Remove how-to instructions and model descriptions, add more sample questions

- Remove 'How to Use VayuChat' instruction section to save space
- Remove 'Current Model' section and model descriptions
- Remove instruction tooltips and help text
- Add more sample questions (15 total, up from 12)
- Include 3 harder analytical questions:
* Which station records highest variability in PM2.5?
* Calculate pollution improvement rate year-over-year by city
* Identify cities with PM2.5 levels consistently above 50 μg/m³ for >6 months
* Find correlation between PM2.5 and PM10 across different seasons and cities
- Cleaner, more focused interface with more query options

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <[email protected]>

app.py

@@ -592,58 +592,34 @@ with st.sidebar:
             "Which month had highest pollution?",
             "Which city has worst air quality?", 
             "Show annual PM2.5 average",
-            "Compare winter vs summer pollution",
-            "List all cities by pollution level",
             "Plot monthly average PM2.5 for 2023",
+            "List all cities by pollution level",
+            "Compare winter vs summer pollution",
             "Show seasonal pollution patterns",
-            "Which pollutant has highest concentration?",
-            "Create correlation plot between pollutants",
+            "Which areas exceed WHO guidelines?",
             "What are peak pollution hours?",
-            "Compare weekday vs weekend levels",
             "Show PM10 vs PM2.5 comparison",
+            "Compare weekday vs weekend levels",
             "Plot yearly trend analysis",
-            "Which areas exceed WHO guidelines?",
-            "Show pollution distribution by city"
+            "Show pollution distribution by city",
+            "Create correlation plot between pollutants",
+            "Which station records highest variability in PM2.5?",
+            "Calculate pollution improvement rate year-over-year by city",
+            "Identify cities with PM2.5 levels consistently above 50 μg/m³ for >6 months",
+            "Find correlation between PM2.5 and PM10 across different seasons and cities"
         ]
     
     # Quick query buttons in sidebar with helpful descriptions
     selected_prompt = None
     
-    # Add description for quick queries
-    st.markdown("""
-    <div style='background: #fef9e7; border: 1px solid #fbbf24; border-radius: 6px; padding: 0.5rem; margin-bottom: 0.75rem; font-size: 0.75rem; color: #92400e;'>
-        💡 <strong>Click any question below</strong> to start analyzing the air quality data instantly
-    </div>
-    """, unsafe_allow_html=True)
     
-    for i, question in enumerate(questions[:12]):  # Show more questions
+    for i, question in enumerate(questions[:15]):  # Show more questions
         # Simple left-aligned buttons without icons for cleaner look
         if st.button(question, key=f"sidebar_prompt_{i}", use_container_width=True, help=f"Click to analyze: {question}"):
             selected_prompt = question
     
     st.markdown("---")
     
-    # Current Model Info
-    st.markdown("### Current Model")
-    st.markdown(f"**{model_name}**")
-    
-    model_descriptions = {
-        "llama3.1": "Fast and efficient for general queries",
-        "llama3.3": "Most advanced LLaMA model for complex reasoning",
-        "mistral": "Balanced performance and speed",
-        "gemma": "Google's lightweight model",
-        "gemini-pro": "Google's most powerful model",
-        "gpt-oss-20b": "OpenAI's compact open-weight GPT for everyday tasks",
-        "gpt-oss-120b": "OpenAI's massive open-weight GPT for nuanced responses",
-        "deepseek-R1": "DeepSeek's distilled LLaMA model for efficient reasoning",
-        "llama4 maverik": "Meta's LLaMA 4 Maverick — high-performance instruction model",
-        "llama4 scout": "Meta's LLaMA 4 Scout — optimized for adaptive reasoning"
-    }
-    
-    if model_name in model_descriptions:
-        st.caption(model_descriptions[model_name])
-    
-    st.markdown("---")
     
     # Clear Chat Button
     if st.button("Clear Chat", use_container_width=True):
@@ -663,19 +639,6 @@ if "processing" not in st.session_state:
 if "session_id" not in st.session_state:
     st.session_state.session_id = str(uuid.uuid4())
 
-# Helpful instructions section
-if not st.session_state.responses:
-    st.markdown("""
-    <div style='background: #f1f5f9; border: 1px solid #e2e8f0; border-radius: 8px; padding: 1.5rem; margin-bottom: 1rem; border-left: 4px solid #3b82f6;'>
-        <h4 style='margin: 0 0 0.5rem 0; color: #1e293b; font-size: 1rem;'>💡 How to Use VayuChat</h4>
-        <p style='margin: 0.25rem 0; font-size: 0.875rem; color: #475569;'>
-            • <strong>Click any quick query</strong> from the sidebar to start analyzing air quality data<br>
-            • <strong>Type your own question</strong> in the chat box below<br>
-            • <strong>Ask about trends, comparisons, or specific data points</strong><br>
-            • <strong>Request visualizations</strong> with phrases like "plot" or "show chart"
-        </p>
-    </div>
-    """, unsafe_allow_html=True)