Local-first, privacy-first, offline-first AI for the browser.
Run ML models entirely in your browser. No servers. No API keys. Your data never leaves your device.
- Docs website: https://localmode.dev
- UI Components: https://localmode.ai
- Blocks & Apps: https://localmode.ai/blocks
LocalMode is a monorepo of packages for building AI-powered applications that run 100% in the browser. Everything from embeddings and vector search to LLM chat, vision, audio, agents, and structured output works offline after the initial model download.
15 packages. 36 demo blocks. Zero cloud dependencies.
- Privacy -- Your data never leaves your device. No telemetry, no tracking, no network requests from core.
- Offline -- Works without internet after model download. Automatic fallbacks for every capability.
- Fast -- No network latency. WebGPU acceleration where available. Instant inference.
- Free -- No API costs, no rate limits, unlimited usage.
- Universal -- Works in Chrome, Edge, Firefox, and Safari. Adapts to device capabilities.
- Interoperable -- Vercel AI SDK patterns. LangChain.js adapters. Import from Pinecone/ChromaDB.
| Package | Version | Description |
|---|---|---|
@localmode/core |
 |
Zero-dependency core -- VectorDB (HNSW, typed metadata, WebGPU search, SQ8/PQ quantization), pipelines, inference queue, model cache, agent framework (ReAct + tools with opt-in human-in-the-loop tool approval + memory), evaluation SDK, vector import/export, multimodal content, knowledge base engine (createKnowledgeBaseEngine + frozen KnowledgeBaseEngine contract), all interfaces |
@localmode/react |
 |
64 React hooks, 10 pipeline step factories, batch/list processing, and browser helpers -- incl. useEncryptedVault passphrase-locked encrypted storage, useAgent tool-approval surface (pendingApproval/approve/deny), useRerank document reranking, useModelLoad unified model-download lifecycle, useChat usage tracking + regenerate() reply variants, useProviderFallback per-capability Chrome AI ⇄ Transformers.js resolution, usePhotoLibrary shared CLIP photo library, and useKnowledgeBase knowledge-base session orchestration |
@localmode/ai-sdk |
 |
Vercel AI SDK provider for local models |
@localmode/transformers |
 |
HuggingFace Transformers.js provider -- 26 model factories covering embeddings, classification, vision, audio, OCR, multimodal (CLIP), and LLM inference via ONNX (Qwen3.5 vision support) |
@localmode/webllm |
 |
WebLLM provider for LLM inference via WebGPU -- 32 curated models including DeepSeek-R1, Qwen3, Llama 3.2, Phi 3.5 Vision |
@localmode/wllama |
 |
GGUF model provider via llama.cpp WASM -- 30 curated models (text, vision, embeddings, reranking), true streaming, structured output (JSON mode), reasoning mode, WebGPU acceleration, tool calling, grammar sampling (GBNF), LoRA adapters, model management, GGUF model discovery (searchGGUFModels/listGGUFFiles), 160K+ HuggingFace models, universal browser support |
@localmode/litert |
 |
Google LiteRT-LM provider (.litertlm models, WebGPU + CPU WASM fallback). Text-only, early preview. Catalog ships Gemma 4 E2B/E4B and Qwen3 0.6B, all verified end-to-end. Gated Gemma 3n / Gemma 3 1B loadable via custom URL. |
@localmode/mediapipe |
 |
Google MediaPipe Tasks provider -- real-time hand/pose/face landmark tracking, gesture recognition, image & audio classification, language detection. WASM + WebGL, all browsers. |
@localmode/chrome-ai |
 |
Chrome Built-in AI provider -- your app ships no model files; Chrome supplies Gemini Nano. Automatic fallback |
@localmode/langchain |
 |
LangChain.js adapters -- drop-in local embeddings, chat, vector store, and reranker for existing LangChain apps, plus createLangChainKnowledgeBaseEngine (the KnowledgeBaseEngine contract over LangChain adapters) |
@localmode/devtools |
 |
In-app AI observability -- 9 React hooks via the @localmode/devtools/react subpath for model cache, VectorDB stats, and inference queue data (the bundled DevTools widget UI was removed in v3.0.0 in favor of the hooks + the ui/devtools registry family and ui/blocks/devtools-drawer at localmode.ai) |
@localmode/pdfjs |
 |
PDF text extraction with PDF.js |
@localmode/dexie |
 |
Dexie.js storage adapter with schema versioning and transactions |
@localmode/idb |
 |
Minimal IndexedDB storage adapter using the idb library |
@localmode/localforage |
 |
Cross-browser storage adapter with automatic fallback |
LocalMode UI is a shadcn-style registry of copy-owned AI UI components: 107 primitives across 10 families, plus 37 blocks that wire them to real on-device models. Like shadcn/ui, you install with the shadcn CLI and own the copied code, styled with shadcn/ui CSS variables so it inherits your theme. See the docs, installation guide, and apps/ui/README.md.
