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Reese Wells
2026-01-21 22:43:00 -05:00
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.gitignore vendored Normal file
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# Python-generated files
__pycache__/
*.py[oc]
build/
dist/
wheels/
*.egg-info
# Virtual environments
.venv

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3.10

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{
// Use IntelliSense to learn about possible attributes.
// Hover to view descriptions of existing attributes.
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "Python Debugger: Current File",
"type": "debugpy",
"request": "launch",
"program": "${file}",
"console": "integratedTerminal",
"args": [
"--message",
"You are an expert BTRFS system administrator. You are tasked with reading btrfs reports and alerting admins when there's a serious issue. Attached is a btrfs summary. If everything looks good reply with a short message saying as such. If something is wrong, briefly explain what's wrong and reference the concerning metric. Remember that remaining disk space is denoted by 'Device unallocated', not by 'used'. High used percentages (>95%) are expected and normal.",
"./example.txt"
]
}
]
}

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README.md Normal file
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# LLM Server Monitor
## summarize.sh
```bash
python post_llama.py --message "summarize this document" ./example.txt
```
## Prompts
```text
You are an expert BTRFS system administrator. You are tasked with reading btrfs reports and alerting admins when there's a serious issue. Attached is a btrfs summary. If everything looks good reply with a short message saying as such. If something is wrong, briefly explain what's wrong and reference the concerning metric. Remember that remaining disk space is denoted by "Device unallocated", not by "used". High used percentages (>95%) are expected and normal.
```

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example.txt Normal file
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Pool 0
Overall:
Device size: 34.57TiB
Device allocated: 22.82TiB
Device unallocated: 11.75TiB
Device missing: 0.00B
Device slack: 0.00B
Used: 22.75TiB
Free (estimated): 5.90TiB (min: 5.90TiB)
Free (statfs, df): 4.97TiB
Data ratio: 2.00
Metadata ratio: 2.00
Global reserve: 512.00MiB (used: 0.00B)
Multiple profiles: no
Data,RAID1: Size:11.38TiB, Used:11.35TiB (99.74%)
/dev/dm-10 5.43TiB
/dev/dm-15 3.62TiB
/dev/dm-9 7.00TiB
/dev/dm-5 286.00GiB
/dev/dm-6 284.00GiB
/dev/dm-8 3.88TiB
/dev/dm-4 2.27TiB
Metadata,RAID1: Size:27.00GiB, Used:21.15GiB (78.34%)
/dev/dm-10 15.00GiB
/dev/dm-15 10.00GiB
/dev/dm-9 12.00GiB
/dev/dm-8 8.00GiB
/dev/dm-4 9.00GiB
System,RAID1: Size:32.00MiB, Used:1.61MiB (5.03%)
/dev/dm-8 32.00MiB
/dev/dm-4 32.00MiB
Unallocated:
/dev/dm-10 1.83TiB
/dev/dm-15 1.83TiB
/dev/dm-9 2.08TiB
/dev/dm-5 1.54TiB
/dev/dm-6 1.54TiB
/dev/dm-8 1.57TiB
/dev/dm-4 1.36TiB
Pool 1
Overall:
Device size: 7.28TiB
Device allocated: 722.02GiB
Device unallocated: 6.57TiB
Device missing: 0.00B
Device slack: 0.00B
Used: 692.25GiB
Free (estimated): 3.30TiB (min: 3.30TiB)
Free (statfs, df): 2.56TiB
Data ratio: 2.00
Metadata ratio: 2.00
Global reserve: 512.00MiB (used: 0.00B)
Multiple profiles: no
Data,RAID1: Size:357.00GiB, Used:343.92GiB (96.34%)
/dev/dm-2 60.00GiB
/dev/dm-14 60.00GiB
/dev/dm-13 60.00GiB
/dev/dm-1 60.00GiB
/dev/dm-12 357.00GiB
/dev/dm-7 59.00GiB
/dev/dm-3 58.00GiB
Metadata,RAID1: Size:4.00GiB, Used:2.21GiB (55.25%)
/dev/dm-2 1.00GiB
/dev/dm-14 1.00GiB
/dev/dm-12 3.00GiB
/dev/dm-7 1.00GiB
/dev/dm-3 2.00GiB
System,RAID1: Size:8.00MiB, Used:80.00KiB (0.98%)
/dev/dm-7 8.00MiB
/dev/dm-3 8.00MiB
Unallocated:
/dev/dm-2 870.50GiB
/dev/dm-14 870.50GiB
/dev/dm-13 871.50GiB
/dev/dm-1 871.50GiB
/dev/dm-12 1.47TiB
/dev/dm-7 871.49GiB
/dev/dm-3 871.49GiB
Backup 0
Overall:
Device size: 16.37TiB
Device allocated: 14.42TiB
Device unallocated: 1.95TiB
Device missing: 0.00B
Device slack: 0.00B
Used: 14.37TiB
Free (estimated): 2.00TiB (min: 1.03TiB)
Free (statfs, df): 2.00TiB
Data ratio: 1.00
Metadata ratio: 2.00
Global reserve: 512.00MiB (used: 0.00B)
Multiple profiles: no
Data,single: Size:14.38TiB, Used:14.33TiB (99.64%)
/dev/mapper/luks-backup0-4ade71f9-e9fe-4a9c-84ea-12fc716626c1 14.38TiB
Metadata,DUP: Size:22.00GiB, Used:21.01GiB (95.51%)
/dev/mapper/luks-backup0-4ade71f9-e9fe-4a9c-84ea-12fc716626c1 44.00GiB
System,DUP: Size:8.00MiB, Used:1.52MiB (18.95%)
/dev/mapper/luks-backup0-4ade71f9-e9fe-4a9c-84ea-12fc716626c1 16.00MiB
Unallocated:
/dev/mapper/luks-backup0-4ade71f9-e9fe-4a9c-84ea-12fc716626c1 1.95TiB

