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+---
+title: Ollama with agent
+description: The smart home reference
+published: true
+date: 2026-02-18T22:14:41.533Z
+tags: 
+editor: markdown
+dateCreated: 2026-02-18T22:14:41.533Z
+---
+
+# AI Automation Stack - Ollama + n8n + Open WebUI
+
+## Overview
+
+This stack provides a complete self-hosted AI automation solution for homelab infrastructure management, documentation generation, and intelligent monitoring. The system consists of four core components that work together to provide AI-powered workflows and knowledge management.
+
+## Architecture
+
+```
+┌─────────────────────────────────────────────────┐
+│              AI Automation Stack                 │
+│                                                  │
+│  Open WebUI ────────┐                           │
+│  (Chat Interface)   │                           │
+│         │           │                           │
+│         ▼           ▼                           │
+│      Ollama ◄──── Qdrant                        │
+│   (LLM Runtime)   (Vector DB)                   │
+│         ▲                                       │
+│         │                                       │
+│       n8n                                       │
+│  (Workflow Engine)                              │
+│         │                                       │
+│         ▼                                       │
+│  Forgejo │ Wiki.js │ Monitoring                 │
+└─────────────────────────────────────────────────┘
+```
+
+## Components
+
+### Ollama
+- **Purpose**: Local LLM runtime engine
+- **Port**: 11434
+- **Resource Usage**: 4-6GB RAM (depending on model)
+- **Recommended Models**:
+  - `qwen2.5-coder:7b` - Code analysis and documentation
+  - `llama3.2:3b` - General queries and chat
+  - `phi3:mini` - Lightweight alternative
+
+### Open WebUI
+- **Purpose**: User-friendly chat interface with built-in RAG (Retrieval Augmented Generation)
+- **Port**: 3000
+- **Features**:
+  - Document ingestion from Wiki.js
+  - Conversational interface for querying documentation
+  - RAG pipeline for context-aware responses
+  - Multi-model support
+- **Access**: `http://your-server-ip:3000`
+
+### Qdrant
+- **Purpose**: Vector database for semantic search and RAG
+- **Ports**: 6333 (HTTP), 6334 (gRPC)
+- **Resource Usage**: ~1GB RAM
+- **Function**: Stores embeddings of your documentation, code, and markdown files
+
+### n8n
+- **Purpose**: Workflow automation and orchestration
+- **Port**: 5678
+- **Default Credentials**: 
+  - Username: `admin`
+  - Password: `change-this-password` (⚠️ **Change this immediately**)
+- **Access**: `http://your-server-ip:5678`
+
+## Installation
+
+### Prerequisites
+- Docker and Docker Compose installed
+- 16GB RAM minimum (8GB available for the stack)
+- 50GB disk space for models and data
+
+### Deployment Steps
+
+1. **Create directory structure**:
+```bash
+mkdir -p ~/ai-stack/{n8n/workflows}
+cd ~/ai-stack
+```
+
+2. **Download the compose file**:
+```bash
+# Place the ai-stack-compose.yml in this directory
+wget [your-internal-url]/ai-stack-compose.yml
+```
+
+3. **Configure environment variables**:
+```bash
+# Edit the compose file and change:
+# - WEBUI_SECRET_KEY
+# - N8N_BASIC_AUTH_PASSWORD
+# - WEBHOOK_URL (use your server's IP)
+# - GENERIC_TIMEZONE
+nano ai-stack-compose.yml
+```
+
+4. **Start the stack**:
+```bash
+docker-compose -f ai-stack-compose.yml up -d
+```
+
+5. **Pull Ollama models**:
+```bash
+docker exec -it ollama ollama pull qwen2.5-coder:7b
+docker exec -it ollama ollama pull llama3.2:3b
+```
+
+6. **Verify services**:
+```bash
+docker-compose -f ai-stack-compose.yml ps
+```
+
+## Configuration
+
+### Open WebUI Setup
+
+1. Navigate to `http://your-server-ip:3000`
+2. Create your admin account (first user becomes admin)
+3. Go to **Settings → Connections** and verify Ollama connection
+4. Configure Qdrant:
+   - Host: `qdrant`
+   - Port: `6333`
