Compare commits

...

12 Commits

Author SHA1 Message Date
29c1a69592 feat(docker): add QEMU cross-compilation support
Add QEMU user-mode emulation for building aarch64 images (uConsole CM5):
- qemu-user-static: Static QEMU binaries for user-mode emulation
- binfmt-support: Linux kernel support for recognizing binary formats
- qemu-user-binfmt: Registers QEMU handlers with binfmt_misc

Enables cross-compilation of NixOS configurations for ARM devices
from the x86_64 Hermes container.

This is PR 4 of 5 for Docker package additions.
Depends on PR #10, #11, and #12.
2026-04-29 21:00:44 +00:00
30f8ca3863 Add AI model optimizer cron job draft and initial state files 2026-04-28 17:19:45 +00:00
7efba3ac5b Compose update 2026-04-27 06:11:34 -04:00
Robert
cf1373cd68 Forced restart for docker services 2026-04-27 06:02:25 -04:00
Robert
bc875ef9fb feat: isolate docker networks and add cyt-pi remote node config
- Refactor all 12 compose stacks to use isolated networks with Traefik as the hub
- Add openclaw-ssh sidecar to ai stack for reverse tunneling (port 2425)
- Add sshnode entrypoint to Traefik configuration
- Add cyt-pi host configuration for Pi Zero 2 W (headless)
- Include kismet and target_detector_cli services for remote Wi-Fi monitoring
- Add reverse SSH tunnel service via autossh
2026-04-06 19:14:57 -04:00
Robert
c579b07843 fix: read gateway token from secret file via bash 2026-04-04 17:49:39 -04:00
Robert
d3f50cdadc fix: always restart node service on exit 2026-04-04 17:43:03 -04:00
Robert
8aa85e62e5 feat: add openclaw CLI to system packages 2026-04-04 17:23:15 -04:00
Robert
b9cf8a47f7 fix: set openclaw secret group to ai-worker 2026-04-04 17:15:24 -04:00
Robert
2e749228bb fix: set correct working directory and create home for ai-worker 2026-04-04 17:07:13 -04:00
Robert
ce20fad4d3 fix: enable flake-self-attrs for lix compatibility 2026-04-04 16:54:10 -04:00
Robert
401b23ce46 feat: add openclaw node service and migrate to lix
- Add headless openclaw node systemd service for host execution
- Migrate from nix to lix package manager
- Permit openclaw-2026.3.12 (insecure package warning)
- Use ai-worker user for node service
2026-04-04 16:26:33 -04:00
20 changed files with 1123 additions and 43 deletions

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# AI Model Optimization Cron Job - EXECUTION PROMPT
**When this cron runs, follow these instructions exactly:**
---
## Your Role
You are an AI model optimization agent. Your task is to find the best ollama/llama.cpp configuration for maximum context size and hardware utilization.
**Hardware:**
- 2× AMD MI50 GPUs (32GB VRAM each, 64GB total)
- 128GB system RAM
- ROCm: HSA_OVERRIDE_GFX_VERSION=9.0.6, HIP_VISIBLE_DEVICES=0,1
---
## File Locations
```
STATE: /opt/data/infra/assets/ai-optimizer/state.json
RESULTS: /opt/data/infra/assets/ai-optimizer/results.csv
INFRA_REPO: /opt/data/infra
```
---
## Model Queues
### GPU Track (Coding - prioritize speed + context on GPU)
1. `devstral-small-2:24b`
2. `qwen2.5-coder:32b`
3. `codellama:34b-instruct`
### RAM Track (Knowledge - prioritize max context)
1. `qwen2.5:72b`
2. `nemotron-3-nano:30b`
3. `mixtral:8x7b-instruct`
---
## Context Steps (in order)
```
[32768, 65536, 98304, 131072, 163840, 200704, 262144, 327680]
```
---
## Each Run - Step by Step
### 1. Read State
```bash
cd /opt/data/infra
cat assets/ai-optimizer/state.json
```
### 2. Determine Next Test
- Read `track` (gpu or ram)
- Read `current_model` from queue at `model_index`
- Read `current_config` for parameters to test
- Select next context step from `context_steps` based on `phase`
### 3. Pull Model (if needed)
```bash
docker exec ollama ollama list | grep -q "<model>" || docker exec ollama ollama pull <model>
```
### 4. Create Test Modelfile
```bash
docker exec ollama bash -c "cat <<EOF > /root/.ollama/test_${model}.modelfile
FROM ${model}
PARAMETER num_ctx ${current_config.num_ctx}
PARAMETER num_gpu ${current_config.num_gpu}
PARAMETER flash_attn ${current_config.flash_attn}
PARAMETER num_predict 4096
PARAMETER num_keep 1024
PARAMETER repeat_penalty 1.1
EOF"
docker exec ollama ollama create test-model -f /root/.ollama/test_${model}.modelfile
```
### 5. Run Benchmark
```bash
# Warm up
docker exec ollama ollama run test-model "Hello" > /dev/null
# Coding prompt
START=$(date +%s%N)
docker exec ollama ollama run test-model "Write a Python async context manager that retries a function with exponential backoff, max 5 retries, and logs each attempt using structlog. Include type hints."
END=$(date +%s%N)
# Calculate tokens/sec from output
```
### 6. Measure VRAM (if possible)
```bash
# Try host first
rocm-smi --showmeminfo vram 2>/dev/null || \
# Try via docker
docker exec --privileged ollama rocm-smi --showmeminfo vram 2>/dev/null || \
# Fallback
echo "VRAM measurement unavailable"
```
### 7. Record Results
- Parse tokens/sec from ollama output
- Record VRAM/RAM usage
- Determine if this is best config so far for this model
- Update `best_configs` if tokens/sec improved or context increased
### 8. Update State
```python
# Logic:
if test_successful:
if context_step < max_reached:
phase = "context_scaling"
current_config.num_ctx = next_context_step
else:
# Move to next model
model_index += 1
phase = "context_scaling"
current_config.num_ctx = context_steps[0]
else:
# OOM or error - record last good as best
best_configs[track][current_model] = last_good_config
model_index += 1
phase = "context_scaling"
```
### 9. Commit to Repo
```bash
cd /opt/data/infra
git add assets/ai-optimizer/
git commit -m "ai-optimizer: tested ${model} at ${num_ctx} ctx - ${status}"
git push origin master
```
### 10. Matrix Notification (if available)
```python
import os
if os.getenv("MATRIX_HOME_SERVER") and os.getenv("MATRIX_ACCESS_TOKEN"):
# Send notification to Matrix room
# Room ID from env or config
pass
# Else: silent
```
---
## Stop Conditions
1. All models in both queues have `best_configs` recorded
2. Manual intervention needed (error in state.json `error` field)
3. No progress for 3 consecutive runs (stuck)
---
## Error Handling
If any step fails:
1. Log error to state.json: `"error": {"message": "...", "timestamp": "..."}`
2. Do NOT increment model_index (retry next run)
3. Commit state with error field
4. Exit gracefully
---
## Important Notes
- **No num_parallel**: Do not use this parameter
- **Two tracks**: Complete GPU track first, then RAM track
- **Backend**: Start with ollama, llama.cpp testing is optional (requires uncommenting in compose.yml)
- **Host access**: Some commands need host - use docker exec or SSH if available
- **Ask before deploy**: If config changes needed in NixOS modules, show diff and wait for user confirmation before `nh os switch`
---
## Example State Transitions
**Start:**
```json
{"track": "gpu", "model_index": 0, "current_model": "devstral-small-2:24b", "current_config": {"num_ctx": 32768, ...}}
```
**After successful test at 32k:**
```json
{"track": "gpu", "model_index": 0, "current_model": "devstral-small-2:24b", "current_config": {"num_ctx": 65536, ...}}
```
**After OOM at 131k:**
```json
{
"track": "gpu",
"model_index": 1,
"current_model": "qwen2.5-coder:32b",
"best_configs": {
"gpu": {
"devstral-small-2:24b": {"num_ctx": 98304, "num_gpu": 99, "tokens_per_sec": 11.2}
}
}
}
```

