/*
 * SwarmAI Framework
 * Copyright (c) 2025 IntelliSwarm.ai (MIT License)
 *
 * Licensed under the MIT License. See LICENSE file for details.
 */
package ai.intelliswarm.swarmai.tool.common;

import ai.intelliswarm.swarmai.tool.base.BaseTool;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.HashMap;
import java.util.Map;
import java.util.Arrays;
import java.util.List;

/**
 * Data Analysis Tool for Processing Market Research Data
 *
 * Provides analytical capabilities for processing market research data,
 * performing comparative analysis, and generating insights.
 * In production, this could integrate with analytics libraries or services.
 */
public class DataAnalysisTool implements BaseTool {

    private static final Logger logger = LoggerFactory.getLogger(DataAnalysisTool.class);

    @Override
    public String getFunctionName() {
        return "data_analysis";
    }

    @Override
    public String getDescription() {
        return "Analyze market research data to identify patterns, trends, and insights. " +
               "Performs comparative analysis, statistical calculations, and generates structured findings.";
    }

    @Override
    public Object execute(Map<String, Object> parameters) {
        String analysisType = (String) parameters.get("analysis_type");
        String dataInput = (String) parameters.get("data_input");
        List<String> metrics = (List<String>) parameters.getOrDefault("metrics", Arrays.asList("all"));

        logger.info("📊 Executing data analysis: type='{}', metrics={}", analysisType, metrics);

        return switch (analysisType.toLowerCase()) {
            case "competitive" -> performCompetitiveAnalysis(dataInput, metrics);
            case "market" -> performMarketAnalysis(dataInput, metrics);
            case "financial" -> performFinancialAnalysis(dataInput, metrics);
            case "trend" -> performTrendAnalysis(dataInput, metrics);
            default -> performGeneralAnalysis(dataInput, metrics);
        };
    }

    private Map<String, Object> performCompetitiveAnalysis(String dataInput, List<String> metrics) {
        Map<String, Object> analysis = new HashMap<>();
        analysis.put("analysis_type", "competitive");
        analysis.put("timestamp", System.currentTimeMillis());

        // Simulate competitive analysis based on common AI/ML platform metrics
        analysis.put("competitive_matrix", generateCompetitiveMatrix());
        analysis.put("market_positioning", analyzeMarketPositioning());
        analysis.put("strength_analysis", analyzeCompetitorStrengths());
        analysis.put("pricing_analysis", analyzePricingStrategies());
        analysis.put("feature_comparison", compareFeatures());
        analysis.put("market_share_estimates", estimateMarketShare());

        analysis.put("key_insights", """
            **Key Competitive Insights:**

            1. **Market Leadership:** OpenAI leads in consumer adoption and brand recognition,
               while Google/Microsoft lead in enterprise integration.

            2. **Pricing Strategies:**
               - OpenAI: Premium pricing for advanced models
               - Google: Competitive pricing with enterprise bundles
               - Anthropic: Premium safety-focused positioning
               - AWS/Azure: Usage-based scaling models

            3. **Differentiation Factors:**
               - OpenAI: Model performance and consumer experience
               - Google: Integration with workspace tools
               - Anthropic: AI safety and enterprise compliance
               - Microsoft: Enterprise ecosystem integration
               - AWS: Infrastructure and scaling capabilities

            4. **Market Gaps:**
               - Industry-specific AI solutions
               - Mid-market pricing tiers
               - Compliance-first enterprise offerings
               - Multi-modal integration platforms
            """);

        return analysis;
    }

    private Map<String, Object> performMarketAnalysis(String dataInput, List<String> metrics) {
        Map<String, Object> analysis = new HashMap<>();
        analysis.put("analysis_type", "market");

        analysis.put("market_size", """
            **Market Size Analysis:**
            - Total Addressable Market (TAM): $1.8T by 2030
            - Serviceable Addressable Market (SAM): $340B by 2030
            - Current Market Size: $196B (2024)
            - Annual Growth Rate: 36.6% CAGR
            """);

        analysis.put("growth_drivers", """
            **Key Growth Drivers:**
            1. Enterprise digital transformation initiatives
            2. Increasing demand for automation and efficiency
            3. Regulatory compliance and governance needs
            4. Integration with existing enterprise systems
            5. Cost reduction pressures in competitive markets
            """);

        analysis.put("market_segments", generateMarketSegmentation());

        return analysis;
    }

    private Map<String, Object> performFinancialAnalysis(String dataInput, List<String> metrics) {
        Map<String, Object> analysis = new HashMap<>();
        analysis.put("analysis_type", "financial");

        analysis.put("revenue_analysis", """
            **Revenue Model Analysis:**

            **OpenAI:**
            - Estimated Revenue: $3.4B (2024 projected)
            - Model: Subscription ($20/month) + API usage
            - Growth: 500%+ YoY

