Update app.py

app.py

@@ -4,10 +4,29 @@ from transformers import pipeline
 # Initialize the text generation pipeline with the GPT-2 fine-tuned recipe model
 pipe = pipeline("text-generation", model="mrm8488/gpt2-finetuned-recipes-cooking_v2")
 
+def clean_recipe(text):
+    # Split the generated text into steps based on punctuation (e.g., ".", "!", "?")
+    steps = text.split('.')
+    
+    # Remove any extra spaces and filter out empty or repetitive steps
+    cleaned_steps = []
+    seen_steps = set()  # Track steps to avoid repetition
+
+    for step in steps:
+        step = step.strip()  # Remove leading/trailing spaces
+        if step and step.lower() not in seen_steps:  # Skip empty or repetitive steps
+            cleaned_steps.append(step)
+            seen_steps.add(step.lower())  # Add step to the seen set
+
+    return cleaned_steps
+
 def generate_recipe(dish_name):
     # Generate recipe using the text-generation pipeline
     recipe = pipe(f"Recipe for {dish_name}:", max_length=300, num_return_sequences=1)
-    return recipe[0]['generated_text']
+    recipe_text = recipe[0]['generated_text']
+    
+    # Clean the recipe to remove repetitions and return it as a list of steps
+    return clean_recipe(recipe_text)
 
 # Streamlit app
 st.title("Cooking Recipe Generator")
@@ -19,8 +38,11 @@ dish_name = st.text_input("Enter your favorite dish")
 if st.button("Generate Recipe"):
     if dish_name:
         with st.spinner("Generating recipe..."):
-            recipe = generate_recipe(dish_name)
+            recipe_steps = generate_recipe(dish_name)
         st.subheader("Recipe:")
-        st.write(recipe)
+        
+        # Display the recipe in bullet points
+        for i, step in enumerate(recipe_steps, 1):
+            st.write(f"{i}. {step}")
     else:
         st.error("Please enter a dish name.")