From f45c5dcbd39ef8910baf8e94913bc0f69e95ab07 Mon Sep 17 00:00:00 2001
From: Atlas <atlas@aipa.local>
Date: Fri, 10 Apr 2026 18:28:16 -0700
Subject: [PATCH] =?UTF-8?q?Update:=20ATLAS/Infrastructure/Infrastructure-P?=
 =?UTF-8?q?FI-Project-Index.md=20=E2=80=94=20Adding=20inference-hardware-p?=
 =?UTF-8?q?rofile.sh=20to=20scripts=20listing=20and=20noting=20that=20phys?=
 =?UTF-8?q?ical=20GPU=20model/VRAM=20are=20currently=20undocumented=20?=
 =?UTF-8?q?=E2=80=94=20the=20new=20script=20should=20be=20run=20on=20VM=20?=
 =?UTF-8?q?102=20to=20capture=20this=20gap.?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 .../Infrastructure-PFI-Project-Index.md       | 76 +++++++++++++++----
 1 file changed, 63 insertions(+), 13 deletions(-)

diff --git a/ATLAS/Infrastructure/Infrastructure-PFI-Project-Index.md b/ATLAS/Infrastructure/Infrastructure-PFI-Project-Index.md
index efa1397..7fdd07b 100644
--- a/ATLAS/Infrastructure/Infrastructure-PFI-Project-Index.md
+++ b/ATLAS/Infrastructure/Infrastructure-PFI-Project-Index.md
@@ -2,20 +2,23 @@
 created: '2026-04-10T17:35:04+00:00'
 id: 850d5cfb-1b10-42cb-a3ad-fe4066c8cb17
 keywords:
-- PFI
-- Tailscale VPN
-- Proxmox VE
-- Docker Compose
+- docker
+- vm
+- full
+- project
+- chromadb
+- models
+- model
+- reference
+- compose.yaml
+- vcpu
+- gb
+- gpu
+- network
 - llama-swap
-- ChromaDB
-- ComfyUI
-- VibeVoice
-- Parakeet STT
-- VM startup order
-- GPU acceleration
-- vector database
+- 'yes'
 links: []
-modified: '2026-04-10T17:35:04+00:00'
+modified: '2026-04-11T01:28:16+00:00'
 summary: Comprehensive architecture reference for the Infrastructure-PFI project covering
   three Tailscale-linked sites, 11 Proxmox VMs at PFI-ANA colo, 6 Docker services
   with GPU workloads, and llama-swap model management across 20 models.
@@ -95,7 +98,8 @@ Infrastructure-PFI/
 │   ├── setup-chromadb.sh                  # Deploy ChromaDB on VM 102
 │   ├── backup-chromadb.sh                 # Hot backup with 30-day retention
 │   ├── health-check-chromadb.sh           # Health monitoring with alerting
-│   └── quickstart-chromadb.sh             # One-command ChromaDB setup wrapper
+│   ├── quickstart-chromadb.sh             # One-command ChromaDB setup wrapper
+│   └── inference-hardware-profile.sh      # ⚠️ NEW — Hardware profiler for AI/ML inference planning (VM 102)
 └── output/                                # Generated output and logs (empty)
 ```
 
@@ -187,6 +191,51 @@ The llama-swap gateway manages **20 GGUF models** across multiple categories:
 
 ---
 
+## Scripts Reference
+
+### ChromaDB Scripts (VM 102)
+| Script | Purpose |
+|---|---|
+| `setup-chromadb.sh` | Deploy ChromaDB container on VM 102 |
+| `backup-chromadb.sh` | Hot backup with 30-day retention |
+| `health-check-chromadb.sh` | Health monitoring with alerting |
+| `quickstart-chromadb.sh` | One-command ChromaDB setup wrapper |
+
+### Utility Scripts
+| Script | Purpose |
+|---|---|
+| `nemotron-query.sh` | Bash client for querying Nemotron via llama-swap API |
+| `inference-hardware-profile.sh` | **NEW** — Comprehensive hardware profiler for AI/ML inference planning |
+
+### inference-hardware-profile.sh
+
+**Target Host:** VM 102 (ana-ml2) at `10.250.50.54` — PFI-ANA Colo
+
+A comprehensive system hardware profiler designed for AI/ML inference capacity planning. Captures the full hardware picture needed to evaluate and optimize GPU inference workloads.
+
+**What it gathers:**
+- System info (OS, kernel, uptime)
+- CPU details (model, cores, threads, clock speed, scaling governor)
+- Memory (total, available, used, swap)
+- Disk storage (all mounts)
+- GPU resources (model, VRAM, utilization, power, temperature, PCIe, clock speeds, throttling, ECC, active processes, MIG mode)
+- Docker container stats (CPU/memory per container)
+- Inference software stack (Python, PyTorch, CUDA, cuDNN, llama.cpp, Ollama, vLLM)
+- Estimated model capacity based on free VRAM (Q4, Q8, FP16)
+- Inference readiness score with actionable recommendations
+
+**Output modes:**
+| Flag | Output |
+|---|---|
+| *(default)* | Full colored terminal report |
+| `--json` | Machine-readable JSON |
+| `--quick` | One-line summary |
+| `--gpu-only` | Full report without Docker sections |
+
+> **⚠️ Action needed:** This script should be run on VM 102 to capture the **physical GPU model, VRAM capacity, and host hardware specs**, which are currently undocumented in this project. The output (especially `--json`) should be saved to close the hardware documentation gap.
+
+---
+
 ## Known Issues & Observations
 
 1. **Nemotron Super** uses `--n-gpu-layers 99` instead of 999 — likely configured to reserve VRAM for other tasks
@@ -194,6 +243,7 @@ The llama-swap gateway manages **20 GGUF models** across multiple categories:
 3. **Granite 4 Small** has `ttl: 0` (persistent caching) but is not assigned to the utility group
 4. **Parakeet STT** references `.env` configuration not tracked in version control
 5. **Qwen3-Coder-Next** download may be incomplete — `.incomplete` files present on disk
+6. **Physical GPU model and VRAM undocumented** — the physical GPU passed through to VM 102 (its model, total VRAM, PCIe slot, etc.) is not recorded anywhere in project documentation. Run `inference-hardware-profile.sh --json` on VM 102 and save the output to close this gap.
 
 ---