+
+### Setting Up RAG for Wiki.js
+
+1. In Open WebUI, go to **Workspace → Knowledge**
+2. Create a new collection: "Homelab Documentation"
+3. Add sources:
+   - **URL Crawl**: Enter your Wiki.js base URL
+   - **File Upload**: Upload markdown files from repositories
+4. Process and index the documents
+
+### n8n Initial Configuration
+
+1. Navigate to `http://your-server-ip:5678`
+2. Log in with credentials from docker-compose file
+3. Import starter workflows from `/n8n/workflows/` directory
+
+## Use Cases
+
+### 1. Automated Documentation Generation
+
+**Workflow**: Forgejo webhook → n8n → Ollama → Wiki.js
+
+When code is pushed to Forgejo:
+1. n8n receives webhook from Forgejo
+2. Extracts changed files and repo context
+3. Sends to Ollama with prompt: "Generate documentation for this code"
+4. Posts generated docs to Wiki.js via API
+
+**Example n8n Workflow**:
+```
+Webhook Trigger
+  → HTTP Request (Forgejo API - get file contents)
+  → Ollama LLM Node (generate docs)
+  → HTTP Request (Wiki.js API - create/update page)
+  → Send notification (completion)
+```
+
+### 2. Docker-Compose Standardization
+
+**Workflow**: Repository scan → compliance check → issue creation
+
+1. n8n runs on schedule (daily/weekly)
+2. Queries Forgejo API for all repositories
+3. Scans for `docker-compose.yml` files
+4. Compares against template standards stored in Qdrant
+5. Generates compliance report with Ollama
+6. Creates Forgejo issues for non-compliant repos
+
+### 3. Intelligent Alert Processing
+
+**Workflow**: Monitoring alert → AI analysis → smart routing
+
+1. Beszel/Uptime Kuma sends webhook to n8n
+2. n8n queries historical data and context
+3. Ollama analyzes:
+   - Is this expected? (scheduled backup, known maintenance)
+   - Severity level
+   - Recommended action
+4. Routes appropriately:
+   - Critical: Immediate notification (Telegram/email)
+   - Warning: Log and monitor
+   - Info: Suppress (expected behavior)
+
+### 4. Email Monitoring & Triage
+
+**Workflow**: IMAP polling → AI classification → action routing
+
+1. n8n polls email inbox every 5 minutes
+2. Filters for keywords: "alert", "critical", "down", "failed"
+3. Ollama classifies urgency and determines if actionable
+4. Routes based on classification:
+   - Urgent: Forward to you immediately
+   - Informational: Daily digest
+   - Spam: Archive
+
+## Common Workflows
+
+### Example: Repository Documentation Generator
+
+```javascript
+// n8n workflow nodes:
+
+1. Schedule Trigger (daily at 2 AM)
+   ↓
+2. HTTP Request - Forgejo API
+   URL: http://forgejo:3000/api/v1/repos/search
+   Method: GET
+   ↓
+3. Loop Over Items (each repo)
+   ↓
+4. HTTP Request - Get repo files
+   URL: {{$node["Forgejo API"].json["clone_url"]}}/contents
+   ↓
+5. Filter - Find docker-compose.yml and README.md
+   ↓
+6. Ollama Node
+   Model: qwen2.5-coder:7b
+   Prompt: "Analyze this docker-compose file and generate comprehensive 
+           documentation including: purpose, services, ports, volumes, 
+           environment variables, and setup instructions."
+   ↓
+7. HTTP Request - Wiki.js API
+   URL: http://wikijs:3000/graphql
+   Method: POST
+   Body: {mutation: createPage(...)}
+   ↓
+8. Send Notification
+   Service: Telegram/Email
+   Message: "Documentation updated for {{repo_name}}"
+```
+
+### Example: Alert Intelligence Workflow
+
+```javascript
+// n8n workflow nodes:
+
+1. Webhook Trigger
+   Path: /webhook/monitoring-alert
+   ↓
+2. Function Node - Parse Alert Data
+   JavaScript: Extract service, metric, value, timestamp
+   ↓
+3. HTTP Request - Query Historical Data
+   URL: http://beszel:8090/api/metrics/history
+   ↓
+4. Ollama Node
+   Model: llama3.2:3b
+   Context: Your knowledge base in Qdrant
+   Prompt: "Alert: {{alert_message}}
+           Historical context: {{historical_data}}
+           Is this expected behavior? 
+           What's the severity? 
+           What action should be taken?"
