 +86,7 @@ def __init__(
 		lowercase=True,
 		preprocessor=None,
 		tokenizer=None,
-		stop_words="english",
+		stop_words='english',
 		token_pattern=r"(?u)\b\w\w+\b",
 		ngram_range=(1, 2),
 		max_df=1,
@@ -124,11 +123,13 @@ def __init__(
 		)
 		self.vectorizer = vectorizer
 
+
 	def fit(self, df, y=None):
 		self.metadata = df
 		self.tfidf_matrix = self.vectorizer.fit_transform(list(map(' '.join, df["pages"])))
 		return self
 
+
 	def predict(self, query: str) -> 'OrderedDict':
 		"""
 		Compute the top_n closest documents given a query
@@ -160,10 +161,8 @@ def predict(self, query: str) -> 'OrderedDict':
 			table = prettytable.PrettyTable(["rank", "index", "title"])
 			for i in range(len(closest_docs_indices)):
 				index = closest_docs_indices[i]
-				# if self.paragraphs:
-				#	  article_index = self.paragraphs[int(index)]["index"]
-				#	  title = self.metadata.iloc[int(article_index)]["title"]
-				# else:
+
+
 				title = self.metadata.iloc[int(index)]["title"]
 				table.add_row([rank, index, title])
 				rank += 1
diff --git a/maryam/core/util/iris/safe_searcher.py b/maryam/core/util/iris/safe_searcher.py
deleted file mode 100644
index a2d08622f..000000000
--- a/maryam/core/util/iris/safe_searcher.py
+++ /dev/null
@@ -1,82 +0,0 @@
-"""
-OWASP Maryam!
-This program is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-any later version.
-This program is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-GNU General Public License for more details.
-You should have received a copy of the GNU General Public License
-along with this program.  If not, see <http://www.gnu.org/licenses/>.
-"""
-
-from inspect import signature
-
-class main:
-	def __init__(self, engine_q=None):
-		self.framework = main.framework
-
-		if engine_q is None:
-			self._engine_q = [
-					self.framework.google,
-					self.framework.duckduckgo,
-					self.framework.bing,
-					self.framework.startpage,
-					self.framework.dogpile,
-					self.framework.qwant,
-					self.framework.yandex,
-					self.framework.yahoo,
-					self.framework.ask,
-				]
-		else:
-			self._engine_q = engine_q
-
-		self._error_record = []
-
-
-	@property
-	def _get_new_errors(self):
-		new_errors = self.framework._error_stack[len(self._error_record):]
-		self._error_record = self.framework._error_stack
-		return new_errors
-
-	def search(self,  q, engine=None, limit=1, count=15):	
-		if engine is None:
-			engine = self._engine_q.pop(0)
-		else:
-			if engine in self._engine_q:
-				self._engine_q.remove(engine)
-
-		results = None
-
-		while results is None:
-			sig = signature(engine.__init__)
-			if 'limit' in sig.parameters and 'count' in sig.parameters:
-				instance = engine(q, limit=limit, count=count)
-			elif 'limit' in sig.parameters:
-				instance = engine(q, limit=limit)
-			elif 'count' in sig.parameters:
-				instance = engine(q, count=count)
-			else:
-				instance = engine(q)
-
-			instance.run_crawl()
-
-			if hasattr(instance,'results'):
-				results = instance.results
-			else:
-				results = instance.links_with_title
-
-			results = results if len(results)>0 else None
-
-			if any('captcha' in x.lower() or 'missed' in x.lower() for x in self.framework._error_stack):
-				self.framework._reset_error_stack()
-				if len(self._engine_q) != 0:
-					engine = self._engine_q.pop(0)
-				else:
-					self.framework.error('All Engines Exhausted')
-					return 
-
-		return results
diff --git a/maryam/core/util/iris/tf_histogram.py b/maryam/core/util/iris/tf_histogram.py
index d80bab4e4..1a564aa5f 100644
--- a/maryam/core/util/iris/tf_histogram.py
+++ b/maryam/core/util/iris/tf_histogram.py
@@ -17,6 +17,7 @@
 from collections import Counter
 BASEDIR = os.path.abspath(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../'))
 
+
 class main:
 
 	def __init__(self, docs: 'documents', form: 'documet form. e.g html', without_punc=True):
@@ -33,18 +34,22 @@ def __init__(self, docs: 'documents', form: 'documet form. e.g html', without_pu
 		if self.without_punc:
 			self._punc()
 
+
 	def remove_stopwords(self, rest):
 		stops = open(os.path.join(BASEDIR, '../../', 'data', 'stopwords.csv')).read().split(',')
 		self.words = [x for x in self.words if x not in stops and x not in rest]
 
+
 	def _punc(self):
 		self.words = re.findall(r"[\w\-_#]{2,}", self.docs)
 
+
 	def _counter(self, last):
 		""" last: number of terms to show in plot """
 		bow = Counter(self.words)
 		return bow.most_common(last)
 
