Create app.py

app.py

@@ -0,0 +1,80 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline
+import re
+
+tokenizer = AutoTokenizer.from_pretrained("bert-base-cased")
+model = AutoModelForSequenceClassification.from_pretrained("Qilex/colorpAI-monocolor")
+
+def round_to_2(num):
+    return round(num, 2)
+
+def format_output(out_list):
+    white = 0
+    for dictionary in out_list:
+        if dictionary["label"] =='W':
+            white = round_to_2(dictionary["score"])
+    for dictionary in out_list:
+        if dictionary["label"] =='U':
+            blue = round_to_2(dictionary["score"])
+    for dictionary in out_list:
+        if dictionary["label"] =='B':
+            black = round_to_2(dictionary["score"])            
+    for dictionary in out_list:
+        if dictionary["label"] =='R':
+            red = round_to_2(dictionary["score"])           
+    for dictionary in out_list:
+        if dictionary["label"] =='G':
+            green = round_to_2(dictionary["score"])
+    for dictionary in out_list:
+        if dictionary["label"] =='C':
+            colorless = round_to_2(dictionary["score"])
+    out= {}
+    out['White'] = white
+    out['Blue'] = blue
+    out['Black'] = black
+    out['Red'] = red
+    out['Green'] = green
+    out['Colorless'] = colorless
+    return out
+
+def predict(card):  
+    return predictor_lg(card)
+
+def remove_colored_pips(text):
+    pattern = r'\{[W,U,B,R,G,C]+/*[W,U,B,R,G,C]*\}'
+    return(re.sub(pattern, '{?}', text))
+
+def preprocess_text(text):
+    return remove_colored_pips(text)
+
+def categorize(card):
+    text = preprocess_text(card)
+    prediction = predict(text)
+    
+    return format_output(prediction)
+    
+title = "Color pAI Version 1.0"
+description = """
+Color pAI is trained on around 18,000 Magic: the Gathering cards made available under Wizards of the Coast's 
+<a href="https://company.wizards.com/en/legal/fancontentpolicy" target = 'blank'>fan content policy</a>.
+<br>
+Input a card text using Scryfall syntax, and the model will tell evaluate which color it is most likely to be.
+<br>Replace any card names with the word CARDNAME.
+<br>
+<br>This only works on monocolored cards. Version 2 will also handle multicolored cards.
+<br>
+"""
+article = '''
+<br>
+Magic: the Gathering is property of Wizards of the Coast.
+'''
+predictor_lg = TextClassificationPipeline(model=model, tokenizer=tokenizer, function_to_apply = 'softmax', top_k = 6)
+
+gr.Interface(
+    fn=categorize,
+    inputs=gr.Textbox(lines=1, placeholder="Type card text here."),
+    outputs=gr.Label(num_top_classes=6),
+    title=title,
+    description=description,
+    article = article,
+).launch()