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# AI Model Optimization Cron Job
**Goal:** Find optimal configurations for maximum context size with full hardware utilization.
**Hardware:**
- 2× AMD MI50 GPUs (32GB VRAM each, 64GB total)
- 128GB system RAM
- ROCm: HSA_OVERRIDE_GFX_VERSION=9.0.6, HIP_VISIBLE_DEVICES=0,1
---
## Model Queue
### GPU-Optimized (Coding - prioritize speed + context on GPU)
1. `devstral-small-2:24b` - Best coding model
2. `qwen2.5-coder:32b` - Strong coder, fits on GPU+offload
3. `codellama:34b-instruct` - Legacy but solid
### RAM-Optimized (Knowledge - prioritize max context, accept slower)
1. `qwen2.5:72b` - Best knowledge, needs heavy offload
2. `nemotron-3-nano:30b` - Good general knowledge
3. `mixtral:8x7b-instruct` - MoE, efficient for knowledge
---
## Optimization Strategy
**Two separate tracks:**
### Track A: GPU-Focused (Coding)
```
Baseline: num_ctx=32768, num_gpu=99, flash_attn=true
Steps:
1. Increase context: 32k → 65k → 98k → 131k → 163k
2. At each step, verify VRAM usage < 60GB (leave headroom)
3. If OOM: reduce num_gpu until stable, record best
4. Measure tokens/sec - if < 5 tok/s, consider context too high
```
### Track B: RAM-Focused (Knowledge)
```
Baseline: num_ctx=65536, num_gpu=50, flash_attn=true
Steps:
1. Increase context: 65k → 131k → 200k → 262k → 327k
2. Allow heavy RAM offload (system RAM up to 100GB)
3. If OOM: reduce context or num_gpu
4. Speed less critical - focus on max stable context
```
---
## Backend-Specific Configs
### Ollama (Modelfile parameters)
```
PARAMETER num_ctx <value>
PARAMETER num_gpu <layers>
PARAMETER flash_attn true/false
PARAMETER num_predict 4096
PARAMETER num_keep 1024
PARAMETER repeat_penalty 1.1
```
### Llama.cpp (CLI flags)
```
--ctx-size <value>
--n-gpu-layers <layers>
--flash-attn on/off
--n-predict 4096
--batch-size 4096
--ubatch-size 512
--cache-type-k f16
--cache-type-v f16
--split-mode layer
--no-mmap
```
---
## Host Test Instructions
**The cron runs inside the hermes container. Some tests require host access:**
### 1. VRAM Monitoring (HOST)
```bash
# Run on host to check VRAM usage during/after benchmark
sudo rocm-smi --showmeminfo vram
# Or via docker exec if rocm-smi available in container
docker exec --privileged ollama rocm-smi --showmeminfo vram
```
### 2. Running Ollama Benchmarks (CONTAINER)
```bash
# Pull model
docker exec ollama ollama pull <model>
# Create custom modelfile
docker exec ollama bash -c 'cat <<EOF > /root/.ollama/test.modelfile
FROM <model>
PARAMETER num_ctx 65536
PARAMETER num_gpu 99
PARAMETER flash_attn true
EOF'
# Create model from modelfile
docker exec ollama ollama create test-model -f /root/.ollama/test.modelfile
# Run benchmark (warm model first)
docker exec ollama ollama run test-model "Write a Python async context manager with exponential backoff"
# Cleanup
docker exec ollama ollama rm test-model
```
### 3. Running Llama.cpp Benchmarks (CONTAINER - needs llama.cpp container)
```bash
# Uncomment llama_cpp_devstral in compose.yml first
# Then rebuild: sudo nh os switch --flake .#lazyworkhorse
# Test via HTTP API
curl http://localhost:8300/v1/completions \
-H "Content-Type: application/json" \
-d '{
"model": "devstral-2-small-llama_cpp",
"prompt": "Write a Python function",
"max_tokens": 100
}'
```
### 4. Deploying Changes (HOST via ai-worker)
```bash
# After optimization, commit results
cd /home/ai-worker/infra
git add assets/ai-optimizer/
git commit -m "ai-optimizer: new best config for <model>"
git push
