feat(openclaw): deploy OpenClaw AI chatbot gateway on VM 120
- Add Docker Compose configs with security hardening (cap_drop ALL, non-root, read-only FS) - Add Prometheus node_exporter scrape target for 192.168.2.120:9100 - Update services/README.md, INDEX.md, and CLAUDE_STATUS.md with VM 120 - Image pinned to v2026.2.1 (patches CVE-2026-25253) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
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CLAUDE_STATUS.md
289
CLAUDE_STATUS.md
@@ -1,24 +1,48 @@
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# Homelab Infrastructure Status
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**Last Updated**: 2025-12-18 17:00:00
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**Last Updated**: 2026-02-03
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**Export Reference**: disaster-recovery/homelab-export-20251211-144345
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**Current Session:** OpenClaw Deployment - VM 120
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## Quick Resume (Current Session Context)
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**Where We Are:** OpenClaw deployed and healthy on VM 120. Container running with full security hardening. Backups configured. Manual steps remain for NPM proxy host, Twingate resource, and Prometheus config on VM 101.
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**Completed:**
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- [x] Config files created (`services/openclaw/`)
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- [x] VM 120 created and hardened (UFW, fail2ban, node-exporter, openclaw user)
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- [x] OpenClaw container deployed and healthy (v2026.2.1)
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- [x] Security verified (cap_drop ALL, non-root, read-only FS, no docker.sock)
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- [x] Prometheus scrape target added to repo copy
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- [x] PBS backup job created (daily 02:00, snapshot, zstd)
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- [x] Application backup script + weekly cron configured
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- [x] Documentation updated (README, services/README, CLAUDE_STATUS, INDEX)
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- [x] node_exporter installed and serving metrics on 192.168.2.120:9100
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**Manual Steps Remaining:**
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- [ ] NPM: Create proxy host for openclaw.apophisnetworking.net -> 192.168.2.120:18789 (WebSocket support, SSL, TinyAuth)
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- [ ] Twingate: Add resource for 192.168.2.120 ports 18789/18790/1455
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- [ ] VM 101: Deploy updated prometheus.yml via Proxmox web console (SSH not configured)
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- [ ] Configure at least one LLM provider API key in /opt/openclaw/.env
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---
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## Current Infrastructure Snapshot
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### Proxmox Environment
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- **Node**: serviceslab
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- **Version**: Proxmox VE 8.4.0
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- **Management IP**: 192.168.2.200
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- **Management IP**: 192.168.2.100
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- **Architecture**: Single-node cluster
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- **Total Resources**: 9 VMs, 2 Templates, 5 LXC Containers
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- **Total Resources**: 10 VMs, 2 Templates, 5 LXC Containers
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---
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## Virtual Machines (QEMU/KVM) - 9 VMs
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## Virtual Machines (QEMU/KVM) - 10 VMs
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| VM ID | Name | IP Address | Status | Purpose |
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|-------|------|------------|--------|---------|
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| 100 | docker-hub | 192.168.2.XXX | Running | Container registry/Docker hub mirror |
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| 100 | docker-hub | 192.168.2.102 | Running | Container registry/Docker hub mirror |
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| 101 | monitoring-docker | 192.168.2.114 | Running | Monitoring stack (Grafana/Prometheus/PVE Exporter) |
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| 105 | dev | - | Stopped | General-purpose development workstation |
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| 106 | Ansible-Control | 192.168.2.XXX | Running | IaC orchestration, configuration management |
