Create app.py

app.py

@@ -0,0 +1,22 @@
+import os
+os.system("pip install gradio transformers torch")
+
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+import gradio as gr
+
+model = T5ForConditionalGeneration.from_pretrained("./Ruttoni_AI")
+tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-base")
+
+print("Model loaded!")
+# Generate a summary using the trained model
+def generate_summary(input_text):
+    input_ids = tokenizer.encode(input_text, return_tensors='pt')
+    outputs = model.generate(input_ids)
+    summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return summary
+
+ai = gr.Interface(fn=generate_summary, inputs="text", outputs="text")
+    
+ai.launch()
+
+print("Interface Started!")