feat: Initialize Craze Analytix project structure

Sets up the project with Vite, React, Tailwind CSS, Gemini AI integration, and necessary dependencies for data analysis. Includes initial configuration for TypeScript, Tailwind, and project metadata.

services/geminiService.ts

@@ -0,0 +1,123 @@
+
+import { GoogleGenAI } from "@google/genai";
+import { AggregatedData } from "../types";
+
+const SYSTEM_INSTRUCTION = `
+You are an expert Data Analyst Assistant for "Craze Analytix".
+You have access to a structured dataset of sales performance including Revenue (Sell Out), Units, Product Lines, and Seasonality.
+
+Your Capabilities:
+1. **Analyze Trends**: Use the provided Seasonality and Yearly Breakdown data.
+2. **Perform Calculations**: You have access to detailed Product Line totals. You MUST calculate growth percentages, market shares, and sums dynamically if the user asks.
+3. **Compare**: Compare performance between years (e.g., 2024 vs 2025).
+
+Rules:
+- If the user asks for a calculation (e.g., "What is the % share of Line X?"), perform the math using the provided numbers.
+- Always format currency as € (e.g., €1,200) and units with 'u' or 'units' (e.g., 500 units).
+- Be concise but insightful. Point out significant growth or decline.
+- If data is missing for a specific query, state clearly that it is not in the current filtered view.
+`;
+
+const formatCurrency = (val: number) => `€${val.toLocaleString(undefined, {minimumFractionDigits: 0, maximumFractionDigits: 0})}`;
+const formatUnits = (val: number) => `${val.toLocaleString()} units`;
+
+export const queryGemini = async (
+  apiKey: string,
+  question: string, 
+  context: AggregatedData, 
+  filteredRecordCount: number
+): Promise<string> => {
+  
+  if (!apiKey) {
+    return "Please provide your Gemini API Key in the settings to enable the AI assistant.";
+  }
+
+  try {
+    // Ensure the key is clean of whitespace
+    const ai = new GoogleGenAI({ apiKey: apiKey.trim() });
+
+    // --- CONTEXT GENERATION ---
+    // We construct a structured report mirroring the dashboard charts
+    
+    // 1. Totals by Year (KPI Cards)
+    const yearlySummary = Object.entries(context.totalsByYear)
+        .sort((a, b) => parseInt(b[0]) - parseInt(a[0])) // Descending years
+        .map(([year, data]) => `  - ${year}: ${formatCurrency(data.sellOut)} | ${formatUnits(data.units)}`)
+        .join('\n');
+
+    // 2. Seasonality (Line Chart Data)
+    const seasonalitySummary = context.seasonality.map(p => {
+        const yearValues = context.availableYears.map(y => `${y}: ${formatCurrency(p[y] as number || 0)}`).join(', ');
+        return `  - ${p.name}: [${yearValues}]`;
+    }).join('\n');
+
+    // 3. Growth/Decline
+    const growthSummary = context.topMovers.slice(0, 10).map(m => 
+        `  - ${m.line}: +€${m.sellOutGrowthValue.toLocaleString()} (${m.sellOutGrowthPercentage.toFixed(1)}%)`
+    ).join('\n');
+
+    const declineSummary = context.bottomMovers.slice(0, 10).map(m => 
+        `  - ${m.line}: -€${Math.abs(m.sellOutGrowthValue).toLocaleString()} (${m.sellOutGrowthPercentage.toFixed(1)}%)`
+    ).join('\n');
+
+    // 4. DETAILED BREAKDOWN (For Calculations)
+    // We provide a JSON-like structure of ALL top product lines so the AI can compute shares/totals.
+    // We limit this to top 100 to avoid token limits, which covers most relevant data.
+    const detailedLines = context.byLine.slice(0, 100).map(l => ({
+        name: l.name,
+        revenue: l.value,
+        units: l.units
+    }));
+
+    const fullReport = `
+REPORT CONTEXT (Based on Current Filters):
+------------------------------------------
+GLOBAL METRICS:
+Total Sell Out: ${formatCurrency(context.totalSellOut)}
+Total Units: ${formatUnits(context.totalUnits)}
+Records Analyzed: ${filteredRecordCount}
+Years Available: ${context.availableYears.join(', ')}
+
+YEARLY TOTALS:
+${yearlySummary}
+
+MONTHLY TRENDS (Seasonality):
+${seasonalitySummary}
+
+TOP PERFORMERS (Growth YoY):
+${growthSummary}
+
+WORST PERFORMERS (Decline YoY):
+${declineSummary}
+
+DETAILED PRODUCT LINE DATA (Use this for specific calculations):
+${JSON.stringify(detailedLines, null, 2)}
+`;
+
+    const response = await ai.models.generateContent({
+      model: 'gemini-3-pro-preview', // Updated to the latest capable model for complex reasoning
+      contents: [
+        {
+          role: 'user',
+          parts: [{ text: `Context Data:\n${fullReport}\n\nUser Question: ${question}` }]
+        }
+      ],
+      config: {
+        systemInstruction: SYSTEM_INSTRUCTION,
+      }
+    });
+
+    return response.text || "I couldn't generate a response based on the data provided.";
+  } catch (error: any) {
+    console.error("Gemini API Error:", error);
+    
+    if (error.message && error.message.includes("403")) {
+       return "Error 403: Invalid API Key. Please check your key in the settings.";
+    }
+    if (error.message && error.message.includes("429")) {
+        return "Error 429: Quota exceeded. You are sending too many requests.";
+    }
+
+    return `Error: ${error.message || "An unexpected error occurred while analyzing the data."}`;
+  }
+};