Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+from transformers import TFT5ForConditionalGeneration, RobertaTokenizer
+
+# load saved finetuned model
+model = TFT5ForConditionalGeneration.from_pretrained('ThoughtFocusAI/CodeGeneration-CodeT5-base')
+# load saved tokenizer
+tokenizer = RobertaTokenizer.from_pretrained('ThoughtFocusAI/CodeGeneration-CodeT5-base')
+
+def chat(chat_history, user_input):
+    query = "Generate Python: " + user_input
+    encoded_text = tokenizer(query, return_tensors='tf', padding='max_length', truncation=True, max_length=48)
+    
+    # inference
+    generated_code = model.generate(
+        encoded_text["input_ids"], attention_mask=encoded_text["attention_mask"], 
+        max_length=128
+    )
+    
+    # decode generated tokens
+    decoded_code = tokenizer.decode(generated_code.numpy()[0], skip_special_tokens=True)
+    
+    return chat_history + [(user_input, "<pre><code>"+decoded_code+"</code></pre>")]
+     
+my_theme = gr.Theme.from_hub('finlaymacklon/boxy_violet')
+with gr.Blocks(title="Python Code Generation",theme=my_theme) as demo:
+    gr.HTML(value="<style>h1 {text-align: center;}</style><h1>Python Code Generation</h1>") 
+    chatbot = gr.Chatbot([], elem_id="chatbot")
+    message = gr.Textbox(label="Write a python script to..",placeholder="Eg. Check if a number is prime")
+    message.submit(chat, [chatbot, message], chatbot)
+
+
+demo.queue().launch(enable_queue=True)