Update app.py

app.py

@@ -14,6 +14,7 @@ MODEL_REPO = 'OFA-Sys/small-stable-diffusion-v0'
 LoRa_DIR = 'weights'
 DATASET_REPO = 'VESSL/Bored_Ape_NFT_text'
 SAMPLE_IMAGE = 'weights/Sample.png'
+
 def load_pipeline_w_lora() :
 
     # Load pretrained unet from huggingface
@@ -64,14 +65,17 @@ def main():
     sample = Image.open(SAMPLE_IMAGE)
     st.image(sample, caption="Example image with prompt <An ape with solid gold fur and beanie>")
 
-    prompt = st.text_input(
-        label="Write prompt to generate your unique BAYC image! (e.g. An ape with golden fur)")
-
-    num_images = int(st.text_input(label="Number of images to generate"))
-
-    seed = int(st.text_input(label="Seed for images"))
+    with st.form(key="information", clear_on_submit=True): 
+        prompt = st.text_input(
+            label="Write prompt to generate your unique BAYC image! (e.g. An ape with golden fur)")
+    
+        num_images = st.number_input(label="Number of images to generate"))
+    
+        seed = st.number_input(label="Seed for images")
 
-    if prompt and num_images and seed:
+        submitted = st.form_submit_button(label="Submit")
+        
+    if submitted :
         st.write(f"Generating {num_images} BAYC image with prompt <{prompt}>...")
 
         generator = torch.Generator(device=device).manual_seed(seed)