Create brainstorm_manager.py

brainstorm_manager.py

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+import streamlit as st
+from typing import Dict, List
+from datetime import datetime
+
+
+class BrainstormManager:
+    def __init__(self):
+        if 'products' not in st.session_state:
+            st.session_state.products = {}
+        
+    def generate_product_form(self) -> tuple:
+        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:
+        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