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@@ -27,8 +51,10 @@
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| 110 | web-server-02 | 192.168.2.XXX | Running | Load-balanced pair with web-server-01 |
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| 111 | db-server-01 | 192.168.2.XXX | Running | Backend database server |
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| 114 | haos | 192.168.2.XXX | Running | Home Assistant OS - smart home automation platform |
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| 120 | openclaw | 192.168.2.120 | Running | OpenClaw AI chatbot gateway |
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**Recent Changes**:
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- Added VM 120 (openclaw) for multi-platform AI chatbot gateway (2026-02-03)
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- Added VM 101 (monitoring-docker) for dedicated monitoring infrastructure
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- Removed VM 101 (gitlab) - service decommissioned
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@@ -52,7 +78,7 @@
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| 102 | nginx | 192.168.2.101 | Running | Reverse proxy/load balancer & NPM |
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| 103 | netbox | 192.168.2.XXX | Running | Network documentation/IPAM |
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| 112 | twingate-connector | 192.168.2.XXX | Running | Zero-trust network access connector |
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| 113 | n8n | 192.168.2.107 | Running | Workflow automation platform |
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| 113 | n8n | 192.168.2.113 | Running | Workflow automation platform |
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| 115 | tinyauth | 192.168.2.10 | Running | SSO authentication layer for NetBox |
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**Recent Changes**:
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@@ -99,7 +125,7 @@
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- **Integration**: Connects homelab to Twingate network
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### Automation & Integration
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**CT 113** - n8n (192.168.2.107)
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**CT 113** - n8n (192.168.2.113)
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- **Purpose**: Workflow automation platform
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- **Technology**: n8n.io
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- **Database**: PostgreSQL 15+
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@@ -118,6 +144,18 @@
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- **Documentation**: `/home/jramos/homelab/services/tinyauth/README.md`
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- **Status**: Operational
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### AI Chatbot Gateway
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**VM 120** - openclaw (192.168.2.120)
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- **Purpose**: Multi-platform AI chatbot gateway
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- **Technology**: OpenClaw (Docker container)
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- **Ports**: 18789 (Gateway WS+UI), 18790 (Bridge), 1455 (OAuth)
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- **Domain**: openclaw.apophisnetworking.net
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- **LLM Providers**: Anthropic, OpenAI, Ollama
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- **Messaging**: Discord, Telegram, Slack, WhatsApp
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- **Security**: CVE-2026-25253 patched (v2026.2.1), cap_drop ALL, non-root, read-only FS
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- **Documentation**: `/home/jramos/homelab/services/openclaw/README.md`
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- **Status**: Operational - Container healthy
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### Infrastructure Documentation
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**CT 103** - netbox
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- **Purpose**: Network documentation and IPAM
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@@ -212,6 +250,47 @@ Hybrid approach balancing performance and resource efficiency:
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## Recent Infrastructure Changes
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### 2026-02-03: OpenClaw AI Chatbot Gateway Deployment (In Progress)
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**Service**: VM 120 - OpenClaw multi-platform AI chatbot gateway
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**Purpose**: Bridge messaging platforms (Discord, Telegram, Slack, WhatsApp) with LLM providers (Anthropic, OpenAI, Ollama) through a unified gateway.
