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Enables natural language to SQL conversion, PostgreSQL integration, and BYOK AI chat proxy.\n\n## Two Deployment Options\n\n### Option 1: Full Server (PostgreSQL + AI)\n\nUse this when you have a PostgreSQL database. The unified handler provides:\n- Auto-discovery of tables from your database\n- Schema introspection \n- SQL query execution with safety validation\n- AI chat proxy\n\n### Option 2: Client-Side Queries + AI Proxy Only\n\nUse this when your data is already in the browser (e.g., DuckDB WASM, static data). You only need a server endpoint for AI chat to keep API keys secure.\n\n---\n\n## Option 1: Full Server Setup\n\n### Requirements\n\n- PostgreSQL database\n- AI API key (OpenAI, Anthropic, or OpenRouter)\n- Node.js 18+\n\n### 1. Install\n\n```bash\npnpm add @smallwebco/tinypivot-server pg\n```\n\n### 2. Set Environment Variables\n\n```bash\n# .env\nDATABASE_URL=postgresql://user:password@localhost:5432/mydb\nAI_API_KEY=sk-... # Your API key\n\n# Optional: Override the default model\nAI_MODEL=claude-sonnet-4-20250514\n```\n\nThe AI provider is **auto-detected** from your API key format:\n- `sk-ant-...` → Anthropic (defaults to `claude-3-haiku-20240307`)\n- `sk-or-...` → OpenRouter (defaults to `anthropic/claude-3-haiku`)\n- `sk-...` → OpenAI (defaults to `gpt-4o-mini`)\n\nDefault models are cheap/fast. Override with `AI_MODEL` for better quality.\n\n### 3. Create API Endpoint\n\n**Next.js App Router**\n\n```typescript\n// app/api/tinypivot/route.ts\nimport { createTinyPivotHandler } from '@smallwebco/tinypivot-server'\n\nexport const POST = createTinyPivotHandler()\n```\n\n**Next.js Pages Router**\n\n```typescript\n// pages/api/tinypivot.ts\nimport type { NextApiRequest, NextApiResponse } from 'next'\nimport { createTinyPivotHandler } from '@smallwebco/tinypivot-server'\n\nconst handler = createTinyPivotHandler()\n\nexport default async function (req: NextApiRequest, res: NextApiResponse) {\n const response = await handler(\n new Request('http://localhost', {\n method: 'POST',\n body: JSON.stringify(req.body),\n headers: { 'Content-Type': 'application/json' },\n })\n )\n const data = await response.json()\n res.status(response.status).json(data)\n}\n```\n\n**Express**\n\n```typescript\nimport express from 'express'\nimport { createTinyPivotHandler } from '@smallwebco/tinypivot-server'\n\nconst app = express()\napp.use(express.json())\n\nconst handler = createTinyPivotHandler()\n\napp.post('/api/tinypivot', async (req, res) => {\n const response = await handler(\n new Request('http://localhost', {\n method: 'POST',\n body: JSON.stringify(req.body),\n headers: { 'Content-Type': 'application/json' },\n })\n )\n const data = await response.json()\n res.status(response.status).json(data)\n})\n```\n\n### 4. Use in Frontend\n\n**Vue 3**\n\n```vue\n\n\n\n```\n\n**React**\n\n```tsx\nimport { DataGrid } from '@smallwebco/tinypivot-react'\nimport '@smallwebco/tinypivot-react/style.css'\n\nfunction App() {\n return (\n \n )\n}\n```\n\n---\n\n## Option 2: Client-Side Queries + AI Proxy\n\nUse this when you're executing queries in the browser (e.g., DuckDB WASM) and only need the server for AI chat.\n\n### 1. Create AI-Only Endpoint\n\n```typescript\n// api/ai-proxy.ts (Vercel) or your framework equivalent\nexport default async function handler(req, res) {\n const apiKey = process.env.AI_API_KEY\n if (!apiKey) {\n return res.status(500).json({ error: 'AI_API_KEY not configured' })\n }\n\n const { messages } = req.body\n\n // Auto-detect provider from key format\n const isAnthropic = apiKey.startsWith('sk-ant-')\n const isOpenRouter = apiKey.startsWith('sk-or-')\n\n // Call the appropriate API...