The primitives are presentational and install with zero @localmode/* packages, so they work with any React AI app — the LocalMode hooks (on-device), the Vercel AI SDK, or your own data. Local-first by design, cloud-compatible by contract.
# components.json → { "registries": { "@localmode": "https://localmode.ai/r/{name}.json" } }
npx shadcn@latest add @localmode/ui/conversation/message # a single component
npx shadcn@latest add @localmode/ui/conversation # a whole family
npx shadcn@latest add @localmode/ui/all # the whole catalog| Family | Count | What it covers |
|---|---|---|
| Conversation | 24 | Chat shell, prompt input, reasoning, sources, tools, agent timelines, branches, citations |
| Local-First | 25 | Model download/selection, Hub search, capability gates, storage quota, cache status, VectorDB observability |
| Results & Insights | 12 | Confidence badges, scored result bars, similarity meters, evaluation dashboards, entity displays |
| Input Controls | 11 | Char-limit rings, fill-mask inputs, mode pickers, parameter sliders, slash-command palettes |
| Audio | 10 | Voice buttons/orbs, waveform bars, TTS voice pickers, streaming-speech panels, transcript viewers |
| Media & Vision | 7 | Image dropzones, bounding-box overlays, before/after viewers, webcam canvas, result galleries |
| Data & Documents | 5 | File dropzones, indexed-document cards, format badges, category facets, chunk visualizers |
| Security & Privacy | 5 | Password-strength bar, differential-privacy controls, passphrase gate, vault item card, lock badge |
| Artifacts & Canvas | 4 | Docked canvas, sortable data tables, charts, code diffs — output rendered beside the chat |
| DevTools | 4 | Inference-queue monitor, event-log viewer, pipeline-run inspector, model-cache table |
Blocks are complete experiences composed from the primitives — the wiring layer, and the only items that depend on @localmode/*. Each runs real models on-device and gates its download behind an explicit in-block action. Try them in the /blocks gallery, then install with npx shadcn@latest add @localmode/ui/blocks/<category>/<block>.
| Category | Blocks |
|---|---|
| chat | The flagship — streaming chat across 76 models and 4 providers, with vision, reasoning, agent mode, semantic caching, and custom GGUF URLs |
| knowledge | semantic-search · document-qa · rag-chat · vector-data-manager — ingest text/PDF/OCR, rerank, ground answers with citations, import/export vectors |
| audio | voice-notes · live-transcription · meeting-assistant · voice-explorer · audiobook-reader · audio-classifier |
| vision | object-detector · live-tracker — DETR and BlazeFace detection, plus real-time hand / pose / face-mesh / gesture tracking |
| text | language-detector — 110-language detection and text-embedder similarity |
| device | device-report · model-advisor · gguf-explorer — capability report, ranked recommendations, and a 160K-model GGUF browser (zero download) |
| agents | research-agent · data-extractor — a ReAct loop with human-in-the-loop tool approval, and schema-validated extraction rendered as artifacts |
| writing-tools | write · translate · summarize · complete — the Chrome Built-in AI ⇄ Transformers.js provider-fallback reference |
| text-insights | sentiment-analyzer · text-classifier · model-evaluator · threshold-calibrator |
| photo | smart-gallery · image-search · duplicate-finder · photo-categorizer — one CLIP model for both embeddings and zero-shot categorization |
| image-studio | background-remover · image-enhancer · image-captioner |
| privacy | pii-redactor · encrypted-vault — on-device NER redaction with a differential-privacy demo, and a passphrase-locked AES-GCM vault |
The 37th item, ui/blocks/devtools-drawer, is layout chrome rather than a gallery page: a six-tab observability drawer over @localmode/devtools, off by default and loaded only on first open. The 34 demo-app URLs from the previous localmode.ai site permanently redirect to the block that absorbed each one.
