Update app.py

app.py

@@ -9,33 +9,38 @@ import os
 # Set up page configuration
 st.set_page_config(page_title="ProductProse - AI Product Description Generator", layout="wide")
 
-# Initialize session state to track API responses and user feedback
+# Initialize session state to track API responses, user feedback, and history
 if 'generated_description' not in st.session_state:
     st.session_state.generated_description = None
 if 'translated_description' not in st.session_state:
     st.session_state.translated_description = None
 if 'customized_description' not in st.session_state:
     st.session_state.customized_description = None
-if 'feedback' not in st.session_state:
-    st.session_state.feedback = None
+if 'feedback_history' not in st.session_state:
+    st.session_state.feedback_history = []
 
 # Sidebar for product data input
-st.sidebar.title("Product Data Input")
-product_name = st.sidebar.text_input("Product Name", "Example Product")
-features = st.sidebar.text_area("Product Features", "Feature 1, Feature 2, Feature 3")
-benefits = st.sidebar.text_area("Product Benefits", "Benefit 1, Benefit 2, Benefit 3")
-specifications = st.sidebar.text_area("Product Specifications", "Specification 1, Specification 2, Specification 3")
+with st.sidebar:
+    st.title("Product Data Input")
+    product_name = st.text_input("Product Name", placeholder="e.g., Smart Home Hub")
+    features = st.text_area("Product Features", placeholder="e.g., Voice Control, Energy Efficient, Compact Design")
+    benefits = st.text_area("Product Benefits", placeholder="e.g., Saves time, Reduces energy usage, Easy to install")
+    specifications = st.text_area("Product Specifications", placeholder="e.g., Dimensions: 10x5x3 inches, Weight: 1.5 lbs")
 
-# Select target language for translation
-target_language = st.sidebar.selectbox("Target Language for Translation",  ["Arabic", "Chinese", "French", "German", "Japanese", "Portugese", "Russian", "Spanish", "Urdu"])
+    # Select target language for translation
+    target_language = st.selectbox("Target Language for Translation", ["French", "Spanish", "German", "Chinese", "Japanese"])
 
 # Main app title and description
-st.title("ProductProse - AI Product Description Generator")
+st.markdown("# ProductProse - AI Product Description Generator")
 st.markdown("""
 Welcome to ProductProse, an AI-powered tool for generating and customizing product descriptions using IBM Granite LLMs.
 Simply input your product data and let the AI do the rest, including generating descriptions, translating them into multiple languages, and customizing them to match your brand tone and style.
 """)
 
+# UI Enhancement: Color-coded sections for clarity
+def section_header(title, color):
+    st.markdown(f'<h2 style="color:{color};">{title}</h2>', unsafe_allow_html=True)
+
 # IBM WatsonX API Setup
 project_id = os.getenv('WATSONX_PROJECT_ID')
 api_key = os.getenv('WATSONX_API_KEY')
@@ -46,15 +51,15 @@ if api_key and project_id:
     client.set.default_project(project_id)
 
     # Tone Selection for Description Customization
-    tone_example = st.sidebar.selectbox("Select Example Tone (Feel free to modify)", ["Formal", "Casual", "Professional", "Playful"])
-    st.sidebar.markdown("_Example: You can choose a tone that best fits your brand's style._")
+    tone_example = st.sidebar.selectbox("Tone Example (Modify as needed)", ["Formal", "Casual", "Professional", "Playful"])
+    st.sidebar.markdown("_Example: Choose a tone to match your brand's style._")
 
     # Keyword Input for SEO Optimization
-    seo_keywords_example = st.sidebar.text_area("SEO Keywords (comma-separated, e.g., 'smart home, automation')", "smart home, intelligent, automation")
-    st.sidebar.markdown("_Example: Add keywords to optimize for search engines._")
+    seo_keywords_example = st.sidebar.text_area("SEO Keywords (comma-separated)", placeholder="e.g., wireless, fast charging, Bluetooth")
+    st.sidebar.markdown("_Example: Add keywords that enhance search engine optimization._")
 
     # Step 1: Generate Product Description
-    st.header("Step 1: Generate Product Description")
+    section_header("Step 1: Generate Product Description", "blue")
     if st.button("Generate Description"):
         if product_name and features and benefits and specifications:
             # Prompt engineering for Granite-13B-Instruct
@@ -78,6 +83,7 @@ if api_key and project_id:
                     description_response = model.generate_text(prompt=prompt)
                     st.session_state.generated_description = description_response
                     st.session_state.translated_description = None  # Clear previous translations
+                    st.session_state.customized_description = None  # Clear previous customizations
                     st.success("Product description generated!")
                     st.write(description_response)
             except Exception as e:
@@ -86,7 +92,7 @@ if api_key and project_id:
             st.warning("Please fill in all the product data fields before generating a description.")
 