# If config changes needed in ollama_init_custom_models.nix:
# 1. Edit the file
# 2. nixpkgs-fmt .
# 3. Show diff to user
# 4. Wait for confirmation
# 5. sudo nh os switch --flake .#lazyworkhorse
```
### 5. Accessing Host from Hermes Container
```bash
# SSH to host as ai-worker (key should be mounted)
ssh -i /path/to/key ai-worker@host.docker.internal
# Or via docker socket if mounted
# (not recommended for security)
```
---
## Benchmark Prompts
### Coding (Track A)
```
"Write a Python async context manager that retries a function with exponential backoff, max 5 retries, and logs each attempt using structlog. Include type hints and error handling."
```
### Knowledge (Track B)
```
"Explain the complete memory hierarchy in modern GPUs, from registers through L1/L2 caches to VRAM, and how data moves between them during matrix multiplication. Include bandwidth considerations for each level."
```
### Measurement
- Tokens per second (generation speed)
- Time to first token (latency)
- VRAM usage (via rocm-smi)
- System RAM usage (via free -h)
- Context success (did it complete without OOM?)
---
## State File Structure
`/opt/data/infra/assets/ai-optimizer/state.json`
```json
{
"track": "gpu",
"current_model": "devstral-small-2:24b",
"model_index": 0,
"phase": "context_scaling",
"backend": "ollama",
"current_config": {
"num_ctx": 65536,
"num_gpu": 99,
"flash_attn": true
},
"best_configs": {
"gpu": {
"devstral-small-2:24b": {
"backend": "ollama",
"num_ctx": 131072,
"num_gpu": 99,
"flash_attn": true,
"tokens_per_sec": 12.5,
"vram_used_gb": 58.2,
"tested_at": "2026-04-28T17:00:00Z"
}
},
"ram": {}
},
"completed_models": [],
"gpu_queue": ["devstral-small-2:24b", "qwen2.5-coder:32b", "codellama:34b-instruct"],
"ram_queue": ["qwen2.5:72b", "nemotron-3-nano:30b", "mixtral:8x7b-instruct"]
}
```
---
## Results CSV
`/opt/data/infra/assets/ai-optimizer/results.csv`
```csv
timestamp,track,model,backend,phase,num_ctx,num_gpu,flash_attn,tokens_per_sec,vram_gb,ram_gb,status,is_best
2026-04-28T17:00:00Z,gpu,devstral-small-2:24b,ollama,context_scaling,65536,99,true,15.2,52.1,18.4,success,false
```
---
## Cron Job Flow
```
1. Read state.json
2. If both queues empty → STOP (all models tested)
3. Select next model from current track queue
4. Pull model if needed (docker exec ollama ollama pull)
5. Create Modelfile / llama.cpp config with current test params
6. Run benchmark (both prompts)
7. Measure: tokens/sec, VRAM (rocm-smi), RAM (free -h)
8. If successful:
- Increase context (next step)
- Update current_config in state
9. If OOM/error:
- Record last good config as best_configs[track][model]
- Move to next model in queue
10. Update state.json
11. Append to results.csv
12. Git commit + push to /opt/data/infra
13. Send Matrix notification if available, else silent
```
---
## Matrix Notification (Optional)
```python
# If matrix credentials available in environment
if os.getenv("MATRIX_HOME_SERVER") and os.getenv("MATRIX_ACCESS_TOKEN"):
# Send completion notification
# Room: !ai-optimizer:lazyworkhorse.net (or similar)
pass
# Else: silent, just commit
```
---
## Files to Create
```
/opt/data/infra/assets/ai-optimizer/
├── state.json # Current progress
├── results.csv # All test results
├── best_configs.json # Final best configs (human-readable)
└── CRON_JOB_DRAFT.md # This file
```
---
## Notes
- **No num_parallel**: Removed to avoid limiting other settings
- **Two tracks**: GPU (coding/speed) vs RAM (knowledge/context)
- **Both backends**: Test ollama first, then llama.cpp if available
- **Host tests**: rocm-smi must run on host or privileged container
- **Deploy**: ai-worker has sudo for nh/nixos-rebuild, must ask user first