            **Anthropic:**
            - Estimated Revenue: $850M (2024 projected)
            - Model: Enterprise contracts + API usage
            - Growth: 300%+ YoY

            **Google AI (Subset):**
            - Estimated Revenue: $2.1B (2024 AI-specific)
            - Model: Integrated with Google Cloud
            - Growth: 150% YoY
            """);

        analysis.put("investment_trends", """
            **Investment and Funding Trends:**
            - Total AI Investment 2024: $41B (projected)
            - Enterprise AI: $12B in funding
            - Average Series A: $15M
            - Average Series B: $45M
            - Valuation Multiples: 15-25x revenue for leading platforms
            """);

        return analysis;
    }

    private Map<String, Object> performTrendAnalysis(String dataInput, List<String> metrics) {
        Map<String, Object> analysis = new HashMap<>();
        analysis.put("analysis_type", "trend");

        analysis.put("emerging_trends", """
            **Emerging Market Trends:**

            1. **Multi-Modal AI Integration** (High Priority)
               - Text + Image + Video + Audio processing
               - Expected growth: 400% by 2026

            2. **AI Agent Frameworks** (High Priority)
               - Autonomous agent orchestration
               - Market size: $15B by 2027

            3. **Industry-Specific AI** (Medium Priority)
               - Healthcare, Finance, Legal vertical solutions
               - Expected growth: 250% by 2026

            4. **Edge AI Deployment** (Medium Priority)
               - On-device and local processing
               - Privacy-focused solutions

            5. **AI Governance & Compliance** (High Priority)
               - Regulatory compliance tools
               - Audit and monitoring capabilities
            """);

        return analysis;
    }

    private Map<String, Object> performGeneralAnalysis(String dataInput, List<String> metrics) {
        Map<String, Object> analysis = new HashMap<>();
        analysis.put("analysis_type", "general");
        analysis.put("summary", "General data analysis performed on provided input");

        // Simulate basic statistical analysis
        analysis.put("statistics", Map.of(
            "data_points", 150,
            "categories", 8,
            "trends_identified", 5,
            "confidence_score", 0.85
        ));

        return analysis;
    }

    private Map<String, Object> generateCompetitiveMatrix() {
        return Map.of(
            "dimensions", Arrays.asList("Model Quality", "Pricing", "Enterprise Features", "Developer Experience", "Market Presence"),
            "competitors", Map.of(
                "OpenAI", Map.of("Model Quality", 9.2, "Pricing", 7.5, "Enterprise Features", 8.0, "Developer Experience", 9.0, "Market Presence", 9.5),
                "Anthropic", Map.of("Model Quality", 8.8, "Pricing", 7.8, "Enterprise Features", 8.5, "Developer Experience", 8.2, "Market Presence", 7.0),
                "Google AI", Map.of("Model Quality", 8.5, "Pricing", 8.5, "Enterprise Features", 9.0, "Developer Experience", 8.0, "Market Presence", 8.5),
                "Microsoft AI", Map.of("Model Quality", 8.0, "Pricing", 8.8, "Enterprise Features", 9.2, "Developer Experience", 8.5, "Market Presence", 8.8),
                "AWS Bedrock", Map.of("Model Quality", 7.8, "Pricing", 9.0, "Enterprise Features", 9.0, "Developer Experience", 8.8, "Market Presence", 8.2)
            )
        );
    }

    private String analyzeMarketPositioning() {
        return """
            **Market Positioning Analysis:**

            **Leaders Quadrant:**
            - OpenAI: Innovation leader, consumer-focused
            - Microsoft: Enterprise integration leader

            **Challengers Quadrant:**
            - Google: Ecosystem integration challenger
            - AWS: Infrastructure challenger

            **Niche Players:**
            - Anthropic: Safety-focused niche
            - Specialized vertical solutions
            """;
    }

    private String analyzeCompetitorStrengths() {
        return """
            **Competitor Strengths Analysis:**

            **OpenAI Strengths:**
            - Superior model performance (GPT-4)
            - Strong brand recognition and consumer adoption
            - First-mover advantage in conversational AI

            **Anthropic Strengths:**
            - Focus on AI safety and alignment
            - Strong enterprise compliance features
            - Constitutional AI approach

            **Google Strengths:**
            - Deep technical expertise and research
            - Integration with Google ecosystem
            - Competitive pricing

            **Microsoft Strengths:**
            - Enterprise customer relationships
            - Azure cloud integration
            - Comprehensive developer tools
            """;
    }

    private String analyzePricingStrategies() {
        return """
            **Pricing Strategy Analysis:**

            **Premium Tier:**
            - OpenAI: $20/month consumer, $0.01-0.12/1K tokens
            - Anthropic: Enterprise contracts, $0.008-0.024/1K tokens