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**Specifications**:
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- **VM**: 120 (cloned from template 107, ubuntu-docker)
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- **IP**: 192.168.2.120
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- **Resources**: 4 vCPUs, 16GB RAM, 50GB disk on Vault (ZFS)
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- **Ports**: 18789 (Gateway WS+UI), 18790 (Bridge), 1455 (OAuth)
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- **Domain**: openclaw.apophisnetworking.net
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- **Image**: ghcr.io/openclaw/openclaw:2026.2.1
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**Security Hardening**:
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- Version >= 2026.2.1 (patches CVE-2026-25253, CVSS 8.8 1-click RCE)
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- All ports bound to 127.0.0.1 (reverse proxy required)
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- Docker: cap_drop ALL, no-new-privileges, read-only filesystem, non-root user (1001:1001)
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- UFW: deny-all + whitelist 192.168.2.0/24 + 192.168.1.91 (desktop PC)
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- fail2ban on SSH (3 retries), unattended-upgrades
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- Prometheus node_exporter at port 9100
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**Completed Steps**:
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- [x] Docker Compose configuration files created
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- [x] Security hardening overlay (docker-compose.override.yml)
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- [x] Environment variable template (.env.example)
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- [x] Prometheus scrape target added
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- [x] Documentation created (README, services/README, CLAUDE_STATUS, INDEX)
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- [x] VM 120 Creation & SSH Setup
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- [x] OS Hardening (UFW, user creation)
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**Pending Steps**:
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- [ ] NPM reverse proxy configuration (manual - web UI)
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- [ ] Twingate resource creation (manual - admin console)
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- [ ] Prometheus config on VM 101 (manual - no SSH access)
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- [ ] Configure LLM provider API key in .env
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**Status**: Container healthy - Manual network integration remaining
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---
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### 2025-12-20: Comprehensive Security Audit Completed
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**Activity:** Complete infrastructure security assessment and remediation planning
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@@ -363,6 +442,51 @@ Hybrid approach balancing performance and resource efficiency:
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---
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### 2025-12-25: RAG Vector Search - Phase 3 Complete
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**Activity:** Implemented and debugged production-ready vector search system for AI-powered documentation retrieval
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**Deliverables:**
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1. **Production Module** (`n8n/vector_search.py`): Complete API for semantic search
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- `search_similar_documents()` - Query with natural language
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- `insert_document()` - Add documents with embeddings
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- `get_stats()` - Database statistics
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- `delete_by_repo()` - Bulk cleanup
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- CLI interface for testing and manual operations
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2. **Documentation Suite:**
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- `SESSION_HANDOFF_PHASE4_READY.md` (17KB) - Comprehensive learning guide for next session
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- `PHASE3_COMPLETE.md` (12KB) - Complete debugging summary and deployment guide
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- `VECTOR_SEARCH_DEBUG.md` (4.7KB) - Technical root cause analysis
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- `VECTOR_SEARCH_COMPARISON.md` (2.5KB) - Before/after code comparison
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3. **Diagnostic Scripts** (8 total):
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- Embedding storage repair, parameter binding tests, SQL validation
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- All scripts validated and preserved for reference
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**Technical Achievement:**
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- PostgreSQL 16.11 + pgvector 0.8.1 fully operational on CT 113
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- Vector similarity search returning accurate scores (0.5765 for related concepts)
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- Resolved 2 critical bugs:
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1. psycopg2 parameter handling for pgvector types (must cast in SQL, not Python)
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2. ORDER BY with vector operations (subquery pattern required)
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**Validation Results:**
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- Query: "How do I create snapshots of virtual machines?"
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- Result: 0.5765 similarity to backup documentation
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- Interpretation: Correctly identifies semantic relationship between "snapshots" and "backups"
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**Infrastructure:**
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- Database: n8n_db on CT 113
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- Table: rag_embeddings (id, source_repo, file_path, chunk_text, embedding vector(768), metadata jsonb)
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- Embedding API: Ollama at 192.168.1.81:11434 (nomic-embed-text, 768 dimensions)
