test: add LLM retrieval accuracy tests

benchmarks/src/datasets.ts

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+/**
+ * Datasets for TOON benchmarks
+ *
+ * These datasets are designed to test TOON's strengths and weaknesses:
+ * - Tabular: Uniform records (TOON optimal)
+ * - Nested: Complex structures with nested objects
+ * - Analytics: Time-series data
+ */
+
+import type { Dataset } from './types'
+import { faker } from '@faker-js/faker'
+import githubRepos from '../data/github-repos.json' with { type: 'json' }
+
+// Seed for reproducibility
+faker.seed(12345)
+
+/**
+ * Tabular dataset: 100 uniform employee records
+ *
+ * @remarks
+ * Tests TOON's tabular array format
+ */
+const departments = ['Engineering', 'Sales', 'Marketing', 'HR', 'Operations', 'Finance']
+const tabularDataset: Dataset = {
+  name: 'tabular',
+  description: 'Uniform employee records (TOON optimal format)',
+  data: {
+    employees: Array.from({ length: 100 }, (_, i) => {
+      const yearsExp = faker.number.int({ min: 1, max: 20 })
+      return {
+        id: i + 1,
+        name: faker.person.fullName(),
+        email: faker.internet.email().toLowerCase(),
+        department: departments[i % departments.length]!,
+        salary: faker.number.int({ min: 45000, max: 150000 }),
+        yearsExperience: yearsExp,
+        active: faker.datatype.boolean(0.8), // 80% active
+      }
+    }),
+  },
+}
+
+/**
+ * Nested dataset: 50 e-commerce orders with nested structures
+ *
+ * @remarks
+ * Tests TOON's handling of complex nested objects
+ */
+const productNames = ['Wireless Mouse', 'USB Cable', 'Laptop Stand', 'Keyboard', 'Webcam', 'Headphones', 'Monitor', 'Desk Lamp']
+const statuses = ['pending', 'processing', 'shipped', 'delivered', 'cancelled']
+
+const nestedDataset: Dataset = {
+  name: 'nested',
+  description: 'E-commerce orders with nested structures',
+  data: {
+    orders: Array.from({ length: 50 }, (_, i) => {
+      const customerId = (i % 20) + 1
+      const itemCount = faker.number.int({ min: 1, max: 4 })
+
+      const items = Array.from({ length: itemCount }, (_, j) => {
+        const price = faker.number.float({ min: 9.99, max: 199.99, fractionDigits: 2 })
+        const quantity = faker.number.int({ min: 1, max: 5 })
+        return {
+          sku: `SKU-${faker.string.alphanumeric({ length: 6 }).toUpperCase()}`,
+          name: productNames[j % productNames.length]!,
+          quantity,
+          price,
+        }
+      })
+
+      const total = Number(items.reduce((sum, item) => sum + (item.price * item.quantity), 0).toFixed(2))
+
+      return {
+        orderId: `ORD-${String(i + 1).padStart(4, '0')}`,
+        customer: {
+          id: customerId,
+          name: faker.person.fullName(),
+          email: faker.internet.email().toLowerCase(),
+        },
+        items,
+        total,
+        status: statuses[i % statuses.length]!,
+        orderDate: faker.date.recent({ days: 90 }).toISOString().split('T')[0],
+      }
+    }),
+  },
+}
+
+/**
+ * Analytics dataset: 60 days of time-series metrics
+ *
+ * @remarks
+ * Tests TOON's handling of numeric data and date fields
+ */
+const analyticsDataset: Dataset = {
+  name: 'analytics',
+  description: 'Time-series analytics data',
+  data: {
+    metrics: Array.from({ length: 60 }, (_, i) => {
+      const date = new Date('2025-01-01')
+      date.setDate(date.getDate() + i)
+
+      // Simulate realistic web traffic with some variation
+      const baseViews = 5000
+      const weekendMultiplier = date.getDay() === 0 || date.getDay() === 6 ? 0.7 : 1.0
+      const views = Math.round(baseViews * weekendMultiplier + faker.number.int({ min: -1000, max: 3000 }))
+      const clicks = Math.round(views * faker.number.float({ min: 0.02, max: 0.08 }))
+      const conversions = Math.round(clicks * faker.number.float({ min: 0.05, max: 0.15 }))
+      const avgOrderValue = faker.number.float({ min: 49.99, max: 299.99 })
+      const revenue = Number((conversions * avgOrderValue).toFixed(2))
+
+      return {
+        date: date.toISOString().split('T')[0]!,
+        views,
+        clicks,
+        conversions,
+        revenue,
+        bounceRate: faker.number.float({ min: 0.3, max: 0.7, fractionDigits: 2 }),
+      }
+    }),
+  },
+}
+
+/**
+ * GitHub dataset: Popular repositories
+ *
+ * @remarks
+ * Tests TOON's tabular format with real-world data
+ */
+const githubDataset: Dataset = {
+  name: 'github',
+  description: 'Popular GitHub repositories',
+  data: {
+    repositories: githubRepos.slice(0, 200),
+  },
+}
+
+/**
+ * All datasets used in the benchmark
+ */
+export const datasets: Dataset[] = [
+  tabularDataset,
+  nestedDataset,
+  analyticsDataset,
+  githubDataset,
+]