\n // (See full implementation in the TinyPivot demo)\n\n return res.json({ content: aiResponse })\n}\n```\n\n### 2. Configure Frontend with queryExecutor\n\n**Vue 3**\n\n```vue\n\n\n\n```\n\n**React**\n\n```tsx\nimport { DataGrid } from '@smallwebco/tinypivot-react'\nimport '@smallwebco/tinypivot-react/style.css'\n\nfunction App() {\n const executeQuery = async (sql: string, table: string) => {\n const result = await duckdb.query(sql)\n return { data: result.toArray(), rowCount: result.numRows }\n }\n\n const aiConfig = {\n endpoint: '/api/ai-proxy',\n queryExecutor: executeQuery,\n dataSources: [\n { id: 'sales', table: 'sales', name: 'Sales Data', description: 'Sales transactions' }\n ],\n dataSourceLoader: async (id) => {\n const data = await loadDataset(id)\n return { data, schema: inferSchema(data) }\n }\n }\n\n return \n}\n```\n\n---\n\n## Configuration Options\n\n### Handler Options (Full Server)\n\n```typescript\ncreateTinyPivotHandler({\n // PostgreSQL connection (default: process.env.DATABASE_URL)\n connectionString: 'postgresql://...',\n \n // AI API key (default: process.env.AI_API_KEY)\n apiKey: 'sk-...',\n \n // Table filtering\n tables: {\n include: ['sales', 'customers'], // Only these tables\n exclude: [/^_/, 'migrations'], // Exclude patterns\n schemas: ['public'], // PostgreSQL schemas\n descriptions: { // Context for AI\n sales: 'Sales transactions with revenue data',\n }\n },\n \n // Query limits (optional)\n maxRows: 10000,\n timeout: 30000,\n \n // AI settings\n model: 'claude-sonnet-4-20250514', // Override default model\n maxTokens: 2048,\n \n // Error handling\n onError: (error) => console.error(error),\n})\n```\n\n### AI Analyst Config (Frontend)\n\n```typescript\ninterface AIAnalystConfig {\n // Required: API endpoint\n endpoint: string\n \n // For client-side queries (Option 2)\n queryExecutor?: (sql: string, table: string) => Promise\n dataSources?: AIDataSource[]\n dataSourceLoader?: (id: string) => Promise<{ data: any[], schema?: Schema }>\n \n // Optional\n enabled?: boolean\n persistToLocalStorage?: boolean\n sessionId?: string\n maxRows?: number\n aiModelName?: string // Display name in UI\n}\n```\n\n---\n\n## API Contract\n\nThe endpoint accepts POST requests with an `action` field:\n\n### `list-tables`\n```typescript\n// Request\n{ action: 'list-tables' }\n\n// Response\n{ tables: [{ name: 'sales', description: '...' }] }\n```\n\n### `get-schema`\n```typescript\n// Request\n{ action: 'get-schema', tables: ['sales'] }\n\n// Response\n{ schemas: [{ table: 'sales', columns: [...] }] }\n```\n\n### `query`\n```typescript\n// Request\n{ action: 'query', sql: 'SELECT ...', table: 'sales' }\n\n// Response\n{ success: true, data: [...], rowCount: 100, truncated: false }\n```\n\n### `chat`\n```typescript\n// Request\n{ action: 'chat', messages: [{ role: 'user', content: '...' }] }\n\n// Response\n{ content: 'AI response with SQL...' }\n```\n\n---\n\n## Security\n\nBuilt-in protections:\n\n1. **SQL Validation**: Only SELECT queries allowed\n2. **Table Whitelisting**: Only configured tables are queryable\n3. **LIMIT Enforcement**: Auto-added if missing\n4. **Error Sanitization**: Connection strings stripped from errors\n\n---\n\n## Troubleshooting\n\n| Error | Solution |\n|-------|----------|\n| \"PostgreSQL driver not installed\" | `pnpm add pg` |\n| \"Database connection not configured\" | Set `DATABASE_URL` |\n| \"AI API key not configured\" | Set `AI_API_KEY` |\n| \"Table X is not allowed\" | Add to `tables.include` or remove from `tables.exclude` |\n\n## License\n\nMIT\n","readmeFilename":"README.md"}