            **Competitive Tier:**
            - Google: $0.0005-0.002/1K tokens (competitive positioning)
            - Microsoft: Bundled with Azure credits

            **Value Tier:**
            - AWS Bedrock: Pay-per-use with volume discounts
            - Open source alternatives: Free/low-cost options
            """;
    }

    private String compareFeatures() {
        return """
            **Feature Comparison Matrix:**

            | Feature | OpenAI | Anthropic | Google | Microsoft | AWS |
            |---------|---------|-----------|---------|-----------|------|
            | Text Generation | ✓✓✓ | ✓✓✓ | ✓✓ | ✓✓ | ✓✓ |
            | Code Generation | ✓✓✓ | ✓✓ | ✓✓ | ✓✓✓ | ✓✓ |
            | Multi-modal | ✓✓✓ | ✓✓ | ✓✓✓ | ✓✓ | ✓✓ |
            | Enterprise SSO | ✓✓ | ✓✓✓ | ✓✓✓ | ✓✓✓ | ✓✓✓ |
            | Custom Training | ✓ | ✓✓ | ✓✓ | ✓✓ | ✓✓✓ |
            | On-Premise | ✗ | ✓ | ✓ | ✓ | ✓✓✓ |
            """;
    }

    private String estimateMarketShare() {
        return """
            **Market Share Estimates (2024):**

            **By Revenue:**
            - OpenAI: ~35% ($3.4B of ~$10B market)
            - Google AI: ~21% ($2.1B)
            - Microsoft AI: ~18% ($1.8B)
            - AWS Bedrock: ~12% ($1.2B)
            - Anthropic: ~8% ($0.8B)
            - Others: ~6% ($0.6B)

            **By Enterprise Adoption:**
            - Microsoft: ~40% (Office 365 integration)
            - Google: ~25% (Workspace integration)
            - AWS: ~20% (Cloud infrastructure)
            - OpenAI: ~10% (Direct enterprise)
            - Others: ~5%
            """;
    }

    private String generateMarketSegmentation() {
        return """
            **Market Segmentation Analysis:**

            **By Company Size:**
            - Enterprise (1000+ employees): 65% of revenue, 15% of customers
            - Mid-market (100-999 employees): 25% of revenue, 35% of customers
            - SMB (<100 employees): 10% of revenue, 50% of customers

            **By Industry Vertical:**
            - Technology: 35%
            - Financial Services: 18%
            - Healthcare: 12%
            - Retail/E-commerce: 10%
            - Manufacturing: 8%
            - Other: 17%

            **By Use Case:**
            - Customer Service: 25%
            - Content Generation: 20%
            - Code Development: 18%
            - Data Analysis: 15%
            - Process Automation: 12%
            - Other: 10%
            """;
    }

    @Override
    public Map<String, Object> getParameterSchema() {
        Map<String, Object> schema = new HashMap<>();
        schema.put("type", "object");

        Map<String, Object> properties = new HashMap<>();

        Map<String, Object> analysisType = new HashMap<>();
        analysisType.put("type", "string");
        analysisType.put("description", "Type of analysis: competitive, market, financial, trend, general");
        analysisType.put("enum", Arrays.asList("competitive", "market", "financial", "trend", "general"));
        properties.put("analysis_type", analysisType);

        Map<String, Object> dataInput = new HashMap<>();
        dataInput.put("type", "string");
        dataInput.put("description", "Input data or research findings to analyze");
        properties.put("data_input", dataInput);

        Map<String, Object> metrics = new HashMap<>();
        metrics.put("type", "array");
        metrics.put("description", "Specific metrics or dimensions to focus on");
        metrics.put("items", Map.of("type", "string"));
        properties.put("metrics", metrics);

        schema.put("properties", properties);
        schema.put("required", new String[]{"analysis_type", "data_input"});

        return schema;
    }

    @Override
    public boolean isAsync() {
        return false;
    }

    @Override
    public String getTriggerWhen() {
        return "User needs statistical analysis, pattern detection, trend identification, or data summarization.";
    }

    @Override
    public String getAvoidWhen() {
        return "User needs raw data access (use file tools) or specific CSV operations (use csv_analysis).";
    }

    @Override
    public String getCategory() {
        return "analysis";
    }

    @Override
    public List<String> getTags() {
        return List.of("analytics", "statistics", "trends", "patterns");
    }

    @Override
    public Map<String, Object> getOutputSchema() {
        return Map.of(
            "type", "json",
            "description", "Structured analysis results with analysis type, key insights, statistical data, and market metrics"
        );
    }

    @Override
    public int getMaxUsageCount() {
        return 25; // Allow up to 25 analyses per agent
    }

    @Override
    public boolean isCacheable() {
        return true; // Cache analysis results
    }
}
