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On-device chat via Apple Intelligence / Gemini Nano (BGE embeddings, SmolLM fallback).","maintainers":[{"name":"annadata","email":"annadataai.app@gmail.com"}],"readme":"# pack-it-pkc\r\n\r\n[![Actions Status](https://github.com/arusatech/pack-it-pkc/workflows/CI/badge.svg)](https://github.com/arusatech/pack-it-pkc/actions)\r\n[![License: MIT](https://img.shields.io/badge/license-MIT-blue.svg)](https://opensource.org/licenses/MIT)\r\n[![npm](https://img.shields.io/npm/v/@annadata/pack-it-pkc.svg)](https://www.npmjs.com/package/@annadata/pack-it-pkc/)\r\n[![Support: ANNADATA.AI](https://img.shields.io/badge/AI-ANNADATA.AI-orange.svg)](https://annadata.ai/)\r\n[![Principal Engineer / Architect: Mr. Yakub Mohammad](https://img.shields.io/badge/Principal%20Architect-Mr.%20Yakub%20Mohammad-blue.svg)](https://annadata.ai/)\r\n\r\nInstallable TypeScript library: convert documents to Markdown, edit PDF blocks, pack **Study PKC v3** (RAG + flash + MCQ), and run **offline KYC** verification with QR proof.\r\n\r\n## What's new in v1.3.0\r\n\r\n- **`@annadata/pack-it-pkc/inference/local-llm`** — `createHybridCapacitorProvider()` uses **Apple Intelligence** (iOS) or **Gemini Nano** (Android) for chat when available; **BGE-micro GGUF** for embeddings; **SmolLM2 GGUF** only as last-resort chat on web or unsupported devices.\r\n- **`@annadata/pack-it-pkc/kyc`** — fully client-side KYC: OCR, PAN/Aadhaar parsing, ONNX face match, background removal, confidence scoring, masked QR artifact.\r\n- Optional peer **`@capacitor/local-llm`** (CapacitorLABS experimental plugin).\r\n\r\n## On-device inference\r\n\r\n| Role | Primary | Fallback |\r\n|------|---------|----------|\r\n| **Chat** (study RAG, flashcards, math/chem assist) | Apple Intelligence / Gemini Nano via `@capacitor/local-llm` | SmolLM2-135M GGUF via `llama-cpp-pro` |\r\n| **Embeddings** (hybrid BM25 + vector retrieval) | BGE-micro GGUF via `llama-cpp-pro` | — (required for vector search) |\r\n\r\nRecommended host wiring:\r\n\r\n```typescript\r\nimport { createHybridCapacitorProvider } from \"@annadata/pack-it-pkc/inference/local-llm\";\r\n\r\nconst llm = await createHybridCapacitorProvider();\r\n// Pass to generateStudyPkc, answerStudyQuestion, MarkItDown, PdfCanvasEditor, etc.\r\n```\r\n\r\nGGUF-only hosts can keep using `CapacitorGgufProvider` from `@annadata/pack-it-pkc/inference/capacitor`.\r\n\r\n**Platform notes** (Capacitor Local LLM):\r\n\r\n- iOS text LLM requires iOS 26+ with Apple Intelligence enabled.\r\n- Android requires a Gemini Nano–capable device (e.g. Pixel 9+); call `systemAvailability()` / `download()` before first prompt.\r\n- Web/PWA: system LLM unavailable → SmolLM GGUF fallback automatically.\r\n- Android caps `maximumOutputTokens` at 256; study RAG clamps accordingly on that path.