Update app.py

app.py

@@ -6,6 +6,13 @@ import numpy as np
 from datetime import datetime, timedelta
 from typing import Dict, List, Any
 
+# --- Brainstorm Class ---
+class BrainstormManager:
+    def __init__(self):
+        # Initialize session state for products
+        if 'products' not in st.session_state:
+            st.session_state.products = {}
+
 # --- Data Processing Class ---
 class DataProcessor:
     def __init__(self):
@@ -177,33 +184,135 @@ def render_analytics():
                 for col, (metric, value) in zip(cols, metrics.items()):
                     col.metric(metric, f"{value:.2f}")
 
-def render_brainstorm():
-    st.header("🧠 Product Brainstorm")
+
+
+        
+    def generate_product_form(self) -> Dict:
+        """Generate dynamic form fields for product input"""
+        with st.form("product_form"):
+            basic_info = {
+                "name": st.text_input("Product Name"),
+                "category": st.selectbox("Category", ["Digital", "Physical", "Service"]),
+                "description": st.text_area("Description"),
+                "target_audience": st.multiselect("Target Audience", 
+                    ["Students", "Professionals", "Businesses", "Seniors", "Youth"]),
+                "price_range": st.slider("Price Range ($)", 0, 1000, (50, 200)),
+                "launch_date": st.date_input("Expected Launch Date")
+            }
+            
+            st.subheader("Market Analysis")
+            market_analysis = {
+                "competitors": st.text_area("Main Competitors (one per line)"),
+                "unique_features": st.text_area("Unique Selling Points"),
+                "market_size": st.selectbox("Market Size", 
+                    ["Small", "Medium", "Large", "Enterprise"]),
+                "growth_potential": st.slider("Growth Potential", 1, 10)
+            }
+            
+            submitted = st.form_submit_button("Save Product")
+            return basic_info, market_analysis, submitted
+
+    def analyze_product(self, product_data: Dict) -> Dict:
+        """Generate insights based on product data"""
+        insights = {
+            "market_opportunity": self._calculate_opportunity_score(product_data),
+            "suggested_price": self._suggest_price(product_data),
+            "risk_factors": self._identify_risks(product_data),
+            "next_steps": self._generate_next_steps(product_data)
+        }
+        return insights
+
+    def _calculate_opportunity_score(self, data: Dict) -> int:
+        score = 0
+        if data.get("market_size") == "Large":
+            score += 3
+        if len(data.get("target_audience", [])) >= 2:
+            score += 2
+        if data.get("growth_potential", 0) > 7:
+            score += 2
+        return min(score, 10)
+
+    def _suggest_price(self, data: Dict) -> float:
+        base_price = sum(data.get("price_range", (0, 0))) / 2
+        if data.get("market_size") == "Enterprise":
+            base_price *= 1.5
+        return round(base_price, 2)
+
+    def _identify_risks(self, data: Dict) -> List[str]:
+        risks = []
+        if data.get("competitors"):
+            risks.append("Competitive market - differentiation crucial")
+        if len(data.get("target_audience", [])) < 2:
+            risks.append("Narrow target audience - consider expansion")
+        return risks
+
+    def _generate_next_steps(self, data: Dict) -> List[str]:
+        steps = [
+            "Create detailed product specification",
+            "Develop MVP timeline",
+            "Plan marketing strategy"
+        ]
+        if data.get("market_size") == "Enterprise":
+            steps.append("Prepare enterprise sales strategy")
+        return steps
+
+def render_brainstorm_page():
+    st.title("Product Brainstorm Hub")
+    manager = BrainstormManager()
     
-    # Product selection
-    products = ["Product A", "Product B", "Product C", "Add New Product"]
-    selected_product = st.selectbox("Select Product", products)
+    # View/Create toggle
+    action = st.sidebar.radio("Action", ["View Products", "Create New Product"])
     
-    if selected_product == "Add New Product":
-        with st.form("new_product"):
-            st.subheader("Add New Product")
-            product_name = st.text_input("Product Name")
-            product_desc = st.text_area("Product Description")
-            product_category = st.selectbox("Category", ["Category A", "Category B", "Category C"])
+    if action == "Create New Product":
+        basic_info, market_analysis, submitted = manager.generate_product_form()
+        
+        if submitted:
+            # Combine form data
+            product_data = {**basic_info, **market_analysis}
+            
+            # Generate insights
+            insights = manager.analyze_product(product_data)
+            
+            # Store product
+            product_id = f"prod_{len(st.session_state.products)}"
+            st.session_state.products[product_id] = {
+                "data": product_data,
+                "insights": insights,
+                "created_at": str(datetime.datetime.now())
+            }
             
-            if st.form_submit_button("Add Product"):
-                st.success(f"Product '{product_name}' added successfully!")
+            st.success("Product added! View insights in the Products tab.")
+    
     else:
-        st.subheader(f"Analysis for {selected_product}")
-        
-        # Sample metrics
-        col1, col2, col3 = st.columns(3)
-        with col1:
-            st.metric("Sales", "$12,345", "+10%")
-        with col2:
-            st.metric("Reviews", "4.5/5", "+0.2")
-        with col3:
-            st.metric("Engagement", "89%", "-2%")
+        if st.session_state.products:
+            for prod_id, product in st.session_state.products.items():
+                with st.expander(f"🎯 {product['data']['name']}"):
+                    col1, col2 = st.columns(2)
+                    
+                    with col1:
+                        st.subheader("Product Details")
+                        st.write(f"Category: {product['data']['category']}")
+                        st.write(f"Target: {', '.join(product['data']['target_audience'])}")
+                        st.write(f"Description: {product['data']['description']}")
+                    
+                    with col2:
+                        st.subheader("Insights")
+                        st.metric("Opportunity Score", f"{product['insights']['market_opportunity']}/10")
+                        st.metric("Suggested Price", f"${product['insights']['suggested_price']}")
+                        
+                        st.write("**Risk Factors:**")
+                        for risk in product['insights']['risk_factors']:
+                            st.write(f"- {risk}")
+                        
+                        st.write("**Next Steps:**")
+                        for step in product['insights']['next_steps']:
+                            st.write(f"- {step}")
+        else:
+            st.info("No products yet. Create one to get started!")
+
+# Usage in main app
+if __name__ == "__main__":
+    render_brainstorm_page()
 
 def render_chat():
     st.header("💬 Business Assistant")
@@ -259,6 +368,10 @@ def main():
         render_brainstorm()
     elif page == "Chat":
         render_chat()
+    #
+    # In your main() function, update this line:
+elif page == "Brainstorm":
+    render_brainstorm_page()  # Changed from render_brainstorm()
 
 if __name__ == "__main__":
     main()