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main.py Normal file
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def main():
print("Hello from llm-server-monitor!")
if __name__ == "__main__":
main()

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post_llama.py Executable file
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#!/usr/bin/env python3
"""
Post a message with an attached file (contents embedded in JSON) to an
OpenAI‑compatible API and echo the response.
Defaults:
• Server: https://llama-cpp.reeselink.com/v1/chat/completions
• Model : gpt-oss-120b
• No API key required (but can be supplied via --api-key)
"""
import argparse
import json
import sys
from pathlib import Path
import requests
# ----------------------------------------------------------------------
# Helper functions
# ----------------------------------------------------------------------
def load_file_text(path: Path) -> str:
"""Read the whole file as UTF‑8 text (fallback to binary → base64 if needed)."""
try:
return path.read_text(encoding="utf-8")
except UnicodeDecodeError:
# For non‑text files we fall back to a base64 representation.
import base64
return base64.b64encode(path.read_bytes()).decode("ascii")
def build_payload(
model: str,
user_message: str,
file_content: str,
file_name: str,
) -> dict:
"""
Construct the JSON body expected by the OpenAI chat completions endpoint.
The “file attachment” is modeled as an extra user‑role message that contains
the file name and its contents. This mirrors the way many front‑ends embed
files in the conversation history.
"""
# Primary user message (the prompt you want the model to answer)
messages = [{"role": "user", "content": user_message}]
# Add a second message that represents the attached file.
# The format is arbitrary – you can change it to suit your downstream model.
file_message = (
f"[Attached file: {file_name}]\n"
f"{file_content}"
)
messages.append({"role": "user", "content": file_message})
return {
"model": model,
"messages": messages,
# Optional parameters – feel free to expose them as CLI args later.
"temperature": 0.7,
"max_tokens": 1024,
}
def post_chat_completion(
endpoint: str,
payload: dict,
api_key: str | None = None,
) -> requests.Response:
"""POST the JSON payload to the API and return the raw response."""
headers = {"Content-Type": "application/json"}
if api_key:
headers["Authorization"] = f"Bearer {api_key}"
response = requests.post(endpoint, headers=headers, json=payload, timeout=300)
response.raise_for_status() # raise an exception for HTTP errors
return response
# ----------------------------------------------------------------------
# CLI entry point
# ----------------------------------------------------------------------
def main() -> None:
parser = argparse.ArgumentParser(
description="Send a message + file contents to an OpenAI‑compatible API."
)
parser.add_argument(
"file",
type=Path,
help="Path to the file whose contents will be sent in the payload.",
)
parser.add_argument(
"-m",
"--message",
default="Please analyse the attached file.",
help="User message to send alongside the file.",
)
parser.add_argument(
"--model",
default="gpt-oss-120b",
help="Model name to request (default: %(default)s).",
)
parser.add_argument(
"--api-key",
default=None,
help="Optional API key; omit if the server does not require authentication.",
)
parser.add_argument(
"--url",
default="https://llama-cpp.reeselink.com/v1/chat/completions",
help="Base URL of the OpenAI‑compatible endpoint (default: %(default)s).",
)
args = parser.parse_args()
# ------------------------------------------------------------------
# Read file and build request
# ------------------------------------------------------------------
if not args.file.is_file():
sys.exit(f"Error: '{args.file}' does not exist or is not a regular file.")
file_content = load_file_text(args.file)
payload = build_payload(
model=args.model,
user_message=args.message,
file_content=file_content,
file_name=args.file.name,
)
# ------------------------------------------------------------------
# Send request
# ------------------------------------------------------------------
try:
resp = post_chat_completion(endpoint=args.url, payload=payload, api_key=args.api_key)
except requests.RequestException as exc:
sys.exit(f"Request failed: {exc}")
# ------------------------------------------------------------------
# Echo the response (pretty‑print JSON if possible)
# ------------------------------------------------------------------
try:
json_resp = resp.json()
print(json.dumps(json_resp["choices"][0]["message"]["content"], indent=2, ensure_ascii=False))
except ValueError:
# Not JSON – just dump raw text
print(resp.text)
if __name__ == "__main__":
main()

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pyproject.toml Normal file
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[project]
name = "llm-server-monitor"
version = "0.1.0"
description = "Add your description here"
readme = "README.md"
requires-python = ">=3.10"
dependencies = [
"requests>=2.32.5",
"types-requests>=2.32.4.20260107",
]

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