\r\n\r\n## Install\r\n\r\n```bash\r\nnpm install @annadata/pack-it-pkc\r\n\r\n# Optional peers (host app)\r\nnpm install llama-cpp-pro            # BGE embeddings + SmolLM chat fallback\r\nnpm install @capacitor/local-llm     # Apple Intelligence / Gemini Nano chat\r\nnpm install @capacitor/filesystem    # native model download (iOS/Android/desktop Capacitor)\r\n```\r\n\r\nLocal link while developing the host app:\r\n\r\n```bash\r\nnpm install ../pack-it-pkc\r\n```\r\n\r\n## Public API\r\n\r\n| Import | Use |\r\n|--------|-----|\r\n| `@annadata/pack-it-pkc` | `MarkItDown`, converters, PDF extract, `generateStudyPkc`, `packToPkc` / `packStudyPkc`, model catalog/download |\r\n| `@annadata/pack-it-pkc/inference/local-llm` | `createHybridCapacitorProvider` (recommended on Capacitor native) |\r\n| `@annadata/pack-it-pkc/inference/capacitor` | `CapacitorGgufProvider` (GGUF only) |\r\n| `@annadata/pack-it-pkc/pdf/editor` | `PdfCanvasEditor` (DOM) |\r\n| `@annadata/pack-it-pkc/pdf/editor.css` | Editor styles |\r\n| `@annadata/pack-it-pkc/kyc` | `runKycVerification`, KYC PKC pack/unpack, QR sign/generate/scan |\r\n| `@annadata/pack-it-pkc/assets/manifest` | KaTeX + language font path helpers |\r\n\r\n### Convert + pack\r\n\r\n```typescript\r\nimport { MarkItDown, packToPkc, generateStudyPkc } from \"@annadata/pack-it-pkc\";\r\nimport { createHybridCapacitorProvider } from \"@annadata/pack-it-pkc/inference/local-llm\";\r\n\r\nconst llm = await createHybridCapacitorProvider();\r\nconst md = new MarkItDown({ llmProvider: llm });\r\n\r\n// Browser / Capacitor / PWA — pass bytes (not filesystem paths)\r\nconst result = await md.convertBytes(pdfBytes, { filename: \"doc.pdf\", extension: \".pdf\" });\r\nconst pkc = packToPkc(result.markdown, { title: result.title, source: \"doc.pdf\" });\r\n```\r\n\r\n`convertLocal(\"/path\")` is **Node-only**. In browser/Capacitor use `convertBytes` / `convert(Uint8Array)`.\r\n\r\n### Study PKC v3 (RAG + flash + MCQ + binary assets)\r\n\r\n```typescript\r\nimport { generateStudyPkc, unpackStudyPkc, answerStudyQuestion } from \"@annadata/pack-it-pkc\";\r\n\r\nconst { document, pkc, warnings } = await generateStudyPkc(pdfBlocks, {\r\n  llmProvider: llm,\r\n  onProgress: console.log,\r\n});\r\n// Study v3: text chunks + binary image assets (no packed embeddings).\r\n// Host runs BGE lazily at chat time (optional durable StudyEmbeddingCache).\r\n\r\nconst loaded = unpackStudyPkc(pkc); // container PKC\\x02\r\nawait answerStudyQuestion({\r\n  doc: loaded,\r\n  query: \"…\",\r\n  provider: llm,\r\n  embeddingCache, // e.g. IndexedDB Float32 cache in the PKC app\r\n});\r\n```\r\n\r\n**Breaking vs ≤1.2.x:** Study schema is **v3**; packs use container **`PKC\\x02`** with raw assets. Legacy Study v2 packs are not readable — re-generate.\r\n\r\n### PDF canvas editor\r\n\r\n```typescript\r\nimport { PdfCanvasEditor } from \"@annadata/pack-it-pkc/pdf/editor\";\r\nimport \"@annadata/pack-it-pkc/pdf/editor.css\";\r\nimport \"@annadata/pack-it-pkc/assets/katex/katex.css\";\r\n\r\nconst editor = new PdfCanvasEditor({\r\n  container,\r\n  fileName: \"doc.pdf\",\r\n  pdfBytes,\r\n  doc: pdfBlocks,\r\n  llmProvider: llm,\r\n  onChange: (doc) => { /* persist */ },\r\n});\r\n```\r\n\r\n### Models\r\n\r\nWith `createHybridCapacitorProvider()`, chat may skip SmolLM download when the system LLM is ready (`skipChatGgufDownload`). Embeddings always use BGE:\r\n\r\n```typescript\r\nimport {\r\n  downloadModel,\r\n  ensureModelReady,\r\n  ensureEmbeddingModelReady,\r\n  DEFAULT_OFFLINE_MODEL_ID,\r\n  SMOL_CHAT_MODEL_ID,\r\n  SYSTEM_LOCAL_LLM_CHAT_ID,\r\n} from \"@annadata/pack-it-pkc\";\r\n\r\n// BGE (~17 MB) — required for hybrid vector retrieval\r\nawait ensureEmbeddingModelReady(llm, DEFAULT_OFFLINE_MODEL_ID);\r\n\r\n// Chat — skips SmolLM when Apple Intelligence / Gemini Nano is available\r\nawait ensureModelReady(llm); // may resolve to SYSTEM_LOCAL_LLM_CHAT_ID\r\n\r\n// Force GGUF chat path (web / fallback)\r\nawait downloadModel(SMOL_CHAT_MODEL_ID);\r\nawait ensureModelReady(llm, SMOL_CHAT_MODEL_ID);\r\n```\r\n\r\nStorage: PWA → OPFS; native Capacitor → `@capacitor/filesystem` Data dir; Node → `~/.cache/pack-it-pkc/models`. ONNX KYC models use the same download machinery (`runtime: \"onnx\"` in catalog).