cli_interface.py

"""
BI Storyteller CLI Interface
Command-line interface for marketing analysis automation
Standard Library Only - No Network Dependencies
"""

import json
import os
from main import BIStoryteller


class BIStoryteller_CLI:
    """Command-line interface for BI Storyteller"""
    
    def __init__(self):
        self.bi = BIStoryteller()
        self.current_step = 1
    
    def print_header(self):
        """Print application header"""
        print("\n" + "="*60)
        print("🚀 BI STORYTELLER - MARKETING ANALYSIS PLATFORM")
        print("="*60)
        print("📊 Complete workflow for marketing data analysis")
        print("🔧 Standard Library Only - No External Dependencies")
        print("="*60)
    
    def print_menu(self):
        """Print main menu"""
        print(f"\n📋 MAIN MENU (Current Step: {self.current_step}/12)")
        print("-" * 40)
        print("1.  🔑 Set API Key (Optional)")
        print("2.  📝 Extract Variables")
        print("3.  📋 Generate Questionnaire")
        print("4.  🔢 Generate Sample Data")
        print("5.  🧹 Clean Data")
        print("6.  📊 Perform EDA")
        print("7.  🤖 Train Predictive Model")
        print("8.  📈 Analyze Trends")
        print("9.  💭 Analyze Sentiment")
        print("10. 🧪 Run A/B Test")
        print("11. 💬 Chat with Data")
        print("12. 📤 Export Results")
        print("-" * 40)
        print("13. 📥 Import Previous Analysis")
        print("14. 📄 Export Data as CSV")
        print("15. ❌ Exit")
        print("-" * 40)
    
    def get_user_input(self, prompt, input_type="string"):
        """Get user input with validation"""
        while True:
            try:
                user_input = input(f"\n{prompt}: ").strip()
                
                if input_type == "int":
                    return int(user_input)
                elif input_type == "float":
                    return float(user_input)
                else:
                    return user_input
            except ValueError:
                print(f"❌ Please enter a valid {input_type}")
            except KeyboardInterrupt:
                print("\n👋 Goodbye!")
                exit(0)
    
    def print_results(self, title, results, success_key="success"):
        """Print formatted results"""
        print(f"\n{title}")
        print("-" * len(title))
        
        if results.get(success_key):
            if "results" in results:
                self.print_dict(results["results"], indent=0)
            else:
                self.print_dict(results, indent=0)
        else:
            print(f"❌ Error: {results.get('error', 'Unknown error')}")
    
    def print_dict(self, data, indent=0):
        """Print dictionary in a formatted way"""
        spaces = "  " * indent
        
        for key, value in data.items():
            if isinstance(value, dict):
                print(f"{spaces}{key}:")
                self.print_dict(value, indent + 1)
            elif isinstance(value, list):
                print(f"{spaces}{key}: [{len(value)} items]")
                if value and len(value) <= 5:
                    for item in value:
                        print(f"{spaces}  • {item}")
            else:
                print(f"{spaces}{key}: {value}")
    
    def module_1_api_key(self):
        """Module 1: Set API Key"""
        print("\n🔑 MODULE 1: API KEY SETUP")
        print("=" * 30)
        print("Enter your Groq API key for AI-powered analysis.")
        print("Leave empty to use offline mode with fallback functionality.")
        
        api_key = self.get_user_input("Groq API Key (or press Enter to skip)")
        
        if api_key:
            result = self.bi.set_groq_api_key(api_key)
            self.print_results("✅ API Key Setup", result)
        else:
            print("⚡ Using offline mode - fallback analysis will be used")
        
        self.current_step = max(self.current_step, 2)
        input("\nPress Enter to continue...")
    
    def module_2_extract_variables(self):
        """Module 2: Extract Variables"""
        print("\n📝 MODULE 2: VARIABLE EXTRACTION")
        print("=" * 35)
        print("Describe your business problem to extract relevant variables.")
        
        business_problem = self.get_user_input("Business Problem Description")
        
        if business_problem:
            result = self.bi.extract_variables(business_problem)
            self.print_results("✅ Variable Extraction Results", result)
            self.current_step = max(self.current_step, 3)
        else:
            print("❌ Please provide a business problem description")
        
        input("\nPress Enter to continue...")
    
