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CLI tool for managing a database of open-source project documentation converted to llms.txt format.","maintainers":[{"name":"harlan_zw","email":"harlan@harlanzw.com"}],"readme":"# @mdream/llms-db\n\nA CLI tool for managing a database of open-source project documentation converted to llms.txt format.\n\n## Features\n\n- **SQLite Database**: Store metadata about crawled sites with full history\n- **Automated Crawling**: Integrates with @mdream/crawl for website processing\n- **Artifact Management**: Automatically compress and store crawled files\n- **llms.txt Generation**: Generate master llms.txt files from database entries\n- **CLI Interface**: Simple command-line interface for managing entries\n\n## Installation\n\n```bash\npnpm install @mdream/llms-db\n```\n\n## Usage\n\n### Run crawler on a URL\n\n```bash\nmdream-db run https://docs.example.com\n\n# With options\nmdream-db run https://docs.example.com --name \"Example Docs\" --description \"Documentation for Example project\"\n\n# Force local mode (ignore production env vars)\nmdream-db run https://docs.example.com --local\n```\n\n### Re-crawl an existing entry\n\n```bash\nmdream-db recrawl \"Example Docs\"\n# or by ID\nmdream-db recrawl 1\n```\n\n### List all entries\n\n```bash\nmdream-db list\n```\n\n### Generate master llms.txt\n\n```bash\nmdream-db generate\n# or specify output path\nmdream-db generate ./my-llms.txt\n```\n\n### Remove an entry\n\n```bash\nmdream-db remove \"Example Docs\"\n```\n\n## CLI Options\n\n### `run` command\n\n- `--name <name>`: Custom name for the entry (defaults to domain)\n- `--description <desc>`: Description of the site\n- `--depth <number>`: Crawl depth (default: 3)\n- `--max-pages <number>`: Maximum pages to crawl\n- `--exclude <pattern>`: Exclude URL patterns (can be used multiple times)\n- `--output <dir>`: Output directory for crawled files\n- `--local`: Force local mode (ignore production environment variables)\n\n### `recrawl` command\n\n- Accepts entry name or ID\n\n## Architecture\n\nThe package uses a **repository pattern** with multiple storage backends:\n\n- **Repository Interface**: `LlmsRepository` defines the contract for database operations\n- **Drizzle Implementation**: `DrizzleLlmsRepository` provides SQLite/LibSQL implementation\n- **Storage Implementation**: `LlmsStorageRepository` provides file-based storage using unstorage\n- **Type Safety**: Full TypeScript support with schema inference\n- **Migrations**: Managed through `drizzle-kit` for schema evolution\n\n## Database Schema\n\n### Drizzle Repository (SQLite/LibSQL)\n\nThe tool creates a database with the following tables:\n\n- `llms_entries`: Main entries with metadata\n- `crawled_pages`: Individual pages crawled for each entry\n- `artifacts`: Generated files (llms.txt, archives, etc.)\n\n### Storage Repository (File-based)\n\nUses unstorage for file-based key-value storage:\n\n- `entries/`: Main entries stored as JSON files\n- `pages/`: Individual pages for each entry\n- `artifacts/`: Generated files metadata\n- `meta/`: Metadata for lookups and counters\n\n## Programmatic Usage\n\n### Using Drizzle Repository (SQLite/LibSQL)\n\n```typescript\nimport { createRepository } from '@mdream/llms-db'\n\n// Local SQLite database\nconst repository = createRepository({ dbPath: './my-database.db' })\n\n// Production LibSQL database (using environment variables)\n// Automatically initializes R2 storage if credentials are available\nconst prodRepository = createRepository({\n  production: true,\n  authToken: process.env.TURSO_AUTH_TOKEN\n})\n\n// Production LibSQL database (with explicit configuration)\nconst prodRepositoryExplicit = createRepository({\n  production: true,\n  authToken: 'your_auth_token_here'\n})\n\n// Create a new entry\nconst entry = await repository.createEntry({\n  name: 'example-docs',\n  url: 'https://docs.example.com',\n  description: 'Example documentation'\n})\n\n// Update status\nawait repository.updateEntryStatus(entry.id, 'completed')\n\n// Upload artifact to R2 (production only)\nconst archiveData = Buffer.from('archive content')\nconst r2Url = await repository.uploadArtifactToR2('my-project', 'archive.tar.gz', archiveData)\n\n// Add artifact with automatic R2 upload (production only)\nconst llmsData = Buffer.from('llms.txt content')\nawait repository.addArtifactWithR2Upload(\n  entry.id,\n  'llms.txt',\n  'llms.txt',\n  llmsData,\n  llmsData.length\n)\n\n// Generate llms.txt\nconst llmsTxt = await repository.generateLlmsTxt()\nconsole.log(llmsTxt)\n\nrepository.close()\n```\n\n### Using Storage Repository (File-based)\n\n```typescript\nimport { createStorageRepository } from '@mdream/llms-db'\n\nconst repository = createStorageRepository({\n  dbPath: './my-storage'\n})\n\n// Same