\r\n\r\n### Offline KYC verification + QR proof\r\n\r\n```typescript\r\nimport { runKycVerification, createHmacSigner, scanKycQrCode } from \"@annadata/pack-it-pkc/kyc\";\r\n\r\nconst signer = createHmacSigner(hostSuppliedKey); // host-injected — never a baked-in default\r\nconst result = await runKycVerification(\r\n  { documentBytes: idPhotoOrPdfBytes, filename: \"id.jpg\", selfieBytes },\r\n  { sign: signer, onStatus: console.log },\r\n);\r\n\r\nresult.record.confidence.status; // \"verified\" | \"needs_review\" | \"rejected\"\r\nresult.pkc; // full unmasked record (PKC\\x02 container) — local archival only\r\nresult.qrPayload; // masked fields + optional photo thumbnail\r\nresult.qrCodeImage?.dataUrl;\r\n\r\nconst scanned = await scanKycQrCode(scannedQrImageBytes, { verify: signer });\r\nscanned.status; // \"valid\" | \"tampered\" | \"unsigned\" | \"unparseable\"\r\n```\r\n\r\nSupports PAN and Aadhaar (Verhoeff checksum) with generic-ID fallback. Face match (SCRFD + MobileFaceNet-class embed) and background removal (U2Netp) are pluggable. Out of scope: liveness, live registry lookups, asymmetric signing.\r\n\r\n## Architecture\r\n\r\n```\r\nassets/         # Static KaTeX + language fonts (copied to dist/assets)\r\nsrc/\r\n  assets/       # Path helpers (manifest.ts)\r\n  detect/       # Magic-byte format detection\r\n  convert/      # MarkItDown + format converters\r\n  inference/    # Catalog, download, session, CapacitorGgufProvider, hybrid local-llm\r\n  pdf/          # Block extract + PdfCanvasEditor\r\n  pkc/          # Markdown PKC v1 + Study PKC v3 + RAG chat\r\n  kyc/          # Offline KYC + QR (separate subpath entry)\r\n  types/ utils/\r\n```\r\n\r\n## Host requirements\r\n\r\n| Dependency | Purpose |\r\n|------------|---------|\r\n| `mupdf` | PDF extraction (AGPL-3.0) |\r\n| `llama-cpp-pro` | BGE embeddings; SmolLM chat fallback |\r\n| `@capacitor/local-llm` | Apple Intelligence / Gemini Nano chat (optional; native Capacitor) |\r\n| `@capacitor/filesystem` | Native model storage (optional; PWA uses OPFS) |\r\n| `tesseract.js` / `onnxruntime-web` / `@zxing/library` | Only when importing `@annadata/pack-it-pkc/kyc` |\r\n\r\n## Scripts\r\n\r\n| Command | Description |\r\n|---------|-------------|\r\n| `npm run build` | Build `dist/` (+ copy KaTeX/assets) |\r\n| `npm test` | Vitest |\r\n| `npm run test:manual` | Local Vite harness |\r\n| `npm run prepublishOnly` | Build + test before publish |\r\n\r\n## Publish\r\n\r\n```bash\r\nnpm run build && npm test\r\nnpm publish --access public\r\n```\r\n\r\nScoped package: [`@annadata/pack-it-pkc`](https://www.npmjs.com/package/@annadata/pack-it-pkc).\r\n\r\n## License\r\n\r\nMIT — Mr. Yakub Mohammad <yakub@annadata.ai>\r\n\r\nPDF conversion uses [MuPDF.js](https://www.npmjs.com/package/mupdf) (AGPL-3.0). Distributing this library with PDF support requires complying with the AGPL.\r\n","readmeFilename":"README.md"}