    def module_3_generate_questionnaire(self):
        """Module 3: Generate Questionnaire"""
        print("\n📋 MODULE 3: QUESTIONNAIRE GENERATION")
        print("=" * 40)
        
        if not self.bi.variables:
            print("❌ Please extract variables first (Module 2)")
            input("Press Enter to continue...")
            return
        
        result = self.bi.generate_questionnaire(self.bi.variables, "")
        self.print_results("✅ Questionnaire Generation Results", result)
        
        if result.get("success"):
            print("\n📝 Sample Questions:")
            for i, question in enumerate(result["questionnaire"][:3]):
                print(f"{i+1}. {question['question']}")
        
        self.current_step = max(self.current_step, 4)
        input("\nPress Enter to continue...")
    
    def module_4_generate_data(self):
        """Module 4: Generate Sample Data"""
        print("\n🔢 MODULE 4: SAMPLE DATA GENERATION")
        print("=" * 38)
        
        if not self.bi.variables:
            print("❌ Please extract variables first (Module 2)")
            input("Press Enter to continue...")
            return
        
        sample_size = self.get_user_input("Sample Size (100-10000)", "int")
        
        if 100 <= sample_size <= 10000:
            result = self.bi.generate_sample_data(self.bi.variables, sample_size)
            self.print_results("✅ Sample Data Generation Results", result)
            
            if result.get("success"):
                print(f"\n📊 Sample Record:")
                self.print_dict(result["data"][0], indent=1)
            
            self.current_step = max(self.current_step, 5)
        else:
            print("❌ Sample size must be between 100 and 10,000")
        
        input("\nPress Enter to continue...")
    
    def module_5_clean_data(self):
        """Module 5: Clean Data"""
        print("\n🧹 MODULE 5: DATA CLEANING")
        print("=" * 28)
        
        if not self.bi.sample_data:
            print("❌ Please generate sample data first (Module 4)")
            input("Press Enter to continue...")
            return
        
        result = self.bi.clean_data(self.bi.sample_data)
        self.print_results("✅ Data Cleaning Results", result)
        
        self.current_step = max(self.current_step, 6)
        input("\nPress Enter to continue...")
    
    def module_6_perform_eda(self):
        """Module 6: Perform EDA"""
        print("\n📊 MODULE 6: EXPLORATORY DATA ANALYSIS")
        print("=" * 40)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        result = self.bi.perform_eda(self.bi.cleaned_data)
        self.print_results("✅ EDA Analysis Results", result)
        
        self.current_step = max(self.current_step, 7)
        input("\nPress Enter to continue...")
    
    def module_7_train_model(self):
        """Module 7: Train Predictive Model"""
        print("\n🤖 MODULE 7: PREDICTIVE ANALYTICS")
        print("=" * 35)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        print("Available algorithms:")
        algorithms = ["Random Forest", "Logistic Regression", "SVM", "Neural Network"]
        for i, alg in enumerate(algorithms, 1):
            print(f"{i}. {alg}")
        
        choice = self.get_user_input("Select algorithm (1-4)", "int")
        
        if 1 <= choice <= 4:
            algorithm = algorithms[choice - 1]
            result = self.bi.train_predictive_model(self.bi.cleaned_data, algorithm)
            self.print_results("✅ Predictive Model Results", result)
            self.current_step = max(self.current_step, 8)
        else:
            print("❌ Invalid algorithm selection")
        
        input("\nPress Enter to continue...")
    
    def module_8_analyze_trends(self):
        """Module 8: Analyze Trends"""
        print("\n📈 MODULE 8: TREND ANALYSIS")
        print("=" * 28)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        print("Time periods:")
        periods = ["Daily", "Weekly", "Monthly"]
        for i, period in enumerate(periods, 1):
            print(f"{i}. {period}")
        
        choice = self.get_user_input("Select time period (1-3)", "int")
        
        if 1 <= choice <= 3:
            time_period = periods[choice - 1]
            result = self.bi.analyze_trends(self.bi.cleaned_data, time_period)
            self.print_results("✅ Trend Analysis Results", result)
            self.current_step = max(self.current_step, 9)
        else:
            print("❌ Invalid time period selection")
        
        input("\nPress Enter to continue...")
    
    def module_9_analyze_sentiment(self):
        """Module 9: Analyze Sentiment"""
        print("\n💭 MODULE 9: SENTIMENT ANALYSIS")
        print("=" * 32)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        result = self.bi.analyze_sentiment(self.bi.cleaned_data)
        self.print_results("✅ Sentiment Analysis Results", result)
        
        self.current_step = max(self.current_step, 10)
        input("\nPress Enter to continue...")
    