+   ↓
+5. Switch Node - Route by Severity
+   Conditions:
+   - Critical: Route to immediate notification
+   - Warning: Route to monitoring channel
+   - Info: Route to log only
+   ↓
+6a. Send Telegram (Critical path)
+6b. Post to Slack (Warning path)
+6c. Write to Log (Info path)
+```
+
+## Maintenance
+
+### Model Management
+
+```bash
+# List installed models
+docker exec -it ollama ollama list
+
+# Update a model
+docker exec -it ollama ollama pull qwen2.5-coder:7b
+
+# Remove unused models
+docker exec -it ollama ollama rm old-model:tag
+```
+
+### Backup Important Data
+
+```bash
+# Backup Qdrant vector database
+docker-compose -f ai-stack-compose.yml stop qdrant
+tar -czf qdrant-backup-$(date +%Y%m%d).tar.gz ./qdrant_data/
+docker-compose -f ai-stack-compose.yml start qdrant
+
+# Backup n8n workflows (automatic to ./n8n/workflows)
+tar -czf n8n-backup-$(date +%Y%m%d).tar.gz ./n8n_data/
+
+# Backup Open WebUI data
+tar -czf openwebui-backup-$(date +%Y%m%d).tar.gz ./open_webui_data/
+```
+
+### Log Monitoring
+
+```bash
+# View all stack logs
+docker-compose -f ai-stack-compose.yml logs -f
+
+# View specific service
+docker logs -f ollama
+docker logs -f n8n
+docker logs -f open-webui
+```
+
+### Resource Monitoring
+
+```bash
+# Check resource usage
+docker stats
+
+# Expected usage:
+# - ollama: 4-6GB RAM (with model loaded)
+# - open-webui: ~500MB RAM
+# - qdrant: ~1GB RAM
+# - n8n: ~200MB RAM
+```
+
+## Troubleshooting
+
+### Ollama Not Responding
+
+```bash
+# Check if Ollama is running
+docker logs ollama
+
+# Restart Ollama
+docker restart ollama
+
+# Test Ollama API
+curl http://localhost:11434/api/tags
+```
+
+### Open WebUI Can't Connect to Ollama
+
+1. Check network connectivity:
+```bash
+docker exec -it open-webui ping ollama
+```
+
+2. Verify Ollama URL in Open WebUI settings
+3. Restart both containers:
+```bash
+docker restart ollama open-webui
+```
+
+### n8n Workflows Failing
+
+1. Check n8n logs:
+```bash
+docker logs n8n
+```
+
+2. Verify webhook URLs are accessible
+3. Test Ollama connection from n8n:
+   - Create test workflow
+   - Add Ollama node
+   - Run execution
+
+### Qdrant Connection Issues
+
+```bash
+# Check Qdrant health
+curl http://localhost:6333/health
+
+# View Qdrant logs
+docker logs qdrant
+
+# Restart if needed
+docker restart qdrant
+```
+
+## Performance Optimization
+
+### Model Selection by Use Case
+
+- **Quick queries, chat**: `llama3.2:3b` or `phi3:mini` (fastest)
+- **Code analysis**: `qwen2.5-coder:7b` or `deepseek-coder:6.7b`
+- **Complex reasoning**: `mistral:7b` or `llama3.1:8b`
+
+### n8n Workflow Optimization
+
+- Use **Wait** nodes to batch operations
+- Enable **Execute Once** for loops to reduce memory
+- Store large data in temporary files instead of node output
+- Use **Split In Batches** for processing large datasets
+
+### Qdrant Performance
+
+- Default settings are optimized for homelab use
+- Increase `collection_shards` if indexing >100,000 documents
+- Enable quantization for large collections
+
+## Security Considerations
+
+### Change Default Credentials
+
+```bash
+# Generate secure password
+openssl rand -base64 32
+
+# Update in docker-compose.yml:
+# - WEBUI_SECRET_KEY
+# - N8N_BASIC_AUTH_PASSWORD
+```
+
+### Network Isolation
+
+Consider using a reverse proxy (Traefik, Nginx Proxy Manager) with authentication:
+- Limit external access to Open WebUI only
+- Keep n8n, Ollama, Qdrant on internal network
+- Use VPN for remote access
+
+### API Security
+
+- Use strong API tokens for Wiki.js and Forgejo integrations
+- Rotate credentials periodically
+- Audit n8n workflow permissions
+
+## Integration Points
+
+### Connecting to Existing Services
+
+**Uptime Kuma**:
+- Configure webhook alerts → n8n webhook URL
+- Path: `http://your-server-ip:5678/webhook/uptime-kuma`
+
+**Beszel**:
+- Use Shoutrrr webhook format
+- URL: `http://your-server-ip:5678/webhook/beszel`
+
+**Forgejo**:
+- Repository webhooks for push events
+- URL: `http://your-server-ip:5678/webhook/forgejo-push`
+- Enable in repo settings → Webhooks
+
+**Wiki.js**:
+- GraphQL API endpoint: `http://wikijs:3000/graphql`
+- Create API key in Wiki.js admin panel
+- Store in n8n credentials
+
+## Advanced Features
+
+### Creating Custom n8n Nodes
+
+For frequently used Ollama prompts, create custom nodes:
+
+1. Go to n8n → Settings → Community Nodes
+2. Install `n8n-nodes-ollama-advanced` if available
+3. Or create Function nodes with reusable code
+
+### Training Custom Models
+
+While Ollama doesn't support fine-tuning directly, you can:
+1. Use RAG with your specific documentation
+2. Create detailed system prompts in n8n
+3. Store organization-specific context in Qdrant
+
+### Multi-Agent Workflows
+
+Chain multiple Ollama calls for complex tasks:
+```
+Planning Agent → Execution Agent → Review Agent → Output
+```
+
+Example: Code refactoring
+1. Planning: Analyze code and create refactoring plan
+2. Execution: Generate refactored code
+3. Review: Check for errors and improvements
+4. Output: Create pull request with changes
+
+## Resources
+
+- **Ollama Documentation**: https://ollama.ai/docs
+- **Open WebUI Docs**: https://docs.openwebui.com
+- **n8n Documentation**: https://docs.n8n.io
+- **Qdrant Docs**: https://qdrant.tech/documentation
+
+## Support
+
+For issues or questions:
+1. Check container logs first
+2. Review this documentation
+3. Search n8n community forums
+4. Check Ollama Discord/GitHub issues
+
+---
+
+**Last Updated**: {{current_date}}  
+**Maintained By**: Homelab Admin  
+**Status**: Production