pnpm install @localmode/core @localmode/transformersimport { createVectorDB, embed, embedMany, chunk } from '@localmode/core';
import { transformers } from '@localmode/transformers';
// Create embedding model
const model = transformers.embedding('Xenova/bge-small-en-v1.5');
// Create vector database with typed metadata
const db = await createVectorDB<{ text: string }>({
name: 'docs',
dimensions: 384,
});
// Chunk and embed documents
const chunks = chunk(documentText, { size: 512, overlap: 50 });
const { embeddings } = await embedMany({
model,
values: chunks.map((c) => c.text),
});
// Store vectors
await db.addMany(
chunks.map((c, i) => ({
id: `chunk-${i}`,
vector: embeddings[i],
metadata: { text: c.text },
}))
);
// Search
const { embedding: query } = await embed({ model, value: 'What is AI?' });
const results = await db.search(query, { k: 5 });Four providers implement the same LanguageModel interface -- choose based on your needs:
# WebGPU (fastest, 32 curated models)
pnpm install @localmode/core @localmode/webllm
# WASM (universal browser support, 160K+ GGUF models)
pnpm install @localmode/core @localmode/wllama
# ONNX (Transformers.js v4, same package as embeddings/vision/audio)
pnpm install @localmode/core @localmode/transformers
# Google LiteRT-LM (.litertlm models, WebGPU — Gemma 4 E2B/E4B, Qwen3 0.6B)
pnpm install @localmode/core @localmode/litertimport { streamText } from '@localmode/core';
import { webllm } from '@localmode/webllm';
import { wllama } from '@localmode/wllama';
import { transformers } from '@localmode/transformers';
import { litert } from '@localmode/litert';
// Pick any provider -- all implement the same LanguageModel interface
const model = webllm.languageModel('Llama-3.2-1B-Instruct-q4f16_1-MLC'); // WebGPU
// const model = wllama.languageModel('Llama-3.2-1B-Instruct-Q4_K_M'); // WASM (GGUF)
// const model = transformers.languageModel('onnx-community/Qwen3-0.6B-ONNX'); // ONNX
// const model = litert.languageModel('gemma-4-E2B'); // LiteRT (WebGPU)
const result = await streamText({
model,
prompt: 'Explain quantum computing simply',
maxTokens: 500,
});
for await (const chunk of result.stream) {
process.stdout.write(chunk.text);
}import { generateObject, jsonSchema } from '@localmode/core';
import { webllm } from '@localmode/webllm';
import { z } from 'zod';
const { object } = await generateObject({
model: webllm.languageModel('Qwen3-1.7B-q4f16_1-MLC'),
schema: jsonSchema(
z.object({
name: z.string(),
age: z.number(),
interests: z.array(z.string()),
})
),
prompt: 'Generate a profile for a software engineer named Alex',
});import { createAgent, defineTool, jsonSchema } from '@localmode/core';
import { webllm } from '@localmode/webllm';
import { z } from 'zod';
// defineTool() infers the parameter/result types so `execute`'s args are typed
const searchTool = defineTool({
name: 'search',
description: 'Search the knowledge base',
parameters: jsonSchema(z.object({ query: z.string() })),
execute: async ({ query }) => searchDB(query),
});
const agent = createAgent({
model: webllm.languageModel('Qwen3-1.7B-q4f16_1-MLC'),
tools: [searchTool],
maxSteps: 5,
});
const result = await agent.run({ prompt: 'Find documents about machine learning' });import { useChat, useEmbed, useClassify } from '@localmode/react';
import { transformers } from '@localmode/transformers';
import { webllm } from '@localmode/webllm';
function ChatApp() {
const { messages, send, isStreaming } = useChat({
model: webllm.languageModel('Qwen3-1.7B-q4f16_1-MLC'),
});
return <ChatUI messages={messages} onSend={send} loading={isStreaming} />;
}import { detectHands } from '@localmode/core';
import { mediapipe } from '@localmode/mediapipe';
// Single-frame: 21-point hand landmarks
const { hands } = await detectHands({
model: mediapipe.handLandmarker(),
image: imageBlob,
});
// Real-time: 30-60fps tracking from a webcam video element
const tracker = mediapipe.createHandTracker({
video: videoElement,
onResults: (hands) => drawLandmarks(hands),
});
await tracker.start();| Feature | Functions | Description |
|---|---|---|
| Embeddings | embed(), embedMany(), streamEmbedMany() |
Text embeddings with streaming and batching |
| Multimodal Embeddings | embedImage(), embedManyImages(), streamEmbedManyImages() |
CLIP-based text-image cross-modal search |
| Streaming LLM | streamText(), generateText() |
Streaming and complete text generation |
| Structured Output | generateObject(), streamObject() |
Typed JSON generation with Zod schema validation |
| Classification | classify(), classifyZeroShot(), classifyMany() |
Sentiment, intent, topic classification |
| NER | extractEntities() |
Named entity recognition |
| Reranking | rerank() |
Document reranking for improved RAG |
| Translation | translate() |
Multi-language translation (20+ languages) |
| Summarization | summarize() |
Text summarization |
| Question Answering | answerQuestion() |