    def module_10_ab_test(self):
        """Module 10: Run A/B Test"""
        print("\n🧪 MODULE 10: A/B TESTING")
        print("=" * 25)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        print("Available variables:")
        if self.bi.variables:
            for i, var in enumerate(self.bi.variables, 1):
                print(f"{i}. {var}")
        
        test_variable = self.get_user_input("Test Variable")
        success_metric = self.get_user_input("Success Metric")
        
        if test_variable and success_metric:
            result = self.bi.run_ab_test(self.bi.cleaned_data, test_variable, success_metric)
            self.print_results("✅ A/B Test Results", result)
            self.current_step = max(self.current_step, 11)
        else:
            print("❌ Please provide both test variable and success metric")
        
        input("\nPress Enter to continue...")
    
    def module_11_chat(self):
        """Module 11: Chat with Data"""
        print("\n💬 MODULE 11: CHAT WITH DATA")
        print("=" * 30)
        print("Ask questions about your analysis. Type 'back' to return to menu.")
        
        while True:
            question = self.get_user_input("\n❓ Your Question (or 'back' to exit)")
            
            if question.lower() == 'back':
                break
            
            result = self.bi.chat_with_data(question)
            
            if result.get("success"):
                print(f"\n🤖 Response: {result['response']}")
                print(f"📊 Context Used: {result['context_used']} analysis modules")
            else:
                print(f"❌ Error: {result.get('error', 'Unknown error')}")
        
        self.current_step = max(self.current_step, 12)
    
    def module_12_export(self):
        """Module 12: Export Results"""
        print("\n📤 MODULE 12: EXPORT RESULTS")
        print("=" * 30)
        
        filename = self.get_user_input("Export filename (or press Enter for auto-generated)")
        
        if not filename:
            filename = None
        
        result = self.bi.export_results(filename)
        self.print_results("✅ Export Results", result)
    
    def module_13_import(self):
        """Module 13: Import Previous Analysis"""
        print("\n📥 IMPORT PREVIOUS ANALYSIS")
        print("=" * 30)
        
        # List available JSON files
        json_files = [f for f in os.listdir('.') if f.endswith('.json')]
        
        if json_files:
            print("Available analysis files:")
            for i, file in enumerate(json_files, 1):
                print(f"{i}. {file}")
            
            choice = self.get_user_input("Select file number", "int")
            
            if 1 <= choice <= len(json_files):
                filename = json_files[choice - 1]
                result = self.bi.import_results(filename)
                self.print_results("✅ Import Results", result)
                
                if result.get("success"):
                    self.current_step = 12  # Set to final step
            else:
                print("❌ Invalid file selection")
        else:
            filename = self.get_user_input("Enter filename to import")
            result = self.bi.import_results(filename)
            self.print_results("✅ Import Results", result)
    
    def module_14_export_csv(self):
        """Module 14: Export Data as CSV"""
        print("\n📄 EXPORT DATA AS CSV")
        print("=" * 25)
        
        print("Data types:")
        print("1. Sample Data")
        print("2. Cleaned Data")
        
        choice = self.get_user_input("Select data type (1-2)", "int")
        
        if choice == 1:
            result = self.bi.export_data_csv("sample")
        elif choice == 2:
            result = self.bi.export_data_csv("cleaned")
        else:
            print("❌ Invalid selection")
            return
        
        self.print_results("✅ CSV Export Results", result)
    
    def run(self):
        """Main CLI loop"""
        self.print_header()
        
        while True:
            self.print_menu()
            
            try:
                choice = self.get_user_input("Select option (1-15)", "int")
                
                if choice == 1:
                    self.module_1_api_key()
                elif choice == 2:
                    self.module_2_extract_variables()
                elif choice == 3:
                    self.module_3_generate_questionnaire()
                elif choice == 4:
                    self.module_4_generate_data()
                elif choice == 5:
                    self.module_5_clean_data()
                elif choice == 6:
                    self.module_6_perform_eda()
                elif choice == 7:
                    self.module_7_train_model()
                elif choice == 8:
                    self.module_8_analyze_trends()
                elif choice == 9:
                    self.module_9_analyze_sentiment()
                elif choice == 10:
                    self.module_10_ab_test()
                elif choice == 11:
                    self.module_11_chat()
                elif choice == 12:
                    self.module_12_export()
                elif choice == 13:
                    self.module_13_import()
                elif choice == 14:
                    self.module_14_export_csv()
                elif choice == 15:
                    print("\n👋 Thank you for using BI Storyteller!")
                    break
                else:
                    print("❌ Invalid option. Please select 1-15.")
                    
