Update app.py

app.py

@@ -1,4 +1,4 @@
-import gradio as gr
+mport gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 import re
@@ -11,7 +11,7 @@ model = AutoModelForCausalLM.from_pretrained(model_name)
 # Generation function
 def generate_affirmation(description):
     # Structured prompt to guide model output
-    prompt = f"[SUBJECT] learning [/SUBJECT] [STREAK] current performance context [/STREAK] [CONTEXT] {description} [/CONTEXT] [AFFIRMATION] Give two positive affirmations. [/AFFIRMATION]"
+    prompt = f"[SUBJECT] learning [/SUBJECT] [STREAK] current performance context [/STREAK] [CONTEXT] {description} [/CONTEXT] [AFFIRMATION]"
 
     inputs = tokenizer(prompt, return_tensors="pt")
     input_ids = inputs["input_ids"]
@@ -19,7 +19,7 @@ def generate_affirmation(description):
     with torch.no_grad():
         outputs = model.generate(
             input_ids,
-            max_new_tokens=100,
+            max_new_tokens=60,
             temperature=0.7,
             top_k=50,
             top_p=0.95,
@@ -54,6 +54,8 @@ demo = gr.Interface(
 if __name__ == "__main__":
     demo.launch()
 
+    
+