Update app.py

app.py

@@ -1,34 +1,18 @@
 import gradio as gr
-from PIL import Image
-from transformers import pipeline, AutoModelForVision2Seq, AutoProcessor
-import torch
-
-# Load the OpenGVLab/InternVL-Chat-V1-5 model and processor
-from transformers import AutoModel
-model = AutoModel.from_pretrained("OpenGVLab/InternVL-Chat-V1-5", trust_remote_code=True)
-
-# Load the Llama3 model for text processing
-#llama_model = pipeline("text2text-generation", model="llama3")
-
-def process_image(image):
-    # Process the image to extract the recipe using OpenGVLab
-    inputs = processor(images=image, return_tensors="pt")
-    generated_ids = model.generate(**inputs)
-    extracted_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-
-    return extracted_text
 
+def process_recipe(i,j):
+  return "Thank you"
+    
 iface = gr.Interface(
-    fn=process_image,
+    fn=process_recipe,
     inputs=[
         gr.components.Image(type="filepath", label="Recipe Image"),
-        #gr.components.Radio(choices=["Double", "Triple", "Half", "Third"], label="Action")
+        gr.components.Radio(choices=["Double","Triple", "Half", "Third"], label="Action")
     ],
     outputs="text",
     title="Recipe Modifier",
     description="Upload an image of a recipe and choose how to modify the measurements.",
 )
 
-
 if __name__ == "__main__":
-    iface.launch(share=True)
+    iface.launch()