genie-npu-ir20

name	genie-npu-ir20
description	Route text generation to the ir20 Windows ARM64 laptop node running GenieAPIService with OpenAI-compatible endpoints over Tailscale mesh. Use when GoatCitadel needs local/private inference, NPU-backed generation, or a mesh compute target via the ir20 node's /v1/chat/completions API.
metadata	{"version":"0.1.0","tags":["inference","npu","mesh","openai-compat"],"tools":["http.get","http.post"],"keywords":["genie","npu","ir20","local inference","mesh compute","openai api","ibm granite","tailscale"]}

Genie NPU Node (ir20)

OpenAI-compatible text generation via a Windows ARM64 laptop node running GenieAPIService (FastAPI/Uvicorn) over Tailscale mesh.

Use this skill when:

• GoatCitadel needs local/private inference that stays on your devices and mesh
• NPU-backed generation is preferred (when available on ir20)
• Another GoatCitadel node needs a mesh compute target for text generation

Do not use this skill when:

• The task requires image generation (ir20 endpoints are probe-only for images)
• Low latency from a cloud provider is more appropriate
• The ir20 node is offline or unreachable

Node Identity

• Node name: ir20
• Service: GenieAPIService
• Port: 8910
• Base path: /v1
• Observed models (from GET /v1/models):
  • IBM-Granite
  • IBM-Granite-v3.1-8B

---

Connection addresses (priority order)

Pick the first that works.

1. Tailscale IP (preferred for mesh):
   http://100.64.0.4:8910/v1

2. Tailscale MagicDNS hostname (if enabled):
   http://ir20:8910/v1

3. LAN IP (same Wi‑Fi/LAN only):
   http://192.168.0.108:8910/v1

Notes

• The service binds to 0.0.0.0:8910 on the laptop (so LAN + Tailscale can reach it).
• Recommended Windows Firewall rule: allow inbound only from Tailscale range 100.64.0.0/10.

---

What the endpoints are (and what they’re for)

Text endpoints (the important ones)

• GET /v1/models
  Returns available model IDs.
• POST /v1/chat/completions
  Main “Chat Completions” endpoint (supports streaming via SSE).
• POST /v1/completions
  Sometimes exists as an alias/compat endpoint. Prefer /v1/chat/completions.

Image endpoints (likely “best effort”)

Swagger/OpenAPI may list:

• POST /v1/images/generations
• POST /images/generations

These are meant for image generation (like “DALL·E style” APIs). On this node, they may be present in OpenAPI but not actually wired to a working image model. Treat them as probe-only: try it, and if it errors, route image generation to another provider/node.

---

Health checks

1) Basic “alive” check (fast)

GET {base}/models

Expected:

• HTTP 200
• JSON body containing model list
• Should respond quickly

2) Functional “can it generate text” check (strict)

POST {base}/chat/completions with a tiny request (max_tokens small).

---

Request format

Chat Completions request schema (practical)

Most requests look like this:

{
  "model": "IBM-Granite",
  "stream": false,
  "messages": [
    { "role": "user", "content": "Reply with exactly: pong" }
  ],
  "temperature": 0,
  "max_tokens": 3
}

Parameters that typically work

• model (string): one of the IDs from /v1/models
• messages (array): {role, content} chat messages
  • roles: system, user, assistant
• stream (bool): true for SSE streaming, false for one-shot
• temperature (number): randomness
• max_tokens (int): keep small for control tests
• top_p (number): nucleus sampling (if supported)
• top_k (int): top‑k sampling (if supported)

Schema mismatch note: temp vs temperature

Some Genie/OpenAPI screens show temp while many OpenAI clients use temperature. You already verified temperature works via Invoke-RestMethod. If a client requires temp, use it as a fallback:

{ "temp": 0.2 }

If both are present, prefer temperature unless Genie errors.

---

Streaming format (SSE)

When stream: true, responses arrive like:

data: { ... "object":"chat.completion.chunk", ... }
data: { ... }
data: [DONE]

Each chunk contains partial text under something like:

• choices[0].delta.content

Implementation tip:

• Concatenate delta.content fields until you see [DONE].

---

PowerShell: common gotchas and working patterns

1) The colon : interpolation trap

In PowerShell, this can break:

$base = "http://$ip:8910/v1"   # ❌ sometimes parses weird

Use either:

$base = "http://$($ip):8910/v1"
# or
$base = "http://{0}:8910/v1" -f $ip

2) The “file didn’t get created” trap

A here-string by itself only prints. You must pipe it to a file:

@'
hello
'@ | Set-Content -Path .\skill.md -Encoding utf8

3) UTF-8 console output (fix weird characters like âï¸)

chcp 65001
[Console]::OutputEncoding = [System.Text.Encoding]::UTF8

---

Working PowerShell examples

Models list

$base = "http://100.64.0.4:8910/v1"
curl.exe -s "$base/models"

One-shot chat completion (Invoke-RestMethod)

