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AI Alliance"},"license":"Apache-2.0","homepage":"https://github.com/The-AI-Alliance/semiont#readme","keywords":["content","storage","working-tree","checksum","pdf","semiont"],"repository":{"url":"git+https://github.com/The-AI-Alliance/semiont.git","type":"git","directory":"packages/content"},"description":"Working-tree storage for project resources and PDF text-layer extraction","maintainers":[{"name":"adamaialliance","email":"apingel@thealliance.ai"}],"readme":"# @semiont/content\n\n[![Tests](https://github.com/The-AI-Alliance/semiont/actions/workflows/package-tests.yml/badge.svg)](https://github.com/The-AI-Alliance/semiont/actions/workflows/package-tests.yml?query=branch%3Amain+is%3Asuccess+job%3A%22Test+content%22)\n[![codecov](https://codecov.io/gh/The-AI-Alliance/semiont/graph/badge.svg?flag=content)](https://codecov.io/gh/The-AI-Alliance/semiont?flag=content)\n[![npm version](https://img.shields.io/npm/v/@semiont/content.svg)](https://www.npmjs.com/package/@semiont/content)\n[![npm downloads](https://img.shields.io/npm/dm/@semiont/content.svg)](https://www.npmjs.com/package/@semiont/content)\n[![License](https://img.shields.io/npm/l/@semiont/content.svg)](https://github.com/The-AI-Alliance/semiont/blob/main/LICENSE)\n\nWorking-tree storage for project resources, with optional git staging, plus PDF text-layer extraction.\n\n## Installation\n\n```bash\nnpm install @semiont/content\n```\n\n## Architecture Context\n\n**Infrastructure Ownership**: In production applications, the working tree store is **created and managed by [@semiont/make-meaning](../make-meaning/)'s `startMakeMeaning()` function**, which serves as the single orchestration point for all infrastructure components. Gateway code accesses it as `knowledgeBase.content`.\n\nThe quick start example below shows direct instantiation for **testing, CLI tools, or content management scripts**.\n\n## Quick Start\n\n```typescript\nimport { WorkingTreeStore, deriveStorageUri } from '@semiont/content';\nimport { SemiontProject } from '@semiont/core/node';\n\nconst project = new SemiontProject('/path/to/project', {\n  anchoredTextDir: process.env.SEMIONT_ANCHORED_TEXT_DIR!,\n});\nconst store = new WorkingTreeStore(project);\n\n// Derive a stable file:// URI from a resource name\nconst uri = deriveStorageUri('My Document', 'text/markdown');\n// => \"file://my-document.md\"\n\n// Write content to the working tree (API/GUI/AI path)\nconst stored = await store.store(Buffer.from('# My Document\\n'), uri);\nconsole.log(stored.checksum);  // SHA-256 hex of the content\nconsole.log(stored.byteSize);  // 14\n\n// Register a file that is already on disk (CLI path)\nconst registered = await store.register('file://docs/overview.md');\n\n// Read content back by URI\nconst content = await store.retrieve(uri);\nconsole.log(content.toString()); // \"# My Document\\n\"\n\n// Move and remove files\nawait store.move(uri, 'file://docs/my-document.md');\nawait store.remove('file://docs/my-document.md');\n```\n\n## Working Tree Storage\n\nThe working tree (project root) is the source of truth for file content. Resources are identified by their `file://` URI, which is stable across content changes; moves are tracked by events.\n\n```\nmy-project/                  ← project root\n├── .semiont/                ← project config and event log\n└── docs/\n    └── overview.md          ← storageUri \"file://docs/overview.md\"\n```\n\nThere are two write paths:\n\n- **`store(content, storageUri)`** — write bytes to disk. Used when the file does not yet exist and the caller provides content (API/GUI/AI path).\n- **`register(storageUri, expectedChecksum?)`** — read an existing file and record its metadata (CLI path). If `expectedChecksum` is provided and does not match, throws `ChecksumMismatchError`.