Update app.py

app.py

@@ -19,20 +19,29 @@ carbon_reduction_data = {
     "Tires": 8.0,
 }
 
-# Function to call Groq LLM
-def get_recycling_suggestions_from_groq(item, quantity):
-    prompt = (
-        f"Suggest profitable and eco-friendly uses for {quantity} kg of {item}, "
-        f"including household uses, ways to monetize them, and calculate carbon footprint reduction."
-    )
-    chat_completion = client.chat.completions.create(
-        messages=[{"role": "user", "content": prompt}],
-        model="llama-3.3-70b-versatile",
-        stream=False,
-    )
-    return chat_completion.choices[0].message.content
+# Custom CSS for color and style
+st.markdown(
+    """
+    <style>
+    body {
+        background-color: #f0f2f6;
+    }
+    .main {
+        background-color: #ffffff;
+        border-radius: 10px;
+        padding: 20px;
+        color: #333333;
+    }
+    .sidebar .sidebar-content {
+        background-color: #eaf4fc;
+        border-radius: 10px;
+    }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
 
-# Sidebar with clean navigation and image
+# Sidebar with navigation
 st.sidebar.title("🌍 RecycleSmart-PK")
 st.sidebar.image(
     "https://via.placeholder.com/300x200?text=RecycleSmart+Logo",
@@ -40,8 +49,7 @@ st.sidebar.image(
 )
 st.sidebar.markdown("### Navigation")
 section = st.sidebar.radio(
-    "Choose a section:",
-    ["Home", "Recycle Suggestions"]
+    "Choose a section:", ["Home", "Recycle Suggestions"]
 )
 
 # Main Content
@@ -54,17 +62,21 @@ if section == "Home":
     st.markdown(
         """
         RecycleSmart-PK helps you turn waste into opportunities while reducing your carbon footprint.  
-        Start by selecting items you want to recycle from the **Recycle Suggestions** tab.
+        Navigate to **Recycle Suggestions** to start recycling smartly!
         """
     )
 
 elif section == "Recycle Suggestions":
     st.title("💡 Recycling Suggestions")
     selected_items = st.multiselect(
-        "Select items to recycle:",
-        list(carbon_reduction_data.keys())
+        "Select items to recycle:", list(carbon_reduction_data.keys())
     )
-    quantities = {item: st.number_input(f"Enter quantity for {item} (in kg):", min_value=0, step=1) for item in selected_items}
+    quantities = {
+        item: st.number_input(
+            f"Enter quantity for {item} (in kg):", min_value=0, step=1
+        )
+        for item in selected_items
+    }
 
     if st.button("Get Suggestions"):
         if selected_items:
@@ -72,12 +84,23 @@ elif section == "Recycle Suggestions":
             st.write("### ♻️ Suggestions and Impact:")
             for item, quantity in quantities.items():
                 if quantity > 0:
-                    llm_response = get_recycling_suggestions_from_groq(item, quantity)
+                    prompt = (
+                        f"Suggest profitable and eco-friendly uses for {quantity} kg of {item}, "
+                        f"including household uses and ways to monetize them."
+                    )
+                    chat_completion = client.chat.completions.create(
+                        messages=[{"role": "user", "content": prompt}],
+                        model="llama-3.3-70b-versatile",
+                        stream=False,
+                    )
+                    llm_response = chat_completion.choices[0].message.content
                     carbon_reduction = carbon_reduction_data.get(item, 0) * quantity
                     total_carbon_reduction += carbon_reduction
-                    st.write(f"**📦 {item} ({quantity} kg)**")
+                    st.write(f"**{item} ({quantity} kg)**")
                     st.write(f"💡 {llm_response}")
-                    st.write(f"🌍 **Carbon Footprint Reduction**: {carbon_reduction:.2f} kg CO₂")
+                    st.write(
+                        f"🌍 **Carbon Footprint Reduction**: {carbon_reduction:.2f} kg CO₂"
+                    )
                     st.markdown("---")
             st.write("### 🌟 Total Carbon Footprint Reduction 🌟")
             st.write(f"🌍 **{total_carbon_reduction:.2f} kg CO₂ saved**")