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timestamp,track,model,backend,phase,num_ctx,num_gpu,flash_attn,tokens_per_sec,vram_gb,ram_gb,status,is_best
1 timestamp track model backend phase num_ctx num_gpu flash_attn tokens_per_sec vram_gb ram_gb status is_best

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{
"track": "gpu",
"current_model": "devstral-small-2:24b",
"model_index": 0,
"phase": "context_scaling",
"backend": "ollama",
"current_config": {
"num_ctx": 32768,
"num_gpu": 99,
"flash_attn": true
},
"best_configs": {
"gpu": {},
"ram": {}
},
"completed_models": [],
"gpu_queue": ["devstral-small-2:24b", "qwen2.5-coder:32b", "codellama:34b-instruct"],
"ram_queue": ["qwen2.5:72b", "nemotron-3-nano:30b", "mixtral:8x7b-instruct"],
"context_steps": [32768, 65536, 98304, 131072, 163840, 200704, 262144, 327680],
"last_updated": "2026-04-28T17:00:00Z"
}

68
docker/hermes/Dockerfile Normal file
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FROM ghcr.io/astral-sh/uv:0.11.6-python3.13-trixie@sha256:b3c543b6c4f23a5f2df22866bd7857e5d304b67a564f4feab6ac22044dde719b AS uv_source
FROM tianon/gosu:1.19-trixie@sha256:3b176695959c71e123eb390d427efc665eeb561b1540e82679c15e992006b8b9 AS gosu_source
FROM debian:13.4
# Disable Python stdout buffering to ensure logs are printed immediately
ENV PYTHONUNBUFFERED=1
# Store Playwright browsers outside the volume mount so the build-time
# install survives the /opt/data volume overlay at runtime.
ENV PLAYWRIGHT_BROWSERS_PATH=/opt/hermes/.playwright
# Install system dependencies in one layer, clear APT cache
# tini reaps orphaned zombie processes (MCP stdio subprocesses, git, bun, etc.)
# that would otherwise accumulate when hermes runs as PID 1. See #15012.
RUN apt-get update && \
apt-get install -y --no-install-recommends \
build-essential nodejs npm python3 ripgrep ffmpeg gcc python3-dev libffi-dev procps git openssh-client docker-cli tini \
curl poppler-utils imagemagick \
chromium xvfb fonts-noto-color-emoji fonts-unifont fonts-liberation fonts-ipafont-gothic fonts-wqy-zenhei fonts-tlwg-loma-otf fonts-freefont-ttf \
libasound2t64 libatk-bridge2.0-0t64 libatk1.0-0t64 libatspi2.0-0t64 libcairo2 libcups2t64 libdbus-1-3 libdrm2 libgbm1 libglib2.0-0t64 libnspr4 libnss3 libpango-1.0-0 libx11-6 libxcb1 libxcomposite1 libxdamage1 libxext6 libxfixes3 libxkbcommon0 libxrandr2 \
texlive-latex-base texlive-latex-extra texlive-fonts-recommended texlive-xetex texlive-science \
qemu-user-static binfmt-support qemu-user-binfmt && \
rm -rf /var/lib/apt/lists/*
# Non-root user for runtime; UID can be overridden via HERMES_UID at runtime
RUN useradd -u 10000 -m -d /opt/data hermes
COPY --chmod=0755 --from=gosu_source /gosu /usr/local/bin/
COPY --chmod=0755 --from=uv_source /usr/local/bin/uv /usr/local/bin/uvx /usr/local/bin/
WORKDIR /opt/hermes
# ---------- Layer-cached dependency install ----------
# Copy only package manifests first so npm install + Playwright are cached
# unless the lockfiles themselves change.
COPY package.json package-lock.json ./
COPY web/package.json web/package-lock.json web/
RUN npm install --prefer-offline --no-audit && \
npx playwright install --with-deps chromium --only-shell && \
(cd web && npm install --prefer-offline --no-audit) && \
npm cache clean --force
# ---------- Source code ----------
# .dockerignore excludes node_modules, so the installs above survive.
COPY --chown=hermes:hermes . .
# Build web dashboard (Vite outputs to hermes_cli/web_dist/)
RUN cd web && npm run build
# ---------- Permissions ----------
# Make install dir world-readable so any HERMES_UID can read it at runtime.
# The venv needs to be traversable too.
USER root
RUN chmod -R a+rX /opt/hermes
# Start as root so the entrypoint can usermod/groupmod + gosu.
# If HERMES_UID is unset, the entrypoint drops to the default hermes user (10000).
# ---------- Python virtualenv ----------
RUN uv venv && \
uv pip install --no-cache-dir -e ".[all]"
# ---------- Runtime ----------
ENV HERMES_WEB_DIST=/opt/hermes/hermes_cli/web_dist
ENV HERMES_HOME=/opt/data
ENV PATH="/opt/data/.local/bin:${PATH}"
VOLUME [ "/opt/data" ]
ENTRYPOINT [ "/usr/bin/tini", "-g", "--", "/opt/hermes/docker/entrypoint.sh" ]