Extractive QA with confidence scores |
| Fill-Mask | fillMask() |
Masked token prediction (BERT-style) |
| OCR | extractText() |
Optical character recognition |
| Document QA | askDocument(), askTable() |
Visual document and table understanding |
| Audio | transcribe(), synthesizeSpeech(), streamSynthesizeSpeech(), playStreamedSpeech(), classifyAudio() |
Speech-to-text, TTS (Kokoro -- 29 English voices, phonemizer-backed), streaming TTS with real-time playback, audio classification |
| Live Transcription | createLiveTranscriber(), createTurnTaker() |
Real-time microphone transcription with VAD (Silero) and turn-based conversation |
| Vision | classifyImage(), captionImage(), detectObjects(), segmentImage(), imageToImage(), estimateDepth() |
Image processing and analysis |
| Landmarks & Gestures | detectHands(), detectPose(), detectFace(), detectFaceLandmarks(), recognizeGesture() |
Hand/pose/face landmark tracking and gesture recognition (MediaPipe) |
| Language Detection | detectLanguage() |
Identify the language of text (110 languages) |
| Feature | Functions | Description |
|---|---|---|
| Vector Database | createVectorDB() |
HNSW index, IndexedDB persistence, cross-tab sync, typed metadata |
| Semantic Search | semanticSearch(), streamSemanticSearch() |
Query-time embed + search in one call |
| Vector Quantization | createVectorDB({ quantization }) |
SQ8 (4x) and Product Quantization (8-32x compression) |
| Storage Compression | createVectorDB({ compression }) |
SQ8 vector compression for 4x IndexedDB disk reduction |
| WebGPU Vector Search | createGPUDistanceComputer() |
WGSL compute shaders for batch distance computation |
| Hybrid Search | createHybridSearch(), reciprocalRankFusion() |
BM25 keyword + vector semantic search fusion |
| Feature | Functions | Description |
|---|---|---|
| Chunking | chunk(), semanticChunk(), codeChunk(), markdownChunk() |
Recursive, semantic, code-aware, and markdown chunking |
| Ingestion | ingest(), createIngestPipeline() |
End-to-end document ingestion with progress tracking |
| Pipelines | createPipeline() |
Composable multi-step workflows with 10 built-in step types |
| Inference Queue | createInferenceQueue() |
Priority-based task scheduling with concurrency control |
| Semantic Cache | createSemanticCache() |
Cache LLM responses using embedding similarity |
| Import/Export | importFrom(), exportToCSV(), exportToJSONL() |
Migrate vectors from Pinecone, ChromaDB, CSV, JSONL |
| Feature | Functions | Description |
|---|---|---|
| Agent Framework | createAgent(), runAgent() |
ReAct loop with tool registry and VectorDB-backed memory |
| Evaluation SDK | evaluateModel(), accuracy(), bleuScore(), ndcg() |
Classification, generation, and retrieval metrics with confusion matrix |
| Threshold Calibration | calibrateThreshold(), getDefaultThreshold() |
Empirical similarity thresholds from corpus data |
| Model Registry | recommendModels(), registerModel() |
Curated model catalog with device-aware recommendations |
| Adaptive Batching | computeOptimalBatchSize() |
Device-aware batch sizing for optimal throughput |
| Feature | Functions | Description |
|---|---|---|
| Encryption | encrypt(), decrypt(), deriveKey() |
Web Crypto API encryption, PBKDF2 key derivation |
| PII Redaction | redactPII(), piiRedactionMiddleware() |
Named entity based PII detection and redaction |
| Differential Privacy | dpEmbeddingMiddleware(), createPrivacyBudget() |
DP noise injection for embeddings and classification |
| Drift Detection | checkModelCompatibility(), reindexCollection() |
Detect model changes, auto-reindex collections |
| Audit Log | createAuditLog() |
Hash-chained, signed, append-only tamper-evident audit log (IndexedDB-backed) |
| Feature | Functions | Description |
|---|---|---|
| Model Cache | createModelLoader() |
Chunked downloads, LRU eviction, cross-tab coordination, offline resume |
| Storage | IndexedDBStorage, MemoryStorage |
Built-in persistent and in-memory storage |
| Middleware | wrapEmbeddingModel(), wrapLanguageModel(), wrapVectorDB() |
Caching, logging, retry, validation, encryption, DP |
| Capabilities | isWebGPUSupported(), detectCapabilities() |
Browser feature detection with automatic fallbacks |
| Cross-Tab Sync | createBroadcaster(), createLockManager() |
BroadcastChannel sync with Web Locks coordination |
| Network Status | getNetworkStatus(), waitForOnline() |
Offline-first with network awareness |
See LocalMode running real models entirely in your browser at the /blocks gallery (localmode.ai/blocks). The gallery ships 36 route-served blocks across 12 categories — full experiences assembled from the registry primitives (chat plus the knowledge, vision, audio, text, device, writing-tools, agents, text-insights, photo, image-studio, and privacy category pages) plus the global-observability devtools-drawer chrome — each installable with npx shadcn@latest add @localmode/ui/blocks/<name>.