            except KeyboardInterrupt:
                print("\n\n👋 Goodbye!")
                break
            except Exception as e:
                print(f"❌ An error occurred: {str(e)}")
                input("Press Enter to continue...")
    
    def module_1_api_key(self):
        """Module 1: Set API Key"""
        print("\n🔑 MODULE 1: API KEY SETUP")
        print("=" * 30)
        print("Enter your Groq API key for AI-powered analysis.")
        print("Leave empty to use offline mode with fallback functionality.")
        
        api_key = self.get_user_input("Groq API Key (or press Enter to skip)")
        
        if api_key:
            result = self.bi.set_groq_api_key(api_key)
            self.print_results("✅ API Key Setup", result)
        else:
            print("⚡ Using offline mode - fallback analysis will be used")
        
        self.current_step = max(self.current_step, 2)
        input("\nPress Enter to continue...")
    
    def module_2_extract_variables(self):
        """Module 2: Extract Variables"""
        print("\n📝 MODULE 2: VARIABLE EXTRACTION")
        print("=" * 35)
        
        business_problem = self.get_user_input("Describe your business problem")
        
        if business_problem:
            result = self.bi.extract_variables(business_problem)
            self.print_results("✅ Variable Extraction Results", result)
            
            if result.get("success"):
                print(f"\n📊 Extracted Variables:")
                for var in result["variables"]:
                    print(f"  • {var.replace('_', ' ').title()}")
            
            self.current_step = max(self.current_step, 3)
        else:
            print("❌ Please provide a business problem description")
        
        input("\nPress Enter to continue...")
    
    def module_3_generate_questionnaire(self):
        """Module 3: Generate Questionnaire"""
        print("\n📋 MODULE 3: QUESTIONNAIRE GENERATION")
        print("=" * 40)
        
        if not self.bi.variables:
            print("❌ Please extract variables first (Module 2)")
            input("Press Enter to continue...")
            return
        
        result = self.bi.generate_questionnaire(self.bi.variables, "")
        self.print_results("✅ Questionnaire Generation Results", result)
        
        if result.get("success"):
            print("\n📝 Sample Questions:")
            for i, question in enumerate(result["questionnaire"][:3]):
                print(f"{i+1}. {question['question']}")
                if question["type"] == "multiple_choice":
                    print(f"   Options: {', '.join(question['options'])}")
        
        self.current_step = max(self.current_step, 4)
        input("\nPress Enter to continue...")
    
    def module_4_generate_data(self):
        """Module 4: Generate Sample Data"""
        print("\n🔢 MODULE 4: SAMPLE DATA GENERATION")
        print("=" * 38)
        
        if not self.bi.variables:
            print("❌ Please extract variables first (Module 2)")
            input("Press Enter to continue...")
            return
        
        sample_size = self.get_user_input("Sample Size (100-10000)", "int")
        
        if 100 <= sample_size <= 10000:
            print(f"🔄 Generating {sample_size} sample records...")
            result = self.bi.generate_sample_data(self.bi.variables, sample_size)
            self.print_results("✅ Sample Data Generation Results", result)
            
            if result.get("success"):
                print(f"\n📊 Sample Record:")
                sample_record = {k: v for k, v in result["data"][0].items() if k != "timestamp"}
                self.print_dict(sample_record, indent=1)
            
            self.current_step = max(self.current_step, 5)
        else:
            print("❌ Sample size must be between 100 and 10,000")
        
        input("\nPress Enter to continue...")
    
    def module_5_clean_data(self):
        """Module 5: Clean Data"""
        print("\n🧹 MODULE 5: DATA CLEANING")
        print("=" * 28)
        
        if not self.bi.sample_data:
            print("❌ Please generate sample data first (Module 4)")
            input("Press Enter to continue...")
            return
        
        print("🔄 Cleaning data...")
        result = self.bi.clean_data(self.bi.sample_data)
        
        if result.get("success"):
            print(f"✅ Data cleaning completed!")
            print(f"📊 Original records: {result['original_size']}")
            print(f"📊 Cleaned records: {result['cleaned_size']}")
            print(f"🗑️  Outliers removed: {result['removed_outliers']}")
            print(f"📈 Data quality: {((result['cleaned_size'] / result['original_size']) * 100):.1f}%")
        else:
            print(f"❌ Error: {result.get('error', 'Unknown error')}")
        
        self.current_step = max(self.current_step, 6)
        input("\nPress Enter to continue...")
    