102
docker/hermes/entrypoint.sh Executable file
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#!/bin/bash
# Docker/Podman entrypoint: bootstrap config files into the mounted volume, then run hermes.
set -e
HERMES_HOME="${HERMES_HOME:-/opt/data}"
INSTALL_DIR="/opt/hermes"
# --- Privilege dropping via gosu ---
# When started as root (the default for Docker, or fakeroot in rootless Podman),
# optionally remap the hermes user/group to match host-side ownership, fix volume
# permissions, then re-exec as hermes.
if [ "$(id -u)" = "0" ]; then
if [ -n "$HERMES_UID" ] && [ "$HERMES_UID" != "$(id -u hermes)" ]; then
echo "Changing hermes UID to $HERMES_UID"
usermod -u "$HERMES_UID" hermes
fi
if [ -n "$HERMES_GID" ] && [ "$HERMES_GID" != "$(id -g hermes)" ]; then
echo "Changing hermes GID to $HERMES_GID"
# -o allows non-unique GID (e.g. macOS GID 20 "staff" may already exist
# as "dialout" in the Debian-based container image)
groupmod -o -g "$HERMES_GID" hermes 2>/dev/null || true
fi
# Fix ownership of the data volume. When HERMES_UID remaps the hermes user,
# files created by previous runs (under the old UID) become inaccessible.
# Always chown -R when UID was remapped; otherwise only if top-level is wrong.
actual_hermes_uid=$(id -u hermes)
needs_chown=false
if [ -n "$HERMES_UID" ] && [ "$HERMES_UID" != "10000" ]; then
needs_chown=true
elif [ "$(stat -c %u "$HERMES_HOME" 2>/dev/null)" != "$actual_hermes_uid" ]; then
needs_chown=true
fi
if [ "$needs_chown" = true ]; then
echo "Fixing ownership of $HERMES_HOME to hermes ($actual_hermes_uid)"
# In rootless Podman the container's "root" is mapped to an unprivileged
# host UID — chown will fail. That's fine: the volume is already owned
# by the mapped user on the host side.
chown -R hermes:hermes "$HERMES_HOME" 2>/dev/null || \
echo "Warning: chown failed (rootless container?) — continuing anyway"
fi
echo "Dropping root privileges"
exec gosu hermes "$0" "$@"
fi
# --- Running as hermes from here ---
source "${INSTALL_DIR}/.venv/bin/activate"
# Create essential directory structure. Cache and platform directories
# (cache/images, cache/audio, platforms/whatsapp, etc.) are created on
# demand by the application — don't pre-create them here so new installs
# get the consolidated layout from get_hermes_dir().
# The "home/" subdirectory is a per-profile HOME for subprocesses (git,
# ssh, gh, npm …). Without it those tools write to /root which is
# ephemeral and shared across profiles. See issue #4426.
mkdir -p "$HERMES_HOME"/{cron,sessions,logs,hooks,memories,skills,skins,plans,workspace,home}
# .env
if [ ! -f "$HERMES_HOME/.env" ]; then
cp "$INSTALL_DIR/.env.example" "$HERMES_HOME/.env"
fi
# config.yaml
if [ ! -f "$HERMES_HOME/config.yaml" ]; then
cp "$INSTALL_DIR/cli-config.yaml.example" "$HERMES_HOME/config.yaml"
fi
# Ensure the main config file remains accessible to the hermes runtime user
# even if it was edited on the host after initial ownership setup.
if [ -f "$HERMES_HOME/config.yaml" ]; then
chown hermes:hermes "$HERMES_HOME/config.yaml"
chmod 640 "$HERMES_HOME/config.yaml"
fi
# SOUL.md
if [ ! -f "$HERMES_HOME/SOUL.md" ]; then
cp "$INSTALL_DIR/docker/SOUL.md" "$HERMES_HOME/SOUL.md"
fi
# Sync bundled skills (manifest-based so user edits are preserved)
if [ -d "$INSTALL_DIR/skills" ]; then
python3 "$INSTALL_DIR/tools/skills_sync.py"
fi
# Final exec: two supported invocation patterns.
#
# docker run <image> -> exec `hermes` with no args (legacy default)
# docker run <image> chat -q "..." -> exec `hermes chat -q "..."` (legacy wrap)
# docker run <image> sleep infinity -> exec `sleep infinity` directly
# docker run <image> bash -> exec `bash` directly
#
# If the first positional arg resolves to an executable on PATH, we assume the
# caller wants to run it directly (needed by the launcher which runs long-lived
# `sleep infinity` sandbox containers — see tools/environments/docker.py).
# Otherwise we treat the args as a hermes subcommand and wrap with `hermes`,
# preserving the documented `docker run <image> <subcommand>` behavior.
if [ $# -gt 0 ] && command -v "$1" >/dev/null 2>&1; then
exec "$@"
fi
exec hermes "$@"