Full block descriptions, what each one covers, and install commands are in the @localmode/ui UI-registry section above (the authoritative block catalog).
Legacy
localmode.ai/<slug>URLs permanently redirect to the corresponding block.
┌──────────────────────────────────────────────────────────────────────────┐
│ Your Application │
├──────────────────────────────────────────────────────────────────────────┤
│ @localmode/react (64 React hooks) │
├────────────────────────┬────────────────────────┬────────────────────────┤
│ @localmode/langchain │ @localmode/ai-sdk │ @localmode/devtools │
├────────────────────────┴────────────────────────┴────────────────────────┤
│ @localmode/core │
│ │
│ VectorDB (HNSW + WebGPU) Embeddings + Multimodal │
│ Agents & Pipelines Evaluation + Metrics │
│ Generation + Structured Output Security (DP, PII, Crypto) │
│ Middleware System Import / Export │
├──────────────────────────────────────────────────────────────────────────┤
│ Provider Packages │
│ │
│ @localmode/transformers HuggingFace Transformers.js, │
│ 26 model factories (ONNX) │
│ @localmode/webllm WebGPU LLM inference, 32 models │
│ @localmode/wllama GGUF via llama.cpp WASM, 30 curated │
│ + 160K+, streaming, JSON mode, rerank │
│ @localmode/litert Google LiteRT-LM, .litertlm models │
│ @localmode/mediapipe Google MediaPipe — landmarks, gestures │
│ @localmode/chrome-ai Gemini Nano, browser-supplied │
├──────────────────────────────────────────────────────────────────────────┤
│ Browser APIs │
│ │
│ WebGPU / WASM · IndexedDB · Web Workers · Web Crypto │
└──────────────────────────────────────────────────────────────────────────┘
- Zero-Dependency Core --
@localmode/corehas no external dependencies - Provider Pattern -- ML frameworks are separate packages implementing core interfaces
- Function-First API -- Top-level async functions, not class methods
- Options Object Pattern -- Single options object for all functions
- Structured Results -- All functions return
{ result, usage, response } - AbortSignal Everywhere -- Every async operation supports cancellation
- Middleware Composability -- Wrap embedding models, language models, and VectorDBs
| WebLLM | Wllama | Transformers.js | LiteRT | |
|---|---|---|---|---|
| Runtime | WebGPU | WASM (llama.cpp) + optional WebGPU | ONNX Runtime | LiteRT-LM (Google) |
| Models | 32 curated (MLC) | 30 curated + 160K+ GGUF from HuggingFace | 16 ONNX (TJS v4) | 3 verified (.litertlm) |
| Speed | Fastest (GPU) | Good (CPU), faster with WebGPU | Good (CPU/GPU) | Fast (WebGPU/CPU) |
| Embeddings | -- | 3 GGUF embedding models | Yes (many models) | -- |
| Reranking | -- | 2 reranker models | Yes (cross-encoder) | -- |
| Structured Output | Yes | Yes (JSON mode / grammar) | -- | -- |
| Reasoning | -- | Yes (thinking mode) | -- | -- |
| Vision | Phi 3.5 Vision | Holo2 4B/8B, Gemma 4 E2B/E4B | Qwen3.5, Gemma 4 | -- |
| Tool Calling | Yes | Yes (via providerOptions) | -- | -- |
| Browser Support | Chrome/Edge 113+ | All modern browsers | All modern browsers | Chrome/Edge 113+ |
| Best For | Maximum performance | Universal compatibility, model variety, reranking | Multi-task (embeddings + LLM in one package) | Google on-device models |
| Browser | WebGPU | WASM | IndexedDB | Workers | Chrome AI |
|---|---|---|---|---|---|
| Chrome 80+ | 113+ | Yes | Yes | Yes | Yes |
| Edge 80+ | 113+ | Yes | Yes | Yes | Yes |
| Firefox 75+ | 141+ | Yes | Yes | Yes | No |
| Safari 14+ | 26+ | Yes | Yes | Partial | No |
- Chrome AI: Gemini Nano supplied by the browser -- your app ships no model files (fallback to Transformers.js)
- WebGPU: 3-5x faster inference (fallback to WASM)
