Building JOSIE: Advanced AI Workflow with Persistent Memory and Live Data Access

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Learn how to build an uncensored AI assistant with persistent memory using n8n automation, vector databases, and privacy-focused web search

TL;DR: I’ve built a sophisticated AI assistant using n8n workflow automation that combines three powerful components: JOSIEFIED-Qwen3:8b for intelligent responses, Qdrant vector database for persistent memory, and SearXNG for unlimited web search—all while maintaining complete data privacy.

The Architecture That Changes Everything

Traditional AI assistants suffer from memory loss and limited web access. JOSIE solves both problems with a three-tier architecture that remembers everything and searches without limits. This AI automation workflow demonstrates how to build enterprise-grade AI systems using open-source tools.

Component 1: JOSIEFIED-Qwen3:8b – The Intelligent Core

JOSIEFIED-Qwen3:8b represents the latest evolution in the JOSIEFIED family, built upon Alibaba’s Qwen3 architecture with 8.19B parameters and a massive 40K context window. This uncensored language model brings several key advantages:

Key Features:

  • Enhanced Intelligence: Built on Qwen3’s advanced architecture with improved reasoning capabilities
  • Extended Context: 40K token context window enables processing of lengthy documents and conversations
  • Tool Integration: Maintains ability to use external APIs and tools despite reduced filtering
  • Local Processing: Complete privacy with no external API dependencies
  • Multiple Quantization Options: Available in Q4_K_M, Q5_K_M, Q6_K, Q8_0, and FP16 variants for different hardware configurations

Running locally via Ollama with optimized parameters (temperature: 0.7, top-P: 0.9), JOSIEFIED-Qwen3:8b delivers intelligent responses while maintaining complete data control. Learn more about running local AI models for privacy-focused implementations.

Component 2: Qdrant Vector Database – The Persistent Memory

Qdrant transforms conversations from fleeting exchanges into permanent knowledge. This open-source vector database creates a three-tier memory system that enables semantic search across all interactions:

Document Ingestion Pipeline

  • PDF processing with form-based uploads
  • Intelligent text chunking (200-character chunks, 50-character overlap)
  • High-quality embeddings using mxbai-embed-large:335m
  • Automatic vector storage with rich metadata

Conversation Memory Processing Every interaction generates multiple memory chunks using LangChain integration:

const conversationChunk = {
  pageContent: `User Question: ${chatInput}\n\nAssistant Response: ${agentOutput}`,
  metadata: {
    type: 'conversation',
    sessionId: sessionId,
    timestamp: timestamp,
    // Rich contextual metadata
  }
};

Advanced Retrieval System

  • Context retrieval for documents (top-K: 3)
  • Memory retrieval for conversation history (top-K: 50)
  • Semantic search with metadata filtering
  • Session-aware context management

The result? Vector quantization reduces RAM usage by up to 97% while maintaining sub-second search times across thousands of conversations.

Component 3: SearXNG – Unlimited Web Intelligence

SearXNG eliminates the constraints of traditional search APIs. This privacy-focused metasearch engine running locally on Docker (port 8080) provides:

  • Unlimited Queries: No rate limits or API costs
  • Privacy Protection: Zero tracking or profiling
  • Multi-Engine Aggregation: Simultaneous results from Google, Bing, DuckDuckGo
  • JSON API: Clean programmatic access perfect for AI integration

Configuration optimized for AI use with the SearXNG API:

GET localhost:8080/search?q={query}&format=json&categories=general&engines=google,bing,duckduckgo&lang=en

The Workflow in Action

Smart Tool Selection: JOSIE automatically decides when to search the web, retrieve memories, or access stored documents based on query context using n8n’s conditional logic.

Session Management: Persistent conversations maintain context across interactions with comprehensive analytics and performance tracking through n8n’s execution data.

Error Handling: Graceful degradation ensures the system continues operating even when components fail, leveraging n8n’s error workflows.

Real-World Applications

Personal Knowledge Management Upload PDFs and query them conversationally. JOSIE remembers every discussion and decision, creating a searchable knowledge base of your interactions. Perfect for document analysis workflows.

Business Intelligence
Maintain context across long-term projects with customer support that remembers all interactions. Combine stored knowledge with live web data for comprehensive research using enterprise AI workflows.

Educational Companion Track learning progress across multiple topics while accessing both academic papers and current web information through automated research pipelines.

Privacy and Security Benefits

Complete Data Control: All AI computations happen locally on your hardware. SearXNG doesn’t track searches, and no data leaves your network. Learn about self-hosted AI benefits for maximum privacy.

Compliance Ready: GDPR-compliant with air-gapped deployment options. Complete audit trails with full control over data retention using local deployment strategies.

Enterprise Security: Isolated environment with comprehensive logging and monitoring capabilities through n8n’s audit logs.

Technical Implementation

n8n Orchestration: Visual workflow builder handles up to 220 executions per second with project-based access controls.

Vector Storage: Qdrant database with cosine similarity and HNSW indexing for fast approximate nearest neighbor search.

Embedding Strategy: 1024-dimensional vectors provide rich semantic representation with consistent local processing using Ollama embeddings.

Performance and Scalability

The modular architecture scales efficiently:

  • Local processing eliminates external dependencies
  • Optimized storage with vector quantization
  • Sub-second search times across massive document collections
  • Kubernetes-ready for high availability deployments

For production scaling, explore n8n cloud deployment and Qdrant cluster setup.

Getting Started

Prerequisites:

Quick Setup:

  1. Deploy SearXNG using official Docker compose
  2. Install Qdrant with persistent storage
  3. Configure Ollama with JOSIEFIED-Qwen3:8b
  4. Import n8n workflow JSON
  5. Configure service credentials

The Future of AI Assistance

JOSIE represents a fundamental shift toward privacy-preserving AI that grows smarter with every interaction. By combining advanced language models, persistent memory, and unlimited web access—all under your complete control—it delivers enterprise-grade capabilities without vendor lock-in.

The combination of JOSIEFIED-Qwen3:8b’s enhanced intelligence, Qdrant’s powerful vector search, and SearXNG’s privacy-focused web access creates a truly autonomous AI assistant that remembers everything while keeping your data completely secure.

Ready to build your own intelligent assistant? The modular architecture makes it easy to implement piece by piece, gradually building up to the full system. Start with the n8n quickstart guide and explore AI workflow templates for inspiration.

Want to discuss advanced AI workflow architectures or share your own automation projects? Let’s connect and explore the future of privacy-preserving AI solutions. Check out more AI automation tutorials and vector database guides to expand your knowledge.

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