diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..ed8ebf5
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+__pycache__
\ No newline at end of file
diff --git a/engine.py b/engine.py
index 9fe7495..6c28233 100644
--- a/engine.py
+++ b/engine.py
@@ -1,73 +1,73 @@
 from simpful import *
 
-FS = FuzzySystem(show_banner=False)
+def fuzzy_system(release_year_param, runtime_param, seasons_param, genres_param, emotions_param):
 
-# Define fuzzy sets for the variable
-# RELEASE_YEAR
-release_year_newer = TriangleFuzzySet(-20, -20, 0, term="newer")
-release_year_similar = TriangleFuzzySet(-20, 0, 20, term="similar")
-release_year_older = TriangleFuzzySet(0, 20, 20, term="older")
+    FS = FuzzySystem(show_banner=False)
 
-FS.add_linguistic_variable("RELEASE_YEAR",
-                           LinguisticVariable([release_year_newer, release_year_similar, release_year_older],
-                                              universe_of_discourse=[-136, 136]))
+    # Define fuzzy sets for the variable
+    # RELEASE_YEAR
+    release_year_newer = TriangleFuzzySet(-20, -20, 0, term="newer")
+    release_year_similar = TriangleFuzzySet(-20, 0, 20, term="similar")
+    release_year_older = TriangleFuzzySet(0, 20, 20, term="older")
 
-# RUNTIME
-runtime_shorter = TriangleFuzzySet(-90, -90, 0, term="shorter")
-runtime_similar = TriangleFuzzySet(-90, 0, 90, term="similar")
-runtime_longer = TriangleFuzzySet(0, 90, 90, term="longer")
+    FS.add_linguistic_variable("RELEASE_YEAR",
+                            LinguisticVariable([release_year_newer, release_year_similar, release_year_older],
+                                                universe_of_discourse=[-136, 136]))
 
-FS.add_linguistic_variable("RUNTIME", LinguisticVariable([runtime_shorter, runtime_similar, runtime_longer],
-                                                         universe_of_discourse=[-476, 476]))
+    # RUNTIME
+    runtime_shorter = TriangleFuzzySet(-90, -90, 0, term="shorter")
+    runtime_similar = TriangleFuzzySet(-90, 0, 90, term="similar")
+    runtime_longer = TriangleFuzzySet(0, 90, 90, term="longer")
 
-# SEASONS
-seasons_less = TriangleFuzzySet(-5, -5, 0, term="less")
-seasons_similar = TriangleFuzzySet(-5, 0, 5, term="similar")
-seasons_more = TriangleFuzzySet(0, 5, 5, term="more")
+    FS.add_linguistic_variable("RUNTIME", LinguisticVariable([runtime_shorter, runtime_similar, runtime_longer],
+                                                            universe_of_discourse=[-476, 476]))
 
-FS.add_linguistic_variable("SEASONS", LinguisticVariable([seasons_less, seasons_similar, seasons_more],
-                                                         universe_of_discourse=[-84, 84]))
+    # SEASONS
+    seasons_less = TriangleFuzzySet(-5, -5, 0, term="less")
+    seasons_similar = TriangleFuzzySet(-5, 0, 5, term="similar")
+    seasons_more = TriangleFuzzySet(0, 5, 5, term="more")
 
-# GENRES
-genres_different = TriangleFuzzySet(0, 0, 0.5, term="different")
-genres_similar = TriangleFuzzySet(0, 0.5, 1, term="similar")
-genres_same = TriangleFuzzySet(0.5, 1, 1, term="same")
+    FS.add_linguistic_variable("SEASONS", LinguisticVariable([seasons_less, seasons_similar, seasons_more],
+                                                            universe_of_discourse=[-84, 84]))
 
-FS.add_linguistic_variable("GENRES", LinguisticVariable([genres_different, genres_similar, genres_same],
-                                                        universe_of_discourse=[0, 1]))
+    # GENRES
+    genres_different = TriangleFuzzySet(0, 0, 0.5, term="different")
+    genres_similar = TriangleFuzzySet(0, 0.5, 1, term="similar")
+    genres_same = TriangleFuzzySet(0.5, 1, 1, term="same")
 
-# EMOTIONS
-emotions_different = TriangleFuzzySet(0, 0, 0.5, term="different")
-emotions_similar = TriangleFuzzySet(0, 0.5, 1, term="similar")
-emotions_same = TriangleFuzzySet(0.5, 1, 1, term="same")
+    FS.add_linguistic_variable("GENRES", LinguisticVariable([genres_different, genres_similar, genres_same],
+                                                            universe_of_discourse=[0, 1]))
 
-FS.add_linguistic_variable("EMOTIONS", LinguisticVariable([emotions_different, emotions_similar, emotions_same],
-                                                          universe_of_discourse=[0, 1]))
+    # EMOTIONS
+    emotions_different = TriangleFuzzySet(0, 0, 0.5, term="different")
+    emotions_similar = TriangleFuzzySet(0, 0.5, 1, term="similar")
+    emotions_same = TriangleFuzzySet(0.5, 1, 1, term="same")
 
-# RECOMMENDATION
-low_recommendation = TriangleFuzzySet(0, 0, 50, term="low_recommendation")
-medium_recommendation = TriangleFuzzySet(0, 50, 100, term="medium_recommendation")
-high_recommendation = TriangleFuzzySet(0, 100, 100, term="high_recommendation")
-FS.add_linguistic_variable("RECOMMENDATION",
-                           LinguisticVariable([low_recommendation, medium_recommendation, high_recommendation],
-                                              universe_of_discourse=[0, 200]))
+    FS.add_linguistic_variable("EMOTIONS", LinguisticVariable([emotions_different, emotions_similar, emotions_same],
+                                                            universe_of_discourse=[0, 1]))
 
