Astermind Pro

Premium ML Toolkit - Advanced RAG, Reranking, Summarization, and Information Flow Analysis

Astermind Pro extends the base @astermind/astermind-elm package with premium features for production-grade machine learning applications.

Features

$3

- Omega RAG System - Complete RAG pipeline with recursive compression
- OmegaRR Reranking - Production-grade reranking with engineered features and MMR filtering
- OmegaSumDet - Intent-aware, deterministic summarization
- Transfer Entropy - Information flow analysis with PWS and closed-loop control
- Advanced Numerical Methods - KRR, RFF, OnlineRidge, and production math utilities
- Hybrid Retrieval - Sparse (TF-IDF) + dense (kernel) retrieval system
- Auto-Tuning - Hyperparameter optimization (dev worker only)
- Tree-Aware Parsing - Hierarchical markdown processing
- Advanced ELM Variants - 5 premium ELM variants (Multi-Kernel, Deep Pro, Online Kernel, Multi-Task, Sparse)

$3

All APIs are public and extensible - no private APIs. Build your own pipelines using this professional toolbox.

``
src/
├── math/ # Production-grade numerical methods
├── omega/ # Omega RAG system
├── retrieval/ # Hybrid retrieval system (sparse + dense)
│ ├── vectorization.ts # TF-IDF, sparse/dense operations
│ ├── index-builder.ts # Vocabulary, IDF, Nyström landmarks
│ └── hybrid-retriever.ts # Hybrid retrieval with ridge regularization
├── elm/ # Advanced ELM variants
│ ├── multi-kernel-elm.ts # Multi-Kernel ELM
│ ├── deep-elm-pro.ts # Improved Deep ELM
│ ├── online-kernel-elm.ts # Online Kernel ELM
│ ├── multi-task-elm.ts # Multi-Task ELM
│ └── sparse-elm.ts # Sparse ELM
├── reranking/ # OmegaRR reranking
├── summarization/ # OmegaSumDet summarization
├── infoflow/ # Transfer Entropy analysis
├── workers/ # Web Workers (dev & production)
├── utils/ # Utility functions
│ ├── tokenization.ts # Tokenization & stemming
│ ├── markdown.ts # Markdown parsing & chunking
│ ├── autotune.ts # Hyperparameter optimization
│ └── model-serialization.ts # Model export/import
└── types.ts # TypeScript types
`

Key Feature: All retrieval and utility functions are now reusable outside of workers - use them directly in your applications!

Installation

`bash
npm install @astermind/astermind-pro
`

Prerequisites:
- @astermind/astermind-elm (peer dependency)
- @astermindai/license-runtime (included as dependency)

Note: Astermind Pro subscription includes Astermind Synth - a synthetic data generator for bootstrapping your projects. See the Developer Guide for details.

License Setup

Astermind Pro uses a centralized license configuration that automatically propagates to both Pro and Synth.

$3

To get started with Astermind Pro, visit our getting started page:

👉 Get Your License Key →

The getting started page provides step-by-step instructions for:
- Creating a free trial account
- Obtaining your license token
- Setting up your development environment

$3

1. Edit src/config/license-config.ts:
`typescript
export const LICENSE_TOKEN: string | null = 'YOUR_LICENSE_TOKEN_HERE';
`

2. Or use environment variable:
`bash
export ASTERMIND_LICENSE_TOKEN="your-license-token-here"
`

3. Or set programmatically:
`typescript
import { setLicenseTokenFromString } from '@astermind/astermind-pro';
await setLicenseTokenFromString('your-license-token-here');
`

See LICENSE_SETUP.md for complete license setup guide.

Usage

$3

`typescript
import {
// License Management
initializeLicense, checkLicense, setLicenseTokenFromString,

// Math utilities
cosine, l2, normalizeL2, ridgeSolvePro, OnlineRidge, buildRFF,

// Retrieval (NEW - reusable outside workers!)
tokenize, expandQuery, toTfidf, hybridRetrieve, buildIndex,
parseMarkdownToSections, flattenSections,

// Omega RAG
omegaComposeAnswer,

// Reranking
rerank, rerankAndFilter, filterMMR,

// Summarization
summarizeDeterministic,

// Information Flow
TransferEntropy, InfoFlowGraph, TEController,

// Auto-tuning (NEW - reusable!)
autoTune, sampleQueriesFromCorpus,

// Model serialization (NEW - reusable!)
exportModel, importModel,

// Advanced ELM Variants (NEW!)
MultiKernelELM, DeepELMPro, OnlineKernelELM, MultiTaskELM, SparseELM,

// Types
SerializedModel, Settings
} from '@astermind/astermind-pro';
`

$3

For development and training:

`typescript
// In browser context
const worker = new Worker(
new URL('@astermind/astermind-pro/workers/dev-worker', import.meta.url),
{ type: 'module' }
);

worker.postMessage({
action: 'init',
payload: {
settings: { / ... / },
chaptersPath: '/chapters.json'
}
});

// Training, autotune, etc. available
worker.postMessage({
action: 'autotune',
payload: { budget: 40, sampleQueries: 24 }
});
`

$3

For production deployments - optimized for inference:

`typescript
// In browser context
const worker = new Worker(
new URL('@astermind/astermind-pro/workers/prod-worker', import.meta.url),
{ type: 'module' }
);

// Load pre-trained model
worker.postMessage({
action: 'init',
payload: {
model: serializedModel // SerializedModel from dev-worker exportModel()
}
});

// Query only
worker.postMessage({
action: 'ask',
payload: { q: 'your query here' }
});
`

Key Features Overview

$3

Complete RAG pipeline with recursive compression, query-aligned sentence selection, and personality modes (neutral, teacher, scientist).

