Update app.py

app.py

@@ -1,23 +1,33 @@
 import torch
+import gradio as gr
 from transformers import GPT2Tokenizer, GPT2LMHeadModel, pipeline
+
 tokenizer = GPT2Tokenizer.from_pretrained('distilgpt2')
 tokenizer.add_special_tokens({'pad_token': '[PAD]'})
 model = GPT2LMHeadModel.from_pretrained('FredZhang7/anime-anything-promptgen-v2')
 
-prompt = r'1girl, genshin'
+# prompt = r'1girl, genshin'
 
 # generate text using fine-tuned model
 nlp = pipeline('text-generation', model=model, tokenizer=tokenizer)
 
-# generate 10 samples using contrastive search
-outs = nlp(prompt, max_length=76, num_return_sequences=10, do_sample=True, repetition_penalty=1.2, temperature=0.7, top_k=4, early_stopping=True)
+def generate(prompt):
+    # generate 10 samples using contrastive search
+    outs = nlp(prompt, max_length=76, num_return_sequences=10, do_sample=True, repetition_penalty=1.2, temperature=0.7, top_k=4, early_stopping=True)
+    print(prompt)
+    print(outs)
+    return outs
+
 
-print('\nInput:\n' + 100 * '-')
-print('\033[96m' + prompt + '\033[0m')
-print('\nOutput:\n' + 100 * '-')
-print(outs)
 # for i in range(len(outs)):
     # remove trailing commas and double spaces
     # outs[i] = str(outs[i]['generated_text']).replace('  ', '').rstrip(',')
 # print('\033[92m' + '\n\n'.join(outs) + '\033[0m\n')
     # print(str(outs[i]['generated_text']))
+    
+input_component = gr.Textbox(label = "Input a prompt", value = "1girl, genshin")
+output_component = gr.Textbox(label = "detail Prompt")
+examples = []
+description = ""
+gr.Interface(generate, inputs = input_component, outputs=output_component, examples=examples, title = "anything prompt", description=description).launch()
+