API as drizzle repository\nconst entry = await repository.createEntry({\n  name: 'example-docs',\n  url: 'https://docs.example.com',\n  description: 'Example documentation'\n})\n\nrepository.close()\n```\n\n## Storage\n\n### Local Development\n- **Database**: `.mdream/llms.db` (SQLite)\n- **File Storage**: `.mdream/llms-storage/` (unstorage)\n- **Crawled files**: `.mdream/crawls/<entry-name>/`\n- **Archives**: `.mdream/archives/<entry-name>.tar.gz`\n\n### Production\n- **Database**: LibSQL (Turso) at `libsql://mdream-production-harlan-zw.aws-ap-northeast-1.turso.io`\n- **Authentication**: Requires `TURSO_AUTH_TOKEN` environment variable\n- **Artifact Storage**: Cloudflare R2 (automatic upload in production mode)\n- **R2 Integration**: Archives and llms.txt files are automatically uploaded to R2\n\n## Environment Variables\n\n### Database Configuration\n- `NODE_ENV=production`: Automatically use production LibSQL database\n- `TURSO_DATABASE_URL`: LibSQL database URL (e.g., `libsql://your-database.turso.io`)\n- `TURSO_AUTH_TOKEN`: Required for production database access\n\n### R2 Storage Configuration (Production)\n- `R2_ACCESS_KEY_ID`: Your R2 access key ID\n- `R2_SECRET_ACCESS_KEY`: Your R2 secret access key\n- `R2_ACCOUNT_ID`: Your Cloudflare account ID\n- `R2_BUCKET_NAME`: Your R2 bucket name\n- `R2_ENDPOINT`: Your R2 endpoint URL\n- `R2_PUBLIC_URL`: Your R2 public URL\n\n### Setup\n\n1. Copy the example environment file:\n   ```bash\n   cp .env.example .env\n   ```\n\n2. Edit `.env` and add your configuration:\n   ```bash\n   # Database Configuration\n   TURSO_DATABASE_URL=libsql://your-database.turso.io\n   TURSO_AUTH_TOKEN=your_actual_token_here\n\n   # R2 Storage Configuration (Production)\n   R2_ACCESS_KEY_ID=your_access_key_id\n   R2_SECRET_ACCESS_KEY=your_secret_access_key\n   R2_ACCOUNT_ID=your_account_id\n   R2_BUCKET_NAME=your_bucket_name\n   R2_ENDPOINT=https://your-account-id.r2.cloudflarestorage.com\n   R2_PUBLIC_URL=https://your-public-url.r2.dev\n   ```\n\n3. Run commands with native Node.js dotenv support:\n   ```bash\n   # Database operations\n   node --env-file=.env ./dist/cli.mjs\n\n   # Drizzle commands\n   pnpm db:generate  # Uses --env-file automatically\n   pnpm db:migrate   # Uses --env-file automatically\n   pnpm db:studio    # Uses --env-file automatically\n   ```\n\n### Native dotenv Support\n\nThis package uses Node.js native dotenv support (available since Node.js 20.6.0) via the `--env-file` flag instead of the `dotenv` package. This provides better performance and reduces dependencies.\n\n## R2 Storage Integration\n\nThe package includes built-in support for Cloudflare R2 object storage for artifact management:\n\n### Automatic R2 Integration (Production)\n\nWhen running in production mode (`NODE_ENV=production` or `production: true`), the drizzle repository automatically:\n\n1. **Initializes R2 Client**: If R2 environment variables are configured, an R2 client is automatically created\n2. **Uploads Artifacts**: When using `addArtifactWithR2Upload()`, artifacts are automatically uploaded to R2\n3. **Stores Public URLs**: The database stores the public R2 URL instead of local file paths\n4. **Fallback Behavior**: If R2 is not configured, it falls back to local storage without errors\n\n```typescript\n// Production repository automatically uses R2 if configured\nconst repository = createRepository({ production: true })\n\n// This will upload to R2 in production, local storage in development\nconst archiveData = Buffer.from('archive content')\nawait repository.addArtifactWithR2Upload(\n  entryId,\n  'archive',\n  'project.tar.gz',\n  archiveData,\n  archiveData.length\n)\n```\n\n### Manual R2 Setup\n\n```typescript\nimport { createR2Client } from '@mdream/llms-db'\n\nconst r2Client = createR2Client({\n  accessKeyId: process.env.R2_ACCESS_KEY_ID,\n  secretAccessKey: process.env.R2_SECRET_ACCESS_KEY,\n  accountId: process.env.R2_ACCOUNT_ID,\n  bucketName: process.env.R2_BUCKET_NAME,\n  endpoint: process.env.R2_ENDPOINT,\n  publicUrl: process.env.R2_PUBLIC_URL,\n})\n\n// Upload an artifact\nconst publicUrl = await r2Client.uploadArtifact('my-project', 'docs.tar.gz', archiveBuffer)\n\n// Download an artifact\nconst data = await r2Client.downloadArtifact('my-project', 'docs.tar.gz')\n\n// Get public URL\nconst url = r2Client.getPublicUrl('my-project', 'docs.tar.gz')\n```\n\n### Environment Variables\n\nAdd these to your `.env` file:\n\n```bash\n# Cloudflare R2 Configuration\nR2_ACCESS_KEY_ID=your_access_key_id\nR2_SECRET_ACCESS_KEY=your_secret_access_key\nR2_ACCOUNT_ID=your_account_id\nR2_BUCKET_NAME=your_bucket_name\nR2_ENDPOINT=https://your-account-id.r2.cloudflarestorage.com\nR2_PUBLIC_URL=https://your-public-url.r2.dev\n```\n","readmeFilename":"README.md"}