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j4f-assistant

J4F Assistant: Comprehensive Project Documentation

High-Level Overview

J4F Assistant is a production-ready, enterprise-grade AI assistant framework featuring:

  • 🚀 NATS-Powered Pipeline Processing - Scalable, real-time data transformation workflows
  • 🔐 Enterprise Authentication - OIDC/Keycloak with comprehensive RBAC system
  • 🧠 LangChain-Powered Streaming - Advanced AI capabilities with conversation memory
  • 🏗️ Fully Modular Architecture - Complete separation of concerns, highly extensible
  • ⚡ Multi-Interface Support - Web UI, CLI, and comprehensive API endpoints
  • 🛡️ Production Security - Command execution, risk analysis, audit logging
  • 🐳 Complete Deployment Infrastructure - Docker, Kubernetes, Helm charts

📚 Comprehensive Documentation Index

🏗️ Core Architecture & Systems

🔐 Security & Authentication

🚀 Deployment & Operations

📖 Getting Started

🎯 Quick Navigation by Role

Developers

  1. Architecture Overview - Understand the modular design
  2. Pipeline System ⭐ FLAGSHIP FEATURE - Learn the NATS-based data processing workflows
  3. Pipeline Step Development Guide ⭐ NEW - Create custom processing modules with templates and patterns
  4. Backend Overview - Core components and streaming
  5. API Reference - Available endpoints and usage

DevOps/Infrastructure

  1. Deployment Infrastructure - Complete deployment guide
  2. Authentication Setup - OIDC/Keycloak configuration
  3. Security Framework - Security implementation
  4. Architecture Overview - System design understanding

Users/Administrators

  1. Authentication System - User roles and permissions
  2. Frontend Overview - UI features and capabilities
  3. API Reference - Available features and endpoints
  4. Security Overview - Security features and controls

🚀 Major Features & Capabilities

Advanced Pipeline Processing ⭐ FLAGSHIP FEATURE

  • Visual Pipeline Editor: Production-ready drag-and-drop interface for pipeline creation ✅ LIVE NOW
  • Real-time Streaming: NATS-based message processing with live data transformation and zero buffering delays
  • Modular Steps: Composable processing steps (markdown normalization, content filtering, syntax highlighting, etc.)
  • Scalable Architecture: Distributed processing with backpressure handling and conversation isolation
  • Configuration-Driven: Visual and database-stored pipeline definitions with runtime composition and version control
  • Developer-Friendly: Comprehensive step development guide with templates, patterns, and best practices

Enterprise-Grade Authentication

  • Multi-Provider OIDC: Keycloak, Auth0, and custom provider support
  • Comprehensive RBAC: Five-tier role system (User → Admin → Dev → Lead → TheDude)
  • Granular Permissions: Fine-grained API and feature access control
  • Session Management: Secure, persistent sessions with automatic token refresh

Production-Ready Architecture

  • Complete Modularity: Every component is focused, reusable, and independently testable
  • LangChain Integration: Advanced AI capabilities with conversation memory and tool integration
  • Security Framework: Risk analysis, audit logging, secure command execution
  • Multi-Interface: Web UI, CLI, and comprehensive REST/WebSocket APIs

Deployment Infrastructure

  • Container-First: Docker Compose for development, Kubernetes for production
  • Helm Charts: Production-ready Kubernetes deployment with auto-scaling
  • Environment Management: Dev, staging, production configurations
  • Monitoring & Health Checks: Built-in observability and performance monitoring

🔧 System Requirements & Dependencies

Core Dependencies

  • Node.js 18+ - Application runtime
  • MongoDB 7+ - Primary database for conversations, pipelines, user data
  • NATS Server - Message queue for pipeline processing
  • Ollama/Anthropic/OpenAI - AI model providers

Optional Components

  • Keycloak - Enterprise authentication (can run without auth)
  • Redis - Session storage and caching (optional)
  • Prometheus/Grafana - Monitoring and metrics (recommended for production)

🚦 Quick Start Paths

Development Setup 

git clone <repository>
cd j4f-assistant
cp .env.example .env
docker-compose up -d

Production Deployment 

helm install j4f-assistant ./helm/j4f-assistant \
  --namespace production --create-namespace \
  --values values-prod.yaml

Pipeline Development ⭐ NEW 

# Create new pipeline step
vim src/pipeline/steps/myStep.js

# Use the step template from the development guide
export async function* myStep(input, config = {}) {
  for await (const chunk of input) {
    yield processChunk(chunk);
  }
}

# Register step
vim src/pipeline/stepRegistry.js

# Test pipeline
curl -X POST /api/unified/stream -d '{"message":"test"}'

📖 Additional Resources

  • Repository: Main codebase with implementation details
  • Wiki: This comprehensive documentation system
  • Issue Tracker: Feature requests and bug reports
  • Contributing Guide: Development guidelines and contribution process

This documentation reflects the current state of the J4F Assistant as a sophisticated, production-ready AI assistant framework with enterprise-grade features and comprehensive deployment infrastructure.