Update app.py

app.py

@@ -1 +1,79 @@
-import gradio as gr
+import gradio as gr
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+
+# xl size run out of memory on 16GB vm
+tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-large")
+model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-large")
+
+title = ""
+
+def get_examples ():
+    return [
+    ["Being a Happier and Healthier Person"],
+    ["Learn to Use Mindfulness to Affect Well Being"],
+    ["Eating and Drinking - Find Healthy Nutrition Habits"],
+    ["Drinking - Find Reasons and Cut Back or Quit Entirely"],
+    ["Stress is relieved by quieting your mind, getting exercise and time with nature"],
+    ["Reprogram Pain Stress Reactions"],
+    ["Brain gamification"],
+    ["Mental Body Scan"],
+    ["Stretch, Calm, Breath"],
+    ["Relaxed Seat Breath"],
+    ["Walk Feel"],
+    ["alleviating stress"],
+    ["helping breathing, satisfaction"],
+    ["Relieve Stress, Build Support"],
+    ["Relaxation Response"],
+    ["Deep Breaths"],
+    ["Delete Not Helpful Thoughts"],
+    ["Strengthen Helpful"],
+    ["Sleep Better and Find Joy"],
+    ["Yoga Sleep"],
+    ["Relieve Pain"],
+    ["Build and Boost Mental Strength"],
+    ["Spending Time Outdoors"],
+    ["Daily Routine Tasks"],
+    ["Feel better each day when you awake by"],
+    ["Feel better physically by"],
+    ["Practicing mindfulness each day"],
+    ["Be happier by"],
+    ["Meditation can improve health"],
+    ["Spending time outdoors"],
+    ["Break the cycle of stress and anxiety"],
+    ["Feel calm in stressful situations"],
+    ["Deal with work pressure"],
+    ["Learn to reduce feelings of overwhelmed"]    
+    ]
+    
+    
+def text2text(input_text):
+    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+
+    outputs = model.generate(input_ids, max_length=200)
+    return tokenizer.decode(outputs[0])
+
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+    """
+    # Flan T5 Large Demo
+    780M parameter Large language model fine tuned on diverse tasks.
+    Prompt the model in the Input box.
+    """)
+    txt_in = gr.Textbox(label="Input", lines=3)
+    correct_label = gr.Label(label="Correct")
+    txt_out = gr.Textbox(value="", label="Output", lines=4)
+    
+
+    btn = gr.Button(value="Submit")
+    btn.click(text2text, inputs=[txt_in], outputs=[txt_out])
+
+
+    gr.Examples(
+        examples=get_examples(),
+        inputs=[txt_in,correct_label]
+    )
+    
+
+if __name__ == "__main__":
+    demo.launch()