$base = "http://100.64.0.4:8910/v1"

$body = @{
  model="IBM-Granite"
  stream=$false
  messages=@(@{ role="user"; content="Reply with exactly: pong" })
  temperature=0
  max_tokens=3
} | ConvertTo-Json -Depth 10

$resp = Invoke-RestMethod -Method Post -Uri ($base + "/chat/completions") `
  -ContentType "application/json" -Body $body

$resp.choices[0].message.content

Streaming (curl SSE)

$base = "http://100.64.0.4:8910/v1"

$payloadPath = "$env:TEMP\genie_stream.json"
@{
  model="IBM-Granite"
  stream=$true
  messages=@(@{ role="user"; content="Count 1 to 10, each on a new line." })
  temperature=0.2
} | ConvertTo-Json -Depth 10 | Set-Content -Encoding utf8 -NoNewline $payloadPath

curl.exe -N -s -X POST ($base + "/chat/completions") `
  -H "Content-Type: application/json" `
  --data-binary "@$payloadPath"

---

Python examples (for GoatCitadel integrations / adapters)

A) Plain HTTP (no OpenAI SDK)

import requests

BASE = "http://100.64.0.4:8910/v1"

payload = {
  "model": "IBM-Granite",
  "stream": False,
  "messages": [{"role": "user", "content": "Reply with exactly: pong"}],
  "temperature": 0,
  "max_tokens": 3,
}

r = requests.post(f"{BASE}/chat/completions", json=payload, timeout=30)
r.raise_for_status()
print(r.json()["choices"][0]["message"]["content"])

B) OpenAI Python SDK pointing at Genie (works if the endpoint is compatible)

If GoatCitadel uses the OpenAI SDK pattern, set:

• base_url to Genie
• api_key to any dummy string (if Genie doesn’t enforce auth)

from openai import OpenAI

client = OpenAI(
  base_url="http://100.64.0.4:8910/v1",
  api_key="local-no-auth",
)

resp = client.chat.completions.create(
  model="IBM-Granite",
  messages=[{"role": "user", "content": "Reply with exactly: pong"}],
  temperature=0,
  max_tokens=3,
)
print(resp.choices[0].message.content)

If the SDK complains about unsupported fields, fall back to the plain HTTP method.

---

GoatCitadel usage guidance (how to route work here)

When GoatCitadel needs text generation, it should:

1. Choose base URL in this order:
   • http://100.64.0.4:8910/v1
   • http://ir20:8910/v1
   • http://192.168.0.108:8910/v1
2. Call GET /models (cache for a short time, e.g., 60 seconds)
3. Prefer IBM-Granite unless explicitly asked for IBM-Granite-v3.1-8B
4. Use POST /chat/completions with:
   • stream: false for short tool calls / structured answers
   • stream: true for long-form interactive output

Recommended defaults for stable agent behavior

• temperature: 0.0 to 0.3
• max_tokens: small for “tool-ish” calls, larger for writing tasks
• Consider enforcing “less chatty” behavior with a system message:
  • “Follow instructions exactly. Output only what’s requested.”

---

Security posture (recommended)

• Prefer allowing inbound 8910 only from Tailscale:
  • RemoteAddress: 100.64.0.0/10
• Avoid exposing 8910 to the public internet.
• If you later want authenticated access:
  • Put a reverse proxy in front (Tailscale Serve / Caddy / Traefik) with auth.
  • Or implement an API key check in GenieAPIService.

---

Troubleshooting quick hits

Port bind error: WinError 10048

Meaning: something else already owns 8910.

Find it:

Get-NetTCPConnection -LocalPort 8910 -State Listen | Select-Object -First 1 | Format-List

Kill the owning PID (careful):

$pid = (Get-NetTCPConnection -LocalPort 8910 -State Listen | Select-Object -First 1).OwningProcess
Stop-Process -Id $pid -Force

Invoke-RestMethod returns weird truncated objects

PowerShell sometimes formats nested objects oddly. For inspection:

$resp | ConvertTo-Json -Depth 50

---

Capability summary

✅ Confirmed working:

• /v1/models
• /v1/chat/completions (non-stream)
• /v1/chat/completions (stream via SSE)

⚠️ Present but not guaranteed:

• image generation endpoints

---

Execution Pipeline

1. Select base URL in priority order (Tailscale IP -> MagicDNS -> LAN)
2. Health check via GET /v1/models - confirm HTTP 200 and model list
3. Choose model (IBM-Granite default, IBM-Granite-v3.1-8B if requested)
4. Send POST /v1/chat/completions with stream: false for tool calls, stream: true for interactive output
5. For streaming, concatenate choices[0].delta.content until [DONE]
6. If connection fails, fall back to next base URL or route to another provider

Future Extension (Planned)

This skill currently hardcodes ir20 details. Later you can generalize by:

• Discovering nodes via mesh registry
• Probing /v1/models to detect capability
• Selecting nodes by latency/cost/availability