-# RULES
-RULE1 = "IF (RELEASE_YEAR IS older) AND (RUNTIME IS longer) AND (SEASONS IS more) THEN (RECOMMENDATION IS low_recommendation)"
-RULE2 = "IF (EMOTIONS IS different) AND (GENRES IS different) THEN (RECOMMENDATION IS low_recommendation)"
-RULE3 = "IF (RELEASE_YEAR IS newer) AND (RUNTIME IS similar) AND (SEASONS IS less) THEN (RECOMMENDATION IS medium_recommendation)"
-RULE4 = "IF (EMOTIONS IS similar) AND (GENRES IS similar) THEN (RECOMMENDATION IS medium_recommendation)"
-RULE5 = "IF (RELEASE_YEAR IS similar) AND (RUNTIME IS similar) AND (SEASONS IS similar) AND (EMOTIONS IS same) AND (GENRES IS same) THEN (RECOMMENDATION IS high_recommendation)"
-# Z regułami trzeba eksperymentować, można porównywać ze scorem dla sprawdzania skuteczności
+    # RECOMMENDATION
+    low_recommendation = TriangleFuzzySet(0, 0, 50, term="low_recommendation")
+    medium_recommendation = TriangleFuzzySet(0, 50, 100, term="medium_recommendation")
+    high_recommendation = TriangleFuzzySet(0, 100, 100, term="high_recommendation")
+    FS.add_linguistic_variable("RECOMMENDATION",
+                            LinguisticVariable([low_recommendation, medium_recommendation, high_recommendation],
+                                                universe_of_discourse=[0, 200]))
 
-FS.add_rules([RULE1, RULE2, RULE3, RULE4, RULE5])
+    # # RULES
+    # RULE1 = "IF (RELEASE_YEAR IS older) AND (RUNTIME IS longer) AND (SEASONS IS more) THEN (RECOMMENDATION IS low_recommendation)"
+    # RULE2 = "IF (EMOTIONS IS different) AND (GENRES IS different) THEN (RECOMMENDATION IS low_recommendation)"
+    # RULE3 = "IF (RELEASE_YEAR IS newer) AND (RUNTIME IS similar) AND (SEASONS IS less) THEN (RECOMMENDATION IS medium_recommendation)"
+    # RULE4 = "IF (EMOTIONS IS similar) AND (GENRES IS similar) THEN (RECOMMENDATION IS medium_recommendation)"
+    # RULE5 = "IF (RELEASE_YEAR IS similar) AND (RUNTIME IS similar) AND (SEASONS IS similar) AND (EMOTIONS IS same) AND (GENRES IS same) THEN (RECOMMENDATION IS high_recommendation)"
+    # # Z regułami trzeba eksperymentować, można porównywać ze scorem dla sprawdzania skuteczności
 
-# FS.set_variable("RELEASE_YEAR", -12.0)
-# FS.set_variable("RUNTIME", -10.0)
-# FS.set_variable("SEASONS", -2.0)
-# FS.set_variable("GENRES", 50.0)
-# FS.set_variable("EMOTIONS", 1.0)
-#
-# print(FS.inference(["RECOMMENDATION"]))
+    # RULES
+    RULE1 = f"IF (NOT (RELEASE_YEAR IS {release_year_param})) AND (NOT (RUNTIME IS {runtime_param})) AND (NOT (SEASONS IS {seasons_param})) THEN (RECOMMENDATION IS low_recommendation)"
+    RULE2 = f"IF (NOT (EMOTIONS IS {emotions_param})) AND (NOT (GENRES IS {genres_param})) THEN (RECOMMENDATION IS low_recommendation)"
+    RULE3 = f"IF (NOT (RELEASE_YEAR IS {release_year_param})) AND (RUNTIME IS {runtime_param}) AND (NOT (SEASONS IS {seasons_param})) THEN (RECOMMENDATION IS medium_recommendation)"
+    RULE4 = f"IF (EMOTIONS IS {emotions_param}) AND (GENRES IS {genres_param}) THEN (RECOMMENDATION IS medium_recommendation)"
+    RULE5 = f"IF (RELEASE_YEAR IS {release_year_param}) AND (RUNTIME IS {runtime_param}) AND (SEASONS IS {seasons_param}) AND (EMOTIONS IS {emotions_param}) AND (GENRES IS {genres_param}) THEN (RECOMMENDATION IS high_recommendation)"
+    FS.add_rules([RULE1, RULE2, RULE3, RULE4, RULE5])
 
-# FS.produce_figure(outputfile='visualize_terms.pdf')
+    return FS
diff --git a/main.py b/main.py
index b38dbf4..2a6a07e 100644
--- a/main.py
+++ b/main.py
@@ -16,7 +16,7 @@ from fastapi import FastAPI
 from scipy.spatial.distance import cosine
 from sklearn.preprocessing import MultiLabelBinarizer
 
-from engine import FS
+from engine import fuzzy_system
 
 app = FastAPI()
 data = pd.DataFrame()
@@ -28,6 +28,8 @@ def inference(first: pandas.core.series.Series, second_id: str, df=None):
     else:
         second = data.loc[second_id]
 
+    FS = fuzzy_system(release_year_param='similar', runtime_param='similar', seasons_param='similar', genres_param='same', emotions_param='same')
+
     year_diff = int(first['release_year'] - second['release_year'])
     FS.set_variable('RELEASE_YEAR', year_diff)