151
flake.lock generated
View File

@@ -23,6 +23,20 @@
"type": "github"
}
},
"flake-compat": {
"flake": false,
"locked": {
"lastModified": 1751685974,
"narHash": "sha256-NKw96t+BgHIYzHUjkTK95FqYRVKB8DHpVhefWSz/kTw=",
"rev": "549f2762aebeff29a2e5ece7a7dc0f955281a1d1",
"type": "tarball",
"url": "https://git.lix.systems/api/v1/repos/lix-project/flake-compat/archive/549f2762aebeff29a2e5ece7a7dc0f955281a1d1.tar.gz"
},
"original": {
"type": "tarball",
"url": "https://git.lix.systems/lix-project/flake-compat/archive/main.tar.gz"
}
},
"home-manager": {
"inputs": {
"nixpkgs": [
@@ -44,7 +58,125 @@
"type": "github"
}
},
"lix": {
"inputs": {
"flake-compat": "flake-compat",
"nix2container": "nix2container",
"nix_2_18": "nix_2_18",
"nixpkgs": [
"nixpkgs"
],
"nixpkgs-regression": "nixpkgs-regression",
"pre-commit-hooks": "pre-commit-hooks"
},
"locked": {
"lastModified": 1774721317,
"narHash": "sha256-KS0ElyhZKdUFcfaxfwid3yi2Id3EP9i+dGL16/wx1T8=",
"ref": "main",
"rev": "d0190cff6f2314cc1c727ff113aea20e086f4bcc",
"revCount": 19103,
"type": "git",
"url": "https://git.lix.systems/lix-project/lix"
},
"original": {
"ref": "main",
"type": "git",
"url": "https://git.lix.systems/lix-project/lix"
}
},
"lowdown-src": {
"flake": false,
"locked": {
"lastModified": 1633514407,
"narHash": "sha256-Dw32tiMjdK9t3ETl5fzGrutQTzh2rufgZV4A/BbxuD4=",
"owner": "kristapsdz",
"repo": "lowdown",
"rev": "d2c2b44ff6c27b936ec27358a2653caaef8f73b8",
"type": "github"
},
"original": {
"owner": "kristapsdz",
"repo": "lowdown",
"type": "github"
}
},
"nix2container": {
"flake": false,
"locked": {
"lastModified": 1767195068,
"narHash": "sha256-+OMnL79ZjqM/PCz2hoQ12MnXNoSSfBGnsYBOZnA9XbI=",
"owner": "nlewo",
"repo": "nix2container",
"rev": "bb6801be998ba857a62c002cb77ece66b0a57298",
"type": "github"
},
"original": {
"owner": "nlewo",
"repo": "nix2container",
"type": "github"
}
},
"nix_2_18": {
"inputs": {
"flake-compat": [
"lix",
"flake-compat"
],
"lowdown-src": "lowdown-src",
"nixpkgs": "nixpkgs",
"nixpkgs-regression": [
"lix",
"nixpkgs-regression"
]
},
"locked": {
"lastModified": 1730375271,
"narHash": "sha256-RrOFlDGmRXcVRV2p2HqHGqvzGNyWoD0Dado/BNlJ1SI=",
"owner": "NixOS",
"repo": "nix",
"rev": "0f665ff6779454f2117dcc32e44380cda7f45523",
"type": "github"
},
"original": {
"owner": "NixOS",
"ref": "2.18.9",
"repo": "nix",
"type": "github"
}
},
"nixpkgs": {
"locked": {
"lastModified": 1705033721,
"narHash": "sha256-K5eJHmL1/kev6WuqyqqbS1cdNnSidIZ3jeqJ7GbrYnQ=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "a1982c92d8980a0114372973cbdfe0a307f1bdea",
"type": "github"
},
"original": {
"owner": "NixOS",
"ref": "nixos-23.05-small",
"repo": "nixpkgs",
"type": "github"
}
},
"nixpkgs-regression": {
"locked": {
"lastModified": 1643052045,
"narHash": "sha256-uGJ0VXIhWKGXxkeNnq4TvV3CIOkUJ3PAoLZ3HMzNVMw=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "215d4d0fd80ca5163643b03a33fde804a29cc1e2",
"type": "github"
},
"original": {
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "215d4d0fd80ca5163643b03a33fde804a29cc1e2",
"type": "github"
}
},
"nixpkgs_2": {
"locked": {
"lastModified": 1774386573,
"narHash": "sha256-4hAV26quOxdC6iyG7kYaZcM3VOskcPUrdCQd/nx8obc=",
@@ -60,10 +192,27 @@
"type": "github"
}
},
"pre-commit-hooks": {
"flake": false,
"locked": {
"lastModified": 1769939035,
"narHash": "sha256-Fok2AmefgVA0+eprw2NDwqKkPGEI5wvR+twiZagBvrg=",
"owner": "cachix",
"repo": "git-hooks.nix",
"rev": "a8ca480175326551d6c4121498316261cbb5b260",
"type": "github"
},
"original": {
"owner": "cachix",
"repo": "git-hooks.nix",
"type": "github"
}
},
"root": {
"inputs": {
"agenix": "agenix",
"nixpkgs": "nixpkgs"
"lix": "lix",
"nixpkgs": "nixpkgs_2"
}
},
"systems": {