Use Cases: Technical documentation assistants, customer support systems, knowledge base Q&A

$3

Production-grade reranking with rich feature engineering (TF-IDF, BM25, structural signals), weak supervision, and MMR filtering.

Use Cases: Search engines, legal document retrieval, product search optimization

$3

Intent-aware, deterministic summarization with code-aware processing and heading alignment.

Use Cases: Code explanation generation, research paper summarization, technical documentation summaries

$3

Information flow monitoring with streaming TE estimation, PWS variant, and closed-loop adaptive control.

Use Cases: Pipeline quality assurance, automatic hyperparameter tuning, system health monitoring

$3

Production-grade math including KRR (Cholesky + CG fallback), RFF approximation, OnlineRidge, and overflow-safe operations.

$3

Sparse (TF-IDF) + dense (kernel) retrieval with Nyström approximation and multiple kernel types. Now available as standalone modules - use hybridRetrieve() and buildIndex() directly in your code, not just in workers!

$3

Automated hyperparameter optimization with random search, refinement, and real-time progress reporting. Now available as standalone function - use autoTune() directly in your applications.

Performance

- Training Speed: Milliseconds (vs. minutes for traditional ML)
- Inference Latency: Microseconds per query
- Model Size: KB-sized (vs. GB for large language models)
- Memory Usage: Minimal - runs entirely on-device
- Scalability: Handles millions of documents

🎁 Bonus: Astermind Synth Included

Every Astermind Pro subscription includes Astermind Synth - the synthetic data generator that helps you bootstrap your ML projects quickly.

Features:
- 5 Generation Modes - From simple retrieval to premium generation
- Pretrained Models - Ready-to-use generators for common data types
- Label-Conditioned - Generate data for specific categories
- High Realism - 56%+ realism scores on internal benchmarks
- ELM Integration - Train ELM models directly from synthetic data

See the Developer Guide for complete examples.

Documentation

- 📖 Developer Guide - Complete API reference (1,657+ lines)
- 💡 Examples - 15+ practical code examples
- 🧠 ELM Variants Examples - Complete examples for all 5 advanced ELM variants
- 💼 ELM Variants Business Examples - Real-world business use cases across industries
- ⚡ Quick Reference - Quick lookup guide
- 🎯 Premium Features - Detailed feature documentation
- 📚 Documentation Index - Complete documentation overview

Technical Specifications

- Language: TypeScript/JavaScript
- Platform: Browser & Node.js
- Dependencies: @astermind/astermind-elm (peer dependency)
- License: Proprietary
- Browser Support: Modern browsers (Chrome, Firefox, Safari, Edge)
- Node.js: Version 18+

Professional Architecture

- No Private APIs - Everything is public and extensible
- Fully Modular - Use components independently or build custom pipelines
- Type-Safe - Full TypeScript support with comprehensive types
- Production Ready - Optimized workers for dev and production deployments

Real-World Applications

- Technical Documentation - Build intelligent assistants that understand code, APIs, and technical concepts
- Legal Research - Extract relevant information from legal documents with citation-aware ranking
- Customer Support - Provide accurate, helpful answers from knowledge bases
- E-Commerce - Improve product search relevance and generate comparison summaries
- Medical Information - Retrieve accurate medical information with trust-weighted ranking
- Research Analysis - Summarize research papers and extract key findings automatically

Quick Start Examples

$3

`typescript
import {
buildIndex,
hybridRetrieve,
rerankAndFilter,
summarizeDeterministic
} from '@astermind/astermind-pro';

// Build index from your documents
const index = buildIndex({
chunks: yourDocuments,
vocab: 10000,
landmarks: 256,
headingW: 2.0,
useStem: true,
kernel: 'rbf',
sigma: 1.0
});

// Perform hybrid retrieval
const retrieved = hybridRetrieve({
query: 'your query',
chunks: yourDocuments,
vocabMap: index.vocabMap,
idf: index.idf,
tfidfDocs: index.tfidfDocs,
denseDocs: index.denseDocs,
landmarksIdx: index.landmarksIdx,
landmarkMat: index.landmarkMat,
vocabSize: index.vocabMap.size,
kernel: 'rbf',
sigma: 1.0,
alpha: 0.7,
beta: 0.1,
ridge: 0.08,
headingW: 2.0,
useStem: true,
expandQuery: false,
topK: 10
});

// Rerank and summarize
const reranked = rerankAndFilter(query, retrieved.items, {
lambdaRidge: 1e-2,
probThresh: 0.45,
useMMR: true
});

const summary = summarizeDeterministic(query, reranked, {
maxAnswerChars: 1000,
includeCitations: true
});
`

$3

`typescript
import {
rerankAndFilter,
summarizeDeterministic,
InfoFlowGraph
} from '@astermind/astermind-pro';

// Build your custom pipeline
const results = rerankAndFilter(query, documents, {
lambdaRidge: 1e-2,
probThresh: 0.45,
useMMR: true
});

const summary = summarizeDeterministic(query, results, {
maxAnswerChars: 1000,
includeCitations: true
});
``

Support & Resources

- Documentation: See DOCS_INDEX.md for complete documentation
- Examples: See EXAMPLES.md for practical code examples
- Pricing: See PRICING_PAGE.md for pricing information
- Legal: See LEGAL_INDEX.md for terms, privacy, and legal documents

License

PROPRIETARY - This is a premium package. See TERMS_OF_SERVICE.md for usage rights.

---

Astermind Pro - Professional ML Toolkit for Production Applications

For questions and support, contact AsterMind LLC.