Delete brainstorm_manager.py

brainstorm_manager.py

@@ -1,76 +0,0 @@
-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