+
 	def plot_histogram(self, title, last, should_show=False):
 		import pandas as pd
 		import matplotlib.pyplot as plt
diff --git a/maryam/core/util/iris/topic.py b/maryam/core/util/iris/topic.py
index 19cdf9161..477f18a1d 100644
--- a/maryam/core/util/iris/topic.py
+++ b/maryam/core/util/iris/topic.py
@@ -11,13 +11,14 @@
 You should have received a copy of the GNU General Public License
 along with this program.  If not, see <http://www.gnu.org/licenses/>.
 """
-# core/util/iris/topic.py
 # Hatma Suryotrisongko
 
+import os
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
 from sentence_transformers import SentenceTransformer
+BASEDIR = os.path.abspath(os.path.join(os.path.dirname(os.path.realpath(__file__)), '../'))
 
 class main:
 
@@ -25,7 +26,7 @@ def __init__(self, inputfile, filetype, keyword, showcharts, verbose):
 
 		from dask import dataframe as dd
 		import json
-		from gensim.parsing.preprocessing import remove_stopwords
+		self.stops = open(os.path.join(BASEDIR, '../../', 'data', 'stopwords.csv')).read().split(',')
 
 		if verbose == True:
 			print("\n\n DATASET = reading file : " + inputfile)
@@ -42,7 +43,7 @@ def __init__(self, inputfile, filetype, keyword, showcharts, verbose):
 				print("\n\n csv file (before preprocessing) = ")
 				print(tmp4)
 
-			self.corpus = tmp4[0].str.lower().apply(remove_stopwords).to_numpy()
+			self.corpus = tmp4[0].str.lower().apply(self.remove_stopwords).to_numpy()
 
 		elif filetype == "json":
 			with open(inputfile) as json_file:
@@ -55,7 +56,7 @@ def __init__(self, inputfile, filetype, keyword, showcharts, verbose):
 				print(tmp)
 
 			tmp['td'] = tmp['t'] + ' ' + tmp['d']
-			self.corpus = tmp['td'].str.lower().apply(remove_stopwords).to_numpy()
+			self.corpus = tmp['td'].str.lower().apply(self.remove_stopwords).to_numpy()
 
 		else:
 			print('ERROR, only accept csv or json file!')
@@ -73,6 +74,11 @@ def __init__(self, inputfile, filetype, keyword, showcharts, verbose):
 			pd.Series([len(e.split()) for e in self.corpus]).hist()
 			plt.show()
 
+
+	def remove_stopwords(self, text):
+		return ''.join([x for x in text if x not in self.stops])
+
+
 	def run_sklearn_cluster_kmeans(self, selected_pretrained_model, showcharts, verbose):
 
 		from sklearn.cluster import KMeans
diff --git a/maryam/core/util/iris/word_cloud.py b/maryam/core/util/iris/word_cloud.py
deleted file mode 100644
index 6f443af7d..000000000
--- a/maryam/core/util/iris/word_cloud.py
+++ /dev/null
@@ -1,52 +0,0 @@
-"""
-OWASP Maryam!
-This program is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-any later version.
-This program is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-GNU General Public License for more details.
-You should have received a copy of the GNU General Public License
-along with this program.  If not, see <http://www.gnu.org/licenses/>.
-"""
-
-import re
-import os
-from wordcloud import WordCloud
-import matplotlib.pyplot as plt
-
-class main:	
-	def __init__(self):	
-		self.framework = main.framework
-
-	def _remove_url(self, data):
-		return re.sub(r"(http|ftp|https)://([\w_-]+(?:(?:\.[\w_-]+)+))([\w.,@?^=%&:/~+#-]*[\w@?^=%&/~+#-])?", '', data)	
-	
-	def plot_wcloud(self, title, docs: 'documents', form: 'documet form. e.g html', limit: 'number of words', 
-	without_punc=True, remove_stopwords=False, should_show=True):
-		docs = str(docs)
-		docs = self._remove_url(docs)
-		tf = self.framework.tf_histogram(docs, form, without_punc)
-
-		if remove_stopwords:
-			tf.remove_stopwords()
-		bow = tf._counter(limit)
-		cloud_data = ' '.join(i[0] for i in bow)
-
-		if not cloud_data:
-			self.framework.error('NoDataToPrintError.', 'util/iris/word_cloud', 'plot_wcloud')
-			return False
-
-		wcd = WordCloud().generate(cloud_data)
-		plt.imshow(wcd, interpolation='bilinear')
-		plt.axis("off")
-		plt.title(title)
-		filename = os.path.join(self.framework.workspace,title.replace(' ','_')+'.png')
-		plt.savefig(filename, format="png")
-		if should_show:
-			plt.show()
-
-		return filename
-
diff --git a/maryam/modules/iris/iris.py b/maryam/modules/iris/iris.py
index 6e9b2c369..c2e7298e6 100755
--- a/maryam/modules/iris/iris.py
+++ b/maryam/modules/iris/iris.py
@@ -21,7 +21,7 @@
 	'description': 'Iris is a built-in meta search engine.',
 	'comments': ('It should be note that this is a beta version and has many bugs!',),
 	'contributors': 'Aman, Dimitris, Divya, Vikas, Kunal',
-	'sources': ('google', 'bing', 'duckduckgo', 'etools', 'startpage', 'searx', 'yahoo'),
+	'sources': ('google', 'bing', 'duckduckgo', 'etools', 'startpage', 'yahoo'),
 	'options': (
 		('query', None, True, 'Query string', '-q', 'store', str),
 	),
diff --git a/maryam/modules/iris/iris_cluster.py b/maryam/modules/iris/iris_cluster.py
index 054e096c7..05443e4b6 100755
--- a/maryam/modules/iris/iris_cluster.py
+++ b/maryam/modules/iris/iris_cluster.py
@@ -13,11 +13,11 @@
 """
 