View File

@@ -8,10 +8,14 @@
inputs.darwin.follows = "";
inputs.nixpkgs.follows = "nixpkgs";
};
lix = {
url = "git+https://git.lix.systems/lix-project/lix?ref=main";
inputs.nixpkgs.follows = "nixpkgs";
};
self.submodules = true;
};
outputs = { self, nixpkgs, agenix, ... }@inputs:
outputs = { self, nixpkgs, agenix, lix, ... }@inputs:
let
system = "x86_64-linux";
keys = import ./lib/keys.nix;
@@ -26,6 +30,9 @@
pkgs = import nixpkgs {
inherit system overlays;
config.allowUnfree = true;
config.permittedInsecurePackages = [
"openclaw-2026.3.12"
];
};
devShell = import ./shells/nix_dev.nix {
@@ -35,12 +42,16 @@
{
nixosConfigurations = {
lazyworkhorse = nixpkgs.lib.nixosSystem {
specialArgs = { inherit system self keys paths; };
specialArgs = { inherit system self keys paths inputs; };
modules = [
{
nixpkgs.overlays = overlays;
nixpkgs.config.allowUnfree = true;
nixpkgs.config.rocmSupport = true;
nixpkgs.config.permittedInsecurePackages = [
"openclaw-2026.3.12"
];
nix.package = lix.packages.${system}.default;
}
agenix.nixosModules.default
./hosts/lazyworkhorse/configuration.nix
@@ -49,7 +60,23 @@
./modules/nixos/services/docker_manager.nix
./modules/nixos/services/open_code_server.nix
./modules/nixos/services/ollama_init_custom_models.nix
./modules/nixos/services/openclaw_node.nix
./users/gortium.nix
./users/ai-worker.nix
];
};
cyt-pi = nixpkgs.lib.nixosSystem {
specialArgs = { inherit self keys paths inputs; };
modules = [
{
nixpkgs.overlays = overlays;
nixpkgs.config.allowUnfree = true;
nixpkgs.hostPlatform = "aarch64-linux";
nix.package = lix.packages."aarch64-linux".default;
}
./hosts/cyt-pi/configuration.nix
./hosts/cyt-pi/hardware-configuration.nix
];
};
};

View File

@@ -0,0 +1,98 @@
{ config, lib, pkgs, paths, self, ... }:
{
# Basic Host Info
networking.hostName = "cyt-pi";
time.timeZone = "America/Montreal";
i18n.defaultLocale = "en_CA.UTF-8";
# System State
system.stateVersion = "25.05";
# Boot & Hardware (Pi Zero 2 W is ARM64)
boot.loader.grub.enable = false;
boot.loader.generic-extlinux-compatible.enable = true;
boot.kernelPackages = pkgs.linuxPackages_latest;
# Networking
networking.networkmanager.enable = true;
services.openssh = {
enable = true;
settings.PermitRootLogin = "prohibit-password";
};
# User
users.users.gortium = {
isNormalUser = true;
extraGroups = [ "wheel" "networkmanager" "kismet" ];
openssh.authorizedKeys.keys = [
# Populate with your public key
];
};
# CYT Project Dependencies (Headless)
environment.systemPackages = with pkgs; [
git
python311
python311Packages.opencv4
python311Packages.numpy
python311Packages.pillow
autossh # For the reverse tunnel
kismet # Wi-Fi monitoring
];
# Kismet Service
systemd.services.kismet = {
description = "Kismet Wi-Fi Monitor";
after = [ "network-online.target" ];
wantedBy = [ "multi-user.target" ];
serviceConfig = {
User = "gortium";
Group = "kismet";
ExecStart = ''
${pkgs.kismet}/bin/kismet -c panda --log-base=/home/gortium/kismet_logs --no-nc-ui
'';
Restart = "always";
RestartSec = "10s";
};
};
# Reverse SSH Tunnel Service
systemd.services.cyt-tunnel = {
description = "Reverse SSH Tunnel to lazyworkhorse.net";
after = [ "network-online.target" ];
wantedBy = [ "multi-user.target" ];
serviceConfig = {
User = "gortium";
ExecStart = ''
${pkgs.autossh}/bin/autossh -M 0 -N \
-o "ServerAliveInterval 30" \
-o "ServerAliveCountMax 3" \
-R 19999:localhost:22 \
gortium@lazyworkhorse.net -p 2425 \
-i /home/gortium/.ssh/cyt_tunnel_key
'';
Restart = "always";
RestartSec = "10s";
};
};
# CYT Application Service
systemd.services.cyt-app = {
description = "Chasing Your Tail - Target Detector";
after = [ "network-online.target" "kismet.service" ];
wantedBy = [ "multi-user.target" ];
serviceConfig = {
User = "gortium";
WorkingDirectory = "/home/gortium/Chasing-Your-Tail-NG";
ExecStart = ''
${pkgs.python311}/bin/python3 target_detector_cli.py --min-ssids 2
'';
Restart = "on-failure";
RestartSec = "60s";
Environment = [
"CYT_KISMET_LOGS=/home/gortium/kismet_logs"
];
};
};
}

View File

@@ -0,0 +1,24 @@
{ config, lib, pkgs, modulesPath, ... }:
{
imports =
[ (modulesPath + "/installer/scan/not-detected.nix")
];
boot.initrd.availableKernelModules = [ "xhci_pci" "usbhid" "sdhci_pci" ];
boot.initrd.kernelModules = [ ];
boot.kernelModules = [ ];
boot.extraModulePackages = [ ];
# Pi Zero 2 W specific filesystem
fileSystems."/" =
{ device = "/dev/disk/by-label/NIXOS_SD";
fsType = "ext4";
options = [ "noatime" ];
};
swapDevices = [ ];
nixpkgs.hostPlatform = lib.mkDefault "aarch64-linux";
hardware.enableRedistributableFirmware = true;
}