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- Storage overhead: ~3KB per vector, ~5KB per document total
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**Status:** ✅ Phase 3 Complete | Phase 4 Ready to Start
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**Next Steps:** Build n8n ingestion workflow to load homelab documentation from Gitea
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---
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### 2025-12-07: Infrastructure Documentation & Monitoring Stack
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#### Additions
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@@ -377,8 +501,9 @@ Hybrid approach balancing performance and resource efficiency:
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- Secure remote access without VPN
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3. **CT 113 (n8n)**: Workflow automation platform
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- PostgreSQL 15+ backend
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- IP: 192.168.2.107
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- PostgreSQL 16.11 backend (upgraded from 15+)
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- pgvector 0.8.1 extension for vector search
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- IP: 192.168.2.113
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- Resolved database locale issues
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### Modifications
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@@ -403,7 +528,19 @@ Hybrid approach balancing performance and resource efficiency:
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```
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homelab/
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monitoring/ # NEW: Monitoring stack configurations
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n8n/ # RAG Vector Search Implementation (NEW)
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vector_search.py # Production module for vector operations
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SESSION_HANDOFF_PHASE4_READY.md # Learning guide for next session
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PHASE3_COMPLETE.md # Phase 3 debugging and achievements summary
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fix_embedding_storage.py # Diagnostic script (embedding repair)
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test_direct_sql.py # Diagnostic script (query testing)
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test_vector_search_working.py # Validated working implementation
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test_parameter_binding.py # Diagnostic script (psycopg2 debugging)
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test_pgvector_direct.sql # Raw SQL tests for pgvector
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VECTOR_SEARCH_DEBUG.md # Technical debugging documentation
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VECTOR_SEARCH_COMPARISON.md # Before/after code comparison
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README_VECTOR_SEARCH.md # Comprehensive setup guide
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monitoring/ # Monitoring stack configurations
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README.md # Comprehensive monitoring documentation
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grafana/
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docker-compose.yml
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@@ -417,6 +554,8 @@ homelab/
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services/ # Docker Compose service configurations
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n8n/ # n8n workflow automation
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netbox/ # Network documentation & IPAM
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openclaw/ # OpenClaw AI chatbot gateway (VM 120)
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tinyauth/ # SSO authentication layer
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README.md # Services overview (updated)
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disaster-recovery/
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homelab-export-20251207-120040/ # Latest infrastructure export
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@@ -424,7 +563,16 @@ homelab/
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crawlers-exporters/ # Infrastructure collection scripts
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fixers/ # Problem-solving scripts
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qol/ # Quality of life improvements
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security/ # Security audit and remediation scripts (NEW)
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verify-service-status.sh
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backup-before-remediation.sh
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rotate-*.sh # Credential rotation scripts
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QUICK_REFERENCE.md # Security operations guide
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troubleshooting/
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SECURITY_AUDIT_2025-12-20.md # Comprehensive security assessment
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loki-stack-bugfix.md # Loki logging troubleshooting
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CLAUDE.md # AI assistant guidance (updated)
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SECURITY.md # Security policy and best practices (NEW)
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INDEX.md # Navigation index (updated)
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README.md # Repository overview (updated)
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CLAUDE_STATUS.md # This file - current infrastructure status
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@@ -454,7 +602,116 @@ homelab/
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---
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## Current Initiative: Security Audit Remediation - Q4 2025
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## Current Initiative: n8n RAG Workflow for Homelab Documentation - Q4 2025
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### Goal
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Build an interactive n8n workflow that implements Retrieval-Augmented Generation (RAG) to query homelab documentation stored in Gitea using local AI (Ollama). This is a learning-focused project to understand RAG architecture, embeddings, vector storage, and LLM integration.