- IndexedDB: Persistent model/data storage (fallback to Memory)
- Workers: Background processing for non-blocking UI
Full documentation available at localmode.dev
packages/
core/ # Zero-dependency core (functions, interfaces, VectorDB, agents, evaluation)
react/ # React hooks for all core functions (64 hooks + pipeline step factories)
ai-sdk/ # Vercel AI SDK provider
transformers/ # HuggingFace Transformers.js provider (26 model factories)
webllm/ # WebLLM provider (32 curated WebGPU models)
wllama/ # Wllama provider (GGUF via llama.cpp WASM, 30 curated + 160K+ models, streaming, JSON mode, reranking, reasoning, LoRA)
litert/ # LiteRT-LM provider (Google's WebGPU/WASM, .litertlm models)
mediapipe/ # MediaPipe Tasks provider (landmarks, gestures, vision/audio/text)
chrome-ai/ # Chrome Built-in AI provider (Gemini Nano)
langchain/ # LangChain.js adapters (embeddings, chat, vector store, reranker)
devtools/ # DevTools observability (/react hooks; widget UI deprecated)
pdfjs/ # PDF text extraction
dexie/ # Dexie.js storage adapter
idb/ # idb storage adapter
localforage/ # localForage storage adapter
apps/
ui/ # @localmode/ui registry + blocks platform — the app-demo layer (localmode.ai; 36-block /blocks gallery across 12 categories + copy-owned UI primitives + Fumadocs)
docs/ # Documentation site (localmode.dev)
- No telemetry -- We don't track anything
- No network requests -- Core package makes zero network calls
- Data stays local -- All processing happens in your browser
- Differential privacy -- Optional DP noise injection for embeddings and classification
- Encryption -- Built-in AES-GCM encryption via Web Crypto API
- PII redaction -- Automatic detection and redaction of sensitive data
- Open source -- Audit the code yourself
LocalMode is built on top of incredible open-source projects:
| Library | Used by | Description |
|---|---|---|
| Transformers.js by HuggingFace | @localmode/transformers |
State-of-the-art ML models in the browser via ONNX Runtime |
| WebLLM by MLC AI | @localmode/webllm |
High-performance LLM inference with WebGPU |
| wllama by ngxson / llama.cpp by Georgi Gerganov | @localmode/wllama |
GGUF model inference via llama.cpp compiled to WASM |
| LiteRT-LM by Google AI Edge | @localmode/litert |
Google's on-device LLM inference engine for browser (WebGPU/WASM, .litertlm models) |
| MediaPipe by Google AI Edge | @localmode/mediapipe |
On-device hand/pose/face landmark tracking, gesture recognition, and vision/audio/text tasks via WASM |
| LangChain.js by LangChain | @localmode/langchain |
Framework for building LLM-powered applications |
| Vercel AI SDK by Vercel | @localmode/ai-sdk |
Universal AI SDK for TypeScript |
| PDF.js by Mozilla | @localmode/pdfjs |
PDF rendering and text extraction |
| Dexie.js by David Fahlander | @localmode/dexie |
IndexedDB wrapper with schema versioning and transactions |
| idb by Jake Archibald | @localmode/idb |
Tiny Promise-based IndexedDB wrapper |
| localForage by Mozilla | @localmode/localforage |
Cross-browser storage with automatic fallback |
| Chrome Built-in AI by Google | @localmode/chrome-ai |
On-device AI APIs powered by Gemini Nano |
Found a bug or unexpected behavior? Open an issue and include:
- A clear description of the problem
- Steps to reproduce
- Expected vs actual behavior
- Browser name and version
- Relevant error messages or console output
- A minimal code snippet or reproduction if possible
Contributions are welcome! See CONTRIBUTING.md for setup, the architecture rules, our testing standards, and the pull-request checklist.
See CHANGELOG.md for a list of notable changes.
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