Remove commas from preset files

presets/Debug-deterministic.txt

@@ -1 +1 @@
-do_sample=False,
+do_sample=False

presets/Default.txt

@@ -1,3 +1,3 @@
-do_sample=True,
-top_k=100,
-top_p=0.9,
+do_sample=True
+top_k=100
+top_p=0.9

presets/Individual Today.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=0.9,
-top_k=50,
-temperature=1.39,
-repetition_penalty=1.08,
-typical_p=0.2,
+do_sample=True
+top_p=0.9
+top_k=50
+temperature=1.39
+repetition_penalty=1.08
+typical_p=0.2

presets/Instruct-Joi.txt

@@ -1,5 +1,5 @@
-top_p=0.95,
-temperature=0.5,
-penalty_alpha=0.6,
-top_k=4,
-repetition_penalty=1.03,
+top_p=0.95
+temperature=0.5
+penalty_alpha=0.6
+top_k=4
+repetition_penalty=1.03

presets/Kobold-Godlike.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=0.5,
-top_k=0,
-temperature=0.7,
-repetition_penalty=1.1,
-typical_p=0.19,
+do_sample=True
+top_p=0.5
+top_k=0
+temperature=0.7
+repetition_penalty=1.1
+typical_p=0.19

presets/Kobold-Liminal Drift.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=1.0,
-top_k=0,
-temperature=0.66,
-repetition_penalty=1.1,
-typical_p=0.6,
+do_sample=True
+top_p=1.0
+top_k=0
+temperature=0.66
+repetition_penalty=1.1
+typical_p=0.6

presets/Naive.txt

@@ -1,4 +1,4 @@
-do_sample=True,
-top_p=1,
-typical_p=0.3,
-temperature=0.7,
+do_sample=True
+top_p=1
+typical_p=0.3
+temperature=0.7

presets/NovelAI-Best Guess.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=0.9,
-top_k=100,
-temperature=0.8,
-repetition_penalty=1.15,
-typical_p=1.0,
+do_sample=True
+top_p=0.9
+top_k=100
+temperature=0.8
+repetition_penalty=1.15
+typical_p=1.0

presets/NovelAI-Decadence.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=1.0,
-top_k=100,
-temperature=2,
-repetition_penalty=1,
-typical_p=0.97,
+do_sample=True
+top_p=1.0
+top_k=100
+temperature=2
+repetition_penalty=1
+typical_p=0.97

presets/NovelAI-Genesis.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=0.98,
-top_k=0,
-temperature=0.63,
-repetition_penalty=1.05,
-typical_p=1.0,
+do_sample=True
+top_p=0.98
+top_k=0
+temperature=0.63
+repetition_penalty=1.05
+typical_p=1.0

presets/NovelAI-Lycaenidae.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=0.85,
-top_k=12,
-temperature=2,
-repetition_penalty=1.15,
-typical_p=1.0,
+do_sample=True
+top_p=0.85
+top_k=12
+temperature=2
+repetition_penalty=1.15
+typical_p=1.0

presets/NovelAI-Ouroboros.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=1.0,
-top_k=100,
-temperature=1.07,
-repetition_penalty=1.05,
-typical_p=1.0,
+do_sample=True
+top_p=1.0
+top_k=100
+temperature=1.07
+repetition_penalty=1.05
+typical_p=1.0

presets/NovelAI-Pleasing Results.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=1.0,
-top_k=0,
-temperature=0.44,
-repetition_penalty=1.15,
-typical_p=1.0,
+do_sample=True
+top_p=1.0
+top_k=0
+temperature=0.44
+repetition_penalty=1.15
+typical_p=1.0

presets/NovelAI-Sphinx Moth.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=0.18,
-top_k=30,
-temperature=2.0,
-repetition_penalty=1.15,
-typical_p=1.0,
+do_sample=True
+top_p=0.18
+top_k=30
+temperature=2.0
+repetition_penalty=1.15
+typical_p=1.0

presets/NovelAI-Storywriter.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=0.73,
-top_k=0,
-temperature=0.72,
-repetition_penalty=1.1,
-typical_p=1.0,
+do_sample=True
+top_p=0.73
+top_k=0
+temperature=0.72
+repetition_penalty=1.1
+typical_p=1.0

presets/Pygmalion.txt

@@ -1,6 +1,6 @@
-do_sample=True,
-top_p=0.9,
-top_k=0,
-temperature=0.5,
-repetition_penalty=1.05,
-typical_p=1.0,
+do_sample=True
+top_p=0.9
+top_k=0
+temperature=0.5
+repetition_penalty=1.05
+typical_p=1.0

presets/Verbose.txt

@@ -1,9 +1,9 @@
-num_beams=10,
-min_length=200,
-length_penalty =1.4,
-no_repeat_ngram_size=2,
-early_stopping=True,
-temperature=0.7,
-top_k=150,
-top_p=0.92,
-repetition_penalty=4.5,
+num_beams=10
+min_length=200
+length_penalty =1.4
+no_repeat_ngram_size=2
+early_stopping=True
+temperature=0.7
+top_k=150
+top_p=0.92
+repetition_penalty=4.5

server.py

@@ -182,8 +182,8 @@ def load_preset_values(preset_menu, return_dict=False):
     }
     with open(Path(f'presets/{preset_menu}.txt'), 'r') as infile:
         preset = infile.read()
-    for i in preset.split(','):
-        i = i.strip().split('=')
+    for i in preset.splitlines():
+        i = i.rstrip(',').strip().split('=')
         if len(i) == 2 and i[0].strip() != 'tokens':
             generate_params[i[0].strip()] = eval(i[1].strip())