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### Phase
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Phase 3 Complete - Vector Storage Operational | Moving to Phase 4 - n8n Workflow Development
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### Infrastructure Components
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- **AI Backend**: Ollama running on Windows 11 PC (192.168.1.81)
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- Hardware: AMD 7900 GRE GPU, i7-12700KF, 32GB RAM @ 4000MHz, 2TB NVMe
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- Installation: Native Windows application (not Docker)
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- Open-WebUI: Running in Docker Desktop on same machine (port 3000)
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- **Orchestrator**: n8n workflow automation (CT 113, 192.168.2.113)
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- **Data Source**: Gitea repositories (192.168.2.102:3060)
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- Repositories: homelab, truenas
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- **Vector Storage**: PostgreSQL 16.11 + pgvector 0.8.1 (operational on CT 113)
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### Progress Checklist
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**Phase 1: Network & Connectivity Setup**
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- [x] Verify Gitea API accessibility (working: http://192.168.2.102:3060/api/v1)
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- [x] Verify n8n instance running (CT 113, 192.168.2.113)
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- [x] Configure Ollama network binding (set OLLAMA_HOST=0.0.0.0 via environment variables)
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- [x] Verify Ollama API accessible from homelab (curl http://192.168.1.81:11434/api/tags)
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- [x] Identify available Ollama models (LLMs: deepseek-r1:8.2B, gpt-oss:20.9B, llama3.2:3.2B, phi3:3.8B)
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- [x] Pull embedding model (nomic-embed-text - 768 dimensions, 274MB)
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**Phase 2: Understanding Embeddings (Learning Phase)**
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- [x] Pull sample document from Gitea API
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- [x] Send text to Ollama for embedding generation
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- [x] Examine vector output (768-dimensional vectors for each text)
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- [x] Understand semantic similarity concept (cosine similarity demo: 0.5764 for related topics)
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**Phase 3: Vector Storage Implementation** ✅ COMPLETE
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- [x] Evaluate PostgreSQL + pgvector (uses existing n8n database)
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- [x] Evaluate Qdrant (lightweight Docker deployment)
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- [x] Choose storage backend based on learning goals (PostgreSQL + pgvector selected)
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- [x] Install pgvector extension on CT 113 (PostgreSQL 16.11, pgvector 0.8.1)
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- [x] Create rag_embeddings table with vector(768) column
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- [x] Debug and fix vector insertion (corrected string→vector conversion)
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- [x] Debug and fix ORDER BY issue (subquery approach working)
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- [x] Verify cosine similarity search (working: 0.5765 similarity for related concepts)
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- [x] Create production-ready vector_search.py module with insert/search/stats functions
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**Phase 4: Build Ingestion Workflow (n8n)** - READY TO START
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- [ ] Deploy vector_search.py production module to CT 113
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- [ ] Test manual document insertion via CLI
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- [ ] Implement text chunking strategy (500 char chunks, 100 char overlap)
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- [ ] Create minimal n8n workflow: Manual Trigger → Gitea API → Chunk → Ollama → PostgreSQL
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- [ ] Test workflow with single README.md file from homelab repo
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- [ ] Scale to process all .md files in homelab repository
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- [ ] Add error handling and deduplication logic
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- [ ] Schedule automated daily ingestion runs
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**Phase 5: Build Query Workflow (n8n)** - NOT STARTED
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- [ ] Create workflow: Webhook → User question
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- [ ] Generate embedding for user query
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- [ ] Implement vector similarity search (threshold >0.5)
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- [ ] Retrieve top 3-5 relevant chunks
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- [ ] Construct prompt with retrieved context
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- [ ] Call Ollama LLM for answer generation (llama3.2 or deepseek-r1)
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- [ ] Return formatted response with source references
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- [ ] Add webhook endpoint for external integrations