\n\nBoth return the same metadata:\n\n```typescript\ninterface StoredResource {\n  storageUri: string;    // file:// URI (e.g. \"file://docs/overview.md\")\n  checksum: string;      // SHA-256 hex of content\n  byteSize: number;      // Size in bytes\n  created: string;       // ISO 8601 timestamp\n}\n```\n\n### Git Integration\n\nWhen the project has `[git] sync = true` in `.semiont/config`, the store keeps the git index up to date automatically:\n\n- `store()` / `register()` run `git add`\n- `move()` runs `git mv`\n- `remove()` runs `git rm` (or `git rm --cached` with `keepFile: true`)\n\nEvery method accepts `{ noGit: true }` to skip staging for a single call. Without git sync, the store falls back to plain filesystem operations.\n\n## PDF Extraction\n\n`EXTRACTORS['pdf-text-layer']` turns a PDF into text plus the geometry that\nindexes it, routing by what the document actually holds:\n\n| Class | Document | Read by |\n|---|---|---|\n| A | native text layer | pdf.js, directly |\n| B | scanned — pixels only | OCR (Tesseract) |\n| C | hybrid — some pages scanned | both; pages still unread are reported |\n| D | tables | grid pages rewritten as markdown rows |\n| E | forms | AcroForm values folded in, anchored to their widgets |\n| F / G | encrypted, corrupt | declined by name, from the parser error |\n\n```typescript\nimport { EXTRACTORS } from '@semiont/content';\nimport { textExtractionOf, locate } from '@semiont/core';\n\nconst extracted = await EXTRACTORS[textExtractionOf('application/pdf')]!\n  .extract(pdfBytes, 'application/pdf');\n\nif (!('declined' in extracted)) {\n  extracted.text;          // reading-order text\n  extracted.items;         // positioned runs indexing it\n  extracted.method;        // 'pdf-text-layer' | 'ocr' | 'table' | 'form'\n  extracted.unreadPages;   // class C: pages no reader could recover\n}\n```\n\nA decline is named (`'no-text-layer' | 'encrypted' | 'corrupt' | 'too-large'`)\nrather than a bare null, so a caller can settle with the reason.\n`'no-text-layer'` means recognition ran and came up empty — not that it was\nnever attempted.\n\n`extractPdfTextLayer()` is the lower-level reader underneath class A, returning\n`null` for a document with no text operators anywhere.\n\nCoordinates are PDF points, origin bottom-left; the Y-flip to canvas pixels\nhappens in the browser. The vocabulary these produce — `AnchoredText`,\n`PdfTextItem` — and the `locate` / `textUnder` pair that reads it are exported\nfrom [`@semiont/core`](../core/README.md), so the browser can reason over\ngeometry without importing this package's extraction stack.\n\n## Anchored-text store\n\nOCR costs ~2.9 s per scanned page and six consumers read the same document, so\nwhat the engine produced is kept rather than re-derived:\n\n```typescript\nimport { createAnchoredTextStore } from '@semiont/content';\n\nconst store = createAnchoredTextStore(dir, logger);\nawait store.write(checksum, { text, items });\nconst map = await store.read(checksum);   // null on any miss\n```\n\nDerived values only, keyed by content checksum and stamped with the versions of\nthis package, the engine and its traineddata. A stamp mismatch, a corrupt file\nand an absent one are all the same answer: a miss. The store may make things\nfaster, never make them fail.\n\nSee **[ANCHORING.md](../../docs/system/ANCHORING.md)** for the pipeline this\nsits in.\n\n## Utilities\n\n```typescript\nimport {\n  calculateChecksum,       // SHA-256 hex of a string or Buffer\n  verifyChecksum,          // Compare content against an expected checksum\n  deriveStorageUri,        // (\"My Doc\", \"text/markdown\") → \"file://my-doc.md\"\n} from '@semiont/content';\n```\n\n`deriveStorageUri` takes a `SupportedMediaType`; the media-type registry —\nwhich types are admitted, their extensions, and their capabilities — lives in\n[@semiont/core](../core/)'s `media-types.ts`. See [docs/mime-types.md](./docs/mime-types.md).\n\n## Documentation\n\n- [API Reference](./docs/API.md) - Complete API documentation\n- [Architecture](./docs/architecture.md) - Design principles\n\n## Development\n\n```bash\n# Install dependencies\nnpm install\n\n# Build package\nnpm run build\n\n# Run tests\nnpm test\n\n# Type checking\nnpm run typecheck\n```\n\n## License\n\nApache-2.0\n","readmeFilename":"README.md"}