    def module_6_perform_eda(self):
        """Module 6: Perform EDA"""
        print("\n📊 MODULE 6: EXPLORATORY DATA ANALYSIS")
        print("=" * 40)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        print("🔄 Performing exploratory data analysis...")
        result = self.bi.perform_eda(self.bi.cleaned_data)
        
        if result.get("success"):
            print("✅ EDA Analysis completed!")
            
            # Show key insights
            if result["results"].get("insights"):
                print("\n🔍 Key Insights:")
                for insight in result["results"]["insights"]:
                    print(f"  • {insight}")
            
            # Show top correlations
            if result["results"].get("correlations"):
                print("\n📈 Top Correlations:")
                correlations = sorted(result["results"]["correlations"].items(), 
                                    key=lambda x: abs(x[1]), reverse=True)[:5]
                for pair, corr in correlations:
                    print(f"  • {pair}: {corr}")
        else:
            print(f"❌ Error: {result.get('error', 'Unknown error')}")
        
        self.current_step = max(self.current_step, 7)
        input("\nPress Enter to continue...")
    
    def module_7_train_model(self):
        """Module 7: Train Predictive Model"""
        print("\n🤖 MODULE 7: PREDICTIVE ANALYTICS")
        print("=" * 35)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        print("Available algorithms:")
        algorithms = ["Random Forest", "Logistic Regression", "SVM", "Neural Network"]
        for i, alg in enumerate(algorithms, 1):
            print(f"{i}. {alg}")
        
        choice = self.get_user_input("Select algorithm (1-4)", "int")
        
        if 1 <= choice <= 4:
            algorithm = algorithms[choice - 1]
            print(f"🔄 Training {algorithm} model...")
            result = self.bi.train_predictive_model(self.bi.cleaned_data, algorithm)
            
            if result.get("success"):
                print(f"✅ Model training completed!")
                print(f"🎯 Algorithm: {result['results']['algorithm']}")
                print(f"📊 Accuracy: {(result['results']['metrics']['accuracy'] * 100):.1f}%")
                print(f"📊 Precision: {(result['results']['metrics']['precision'] * 100):.1f}%")
                print(f"📊 Recall: {(result['results']['metrics']['recall'] * 100):.1f}%")
                
                # Show feature importance
                if result["results"].get("feature_importance"):
                    print("\n🔍 Top Feature Importance:")
                    importance = sorted(result["results"]["feature_importance"].items(), 
                                      key=lambda x: x[1], reverse=True)[:5]
                    for feature, imp in importance:
                        print(f"  • {feature}: {(imp * 100):.1f}%")
            else:
                print(f"❌ Error: {result.get('error', 'Unknown error')}")
            
            self.current_step = max(self.current_step, 8)
        else:
            print("❌ Invalid algorithm selection")
        
        input("\nPress Enter to continue...")
    
    def module_8_analyze_trends(self):
        """Module 8: Analyze Trends"""
        print("\n📈 MODULE 8: TREND ANALYSIS")
        print("=" * 28)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        print("Time periods:")
        periods = ["Daily", "Weekly", "Monthly"]
        for i, period in enumerate(periods, 1):
            print(f"{i}. {period}")
        
        choice = self.get_user_input("Select time period (1-3)", "int")
        
        if 1 <= choice <= 3:
            time_period = periods[choice - 1]
            print(f"🔄 Analyzing {time_period.lower()} trends...")
            result = self.bi.analyze_trends(self.bi.cleaned_data, time_period)
            
            if result.get("success"):
                print(f"✅ Trend analysis completed!")
                print(f"📊 Time Period: {result['results']['time_period']}")
                print(f"📊 Analysis Periods: {result['results']['analysis_periods']}")
                