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### Context
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**RAG Architecture Overview:**
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1. **Ingestion Pipeline**: Gitea API → Text Chunking → Ollama Embeddings → Vector Database
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2. **Query Pipeline**: User Question → Embedding → Vector Search → Context Retrieval → LLM Generation → Answer
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**Phase 3 Achievements (2025-12-25):**
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- ✅ PostgreSQL + pgvector fully operational on CT 113
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- ✅ Vector search working with 0.5765 similarity for related concepts
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- ✅ Production-ready Python module (`vector_search.py`) with insert/search/stats functions
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- ✅ Debugged and resolved 2 critical issues:
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1. Embedding storage: Fixed psycopg2 parameter handling (must cast to `::vector(768)` in SQL, not Python)
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2. ORDER BY bug: Subquery approach works, CTE approach fails (use `ORDER BY similarity DESC` instead of vector operation)
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**Key Learnings:**
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- ✅ Embeddings convert text to 768-dimensional vectors representing semantic meaning
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- ✅ Vector databases enable semantic search (meaning-based, not keyword-based)
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- ✅ pgvector cosine distance operator (`<=>`) measures similarity: 0=identical, 2=opposite
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- ✅ Similarity scores: >0.7=highly relevant, 0.5-0.7=related, 0.3-0.5=somewhat related, <0.3=unrelated
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- ✅ psycopg2 doesn't natively support pgvector - must format vectors as strings and cast in SQL
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- ✅ Reusing vector parameters in ORDER BY causes silent failures - use subqueries instead
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**Technical Stack Validated:**
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- Ollama API (192.168.1.81:11434) ✅ Accessible across subnets
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- nomic-embed-text model ✅ 768 dimensions, fast generation
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- PostgreSQL 16.11 + pgvector 0.8.1 ✅ Operators working correctly
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- Python psycopg2 ✅ With workarounds for vector handling
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**Success Metrics - Phase 3:**
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- ✅ Successfully query "how to backup VM" and retrieve relevant homelab documentation (0.5765 similarity)
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- ✅ Understand each component of the vector storage pipeline
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- ✅ Create reusable Python module for n8n integration
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**Next Steps - Phase 4:**
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- Deploy vector_search.py to CT 113 and test CLI interface
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- Create text chunking function (500 char chunks, 100 char overlap)
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- Build minimal n8n workflow: Manual Trigger → Gitea API → Chunk → Ollama → PostgreSQL
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- Scale to process all .md files in homelab repository
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- Add error handling and deduplication logic
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**Session Handoff Document:** `/home/jramos/homelab/n8n/SESSION_HANDOFF_PHASE4_READY.md`
|
||||
**Learning Resources:** Step-by-step lessons with examples, mental models, troubleshooting guide
|
||||
|
||||
---
|
||||
|
||||
## Previous Initiative: Security Audit Remediation - Q4 2025
|
||||
|
||||
### Goal
|
||||
Remediate 31 security findings identified in comprehensive security audit (2025-12-20), addressing critical vulnerabilities in Docker socket exposure, credential management, and SSL/TLS configuration.
|
||||
@@ -632,16 +889,18 @@ Documentation & Maintenance
|
||||
- **Grafana**: http://192.168.2.114:3000
|
||||
- **Prometheus**: http://192.168.2.114:9090
|
||||
- **Nginx Proxy Manager**: http://192.168.2.101:81
|
||||
- **n8n**: http://192.168.2.107:5678
|
||||
- **n8n**: http://192.168.2.113:5678
|
||||
- **TinyAuth**: https://tinyauth.apophisnetworking.net (internal: http://192.168.2.10:8000)
|
||||
- **OpenClaw**: https://openclaw.apophisnetworking.net (internal: http://192.168.2.120:18789)
|
||||
|
||||
### Key Network Segments
|
||||
- **Management Network**: 192.168.2.0/24
|
||||
- **Proxmox Host**: 192.168.2.200
|
||||
- **Reverse Proxy**: 192.168.2.101 (CT 102)
|
||||
- **TinyAuth**: 192.168.2.10 (CT 115)
|
||||
- **n8n**: 192.168.2.107 (CT 113)
|
||||
- **n8n**: 192.168.2.113 (CT 113)
|
||||
- **Monitoring**: 192.168.2.114 (VM 101)
|
||||
- **OpenClaw**: 192.168.2.120 (VM 120)
|
||||
|
||||
---
|
||||
|
||||
@@ -726,5 +985,5 @@ Documentation & Maintenance
|
||||
**Maintained by**: jramos
|
||||
**Repository**: Homelab Infrastructure Configuration
|
||||
**Platform**: Proxmox VE 8.4.0
|
||||
**Infrastructure Scale**: 9 VMs, 2 Templates, 4 Containers
|
||||
**Current Status**: Operational - Home Automation Integration Deployed
|
||||
**Infrastructure Scale**: 10 VMs, 2 Templates, 5 Containers
|
||||
**Current Status**: Operational - OpenClaw Deployment In Progress
|
||||
Reference in New Issue
Block a user