Update main.py

main.py

@@ -0,0 +1,68 @@
+import pickle
+import random
+import numpy as np
+
+with open('models.pickle', 'rb')as f:
+    models = pickle.load(f)
+
+LORA_TOKEN = ''#'<|>LORA_TOKEN<|>'
+# WEIGHT_TOKEN = '<|>WEIGHT_TOKEN<|>'
+NOT_SPLIT_TOKEN = '<|>NOT_SPLIT_TOKEN<|>'
+
+def sample_next(ctx:str,model,k):
+ 
+    ctx = ', '.join(ctx.split(', ')[-k:])
+    if model.get(ctx) is None:
+        return " "
+    possible_Chars = list(model[ctx].keys())
+    possible_values = list(model[ctx].values())
+    
+    # print(possible_Chars)
+    # print(possible_values)
+ 
+    return np.random.choice(possible_Chars,p=possible_values)
+
+def generateText(model, minLen=100, size=5):
+    keys = list(model.keys())
+    starting_sent = random.choice(keys)
+    k = len(random.choice(keys).split(', '))
+
+    sentence = starting_sent
+    ctx = ', '.join(starting_sent.split(', ')[-k:])
+    
+    while True:
+        next_prediction = sample_next(ctx,model,k)
+        sentence += f", {next_prediction}"
+        ctx = ', '.join(sentence.split(', ')[-k:])
+        # if sentence.count('\n')>size: break
+        if '\n' in sentence: break
+    sentence = sentence.replace(NOT_SPLIT_TOKEN, ', ')
+    # sentence = re.sub(WEIGHT_TOKEN.replace('|', '\|'), lambda match: f":{random.randint(0,2)}.{random.randint(0,9)}", sentence)
+    # sentence = sentence.replace(":0.0", ':0.1')
+    # return sentence
+    
+    prompt = sentence.split('\n')[0]
+    if len(prompt)<minLen: 
+        prompt = generateText(model, minLen, size=1)[0]
+
+    size = size-1
+    if size == 0: return [prompt]
+    output = []
+    for i in range(size+1):
+        prompt = generateText(model, minLen, size=1)[0]
+        output.append(prompt)
+
+    return output
+if __name__ == "__main__":
+    for model in models: # models = [(model, neg_model), (nsfw, neg_nsfw), (sfw, neg_sfw)]
+        text = generateText(model[0], k=k, minLen=300, size=5)
+        text_neg = generateText(model[1], k=k, minLen=300, size=5)
+
+        # print('\n'.join(text))
+        for i in range(len(text)):
+            print(text[i])
+            # print('negativePrompt:')
+            print(text_neg[i])
+            print('----------------------------------------------------------------')
+        print('********************************************************************************************************************************************************')
+