View File

@@ -9,7 +9,7 @@
hoardingcow-mount.enable = true;
# Flakesss
nix.settings.experimental-features = [ "nix-command" "flakes" ];
nix.settings.experimental-features = [ "nix-command" "flakes" "flake-self-attrs" ];
nix.settings.trusted-users = [ "root" "gortium" ];
# Garbage collection
@@ -135,6 +135,7 @@
kitty.terminfo
nodejs_22
uv
openclaw
(python3.withPackages (ps: with ps; [
openai-whisper
]))
@@ -209,6 +210,7 @@
coms = {
path = self + "/assets/compose/coms";
envFile = config.age.secrets.containers_env.path;
};
finance = {
@@ -248,16 +250,33 @@
mode = "0600";
path = "/etc/ssh/ssh_host_ed25519_key";
};
# n8n_ssh_key = {
# file = ../../secrets/n8n_ssh_key.age;
# owner = "root";
# group = "root";
# mode = "0600";
# path = "/home/n8n-worker/.ssh/n8n_ssh_key";
# };
ai_ssh_key = {
file = ../../secrets/ai_ssh_key.age;
owner = "root";
group = "root";
mode = "0600";
path = "/home/ai-worker/.ssh/ai_ssh_key";
};
openclaw_gateway_token = {
file = ../../secrets/openclaw_gateway_token.age;
owner = "root";
group = "ai-worker";
mode = "0440";
path = "/run/secrets/openclaw_gateway_token";
};
};
};
# OpenClaw Node service (host-side execution for Docker gateway)
services.openclaw-node = {
enable = true;
user = "ai-worker";
gatewayHost = "127.0.0.1";
gatewayPort = 18789;
gatewayTokenFile = "/run/secrets/openclaw_gateway_token";
displayName = "lazyworkhorse-host";
};
# Public host ssh key (kept in sync with the private one)
environment.etc."ssh/ssh_host_ed25519_key.pub".text =
"${keys.hosts.lazyworkhorse.main}";

View File

@@ -6,7 +6,7 @@
gitea = "ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIN9tKezYidZglWBRI9/2I/cBGUUHj2dHY8rHXppYmf7F";
};
n8n-worker = {
ai-worker = {
main = "ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIAXeGtPPcsP2IYRQNvII41NVWhJsarEk8c4qxs/a5sXf";
};
};

View File

@@ -29,6 +29,11 @@ with lib;
systemd.services = mapAttrs' (name: value: nameValuePair "${name}_stack" {
description = "Docker Compose stack: ${name}";
# Forces systemd to restart when the files change
reloadTriggers = [
"${builtins.hashFile "sha256" (toString value.path + "/compose.yml")}"
] ++ (lib.optional (value.envFile != null) "${value.envFile}");
after = [ "network.target" "docker.service" "docker.socket" "agenix.service" ];
wants = [ "docker.socket" "agenix.service" ];
requires = [ "docker.service" ];

View File

@@ -0,0 +1,64 @@
{ config, lib, pkgs, ... }:
let
cfg = config.services.openclaw-node;
openclawPkg = pkgs.openclaw;
in {
options.services.openclaw-node = {
enable = lib.mkEnableOption "OpenClaw Node service";
user = lib.mkOption {
type = lib.types.str;
default = "ai-worker";
description = "User to run the OpenClaw headless node as.";
};
gatewayHost = lib.mkOption {
type = lib.types.str;
default = "127.0.0.1";
description = "Gateway host (IP or hostname).";
};
gatewayPort = lib.mkOption {
type = lib.types.int;
default = 18789;
description = "Gateway WebSocket port.";
};
gatewayTokenFile = lib.mkOption {
type = lib.types.str;
default = "";
description = "Path to file containing the gateway auth token.";
};
displayName = lib.mkOption {
type = lib.types.str;
default = "lazyworkhorse-host";
description = "Display name for this node (shown in pairing).";
};
};
config = lib.mkIf cfg.enable {
systemd.services.openclaw-node = {
description = "OpenClaw Headless Node Service";
after = [ "network.target" ];
wantedBy = [ "multi-user.target" ];
serviceConfig = {
Type = "exec";
User = cfg.user;
Group = cfg.user;
WorkingDirectory = "/home/${cfg.user}";
ExecStart = ''
${pkgs.bash}/bin/bash -c 'export OPENCLAW_GATEWAY_TOKEN=$(cat ${cfg.gatewayTokenFile}) && exec ${openclawPkg}/bin/openclaw node run --host ${cfg.gatewayHost} --port ${toString cfg.gatewayPort} --display-name "${cfg.displayName}"'
'';
Restart = "always";
RestartSec = 5;
};
environment = {
NODE_ENV = "production";
};
};
};
}

View File

@@ -1,32 +1,34 @@
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OKrnmfuSvBgyuIOj5e6uWW0+Zs8dHKXu2TgV8WignxOhl5zQgCpCBlqVfO0t+NCu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-----END AGE ENCRYPTED FILE-----

View File

@@ -0,0 +1,11 @@
-----BEGIN AGE ENCRYPTED FILE-----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-----END AGE ENCRYPTED FILE-----

View File

@@ -10,4 +10,5 @@ in
"containers.env.age".publicKeys = authorizedKeys;
"lazyworkhorse_host_ssh_key.age".publicKeys = authorizedKeys;
"n8n_ssh_key.age".publicKeys = authorizedKeys;
"openclaw_gateway_token.age".publicKeys = authorizedKeys;
}

View File

@@ -2,6 +2,8 @@
users.users.ai-worker = {
isSystemUser = true;
group = "ai-worker";
home = "/home/ai-worker";
createHome = true;
extraGroups = [ "docker" ];
shell = pkgs.bashInteractive;
openssh.authorizedKeys.keys = [