 meta = {
-	'name': 'Iris_Cluster',
+	'name': 'Iris Cluster',
 	'author': 'Shaad',
 	'version': '0.1',
 	'description': 'Get Iris Search result and clustered results for your query',
-	'required': ('kneed', 'mlxtend, numpy, sklearn'),
+	'required': ('kneed', 'mlxtend', 'numpy', 'sklearn'),
 	'options': (
 			('query', None, True, 'Query string', '-q', 'store', str),
 		),
@@ -51,7 +51,7 @@ def module_run(self):
 
 	print('\n\nCLUSTER RESULT: ')
 	for index, title in enumerate(output):
-	    print('\n')
-	    print(f"CLUSTER {index+1}")
-	    print(f"TITLE: {title}")
-	    print('  '+'\n  '.join(output[title]))
+		print('\n')
+		print(f"CLUSTER {index+1}")
+		print(f"TITLE: {title}")
+		print('  '+'\n  '.join(output[title]))
diff --git a/maryam/modules/iris/sentiment.py b/maryam/modules/iris/sentiment.py
index 253216270..dc2367da5 100755
--- a/maryam/modules/iris/sentiment.py
+++ b/maryam/modules/iris/sentiment.py
@@ -70,7 +70,7 @@ def module_api(self):
 			return
 		DATA = loads(file.read())
 		if key not in DATA and key != None:
-			self.error("The key doesn't exists", 'module_api', 'iris/sentiment')
+			self.error('The key doesn\'t exists', 'module_api', 'iris/sentiment')
 			return
 		if key != None:
 			DATA = DATA[key]
diff --git a/maryam/modules/iris/topicmodeling.py b/maryam/modules/iris/topicmodeling.py
index 61d6f5d2e..3818e0225 100755
--- a/maryam/modules/iris/topicmodeling.py
+++ b/maryam/modules/iris/topicmodeling.py
@@ -60,4 +60,4 @@ def module_api(self):
 def module_run(self):
 	output = module_api(self)
 	self.output("\n\nOutput = \n")
-	self.output( output )
\ No newline at end of file
+	self.output( output )
diff --git a/requirements b/requirements
index 5b06f8d64..b12bf0c36 100644
--- a/requirements
+++ b/requirements
@@ -1,55 +1,21 @@
 beautifulsoup4
 bertopic
-bs4
 certifi
-charset-normalizer
-click
 cloudscraper
-Cython
 dask
 Flask
-gensim
 huggingface-hub
-Jinja2
-joblib
-locket
 lxml
 matplotlib
-mpmath
 numpy
 packaging
 pandas
-partd
-Pillow
-plotly
-pynndescent
-pyparsing
-python-dateutil
-pytz
-PyYAML
-regex
 requests
-requests-toolbelt
 scikit-learn
-scipy
 sentence-transformers
-sentencepiece
-six
-smart-open
-soupsieve
-sympy
-tenacity
-threadpoolctl
-tokenizers
-toolz
 top2vec
-tqdm
 transformers
 typing-extensions
 umap
 umap-learn
-urllib3
 vaderSentiment
-Werkzeug
-wordcloud
-zipp
diff --git a/setup.py b/setup.py
index 54ce643f7..59f92e715 100644
--- a/setup.py
+++ b/setup.py
@@ -1,4 +1,3 @@
-#!/usr/bin/env python3
 """
 OWASP Maryam!
 
@@ -34,25 +33,27 @@
 	keywords=['OWASP', 'OSINT', 'search-engine', 'social-networks', 'Maryam'],
 	scripts=['bin/maryam'],
 	install_requires=[
-		'requests',
+		'beautifulsoup4',
+		'bertopic',
+		'certifi',
 		'cloudscraper',
-		'bs4',
+		'dask',
+		'Flask',
+		'huggingface-hub',
 		'lxml',
-		'flask',
-		'vaderSentiment',
-		'plotly',
 		'matplotlib',
-		'pandas',
-		'wordcloud',
 		'numpy',
-		'dask',
+		'packaging',
+		'pandas',
+		'requests',
 		'scikit-learn',
-		'scipy',
+		'sentence-transformers',
+		'top2vec',
+		'transformers',
+		'typing-extensions',
 		'umap',
-		'bertopic',
-		'sentence_transformers',
-		'gensim',
-		'top2vec'
+		'umap-learn',
+		'vaderSentiment',
 	],
 	classifiers=[
 		'Programming Language :: Python :: 3.10',