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,
+do_sample=True
-top_k=100,
+top_k=100
-top_p=0.9,
+top_p=0.9

presets/Individual Today.txt

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

presets/Instruct-Joi.txt

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

presets/Kobold-Godlike.txt

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

presets/Kobold-Liminal Drift.txt

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

presets/Naive.txt

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

presets/NovelAI-Best Guess.txt

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

presets/NovelAI-Decadence.txt

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

presets/NovelAI-Genesis.txt

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

presets/NovelAI-Lycaenidae.txt

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

presets/NovelAI-Ouroboros.txt

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

presets/NovelAI-Pleasing Results.txt

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

presets/NovelAI-Sphinx Moth.txt

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

presets/NovelAI-Storywriter.txt

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

presets/Pygmalion.txt

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

presets/Verbose.txt

@@ -1,9 +1,9 @@
-num_beams=10,
+num_beams=10
-min_length=200,
+min_length=200
-length_penalty =1.4,
+length_penalty =1.4
-no_repeat_ngram_size=2,
+no_repeat_ngram_size=2
-early_stopping=True,
+early_stopping=True
-temperature=0.7,
+temperature=0.7
-top_k=150,
+top_k=150
-top_p=0.92,
+top_p=0.92
-repetition_penalty=4.5,
+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(','):
+    for i in preset.splitlines():
-        i = i.strip().split('=')
+        i = i.rstrip(',').strip().split('=')
         if len(i) == 2 and i[0].strip() != 'tokens':
             generate_params[i[0].strip()] = eval(i[1].strip())