                # Show trends
                if result["results"].get("trends"):
                    print("\n📈 Key Trends:")
                    for variable, trend in result["results"]["trends"].items():
                        print(f"  • {variable}: {trend['direction']} (slope: {trend['slope']})")
            else:
                print(f"❌ Error: {result.get('error', 'Unknown error')}")
            
            self.current_step = max(self.current_step, 9)
        else:
            print("❌ Invalid time period selection")
        
        input("\nPress Enter to continue...")
    
    def module_9_analyze_sentiment(self):
        """Module 9: Analyze Sentiment"""
        print("\n💭 MODULE 9: SENTIMENT ANALYSIS")
        print("=" * 32)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        print("🔄 Analyzing sentiment...")
        result = self.bi.analyze_sentiment(self.bi.cleaned_data)
        
        if result.get("success"):
            print("✅ Sentiment analysis completed!")
            print(f"📊 Total Analyzed: {result['results']['total_analyzed']}")
            print(f"🎯 Dominant Sentiment: {result['results']['dominant_sentiment']}")
            
            print("\n📊 Sentiment Distribution:")
            for sentiment, percentage in result["results"]["sentiment_distribution"].items():
                print(f"  • {sentiment}: {percentage}%")
        else:
            print(f"❌ Error: {result.get('error', 'Unknown error')}")
        
        self.current_step = max(self.current_step, 10)
        input("\nPress Enter to continue...")
    
    def module_10_ab_test(self):
        """Module 10: Run A/B Test"""
        print("\n🧪 MODULE 10: A/B TESTING")
        print("=" * 25)
        
        if not self.bi.cleaned_data:
            print("❌ Please clean data first (Module 5)")
            input("Press Enter to continue...")
            return
        
        print("Available variables:")
        if self.bi.variables:
            for i, var in enumerate(self.bi.variables, 1):
                print(f"  {i}. {var}")
        
        test_variable = self.get_user_input("Test Variable")
        success_metric = self.get_user_input("Success Metric")
        
        if test_variable and success_metric:
            print("🔄 Running A/B test...")
            result = self.bi.run_ab_test(self.bi.cleaned_data, test_variable, success_metric)
            
            if result.get("success"):
                print("✅ A/B test completed!")
                print(f"👥 Group A: {result['results']['group_a']['size']} users, {(result['results']['group_a']['success_rate'] * 100):.1f}% success")
                print(f"👥 Group B: {result['results']['group_b']['size']} users, {(result['results']['group_b']['success_rate'] * 100):.1f}% success")
                print(f"📊 P-Value: {result['results']['statistical_test']['p_value']}")
                print(f"🏆 Winner: {result['results']['conclusion']['winner']}")
                print(f"📈 Lift: {result['results']['conclusion']['lift']}%")
            else:
                print(f"❌ Error: {result.get('error', 'Unknown error')}")
            
            self.current_step = max(self.current_step, 11)
        else:
            print("❌ Please provide both test variable and success metric")
        
        input("\nPress Enter to continue...")
    
    def module_11_chat(self):
        """Module 11: Chat with Data"""
        print("\n💬 MODULE 11: CHAT WITH DATA")
        print("=" * 30)
        print("Ask questions about your analysis. Type 'back' to return to menu.")
        
        while True:
            question = self.get_user_input("\n❓ Your Question (or 'back' to exit)")
            
            if question.lower() == 'back':
                break
            
            result = self.bi.chat_with_data(question)
            
            if result.get("success"):
                print(f"\n🤖 Response: {result['response']}")
                print(f"📊 Context Used: {result['context_used']} analysis modules")
            else:
                print(f"❌ Error: {result.get('error', 'Unknown error')}")
        
        self.current_step = max(self.current_step, 12)
    
    def module_12_export(self):
        """Module 12: Export Results"""
        print("\n📤 MODULE 12: EXPORT RESULTS")
        print("=" * 30)
        
        filename = self.get_user_input("Export filename (or press Enter for auto-generated)")
        
        if not filename:
            filename = None
        
        print("🔄 Exporting analysis results...")
        result = self.bi.export_results(filename)
        
        if result.get("success"):
            print("✅ Export completed!")
            print(f"📁 Filename: {result['filename']}")
            print(f"📊 Modules Completed: {result['modules_completed']}")
            print(f"💾 File Size: {(result['file_size'] / 1024):.1f} KB")
        else:
            print(f"❌ Error: {result.get('error', 'Unknown error')}")


def main():
    """Main function to start CLI interface"""
    cli = BIStoryteller_CLI()
    cli.run()


if __name__ == "__main__":
    main()