     # Step 2: Translate Product Description
-    st.header("Step 2: Translate Product Description")
+    section_header("Step 2: Translate Product Description", "green")
     if st.session_state.generated_description:
         if st.button("Translate Description"):
             try:
@@ -117,8 +123,8 @@ if api_key and project_id:
         st.write(st.session_state.translated_description)
 
     # Step 3: Customize Product Description via Chat Interface
-    st.header("Step 3: Customize Product Description")
-    customization_prompt = st.text_input("Customize the product description (Feel free to modify the example tone and SEO keywords)")
+    section_header("Step 3: Customize Product Description", "orange")
+    customization_prompt = st.text_input("Customize the product description", placeholder="e.g., Make the tone more playful and mention our eco-friendly packaging")
 
     if st.session_state.generated_description and customization_prompt:
         if st.button("Customize Description"):
@@ -145,15 +151,59 @@ if api_key and project_id:
         st.subheader("Customized Product Description")
         st.write(st.session_state.customized_description)
 
+        # Option to translate the customized description if it hasn't been translated yet
+        if st.session_state.translated_description:
+            if st.button("Translate Customized Description"):
+                try:
+                    # Translate the customized description using Granite-20B-Multilingual
+                    prompt = f"Translate the following customized product description into {target_language}:\n{st.session_state.customized_description}"
+                    model = ModelInference(model_id=ModelTypes.GRANITE_20B_MULTILINGUAL, params={
+                        GenParams.DECODING_METHOD: DecodingMethods.GREEDY,
+                        GenParams.MIN_NEW_TOKENS: 50,
+                        GenParams.MAX_NEW_TOKENS: 200,
+                        GenParams.STOP_SEQUENCES: ["\n"]
+                    }, credentials=credentials, project_id=project_id)
+
+                    with st.spinner(f"Translating customized product description to {target_language}..."):
+                        customized_translation_response = model.generate_text(prompt=prompt)
+                        st.session_state.translated_customized_description = customized_translation_response
+                        st.success(f"Customized product description translated to {target_language}!")
+                        st.write(customized_translation_response)
+                except Exception as e:
+                    st.error(f"An error occurred while translating the customized description: {e}")
+
+    # Display the translated customized description if available
+    if 'translated_customized_description' in st.session_state:
+        st.subheader(f"Translated Customized Product Description ({target_language})")
+        st.write(st.session_state.translated_customized_description)
+
     # Step 4: Feedback and Quality Scoring
-    st.header("Step 4: Provide Feedback")
-    feedback = st.slider("Rate the quality of the generated product description (1 = Poor, 5 = Excellent)", 1, 5, 3)
+    section_header("Step 4: Provide Feedback", "purple")
+    feedback_rating = st.slider("Rate the quality of the generated product description (1 = Poor, 5 = Excellent)", 1, 5, 3)
     feedback_comments = st.text_area("Additional Comments")
 
     if st.button("Submit Feedback"):
-        st.session_state.feedback = {"rating": feedback, "comments": feedback_comments}
+        # Save the feedback in session state
+        feedback_entry = {
+            "rating": feedback_rating,
+            "comments": feedback_comments,
+            "description": st.session_state.generated_description,
+            "customized_description": st.session_state.customized_description if st.session_state.customized_description else "N/A",
+            "translated_description": st.session_state.translated_description if st.session_state.translated_description else "N/A"
+        }
+        st.session_state.feedback_history.append(feedback_entry)
         st.success("Thank you for your feedback!")
-        st.write(st.session_state.feedback)
+
+        # Display the feedback summary
+        st.subheader("Feedback Summary")
+        for i, feedback in enumerate(st.session_state.feedback_history, 1):
+            st.write(f"**Feedback {i}:**")
+            st.write(f"Rating: {feedback['rating']}")
+            st.write(f"Comments: {feedback['comments']}")
+            st.write(f"Generated Description: {feedback['description']}")
+            st.write(f"Customized Description: {feedback['customized_description']}")
+            st.write(f"Translated Description: {feedback['translated_description']}")
+            st.markdown("---")
 
 else:
     st.error("IBM WatsonX API credentials are not set. Please check your environment variables.")